DRAM1 Regulates Autophagy Flux through Lysosomes

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Open Access

Peer-reviewed

Xing-Ding Zhang ,
Lin Qi ,
Jun-Chao Wu,
Zheng-Hong Qin

Xing-Ding Zhang,
Lin Qi,
Jun-Chao Wu,
Zheng-Hong Qin

Abstract

We have previously reported that the mitochondria inhibitor 3-nitropropionic acid (3-NP), induces the expression of DNA damage-regulated autophagy modulator1 (DRAM1) and activation of autophagy in rat striatum. Although the role of DRAM1 in autophagy has been previously characterized, the detailed mechanism by which DRAM1 regulates autophagy activity has not been fully understood. The present study investigated the role of DRAM1 in regulating autophagy flux. In A549 cells expressing wilt-type TP53, 3-NP increased the protein levels of DRAM1 and LC3-II, whereas decreased the levels of SQSTM1 (sequestosome 1). The increase in LC3-II and decrease in SQSTM1 were blocked by the autophagy inhibitor 3-methyl-adenine. Lack of TP53 or knock-down of TP53 in cells impaired the induction of DRAM1. Knock-down of DRAM1 with siRNA significantly reduced 3-NP-induced upregulation of LC3-II and downregulation of SQSTM1, indicating DRAM1 contributes to autophagy activation. Knock-down of DRAM1 robustly decreased rate of disappearance of induced autophagosomes, increased RFP-LC3 fluorescence dots and decreased the decline of LC3-II after withdraw of rapamycin, indicating DRAM1 promotes autophagy flux. DRAM1 siRNA inhibited lysosomal V-ATPase and acidification of lysosomes. As a result, DRAM1 siRNA reduced activation of lysosomal cathepsin D. Similar to DRAM1 siRNA, lysosomal inhibitors E64d and chloroquine also inhibited clearance of autophagosomes and activation of lysosomal cathapsin D after 3-NP treatment. These data suggest that DRAM1 plays important roles in autophagy activation induced by mitochondria dysfunction. DRAM1 affects autophagy through argument of lysosomal acidification, fusion of lysosomes with autophagosomes and clearance of autophagosomes.

Citation: Zhang X-D, Qi L, Wu J-C, Qin Z-H (2013) DRAM1 Regulates Autophagy Flux through Lysosomes. PLoS ONE 8(5): e63245. https://doi.org/10.1371/journal.pone.0063245

Editor: Arun Rishi, Wayne State University, United States of America

Received: November 13, 2012; Accepted: March 29, 2013; Published: May 17, 2013

Copyright: © 2013 Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was partially supported by the National Natural Science Foundation of China (No 30930035), by the National Basic Science Key Project (973 project, CB510003), by the Priority Academic Program development of Jiangsu Higher Education Institutes, and by Graduate Training Innovation Project of Jiangsu Province (CX09B_042Z). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

3-nitropropionic acid (3-NP), a suicide inhibitor of the mitochondrial respiratory enzyme succinate dehydrogenase (SDH) [1], induces striatal cell death in vivo and in vitro [2]–[4]. When intoxicated in vivo, 3-NP produces symptoms and striatal neuronal loss in human brains replicating neuropathology of Huntington’s disease [4], [5]. We previously reported that intrastriatal administration of 3-NP induced TP53-dependent autpophagy activation and apoptosis. The TP53 specific inhibitor pifithrin-α (PFT-α) blocked induction of autophagic proteins including DNA Damage Regulated Autophagy Modulator1 (DRAM1), LC3-II and beclin1 and apoptotic proteins including TP53-upregulated modulator of apoptosis (PUMA) and BAX. Both pharmacological inhibitors of autophagy and caspases effectively inhibited 3-NP-induced cell death [6], [7].

DRAM1, a novel TP53 target gene, is an evolutionarily conserved lysosomal protein and has been reported to play an essential role in TP53-dependent autophagy activation and apoptosis [8]. The mechanism by which DRAM1 promotes autophagy is not clear. It is proposed that DRAM1 may exert its effects on autophagy through lysosomes, given the fact as a lysosomal membrane protein. Uncovering the molecular mechanism by which DRAM1 regulates autophagy would provide a better understanding of the role of TP53 signaling pathway in the regulation of cell death and survival.

Autophagy is a pathway delivering cytoplasmic components to lysosomes for degradation [9]–[13]. Macroautophagy involves the sequestration of a region of the cytoplasm in a double-membrane structure to form a unique vesicle called the autophagosome. Acidification of lysosomes is crucial for activation of cathepsins, fusion of lysosomes and autophagosomes and effective degradation of autophagic substrates. However, these late digestive steps of autophagy remain largely uncharacterized.

Lysosomes are cytoplasmic organelles that contain several enzymes mostly belonging to the hydrolases [14]. Internal pH of lysosomal is characteristically acidic and it is maintained around pH 4.5 by a proton pump, that transport H⁺ ions into lysosomes [15], [16]. Many autophagy inhibitors including the vinca alkaloids (e.g., vinblastine) and microtubule poisons that inhibit fusion of autophagosomes with lysosomes, inhibitors of lysosomal enzymes (e.g., leupeptin, pepstatin A and E64d), and compounds that elevate lysosomal pH (e.g., inhibitors of vacuolar-type ATPases, such as bafilomycin A1 and weak base amines including ammonia, methyl- or propylamine, chloroquine, and Neutral Red, some of which slow down fusion), act at the fusion and lysosomal degradation steps [17]. Lysosomal enzymes also play a role in activation of certain types of caspases and therefore, are involved in apoptosis [18]. Inhibition of lysosomes or lysosomal enzymes protects neurons against excitotoxicity and ischemic insults [19], [20]. Thus, it is of particularly interest to investigate if DRAM1 modulates autophagy through influencing lysosomal functions.

In this study, we report that 3-NP induced DRAM1-dependent stimulation of autophagy in A549 cell lines. DRAM1 promotes autophagy flux by enhancing lysosomal acidification.

Materials and Methods

Cell Lines and Reagents

A549 (TP53^+/+) and H1299 (TP53^−/−) and Hela cell lines were purchased from Shanghai Institute of Biochemistry and Cell Biology in China, and were grown at 37°C in 5% CO₂ in RPMI supplemented with 2 mmol/L L-glutamine and 10% FCS. Primary mouse embryonic fibroblasts (MEFs) were derived from p53 wt and p53 KO sibling embryos, and maintained with DMEM supplemented with 10% FCS and antibiotics. 3-NP (N5636), 3-MA (M9281), carbonyl cyanide m-chlorophenylhydrazone (CCCP, C2759), ATP (A6559), chloroquine (C6628), E-64d (E8640) and Z-Vad-FMK (V116) were all purchased from Sigma-Aldrich (Saint Louis, MO, USA). LysoTracker Red (L7528) and LysoSentor (L7533) were purchased from Invitrogen-Molecular Probes (Shanghai, China). All cell culture reagents were purchased from Gibco (Gaithersburg, MD, USA) unless otherwise noted.

Expression of GFP-LC3 and DRAM1-pEGFP

The activation of autophagy was detected following transfection of cells with GFP-LC3 and mRFP-GFP-LC3 expression plasmids (kindly provided by Dr. T. Yoshimori, National Institute of Genetics, Japan). The presence of several intense fluorescent dots in cells is indicative of the accumulation of autophagosomes. Transfection of cells with expression plasmids was performed using Lipofectamine 2000 (Invitrogen, 11668-019, Shanghai, China). For each condition, the number of GFP-LC3 dots per cell was determined with a fluorescence microscopy for at least 100 GFP-LC3-positive cells.

PcDNA4-DRAM1-His was generated by PCR from the I.M.A.G.E. clone for DRAM1 (Clone ID: NM_018370) with: CCCAAGCTTATGCTGTGCTTCCTGAGGGGAATG (forward) and CCGCTCGAGTCAAATATCACCATTGATTTCTGTG (reverse), and subsequently digested with BamH I and Xho I and cloned in to the BamH I and Xho I sites of pcDNA4/HisA (Invitrogen Carlsbad, CA, USA). pEGFP-N1-DRAM1 was generated through PCR primer: ATAGAATTCATGCTGTGCTTCCTGAGGGGA (forward) and CCGGGATCCTAATATCACCATTGATTTCTGTG(reverse), and products were T-A cloned in pMDTM19-T Vectors (Takara, D102A, Dalian, China) and digested with EcoR I and BamH I and cloned into pEGFP-N1 (Clonetech, D102A, Mountain View, CA, USA). Transfection of cells with expression plasmids was performed using Lipofectamine 2000 (Invitrogen, 11668-019, Shanghai, China).

Knock-down of TP53 and DRAM1

Small interfering RNAs (siRNA) targeting the following mRNA: TP53, AAGACUCCAGUGGUAAUCUAC; DRAM1, (1) CCACGATGTATACAAGATA and (2) CCACAGAAATCAATGGTGA. Negative siRNA TAAGGCTATGAAGAGATAC, were synthesized by GenePharma (Shanghai, China). The siRNA oligos used to target DRAM1 genes were previously validated and described in the following articles [8], [21], [22]. For transfection, cells were plated in 9-cm dishes at 30% confluence, and siRNA duplexes (200 nM) were introduced into the cells using Lipofectamine 2000 (Invitrogen, 11668-019, Shanghai, China) according to the manufacturer’s recommendations.

LC3 Immunofluorescence Assay

For immunofluorescence microscopic examination, cells were plated on 12-mm Poly-L-Lysine-coated cover slips and cultured for 24 h, then cells were treated with siRNA and drugs. Cells were washed in PBS, fixed with 4% paraformaldehyde in PBS at 4°C for 10 min, and then washed again with PBS. The cells were permeabilized with 0.25% Triton X-100, and were then blocked with 10% normal goat serum (NGS) for 15 min. Primary antibodies: a rabbit polyclonal antibody against LC-3 (Abgent, AJ1456c, Suzhou, China), a goat polyclonal antibody against cathepsin D (Santa Cruz, sc-6488, Santa Cruz, CA, USA) and a rabbit polyclonal antibody against LAMP2 (Abcam, ab37024, Cambridge, MA, USA) diluted in PBS were added to the cells and left for overnight at 4°C. The cover slips were washed three times before incubation with secondary antibodies using the same procedure as for the primary antibodies. The cover slips were mounted on slides with mounting medium (Sigma-Aldrich, F4680, Saint Louis, MO, USA) and were examined with a laser scanning confocal microscopy (Nikon, C1S1, Tokyo, Japan).

The pattern of distribution of exogenously expressed GFP-LC3 in A549 cells was observed with fluorescent microscopy. GFP-LC3 dot formation was quantified by counting 500 GFP-LC3-positive cells and expressed as the ratio of the number of cells with at least 5 GFP-LC3 dots and the number of GFP-LC3-positive cells. The assays were independently performed by two investigators in a blinded manner and similar results were obtained.

Western Blot Analysis

Western blot analysis was performed as scribed previously [23]. Cells were harvested and rinsed twice with ice-cooled PBS and homogenized in a buffer containing 10 mmol/L Tris-HCl (pH 7.4), 150 mmol/L NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS, 5 mol/L edetic acid, 1 mmol/L PMSF, 0.28 U/L aprotinin, 50 mg/L leupeptin, 1 mmol/L benzamidine, 7 mg/L pepstain A. Protein concentration was determined using the BCA kit. Thirty micrograms of protein from each sample was subjected to electrophoresis on 10–12% SDS-PAGE gel using a constant current. Proteins were transferred to nitrocellulose membranes and incubated with the Tris-buffered saline containing 0.2% Tween-20 (TBST) and 3% non-fat dry milk for 3 h in the presence of one of the following antibodies: a rabbit polyclonal antibody against LC-3 (Abgent, AJ1456c, San Diego, CA, USA), a mouse monoclonal antibody against TP53 (Cell Signaling Technology, 2524S, Boston, MA, USA), a mouse monoclonal antibody against β-actin (Santa Cruz, sc-58669), a goat polyclonal antibody against cathepsin D (Santa Cruz, sc-6488), rabbit polyclonal antibodies against DRAM1 (Stressgen, 905-738-100, Farmingdale, NY, USA), a rabbit polyclonal antibodies against SQSTM1 (Enzo Life Sciences, PW9860, Farmingdale, NY, USA),Membranes were washed and incubated with horseradish peroxidase-conjugated secondary antibodies in TBST containing 3% non-fat dry milk for 1 h. Immunoreactivity was detected with enhanced chemoluminescent autoradiography (ECL kit, Amersham, RPN2232, Piscataway, NJ, USA) according to the manufacturer’s instructions. The levels of protein expression were quantitatively analyzed with SigmaScan Pro 5. The results were normalized to loading control β-actin (Santa Cruz, sc-58669). DRAM1 peptide (Acris Antibodies, AP30304CP-N, San Diego, CA, USA) was used for evaluating the specificity of DRAM1 antibody. Pre-incubation of DRAM1 antibody with control peptide (1 µg control peptide/1 µL DRAM1 antibody) abolished binding activity of DRAM1 antibody (Figure S2).

Determination of Lysosomal pH

For lysosomal pH estimation, A549 and Hela cells were seeded on circular glass cover slips and grown to conﬂuence in Dulbecco’s modified Eagle’s medium (DMEM) with 10% fetal bovine serum (FBS; Wisent, 080–150) at 37°C, 5% CO². Lysosomes were loaded overnight with 70000 MW FITC-dextran (Sigma-Aldrich, 53471). and 0.5 mg/mL dextran-coupled Oregon Green 488 (Invitrogen-Molecular Probes, D-7173, Grand Island, NY, USA) in DMEM supplemented with 10% FBS, chased for 2 h at 37°C with 5% CO2 in DMEM (10% FBS) to allow complete transfer of dextrans to lysosomes, and washed to remove residual dextran. Non-attached cells were removed by rinsing with PBS and the cover slips were immediately placed in a cuvette filled with growth medium or PBS and pH was estimated from excitation ratio measurements as described previously [24]. The fluorescence emitted was recorded at two excitation wavelengths (440/490 nm for Oregon Green 488) using the largest excitation and emission slits by a scanning multiwell spectrophotometer (Ultra Micro- plate Reader; BIO-TEK Instruments, ELx800, Winooski, VT, USA). The pH values were derived from the linear standard curve generated via each fluorescent dextran in phosphate/citrate buffers of different pH between 3.5 and 7.5. The experiment was repeated six times.

Spectrophotometric Measurement of H⁺ Transport

FITC-dextran loaded A549 and Hela cells were prepared as described above. After washing in PBS, cells were resuspended (10⁸ cells in 2 ml) in homogenization buffer (0.25 M sucrose, 2 mM EDTA, and 10 mM Hepes [pH 7.4]) and homogenized in a tight-fitting glass Dounce homogenizer. The homogenate was centrifuged (800 g, 10 min) to remove unbroken cells and the nuclei. The supernatant was centrifuged (6800 g, 10 min) to remove the large organelle such as mitochondrial. The supernatant was centrifuged (25000 g, 10 min) to obtain the light organelle including lysosomes. The precipitation layered over 10 ml of a 27% Percoll (Pharmacia Inc, 17-0891-01, New York, NY, USA) solution in homogenization buffer, underlayered with 0.5 ml of a 2.5 M sucrose solution. Centrifugation was done in a SW41Ti rotor (Beckman Instruments Inc, Brea, CA, USA) for 1.5 h at 35000 g. The layer of crude lysosomes of about 1.5 ml was collected at the bottom and then was centrifuged (100000 g, 60 min) to remove the other light organelle including mitochondrial at the bottom of the tube. Lysosomal fractions were equilibrated for up to 1 h in 125 mM KCl, 1 mM EDTA, and 20 mM Hepes (pH 7.5). Fluorescence was recorded continuously with excitation at 490 nm and emission at 520 nm. Upon addition of ATP (Sigma-Aldrich, A6559, Saint Louis, MO, USA), a progressive decrease in fluorescence intensity was observed, indicative of intralysosomal acidification [25]. As expected, the pH gradients in both samples were collapsed by the addition of the bafilomycin A1 (1 µM) (Sigma-Aldrich, B1793). The solvents alone had no effect on lysosomal pH. The reagents used and their final concentrations were: ATP (K⁺ salt, pH 7.5, 5 mM), bafilomycin A1 (1 µM).

Statistical Analysis

Statistical analysis was carried out by one-way analysis of variance (ANOVA) followed by Dunnett t-test or multiple means comparisons by Tukey’s test. Differences were considered significant when p<0.05.

Results

3-NP Induces Autophagy Activation

The present study examined if autophagic and apoptotic pathways are activated in A549 cells after 3-NP treatment. The results showed that 3-NP-induced a significant increase in the protein levels of DRAM1 from 3 to 72 h, with a peak induction at 24 h after 3-NP treatment (Figure 1A). The specificity of DRAM1 antibody was checked with Western blot analysis and immunofluorescence assay using DRAM1 control peptide (Figure S2). To further test if mitochondria respiration failure triggers DRAM1 expression, we used CCCP to uncouple mitochondria oxidation and phosphorylation, the results showed that CCCP significantly increased the DRAM1 protein levels (Figure 1B). LC3 is a mammalian homologue of yeast Atg8p and LC3-II is required for the formation of autophagosomes [26]. As shown in Fig. 1C, 3-NP induced a time-dependent increase in GFP-LC3 in A549 cells, and LC3-positive vesicular profiles of sizes 0.5–2.0 µm were significantly more numerous in 3-NP-treated cells 48 h after treatment (Figure 1C and 1D). To provide biochemical evidence of autophagy activation, the time-course of 3-NP-induced changes in LC3-II in A549 cells was determined 24 to 72 h after 3-NP (500 µM) treatment. The expression of LC3-II significantly increased 24 h after 3-NP treatment (Figure 2A). As an additional assessment of autophagy activity, the degradation of SQSTM1 (sequestosome 1), an autophagy substrate, was determined [27]. The present results showed that the protein level of SQSTM1 decreased 24–72 h after 3-NP treatment (Figure 2A). As a confirmation of autophagy activation, the present study demonstrated that the elevation of LC3- II and the decline of SQSTM1 were blocked by the autophagy inhibitor 3-methyl-adenine (Figure 2B).

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Figure 1. 3-NP activated autophagy.

A549 cells were treated with 3-NP (500 µM) and harvested 24, 48 and 72 h later. (A) Immunoblot analysis of DRAM1 levels in A549 cells under conditions of: no treatment (Ctrl) and 3, 6, 12, 24, 48 and 72 h after 3-NP. (B) Immunoblot analysis of DRAM1 levels in A549 cells under conditions of: no treatment (Ctrl) and 12.5µM and 25 µM of CCCP treatment for 4 h. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (3-NP group vs. control group). (C) Representative images of GFP-LC3 fluorescence in cells transfected with GFP-LC3 plasmid 24, 48 and 72 h after 3-NP (500 µM). N: the nucleus. Thin arrows: GFP-LC3 dots. The scale bar represents 10 µm. (D) Quantitative analysis of the number of GFP-LC3 puncta. Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (3-NP group vs. control group).

https://doi.org/10.1371/journal.pone.0063245.g001

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Figure 2. Autophagy was induced by 3-NP and blocked by 3-MA.

(A) Immunoblot analysis of LC3 and SQSTM1 levels in A549 cells under conditions of: no treatment (Ctrl) and 24, 48 and 72 h after 3-NP. Protein extracts were subjected to SDS-PAGE and immunoblotting. Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. (B) Immunoblot analysis of LC3 and SQSTM1 levels in cells under conditions of: no treatment (Cont), 3-NP (500 µM) and 3-MA (200 µM) +3-NP (500 µM). Protein extracts were subjected to SDS-PAGE and immunoblotting. Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. *P<0.05 (3-NP group vs. control group). #P<0.05 (3-MA +3-NP- treated group vs. 3-NP- treated group). **P<0.01 (3-NP group vs. control group). ##P<0.05 (3-MA +3-NP- treated group vs. 3-NP- treated group).

https://doi.org/10.1371/journal.pone.0063245.g002

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Figure 3. TP53 dependency of DRAM1 induction after 3-NP treatment.

A549 and H1299 cells were treated with 3-NP (500 µM) and harvested 48 h later. (A) Immunoblot analysis of TP53 and DRAM1 levels in A549 and H1299 cells under conditions of: no treatment (Ctrl) and 48 h after 3-NP. Protein extracts were subjected to SDS-PAGE and immunoblotting. Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (3-NP group vs. control group). ^##P<0.01 (3-NP group vs. control group). ^$$P<0.01 (3-NP group vs. control group). (B) Immunoblot analysis of TP53 and DRAM1 levels in p53 wt and p53 KO MEFs under conditions of: no treatment (Ctrl) and 48 h after 3-NP. Protein extracts were subjected to SDS-PAGE and immunoblotting. Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (3-NP group vs. control group). ^##P<0.01 (3-NP group vs. control group). ^$$P<0.01 (3-NP group vs. control group). (C) A549 cells were transfected with TP53 siRNA or a non-silencing siRNA. Forty-eight hours after transfection of cells with TP53 siRNA, cells were harvested and protein levels of TP53 and DRAM1 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein bands were analyzed with Sigma Scan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 TP53 siRNA group vs. non-silencing siRNA group. (D) H1299 cells were transfected with TP53 siRNA or a non-silencing siRNA. Forty-eight hours after transfection of cells with TP53 siRNA, cells were harvested and protein levels of TP53 and DRAM1 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein bands were analyzed with Sigma Scan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test.

https://doi.org/10.1371/journal.pone.0063245.g003

It was reported that DRAM1 is a TP53 target gene. We determined the TP53 dependency in 3-NP-induced DRAM1 expression. In H1299 cells which lack of TP53, 3-NP only slightly induced DRAM1 expression, while in A549 cells which express wt TP53, 3-NP robustly induced the expression of DRAM1 (Figure 3A). The similar results were seen in TP53 wt and TP53 null MEFs cells (Figure 3B). Treatment of A549 cells with TP53 siRNA, partially inhibited both basal and 3-NP-induced the expression of DRAM1 (Figure 3C). In contrast, treatment of H1299 with TP53 siRNA did not block 3-NP-induced expression of DRAM1 (Figure 3D). These results suggest that induction of DRAM1 largely depends on TP53 mechanism, but other signaling pathways are also be involved in regulating DRAM1 expression after 3-NP treatment [28].

DRAM1 Mediates Autophagy Activation

To understand the role of DRAM1 in the regulation of autophagy, the present study investigated the role of DRAM1 in autophagy activation in response to 3-NP treatment in A549 and Hela cells. Knock-down of DRAM1 using siRNA significantly reduced the expression of DRAM1 proteins in A549 cells (Figure 4A) and in Hella cells (Figure S1 A). After knock-down of DRAM1 with siRNA, the basal expression and induction of LC3-II by 3-NP was markedly reduced in both A549 cells (Figure 4B) and Hela cells (Figure S1A). In addition, 3-NP-induced reduction of SQSTM1 was blocked by DRAM1 siRNA in A549 cells (Figure 4B). The formation of GFP-LC3 puncta after 3-NP treatment was also inhibited in the presence of DRAM1 siRNA in A549 cells (Figure 4C) and in Hela cells (Figure S1 B). In addition to inhibiting the production of LC3-II, SQSTM1 levels increased in DRAM1 siRNA-treated cells (Figure 4B). These lines of evidence support an important role of DRAM1 in autophagy activation.

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Figure 4. DRAM1 mediated autophagy activation.

(A, B) A549 cells were transfected with DRAM1 siRNA or a non-silencing siRNA. Left: Forty-eight hours after transfection of cells with DRAM1 siRNA, cells were harvested and protein levels of DRAM1, LC3 and SQSTM1 were analyzed with immunoblotting. Right: Twenty-four hours after transfection of cells with DRAM1 siRNA, cells were treated with 3-NP (500 µM). Cells were harvested and protein levels of LC3 and SQSTM1 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein bands were analyzed with SigmaScan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA group). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 non-silencing siRNA group vs. control group. ^##P<0.01 DRAM1 siRNA group vs. non-silencing siRNA group. (C) Representative images of GFP-LC3 fluorescence in cells transfected with GFP-LC3 and treated with DRAM1 siRNAs in the presence or absence of 3-NP (500 µM). Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. N: the nucleus. Thin arrows: GFP-LC3 dots. The scale bar represents 10 µm. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (siRNA group vs. non-silencing siRNA group).

https://doi.org/10.1371/journal.pone.0063245.g004

DRAM1 Enhances Autophagosomes Clearance

To study the mechanisms of DRAM1 in regulating autophagy, A549 cells were transfected with GFP-DRAM1. The lysosomal localization of DRAM1 was examined with LysoTracker and LAMP2 immunofluorescence or double immunofluorescence of DRAM1 and LAMP2. LysoTracker is a commonly used lysosomal probe because it is an acidotropic fluorescent dye for labeling and tracking acidic organelles in live cells. Marked co-localization of DRAM1 and LysoTracker (Figure 5A) or DRAM1 and LAMP2 (Figure 5B) was seen with a confocal microscopy. The quantitative analysis revealed that colocalization of DRAM1 puncta and LAMP2 was 74.8±5.6% (data not shown), suggesting that DRAM1 predominantly localizes to lysosomes. The clearance of autophagosomes is a measure of autophagy flux. In control cells, acute autophagy induction with rapamycin elevated LC3-II levels as revealed by immunoblotting. After removing rapamycin from the medium for 6 h, LC3-II returned towards baseline levels. While in DRAM1 siRNA-treated cells, LC3-II remained elevated 6 h after removing rapamycin (Figure 5C). Double immunofluorescence of LC3 and LAMP2 demonstrated the formation of large number of LC3-LAMP2-positive vesicles in siRNA untreated cells after rapamycin exposure. Treatment of cells with DRAM1 siRNA reduced the number of LC3-LAMP2-posive vesicles (Figure 5D). After removal of rapamycin for 6 h, a number of LC3-LAMP2-positive vesicles were cleared in siRNA untreated cells but more LC3-LAMP2-positive vesicles remained in the cells treated with DRAM1 siRNA (Figure 5E and 5F). These suggest that both the formation and the clearance of autophagic vacuoles are impaired in DRAM1 siRNA-treated A549 cells.

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Figure 5. Knock-down of DRAM1 impaired the clearance of autophagosomes.

(A) DRAM1 was predominantly localized in lysosomes (Lysotraker). A549 cells were transfected with GFP-DRAM1 for 48 h. Cells were incubated with LysoTracker (0.5 µM) and co-localization of DRAM1-GFP (green) and the LysoTracker (red) was assessed with a confocal microscopy. N: the nucleus. Thin arrows: GFP-DRAM1 fluorescence. Thick arrows: LysoTracker. (B) DRAM1 was predominantly localized in lysosomes (LAMP2). Up panel: A549 cells were transfected with GFP-DRAM1 for 48 h. Cells were processed for immunofluorescence using LAMP2 antibodies and co-localization of DRAM1-GFP (green) and the LAMP2 (red) was assessed with a confocal microscopy. N: the nucleus. Thin arrows: GFP-DRAM1 fluorescence. Thick arrows: LAMP2. Low panel: A549 cells were processed for immunofluorescence using DRAM1 and LAMP2 antibodies, and co-localization of DRAM1 (green) and the LAMP2 (red) was assessed with a confocal microscopy. N: the nucleus. Thin arrows: anti-DRAM1 fluorescence. Thick arrows: LAMP2. (C) Immunoblot analysis of LC3 levels in A549 cells under conditions: untreated (Cont), rapamycin (Rap) treatment, and 6 h after rapamycin removal (Rap/Rec). Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA group). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Tukey’s test. **P<0.01 (DRAM1 siRNA treatment group vs. non-silencing siRNA group). (D) A549 cells were analyzed with double-immunofluorescence using LC3 and LAMP2 antibodies in the presence of rapamycin and 6 h after removal of rapamycin. N: the nucleus. Thin arrows: dots of LC3 immonureactivity. Thick arrows: LAMP2. The scale bar represents 10 µm. (E) DRAM1 siRNA-treated cells were analyzed with double-immunofluorescence using LC3 and LAMP2 antibodies in the presence of rapamycin and 6 h after removal of rapamycin. N: the nucleus. Thin arrows: dots of GFP-LC3 fluorescence. Thick arrows: LAMP2. The scale bar represents 10 µm. (F) In cells after DRAM1 siRNA treatment, the number of LC3 dots was scored in 100 GFP-LC3-positive cells in the presence or absence of 3-NP. The data are expressed as percentage of control. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by Tukey’s test. **P<0.01 (DRAM1 siRNA treatment group vs. non-silencing siRNA group). ^#P<0.05 (DRAM1 siRNA treatment group vs. non-silencing siRNA group).

https://doi.org/10.1371/journal.pone.0063245.g005

DRAM1 Affects Lysosomal Degradation and Lysosomal Acidification

Lysosomal enzyme, cathepsin D, plays an essential role in the degradation process of autophagic activity. The present study employed double immunofluorescence of cathepsin D and LysoTracker to explore the role of DRAM1 in lysosomal function. We observed that cathepsin D was virtually confined in LysoTracker fluorescence-positive vesicles in A549 cells. 3-NP treatment increased the expression of cathepsin D and the number of LysoTraker labeled lysosomes (Figure 6A).

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Figure 6. Knock-down DRAM1 inhibited autophagosome maturation process.

(A) Lysosomes were activated by 3-NP. A549 cells were treated with 3-NP (500 µM) for 48 h. Cells were incubated with LysoTracker (0.5 µM) and processed for immunofluorescence using Cathepsin D (Cat D) antibodies. The co-localization of Cat D (green) and the LysoTracker (red) was assayed by confocal microscopy. N: the nucleus. Thin arrows: Cat D immunoreactivity. Thick arrows: LysoTracker. The scale bar represents 10 µm. (B) Accumulation of mRFP-LC3 in DRAM1 siRNA-treated cells. Representative images of mRFP-GFP-LC3 fluorescence in cells transfected with mRFP-GFP-LC3 and treated with DRAM1 siRNAs in the presence or absence of 3-NP (500 µM). N: the nucleus. Thin arrows: GFP-LC3 dots. Thick arrows: mRFP-LC3 dots. The scale bar represents 10 µm. (C) Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 non-silencing siRNA group vs. control group. ^##P<0.01 DRAM1 siRNA group vs. non-silencing siRNA group.

https://doi.org/10.1371/journal.pone.0063245.g006

GFP-LC3 is the most widely used marker for autophagosomes. When localized to autolysosomes, GFP-LC3 loses fluorescence due to lysosomal acidic and degradative conditions. While mRFP-LC3 is more stable in acidic conditions and fluorescence remains after fusion of autophagosomes with lysosomes. Thus, we used mRFP-GFP tandem fluorescent-tagged LC3 to monitor the process of autophagy maturation [29]. The result showed that 3-NP increased the expression of LC3, most of LC3 displayed yellow color due to emitted both GFP and RFP fluorescence. However, due to stronger fluorescence of GFP than that of RFP, some green LC3 patches were also observed. Knock-down of DRAM1 with siRNA slightly reduced GFP-LC3 fluorescence (reflecting attenuation of autophagy induction), but robustly increased the number of large mRFP-LC3 puncta (Figure 6B and 6C). In the condition of treatment with 3-NP in the presence of non-sil siRNA, yellow punctas were few because degradation of autolysosomes was smooth. While in the condition of treatment with 3-NP in the presence of DRAM1 siRNA, more large yellow pinctas were observed (Figure 6B). These results indicate that the clearance of autophagic vacuoles is impaired in DRAM1 siRNA-treated A549 cells.

As most lysosomal cathepsins work at acidic pH, the effect of DRAM1 silencing on activation of cathepsin D was examined. The results of immunoblotting showed that knock-down of DRAM1 significantly inhibited 3-NP-induced production of the active form of cathepsin D (Figure 7A), suggesting activation of cathepsin D is compromised. To assess lysosomal acidification, we used LysoSensor DND-167. The LysoSensor dye is an acidotropic probe that appears to accumulate in acidic organelles as the result of protonation. In control cells, the fluorescence of LysoSensor was enhanced from 24 to 72 h after 3-NP exposure. By contrast, in DRAM1 siRNA-treated cells, the fluorescence was lower than that in the control cells (Figure 7B). We further measured lysosomal pH in quantization. The cells were loaded with the pH-sensitive reporter FITC-dextran by endocytosis for 1 h and then chased in the control and DRAM1 siRNA-treated cells in the presence and absence of 3-NP. WT cells exhibited an intralysosomal pH of 4.75, and lysosomal pH decreased following 3-NP treatment (Figure 7C). In contrast, the lysosomal pH values decreased to a lesser extent (5.23) in DRAM1 siRNA-treated cells following 3-NP treatment in both A549 cells (Figure 7C) and in Hela cells (Figure S1 C). These results suggest that there is a defective lysosomal acidification in DRAM1 siRNA-treated cells. Lysosomal acidification requires the activity of the ATP-dependent vacuolar proton pump [30]. We examined the ATP-dependent lysosomal acidification using the pH sensitive dye FITC-dextran. This dye accumulates inside lysosomes due to its weak basic net charge in response to ATP addition. As shown in Figure 7D, addition of ATP caused a dramatic drop in FITC fluorescence as a result of lysosomal acidification in control and 3-NP-treated cells. In DRAM1 siRNA-treated cells, ATP-induced drop in fluorescence emission was reduced, reflecting a reduction in internal lysosomal acidification. Reduction in FITC fluorescence by ATP was inhibited by the V-ATPase inhibitor bafilomycin A1. The similar results were obtained in Hela cells (Figure S1 D). Thus, the impairment of acidification in DRAM1 siRNA-treated cells might be due to a decrease in V-ATPase activity.

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Figure 7. Knock down DRAM1 inhibited lysosomal acidification and cathepsin D activation.

(A) A549 cells were transfected with DRAM1 siRNA or a non-silencing siRNA. Left: Forty-eight hours after transfection of DRAM1 siRNA, cells were harvested and protein levels of cat D were analyzed with immunoblotting. Right: Twenty-four hours after transfection of cells with DRAM1 siRNA, cells were treated with 3-NP (500 µM) for 24 h. Cells were harvested and protein levels of cat D were analyzed with immunoblotting. Densities of protein bands were analyzed with SigmaScan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). (B) Lysosomal acidification was measured using LysoSensor DND-167. In control cells, the fluorescence of LysoSensor was measured from 24 to 72 h, and in DRAM siRNA-treated cells the fluorescence was measured in 48 h after transfection of DRAM1 siRNA. N: the nucleus. The scale bar represents 10 µm. (C) Lysosomal pH was measured ratio-metrically using fluorescent dextrans. WT cells and DRAM1 siRNA1-treated cells were loaded with the pH-sensitive fluorescent dextrans by endocytosis for 1 h at 37°C and then subjected to pulse-chase assay in the presence or absence of the 3-NP (500 µM). Lanes 2 and 4 depict pH values obtained with FITC-dextran after the addition of 500 nM 3-NP. The data are expressed as percentage of control (non-silencing siRNA cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). ^##P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group with 3-NP treatment). (D) Lysosomal V-ATPase activity was inhibited in DRAM1 siRNA1-treated cells. Lysosomes from control cells and DRAM1 siRNA1-treated cells were loaded with FITC-dextran (molecular weight 70,000). A549 cells were then homogenized and used for in vitro-acidification assays. Fluorescence was recorded continuously with excitation at 490 nm and emission at 520 nm. Upon addition of ATP, a progressive decrease in fluorescence intensity was observed, indicative of intralysosomal acidification. The decrement was reversed by bafilomycin A1, a V-ATPase inhibitor.

https://doi.org/10.1371/journal.pone.0063245.g007

Foregoing observations indicate that DRAM1 regulates autophagy flux mainly thought lysosomes. Thus, the lysosomal inhibitors E64d (10 µM) and chloroquine (20 µM) were used to evaluate if inhibition of lysosomal functions produces effects similar to knock-down of DRAM1. Many autophagy inhibitors act on post-sequestration steps and agents, such as bafilomycin A1, that blocks autophagy activity are known to cause accumulation of autophagosomes [31]. Chloroquine is a compound that elevates lysosomal pH, and E64d is an effective inhibitor of lysosomal enzymes [32]. After 3-NP treatment, more LAMP2-positive vacuoles were observed. Compared with cells treated with 3-NP alone, LC3 in E64d or chloroquine-treated cells accumulated more LAMP2-positive vacuoles (Figure 8A). As shown in Fig. 8B, LC3-II accumulated after E64d or chloroquine treatment. These results suggest a defective clearance of autophagic vacuoles in E64d- and chloroquine-treated cells.

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Figure 8. Lysosomal inhibitors inhibited autophagosome clearance.

(A) Accumulation of autophagosomes was analyzed with double-immunofluorescence using antibodies against LC3 and LAMP2 after E64d (10 µM) or chloroquine (20 µM) treatment for 24 h in the presence or absence of 3-NP (500 µM). N: the nucleus. Thin arrows: dots of LC3 immunoreactivity. Thick arrows: LAMP2 immunoreactivity. The scale bar represents 10 µm. (B) Immunoblot analysis of LC3-II levels in cells under conditions of: no treatment (Cont), E64d (10 µM), chloroquine (20 µM), 3-NP (500 µM), E64d (10 µM) +3-NP (500 µM) or chloroquine (20 µM) +3-NP (500 µM). Cells were harvested for immunoblotting 48 h after 3-NP treatment. Densities of protein bands were analyzed with SigmaScan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. *P<0.05 (3-NP treated group vs. control group). ^#P<0.05 (E64d+3-NP- or chloroquine +3-NP-treated group vs. 3-NP- treated group). ^##P<0.01 (E64d plus 3-NP or chloroquine plus 3-NP treatment group vs. 3-NP treatment group).

https://doi.org/10.1371/journal.pone.0063245.g008

Discussion

3-NP acts as an irreversible inhibitor of succinate dehydrogenase and thus results in an impairement of energy metabolism, oxidative stress and activation of glutamate receptors [33]. Mitochondria are important intracellular organelles and the collapse of mitochondria membrane potential may be a signal for activation of autophagy and apoptosis. Previous in vivo studies suggest that 3-NP-induced cell death in rat striatum involves TP53-dependent activation of apoptosis and autophagy [6]. It was also reported that DRAM1 and SQSTM1 regulated cell migration and invasion of glioblastoma stem cells [34]. TP53 target gene DRAM1 possibly mediates down stream multiple functions in autophagy and cell death. The present in vitro studies found that 3-NP inhibited cell viability of A549 cells at the doses of 250 µM to 1 mM (data not shown). The activation of autophagy was demonstrated by increases in LC3-II protein levels, GFP-LC3 puncta and a decrease in SQSTM1 protein levels. These studies suggest that mitochondria dysfunction induced by 3-NP triggered autophagy activation. Biochemical analysis showed that 3-NP and CCCP significantly increased DRAM1 protein levels and this increase in DRAM1 played a role in 3-NP-induced autophagy activation. Although upregulation of DRAM1 by 3-NP largely depended on TP53, our present results suggested there were also other mechanisms involved [28]. The human DRAM1 gene encodes a 238 amino acid protein which acts as a stress-induced regulator of autophagy and damage-induced programmed cell death [8]. The present study demonstrated that knock-down of DRAM1 effectively blocked the 3-NP-induced induction of LC3-II and decline in SQSTM1. These studies confirm that DRAM1 plays an important role in autophagy activation.

To investigate the underlying mechanism by which DRAM1 regulates autophagy, we investigated the effects of DRAM1 on autophagosome clearance. Colocalization of EGFP-DRAM1 and LysoTracker fluorescence or DRAM1 and LAMP2 immunoflurescence confirmed predominant lysosomal localization of expressed DRAM1. We first tested if DRAM1 has an effect on autophagosome turnover following induction with rapamycin. Rapamycin can stimulate the formation of autophagosome through inhibiting mTOR. Upon removal of rapamycin, autophagosomes should be cleared if autophagy pathway is normal. The present study demonstrated that rapamycin increased the abundance of autophagosomes and the number of autophagosomes returned towards the basal levels 6 h after withdrawal of rapamycin. Knock-down of DRAM1 reduced the rate of clearance of autophagosomes after rapamycin withdrawal. Galavotti et al reported that knock-down of DRAM1 inhibited targeting of SQSTM1 to autophagosomes and reduced its degradation [34]. Our data also support the involvement of DRAM1 in degradation of autophagososmes. However, Galavotti et al found that DRAM1 was not involved in starvation- and mTOR-mediated autophagy activation [34]. Therefore, the role of DRAM1 in autophagy activation induced by other stimuli need to be further studied.

The abundance of autophagosomes is balanced by the formation and clearance of autophagosomes. After the formation, the turn-over of autophagosomes is largely determined by the process of fusion between autophagososmes and lysosomes and degradation of autophagy contents by lysosomal enzymes. mRFP-GFP tandem fluorescent-tagged LC3 showed both GFP and mRFP signal of LC3 before the fusion with lysosomes, and exhibited only the mRFP signal when LC3 transmit into lysosomes because of lysosomal acidic environment and degradation [29]. After rapamycin treatment, there was more number of mRFP-GFP-LC3 patches in non-silencing RNA-treated cells than that in DRAM1 siRAN-treated cells, suggesting DRAM1 plays a role in the formation of autophagosomes. In response to withdrawal of rapamycin, mRFP-GFP-LC3 patches quickly declined in control cells. Knock-down of DRAM1 markedly retained these mRFP-GFP-LC3 patches in the cells. These results suggest that DRAM1 stimulates clearance of autophagosomes.

Lysosomes are rich in hydrolytic enzymes and are responsible for the degradation of intracellular materials captured by autophagy [35]. After 3-NP treatment, an increase in the abundance of autophagosomes was accompanied by an increase in the number of lysosomes. The increase in acidic lysosomes was noticeable as indicated by a fluorescence dye. Knock-down of DRAM1 resulted in an impairment of lysosomal acidification and accumulation of LC3-II, indicating reduced autophagy flux. It is now generally accepted that intralysosomal low pH is maintained by an active proton pump, vacuolar H⁺ATPases or VATPases. Proton transport into intracellular organelles is primarily mediated by ATPdependent proton pumps. These pumps are therefore central to pH homeostasis in organelles. Autophagosomes and their contents are cleared upon fusing with late endosomes or lysosomes containing cathepsins, other acid hydrolases, and vacuolar [H⁺] ATPase(v-ATPase) [36], a proton pump that acidifies the newly created autolysosome. It is suggested that the proton pumps and acidification of the lysosomes were essential for the activation of lysosomal hydrolases and completion of the process of autophagy. V-ATPase may also play a role in amino acid sensing, thus plays a role in mTOR-mediated autophagy activation [37]. Inhibition of mitochondrial respiratory complex may decrease ATP production and thus decrease the activity of V-ATPase. However, due to a significant induction of DRAM1 and activation of autophagy in the present study, the V-ATPase activity was preserved to sufficiently acidify lysosomes. We speculate that DRAM1 may improve the efficiency of ATP utilization by V-ATPase. The present study found that the lower capacity for acidification of lysosomes in DRAM1 siRNA-treated cells was due to decreased V-ATPase activity. These results provide experimental data, for the first time, supporting an important role of DRAM1 in lysosomal function.

Lysosomes play important roles in autophagy. To test if the effects of DRAM1 on lysosomal functions are responsible for DRAM1-mediated autophagy activation after 3-NP treatment, the present study assessed the effects of lysosomal inhibitors on autophagosome accumulation in the presence of 3-NP. The results showed that elevating lysosomal pH and inhibiting lysosomal enzymes both increased accumulation of autophagosomes and inhibited cathepsin D activation. These results largely replicated the effects of knock-down of DRAM1 and suggested that DRAM1 probably regulated autophagy flux through lysosomes.

It should be pointed out that DRAM1 appears regulate autophagy in both early and later stages of autophagy. DRAM1 can increase the formation of autophagosomes and the clearance of autophagosomes. These effects may work through the same mechanism as DRAM1 is a lysosomal protein and may regulates dynamics of lysosomal membranes to increase V-ATPase activity and to facilitate membrane recycle for autophagosomal formation.

In conclusion, current data indicate that DRAM1 regulates autophagosome clearance through promoting lysosomal acidification and activation of lysosomal enzymes. The fusion of autophagosomes with lysosomes is an important step for autophagic degradation. In order to fully understand the role of DRAM1 in autophagy flux, the effects of DRAM1 on the fusion process between autophagosomes and lysosomes needs to be studied in the future.

Supporting Information

Figure S1.

DRAM1 mediated autophagy activation and lysosomal acidification in Hela cells. (A) Hela cells were transfected with DRAM1 siRNA or a non-silencing siRNA. Left: Forty-eight h after transfection of cells with DRAM1 siRNA, cells were harvested and protein levels of DRAM1 and LC3 were analyzed with immunoblotting. Right: Twenty-four hours after transfection of cells with DRAM1 siRNA, cells were treated with 3-NP (500 µM). Cells were harvested and protein levels of DRAM1 and LC3 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein bands were analyzed with Sigma Scan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA group). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). ^##P<0.01 (3-NP treated group vs. control group). ^$$P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group with 3-NP treatment). (B) Representative images of GFP-LC3 fluorescence in Hela cells transfected with GFP-LC3 and treated with DRAM1 siRNAs in the presence or absence of 3-NP (500 µM). Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. N: the nucleus. Thin arrows: GFP-LC3 dots. The scale bar represents 10 µm Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (siRNA group vs. non-silencing siRNA group). (C) Lysosomal pH was measured ratio-metrically using fluorescent dextrans in Hela cells. WT Hela cells and DRAM1 siRNA1-treated cells were loaded with the pH-sensitive fluorescent dextrans by endocytosis for 1 h at 37°C and then subjected to pulse-chase assay in the presence or absence of the 3-NP (500 µM). Lanes 2 and 4 depict pH values obtained with FITC-dextran after the addition of 500 nM 3-NP. The data are expressed as percentage of control (non-silencing siRNA cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). ^##P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group with 3-NP treatment). (D) Lysosomal V-ATPase activity was inhibited in DRAM1 siRNA1-treated Hela cells. Lysosomes from control cells and DRAM1 siRNA1-treated cells were loaded with FITC-dextran (molecular weight 70,000). Hela cells were then homogenized and used for in vitro-acidification assays. Fluorescence was recorded continuously with excitation at 490 nm and emission at 520 nm. Upon addition of ATP, a progressive decrease in fluorescence intensity was observed, indicative of intralysosomal acidification. The decrement was reversed by bafilomycin A1, a V-ATPase inhibitor.

https://doi.org/10.1371/journal.pone.0063245.s001

(TIF)

Figure S2.

Activity of DRAM1 antibody was blocked by DRAM1 peptide. (A) Cells were harvested and immunoblot analysis of DRAM1 protein levels in A549 and Hela cells. Left: No peptide incubated with DRAM1 antibody before primary antibody incubation. Right: DRAM1 peptide was incubated with DRAM1 antibody for 30 min at 37°C before primary antibody incubation. (B) Cells were processed for immunofluorescence using DRAM1 antibodies (green) and DAPI (the nucleus, blue) in A549 and Hela cells, and was assessed with a confocal microscopy. Left: No peptide incubated with DRAM1 antibody before primary antibody incubation. Right: DRAM1 peptide was incubated with DRAM1 antibody for 30 min at 37°C before primary antibody incubation. N: the nucleus. Thin arrows: anti-DRAM1 fluorescence.

https://doi.org/10.1371/journal.pone.0063245.s002

(TIF)

Author Contributions

Conceived and designed the experiments: ZQ XZ. Performed the experiments: XZ LQ. Analyzed the data: XZ LQ. Contributed reagents/materials/analysis tools: XZ JW. Wrote the paper: XZ ZQ.

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Lysosomes
Small interfering RNA
Autophagic cell death
Transfection
HeLa cells
Immunoblotting
Analysis of variance
Apoptosis

Hog1 Mitogen-Activated Protein Kinase Phosphorylation Targets the Yeast Fps1 Aquaglyceroporin for Endocytosis, Thereby Rendering Cells Resistant to Acetic Acid^▿

Mehdi Mollapour and Peter W. Piper^*

Mehdi Mollapour

Department of Molecular Biology and Biotechnology, University of Sheffield, Firth Court, Western Bank, Sheffield S10 2TN, England

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Peter W. Piper

Department of Molecular Biology and Biotechnology, University of Sheffield, Firth Court, Western Bank, Sheffield S10 2TN, England

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Author informationArticle notesCopyright and License informationDisclaimer

Department of Molecular Biology and Biotechnology, University of Sheffield, Firth Court, Western Bank, Sheffield S10 2TN, England

^*Corresponding author. Mailing address: Department of Molecular Biology and Biotechnology, University of Sheffield, Firth Court, Western Bank, Sheffield S10 2TN, United Kingdom. Phone: 44-114-222-2851. Fax: 44-114-222-2800. E-mail: ku.ca.dleiffehs@repip.retep

Received 2006 Nov 24; Revised 2007 Jan 22; Accepted 2007 Jun 25.

Abstract

Aquaporins and aquaglyceroporins form the membrane channels that mediate fluxes of water and small solute molecules into and out of cells. Eukaryotes often use mitogen-activated protein kinase (MAPK) cascades for the intracellular signaling of stress. This study reveals an aquaglyceroporin being destabilized by direct MAPK phosphorylation and also a stress resistance being acquired through this channel loss. Hog1 MAPK is transiently activated in yeast exposed to high, toxic levels of acetic acid. This Hog1 then phosphorylates the plasma membrane aquaglyceroporin, Fps1, a phosphorylation that results in Fps1 becoming ubiquitinated and endocytosed and then degraded in the vacuole. As Fps1 is the membrane channel that facilitates passive diffusional flux of undissociated acetic acid into the cell, this loss downregulates such influx in low-pH cultures, where acetic acid (pK_a, 4.75) is substantially undissociated. Consistent with this downregulation of the acid entry generating resistance, sensitivity to acetic acid is seen with diverse mutational defects that abolish endocytic removal of Fps1 from the plasma membrane (loss of Hog1, loss of the soluble domains of Fps1, a T231A S537A double mutation of Fps1 that prevents its in vivo phosphorylation, or mutations generating a general loss of endocytosis of cell surface proteins [doa4Δ and end3Δ]). Remarkably, targetting of Fps1 for degradation may be the major requirement for an active Hog1 in acetic acid resistance, since Hog1 is largely dispensable for such resistance when the cells lack Fps1. Evidence is presented that in unstressed cells, Hog1 exists in physical association with the N-terminal cytosolic domain of Fps1.

Baker's yeast (Saccharomyces cerevisiae) is extensively used as a model for studying how cells adapt to and survive different forms of stress. Its responses to hyperosmotic stress have been the subject of extensive investigations (11, 12, 21, 26). Important for an adaptation to hyperosmotic conditions is counteracting the water loss from the cell, which is achieved in yeast by accumulating a high intracellular pool of glycerol. This glycerol acts as a compatible solute, ensuring that the proteins in the intracellular environment remain hydrated and protected. Osmostress adaptation also involves the activation of the high-osmolarity glycerol (HOG) mitogen-activated protein kinase (MAPK) signaling cascades, which generate an activation of a multifunctional Hog1 MAPK. This activated Hog1 then translocates to the nucleus, where, by the phosphorylation of at least three separate transcription factors (Sko1, Hot1, and Smp1), it can generate an altered regulation of >10% of the total yeast genome (21). Active Hog1 has recently been found to exert important actions, much more instant than its effects on transcription, at the plasma membrane, where it directly phosphorylates certain of the membrane ion transporters in osmostressed cells in order to rapidly readjust the transmembrane fluxes of Na⁺ and K⁺ (26). In this work, we show that activated Hog1 can also phosphorylate a plasma membrane aquaglyceroporin, in order to trigger the endocytosis and degradation of this Fps1 channel. This Fps1 destabilization is seen, though, in response to a different condition of Hog1-activating stress: a high acetic acid level, not hyperosmotic stress. In addition, we describe how this targeting of Fps1 for degradation is important for the acquisition of acetic acid resistance.

Our attention was initially drawn to the S. cerevisiae acetic acid response by a discovery that in cultures growing at slightly acid pH (pH 4.5), this stress response involves the activation of HOG pathway signaling, the same pathway that is activated by osmostress, but without the strong GPD1 gene or intracellular glycerol inductions that are hallmarks of Hog1 becoming activated by a hyperosmotic stress (19). It appeared, therefore, that the Hog1 MAPK activated by acetic acid stress might be initiating a response rather different from the Hog1 activated by hyperosmotic stress. We show here that the Hog1 activated by acetic acid stress generates endocytosis and degradation of the Fps1 aquaglyceroporin. Such Fps1 destabilization does not occur when Hog1 is activated by hyperosmotic stress. In low-pH yeast cultures this loss of Fps1 is important for the acquisition of resistance to acetic acid, as it eliminates the channel for the passive diffusional entry of this acid into cells. In nature this response may help yeast survive in environments where competitor organisms (e.g., Acetobacter spp.) are excreting large amounts of acetic acid.

Aquaporins and aquaglyceroporins (also called the major intrinsic proteins) are integral membrane channels that facilitate an energy-independent transmembrane transport of small molecules such as water, glycerol, glyceraldehyde, glycine, and urea (2, 11, 14). As such, they are important mediators of the water and solute fluxes in both prokaryotes and eukaryotes. Their proper functioning and regulation are vital for several aspects of cellular physiology, with an altered functioning of these channels now being implicated in a number of diverse disease disorders such as congestive heart failure, glaucoma, and brain edema (2, 14). These channels are also important in toxicology, as they often facilitate the entry/exit of small toxic compounds to/from the cell. Though we focus in this study on the importance of Fps1 for acetic acid resistance, as the channel that facilitates the entry of this acid into cells, the same aquaglyceroporin has also been studied from the standpoint of its capacity to facilitate the exit of toxic methylamine from (37) or the entry of toxic metalloids to (33, 36) yeast.

MATERIALS AND METHODS

Strains and plasmids.

The yeast strains used in this study (BY4741, BY4741 fps1Δ kanMX4, and BY4743) were from Euroscarf (www.uni-frankfurt.de/fb15/mikro/euroscarf/), except for the hog1Δ fps1Δ strain (generated by hphMX4 cassette [8] deletion of the HOG1 gene in BY4741 fps1Δ). YEpFPS1, YEpfps1-Δ1, and YEpFPS1-cmyc (16, 28, 30) were generously provided by S. Hohmann. YEpFPS1-ΔN-cmyc (deletion of amino acids 13 to 230) was made by replacing the SalI-PstI fragment from YEpFPS1-cmyc with the SalI-PstI-truncated fragment from YEpfps1-Δ1. YEpFPS1-ΔC-cmyc (Fps1 lacking amino acids 534 to 650) was generated by removing the KpnI-XbaI fragment from the YEpFPS1-cmyc plasmid and replacing it with the PCR-amplified truncated Fps1 lacking amino acids 534 to 650 amino acid fragment, the latter digested with KpnI-XbaI.

Fps1 was C-terminally green fluorescent protein (GFP) tagged using pUG23 (20), with Fps1 without the stop codon being ligated to the SpeI-SalI-cut vector to generate pUG23FPS1-C-GFP. Mutant forms of YEpFPS1-cmyc and pUG23FPS1-C-GFP were derived by site-directed mutagenesis of these vectors and checked by DNA sequencing. N-Fps1-His₆ and C-Fps1-His₆, C-terminally hexahistidine (His₆)-tagged forms of Fps1(1-255) and Fps1(531-669), respectively, were generated by PCR. N-Fps1-His₆ and C-Fps1-His₆, as well as their mutant derivatives N-Fps1^T231A-His₆ and C-Fps1^S537A-His₆, were then ligated to PstI-XhoI-cut YEp81Met (this plasmid, a gift of Frank Cooke, is YEplac181 [7] with an insert containing the MET25-inducible promoter and the transcription termination site from PGK1, separated by a multiple cloning site).

pES86-HA-HOG1 (a hemagglutinin [HA]-tagged HOG1 coding sequence under ADH1 promoter control) and various mutant derivatives of this plasmid were gifts of David Engelberg. P_GAL1-PBS2DD in pYES2 was from Francesc Posas.

Growth conditions.

Yeast was grown on YPD (2% [wt/vol] Bacto peptone, 1% yeast extract, 2% glucose, 20 mg/liter adenine). Selective growth was on dropout 2% glucose (DO) medium (1). The medium pH was adjusted to 4.5 or 6.8 with either HCl or NaOH before autoclaving. Acetic acid was added from an 8.7 M stock acetic acid solution titrated to pH 4.5 with NaOH. For agar growth acetic acid sensitivity assays, overnight pH 4.5 YPD cultures were diluted to an optical density at 600 nm of 0.5, and ∼5-μl aliquots of a 10-fold dilution series were spotted onto YPD (pH 4.5)-1.5% agar plates supplemented with the indicated level of acetic acid. Growth was monitored over 3 to 5 days at 30°C.

Acetic acid uptake measurements.

Cultures in exponential growth at 30°C (5 × 10⁷ cells ml⁻¹) on pH 4.5 DO or YPD medium were transferred to medium of the same pH plus 100 mM acetic acid. Accumulation of radiolabeled acetic acid was determined essentially as described previously for measurements of the uptake of radiolabeled benzoic acid (10, 23). Fifty-milliliter mid-exponential-phase cultures, grown at 30°C on pH 4.5 DO or YPD medium, were harvested and resuspended (5 × 10⁷ cells ml⁻¹) in 6 ml of medium of the same pH containing 100 mM acetic acid, which was labeled with 25 μCi (15) (Amersham, United Kingdom). Intracellular versus extracellular radiolabeled acetic acid was then measured at different times during subsequent 30°C maintenance by rapidly filtering 0.5 ml of culture and then briefly washing the filters with ice-cold water. Filters were air dried and weighed, and their radioactivity was determined by liquid scintillation counting. Each data point is the mean of three separate determinations at each time point using the same culture.

Protein analysis and immunoblots.

Total protein extracts were prepared and analyzed by Western blotting, as described previously (18). Western blot analysis of total Hog1 used polyclonal anti-Hog1 (Y-215) antibody (Santa Cruz Biotechnology). Analysis of the active form of Hog1 used anti-dually phosphorylated (Thr¹⁸⁰/Tyr¹⁸²) p38 MAPK antibody (New England Biolabs). As a loading control, Sba1 levels were measured (17). His₆-tagged full-length Fps1 or the His₆-tagged N- and C-terminal fragments of Fps1 were detected with monoclonal anti-tetra-His antibody (QIAGEN), and GFP-tagged Fps1 was detected with monoclonal anti-GFP antibody (Roche). cmyc-tagged Fps1 detection used a monoclonal anti-c-myc (9B11) antibody (New England Biolabs), and HA-tagged Hog1 detection used a monoclonal anti-HA (HA.11) antibody (Convance). Fps1 ubiquitination was detected with monoclonal antiubiquitin (P4D1) antibody (Santa Cruz Biotechnology). Detection of Fps1 phosphorylation was with antiphosphoserine or antiphosphothreonine monoclonal antibodies (QIAGEN). Secondary antisera were horseradish peroxidase-anti-rabbit, -anti-goat or -anti-mouse immunoglobulin G (Amersham) diluted 2,000-fold. Enhanced chemiluminescence reagents (Amersham) were used for detection.

Binding assays.

Interaction between Fps1 and Hog1 was analyzed by in vivo coimmunoprecipitation. Fps1-cmyc was purified using protein A/G-agarose plus (Santa Cruz Biotechnology). Interactions of His₆-tagged N- or C-Fps1 fragments with Hog1 were analyzed in vitro by incubating 50 μg of the total protein lysate from wild-type and hog1Δ cells with 50 μl of Talon beads (Clontech) with the N-Fps1-His₆ or C-Fps1-His₆ bound. Incubation was at 4°C for 30 min in a buffer containing 20 mM Tris-HCl (pH 7.5), 50 mM NaCl, and protease inhibitor cocktail (Roche).The beads were washed three times with the same buffer on Coster spin filters. Twenty microliters of sodium dodecyl sulfate-polyacrylamide gel electrophoresis loading buffer was added to the beads, and 15 μl was loaded on sodium dodecyl sulfate-polyacrylamide gels for blotting onto nitrocellulose membranes.

In vitro kinase assay.

The N-Fps1-His₆ and the mutant N-Fps1^T231A-His₆ were expressed in hog1Δ cells and purified using Talon beads (Clontech). Hog1-HA was expressed and purified from exponentially grown cells subjected to brief acetic acid stress (100 mM, 10 min). Hog1-HA was immunoprecipitated from 2 mg yeast protein extract using monoclonal anti-HA-agarose conjugate clone HA-7 (Sigma). Hog1-HA kinase reactions were essentially as previously described (25).

Fluorescence microscopy.

Fluorescent and Nomarski images were acquired using a Leica DMLB microscope equipped with a GFP and red filter set and Nomarski objectives, and images were captured using OpenLab imaging software (Improvision Ltd.).

Two-hybrid analysis.

The two-hybrid analysis was essentially as described previously (17, 18). Genes for amino acids 1 to 255 and 531 to 669 of Fps1 fused at their C terminus to the Gal4 binding domain (BD) were generated by gap repair using vector pBDC (18) and strain PJ694α (34). Wild-type, nonphosphorylatable (NP), and kinase-inactive mutant (K52R) activator domain (AD)-Hog1 fusions were constructed by gap repair using vector pADC and strain PJ694a (34). PJ694α and PJ694a strains were then mated, with the diploids being selected on DO lacking tryptophan and leucine. Protein-protein interactions were checked by spotting these diploids onto DO lacking leucine, tryptophan, and histidine and supplemented with increasing concentrations (0 to 6 mM) of 3-aminotriazole. Growth on these selective plates was scored after 4 days at 30°C.

RESULTS

Loss of Fps1 influences acetic acid uptake and resistance in yeast.

Accumulation of a high intracellular glycerol pool by osmostressed yeast cells reflects both increased glycerol synthesis and an increased capacity of the cell to retain this glycerol, rather than lose it to the culture medium. The increased glycerol retention is achieved by turgor-mediated closure of the plasma membrane aquaglyceroporin Fps1, a closure that prevents glycerol diffusion through this channel and therefore the glycerol loss from the cell (9, 11, 12, 22). Though the acetic acid response of yeast grown at slightly acid pH (pH 4.5) does not involve increases in intracellular glycerol (19), we found that Fps1 was still a major factor in acetic acid resistance. With Fps1 loss, the cells were even more resistant to acetic acid than normal (compare wild-type and fps1Δ mutant cells in Fig. 1a). In addition, whereas Hog1 MAPK is normally essential for acetic acid resistance (19), this activity was rendered almost completely dispensable for this resistance by the loss of Fps1 (compare wild-type, hog1Δ, and fps1Δ single gene deletion mutant and fps1Δ hog1Δ double gene deletion mutant cells in Fig. 1a).

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FIG. 1.

(a) Loss of Fps1 enhances acetate resistance and suppresses the acetate sensitivity generated by the loss of Hog1. Growth of wild-type (wt), fps1Δ and hog1Δ single mutant, and fps1Δ hog1Δ double mutant cells (a 1:10 dilution series grown [3 days, 30°C] on pH 4.5 YPD agar containing the indicated level of acetic acid) is shown. (b) Acetic acid accumulation by pH 4.5 and pH 6.8 YPD cultures of the strains in panel a, measured over the initial 40 min following the addition of 100 mM acetic acid. (c) A working model to explain the results in panels a and b. Entry of undissociated acetic acid into the cell is Fps1 facilitated, with the acid that enters the cell in this way then dissociating in the cytosol (where the pH is close to neutral) so as to generate an intracellular pool of the acetate anion. This acetate then activates Hog1, an activity that in turn downregulates the Fps1-mediated acid influx into the cell.

Fps1 mediates the diffusional entry of undissociated acetic acid to glucose-repressed yeast.

Before investigating further this apparent linkage between the requirement for Hog1 MAPK in acetic acid resistance and the presence of Fps1, we first had to establish whether the Fps1 aquaglyceroporin could facilitate the diffusion of acetic acid across the cell membrane. Acetic acid accumulation was measured in cells suddenly exposed to the highest acetic acid level that would enable the growth of glucose-repressed, wild-type cultures at pH 4.5 (100 mM), with this acid being labeled to low specific activity with ¹⁴C. The initial rate of acetic acid accumulation by these cells, suddenly exposed to such a high level of acetic acid, is essentially a measure of their acetic acid uptake (S. cerevisiae does not use acetic acid as a carbon source in the presence of high glucose levels). These measurements indicated a relatively slow equilibration of the intracellular and extracellular acetic acid pools (Fig. 1b). The yeast cell membrane is therefore not freely permeable to acetic acid (in contrast to what is observed with more lipophilic carboxylic acids, compounds that equilibrate much more rapidly across this membrane [e.g., benzoic acid]) (10, 23). Importantly, the loss of Fps1 essentially eliminated acetic acid accumulation by these acid-challenged cells (compare wild-type and fps1Δ mutant cells in Fig. 1b), revealing that the entry of this acid into glucose-repressed, wild-type yeast is mainly by passive diffusion through the Fps1 channel. When cultures were exposed to the same level of acetic acid (100 mM) but at pH 6.8, when the acetic acid (pK_a 4.75) in the medium will be almost completely dissociated, cellular accumulation of acetate was greatly reduced (compare pH 4.5 versus pH 6.8 cultures in Fig. 1b). We interpret this as the open Fps1 channel facilitating the transmembrane flux of only the uncharged, undissociated acetic acid (CH₃COOH) (Fig. 1c), not the acetate anion (CH₃COO−). The Fps1 pore is structurally similar to that of bacterial GlpF (5, 13). It is therefore too small to readily accommodate the hydrated acetate anion. Since Fps1 therefore facilitates a substantial acetic acid entry to cells only at low pH (Fig. 1b), all of the experiments described below on the interplay between acetic acid and Fps1 analyzed the effects of 100 mM acetic acid challenge in pH 4.5 cultures (a regimen hereafter termed “acetic acid stress”). At pH 6.8 considerably higher acetate levels, effectively a high osmostress generated by a high acetate salt concentration, are needed in order to achieve any comparable degree of growth inhibition (19).

Remarkably, the loss of Hog1 MAPK generated a higher-than-normal acetic acid accumulation in pH 4.5 cultures (compare wild-type and hog1Δ deletant strains in Fig. 1b). This enhanced acetic acid uptake by the hog1Δ mutant was Fps1 mediated, as uptake was almost completely abolished in the double fps1Δ hog1Δ deletion strain (Fig. 1b). Hog1, an activity required for resistance to these conditions of acetic acid stress (19) (Fig. 1a), therefore appeared, from these acetate accumulation measurements, to be downregulating Fps1-facilitated acetic acid entry into the cell.

Figure 1c shows the model that was indicated by these acetic acid accumulation measurements, the model on which we based our subsequent experimentation. In this, the initial acetic acid entry to the cell is an Fps1-facilitated diffusional entry of the undissociated acid, and this generates an intracellular acetate anion pool that then provides the signal for transient Hog1 activation (pH 4.5 fps1Δ cultures lack any acetic acid-induced activation of Hog1 [unpublished observations]). This activated Hog1 then downregulates the Fps1-mediated influx of the acid into the cell (Fig. 1b and c). When cultures are exposed to 100 mM acetic acid, but at the higher pH of 6.8, both the uptake of the acid (Fig. 1b) and the Hog1 activation (19) are much slower than at pH 4.5, since a much smaller fraction of the acid is now undissociated and therefore able to traverse the Fps1 pore (Fig. 1b and c).

Hog1 MAPK activation by acetic acid stress directs endocytosis and degradation of Fps1.

To determine how Hog1 MAPK might be downregulating the Fps1-facilitated entry of acetic acid into the cell, we initially measured whether Fps1 levels were affected by acetic acid stress. Western blot analysis of a functional cmyc-tagged Fps1 (Fps1-cmyc) (28) expressed as the sole form of Fps1 channel in pH 4.5 HOG1⁺ and hog1Δ cultures revealed that this Fps1-cmyc was being degraded when HOG1⁺, but not hog1Δ, cells were exposed to acetic acid (Fig. 2a). The Hog1 that is transiently activated by and which confers resistance to these conditions of acetic acid stress (19) (Fig. 1a) appeared therefore to be directing the destabilization of Fps1 (Fig. 2a). Importantly, no Fps1-cmyc loss could be observed when, instead of the 100 mM acetic acid addition, the same pH 4.5 cultures were challenged by different conditions of osmostress, irrespective of the presence or absence of Hog1 (the effects of a 1 M NaCl addition are shown in Fig. 2a). Furthermore, addition of 1 M NaCl 10 min prior to addition of 100 mM acetic acid also prevented the Fps1-cmyc degradation seen with the application of just the latter stress alone (data not shown). It is possible, therefore, that only the open-channel state of Fps1 is destabilized by an active Hog1, not the closed conformation that is rapidly adopted by this plasma membrane channel in cells exposed to osmostress (see Discussion).

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FIG. 2.

(a) Measurements of Fps1-cmyc, expressed as the sole form of Fps1 channel in fps1Δ (wt) and fps1Δ hog1Δ (hog1Δ) mutant cells, at time points following the addition of either 100 mM acetic acid or 1 M NaCl. (b) Fps1-cmyc is degraded in unstressed cells in response to the active form of Hog1 (P-Hog1), the latter generated by galactose-inducible expression of the hyperactive PBS2^DD allele. (c) Forms of Fps1-cmyc that lack the amino-terminal or carboxy-terminal cytosolic domain of the channel (Fps1-ΔN-cmyc and Fps1-ΔC-cmyc) did not undergo the degradation in response to acetic acid stress shown for the full-length Fps1-cmyc in panel a. (d) Acetic acid sensitivity of BY4741 fps1Δ cells transformed, as indicated, with either empty YEplac195 vector, a plasmid for full-length Fps1 expression (YEpFPS1), or plasmids for expression of Fps1 forms that lack either the amino-terminal or the carboxy-terminal cytosolic domain (YEpfps1-ΔN and YEpfps1-ΔC). (e) Acetic acid sensitivity of a BY4743 (FPS1/FPS1) diploid transformed, as indicated, with either empty YEplac195 vector or plasmid YEpfps1-ΔN containing the gene for an unregulated Fps1. In panels d and e, cells were spotted in a 1:10 dilution series onto pH 4.5 DO plates lacking leucine and lacking or containing 100 mM acetic acid and then were grown for 3 days at 30°C.

The experiments in Fig. 2a indicated, therefore, that the downregulation of acetic acid influx into wild-type yeast is due to Hog1-dependent loss of the channel that mediates this influx (hog1Δ cells, where Fps1 does not degrade [Fig. 2a], exhibit a higher acid accumulation [Fig. 1b]). To obtain further evidence that it is indeed the activation of Hog1 that provides the Fps1 degradation signal we studied the effects of inducing, in the absence of applied stress, a hyperactive allele of the MAPK activator of Hog1, Pbs2 (Pbs2^DD) (24). Fps1-cmyc was rapidly destabilized in response to a GAL1 promoter-directed induction of this Pbs2^DD allele, with this destabilization of Fps1-cmyc by Pbs2^DD expression occurring in the absence of either acetic acid stress or osmotic stress (Fig. 2b).

Fps1 has cytosolic domains at its amino and carboxy termini, both of which are crucial for its regulation. Loss of either cytosolic domain generates a channel protein with constitutive, unregulated glycerol transport activity, whose in vivo expression causes an inability to retain glycerol and accumulate an osmolyte pool and therefore a sensitivity to hyperosmotic stress (9, 28-30). Fps1-cmyc forms lacking either of these cytosolic domains (Fps1-ΔN-cmyc and Fps1-ΔC-cmyc) were found not to degrade in response to acetic acid stress (Fig. 2c), their presence creating a sensitivity to this stress (Fig. 2d and e). Plasmids for expression of the wild-type Fps1 or an N-terminally truncated, unregulated Fps1 (YEpFPS1 and YEpfps1-Δ1) (28) were also transformed into the FPS1/FPS1 diploid strain BY4743. As expected for the acetate sensitivity with expression of an N-terminally truncated Fps1 corresponding to a gain of function (the presence of an unregulated, permanently open Fps1 channel), the capacity of the fps1-Δ1 allele to confer acetate sensitivity was genetically dominant (Fig. 2d).

Fps1-GFP undergoes Hog1-dependent endocytosis in response to acetic acid but not salt stress.

We next observed the fate of a functional Fps1-GFP fusion, expressed as the sole form of Fps1 in HOG1⁺ and hog1Δ cells. This Fps1-GFP was placed under MET25 promoter control so as to enable its expression to be switched off by addition of methionine 2 h prior to stress and therefore observations of the fate of the Fps1-GFP preexisting in the cells at the time of the stress application. Unstressed cells showed a uniform Fps1-GFP distribution in the plasma membrane, irrespective of the presence or absence of Hog1 (Fig. 3a). Upon application of acetic acid stress, this Fps1-GFP was endocytosed to the vacuole in 80 to 90% of the HOG1⁺ cells examined (Fig. 3a). Simultaneously it was also degraded (Fig. 3c). In contrast, in the hog1Δ mutant subjected to an identical acetic acid stress, Fps1-GFP remained at the plasma membrane and intact (Fig. 3a and c). Both the Fps1-cmyc degradation (Fig. 2) and the Fps1-GFP endocytosis/degradation (Fig. 3a) in response to acetic acid stress are therefore Hog1-dependent events.

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FIG. 3.

(a and b) Visualization of Fps1-GFP expressed as the sole form of Fps1 channel in fps1Δ (wt) and fps1Δ hog1Δ (hog1Δ) mutant cells stressed for 0, 20, or 60 min either with 100 mM acetic acid (a) (vacuoles revealed by FM4-64 staining) or 1 M NaCl (b). (c) An analysis of Fps1-GFP fusion integrity in these same cultures by Western blotting. The blots were probed using anti-GFP and anti-Sba1 antisera (the latter as a loading control). (d) Expressed as the sole Fps1 of HOG1⁺ cells, a nonphosphorylatable T231A S537A double mutant Fps1-GFP was correctly plasma membrane localized but was not endocytosed under the conditions of acetate stress where the wild-type Fps1-GFP is endocytosed to the vacuole (a). In contrast, very little of a phosphomimic T231E S537D double mutant Fps1-GFP was plasma membrane localized, even in the absence of stress.

When, instead of being subjected to acetic acid stress, these Fps1-GFP-expressing HOG1⁺ and hog1Δ cultures were subjected to 1 M NaCl stress, their Fps1-GFP remained at the cell membrane and intact (Fig. 3b and c), moving rapidly from a uniform distribution in this membrane into dot-like structures (Fig. 3b). Though the nature of the Fps1-GFP in these dot-like structures was not investigated further, this Fps1-GFP was observed to return subsequently to a uniform plasma membrane distribution when these salt-stressed cells were reshifted from high to low osmolarity (data not shown).

Fps1 undergoes Hog1-dependent phosphorylation in response to acetic acid stress.

The next question we addressed is whether Hog1 directly binds to and phosphorylates Fps1 or whether its action in targetting this channel for degradation is indirect, for example, mediated through an intermediary protein kinase. Lack of the Fps1 degradation in response to acetic acid stress generates a sensitivity to this stress (hog1Δ cells) (Fig. 1a and 2a), but our recent screen for such sensitivity among the collection of strains lacking nonessential yeast protein kinases uncovered only the kinases of the HOG signaling cascade as being important for acetic acid resistance (19).

Upon immunoprecipitating Fps1-cmyc from extracts of unstressed cells or extracts of cells exposed, very briefly, to 100 mM acetic acid (a 10-min treatment; longer stress would have caused Fps1-cmyc degradation), we made two important observations: first, that Fps1-cmyc was acquiring Hog1-dependent phosphorylations on threonine and on serine in vivo in response to the acid stress (Fig. 4a) and second, that appreciable amounts of Hog1 were coprecipitated with this Fps1-cmyc, with the levels of this coprecipitated Hog1 being unaffected by the brief in vivo acetic acid treatment prior to extract preparation (Fig. 4b). Further evidence of a direct Hog1-Fps1 association is presented later in this report.

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FIG. 4.

(a) Brief acetic acid stress leads to in vivo phosphorylation of Fps1-cmyc on both threonine (p-T) and serine (p-S), phosphorylations that are abolished by the lack of Hog1 or the expression of T231A S537A double mutant Fps1-cmyc. (b) Immunoprecipitated (IP) Fps1-cmyc coprecipitates Hog1. (c)T231A S537A double mutant forms of Fps1-cmyc and Fps1-GFP are refractory to acetate-induced degradation under conditions where the wild-type forms become degraded (Fig. 2d and 3c). (d) The acetate sensitivity generated by MET25 promoter-regulated induction of a functional wild-type Fps1-GFP fusion (FPS1), expressed as the sole Fps1 channel in fps1Δ and fps1Δ hog1Δ mutant cells, is made more severe by T231A S537A double mutation of this Fps1-GFP, whereas the induction of a phosphomimic (T231E S537D) Fps1-GFP has no influence over acetate resistance. (e) Expression of a T231A S537A double mutant Fps1-cmyc as the sole Fps1 of HOG1⁺ cells leads to enhanced acetate accumulation (measured as for Fig. 1c, except that cultures were maintained on pH 4.5 DO medium lacking uracil).

As proline-directed protein kinases, MAPKs phosphorylate their substrates at TP/SP motifs (32). There are two such motifs (corresponding to T231 and S537 in the S. cerevisiae Fps1) within two 12-amino-acid regions previously identified as being important for Fps1 channel regulation, regions that are on the cytosolic surface but located immediately adjacent to the amino-terminal and carboxy-terminal transmembrane domains of the channel (9, 28). These TP/SP motifs are also conserved among Fps1 aquaglyceroporins of diverse yeasts (http://www.gmm.gu.se/groups/hohmann/fungalMIP/index.htm). If Hog1 phosphorylates Fps1 at T231 and/or S537 in order to initiate the Hog1-dependent endocytosis seen in Fig. 3a, then conservative mutation of these residues should render Fps1 refractory to this endocytosis.

We mutated both T231 and S537 in the Fps1-GFP fusion to either nonphosphorylatable alanine residues (Fps1^{T231A 537A}-GFP) or phosphomimic amino acid residues (Fps1^{T231E 537D}-GFP). The Fps1^{T231A 537A}-GFP fusion was both localized correctly at the plasma membrane (Fig. 3d) and functional as an osmogated glycerol channel (data not shown). Despite this, when expressed as the sole Fps1 channel of HOG1⁺ cells, this Fps1^{T231A 537A}-GFP remained at the plasma membrane and was stable under conditions of acetic acid stress where the wild-type Fps1-GFP fusion was endocytosed to the vacuole and degraded (Fig. 3d). In contrast, the mutation of T231 and S537 in the Fps1-GFP fusion to phosphomimic residues resulted in a substantial reduction of the GFP signal at the plasma membrane, even in unstressed cells (Fps1^{T231E 537D}-GFP) (Fig. 3d), a result consistent with phosphorylation of Fps1 at T231 and/or S537 in such cells normally providing a signal for channel endocytosis.

The T231A S537A double mutant Fps1-cmyc (Fps1^{T231A 537A}−cmyc), expressed as the sole Fps1 channel in HOG1⁺ cells, was found to lack the acetic acid-induced in vivo phosphorylation (Fig. 4a) and in vivo degradation (Fig. 4c) exhibited by the wild-type Fps1-cmyc. Furthermore, the expression of T231A S537A double mutant Fps1 forms as the sole Fps1 channel of fps1Δ HOG1⁺ or fps1Δ hog1Δ deletion strains generated (like the loss of Hog1 MAPK in cells with normal Fps1 [Fig. 1a and b] a hypersensitivity to acetic acid (Fig. 4d) and a higher-than-normal acetic acid accumulation (Fig. 4e), results that are consistent with the wild-type Fps1-GFP being endocytosed but the mutant Fps1^{T231A 537A}-GFP remaining at the plasma membrane during acid stress (Fig. 3a and d). Conversely, expression of the phosphomimic (T231E S537D) double mutant Fps1-GFP (a form substantially not plasma membrane localized even in unstressed cells [Fig. 3d]) had no discernible effect on the levels of acetate resistance displayed by the fps1Δ HOG1⁺ and fps1Δ hog1Δ deletion strains (Fig. 4d).

In vivo, therefore, double T231A S537A mutation of Fps1 abolishes the Hog1-dependent phosphorylation and the endocytosis of this aquaglyceroporin in response to acetic acid stress. As a result, this channel now remains in the membrane, where it generates a sensitivity to acetic acid by providing an open channel for acid entry into the cell. In contrast, the corresponding phosphomimic (T231E S537D) mutant form of Fps1 is constitutively delocalized from the plasma membrane, such that its expression does not compromise the acetate resistance intrinsic to fps1Δ deletion strains, irrespective of the presence or absence of Hog1 (Fig. 4d).

Acetic acid induces a transient Fps1 ubiquitination that is Hog1 dependent.

Ubiquitination of cell surface proteins is generally a key step in triggering their internalization by endocytosis (4, 35). In yeast exposed to a brief acetic acid stress, ubiquitinated forms of Fps1-cmyc were readily detectable, with their appearance being abolished by either the loss of Hog1 or the expression of the T231A S537A double mutant Fps1-cmyc (Fig. 5a). Hog1-dependent phosphorylation of Fps1 appears therefore to be the signal for this aquaglyceroporin to become ubiquitinated prior to its endocytosis and degradation in the vacuole (Fig. 6d).

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FIG. 5.

(a) Transient, Hog1-dependent ubiquitination of wild-type but not T231A S537A double mutant Fps1-cmyc in cells exposed to a brief (10-min) acetate stress (protein was immunoprecipitated from cell extracts and then detected by immunoblotting using either antiubiquitin [upper image] or anti-c-myc [lower image] antisera). (b and c) In the doa4Δ and end3Δ mutants, Fps1-GFP remained at the plasma membrane (b) and was stable (c) under conditions of acetic acid stress where in wild-type cells it was endocytosed and degraded (Fig. 2c and d). (d) The doa4Δ and end3Δ mutants are acetic acid sensitive (growth was as for Fig. 1a).

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FIG. 6.

(a) A functional AD-Hog1 fusion interacts with Fps1(1-255)-BD but not Fps1(531-669)-BD in the two-hybrid system; this interaction is unaffected by mutations that render this AD-Hog1 either nonphosphorylatable by Pbs2 (NP) or inactive (K52R). Interaction was detected as yeast growth in the absence of histidine and in the presence of 3-amino-1,2,4-triazole; the latter is an inhibitor of the HIS3 product. (b) Hog1 binds Fps1(1-255)-His₆ but not Fps1(531-669)-His₆ in cell extracts, with Hog1 binding to the former fragment being unaffected by the T231A mutation. (c) HA-Hog1 immunoprecipitated from extracts of briefly acetate-stressed cells is in a phosphorylated, active form (P-HA-Hog1) and in an in vitro kinase assay phosphorylates the Fps1(1-255)-His₆ fragment at T231 (the controls in lanes 2 and 3 were immunoprecipitates from non-HA-Hog1-expressing cells). (d) Model of the acetic acid stress response. Hog1 is constitutively bound to the open Fps1 channel and thereby is poised to achieve an almost instant phosphorylation of the latter whenever there is activation of HOG pathway signaling. Such phosphorylation in turn causes Fps1 to be ubiquitinated and endocytosed to the vacuole.

doa4Δ and end3Δ, two mutations causing a general loss of endocytosis of cell surface proteins, also caused Fps1-GFP to remain stable and plasma membrane localized under those conditions of acetic acid stress where it is normally endocytosed (Fig. 5b and c). In addition, these mutants displayed an acetic acid sensitivity phenotype (Fig. 5d). The doa4Δ and end3Δ mutants are, respectively, defective in Doa4, a ubiquitin-protein hydrolase important in recycling ubiquitin from proteolytic substrates destined for degradation by the 26S proteasome or the vacuole (3, 27), and End3, a component of a multiprotein complex required for the internalization step of endocytosis (31).

Hog1 binds the N-terminal regulatory domain of Fps1, with the active form of this MAPK phosphorylating threonine 231 of this domain, both in vivo and in vitro.

The experiments described above reveal that the active Hog1 MAPK generated by acetic acid stress directs phosphorylation, ubiquitination, and endocytosis of Fps1, thereby removing from the plasma membrane the major route for diffusional entry of acetic acid into the cell (Fig. 1 and 6). Removal of this channel is important for resistance to toxic levels of acetic acid, since acid sensitivity is apparent with diverse defects that abolish this loss of Fps1. Thus, defective Fps1 endocytosis and acid sensitivity are apparent with the loss of Hog1 (Fig. 1a), with the loss of the amino- or carboxy-terminal cytosolic domain of Fps1 (Fig. 2c-e), with T231A S537A double mutation of Fps1 (Fig. 3d and 4d), or with mutations causing a general loss of endocytosis of cell surface proteins (doa4Δ and end3Δ) (Fig. 5b to d). Figure 4a reveals that the in vivo Hog1-dependent phosphorylation of Fps1 involves two residues (T231 and S537), both of which correspond to SP/TP motifs such as are recognized by the MAPKs.

While these results are fully consistent with the signal for the endocytosis of Fps1 being a direct Hog1 phosphorylation of this channel protein, we sought further evidence that Hog1 interacts with, and phosphorylates, Fps1. Finding that appreciable amounts of Hog1 coprecipitated with the Fps1-cmyc immunoprecipitated from yeast cell extracts (Fig. 4b), we next used two-hybrid analysis to probe for an in vivo Hog1 interaction with the amino- or carboxy-terminal hydrophilic region of Fps1 (amino acids 1 to 255 and 531 to 669, respectively). These are regulatory domains exposed on the cytosolic face of the cell membrane in the open-channel state of this aquaglyceroporin (9, 28). Interaction of Fps1(1-255) and Fps1(531-669), each fused to the Gal4 BD, was tested with fusions of the Gal4 AD to the native Hog1 MAPK, a nonactivatable (T180AY182F double mutant) Hog1 (NP), and a kinase-dead (K52R) Hog1. The Fps1(1-255)-BD “bait,” but not Fps1(531-669)-BD, exhibited strong two hybrid interaction with the wild-type AD-Hog1, as well as with both the NP and K52R mutant forms of this AD-Hog1 “prey” fusion (Fig. 5a).

This Fps1(1-255)-Hog1 two-hybrid interaction was then confirmed in studies of in vitro protein binding. His₆-tagged versions of Fps1(1-255) and Fps1(531-669) were expressed separately in the fps1Δhog1Δ yeast mutant and then isolated from extracts of these cells using nickel affinity resin (see Materials and Methods). These soluble subdomains of the aquaglyceroporin were then incubated with extracts from nonstressed or briefly acetic acid-stressed wild-type or hog1Δ cells. Hog1 MAPK was found to be associated with the Fps1(1-255)-His₆ fragment but not with Fps1(531-669)-His₆ (Fig. 6b), its binding to the former fragment being unaffected by whether or not the wild-type cells used for extract preparation had been preconditioned by brief, Hog1-activating (Fig. 6c) acetic acid stress. Together, the experiments in Fig. 4b and 6a and b indicate that Hog1 binds to the amino-terminal cytosolic domain of Fps1, irrespective of the activation state or activity of this MAPK, and also that in unstressed yeast cells, significant amounts of Hog1 are associated with the plasma membrane Fps1. Hog1 has traditionally been thought to exist mainly in association with its MAPK activator, Pbs2 (32). Hog1 is, though, considerably more abundant than Pbs2 in yeast (6).

Using an HA epitope-tagged Hog1 (HA-Hog1) immunoprecipitated from extracts of unstressed or briefly acetic acid-stressed yeast, we investigated whether Hog1 would directly phosphorylate the amino- or carboxy-terminal hydrophilic regions of Fps1 in vitro. As substrates, we added Fps1(1-255)-His₆ (either the wild-type or T231A mutant form) and Fps1(531-669)-His₆, which were previously expressed in and then purified from fps1Δhog1Δ mutant cells. HA-Hog1 phosphorylated the Fps1(1-255)-His₆ fragment (Fig. 6c) but not Fps1(531-669)-His₆ (not shown). Furthermore, in vitro phosphorylation of the former fragment was much more efficient using HA-Hog1 purified from briefly acetate-stressed cells (consistent with the greater pool of active Hog1 MAPK in these cells [19] [Fig. 6c]). The T231A mutation in Fps1(1-255)-His₆ abolished this in vitro phosphorylation by HA-Hog1 (Fig. 6c) but not Hog1 binding to this fragment (Fig. 6b). In vivo, the Hog1-dependent threonine phosphorylation of the full-length Fps1-cmyc in response to acetic acid stress was similarly abolished by the T231A S537A double mutation of this Fps1-cmyc (Fig. 4a). Therefore, Hog1 binds the region from amino acid 1 to 255 of Fps1, phosphorylating this region at T231 (Fig. 4a and 6c). Thorsen et al. have also recently presented independent evidence for Fps1 being regulated by a Hog1-dependent phosphorylation of T231, though under a different stress condition (arsenite, not acetate, stress) (33) (see Discussion).

Hog1 may also phosphorylate Fps1 on the S537 residue of the latter, since acetic acid-induced, Hog1-dependent phosphorylation of Fps1-cmyc on serine was detected in vivo, with this serine phosphorylation being abolished by the T231A S537A double mutation of Fps1-cmyc (Fig. 4a). The Fps1(531-669)-His₆ soluble subdomain of the channel that contains this S537 was not phosphorylated by HA-Hog1 in our in vitro kinase assays, possibly due to a lack of Hog1 binding to this subfragment (Fig. 6c). Thus, our in vitro assays were able to confirm direct Hog1 phosphorylation only of the T231 Fps1 residue.

DISCUSSION

In this study we show that acetic acid enters glucose-repressed yeast cells primarily by facilitated diffusion of the undissociated acid through the Fps1 aquaglyceroporin channel (Fig. 1). When cells are challenged with inhibitory concentrations of acetic acid, there is a transient activation of Hog1 (19). This MAPK then directly phosphorylates Fps1 on T231 and also probably on S537 (Fig. 4a and 6), a phosphorylation that is the signal for this channel to be ubiquitinated and endocytosed to the vacuole. Fps1 is degraded even when Hog1 is activated in the absence of stress (Fig. 2b). Double T231A S537A mutation of Fps1 abolishes this phosphorylation by Hog1, as well as the Hog1-dependent ubiquitination and endocytosis (Fig. 3d, 4a, and 5a), generating a hypersensitivity to acetic acid (Fig. 4d) that appears to reflect a higher-than-normal acid entry into cells (Fig. 4e). In contrast, a phosphomimic mutant Fps1^{T231E 537D}-GFP fusion is substantially delocalized from the plasma membrane, even in the absence of stress (Fig. 3d), and cannot confer Fps1 function (Fig. 4d and data not shown).

This removal of Fps1 from the plasma membrane appears to be essential for downregulating the acetic acid influx to the cell (Fig. 1b and 4e), since the acetic acid stress alone appears not to cause the complete closure of the Fps1 channel (Fps1-dependent acetic acid uptake is not immediately arrested in stressed wild-type cells; also, it is enhanced should this channel remain in the plasma membrane, as occurs in the hog1Δ mutant [Fig. 1b and 3a] or with the expression of the T231A S537A double mutant Fps1 [Fig. 3d and 4e]). Indeed, targeting Fps1 for degradation may be the major requirement for an active Hog1 in acetic acid resistance (19), since, remarkably, Hog1 is largely dispensable for this resistance when the cells lack Fps1 (Fig. 1a). Total loss of Fps1 also creates an acetate-resistant phenotype (the fps1Δ mutant; Fig. 1a), probably as this loss eliminates the major source of the acetic acid flux into the cell.

Activation of HOG MAPK pathway signaling is apparent both with osmostress (9, 12, 22) and with acetic acid stress (19), but Fps1 is destabilized only with the latter and not with the former condition of stress (Fig. 2a). According to current models, Fps1 refolds to a closed-channel conformation within seconds in cells shifted to high osmolarity, a Hog1-independent response to an altered cell turgor (9, 12, 22). With osmostress Fps1-cmyc and Fps1-GFP were not destabilized in HOG1⁺ cells (Fig. 2a and 3b and c), their stability under these conditions contrasting with their destabilization when the same HOG1⁺ transformants were exposed, instead, to acetic acid (Fig. 2a and 3a and c). Fps1 is therefore either unstable or stable under different conditions of HOG pathway-activating stress. Measurements of the acetic acid accumulation by the hog1Δ mutant (Fig. 1b) indicate that should this channel remain in the plasma membrane (Fig. 2a and 3a), it does not close completely in response to acetic acid stress. It appears, therefore, that an active Hog1 MAPK may target only the open-channel state of Fps1 for degradation, not the closed-channel conformation that is rapidly adopted by Fps1 in cells shifted to high osmolarity.

The Fps1 channel is also the route whereby toxic metalloids, such as arsenite and antimonite, enter yeast (36). Recently, Hog1 was shown to mediate a protective response to these metalloids, acting to downregulate their entry into the cell through this channel (33). There are some striking parallels with this metalloid response and the acetic acid response that we have been studying (notably, Hog1-dependent downregulation of the entry of the xenobiotic compound to the cell via Fps1 and also the requirement for the T231 residue of Fps1 in this downregulation). There appears, though, to be an important difference between the response to arsenite and the acetic acid response that we describe here. Unfortunately, Thorsen et al. did not investigate the in vivo localization of Fps1 in their study, but it is evident from their data that Fps1 is not becoming degraded in arsenite-treated cells but appears instead to be adopting a closed-channel conformation in response to the arsenite-triggered, Hog1-dependent phosphorylation (33). High intracellular levels of arsenite may be strongly inhibitory to the events of endocytosis that we observe. It is also possible that the Hog1 phosphorylation of Fps1 in response to acetic acid (Fig. 4a) generates closure of the Fps1 channel but that, because these same phosphorylations also target the channel for endocytosis, it is the latter events of endocytosis that are observed as the dominant phenotype in the case of our acetic acid-stressed cells.

Furthermore, our results indicate that Hog1 is bound constitutively to the amino-terminal cytosolic domain of Fps1 (Fig. 6). This domain is thought to “dip” into the membrane during the turgor-mediated channel closure (9, 22), whereupon Hog1 may dissociate (an aspect not investigated here). Our data reveal that Fps1 engages in an association with Hog1 irrespective of the activation state or the activity of this MAPK (Fig. 6). Hog1 is thereby “poised” to achieve almost instant Fps1 phosphorylation, and thereby an altered stability (and possibly conformation) of this aquaglyceroporin, in response to the activation of HOG pathway signaling.

As far as we are aware this is the first demonstration of the destabilization of an aquaglyceroporin being dependent upon direct MAPK phosphorylation and of a resistance being acquired through the selective degradation of such a channel protein. It also appears to be the first evidence for the MAPK that regulates the activity and stability of an aquaglyceroporin also being engaged in a strong, constitutive association with this target aquaglyceroporin.

Acknowledgments

We are indebted to Francesc Posas, Stefan Hohmann, David Engelberg, and Frank Cooke for plasmids and strains; to Ewald Hettema for comments on the manuscript; to Barry Panaretou for the use of his King's College London laboratory; and to Sally Thomas for technical assistance.

This work was supported by BBSRC grant BB/E003311/1.

Footnotes

^▿Published ahead of print on 9 July 2007.

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Neural Network primitives from NNlib.jl

Flux re-exports all of the functions exported by the NNlib package.

Activation Functions

Non-linearities that go between layers of your model. Note that, unless otherwise stated, activation functions operate on scalars. To apply them to an array you can call , and so on.

— Function

Activation function from "Continuously Differentiable Exponential Linear Units".

— Function

Exponential Linear Unit activation function. See "Fast and Accurate Deep Network Learning by Exponential Linear Units". You can also specify the coefficient explicitly, e.g. .

— Function

Activation function from "Gaussian Error Linear Units".

— Function

Piecewise linear approximation of .

— Function

This is a faster, and very slightly less accurate, version of . For `x::Float32, perhaps 3 times faster, and maximum errors 2 eps instead of 1.

See also .

— Function

Segment-wise linear approximation of , much cheaper to compute. See "Large Scale Machine Learning".

See also .

— Function

This is a faster but slighly less accurate version of .

Where Julia's function has an error under 2 eps, this may be wrong by 5 eps, a reduction by less than one decimal digit.

For this is usually about 10 times faster, with a smaller speedup for . For any other number types, it just calls .

See also .

— Function

Leaky Rectified Linear Unit activation function. You can also specify the coefficient explicitly, e.g. .

— Function

Activation function from "LiSHT: Non-Parametric Linearly Scaled Hyperbolic Tangent ..."

— Function

Return which is computed in a numerically stable way.

— Function

Return which is computed in a numerically stable way.

— Function

Activation function from "Mish: A Self Regularized Non-Monotonic Neural Activation Function".

— Function

Rectified Linear Unit activation function.

— Function

Rectified Linear Unit activation function capped at 6. See "Convolutional Deep Belief Networks" from CIFAR-10.

— Function

Randomized Leaky Rectified Linear Unit activation function. See "Empirical Evaluation of Rectified Activations" You can also specify the bound explicitly, e.g. .

— Function

Scaled exponential linear units. See "Self-Normalizing Neural Networks".

— Function

Classic sigmoid activation function. Unicode can be entered as then tab, in many editors. The ascii name is also exported.

See also .

— Function

See "Deep Sparse Rectifier Neural Networks", JMLR 2011.

— Function

See "Softshrink Activation Function".

— Function

See "Quadratic Polynomials Learn Better Image Features" (2009).

— Function

Self-gated activation function. See "Swish: a Self-Gated Activation Function".

— Function

Hard-Swish activation function. See "Searching for MobileNetV3".

— Function

See "Tanhshrink Activation Function".

— Function

Threshold gated rectified linear activation function. See "Zero-bias autoencoders and the benefits of co-adapting features"

Softmax

's uses internally.

— Function

Softmax turns input array into probability distributions that sum to 1 along the dimensions specified by . It is semantically equivalent to the following:

with additional manipulations enhancing numerical stability.

For a matrix input it will by default () treat it as a batch of vectors, with each column independent. Keyword will instead treat rows independently, and so on.

See also .

Examples

Note that, when used with Flux.jl, must not be passed to layers like which accept an activation function. The activation is broadcasted over the result, thus applies to individual numbers. But always needs to see the whole column.

— Function

Computes the log of softmax in a more numerically stable way than directly taking . Commonly used in computing cross entropy loss.

It is semantically equivalent to the following:

See also .

Pooling

's , , , , , and use , , and as their backend.

— Type

Dimensions for a "pooling" operation that can have an arbitrary input size, kernel size, stride, dilation, and channel count. Used to dispatch onto efficient implementations at compile-time.

— Function

Perform max pool operation with window size on input tensor .

— Function

Perform mean pool operation with window size on input tensor .

Padding

— Function

Pad the array reflecting its values across the border.

can a tuple of integers of some length that specifies the left and right padding size for each of the dimensions in . If is not given, it defaults to the first dimensions.

For integer input instead, it is applied on both sides on every dimension in . In this case, defaults to the first dimensions (i.e. excludes the channel and batch dimension).

See also and .

— Function

Pad the array with the constant value .

can be a tuple of integers. If it is of some length that specifies the left and right padding size for each of the dimensions in as . If supplied with a tuple of length instead, it applies symmetric padding. If is not given, it defaults to all dimensions.

For integer input, it is applied on both sides on every dimension in .

See also and .

— Function

Pad the array with zeros. Equivalent to with the constant equal to 0.

Convolution

's and layers use and internally.

— Function

Apply convolution filter to input . and are 3d/4d/5d tensors in 1d/2d/3d convolutions respectively.

— Type

Type system-level information about convolution dimensions. Critical for things like to generate efficient code, and helpful to reduce the number of kwargs getting passed around.

— Function

Depthwise convolution operation with filter on input . and are 3d/4d/5d tensors in 1d/2d/3d convolutions respectively.

— Type

Concrete subclass of for a depthwise convolution. Differs primarily due to characterization by Cin, Cmult, rather than Cin, Cout. Useful to be separate from DenseConvDims primarily for channel calculation differences.

— Type

Concrete subclass of for a normal, dense, conv2d/conv3d.

Upsampling

's layer uses , , and as its backend. Additionally, 's layer uses as its backend.

— Function

Upsamples the array by integer multiples along the first dimensions. Subsequent dimensions of are not altered.

Either the factors or the final output can be specified.

See also , for two dimensions of an array.

Example

Missing docstring for . Check Documenter's build log for details.

— Function

Arguments

: Incoming gradient array, backpropagated from downstream layers
: Size of the image upsampled in the first place

Outputs

: Downsampled version of

— Function

Upsamples the first 2 dimensions of the array by the upsample factors stored in , using bilinear interpolation. As an alternative to using , the resulting image can be directly specified with a keyword argument.

The size of the output is equal to , where .

Examples

— Function

Arguments

: Incoming gradient array, backpropagated from downstream layers
: Lateral (W,H) size of the image upsampled in the first place

Outputs

: Downsampled version of

— Function

Upsamples the first 3 dimensions of the array by the upsample factors stored in , using trilinear interpolation. As an alternative to using , the resulting image can be directly specified with a keyword argument.

The size of the output is equal to , where .

Examples

— Function

Arguments

: Incoming gradient array, backpropagated from downstream layers
: Lateral size & depth (W,H,D) of the image upsampled in the first place

Outputs

: Downsampled version of

— Function

Pixel shuffling operation, upscaling by a factor .

For 4-arrays representing images, the operation converts input to output of size . For -dimensional data, it expects with channel and batch dimensions, and divides the number of channels by .

Used in super-resolution networks to upsample towards high resolution features. Reference: Shi et. al., "Real-Time Single Image and Video Super-Resolution ...", CVPR 2016, https://arxiv.org/abs/1609.05158

Examples

Batched Operations

's layer uses internally.

— Function

Batched matrix multiplication. Result has for all . If then instead , and similarly for .

To transpose each matrix, apply to the array, or for conjugate-transpose:

The equivalent may be used in place of . Other permutations are also handled by BLAS, provided that the batch index is not the first dimension of the underlying array. Thus and are fine.

However, is not acceptable to BLAS, since the batch dimension is the contiguous one: . This will be copied, as doing so is faster than .

Both this and produce messages, and setting for instance will display them.

This is always matrix-matrix multiplication, but either or may lack a batch index.

When is a matrix, result has for all .
When is a matrix, then . This can also be done by reshaping and calling , for instance using TensorCore.jl, but is implemented here using instead of .

See also to regard as a batch of vectors, .

— Function

In-place batched matrix multiplication, equivalent to for all . If then every batch uses instead.

This will call whenever possible. For real arrays this means that, for , either or , the latter may be caused by or by for instance . Unlike this will never make a copy.

For complex arrays, the wrapper made by must be outermost to be seen. In this case the strided accepted by BLAS are more restricted, if then only is accepted.

— Function

Equivalent to applying or to each matrix .

These exist to control how behaves, as it operates on such matrix slices of an array with .

is equivalent to , and is also understood by (and more widely supported elsewhere).

Lazy wrappers analogous to and , returned by etc.

— Function

Equivalent to applying or to each matrix .

These exist to control how behaves, as it operates on such matrix slices of an array with .

is equivalent to , and is also understood by (and more widely supported elsewhere).

Lazy wrappers analogous to and , returned by etc.

— Function

Batched matrix-vector multiplication: the result has for all , or else for .

With the same argument types, would regard as a fixed matrix, not a batch of vectors. Both reshape and then call .

Gather and Scatter

's layer uses as its backend.

— Function

Reverse operation of . Gathers data from source and writes it in a destination according to the index array . For each in , assign values to according to

Notice that if is a vector containing integers and is a matrix, previous expression simplifies to

and will run over .

The elements of can be integers or integer tuples and may be repeated. A single column can end up being copied into zero, one, or multiple columns.

See for an in-place version.

Examples

— Function

Reverse operation of . Gathers data from source and writes it in destination according to the index array . For each in , assign values to according to

Notice that if is a vector containing integers, and both and are matrices, previous expression simplifies to

and will run over .

The elements of can be integers or integer tuples and may be repeated. A single column can end up being copied into zero, one, or multiple columns.

See for an allocating version.

— Function

Scatter operation allocating a destination array and calling on it.

If keyword is provided, it is used to initialize the content of . Otherwise, the init values is inferred from the reduction operator for some common operators (e.g. for ).
If is provided, it will be used to define the size of destination array, otherwise it will be inferred by and .

See for full details on how works.

Examples

— Function

Scatter operation, which writes data in into at locations . A binary reduction operator is applied during the scatter. For each index in , accumulates values in according to

Sampling

— Function

Given , compute output by sampling values at pixel locations from . Uses bilinear interpolation to calculate output values.

This implementation assumes the extrema ( and ) are considered as referring to the center points of the input’s corner pixels (i.e. align corners is ).

Arguments

: Input array in shape.
: Input grid in shape. Where for each grid contains coordinates that specify sampling locations normalized by the shape.
Therefore, and should have values in range. For example, is the left-top pixel of , and is the right-bottom pixel of .
Out-of-bound values are handled according to the .
: Out-of-bound padding. to use for out-of-bound grid locations. to use border values for out-of-bound grid locations. Default is .

Returns

sampled grid from .

Examples

In the example below, grid contains two out-of-bound sampling locations, which are handled differently, depending on the .

— Function

Arguments

: Input gradient in shape (same as output of the primal computation).
: Input from primal computation in shape.
: Grid from primal computation in shape.
: Out-of-bound padding. to use for out-of-bound grid locations. to use border values for out-of-bound grid locations. Should be the same as in primal computation. Default is .

Returns

(same shape as ) and (same shape as ) gradients.

Losses

— Function

ctcloss(ŷ, y) Computes the connectionist temporal classification loss between and . must be a classes-by-time matrices, i.e., each row represents a class and each column represents a time step. Additionally, the function will be applied to , so must be the raw activation values from the neural network and not, for example, the activations after being passed through a activation function. must be a 1D array of the labels associated with . The blank label is assumed to be the last label category in , so it is equivalent to . Used for sequence-to-sequence classification problems such as speech recognition and handwriting recognition where the exact time-alignment of the output (e.g., letters) is not needed to solve the problem. See [Graves et al. (2006)](https://www.cs.toronto.edu/~graves/icml2006.pdf) or Graves (2012) for mathematical details.

Miscellaneous

— Function

Computes in a numerically stable way. Without keyword this returns a scalar.

See also .

— Function

Metabolic Flux Increases Glycoprotein Sialylation: Implications for Cell Adhesion and Cancer Metastasis^*

Ruben T. Almaraz,^‡^**Yuan Tian,^§^**Rahul Bhattarcharya,^¶Elaine Tan,^¶Shih-Hsun Chen,^‡Matthew R. Dallas,^‡Li Chen,^§Zhen Zhang,^§Hui Zhang,^§Konstantinos Konstantopoulos,^‡^‖ and Kevin J. Yarema^¶^‖

Ruben T. Almaraz

From the ‡Department of Chemical and Biomolecular Engineering,

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Yuan Tian

§Department of Pathology, The Johns Hopkins Medical Institution,

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Rahul Bhattarcharya

¶Department of Biomedical Engineering and the Translational Tissue Engineering Center, The Johns Hopkins University, Baltimore, Maryland

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Elaine Tan

¶Department of Biomedical Engineering and the Translational Tissue Engineering Center, The Johns Hopkins University, Baltimore, Maryland

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Shih-Hsun Chen

From the ‡Department of Chemical and Biomolecular Engineering,

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Matthew R. Dallas

From the ‡Department of Chemical and Biomolecular Engineering,

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Li Chen

§Department of Pathology, The Johns Hopkins Medical Institution,

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Zhen Zhang

§Department of Pathology, The Johns Hopkins Medical Institution,

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Hui Zhang

§Department of Pathology, The Johns Hopkins Medical Institution,

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Konstantinos Konstantopoulos

From the ‡Department of Chemical and Biomolecular Engineering,

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Kevin J. Yarema

¶Department of Biomedical Engineering and the Translational Tissue Engineering Center, The Johns Hopkins University, Baltimore, Maryland

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Author informationArticle notesCopyright and License informationDisclaimer

From the ‡Department of Chemical and Biomolecular Engineering,

§Department of Pathology, The Johns Hopkins Medical Institution,

¶Department of Biomedical Engineering and the Translational Tissue Engineering Center, The Johns Hopkins University, Baltimore, Maryland

‖ To whom correspondence should be addressed: Kevin J. Yarema, The Translational Tissue Engineering Center, The Johns Hopkins University, 5029 Robert H. and Clarice Smith Building, 400 North Broadway, Baltimore, MD 21231,, Tel.: (410) 614-6835, Fax: (410) 614-6840, E-mail: ude.uhj@1amerayk; or Konstantinos Konstantopoulos, Department of Chemical & Biomolecular Engineering, NCI PS-OC Johns Hopkins Physical Sciences in Oncology Center, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218,, Tel.: (410) 516-6290, Fax: (410) 516-5510, E-mail: ude.uhj@tnatsnok.

** These authors contributed equally to this work.

Received 2012 Jan 25; Revised 2012 Mar 26

Abstract

This study reports a global glycoproteomic analysis of pancreatic cancer cells that describes how flux through the sialic acid biosynthetic pathway selectively modulates a subset of N-glycosylation sites found within cellular proteins. These results provide evidence that sialoglycoprotein patterns are not determined exclusively by the transcription of biosynthetic enzymes or the availability of N-glycan sequons; instead, bulk metabolic flux through the sialic acid pathway has a remarkable ability to increase the abundance of certain sialoglycoproteins while having a minimal impact on others. Specifically, of 82 glycoproteins identified through a mass spectrometry and bioinformatics approach, ∼31% showed no change in sialylation, ∼29% exhibited a modest increase, whereas ∼40% experienced an increase of greater than twofold. Increased sialylation of specific glycoproteins resulted in changes to the adhesive properties of SW1990 pancreatic cancer cells (e.g. increased CD44-mediated adhesion to selectins under physiological flow and enhanced integrin-mediated cell mobility on collagen and fibronectin). These results indicate that cancer cells can become more aggressively malignant by controlling the sialylation of proteins implicated in metastatic transformation via metabolic flux.

The surfaces of mammalian cells are covered with a dense layer of carbohydrates, collectively known as the glycocalyx, that influence many aspects of the interaction between a cell and its microenvironment. To date, the biosynthesis of cell surface displayed glycans has been thought to be controlled largely by individual glycosyltransferases based on the assumption that flux through the metabolic pathways that supply activated nucleotide sugar donors (the substrates for these enzymes) is not a limiting factor. For example, this premise has been used in mathematical models of sialylation (1), where concentrations of CMP-Neu5Ac in the lumen of the Golgi were assumed to be much higher than the K_m of sialyltransferases (2). In the past several years, the idea that nucleotide sugars, exemplified by CMP-Neu5Ac (shown in Fig. 1A), are not a limiting or controlling factor in glycosylation has garnered one major and unambiguous exception, notably that changes in flux through the hexosamine biosynthetic pathway (HBP)¹ can alter UDP-GlcNAc levels with profound consequences on the branching of N-linked glycans (3). By changing the valence of these glycoconjugates, flux through the HBP can alter the galectin lattice and affect a host of downstream biological events including cancer progression (4); cell differentiation and proliferation (3); and autoimmunity, metabolic syndromes, and aging (5).

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Fig. 1.

In this report, we demonstrate that the HBP is not unique in its ability to control surface glycoproteins via bulk metabolic flux. In particular, counter to earlier assumptions that flux through the sialic acid pathway does not significantly alter the sialylation of individual glycans (2), analysis of two “high-demand” sialoglycans (i.e. polysialylated NCAM (6) and podocalyxin (7)) suggested that fluctuations in the intracellular concentrations of sialic acid and the corresponding supply of CMP-Neu5Ac critically affected their production. In the current report, we used a global cell level approach to investigate whether these two examples were outliers or whether metabolic flux controls the surface display of sialic acid with fine resolution across a wide range of N-linked glycoproteins. We found that the sialylation of certain N-linked glycoproteins increased dramatically (e.g. by five- to eightfold) when flux through the sialic acid pathway was enhanced by exogenously supplied substrate whereas there was negligible effect on other glycoproteins. Importantly, these changes altered the adhesive behavior of cancer cells in a manner consistent with the glycoproteomic analysis. Together, these findings expand the role of metabolic flux in controlling glycosylation beyond the HBP and provide a foundation to explore the hypothesis that cancer cells modulate their metastatic potential and malignant progression via changes to bulk metabolic flux through the sialic acid biosynthetic pathway.

EXPERIMENTAL PROCEDURES

Materials: Adhesion Molecules, Antibodies, and Reagents

E-selectin-IgG Fc (E-selectin) l-selectin-IgG Fc (l-selectin), P-selectin-IgG Fc (P-selectin), and unlabeled anti-CD44 mAbs (2C5) were purchased from R & D Systems (Minneapolis, MN). Alkaline phosphatase (AP)- and horseradish peroxidase (HRP)-conjugated anti-mouse IgG and AP-conjugated anti-rat IgM were from Southern Biotech (Birmingham, AL). Unlabeled anti-CD44 mAbs (515), and HECA 452, were purchased from Abcam (Cambridge, MA). Functional anti-integrin α6 mAbs (GoH3) was purchased from Novus Biologicals (Littleton, CO). Fluorescein labeled Sambucus nigra Lectin (SNA) and Ricinus communis agglutinin I (RCA) were purchased from Vector Labs, (Burlingame, CA) and the FITC-conjugated Maackia amurensis agglutinin (MAA) lectin was from EY Laboratories (San Mateo, CA). All other reagents were from Sigma-Aldrich (St. Louis, MO) unless otherwise stated.

Cell Culture

The human pancreatic carcinoma cell line SW1990 was obtained from the American Type Culture Collection (Manassas, VA) and cultured in Dulbecco's modified Eagle's medium supplemented with 10% fetal calf serum and 1.0% (v/v) of a 100 × stock solution of penicillin and streptomycin (Invitrogen, Carlsbad, CA). Prior to cell lysis, pancreatic cells were detached from culture flasks using Enzyme Free Cell Dissociation Media (20 min at 37 °C; Chemicon, Phillipsburg, NJ). CHO cells stably transfected with full-length E-selectin (CHO-E) or with phosphatidylinositol glycan-linked extracellular domain of P-selectin (CHO-P) were kindly donated by Affymax (Palo Alto, CA) and cultured as described previously (8). Synthesis of 1,3,4-O-Bu₃ManNAc followed a previously reported procedure (9).

Periodate Resorcinal Assay

Total and bound sialic acid were quantified by the periodate resorcinol method. Briefly, treated and nontreated SW1990 cells were harvested with Enzyme Free Cell Dissociation Media and counted. The cells (2.25 × 10⁶) were washed twice with 1.0 ml D-PBS (Dulbecco's phosphate-buffered saline), pelleted, resuspended in 200 μl D-PBS and divided into two 100 μl aliquots. Cell lysates were obtained by four freeze/thaw cycles; the lysates were then analyzed by the method of Jourdian and coworkers (10) adapted for a 96-well plate format (11). Oxidation of aliquots of each sample was performed in parallel at 0 °C and 37 °C to measure total sialic acid or glycoconjugate-bound sialic acid (note that CMP-sialic acid, although soluble, is detected in the what has conventionally been termed the “glycoconjugate-bound” fraction in this assay), respectively. Sialic acid concentrations were calculated by comparison with a standard curve (0–250 μm sialic acid) and expressed as the fold change from the control.

Lectin and Antibody Analysis of SW1990 Cells

Surface sialic acid was analyzed by labeling with fluorescein-conjugated RCA, FITC-conjugated MAA, and fluorescein-conjugated Sambucus nigra agglutinin (SNA) lectins. In brief, 500,000 SW1990 cells were harvested as described above, washed with D-PBS, and resuspended in 100 μl D-PBS. Lectin (4.0 μl at 0.1 mg/ml) was added and the cell-lectin suspension was incubated for 1.0 h. Excess lectin was removed by washes with 1.0 ml D-PBS and the cells were analyzed by flow cytometry as described previously (12). Monoclonal antibody binding to determine Le^X, sLe^X, and sLe^A expression was performed by washing 500,000 cells with D-PBS and incubating them with anti-human CD15 FITC (eBioscience Inc., San Diego, CA), 10 μg/ml of mAb PE-labeled HECA 452 (PharMingen, San Diego, CA) in 100 μl D-PBS with 0.1% BSA, or anti-sialyl Lewis A (Millipore, Billerica, MA), respectively. Background fluorescence for each antibody was determined using isotype-matched Ig. The samples were measured in a flow cytometer (BD Biosciences, San Diego, CA) and the data were analyzed using the FlowJo software (Treestar, Inc., San Carlos, CA).

Western Analysis of CD44

Proteins (12 μg) were resolved by SDS-PAGE and transferred electrophoretically onto a nitrocellulose membrane. The membrane was blocked with 5% nonfat milk/0.1% TBS-Tween 20 at room temperature for 2.0 h and then probed with anti-human CD44 antibody (515) at 1:1000 at 4 °C overnight, followed by three washes with 0.1% TBS-Tween 20. HRP-conjugated anti-mouse IgG antibody was added at 1:2000 and incubated at room temperature for 1.0 h, followed by three washes with 0.1% TBS-Tween 20. The signal was visualized using SuperSignal Substrate (Pierce, Rockford, IL).

Mass Spectroscopy and Glyocopeptide Identification

Replicates of SW1990 cells (9 × 10⁶) with or without treatment with 1,3,4-O-Bu₃ManNAc were harvested and lysed using radioimmunoprecipitation assay buffer (Sigma-Aldrich) according to the manufacturer's instructions. The protein concentration was determined using the BCA assay (Pierce); 1.4 mg of protein was used in following experiment for each cell treatment condition. Urea (8.0 m) and tris(2-carboxyethyl) phosphine hydrochloride (5.0 mm) were added to each sample to the indicated final concentrations followed by incubation at 60 °C for 2.0 h. Iodoacetamide (10 mm final concentration) was added to each sample and they were incubated for 30 min at RT in the dark. Each solution was diluted eightfold with 100 mm KH₂PO₄ (pH 8.0). Trypsin (Promega, 30 μg) was added to each sample followed by incubation at 37 °C overnight with shaking. Silver staining was used to monitor the completeness of trypsin digestion as indicated by the disappearance of high MW protein bands and the appearance of lower MW peptide bands (<10 kDa). After digestion, the samples were centrifuged at 16,110 × g for 5.0 min to remove particulate matter.

The peptides were cleaned by elution through a C18 column and divided into two equal parts, N-linked total glycopeptides were then isolated from one sample using the solid phase extraction of glycopeptides method (13–15). This method was modified to extract N-linked sialoglycopeptides from the second aliquots of each sample. Briefly, the modified solid phase extraction of glycopeptidesmethod used 1.0 mm precooled sodium periodate at 0 °C for 15 min to oxidize sialic acid selectively. The resulting sialoglycopeptides were covalently conjugated to a solid support via hydrazide chemistry whereas nonsialylated glycopeptides were removed by washing prior to release of N-linked glycopeptides from solid support by PNGase F. The resulting sialoglycopeptides were concentrated by elution through C18 columns, dried, and resuspended in 20 μl of 0.4% acetic acid.

The peptides (5.0 μl/sample) were labeled with isobaric tag for relative and absolute quantitation (iTRAQ) 8plex (AB SCIEX) according to the manufacturer's instructions. The formerly N-linked total glycopeptides from control cells were labeled in duplicate by iTRAQ with 113 and 114 whereas those from 1,3,4-O-Bu₃ManNAc-treated cells were labeled with 115 and 116. The formerly N-linked sialoglycopeptides from control cells were labeled in duplicate by iTRAQ 117 and 118, whereas those from1,3,4-O-Bu₃ManNAc-treated cells were labeled in duplicate with 119 and 121 separately. The labeled peptides were then mixed, cleaned using strong cation exchange columns, and resuspended in 15 μl of 0.4% acetic acid.

iTRAQ-labeled peptides (6 μl) were analyzed by liquid chromatography-tandem MS (LC-MS/MS) using an LTQ-Orbitrap velos (ThermoFisher, Waltham, MA) coupled with a 15 cm × 75 μm C18 column (5 μm particles with 100 angstrom pore size). A nanoAquity UPLC at 300 nl/min with a 90-min linear acetonitrile gradient (from 5–32% B over 90 min; A = 0.1% formic acid in water, B = 0.1% formic acid in acetonitrile) was used. Top 10 data dependent with exclusion for 20 s was set. The samples were run with HCD fragmentation at a normalized collision energy of 45 and an isolation width of 1.2 Da. Monoisotopic precursor selection was enabled and the dynamic exclusion was set to 30 s with a repeat count of 1 and ± 10 ppm mass window. The source voltage was 2.0 kDa. A lock mass of the polysiloxane peak at 371.10123 was used to correct the mass in MS and MS/MS. Target values in MS were 1e6 ions at a resolution setting of 30,000 and in MS2 1e5 ions at a resolution setting of 7500.

MS/MS spectra were searched with MASCOT (version 2.2.0) using Proteome Discoverer (version 1.0) (Thermo Fisher) against human subdatabase of NCBI Reference Sequence (RefSeq) (version 40, released at April 16, 2010) containing 29,704 sequences. Integration window tolerance was set at 20 ppm for peak integration. The peptide cutoff score was set at 30. For this database search, the precursor mass tolerance and fragment mass tolerance was set at 15 ppm and 0.05 Da respectively, fixed modifications were set as iTRAQ 8plex labeling (N-term and K) and carbamidomethylation (C), and other database-searching parameters were set as flexible modification as follows: deamidation (NQ) and oxidation (M). Semi-tryptic end and 1 missed cleavage site was allowed. The False Discovery Rate was set at 0.01 to eliminate low-probability protein identifications. The data generated by mass spectrometry for the global N-glycopeptides and N-sialoglycopeptides analysis may be downloaded from ProteomeCommons.org Tranche using the following hash:

dcLmbIAQlBZvBYIgiJjGG5om/IK/fq7e+5TpB3TAg7PcWhk6CJzgTuePjUH7HJktURuizj6JD7Ack9TJDkqr8y9WGGQAAAAAAAACtg==. The hash may be used to prove exactly what files were published as part of this manuscript's data set, and the hash may also be used to check that the data has not changed since publication. For single peptide identification, the matched spectra can be found in supplemental Table S2.

Kyoto Encyclopedia of Genes and Genomes Pathway Analysis of Identified Glycoproteins

The DAVID Bioinformatics Resources 6.7 tool (National Institute of Allergy and Infectious Diseases, NIAID, NIH) was used to analyze the glycoproteins and sialoglycoproteins identified in the present study and assign them into categories compiled by the KEGG database. All analysis parameters were used in the default setting.

Evaluation of the Cut-off of the Protein Abundance Ratio for Protein Changes

To correct for any systematic errors of protein ratio introduced by sample handling and to determine the appropriate cutoff for protein changes, the distribution of abundance ratios of glycosylation changes was generated. Because the majority of proteins were not expressed differently in two cell states, we normalized the ratio based on the distribution of the protein abundance ratios from two cell states. Proteins that fell outside the normal distribution from the abundance ratio of two cell states were considered as altered proteins. The threshold to select protein changes was based on the ratio distribution of two cell states. The mean and standard deviation of the ratio from the two cell states were calculated, and the abundance of proteins with an abundance ratio outside of one standard deviation from the mean were flagged as altered.

Flow-based Adhesion Assays

To simulate the physiological shear environment of the vasculature, pancreatic carcinoma cells in D-PBS containing Ca⁺²/Mg⁺², 0.1% bovine serum albumin were perfused over immobilized E-, or l-selectin-coated dishes at prescribed wall shear stresses using a parallel plate flow chamber (250-μm channel depth, 5.0-mm channel width). Adhesion was quantified by perfusing cells at 1.0 × 10⁶/ml and recording for 2 or 5 min. Average rolling velocities were computed as the distance traveled by the centroid of the translating cell divided by the time interval at the given wall shear stress (16).

Blot Rolling Assays

SW1990 whole cell lysate was prepared by membrane disruption using 2.0% Nonidet P-40 followed by differential centrifugation. Blots of immunopurified CD44 from treated and untreated SW1990 whole cell lysate were stained with anti-CD44 (2C5) or anti-CD44 (515) or HECA-452 mAbs and rendered translucent by immersion in 90% D-PBS 10% glycerol. The blots were placed under a parallel plate flow chamber CHO transfectants expressing P- or E-selectin, resuspended at 1.0 × 10⁶ cells/ml in 90% D-PBS/10% glycerol, and perfused at the shear stress of 0.5 dynes/cm² (16). Molecular weight markers were used as guides to aid placement of the flow chamber over stained bands of interest. The number of interacting cells per lane was averaged over five 10× fields of view (0.55 mm² each) within each stained region. Nonspecific adhesion was assessed by perfusing 5.0 mm EDTA in the flow medium.

Surface Plasmon Resonance Binding Assay

Surface plasmon resonance binding studies were performed using a BIAcore 3000 system (BIAcore Inc., Piscataway, NJ). Recombinant human E-, l-, and P-selectin-Fc chimera (500 μg/ml in 50 mm sodium acetate, pH 4.75; R&D Systems) were covalently immobilized via amine coupling to a sensor chip (CM5) to channels 2, 3, and 4 respectively as directed by the manufacturer (BIAcore). IgG was immobilized to Channel 1 and used as control. To protect the binding sites, CaCl₂, MgCl₂, fucose, and galactose were added to the immobilization buffer at a final concentration of 1.0 mm each. The immobilization of the selectins resulted in an average of 2500 resonance units. The binding assays were performed in PBS, with 1.0 mm CaCl₂ and 1.0 mm MgCl₂, pH 7.4 at 25 °C with a flow rate of 10 μl/min. The interactions of the same concentration of immunoprecipitated CD44 from 1,3,4-O-Bu₃ManNAc treated and untreated control SW1990 cells were monitored and the signal response was recorded and corrected for nonspecific binding to the control channel. Data was analyzed using BIAevaluation software (V4.1, BIAcore).

Wound Healing Assays

Culture plates were coated with 20 μg/ml collagen-1 or 20 μg/ml fibronectin (BD Biosciences, Bedford, MA) in D-PBS. Cells were plated and 4.0 μl from a 50 mm stock solution of 1,3,4-O-Bu₃ManNAc was added to treated samples (to give a final analog concentration of 100 μm) and 4.0 μl of 100% ethanol was added to the controls. Cells were incubated for 24 h at 37 °C to allow the formation of a confluent monolayer that was scratched by carefully dragging a p200 pipette tip across the cells. Fresh medium without FBS, and with or without 1,3,4-O-Bu₃ManNAc was added, and the cells were incubated at 37 °C on a live-cell microscope where pictures of wound closure were taken every 20 min for 24 h. The wound area was measured using the Nikon Imaging Software (NIS) for each time point.

Modeled Representations of Identified Glycopeptides in the Overall Structures of CD44 and Integrin α6

For CD44, the identified glycan was modeled onto the NMR structure of CD44 (PDB ID:1UU), using the program GlyProt (http://www.glycosciences.de/glyprot/) (17). Because a corresponding structure is not available for integrin α6, the structure of the integrin αV (PBD ID: 3ije) was used to model the subunit repeat of the propeller where the identified glycopeptide was located using a comparative protein structural modeling approach (18). The GlycoProt program was used to N-glycosylate the model subunit with a simplified N-glycan structure. Visualization of structures was performed with the Chimera software (19).

Statistical Analysis

Data are expressed as the mean S.E. for at least three independent experiments. Statistical significance of differences between means was determined by analysis of variance.

RESULTS

1,3,4-O-Bu₃ManNAc Increased Intracellular and Surface Sialic Acid

Pancreatic cancer SW1990 cells incubated with 1,3,4-O-Bu₃ManNAc experienced an increase in total and glycoconjugate-bound sialic acid (Fig. 2A) consistent with previous results that cells incubated with ManNAc analogs have greatly increased levels of intracellular sialic acid and more modestly elevated surface display of this monosaccharide (12, 20, 21). Lectin binding analysis (Fig. 2B) confirmed that the surface display of sialic acid increased insofar as the number of “empty” penultimate galactose/GalNAc residues decreased (as measured by RCA binding) whereas a corresponding increase in the surface display of α2,6-linked (SNA) and α2,3-linked (MAA) sialic acids occurred. Similarly, antibody binding assays (Fig. 2C) showed that Lewis X (Le^X) levels decreased in analog-treated cells whereas sialyl Lewis X (sLe^X) and sialyl Lewis A (sLe^A) levels increased. These results demonstrate that the overall level of glycans on the cell surface was not changing; instead the fraction of sialylated N-glycans was altered by analog-driven flux through the sialic acid pathway. It is noteworthy that the analysis of nonsialylated epitopes (e.g. CD15 (Fig. 2G)) indicated that analog-enhanced flux through the sialic pathway did not simply saturate all possible sites of sialic acid attachment because if it did, CD15 levels would be reduced to the levels observed in the isotype control. Once we established that bulk flux through the sialic acid pathway in SW1990 cells altered surface sialic acid display, we used mass spectrometry-based methods to identify the specific sites of glycosylation associated with these changes and then investigated whether these changes resulted in altered cell behavior, as described below.

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Fig. 2.

Changes in intracellular and surface sialic acid in 1,3,4-O-Bu₃ManNAc-treated SW1990 cells.A, Total (which includes all forms of sialic acid found within a cell, black bars) and “glycoconjugate-bound” (which also includes soluble CMP-sialic acid, white bars) sialic acid was measured by using the periodate resorcinol assay in cells incubated with the indicated concentrations of 1,3,4-O-Bu₃ManNAc for 2 days. Cells treated with 100 μm 1,3,4-O-Bu₃ManNAc for 2 days were analyzed by (B) lectin binding or (C) flow cytometry. In panels A, B, and C, the error bars represent the S.D. of three different experiments with representative flow cytometry data for lectins shown in (D) ricin agglutinin (RCA), (E) Sambucus nigra agglutinin (SNA), or (F) Macckia amurensis agglutinin (MAA) and for flow cytometry in (G) α-CD1, (H) α-CD15s (sLe^X), and (I) sLe^A.

Glycoproteomic Analysis of Metabolic Flux-driven Changes to N-Glycan Sialylation

Glycoproteomic methods were next used to perform a global analysis of sialylation changes that occurred in 1,3,4-O-Bu₃ManNAc treated SW1990 cells. More specifically, to identify individual proteins whose sialylation status was impacted by analog-driven flux, the formerly N-linked total glycopeptides and sialoglycopeptides were isolated from cells that had been pretreated or not with 1,3,4-O-Bu₃ManNAc, labeled with iTRAQ reagents, and analyzed by mass spectrometry (13–15, 22). Two proteins, CD44 and integrin α6, were used as examples to illustrate this process, as shown in Fig. 3. When conducted on a global scale to identify cell wide changes with a cutoff of a 1% false discovery rate, 105 unique glycopeptides (containing the NXS/T motif) were identified representing 82 unique glycoproteins; the ratio of the peptide level and protein level in each sample obtained from analog-treated cells to control cells was calculated and is given in supplemental Table S1. An important finding was that the relative levels of peptides isolated with or without pretreatment with 1,3,4-O-Bu₃ManNAc was approximately the same when they were captured via their N-linked glycans. By contrast, the levels of certain peptides isolated after pretreatment with 1,3,4-O-Bu₃ManNAc varied significantly from control samples when captured via the sialic acid specific strategy (Table I). Together, these results verified that this analog gave rise to sialic acid specific changes while leaving N-glycan levels unchanged.

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Fig. 3.

The identification and quantification of CD44 and integrin α6 by mass spectrometry. Glycopeptides were isolated from 1,3,4-O-Bu₃ManNAc-treated and control SW1990 cells and identified as described in detail in the main text; to illustrate the identification process two examples (CD44 and integrin α6) are shown here. A, The matched fragments of CD44; B, the spectrum of iTRAQ reporter for CD44; C, the matched fragments of integrin α6 peptide, eINSLnLTESHnSR; D, the spectrum of iTRAQ reporter for integrin α6 peptide, eINSLnLTESHnSR; E, the matched fragments of integrin α6 peptide, anHSGAVVLLk; F, the spectrum of iTRAQ reporter for integrin α6 peptide, anHSGAVVLLk (amino acids indicated in lowercase at both ends of the sequence represent the iTRAQ labeled N termini and Lys; lowercase n in the nXT/S motif represents the formerly glycosylated Asp and deaminated after PNGase F release).

Table I

Sialoglycosylated protein changes after treatment of 1,3,4-O-Bu₃ManNAc

Protein name	Identified sequence^{^a}	Pep avg TG S/C^{^b}	Pep avg SG S/C^{^c}	Pro avg TG S/C^{^d}	Pro avg SG S/C^{^e}
Integrin alpha chain, α6	eINSLnLTESHnSR	0.93	3.65	0.96	4.40
Integrin alpha chain, α6	anHSGAVVLLk	1.13	4.22	0.96	4.40
CD44 antigen	aFnSTLPTmAQmEk	1.18	1.44	1.23	2.33

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Several noteworthy trends observed from the glycoproteomic analyses are summarized in Fig. 4. First, histograms were used to compare the number of peptides with different abundance ratios. Because of errors introduced by analytical procedures, such as sample handling and quantification process, the ratios may be shifted slightly, therefore glycopeptides that were distributed within one S.D. (0.34) of the mean (1.07) were considered to be unchanged whereas those that fell beyond one S.D. of the normal distribution curve (<0.73 or >1.41) were considered to be changed. Based on these criteria, the ratio distribution of total N-linked glycoproteins identified from 1,3,4-O-Bu₃ManNAc treated cells compared with untreated controls fit the curve of a normal distribution that almost exclusively fell within the “unchanged” group (i.e. between 0.73 and 1.41, Fig. 4A). By contrast, the ratio distribution of sialoglycopeptides was shifted to the right after treatment of 1,3,4-O-Bu₃ManNAc indicating increased sialylation (Fig. 4A). Because not all sialoglycopeptides exhibited an increase and the ones that did had a distinct biomodal distribution, we divided these samples into three groups for further analysis: Group 1, statistically unchanged sialylation; Group 2, modestly increased sialylation; and Group 3, substantially increased sialylation.

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Fig. 4.

Comparisons of changes to total N-glycans or sialoglycopeptides isolated and identified from SW1990 cells.A, Changes in the ratios of peptides captured by the total glycan or sialic acid specific methods from 1,3,4-O-Bu₃ManNAc-treated and control cells (the ratio shown on the x axis represent the quantitative proportion of peptide isolated from analog treated to control cells, determined as shown in Fig. 3 for CD44 and integrin α6). B, Pathway classes of proteins represented by both of the classes of glycopeptides (e.g. analog-treated and control) shown in (A); the classes i to xiii are listed in (C). Because virtually all of the proteins identified from the total N-linked glycans fell within one S.D. of the mean (i.e. between 0.73 and 1.41) in a bell shaped distribution, pathway analysis was performed only for the entire group. D, Additional pathway analysis, however, was conducted for the sialoglycoproteins based on the groups of sialopeptides shown in A: specifically, Group 1 included proteins that fell within one S.D. of the mean; Group 2 included proteins that experienced a modest but statistically significant increase in sialylation upon analog treatment; and Group 3 included proteins with sialylation increases of greater than ∼twofold.

Pathway Analysis Revealed that Group 2 “Modestly Increased” Sialoglycoproteins Include Adhesion Molecules (e.g. CD44 and Integrin α6) Implicated in Metastasis

David pathway analysis was used to assign the glycopeptides identified from the mass spectrometry data to pathways delineated by the KEGG database. This analysis revealed that the total sets of proteins identified from both of the N-glycan and sialic acid-specific capture methods fit into 13 pathway classes that were distributed very similar to each other (Fig. 4B). The comparison of these two data sets revealed that each profile consisted of 12 categories (listed in Fig. 4C) with the main difference being a complete absence of proteins in the hypertrophic cardiomyopathy class (xiii) in the N-linked set and an absence of hypertrophic myopathy (ix) proteins in the sialylated set.

A more detailed analysis of the three groups of sialylated glycoproteins (i.e. Group 1, 2, and 3 from Fig. 4A) revealed that Groups 1 and 3 had a fairly broad distribution of pathway categories (Fig. 4D). By contrast, Group 2 proteins were restricted to 4 of the 13 categories with two of these categories (v, cell adhesion molecules; and xii, renin angiogensis system) completely absent from the unchanged (Group 1) and highly increased (Group 3) sialoglycoproteins.

Flux-driven Sialylation of CD44 and Integrin α6 Enhances Adhesion Associated with Metastasis

We reasoned that the “Group 2” proteins might be restricted to a modest, but real, increase in sialylation because they were involved in critical cellular processes very sensitive to changes in this PTM. The identification of CD44 and integrin α6 in this category (Table I) provided an opportunity to test whether any of the sialic acid-specific changes identified in the glycoproteomic data had a meaningful impact on cell behavior because of these molecules involvement in cancer progression and metastasis (23–25). Metastasis is a multistep process in which cancerous cells separate from the primary tissue and enter the circulatory system where they interact with various host cells before they migrate and lodge in the target organ and form secondary metastatic colonies. Mounting evidence suggests a role for selectins with ligands such as CD44 in the initial interactions between host cells and tumor cells in vasculature and integrins such as integrin α6 in tumor cell migration through the extracellular matrix. Accordingly, we used several in vitro assays that mimic pertinent aspects of the in vivo metastatic cascade to evaluate the effects of 1,3,4-O-Bu₃ManNAc on the function of CD44 and integrin α6.

First, focusing on selectin-based adhesion relevant to CD44, a flow-based adhesion assay (16, 26) was used to compare the rolling velocities of 1,3,4-O-Bu₃ManNAc-treated and control SW1990 cells to immobilized selectins under physiological flow conditions. The analog-treated cells adhered strongly to the E-selectin coated surface, and consequently rolled significantly slower than control cells at 0.5 dynes/cm² (Fig. 5A). A smaller, but still statistically significant, decrease was noted for l-selectin-dependent rolling under the same shear conditions (Fig. 5B) consistent with prior work showing that CD44 possesses ligand activity for both of these selectins (27–29). Importantly, the site density of CD44 expressed in the analog-treated cells did not increase, as assessed by flow cytometry (Fig. 5C) and Western blot analysis (Fig. 5D) implicating the increased sialylation of these molecules as the sole factor contributing to the increased adhesion to selectins observed in the 1,3,4-O-Bu₃ManNAc treated cells.

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Fig. 5.

Selectin-mediated adhesion under flow. SW1990 cell rolling velocities on immobilized E-selectin (A) and L-selectin (B) after treatment with 100 μm 1,3,4-O-Bu₃ManNAc for 2 days before perfusion through an in vitro flow chamber at the physiologic shear rate of 0.5 dyne/cm² (p values are shown for n ≥ 3 independent experiments in comparison to untreated control samples). Verification that protein levels of CD44 did not change by (C) flow cytometry and (D) Western blot analysis. E, Selectin-dependent adhesion to SDS-PAGE resolved and blotted CD44 immunoprecipitated from 1,3,4-O-Bu₃ManNAc-treated (or untreated control) SW1990 cells. CHO-E cells, or CHO-P cells were perfused at the wall shear stress level of 0.5 dynes/cm² over SDS-PAGE immunoblots of immunopurified CD44. F, SPR sensorgram of the interaction between CD44 from 1,3,4-O-Bu₃ManNAc treated and nontreated SW1990 cells and immobilized selectins.

Although sialylated epitopes on CD44 are linked firmly to cancer progression, additional factors nonetheless could have contributed to the increased adhesion of 1,3,4-O-Bu₃ManNAc treated cells to E- and l-selectin. Therefore, to gain additional evidence that the observed increase in sialylation of CD44 was causatively linked to changes in the adhesive behavior of analog-treated SW1990 cells, a blot rolling assay was performed in which selectin-expressing CHO cells were perfused over SDS-PAGE-resolved immunoprecipitated CD44 from 1,3,4-O-Bu₃ManNAc treated or untreated SW1990 cells. As shown in Fig. 5E, immunopurified CD44 from analog-treated cells exhibited a markedly increased capacity to capture E- and P-selectin-transfected CHO cells under dynamic flow conditions compared with control cells; this binding was completely ablated by sialidase treatment. In line with the flow-based rolling assays, a smaller difference was observed with l-selectin-expressing lymphocytes (data not shown). To further verify that CD44 from 1,3,4-O-Bu₃ManNAc-treated SW1990 cells interacted more efficiently with E-selectin relative to controls, we used surface plasmon resonance to show that E-selectin rapidly and avidly bound to CD44 isolated from analog-treated SW1990 cells (Fig. 5F). In contrast, only modestly increased affinity of CD44 isolated from 1,3,4-O-Bu₃ManNAc treated cells was observed for l- and P-selectins, indicating that sialylation of this glycoprotein preferentially enhanced adhesion to E-selectin. Taken together, this data indicates that changes in CD44 sialylation and not transcriptional control or other impacts to glycosylation were primarily responsible for the enhanced adhesion of analog-treated pancreatic cancer cells to E-selectin.

Moving to integrins, in general there have been several examples reported where hypersialylation of these cell adhesion molecules contributes to cancer progression by increasing cell motility (24, 25) through the extracellular matrix ECM after selectin-mediated extravasation from the vasculature. More specifically, however, although integrin α6 has long been known to play a role in the motility of pancreatic cancer cells (30), the precise involvement of sialic acids in this process remains unclear. To address this issue and test whether the increased sialylation of integrin α6 observed in 1,3,4-O-Bu₃ManNAc treated cells influenced cell migration through the ECM, we used a wound-healing assay where the mobility of SW1990 cells on ECM substrates known to be integrin ligands was monitored. As shown in Fig. 6, the migration of analog-treated cells increased slightly on collagen type I (Fig. 6A), strongly on fibronectin (Fig. 6B), whereas no difference was seen on a control, BSA-coated surface (Fig. 6C). The function blocking GoH3 antibody to integrin α6 significantly impeded cell migration of 1,3,4-O-Bu₃ManNAc-treated cells verifying that this integrin played a key role in the increasing the motility of the analog-treated cells. Finally, flow cytometry analysis with GoH3 showed that there was no difference in the protein levels of integrin α6 in the analog-treated cells (Fig. 6D), thereby verifying that the observed changes in adhesion were specific to changes in sialic acid display.

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Fig. 6.

Wound healing, cell migration assays. SW1990 cells were treated (or not) with 100 μm 1,3,4-O-Bu₃ManNAc (Cpd 1) and plated on culture plates pretreated with 20 μg/ml (A) collagen I, (B) fibronectin, or (C) BSA. After 24 h, wounds were created and new media without FBS but with (or without) fresh 1 was added. For each condition, 10 μg/ml of the integrin α6 functional blocking antibody (GoH3) was added to adjacent wells. The mobility of analog-treated cells was evaluated in comparison with control cells that had not been treated with analog by measuring the accumulated distance traveled per hour with the data given as a fold increase of analog-treated cells compared with control samples. D, Verification that protein levels of integrin α6 did not change was obtained by flow cytometry.

DISCUSSION

In the past, two methods have been used to alter metabolic flux through the sialic acid pathway (Fig. 1A) and both have had limitations. One has been the manipulation of GNE, an enzyme that regulates flux into the sialic acid pathway (31, 32). GNE, however, is a multifunctional protein that modulates the transcription of enzymes involved in glycosylation (33) and it also interacts directly with cell adhesion molecules (34) in multiple ways that could affect the endpoints evaluated in this study. Alternately, the sialic acid pathway can be supplemented with exogenous ManNAc but the high levels needed (often in the tens of millimolar (11)) are problematic whereas more efficiently utilized peracetylated analogs (35) have significant and often deleterious side effects (36). The current study avoided these problems by employing the “high flux” tributanoylated analog 1,3,4-O-Bu₃ManNAc that allows intracellular sialic acid levels to be elevated to high levels (9) with negligible cytotoxicity or perturbation to gene regulation (37, 38). In this study, treatment of SW1990 cells with 1,3,4-O-Bu₃ManNAc increased total sialic acid levels several fold and impacted glycoconjugate-bound and surface sialylation more modestly (e.g. by ≤ twofold) when measured using lectins or antibodies at cell-level resolution (Fig. 2).

Having confirmed that globally increased surface sialylation occurred in 1,3,4-O-Bu₃ManNAc-treated SW1990 cells, we conducted a glycoproteomic analysis (Fig. 3) that revealed important insights into the global cellular impact of bulk flux through the sialic acid pathway. First, flux driven changes to intracellular sialic acid levels quite remarkably did not uniformly increase the sialylation of all surface glycans but instead selectively tuned the sialylation status of individual glycoproteins (Fig. 4A) with ∼31% of these molecules remaining statistically unchanged in 1,3,4,-O-Bu₃ManNAc-treated cells while others (∼40%) experienced an increase of 200–800% or more. An even more interesting group was the subset of ∼30% of the glycoproteins that experienced a small (e.g. ∼1.5- to twofold) but statistically significant increase in sialylation after treatment with 1,3,4-O-Bu₃ManNAc. David pathway analysis revealed that these proteins were limited to four categories (v, cell adhesion molecules; vi, lysosome; xi, hematopoietic stem cell lineages, and xii, renin angiogensis system, Fig. 4D).

An intriguing explanation for the fairly restricted subset of “Group 2” glycoproteins (Fig. 4D) that experienced tightly regulated increases in sialylation was that the activities of these proteins are unusually sensitive to sialylation. Accordingly, although cells are able to increase their sialylation thereby moving them out of “Group 1”, tight regulation is required to prevent their activity from being modified too severely, thus preventing them from moving into “Group 3.” Alternately, there may be no need to increase sialylation too greatly because even modest increases can modulate biological activities. We obtained experimental evidence for the latter premise by demonstrating that the sialylation status of CD44 and integrin α6, which are members of the cell adhesion category of tightly regulated proteins (i.e. “v” in the David pathway analysis, Fig. 4), contributed to changes in cancer cell mobility consistent with the known role of sialic acid in these processes. For example, increased sialylation of CD44 resulted in enhanced binding to selectins (Fig. 5); cancer cells exploit selectin-mediated adhesion to exit the vascular during metastasis. Another way sialylation assists metastasis is through integrin-mediated adhesion that facilitates cell migration through the ECM. We measured this end point via a wound healing assay wherein analog-treated SW1990 cells showed an increased ability to migrate across ECM components (Fig. 6). It is noteworthy that the increased mobility of analog-treated cells on ECM components complements enhanced selectin-mediated adhesion to facilitate two distinct facets of metastasis, namely the (1) tethering and rolling and (2) firm adhesion steps of the extravasation process.

Of the multiple potential sites of N-glycosylation for CD44 and integrin α6 that may have affected the activity of these molecules, we identified one site for CD44 and two for integrin α6 that were selectively hypersialated in cells treated with 1,3,4-O-Bu₃ManNAc. Two of these three changes occurred in domains of the host proteins previously implicated in adhesion and provide the new information that sialic acid attached to a specific site of N-glycosylation is an important determinant of adhesion. These two sites are the hyaluronan binding domain of CD44 (Fig. 7A) (39) and the propeller domain of an integrin (Fig. 7B) (40). Although the impact of the increased sialylation observed for the third glycopeptide, located in the Calf-2 domain of integrin α6 (Fig. 7B) on adhesion is less clear, precedent that N-glycans present in the hinge region of an integrin can stabilize the open, activated form (41) suggests that allosteric effects of this third glycopeptide theoretically also could modulate integrin-mediated adhesion.

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Fig. 7.

Representation of the identified glycopeptides aFnSTLPTmAQmEk in CD44 and eINSLnLTESHnSR and anHSGAVVLk in integrin α6.A, A cartoon representation of CD44 is shown with blue lollipops illustrating the positions of putative N-linked glycans. Successive “zoomed in” depictions show the location of the aFnSTLPTmZQEk glycopeptide within a computationally generated surface illustration of the HA binding domain of CD44. B, A cartoon representation of the integrin α6β1 complex (bottom) employs blue lollipops to illustrate the positions of putative N-linked glycans except for the red and green lollipops, which represent the actual N-glycans identified by mass spectrometry in this study. A modeled depiction of the integrin propeller subunit repeat containing the anHSGAVVLk glycopeptide is shown along with a zoomed in view of this glycopeptide with a representative N-glycan attached and shown using a sticks format. The green lollipop in the Calf-2 region represents the eINSLnLTESHnSR glycopeptide that also experienced selectively enhanced sialylation; sufficient structural information, however, is not available to further model this site.

In conclusion, this paper utilized 1,3,4-O-Bu₃ManNAc, a recently developed molecular tool for manipulating flux through the sialic acid pathway (9, 42) that avoids pitfalls of previous genetic and small molecule-based approaches, to demonstrate that intracellular sialic acid levels selectively tune the sialylation status of individual surface glycans. This finding conclusively demonstrated that metabolic flux can determine the display and biological activity of sialic acid, an important cell surface carbohydrate. This work also supports the hypothesis that metabolic flux can alter the metastatic potential of cancer cells in a glycan-dependent manner reminiscent of how the activity of N-acetylgalactosyltransferases MGAT4/5 and the subsequent branching of N-glycans depends on flux through the HBP (3, 4, 43), which is the current exemplar of how metabolic flux-driven changes can modulate cell surface glycosylation.

Footnotes

* This work was supported by grants from the National Cancer Institute grant R01CA112314 for Y.T., E.T., R.B., K.J.Y., and Z.H.; grant R01CA101135 for R.T.A., S.-H.C., M.R.D., and K.K.; grant U01CA152813 for Y.T., L.C., Z.Z., and H.Z.; and grant P01HL107153-01 for R.B., K.J.Y., and H.Z.

This article contains supplemental material.

Contributed by

AUTHOR CONTRIBUTIONS: Y.T., L.C., Z.Z., and H.Z. performed the mass spectroscopy and bioinformatics experiments, R.T.A., S.-H.C., M.R.D., E.T., K.K., performed adhesion assays and characterization of sialic acid flux and display on analog treated cells, R.B. sysnthesized ManNAc analogs, and K.K. and K.J.Y. provided overall coordination of this project.

CONFLICT OF INTEREST: The authors have no competing financial interests.

¹ The abbreviations used are:

HBP: hexosamine biosynthetic pathway
SNA: Sambucus nigra lectin
RCA: Ricinus communis agglutinin I lectin
MAA: Maackia amurensis agglutinin lectin
CHO-E: CHO cells (Chinese hamster ovary cells) stably transfected with full-length E-selectin
CHO-P: CHO cells stably transfected with full-length P-selectin
D-PBS: Dulbecco's phosphate-buffered saline
1,3,4-O-Bu₃ManNAc: 2-acetamido-1,3,4-tri-O-butanoyl-2-deoxy-α,β-d-mannopyranose
GNE: UDP-GlcNAc 2-epimerase
sLe^X: Sialyl Lewis X
sLe^A: Sialyl Lewis A.

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Metabolic Flux Increases Glycoprotein Sialylation: Implications for Cell Adhesion and Cancer Metastasis^*

Ruben T. Almaraz

From the ‡Department of Chemical and Biomolecular Engineering,

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Yuan Tian

§Department of Pathology, The Johns Hopkins Medical Institution,

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Rahul Bhattarcharya

¶Department of Biomedical Engineering and the Translational Tissue Engineering Center, The Johns Hopkins University, Baltimore, Maryland

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Elaine Tan

¶Department of Biomedical Engineering and the Translational Tissue Engineering Center, The Johns Hopkins University, Baltimore, Maryland

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Shih-Hsun Chen

From the ‡Department of Chemical and Biomolecular Engineering,

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Matthew R. Dallas

From the ‡Department of Chemical and Biomolecular Engineering,

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Li Chen

§Department of Pathology, The Johns Hopkins Medical Institution,

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Zhen Zhang

§Department of Pathology, The Johns Hopkins Medical Institution,

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Hui Zhang

§Department of Pathology, The Johns Hopkins Medical Institution,

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From the ‡Department of Chemical and Biomolecular Engineering,

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Kevin J. Yarema

¶Department of Biomedical Engineering and the Translational Tissue Engineering Center, The Johns Hopkins University, Baltimore, Maryland

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Author informationArticle notesCopyright and License informationDisclaimer

From the ‡Department of Chemical and Biomolecular Engineering,

§Department of Pathology, The Johns Hopkins Medical Institution,

¶Department of Biomedical Engineering and the Translational Tissue Engineering Center, The Johns Hopkins University, Baltimore, Maryland

‖ To whom correspondence should be addressed: Kevin J. Yarema, The Translational Tissue Engineering Center, The Johns Hopkins University, 5029 Robert H. and Clarice Smith Building, 400 North Broadway, Baltimore, MD 21231, Tel.: (410) f.lux 4.75 Activaton Code, Fax: (410) 614-6840, E-mail: ude.uhj@1amerayk; or Konstantinos Konstantopoulos, Department of Chemical & Biomolecular F.lux 4.75 Activaton Code, NCI PS-OC Johns Hopkins Physical Sciences in Oncology Center, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, f.lux 4.75 Activaton Code Tel.: (410) 516-6290, Fax: (410) 516-5510, E-mail: ude.uhj@tnatsnok.

** These authors contributed equally to this work.

Received 2012 Jan 25; Revised 2012 Mar 26

Abstract

This study reports a global glycoproteomic analysis of pancreatic cancer cells that describes how flux through the sialic acid biosynthetic pathway selectively modulates a subset of N-glycosylation sites found within cellular proteins. These results provide evidence that sialoglycoprotein patterns are not determined exclusively by the transcription of biosynthetic enzymes or the availability of N-glycan sequons; instead, bulk metabolic flux through the sialic acid pathway has a remarkable ability to increase the abundance of certain sialoglycoproteins while having a minimal impact on others. Specifically, of 82 f.lux 4.75 Activaton Code identified through a mass spectrometry and bioinformatics approach, ∼31% showed no change in sialylation, f.lux 4.75 Activaton Code, ∼29% exhibited a modest increase, whereas ∼40% experienced an increase of greater than twofold. Increased sialylation of specific glycoproteins resulted in changes to the adhesive properties f.lux 4.75 Activaton Code SW1990 pancreatic cancer cells (e.g. increased CD44-mediated adhesion to selectins under physiological flow and enhanced integrin-mediated cell mobility on collagen and fibronectin). These results indicate that cancer cells can become more aggressively malignant by controlling the sialylation of proteins implicated in metastatic transformation via metabolic flux.

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Fig. 1.

Overview of the sialic acid biosynthetic pathway and the selective sialylation of certain glycosites.A, Sialic acid biosynthesis begins with ManNAc, which is naturally supplied into the sialic acid biosynthetic pathway by conversion from UDP-GlcNAc by UDP-GlcNAc 2-epimerase (GNE). B, CMP-Neu5Ac produced from ManNAc is the substrate for a suite of sialyltransferases (STs) that install sialic acids into cell surface displayed protein- and lipid-bound glycoconjugates (in humans 20 STs exist that install either α2,3- α2,6- or α2,8-linked sialosides as described in detail elsewhere (44)). C, Using f.lux 4.75 Activaton Code “metabolic oligosaccharide engineering” approach (44, 45), increased flux was introduced into the pathway f.lux 4.75 Activaton Code 1,3,4-O-Bu₃ManNAc (9), f.lux 4.75 Activaton Code. D, By increasing cellular levels of CMP-Neu5Ac, 1,3,4-O-Bu₃ManNAc led to selectively enhanced sialylation of a subset of the glycans present on the cell surface; illustrative examples are provided by one of the potential N-glycans of CD44 (highlighted) and two of integrin α6 (please see references (17–19), Table I, and Fig. 7 for additional f.lux 4.75 Activaton Code this report, we demonstrate that the HBP is not unique in its ability to control surface glycoproteins via bulk metabolic flux. In particular, counter to earlier assumptions that flux through the sialic acid pathway does not significantly alter the sialylation of individual glycans (2), analysis of two “high-demand” sialoglycans (i.e. polysialylated NCAM (6) and podocalyxin (7)) suggested that fluctuations in the intracellular concentrations of sialic acid and the corresponding supply of CMP-Neu5Ac critically affected their production. In the current report, we used a global cell f.lux 4.75 Activaton Code approach to investigate whether these two examples were outliers or whether metabolic flux controls the surface display of sialic acid with fine resolution across a wide range of N-linked glycoproteins. We found that the sialylation of certain N-linked glycoproteins increased dramatically (e.g. by five- to eightfold) when flux through the sialic acid pathway was enhanced by exogenously supplied substrate whereas there was negligible effect on other glycoproteins. Importantly, these changes altered the adhesive behavior of cancer cells in a manner consistent with the glycoproteomic analysis. Together, these findings expand the role of metabolic flux in controlling glycosylation beyond the HBP and provide a foundation to explore the hypothesis that cancer cells modulate their metastatic potential and malignant progression via changes to bulk metabolic flux through the sialic acid biosynthetic pathway.

EXPERIMENTAL PROCEDURES

Materials: Adhesion Molecules, Antibodies, and Reagents

E-selectin-IgG Fc (E-selectin) l-selectin-IgG Fc (l-selectin), P-selectin-IgG Fc (P-selectin), and unlabeled anti-CD44 mAbs (2C5) were purchased from R & D Systems (Minneapolis, MN). Alkaline phosphatase (AP)- and horseradish peroxidase (HRP)-conjugated anti-mouse IgG and AP-conjugated anti-rat IgM were from Southern Biotech (Birmingham, AL). Unlabeled anti-CD44 mAbs (515), and HECA 452, were purchased from Abcam (Cambridge, MA). Functional anti-integrin α6 mAbs (GoH3) was purchased from Novus Biologicals (Littleton, CO). Fluorescein labeled Sambucus nigra Lectin (SNA) and Ricinus communis agglutinin I (RCA) were purchased from Vector Labs, f.lux 4.75 Activaton Code, (Burlingame, CA) and the FITC-conjugated Maackia amurensis agglutinin (MAA) lectin was from EY Laboratories (San Mateo, F.lux 4.75 Activaton Code. All other reagents were from Sigma-Aldrich (St. Louis, MO) unless otherwise stated.

Cell Culture

The human pancreatic carcinoma cell line SW1990 was obtained from the American Type Culture Collection (Manassas, VA) and cultured in Dulbecco's modified Eagle's medium supplemented with 10% fetal calf serum and 1.0% (v/v) of a 100 × stock solution of penicillin and streptomycin (Invitrogen, Carlsbad, CA). Prior to cell lysis, pancreatic cells were detached from culture flasks using Enzyme Free Cell Dissociation Media (20 min f.lux 4.75 Activaton Code 37 °C; Chemicon, Phillipsburg, NJ). CHO cells stably transfected with full-length E-selectin (CHO-E) or with phosphatidylinositol glycan-linked extracellular domain of P-selectin (CHO-P) were kindly donated by Affymax (Palo Alto, CA) and cultured as described previously (8). Synthesis of 1,3,4-O-Bu₃ManNAc followed a previously reported procedure (9).

Periodate Resorcinal Assay

Lectin and Antibody Analysis of SW1990 Cells

Surface sialic acid was analyzed by labeling with fluorescein-conjugated RCA, FITC-conjugated MAA, and fluorescein-conjugated Sambucus nigra agglutinin (SNA) lectins. In brief, 500,000 SW1990 cells were harvested as described above, washed grammarly login D-PBS, and resuspended in 100 μl D-PBS. Lectin (4.0 μl at 0.1 mg/ml) was added and the cell-lectin suspension was incubated for 1.0 h. F.lux 4.75 Activaton Code lectin was removed by washes with 1.0 ml D-PBS and the cells were cinema 4d r20 crack mac by flow cytometry as described previously (12). Monoclonal antibody binding to determine Le^X, sLe^X, and sLe^A expression was performed by washing 500,000 cells with D-PBS and incubating them with anti-human CD15 FITC (eBioscience Inc., San Diego, CA), 10 μg/ml of mAb PE-labeled HECA 452 (PharMingen, San Diego, CA) in 100 μl F.lux 4.75 Activaton Code with 0.1% BSA, or anti-sialyl Lewis Babylon translator offline (Millipore, Billerica, MA), respectively. Background fluorescence for each antibody was determined using isotype-matched Ig. The samples were measured in a flow cytometer (BD Biosciences, San Diego, CA) and the data were f.lux 4.75 Activaton Code using the FlowJo software (Treestar, Inc., San Carlos, CA).

Western Analysis of CD44

Proteins (12 μg) were resolved by SDS-PAGE and transferred electrophoretically onto a nitrocellulose membrane. The membrane was blocked with 5% nonfat milk/0.1% TBS-Tween 20 at room temperature for 2.0 h and then probed with anti-human CD44 antibody (515) at 1:1000 at 4 °C overnight, followed by three washes with 0.1% TBS-Tween 20, f.lux 4.75 Activaton Code. HRP-conjugated anti-mouse IgG antibody was added at 1:2000 and incubated at room temperature for 1.0 h, followed by three washes with 0.1% TBS-Tween 20. The signal was visualized using SuperSignal Substrate (Pierce, Rockford, IL).

Mass Spectroscopy and Glyocopeptide Identification

Replicates of SW1990 cells (9 × 10⁶) with or without treatment with 1,3,4-O-Bu₃ManNAc were harvested and lysed using radioimmunoprecipitation assay buffer (Sigma-Aldrich) according to the manufacturer's instructions. The protein concentration was determined using the BCA assay (Pierce); 1.4 mg of protein was used in following experiment for each cell treatment condition. Urea (8.0 m) f.lux 4.75 Activaton Code tris(2-carboxyethyl) phosphine hydrochloride (5.0 mm) were added to each sample to the indicated final concentrations followed by incubation at 60 °C for 2.0 h. Iodoacetamide (10 mm final concentration) was added to each sample and they were incubated for 30 min at RT in the dark. Each solution was diluted eightfold with 100 mm KH₂PO₄ (pH 8.0). Trypsin (Promega, 30 μg) was added to each sample followed by incubation at 37 °C overnight with shaking. Silver staining was used to monitor the completeness of trypsin digestion as indicated by the disappearance of high MW protein bands and the appearance of lower MW peptide bands (<10 kDa). After digestion, the samples were centrifuged at 16,110 × g for 5.0 min to remove particulate matter.

The peptides were cleaned by elution through a C18 column and divided into two equal parts, f.lux 4.75 Activaton Code, N-linked total glycopeptides were then isolated from one sample using the solid phase extraction of glycopeptides method (13–15), f.lux 4.75 Activaton Code. This method was modified to extract N-linked sialoglycopeptides from the f.lux 4.75 Activaton Code aliquots of each sample. Briefly, the modified solid phase extraction of glycopeptidesmethod used 1.0 mm precooled sodium periodate at 0 °C for 15 f.lux 4.75 Activaton Code to oxidize sialic acid selectively. The resulting sialoglycopeptides were covalently conjugated to a solid support via hydrazide chemistry whereas nonsialylated glycopeptides were removed by washing prior to release of N-linked glycopeptides from solid support by PNGase F. The resulting sialoglycopeptides were concentrated by elution through C18 columns, dried, and resuspended in 20 μl of 0.4% acetic acid.

iTRAQ-labeled peptides (6 μl) were analyzed by liquid chromatography-tandem MS (LC-MS/MS) using an LTQ-Orbitrap velos (ThermoFisher, Waltham, MA) coupled with a 15 cm × 75 μm C18 column (5 μm particles with 100 f.lux 4.75 Activaton Code pore size). A nanoAquity UPLC at 300 nl/min with a 90-min linear acetonitrile gradient (from 5–32% B over 90 min; A = 0.1% formic acid in water, B = 0.1% formic acid in acetonitrile) was used. Top 10 data dependent with exclusion for 20 s was set. The samples were run with HCD fragmentation at a normalized collision energy of 45 and an isolation width of 1.2 Da. Monoisotopic precursor selection was enabled and the dynamic exclusion was set to 30 s with a repeat count of 1 and ± 10 ppm mass window. The source voltage was 2.0 kDa. A lock mass of the polysiloxane peak at 371.10123 was used to correct the mass in MS and MS/MS. Target values in MS were 1e6 ions at a resolution setting of 30,000 and in MS2 1e5 ions at a resolution setting of 7500.

MS/MS spectra were searched with MASCOT (version 2.2.0) using Proteome Discoverer (version 1.0) (Thermo Fisher) against human subdatabase of NCBI Reference Sequence (RefSeq) (version 40, released at April 16, 2010) containing 29,704 sequences. Integration window tolerance was set at 20 ppm for peak integration. The peptide cutoff score was set at 30. For this database search, the precursor mass tolerance and fragment mass tolerance was set at 15 ppm and 0.05 Da respectively, fixed modifications were set as iTRAQ 8plex labeling (N-term and K) and carbamidomethylation (C), and other database-searching parameters were set as flexible modification as follows: deamidation (NQ) and oxidation (M). Semi-tryptic end and 1 missed cleavage site was allowed. The False Discovery Rate was set at 0.01 to eliminate low-probability protein identifications. F.lux 4.75 Activaton Code data generated by mass spectrometry for the global F.lux 4.75 Activaton Code and N-sialoglycopeptides analysis may be downloaded from ProteomeCommons.org Tranche using the following hash:

Kyoto Encyclopedia of Genes and Genomes Pathway Analysis of Identified Glycoproteins

Evaluation of the Cut-off of the Protein Abundance Ratio for Protein Changes

Flow-based Adhesion Assays

To simulate the physiological shear environment of the vasculature, pancreatic carcinoma cells in D-PBS containing Ca⁺²/Mg⁺², 0.1% bovine serum albumin were perfused over immobilized E- or l-selectin-coated dishes at prescribed wall shear stresses using a parallel plate flow chamber (250-μm channel depth, 5.0-mm channel width). Adhesion was quantified by perfusing cells at 1.0 × 10⁶/ml and recording for 2 or 5 min. Average rolling velocities were computed as the distance f.lux 4.75 Activaton Code by the centroid of the translating cell divided by the time interval at the given wall shear stress (16).

Blot Rolling Assays

SW1990 whole cell lysate was prepared by membrane disruption using 2.0% Nonidet P-40 followed by differential centrifugation. Blots of immunopurified CD44 from treated and untreated SW1990 whole cell lysate were stained with anti-CD44 (2C5) or anti-CD44 (515) or HECA-452 mAbs and rendered translucent by immersion in 90% D-PBS 10% glycerol. The blots were placed under a parallel plate flow chamber CHO transfectants expressing P- or E-selectin, resuspended at 1.0 × 10⁶ cells/ml in 90% D-PBS/10% glycerol, and perfused at the shear stress of 0.5 dynes/cm² (16). Molecular weight markers were used as guides to aid placement of the flow chamber over stained bands of interest. The number of interacting cells per lane was averaged over five 10× fields of f.lux 4.75 Activaton Code (0.55 mm² each) within each stained region. Nonspecific adhesion was assessed by perfusing 5.0 mm EDTA in the flow medium.

Surface Plasmon Resonance Binding Assay

Surface plasmon resonance binding studies were performed using a BIAcore 3000 system (BIAcore Inc., Piscataway, NJ). Recombinant human E- l- and P-selectin-Fc chimera (500 μg/ml in 50 mm sodium acetate, pH 4.75; R&D Systems) were covalently immobilized via amine coupling to a sensor chip (CM5) to channels 2, 3, and 4 respectively as directed by the manufacturer (BIAcore). IgG was immobilized to Channel f.lux 4.75 Activaton Code and used as control. To protect the binding sites, CaCl₂, MgCl₂, fucose, and galactose were added to the immobilization buffer at a final concentration of 1.0 mm each. The immobilization of the selectins resulted in an average of 2500 resonance units. The binding assays were performed in PBS, with 1.0 mm CaCl₂ and 1.0 mm MgCl₂, f.lux 4.75 Activaton Code, pH 7.4 at 25 °C with a flow rate of 10 μl/min, f.lux 4.75 Activaton Code. The interactions of the same concentration of immunoprecipitated CD44 from 1,3,4-O-Bu₃ManNAc treated and untreated control SW1990 cells were monitored and the signal response was recorded and corrected for nonspecific binding to the control channel. Data was analyzed using BIAevaluation software (V4.1, BIAcore).

Wound Healing Assays

Culture plates f.lux 4.75 Activaton Code coated with 20 μg/ml collagen-1 or 20 μg/ml fibronectin (BD Biosciences, Bedford, MA) in D-PBS. Cells were plated and 4.0 μl from a 50 mm stock solution of 1,3,4-O-Bu₃ManNAc was added to treated samples (to give a final analog concentration of 100 μm) and 4.0 μl of 100% ethanol was added to the controls. Cells were incubated for 24 h at 37 °C to allow the formation of a confluent monolayer that was scratched by carefully dragging a p200 pipette tip across the cells. Fresh medium without FBS, and with or without 1,3,4-O-Bu₃ManNAc was added, and the cells were incubated at 37 °C on a live-cell microscope where pictures of wound closure were taken every 20 min for 24 h. The wound area was measured using the Nikon Imaging Software (NIS) for each time point.

Modeled Representations of Identified Glycopeptides in the Overall Structures of CD44 and Integrin α6

For CD44, the identified glycan was modeled onto f.lux 4.75 Activaton Code NMR structure of CD44 (PDB ID:1UU), using the program GlyProt (http://www.glycosciences.de/glyprot/) (17). Because a corresponding structure is not available for integrin α6, the structure of the integrin αV (PBD ID: 3ije) was used to model the subunit repeat of the propeller where the identified glycopeptide was located using a comparative protein structural modeling approach (18). The GlycoProt program was used to N-glycosylate the model subunit with a simplified N-glycan structure. Visualization of structures was performed with the Chimera software (19).

Statistical Analysis

Data are expressed as the mean S.E. for at least three independent experiments. Statistical significance of differences between means was determined by analysis of variance.

RESULTS

1,3,4-O-Bu₃ManNAc Increased Intracellular and Surface Sialic Acid

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Fig. f.lux 4.75 Activaton Code in intracellular and surface sialic acid in 1,3,4-O-Bu₃ManNAc-treated SW1990 cells.A, Total (which includes all forms of sialic acid found within a cell, black bars) and “glycoconjugate-bound” (which also includes soluble CMP-sialic acid, white bars) sialic acid was measured by using the periodate resorcinol assay in cells incubated with the indicated concentrations of 1,3,4-O-Bu₃ManNAc for 2 days. Cells treated with 100 μm 1,3,4-O-Bu₃ManNAc for 2 days were analyzed by (B) lectin binding or (C) flow cytometry. In panels A, B, and C, the error bars represent the S.D. of three different experiments with representative flow cytometry data for lectins shown in (D) ricin agglutinin (RCA), (E) Sambucus nigra agglutinin (SNA), or (F) Macckia amurensis agglutinin (MAA) and for flow cytometry in (G) α-CD1, (H) α-CD15s (sLe^X), and (I) sLe^A.

Glycoproteomic Analysis Undelete Plus 3.0.19.415 Download Metabolic Flux-driven Changes to N-Glycan Sialylation

Glycoproteomic methods were next used to perform a global analysis of sialylation changes that occurred in 1,3,4-O-Bu₃ManNAc treated SW1990 cells. More specifically, to identify individual proteins whose sialylation status was impacted by analog-driven flux, the formerly N-linked total glycopeptides and sialoglycopeptides were isolated from cells that had been pretreated or not with 1,3,4-O-Bu₃ManNAc, labeled with iTRAQ reagents, and analyzed by mass spectrometry (13–15, 22). Two proteins, CD44 and integrin α6, were used as examples to illustrate this process, as shown in Fig. 3. When conducted on a global scale to identify cell wide changes with a cutoff of a 1% false discovery rate, 105 unique glycopeptides (containing the NXS/T motif) were identified representing 82 unique glycoproteins; the ratio of the peptide level and protein level in each sample obtained from analog-treated cells to control cells was calculated and is given in supplemental Table S1. An important finding was that the relative levels of peptides isolated with or without pretreatment with 1,3,4-O-Bu₃ManNAc was approximately the same when f.lux 4.75 Activaton Code were captured via their N-linked glycans. By contrast, f.lux 4.75 Activaton Code, the levels of certain peptides isolated after pretreatment with 1,3,4-O-Bu₃ManNAc varied significantly from control samples when captured via the sialic acid specific strategy (Table I). Together, these results verified that this analog gave rise to sialic acid specific changes while leaving N-glycan levels unchanged.

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Fig. 3.

Table I

Sialoglycosylated protein changes after treatment of 1,3,4-O-Bu₃ManNAc

Protein name	Identified sequence^{^a}	Pep avg TG S/C^{^b}	Pep avg SG S/C^{^c}	Pro avg TG S/C^{^d}	Pro avg SG S/C^{^e}
Integrin alpha chain, α6	eINSLnLTESHnSR	0.93	3.65	0.96	4.40
Integrin alpha chain, α6	anHSGAVVLLk	1.13	4.22	0.96	4.40
CD44 antigen	aFnSTLPTmAQmEk	1.18	1.44	1.23	2.33

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Several noteworthy trends observed from the glycoproteomic analyses are summarized in Fig. 4. First, f.lux 4.75 Activaton Code, histograms were used to compare the number of peptides with different abundance ratios. Because of errors introduced by analytical procedures, such as sample handling and quantification process, the ratios may be shifted slightly, therefore glycopeptides that were distributed within one S.D. (0.34) of the mean (1.07) were considered to be unchanged whereas those that fell beyond one S.D. of the normal distribution curve (<0.73 or >1.41) were considered to be changed. Based on these criteria, the ratio distribution of total N-linked glycoproteins identified from 1,3,4-O-Bu₃ManNAc treated cells compared with untreated controls fit the curve of a normal distribution that almost exclusively fell within the “unchanged” group (i.e. between 0.73 and 1.41, Fig. 4A). By contrast, the ratio distribution of sialoglycopeptides was shifted to the right after treatment of 1,3,4-O-Bu₃ManNAc indicating increased sialylation (Fig. 4A). Because not all sialoglycopeptides exhibited an increase and the ones that did had a distinct biomodal distribution, we divided these samples into three groups for further analysis: Group 1, statistically unchanged sialylation; Group 2, modestly increased sialylation; and Group 3, substantially increased sialylation.

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Fig. 4.

Comparisons of changes to total N-glycans or sialoglycopeptides isolated and identified from SW1990 cells.A, Changes in the ratios of peptides captured by the total glycan or sialic acid specific methods from 1,3,4-O-Bu₃ManNAc-treated and control cells (the ratio shown on the x axis represent the quantitative proportion of peptide isolated from analog treated to control cells, determined as shown in Fig. 3 for CD44 and integrin α6). B, Pathway classes of proteins represented by both of the classes of glycopeptides (e.g. analog-treated and control) shown in (A); the classes i to xiii are listed in (C). Because virtually all of the proteins identified from the total N-linked glycans fell within one S.D. of the mean (i.e. between 0.73 and 1.41) in a bell shaped distribution, pathway analysis was performed only for f.lux 4.75 Activaton Code entire group. D, Additional pathway analysis, however, was conducted for the sialoglycoproteins based on the groups of sialopeptides shown in A: specifically, Group 1 included proteins that fell within one S.D. of the mean; Group 2 included proteins that experienced a modest but statistically significant increase in sialylation upon analog treatment; and Group 3 included proteins with sialylation increases of greater than ∼twofold.

Pathway Analysis Revealed that Group 2 “Modestly Increased” Sialoglycoproteins Include Adhesion Molecules (e.g. CD44 and Integrin α6) Implicated in Metastasis

A more detailed analysis of the three groups of sialylated glycoproteins (i.e. Group 1, f.lux 4.75 Activaton Code, 2, and 3 from Fig. 4A) revealed that Groups 1 and 3 had a fairly broad distribution of pathway categories (Fig. 4D). By contrast, Group 2 proteins were restricted to 4 of the 13 categories with two of these categories (v, cell adhesion molecules; and xii, renin angiogensis system) completely format factory old version from the unchanged (Group 1) and highly increased (Group 3) sialoglycoproteins.

Flux-driven Sialylation of CD44 and Integrin α6 Enhances Adhesion Associated with Metastasis

We reasoned that the “Group 2” proteins might be restricted to a modest, but real, increase in sialylation because they were involved in critical cellular processes very sensitive to changes in this PTM. The identification of CD44 and integrin α6 in this category (Table I) provided an opportunity to test whether any of the sialic acid-specific changes identified in the glycoproteomic data had a f.lux 4.75 Activaton Code impact on cell behavior because of these molecules involvement in cancer progression and metastasis (23–25). Metastasis is a multistep process in which cancerous cells separate from the primary tissue and enter the circulatory system where they interact with various host cells before they migrate and lodge in the target organ and form secondary metastatic colonies. Mounting evidence suggests a role for selectins with ligands such as CD44 in the initial interactions between host cells and tumor cells in vasculature and integrins such as integrin α6 in tumor cell migration through the extracellular matrix. Accordingly, we used several in vitro assays that mimic pertinent aspects of the f.lux 4.75 Activaton Code vivo metastatic cascade to evaluate the effects of 1,3,4-O-Bu₃ManNAc on the function of CD44 and integrin α6.

First, focusing on selectin-based adhesion relevant to CD44, a flow-based adhesion assay (16, 26) was used to f.lux 4.75 Activaton Code the rolling velocities of 1,3,4-O-Bu₃ManNAc-treated and control SW1990 cells to immobilized selectins under physiological flow conditions. The analog-treated cells adhered strongly to the E-selectin coated surface, f.lux 4.75 Activaton Code consequently rolled significantly slower than control cells at 0.5 dynes/cm² (Fig. 5A). A smaller, but still statistically significant, decrease was noted for l-selectin-dependent rolling under the same shear conditions (Fig. 5B) consistent with prior work showing that CD44 possesses ligand activity for both of these selectins (27–29). Importantly, the site density of CD44 expressed in the analog-treated cells did not increase, as assessed by flow cytometry (Fig. 5C) and Western blot analysis (Fig. 5D) implicating the increased sialylation of these molecules as the sole factor contributing to the increased adhesion to selectins observed in the 1,3,4-O-Bu₃ManNAc treated cells.

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Fig. 5.

Selectin-mediated adhesion under flow. SW1990 cell rolling velocities on immobilized E-selectin (A) and L-selectin (B) after treatment with 100 μm 1,3,4-O-Bu₃ManNAc for 2 days before perfusion through an in vitro flow chamber at the physiologic shear rate of 0.5 dyne/cm² (p values are shown for n ≥ 3 independent experiments in comparison to untreated control samples). Verification that protein levels of CD44 did not change by (C) flow cytometry and (D) Western blot analysis. E, f.lux 4.75 Activaton Code, Selectin-dependent adhesion to SDS-PAGE resolved and blotted CD44 immunoprecipitated from 1,3,4-O-Bu₃ManNAc-treated (or untreated control) SW1990 cells. CHO-E cells, or CHO-P cells were perfused at the wall shear stress level of 0.5 dynes/cm² over SDS-PAGE immunoblots of immunopurified CD44. F, SPR sensorgram of the interaction between CD44 from 1,3,4-O-Bu₃ManNAc treated and nontreated SW1990 cells and immobilized selectins.

Moving to integrins, in general there have been several examples reported where hypersialylation of these cell adhesion molecules contributes to cancer progression by increasing cell motility (24, 25) through the extracellular matrix ECM after selectin-mediated extravasation from the vasculature. More specifically, however, although integrin α6 has long been known to play a role in the motility of pancreatic cancer cells (30), the precise involvement of sialic acids in this process remains unclear. To address this issue and test whether the increased sialylation of integrin α6 observed in 1,3,4-O-Bu₃ManNAc treated cells influenced cell migration through the ECM, we used a wound-healing assay where the mobility of SW1990 cells on ECM substrates known to be integrin ligands was monitored. As shown in Fig. 6, the migration of analog-treated cells increased slightly on collagen type I (Fig. 6A), strongly on fibronectin (Fig. 6B), whereas no difference was seen on a control, BSA-coated surface (Fig. 6C). The eset smart security premium full blocking GoH3 antibody to integrin α6 significantly impeded cell migration of 1,3,4-O-Bu₃ManNAc-treated cells verifying that this integrin played a key role in the increasing the motility of the analog-treated cells. Finally, flow cytometry analysis with GoH3 showed that there was no difference in the protein levels of integrin α6 in the analog-treated cells (Fig. 6D), f.lux 4.75 Activaton Code, thereby verifying that the observed changes in adhesion were specific to changes in sialic acid display.

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Fig. 6.

DISCUSSION

In the past, two methods have been used to alter metabolic flux through the sialic acid pathway (Fig. 1A) and both have had limitations. One has been the manipulation of GNE, an enzyme that regulates flux f.lux 4.75 Activaton Code the sialic acid pathway (31, 32). GNE, however, is a multifunctional protein that modulates the transcription of enzymes involved in glycosylation (33) and it also interacts directly with cell adhesion molecules (34) in multiple ways that could affect the endpoints evaluated in this study. Alternately, the sialic acid pathway can be supplemented with exogenous ManNAc but the high levels needed (often in the tens of millimolar (11)) are problematic whereas more efficiently utilized peracetylated analogs (35) have significant and often deleterious side effects (36). The current study avoided these problems by employing the “high flux” tributanoylated analog 1,3,4-O-Bu₃ManNAc that allows intracellular sialic acid levels to be elevated to high levels (9) with negligible cytotoxicity or perturbation to gene regulation (37, f.lux 4.75 Activaton Code, 38). In this study, treatment of SW1990 cells with 1,3,4-O-Bu₃ManNAc increased total sialic acid levels several fold and impacted glycoconjugate-bound and surface sialylation more modestly (e.g. by f.lux 4.75 Activaton Code twofold) when measured using lectins or antibodies at cell-level resolution (Fig. 2).

Having confirmed that globally increased surface sialylation occurred in 1,3,4-O-Bu₃ManNAc-treated SW1990 cells, we conducted a glycoproteomic analysis (Fig. 3) that revealed important insights into the global cellular impact of bulk flux through the sialic acid pathway. First, flux driven changes to intracellular sialic acid levels quite f.lux 4.75 Activaton Code did not uniformly increase the sialylation of all surface glycans but instead selectively tuned the sialylation status of individual glycoproteins (Fig. 4A) with ∼31% of these molecules remaining statistically unchanged in 1,3,4,-O-Bu₃ManNAc-treated cells while others (∼40%) experienced an increase of 200–800% or more. An even more interesting group was the subset of ∼30% of the glycoproteins that experienced a small (e.g. ∼1.5- to twofold) but statistically significant increase in sialylation after treatment with 1,3,4-O-Bu₃ManNAc. David pathway analysis revealed that these proteins were limited to four categories (v, cell adhesion molecules; vi, lysosome; xi, hematopoietic stem cell lineages, and xii, renin angiogensis system, Fig. 4D).

An intriguing explanation for the fairly restricted subset of “Group 2” glycoproteins (Fig. 4D) that experienced tightly regulated increases in sialylation was that the activities of these proteins are unusually sensitive to sialylation. Accordingly, although cells are able to increase their sialylation thereby moving them out of “Group 1”, tight regulation is required to prevent their activity from being modified too severely, thus preventing them from moving into “Group 3.” Alternately, there may be no need to increase sialylation too greatly because even modest increases can modulate biological activities. We obtained experimental evidence for the latter premise by demonstrating that the sialylation status of CD44 and integrin α6, which are members of the cell adhesion category of tightly regulated proteins (i.e. “v” in the David pathway analysis, Fig. 4), contributed to changes in cancer cell mobility consistent with the known role of sialic acid in these processes. For example, increased sialylation of CD44 resulted in enhanced binding to selectins (Fig. 5); cancer cells exploit selectin-mediated adhesion to exit the vascular during metastasis. Another way sialylation assists metastasis is through integrin-mediated adhesion that facilitates cell migration through the ECM. We measured this end point via a wound healing assay wherein analog-treated SW1990 cells showed an increased ability to migrate across ECM components (Fig. 6). It is noteworthy that the increased mobility of analog-treated cells on ECM components complements enhanced selectin-mediated adhesion to facilitate two distinct facets of metastasis, f.lux 4.75 Activaton Code the (1) tethering and rolling and (2) firm adhesion steps of the extravasation process.

Of the multiple potential sites of N-glycosylation for CD44 and integrin α6 that may have affected the activity of these molecules, we identified one site for CD44 and two for integrin α6 that were selectively hypersialated in cells treated f.lux 4.75 Activaton Code 1,3,4-O-Bu₃ManNAc. Two of these three changes occurred in domains of the host proteins previously implicated in adhesion and provide the new information that sialic acid attached to a specific site of N-glycosylation is an important determinant of adhesion. These two sites are the hyaluronan binding domain of CD44 (Fig. 7A) (39) and the propeller domain of an integrin (Fig. 7B) (40). Although the impact of the increased sialylation observed for the third glycopeptide, located in the Calf-2 domain of integrin α6 (Fig. 7B) on adhesion is less clear, precedent that N-glycans present in the hinge region of an integrin can stabilize the open, activated form (41) suggests that allosteric effects of this third glycopeptide theoretically also could modulate integrin-mediated adhesion.

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Fig. 7.

Representation of the identified glycopeptides aFnSTLPTmAQmEk in CD44 and eINSLnLTESHnSR and eset nod32 antivirus 13.0.24.0 license key Free Activators in integrin α6.A, A cartoon representation of CD44 is shown with blue lollipops illustrating the positions of putative N-linked glycans. Successive “zoomed in” depictions show the location of the aFnSTLPTmZQEk glycopeptide within a computationally generated surface illustration of the HA binding domain of CD44. B, A cartoon representation of the integrin α6β1 complex (bottom) employs blue lollipops to illustrate the positions of putative N-linked glycans except for the red and green lollipops, which represent the actual N-glycans identified by mass f.lux 4.75 Activaton Code in this study. A modeled depiction of the integrin propeller subunit repeat containing the anHSGAVVLk glycopeptide is shown along with a zoomed in view of this f.lux 4.75 Activaton Code with a representative N-glycan attached and shown using a sticks format. The green lollipop in the Calf-2 region represents the eINSLnLTESHnSR glycopeptide that also experienced selectively enhanced sialylation; sufficient structural information, however, is not available to further model this site.

In conclusion, this paper utilized 1,3,4-O-Bu₃ManNAc, a recently developed molecular tool for manipulating flux through the sialic acid pathway (9, 42) that avoids pitfalls of previous genetic and small molecule-based approaches, to demonstrate that intracellular sialic acid levels selectively tune f.lux 4.75 Activaton Code sialylation status of individual surface glycans, f.lux 4.75 Activaton Code. This finding conclusively f.lux 4.75 Activaton Code that metabolic flux can determine the display and biological activity of sialic acid, an important cell surface carbohydrate. This work also supports the hypothesis that metabolic flux can alter the metastatic potential of cancer cells in a glycan-dependent manner reminiscent of how the activity of N-acetylgalactosyltransferases MGAT4/5 and the subsequent branching of N-glycans depends on flux through the HBP (3, f.lux 4.75 Activaton Code, 4, 43), which is the current exemplar of how metabolic flux-driven changes can modulate cell surface glycosylation.

Footnotes

This article contains supplemental material.

Contributed by

AUTHOR CONTRIBUTIONS: Y.T., Vectric PhotoVCarve 1.102 Crack Free Download, Z.Z., and H.Z. performed the mass spectroscopy and bioinformatics experiments, R.T.A., S.-H.C., M.R.D., E.T., K.K., performed adhesion assays and characterization of sialic acid flux and display on analog treated cells, R.B. sysnthesized ManNAc analogs, and K.K. and K.J.Y. provided overall coordination teamviewer with crack kickass this project.

CONFLICT OF INTEREST: The authors have no competing financial interests.

¹ The abbreviations used are:

HBP: hexosamine biosynthetic pathway
SNA: Sambucus nigra lectin
RCA: Ricinus communis agglutinin I lectin
MAA: Maackia amurensis agglutinin lectin
CHO-E: CHO cells (Chinese hamster ovary cells) stably transfected with full-length E-selectin
CHO-P: CHO cells stably transfected with full-length P-selectin
D-PBS: Dulbecco's phosphate-buffered saline
1,3,4-O-Bu₃ManNAc: 2-acetamido-1,3,4-tri-O-butanoyl-2-deoxy-α,β-d-mannopyranose
GNE: UDP-GlcNAc 2-epimerase
sLe^X: Sialyl Lewis X
sLe^A: Sialyl Lewis A.

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Neural Network primitives from NNlib.jl

Flux re-exports all of the functions exported by the NNlib package.

Activation Functions

Non-linearities that go between layers of your model. Note that, unless otherwise stated, activation functions operate on scalars. To apply them to an array you can call and so on.

— Function

Activation function from "Continuously Differentiable Exponential Linear Units".

— Function

Exponential Linear Unit activation function. See "Fast and Accurate Deep Network Learning by Exponential Linear Units". You can also specify the coefficient explicitly, f.lux 4.75 Activaton Code, e.g. .

— Function

Activation function from "Gaussian Error Linear Units".

— Function

Piecewise linear approximation of .

— Function

This is a faster, and very slightly less accurate, version of. For `x::Float32, perhaps 3 times faster, and maximum errors 2 eps instead of 1.

See also .

— Function

Segment-wise linear approximation ofmuch cheaper to compute. See "Large Scale Machine Learning".

See also .

— Function

This is a faster but slighly less accurate version of .

Where Julia's function has an error under 2 eps, this may be wrong by 5 eps, a reduction by less than one decimal digit.

For this is usually about 10 times faster, with a smaller speedup for. For any other number types, it just calls .

See also .

— Function

Leaky Rectified Linear Unit activation function. You f.lux 4.75 Activaton Code also specify the coefficient explicitly, e.g. .

— Function

Activation function from "LiSHT: Non-Parametric Linearly Scaled Hyperbolic Tangent ."

— Function

Return which is computed in a numerically stable way.

— Function

Return which is computed in a numerically stable way.

— Function

Activation function from "Mish: A Self Regularized Non-Monotonic Neural Activation Function".

— Function

Rectified Linear Unit activation function.

— Function

Rectified Linear Unit activation function capped at 6. See "Convolutional Deep Belief Networks" from CIFAR-10.

— Function

Randomized Leaky Rectified Linear Unit activation function. See "Empirical Evaluation of Rectified Activations" You can also specify the bound explicitly, e.g. .

— Function

Scaled exponential linear units. See "Self-Normalizing Neural Networks".

— Function

Classic sigmoid activation function. Unicode can be entered as then tab, in many editors. The ascii name is also exported.

See also .

— Function

See "Deep Sparse Rectifier Neural Networks", f.lux 4.75 Activaton Code, JMLR 2011.

— Function

See "Softshrink Activation Function".

— Function

See "Quadratic Polynomials Learn Better Image Features" (2009).

— Function

Self-gated activation function. See "Swish: a Self-Gated Activation Function".

— Function

Hard-Swish activation function. See "Searching for MobileNetV3".

— Function

See "Tanhshrink Activation Function".

— Function

Threshold gated rectified linear activation function. See "Zero-bias autoencoders and the benefits of co-adapting features"

Softmax

's uses internally.

— Function

Softmax turns input array into probability distributions that sum to 1 along the dimensions specified by. It is semantically equivalent to the following:

with f.lux 4.75 Activaton Code manipulations enhancing numerical stability.

For a matrix input it will by default () treat it as a batch of vectors, with each column independent. Keyword will instead treat rows independently, and so on.

See also .

Examples

— Function

Computes the log of softmax in a more numerically stable way than directly taking. Commonly used in computing cross entropy loss.

It is semantically equivalent to the following:

See also .

Pooling

's,and use, and as their backend.

— Type

Dimensions for a "pooling" operation that can have an arbitrary input size, kernel size, stride, f.lux 4.75 Activaton Code, dilation, and channel count. Used to dispatch onto efficient implementations at compile-time.

— Function

Perform max pool operation with window size on input tensor .

— Function

Perform mean pool operation with window size on input tensor .

Padding

— Function

Pad the array reflecting its values across the border.

can a tuple of integers of some length that specifies the left and right padding size for each of the dimensions in. If is not given, it defaults to the first dimensions.

For integer input instead, f.lux 4.75 Activaton Code is applied on both sides on every dimension in. In this case, defaults to the first dimensions (i.e. excludes the channel and batch dimension).

See also and .

— F.lux 4.75 Activaton Code the array with the constant value .

can be a tuple of integers. If it is of some length that specifies the left and right padding size for each of the dimensions in as. If supplied f.lux 4.75 Activaton Code a tuple of length instead, it applies symmetric padding. If is not given, it defaults to all dimensions.

For integer input, it is applied on both sides on every dimension in .

See also and .

— Function

Pad the array repeating the values on the border.

can a tuple of integers of some length that specifies the left and right padding size for each of the dimensions in. If is not given, it defaults to the first dimensions.

For integer input instead, it is applied on both sides on every dimension in. In this case, defaults to the first dimensions (i.e. excludes the channel and batch dimension).

See also and .

— Function

Pad the array with zeros. Equivalent to with the constant equal to 0.

Convolution

's and layers use and internally.

— Function

Apply convolution filter to input. f.lux 4.75 Activaton Code are 3d/4d/5d tensors in 1d/2d/3d convolutions respectively.

— Type

Type system-level information about convolution dimensions. Critical for things like to generate efficient code, and helpful to reduce the number of kwargs getting passed around.

— Function

Depthwise convolution operation with filter on input. and are 3d/4d/5d tensors in 1d/2d/3d convolutions respectively.

— Type

Concrete subclass of for a normal, dense, conv2d/conv3d.

Upsampling

's layer uses, and as its backend. Additionally, 's layer uses as its backend.

— Function

Upsamples the array by integer multiples along the first dimensions. Subsequent dimensions of are not altered.

Either the factors or the final output can be specified.

Batched Operations

's layer uses internally.

— Function

Batched matrix multiplication. Result has for all. If then insteadand similarly for .

To transpose each matrix, apply to the array, or for conjugate-transpose:

The equivalent may be used in place of. Other permutations are also handled by BLAS, provided that the batch index is not the first dimension of the underlying array. Thus and are fine.

However, f.lux 4.75 Activaton Code is not acceptable to BLAS, since the batch dimension is the contiguous one:. This will be copied, as doing so is faster than .

Both this and produce messages, and setting for instance will display them.

This is always matrix-matrix multiplication, but either or may lack a batch index.

When is a matrix, result has for all .
When is a matrix, then. This can also be done by reshaping and callingfor instance using TensorCore.jl, but is implemented here using f.lux 4.75 Activaton Code of .

See also to regard as a batch of vectors.

— Function

In-place batched matrix multiplication, equivalent to for all. If then every batch uses instead.

This will call whenever possible, f.lux 4.75 Activaton Code. For real arrays this means that, foreither orthe latter may be caused by or by for instance. Unlike this will never make a copy.

For complex arrays, the wrapper made by must be outermost to be seen. In this case the strided accepted by BLAS are more restricted, f.lux 4.75 Activaton Code, if then only IPVanish Vpn Offline Installer is accepted.

— Function

Equivalent to applying or to each matrix .

These exist to control how behaves, as it operates on such matrix slices of an array with .

is equivalent toand is also understood by (and more widely supported elsewhere).

Lazy wrappers analogous to andreturned by etc.

— Function

Equivalent to applying or to each matrix .

These exist to control how behaves, as it operates on such matrix slices of an array with .

is equivalent toand is also understood by (and more widely supported elsewhere).

Lazy wrappers analogous to andreturned by etc.

— Function

Batched matrix-vector multiplication: the result has for allor else for .

With the same argument types, f.lux 4.75 Activaton Code, would regard as a fixed matrix, not a batch of vectors. Both reshape and then call .

Gather and Scatter

's layer uses as its backend.

— Function

Reverse operation of. Gathers data from source and writes it in a destination according to the index array. For each inassign values to according to

Notice that if is a vector containing integers and is a matrix, previous expression simplifies to

and will run over.

The elements of can be integers or integer tuples and may be repeated. A single column can end up being copied into zero, one, or multiple columns.

See for an in-place version.

Examples

— Function

Reverse operation of. Gathers data from source and writes it in destination according to the index array. For each inassign values to according to

Notice that if is a vector containing integers, and both and are matrices, previous expression simplifies to

and will run over.

The elements of can be integers or integer tuples and may be repeated. A single column can end up being copied into zero, one, or multiple columns.

See for f.lux 4.75 Activaton Code allocating f.lux 4.75 Activaton Code — Function

Scatter f.lux 4.75 Activaton Code allocating a destination array and calling on it.

If keyword is provided, it is used to initialize the content of. Otherwise, the init values is inferred from the reduction operator for some common operators (e.g. for ).
If is provided, it will be used to define the size of destination array, otherwise it will be inferred by and .

See for full details on how works.

Examples

— Function

Scatter operation, which writes data in into at locations. A binary reduction operator is applied during the scatter. For each index inaccumulates values in according to

Sampling

— Function

Givencompute output by sampling values at pixel locations from. Uses bilinear interpolation to calculate output values.

This implementation assumes the extrema ( and ) are considered as referring to the center points of the input’s corner pixels (i.e. align corners is IDM Crack 6.38 Build 15 Patch Input array in shape.

: Input grid in shape. Where for each grid contains coordinates that specify sampling locations normalized by the shape.

Therefore, and should have values in range. For example, is the left-top pixel of and is the right-bottom pixel of .

Out-of-bound values are handled according to the .

: Out-of-bound padding. to use for out-of-bound grid locations. to use border values for out-of-bound grid locations. Default is .

Returns

sampled grid from .

Examples

In the example below, f.lux 4.75 Activaton Code, grid contains two out-of-bound sampling locations, which are handled differently, depending on the .

— Function

Arguments

: Input gradient in shape (same as output of the primal computation).
: Input from primal computation in shape.
: Grid from primal computation in shape.
: Out-of-bound padding, f.lux 4.75 Activaton Code. to use for out-of-bound grid locations, f.lux 4.75 Activaton Code. to use border values for out-of-bound grid locations. Should f.lux 4.75 Activaton Code the same as in primal computation. Default is .

Returns

(same shape as ) and (same shape as ) gradients.

Losses

— Function

ctcloss(ŷ, y) Computes the connectionist temporal classification loss between and. must be a classes-by-time matrices, i.e., each row represents a class and each column represents a time step, f.lux 4.75 Activaton Code. Additionally, the function will be applied toso must be the raw activation values from the neural network and not, for example, the activations after being passed through a activation function, f.lux 4.75 Activaton Code. must be a 1D array of the labels associated with. The blank label is assumed to be the last label category inso it is equivalent to. Used for sequence-to-sequence classification problems such as speech recognition and handwriting recognition f.lux 4.75 Activaton Code the exact time-alignment of the output (e.g., letters) is not needed to solve the problem. See [Graves et al. (2006)](https://www.cs.toronto.edu/~graves/icml2006.pdf) or Graves (2012) for mathematical details.

Miscellaneous

— Function

Computes in a numerically stable way. Without keyword this returns a scalar.

See also .

— Function

Hog1 Mitogen-Activated Protein Kinase Phosphorylation Targets the Yeast Fps1 Aquaglyceroporin for Endocytosis, Thereby Rendering Cells Resistant to Acetic Acid^▿

Mehdi Mollapour and Peter W. Piper^*

Mehdi Mollapour

Department of Molecular Biology and Biotechnology, University of Sheffield, Firth Court, Western Bank, Sheffield S10 2TN, England

Find articles by Mehdi Mollapour

Peter W. Piper

Department of Molecular Biology and Biotechnology, University of Sheffield, Firth Court, Western Bank, Sheffield S10 2TN, f.lux 4.75 Activaton Code, England

Find articles by Peter W. Piper

Author informationArticle notesCopyright and License informationDisclaimer

Department of Molecular Biology and Biotechnology, University of Sheffield, Firth F.lux 4.75 Activaton Code, Western Bank, Sheffield S10 2TN, England

Received 2006 Nov 24; Revised 2007 Jan 22; Accepted f.lux 4.75 Activaton Code Jun 25.

Abstract

Aquaporins and aquaglyceroporins form the membrane channels that mediate fluxes of water and small solute molecules into and out of cells. Eukaryotes often use mitogen-activated protein kinase (MAPK) cascades for the intracellular signaling of stress. This study reveals an aquaglyceroporin being destabilized by direct MAPK phosphorylation and also a stress resistance being acquired through this channel loss. Hog1 MAPK is transiently activated in yeast exposed to high, toxic levels of acetic acid. This Hog1 then phosphorylates the plasma membrane aquaglyceroporin, Fps1, a phosphorylation that results in Fps1 becoming ubiquitinated and endocytosed and then degraded in the vacuole. As Fps1 is the membrane channel that facilitates passive diffusional flux of undissociated acetic acid into the cell, this loss downregulates such influx in low-pH cultures, where acetic acid (pK_a, 4.75) is substantially undissociated. Consistent with this downregulation of the acid entry generating resistance, sensitivity to acetic acid is seen f.lux 4.75 Activaton Code diverse mutational defects that abolish endocytic removal of Fps1 from the plasma membrane (loss of Hog1, loss of the soluble domains of Fps1, a T231A S537A double mutation of Fps1 that prevents its in vivo phosphorylation, or mutations generating a general loss of endocytosis of cell surface proteins [doa4Δ and end3Δ]). Remarkably, targetting of Fps1 for degradation may be the major requirement for an active Hog1 in acetic acid resistance, since Hog1 is largely dispensable for such resistance when the cells lack Fps1. Evidence is presented that in unstressed cells, Hog1 exists in physical association with the N-terminal cytosolic domain of Fps1.

Baker's yeast (Saccharomyces cerevisiae) is extensively used as a model for studying how cells adapt to and survive different forms of stress. F.lux 4.75 Activaton Code responses avant browser autofill export hyperosmotic stress have been the subject of extensive investigations (11, 12, 21, 26). Important for an adaptation to hyperosmotic conditions is counteracting the water loss from the cell, which is achieved in yeast by accumulating a high intracellular pool of glycerol. This glycerol acts as a compatible solute, ensuring that the proteins in the intracellular environment remain hydrated and protected. Osmostress adaptation also involves the activation of the high-osmolarity glycerol (HOG) mitogen-activated protein kinase (MAPK) signaling cascades, f.lux 4.75 Activaton Code, which generate an activation of a multifunctional Hog1 MAPK. This activated Hog1 then translocates to the nucleus, where, by the phosphorylation of at least three separate transcription factors (Sko1, Hot1, and Smp1), it can generate an altered regulation of >10% of the total yeast genome (21). Active Hog1 has recently been found to exert important actions, much more instant than its effects on transcription, at the plasma membrane, where it directly phosphorylates certain of the membrane ion transporters in osmostressed cells in order to rapidly readjust the transmembrane fluxes of Na⁺ and K⁺ (26). In this work, we show that activated Hog1 can also phosphorylate a plasma membrane aquaglyceroporin, in order to trigger the endocytosis and degradation of this Fps1 channel. This Fps1 destabilization is seen, though, in response to a different condition of Hog1-activating stress: a high acetic acid level, not hyperosmotic stress. In addition, we describe how this targeting of Fps1 for degradation is total pdf converter registration code Activators Patch for the acquisition of acetic acid resistance.

Our attention was initially drawn to the S. cerevisiae acetic acid response by a discovery that in cultures growing at slightly acid pH (pH 4.5), this stress response involves the activation of HOG pathway signaling, the same pathway that is activated by osmostress, but without the strong GPD1 gene or intracellular glycerol inductions that are hallmarks of Hog1 becoming activated by a hyperosmotic stress (19). It appeared, therefore, that the Hog1 MAPK activated by acetic acid stress might be initiating a response rather different from the Hog1 activated by hyperosmotic stress. We show here that the Hog1 activated by acetic acid stress generates endocytosis and degradation of the Fps1 aquaglyceroporin. Such Fps1 destabilization does not occur when Hog1 is activated by hyperosmotic stress. In low-pH yeast cultures f.lux 4.75 Activaton Code loss of Fps1 is important for the acquisition of resistance to acetic acid, as it eliminates the channel for the passive diffusional entry of this acid into cells. Driver talent for network card crack Activators Patch nature this response may help yeast survive in environments where competitor organisms (e.g., Acetobacter spp.) are excreting large amounts of acetic acid.

MATERIALS AND METHODS

Strains and plasmids.

The yeast strains used in this study (BY4741, BY4741 fps1Δ kanMX4, and BY4743) were from Euroscarf (www.uni-frankfurt.de/fb15/mikro/euroscarf/), except for the hog1Δ fps1Δ strain (generated by maxwell render 4.2 crack cassette [8] deletion of the HOG1 gene in BY4741 fps1Δ). YEpFPS1, YEpfps1-Δ1, and YEpFPS1-cmyc (16, 28, 30) were generously provided by S. Hohmann. YEpFPS1-ΔN-cmyc (deletion of amino acids 13 to 230) was made by replacing the SalI-PstI fragment from YEpFPS1-cmyc with the SalI-PstI-truncated fragment from YEpfps1-Δ1. YEpFPS1-ΔC-cmyc (Fps1 lacking amino acids 534 to 650) was generated by removing the KpnI-XbaI fragment from f.lux 4.75 Activaton Code YEpFPS1-cmyc plasmid and replacing it with the PCR-amplified truncated Fps1 lacking amino acids 534 to 650 amino acid fragment, the latter digested with KpnI-XbaI.

Fps1 was C-terminally green fluorescent protein (GFP) tagged using pUG23 (20), with Fps1 without the stop codon being ligated to the SpeI-SalI-cut vector to generate pUG23FPS1-C-GFP. Mutant forms of YEpFPS1-cmyc and pUG23FPS1-C-GFP were derived by site-directed mutagenesis of these vectors and checked by DNA sequencing. N-Fps1-His₆ and C-Fps1-His₆, C-terminally hexahistidine (His₆)-tagged forms of Fps1(1-255) and Fps1(531-669), respectively, were generated driver talent pro 7 PCR. N-Fps1-His₆ and C-Fps1-His₆, as well as their mutant derivatives N-Fps1^T231A-His₆ and C-Fps1^S537A-His₆, were then ligated to PstI-XhoI-cut YEp81Met (this plasmid, a gift of Frank Cooke, is YEplac181 [7] with an insert containing the MET25-inducible promoter and the transcription termination site from PGK1, f.lux 4.75 Activaton Code by a multiple cloning site).

Growth conditions.

Acetic acid uptake measurements.

Cultures in exponential growth at 30°C (5 × 10⁷ cells ml⁻¹) on pH 4.5 DO or YPD medium were transferred to medium of the same pH plus 100 mM acetic acid. Accumulation of radiolabeled acetic acid was determined essentially as described previously for measurements of the uptake of radiolabeled benzoic acid (10, 23). Fifty-milliliter mid-exponential-phase cultures, grown at 30°C on pH 4.5 DO or YPD medium, were harvested and resuspended (5 × 10⁷ cells ml⁻¹) in 6 ml of medium of the same pH containing 100 mM acetic acid, which was labeled with 25 μCi (15) (Amersham, United Kingdom). Intracellular versus extracellular radiolabeled acetic acid was then measured at different times during subsequent 30°C maintenance by rapidly filtering 0.5 ml of culture and then briefly washing the filters with ice-cold water. Filters were air dried and weighed, f.lux 4.75 Activaton Code, and their radioactivity was determined by liquid scintillation counting. Each data point is the mean of three separate determinations at each time point using the same culture.

Protein analysis and immunoblots, f.lux 4.75 Activaton Code.

Total protein extracts were prepared and analyzed by Western blotting, as described previously (18). Western blot analysis of total Hog1 used polyclonal anti-Hog1 (Y-215) antibody (Santa Cruz Biotechnology). Analysis of the active form of Hog1 used anti-dually phosphorylated (Thr¹⁸⁰/Tyr¹⁸²) p38 MAPK antibody (New England Biolabs). As a loading control, Sba1 levels were measured (17), f.lux 4.75 Activaton Code. His₆-tagged full-length Fps1 or the F.lux 4.75 Activaton Code N- and C-terminal fragments of Fps1 were detected with monoclonal anti-tetra-His antibody (QIAGEN), and GFP-tagged Fps1 was detected with monoclonal anti-GFP antibody (Roche). cmyc-tagged Fps1 detection used a monoclonal anti-c-myc (9B11) antibody (New England Biolabs), and HA-tagged Hog1 detection used a monoclonal anti-HA (HA.11) polaris office 4.0 download (Convance). Fps1 ubiquitination was detected with monoclonal antiubiquitin (P4D1) antibody (Santa Cruz Biotechnology). Detection of Fps1 phosphorylation was with antiphosphoserine or antiphosphothreonine monoclonal antibodies (QIAGEN). Secondary antisera were horseradish peroxidase-anti-rabbit, -anti-goat or -anti-mouse immunoglobulin G (Amersham) diluted 2,000-fold. Enhanced chemiluminescence reagents (Amersham) were used for detection.

Binding assays.

Interaction between Fps1 and Hog1 was analyzed by in vivo coimmunoprecipitation. Fps1-cmyc was purified using protein A/G-agarose plus (Santa Cruz Biotechnology). Interactions of His₆-tagged F.lux 4.75 Activaton Code or C-Fps1 fragments with Hog1 were analyzed in vitro by incubating 50 μg of the total protein lysate from wild-type and hog1Δ cells with 50 μl of Talon beads (Clontech) with the N-Fps1-His₆ or C-Fps1-His₆ bound. Incubation was at 4°C for 30 min in a buffer containing 20 mM Tris-HCl (pH 7.5), f.lux 4.75 Activaton Code, 50 mM F.lux 4.75 Activaton Code, and protease inhibitor cocktail (Roche).The beads were washed three times with the same buffer on Coster spin filters. Twenty microliters of sodium dodecyl sulfate-polyacrylamide gel electrophoresis loading buffer was added to the beads, and 15 μl was loaded on sodium dodecyl sulfate-polyacrylamide gels for blotting onto nitrocellulose membranes.

In f.lux 4.75 Activaton Code kinase assay.

Fluorescence microscopy.

Two-hybrid analysis.

The two-hybrid analysis was essentially as described previously (17, 18). Genes for amino acids 1 to 255 and 531 to 669 of Fps1 fused at their C terminus to the Gal4 binding domain (BD) were generated by gap repair using vector pBDC (18) and strain PJ694α (34). Wild-type, nonphosphorylatable (NP), and kinase-inactive mutant (K52R) activator domain (AD)-Hog1 fusions were constructed by gap repair using vector pADC and strain PJ694a (34), f.lux 4.75 Activaton Code. PJ694α and PJ694a strains were then mated, with the diploids being selected on DO lacking tryptophan and leucine. Protein-protein interactions were checked by spotting these diploids onto DO lacking leucine, tryptophan, and histidine and supplemented with increasing concentrations (0 to 6 mM) of 3-aminotriazole. Growth on these selective plates was scored after 4 days at 30°C.

RESULTS

Loss of Fps1 influences acetic acid uptake and resistance in yeast.

Accumulation of a high intracellular glycerol pool by osmostressed yeast cells reflects both increased glycerol synthesis and an increased capacity of the cell to retain this glycerol, rather than lose it to the culture medium. The increased glycerol retention is achieved by turgor-mediated closure of the plasma membrane aquaglyceroporin Fps1, a closure that prevents glycerol diffusion through this channel and therefore the glycerol loss from the cell (9, 11, 12, 22). Though the acetic acid response of yeast grown at slightly acid pH (pH 4.5) does not f.lux 4.75 Activaton Code increases in intracellular glycerol (19), we found that Fps1 was still a major factor in acetic acid resistance. With Fps1 loss, the cells were even more resistant to acetic acid than normal (compare wild-type and fps1Δ mutant cells in Fig. 1a). In addition, whereas Hog1 MAPK is normally essential for acetic acid resistance (19), this activity was rendered almost completely dispensable for this resistance by the loss of Fps1 (compare wild-type, hog1Δ, and fps1Δ single gene deletion mutant and fps1Δ hog1Δ double gene deletion mutant cells in Fig. 1a).

Open in a separate window

FIG. 1.

(a) Loss of Fps1 enhances acetate resistance and suppresses the acetate sensitivity generated by the loss of Hog1. Growth of wild-type (wt), fps1Δ and hog1Δ single mutant, and fps1Δ hog1Δ double mutant cells (a 1:10 dilution series grown f.lux 4.75 Activaton Code days, 30°C] on pH 4.5 YPD agar containing the indicated level of acetic acid) is shown. (b) Acetic acid accumulation by pH 4.5 and pH 6.8 YPD cultures of the strains in panel a, measured over the initial 40 min following the addition of 100 mM acetic acid. (c) A working model to explain the results in panels a and b. Entry of undissociated acetic acid into the cell is Fps1 facilitated, with the acid that enters the cell in this way then dissociating in the cytosol (where the pH is close to neutral) so as to generate an intracellular pool of the acetate anion. This acetate then activates Hog1, an activity that in turn downregulates the Fps1-mediated acid influx into the cell.

Fps1 mediates the diffusional entry of undissociated acetic acid to glucose-repressed yeast.

Before investigating further this apparent linkage between the requirement for Hog1 MAPK in acetic acid resistance and the presence of Fps1, we first had to establish whether the Fps1 aquaglyceroporin could facilitate the diffusion of acetic acid across the cell membrane. Acetic acid accumulation f.lux 4.75 Activaton Code measured in cells suddenly exposed to the highest acetic acid level that would enable the growth of glucose-repressed, wild-type cultures at pH 4.5 (100 mM), with this acid being labeled to low specific activity with ¹⁴C. The initial rate of acetic acid accumulation by these cells, suddenly exposed to such a high level of acetic acid, is essentially a measure of their acetic acid uptake (S. cerevisiae does not use acetic acid as a carbon source in the presence of high glucose levels). These measurements indicated a relatively slow equilibration of the intracellular and extracellular acetic acid pools (Fig. 1b). The yeast cell membrane is therefore not freely permeable to acetic acid (in contrast to what is f.lux 4.75 Activaton Code with more f.lux 4.75 Activaton Code carboxylic acids, compounds that equilibrate much more rapidly across this membrane [e.g., benzoic acid]) (10, 23). Importantly, the loss of Fps1 essentially eliminated acetic acid accumulation by these acid-challenged Corel WinDVD Pro Free Download (compare wild-type and fps1Δ mutant cells in Fig. 1b), f.lux 4.75 Activaton Code, revealing that the entry of this acid into glucose-repressed, wild-type yeast is mainly by passive diffusion through the Fps1 channel. When cultures were exposed to the same level of acetic acid (100 mM) but at pH 6.8, when the acetic acid (pK_a 4.75) in the medium will be almost completely dissociated, cellular accumulation of acetate was greatly reduced (compare pH 4.5 versus pH 6.8 cultures in Fig. 1b). We interpret this as the open Fps1 channel facilitating the transmembrane flux of only the uncharged, undissociated acetic acid (CH₃COOH) (Fig. 1c), not the acetate anion (CH₃COO−). F.lux 4.75 Activaton Code Fps1 pore is structurally similar to that of bacterial GlpF (5, 13). It is therefore too small to readily accommodate the hydrated acetate anion. Since Fps1 therefore facilitates a substantial acetic acid entry to cells only at low pH (Fig. 1b), all of the experiments described below on the interplay between acetic acid and Fps1 analyzed the effects of 100 mM acetic acid challenge in pH 4.5 cultures (a regimen hereafter termed “acetic acid stress”). At pH 6.8 considerably higher acetate levels, effectively a high osmostress generated by a high acetate salt concentration, are needed in order to achieve any comparable degree of growth inhibition (19).

Hog1 MAPK activation by acetic acid stress directs endocytosis and degradation of Fps1.

To determine how Hog1 MAPK might be downregulating the F.lux 4.75 Activaton Code entry of acetic acid into the cell, we initially measured whether Fps1 levels were affected by acetic acid stress. Western blot analysis of a functional cmyc-tagged Fps1 (Fps1-cmyc) (28) expressed as the sole form of Fps1 channel in pH 4.5 HOG1⁺ and hog1Δ cultures revealed that this Fps1-cmyc was being degraded when HOG1⁺, but not hog1Δ, cells were exposed to acetic acid (Fig. 2a). The Hog1 that is transiently activated by and which confers resistance to these conditions of acetic acid stress (19) (Fig. 1a) appeared therefore to be directing the destabilization of Fps1 (Fig. 2a). Importantly, f.lux 4.75 Activaton Code, no Fps1-cmyc loss could be observed when, instead of the 100 mM acetic acid addition, the same pH 4.5 cultures were challenged by different conditions of osmostress, irrespective of the presence or absence of Hog1 (the effects of a 1 M NaCl addition are shown in Fig. 2a), f.lux 4.75 Activaton Code. Furthermore, addition of 1 M NaCl 10 min prior to addition of 100 mM acetic acid also prevented the Fps1-cmyc degradation seen with the application of just the latter stress alone (data not shown). It is possible, therefore, that only the open-channel state of Fps1 is destabilized by an active Hog1, not the closed f.lux 4.75 Activaton Code that is rapidly adopted by this plasma membrane channel in cells exposed to osmostress (see Discussion).

Open in a separate window

FIG. 2.

(a) Measurements of Fps1-cmyc, expressed as the sole form of Fps1 channel f.lux 4.75 Activaton Code fps1Δ (wt) and fps1Δ hog1Δ (hog1Δ) mutant cells, at time points following the addition of either 100 mM acetic acid or 1 M NaCl. (b) Fps1-cmyc is degraded in unstressed cells in response to the active form of Hog1 (P-Hog1), the latter generated by galactose-inducible expression of the hyperactive PBS2^DD allele. (c) Forms of Fps1-cmyc that lack the amino-terminal or carboxy-terminal cytosolic domain of the channel (Fps1-ΔN-cmyc and Fps1-ΔC-cmyc) did not undergo the degradation in response to acetic acid stress shown for the full-length Fps1-cmyc in panel a. (d) Acetic acid sensitivity of BY4741 fps1Δ cells transformed, as indicated, with either empty YEplac195 vector, a plasmid for full-length Fps1 expression (YEpFPS1), or plasmids for expression of Fps1 forms that lack either the amino-terminal or the carboxy-terminal cytosolic domain (YEpfps1-ΔN and YEpfps1-ΔC). (e) Acetic acid sensitivity of a BY4743 (FPS1/FPS1) diploid f.lux 4.75 Activaton Code, as indicated, with either empty YEplac195 vector or plasmid YEpfps1-ΔN containing the gene for an unregulated Fps1. In panels d and e, cells were spotted in a 1:10 dilution series onto pH 4.5 DO plates lacking leucine and lacking or containing 100 mM acetic acid and then were grown for 3 days at 30°C.

The experiments in Fig. 2a indicated, therefore, that the downregulation of acetic acid influx into wild-type yeast is due to Hog1-dependent loss of the channel that mediates this influx (hog1Δ cells, where Fps1 does not degrade f.lux 4.75 Activaton Code. 2a], exhibit a higher acid accumulation [Fig. f.lux 4.75 Activaton Code. To obtain further evidence that it is indeed the activation of Hog1 that provides the Fps1 degradation signal we studied the effects of inducing, in the absence of applied stress, a hyperactive allele of the MAPK activator of Hog1, Pbs2 (Pbs2^DD) (24). Fps1-cmyc was rapidly destabilized in response to a GAL1 promoter-directed induction of this Pbs2^DD allele, with this destabilization of Fps1-cmyc by Pbs2^DD expression occurring in the absence of either acetic acid stress or osmotic stress (Fig. 2b).

Fps1 has cytosolic domains at its amino and carboxy termini, both of which are crucial for its regulation. Loss of either cytosolic domain generates a channel protein with constitutive, unregulated glycerol transport activity, whose in vivo expression causes an inability to retain glycerol and accumulate an osmolyte pool and therefore a sensitivity to hyperosmotic stress (9, 28-30). Fps1-cmyc forms lacking either of these cytosolic domains (Fps1-ΔN-cmyc and Fps1-ΔC-cmyc) were found not to degrade in response to acetic acid stress (Fig. 2c), their presence creating a sensitivity to this stress (Fig. 2d and e). Plasmids for expression of the wild-type Fps1 or an N-terminally truncated, unregulated Fps1 (YEpFPS1 and YEpfps1-Δ1) f.lux 4.75 Activaton Code were also transformed into the FPS1/FPS1 diploid strain BY4743. As expected for the acetate sensitivity with expression of an N-terminally truncated Fps1 corresponding to a gain of function (the presence of an unregulated, permanently open Fps1 channel), the capacity of the fps1-Δ1 allele to confer acetate sensitivity was genetically dominant (Fig. 2d).

Fps1-GFP undergoes Hog1-dependent endocytosis in response to acetic acid but not salt stress.

We next observed the fate of a functional Fps1-GFP fusion, f.lux 4.75 Activaton Code, expressed as the sole form of Fps1 in HOG1⁺ and hog1Δ cells. This Fps1-GFP was placed under MET25 promoter control so as to enable its expression to be switched off by addition of methionine 2 h prior to stress and therefore observations of the fate of the Fps1-GFP preexisting in the f.lux 4.75 Activaton Code at the time of the stress application. Unstressed cells showed a uniform Fps1-GFP distribution in the plasma membrane, irrespective of the presence or absence of Hog1 (Fig. 3a). Upon application of acetic acid stress, this Fps1-GFP was endocytosed to the vacuole in 80 to 90% of the HOG1⁺ cells examined (Fig. 3a). Simultaneously it was also degraded (Fig. 3c). In contrast, in the hog1Δ mutant subjected to an identical acetic acid stress, Fps1-GFP remained at the plasma membrane and intact (Fig. 3a and c). Both the Fps1-cmyc degradation (Fig. 2) and the Fps1-GFP endocytosis/degradation (Fig. 3a) in response to acetic acid stress are therefore Hog1-dependent events.

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FIG. 3.

(a and b) Visualization of Fps1-GFP expressed as the sole form of Fps1 channel in fps1Δ (wt) and fps1Δ hog1Δ (hog1Δ) mutant cells stressed for f.lux 4.75 Activaton Code, 20, f.lux 4.75 Activaton Code, or 60 min either with 100 mM acetic acid (a) (vacuoles revealed by FM4-64 staining) or 1 M NaCl (b). (c) An analysis of Fps1-GFP fusion integrity in these same cultures by Western blotting. The blots were probed using anti-GFP and anti-Sba1 antisera (the latter as a loading control). (d) Expressed as the sole Fps1 of HOG1⁺ cells, a nonphosphorylatable T231A S537A double mutant Fps1-GFP was correctly plasma membrane localized but was not endocytosed under the conditions of acetate stress where the wild-type Fps1-GFP is endocytosed to the vacuole (a). In contrast, very little of a phosphomimic T231E S537D double mutant Fps1-GFP was plasma membrane localized, even in the absence of stress.

Fps1 undergoes Hog1-dependent phosphorylation in response to acetic acid stress.

The next question we addressed is whether Hog1 directly binds to and phosphorylates Fps1 or whether its action in targetting this channel for degradation is indirect, for example, f.lux 4.75 Activaton Code, mediated through an intermediary protein kinase. Lack of the Fps1 degradation in response to acetic acid stress generates a sensitivity to this stress (hog1Δ cells) (Fig. 1a and 2a), but our recent screen for such sensitivity among the f.lux 4.75 Activaton Code of strains lacking nonessential yeast protein kinases uncovered only the kinases of the HOG signaling cascade as being important for acetic acid resistance (19).

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FIG, f.lux 4.75 Activaton Code. 4.

(a) Brief acetic acid stress leads to in vivo phosphorylation of Fps1-cmyc on both threonine (p-T) and serine (p-S), f.lux 4.75 Activaton Code, phosphorylations that are abolished by the lack of Hog1 or the expression of T231A S537A double mutant Fps1-cmyc. (b) Immunoprecipitated (IP) Fps1-cmyc coprecipitates Hog1. (c)T231A S537A double mutant forms of Fps1-cmyc and Fps1-GFP are refractory to acetate-induced degradation under conditions where the wild-type forms become degraded (Fig. 2d and 3c). (d) The acetate sensitivity generated by MET25 promoter-regulated induction of a functional wild-type Fps1-GFP fusion (FPS1), expressed as the sole Fps1 channel in fps1Δ and fps1Δ hog1Δ mutant cells, is made more severe by T231A S537A double mutation of this Fps1-GFP, whereas the induction of a phosphomimic (T231E S537D) Fps1-GFP has no influence over acetate resistance, f.lux 4.75 Activaton Code. (e) Expression of a T231A S537A double mutant Fps1-cmyc as the sole Fps1 of HOG1⁺ cells leads to enhanced acetate accumulation (measured as for Fig. 1c, except that cultures were maintained on pH 4.5 DO medium lacking uracil).

We mutated f.lux 4.75 Activaton Code T231 and S537 in the Fps1-GFP fusion to either nonphosphorylatable alanine residues (Fps1^{T231A 537A}-GFP) or phosphomimic amino acid residues (Fps1^{T231E 537D}-GFP). The Fps1^{T231A 537A}-GFP fusion was both localized correctly at the plasma membrane (Fig. 3d) and functional as an osmogated glycerol channel (data not shown). Despite this, when expressed as the sole Fps1 channel of HOG1⁺ cells, this Fps1^{T231A 537A}-GFP remained at the plasma membrane and was stable under conditions of acetic acid stress where the wild-type Fps1-GFP fusion was endocytosed to the vacuole and degraded (Fig. 3d). In contrast, the mutation of T231 and S537 in the Fps1-GFP fusion to phosphomimic residues resulted in a substantial reduction of the GFP signal at the plasma membrane, even in unstressed cells (Fps1^{T231E 537D}-GFP) (Fig. 3d), f.lux 4.75 Activaton Code, a result consistent with phosphorylation of Fps1 at T231 and/or S537 in such cells normally providing a signal for channel endocytosis.

The T231A S537A double mutant Fps1-cmyc (Fps1^{T231A 537A}−cmyc), expressed as the sole Fps1 channel in HOG1⁺ cells, was found to f.lux 4.75 Activaton Code the acetic acid-induced in vivo phosphorylation (Fig. 4a) and in vivo degradation (Fig. 4c) exhibited by the wild-type Fps1-cmyc. Furthermore, the expression of T231A S537A double mutant Fps1 forms as the sole F.lux 4.75 Activaton Code channel of fps1Δ HOG1⁺ or fps1Δ hog1Δ deletion strains generated (like the loss of Hog1 MAPK in cells with normal Fps1 [Fig. 1a f.lux 4.75 Activaton Code b] ant download manager pro registration key Activators Patch hypersensitivity to acetic acid (Fig. 4d) and a higher-than-normal acetic acid accumulation (Fig. 4e), results that are consistent with the wild-type Fps1-GFP being endocytosed but the mutant Fps1^{T231A 537A}-GFP remaining at the plasma membrane during acid stress (Fig. 3a and d). Conversely, expression of the phosphomimic (T231E S537D) double mutant Fps1-GFP (a form substantially not plasma membrane localized even in unstressed cells [Fig. 3d]) had no discernible effect on the levels of acetate resistance displayed by the fps1Δ HOG1⁺ and fps1Δ hog1Δ deletion strains (Fig. 4d).

Acetic acid induces a transient Fps1 ubiquitination that is Hog1 dependent.

Ubiquitination of cell surface proteins is generally a key step in triggering their internalization by endocytosis (4, 35). In yeast exposed to a brief acetic acid stress, f.lux 4.75 Activaton Code, ubiquitinated forms of Fps1-cmyc were readily detectable, f.lux 4.75 Activaton Code, with their appearance being abolished by either the loss of Hog1 or the expression of the T231A S537A double mutant Fps1-cmyc (Fig. 5a). Hog1-dependent phosphorylation of Fps1 appears therefore to be the signal for this aquaglyceroporin to become ubiquitinated prior to its endocytosis and degradation in the vacuole (Fig. 6d).

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FIG. 5.

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FIG. 6.

doa4Δ and end3Δ, two mutations causing a general loss of endocytosis of cell surface proteins, also caused Fps1-GFP to remain stable and plasma membrane localized under f.lux 4.75 Activaton Code conditions of acetic acid stress where it is normally endocytosed (Fig. 5b and c). In addition, these mutants displayed an acetic acid sensitivity phenotype (Fig. 5d). The doa4Δ and end3Δ mutants are, respectively, defective in Doa4, a ubiquitin-protein hydrolase important in recycling ubiquitin from proteolytic substrates destined for degradation by the 26S proteasome or the vacuole (3, 27), and End3, a component of a multiprotein complex required for the internalization step of endocytosis (31).

Hog1 binds the N-terminal regulatory domain of Fps1, with the active form of f.lux 4.75 Activaton Code MAPK phosphorylating threonine 231 of this domain, both in vivo and in vitro.

The experiments described above reveal that the active Hog1 MAPK generated by acetic acid stress directs phosphorylation, ubiquitination, and endocytosis of Fps1, thereby removing from the plasma membrane the major route for diffusional entry of acetic acid into the cell (Fig. 1 and 6). Removal of this channel is important for resistance to toxic levels of acetic acid, since acid sensitivity is apparent with diverse defects that abolish this loss of Fps1. Thus, defective Fps1 endocytosis and acid sensitivity are apparent with the loss of Hog1 (Fig. 1a), f.lux 4.75 Activaton Code, with the loss of the amino- or carboxy-terminal cytosolic domain of Fps1 (Fig. 2c-e), with T231A S537A double mutation of Fps1 (Fig. 3d and 4d), or with mutations causing a general loss of endocytosis of cell surface proteins (doa4Δ and end3Δ) (Fig. 5b to d). Figure 4a reveals that the in vivo Hog1-dependent phosphorylation of Fps1 involves two residues (T231 and S537), both of which correspond to SP/TP motifs such as are recognized by the MAPKs.

While these results are fully consistent with the signal for the endocytosis of Fps1 being a direct Hog1 phosphorylation of this channel protein, f.lux 4.75 Activaton Code sought further evidence that Hog1 interacts with, and phosphorylates, Fps1. Finding that appreciable amounts of Hog1 coprecipitated with the Fps1-cmyc immunoprecipitated from f.lux 4.75 Activaton Code cell extracts (Fig. 4b), we next used two-hybrid analysis to probe for an in vivo Hog1 interaction with the amino- or carboxy-terminal hydrophilic region of Fps1 (amino acids 1 to 255 and 531 to 669, respectively). These are regulatory domains exposed on the cytosolic face of the cell membrane in the open-channel state of this aquaglyceroporin (9, 28). Interaction of Fps1(1-255) and Fps1(531-669), each fused to the Gal4 BD, was tested with fusions of the Gal4 AD to the native Hog1 MAPK, a nonactivatable (T180AY182F double mutant) Hog1 (NP), and a f.lux 4.75 Activaton Code (K52R) Hog1. The Fps1(1-255)-BD “bait,” but not Fps1(531-669)-BD, exhibited strong two hybrid interaction with the wild-type AD-Hog1, as well as with both the NP and K52R mutant forms of this AD-Hog1 “prey” fusion (Fig. 5a).

Using an HA epitope-tagged Hog1 (HA-Hog1) immunoprecipitated from extracts of unstressed or briefly acetic acid-stressed yeast, we investigated whether Hog1 would directly phosphorylate the amino- or carboxy-terminal hydrophilic regions of Fps1 in vitro. As substrates, we added Fps1(1-255)-His₆ (either the wild-type or T231A mutant form) and Fps1(531-669)-His₆, which were previously expressed in and then purified from fps1Δhog1Δ mutant cells. HA-Hog1 phosphorylated the Fps1(1-255)-His₆ fragment (Fig. 6c) but not Fps1(531-669)-His₆ (not shown). Furthermore, in vitro phosphorylation of the former fragment was much more efficient using HA-Hog1 purified from briefly acetate-stressed cells (consistent with the greater pool of active Hog1 MAPK in these cells [19] [Fig. 6c]). The T231A mutation in Fps1(1-255)-His₆ abolished this in vitro phosphorylation by HA-Hog1 (Fig. 6c) but not Hog1 binding to this fragment (Fig. 6b). In vivo, the Hog1-dependent threonine phosphorylation of the full-length Fps1-cmyc in response to acetic acid stress was similarly abolished by the T231A S537A double mutation of this Fps1-cmyc (Fig. 4a). Therefore, Hog1 binds the region from amino acid 1 to 255 of Fps1, phosphorylating this region at T231 (Fig, f.lux 4.75 Activaton Code. 4a and 6c). Thorsen et al. have also recently presented independent evidence for Fps1 being regulated by a Hog1-dependent phosphorylation of T231, though under a different stress condition (arsenite, f.lux 4.75 Activaton Code, not acetate, stress) (33) f.lux 4.75 Activaton Code Discussion).

DISCUSSION

In this study we show that acetic acid enters glucose-repressed yeast cells primarily by facilitated diffusion of the undissociated acid through the Fps1 aquaglyceroporin channel (Fig. 1). When cells are challenged with inhibitory concentrations of acetic acid, f.lux 4.75 Activaton Code, there is a transient activation of Hog1 (19). This MAPK then directly phosphorylates Fps1 on T231 and also probably on S537 (Fig. 4a and 6), a phosphorylation that is the signal for this channel to be ubiquitinated and endocytosed to the vacuole. Fps1 is degraded even when Hog1 is activated in the absence of stress (Fig, f.lux 4.75 Activaton Code. 2b). Double T231A S537A mutation of Fps1 abolishes this phosphorylation by Hog1, as well as the Hog1-dependent ubiquitination and endocytosis (Fig. 3d, 4a, and 5a), generating a hypersensitivity to acetic acid (Fig. 4d) that appears to reflect a higher-than-normal acid entry into cells (Fig. 4e). In contrast, a phosphomimic mutant Fps1^{T231E 537D}-GFP fusion is substantially delocalized from the plasma membrane, even in the absence of stress (Fig. 3d), and cannot confer Fps1 function (Fig. 4d and data not shown).

This removal of Fps1 from the plasma membrane appears to be essential for downregulating the acetic acid influx to the cell (Fig. 1b and 4e), since the acetic acid stress alone appears not to cause the complete closure of the Fps1 channel (Fps1-dependent acetic acid uptake is not immediately arrested in stressed wild-type cells; also, it is enhanced should this channel remain in the plasma membrane, as occurs in the hog1Δ mutant [Fig. 1b and 3a] or with the expression of the T231A S537A double mutant Fps1 [Fig. 3d and 4e]). Indeed, targeting Fps1 for degradation may be the major requirement for an active Hog1 in acetic acid resistance (19), since, remarkably, Hog1 is largely dispensable for this resistance when the cells lack Fps1 (Fig. 1a). Total f.lux 4.75 Activaton Code of Fps1 also creates an acetate-resistant phenotype (the fps1Δ mutant; Fig. 1a), probably as this loss Ashampoo Movie Studio Pro 3.0.0 Crack product key the major source of the acetic acid flux into the cell.

Activation of HOG MAPK pathway signaling is apparent f.lux 4.75 Activaton Code with osmostress (9, 12, 22) and with acetic acid stress (19), but Fps1 is destabilized only with the latter and not with the former condition of stress (Fig. 2a). According to current models, Fps1 refolds to a closed-channel conformation within seconds in cells shifted to high osmolarity, a Hog1-independent response to an altered cell turgor (9, 12, 22). With osmostress Fps1-cmyc and Fps1-GFP were not destabilized in HOG1⁺ cells (Fig. 2a and 3b and c), their stability under these conditions contrasting with their destabilization when the same HOG1⁺ transformants were exposed, instead, to acetic acid (Fig. 2a and 3a and c). Fps1 is therefore either unstable or stable under different conditions of HOG pathway-activating stress. Measurements of the acetic acid accumulation by the hog1Δ mutant (Fig. 1b) indicate that should this channel remain in the plasma membrane (Fig. 2a and 3a), it does not close completely in response to acetic acid stress. It appears, therefore, that an active Hog1 MAPK may target only the open-channel state of Fps1 for degradation, not the closed-channel conformation that is rapidly adopted by Fps1 in cells shifted to high osmolarity.

The Fps1 channel is also the route whereby toxic metalloids, such as arsenite and antimonite, enter yeast (36). Recently, Hog1 was shown to mediate a protective response to these metalloids, acting to downregulate their entry into the cell through this channel (33). There are some striking parallels with this metalloid response and the acetic acid response that we have been studying (notably, Hog1-dependent downregulation of the entry of the xenobiotic compound to the cell via Fps1 and also the requirement for the T231 residue of Fps1 in this downregulation). There appears, though, f.lux 4.75 Activaton Code, to be an important difference between the response to arsenite and the acetic acid response that we describe here. Unfortunately, Thorsen et al. did not investigate the in vivo localization of Fps1 in their study, but it is evident from their data that Fps1 is not becoming degraded in arsenite-treated cells but appears instead to be adopting a closed-channel conformation in response to the arsenite-triggered, Hog1-dependent phosphorylation (33). High intracellular levels of arsenite may be strongly inhibitory to the events of endocytosis that we observe. It is also possible that the Hog1 phosphorylation of Fps1 in response to acetic acid (Fig. 4a) generates closure of the Fps1 channel but that, because these same phosphorylations also target the channel for endocytosis, it is the latter events of endocytosis that are observed as the dominant phenotype in the case of our acetic acid-stressed cells.

Furthermore, our results indicate that Hog1 is bound constitutively to the amino-terminal cytosolic domain of Fps1 (Fig. 6), f.lux 4.75 Activaton Code. This domain is thought to “dip” into the membrane during the turgor-mediated channel closure (9, 22), whereupon Hog1 may dissociate (an aspect not investigated here). Our data reveal that Fps1 engages in an association with Hog1 irrespective of the activation state or the activity of this MAPK (Fig. 6). Hog1 is thereby “poised” to achieve almost instant Fps1 phosphorylation, and thereby an altered stability (and possibly conformation) of this aquaglyceroporin, in response to the activation of HOG pathway signaling.

Acknowledgments

We are indebted to Francesc Posas, Stefan Hohmann, f.lux 4.75 Activaton Code, David Engelberg, and Frank Cooke for plasmids and strains; to Ewald Hettema for comments on the manuscript; to Barry Panaretou for the use of his King's College London laboratory; and to Sally Thomas for technical assistance.

This work was supported by BBSRC grant BB/E003311/1.

Footnotes

^▿Published ahead of print on 9 July 2007.

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Open Access
Peer-reviewed
Xing-Ding Zhang ,
Lin Qi ,
Jun-Chao Wu,
Zheng-Hong Qin
Xing-Ding Zhang,
Lin Qi,
Jun-Chao Wu,
Zheng-Hong Qin
x
Abstract
We have previously reported that the mitochondria inhibitor 3-nitropropionic acid (3-NP), induces the expression of DNA damage-regulated autophagy modulator1 (DRAM1) and activation of autophagy in rat striatum. Although the role of DRAM1 in autophagy has been previously characterized, the detailed mechanism by which DRAM1 regulates autophagy activity has not been fully understood. The present study investigated the role of DRAM1 in regulating autophagy flux. In A549 cells expressing wilt-type TP53, f.lux 4.75 Activaton Code increased the protein levels of DRAM1 and LC3-II, whereas decreased the levels of SQSTM1 (sequestosome 1). The increase in LC3-II and decrease in SQSTM1 were blocked by the autophagy inhibitor 3-methyl-adenine. Lack of TP53 or knock-down of TP53 all picture finder keygen Free Activators cells impaired the induction of DRAM1. Knock-down of DRAM1 f.lux 4.75 Activaton Code siRNA significantly reduced 3-NP-induced upregulation of LC3-II and downregulation of SQSTM1, indicating DRAM1 contributes to autophagy amibroker add-ons Activators Patch. Knock-down of DRAM1 robustly decreased rate of disappearance of induced autophagosomes, increased RFP-LC3 fluorescence dots and decreased the decline of LC3-II after withdraw of rapamycin, indicating DRAM1 promotes autophagy flux. DRAM1 siRNA inhibited lysosomal V-ATPase and acidification of lysosomes. As a result, DRAM1 siRNA reduced activation of lysosomal cathepsin D. Similar to DRAM1 siRNA, lysosomal inhibitors E64d and f.lux 4.75 Activaton Code also inhibited clearance of autophagosomes and activation of lysosomal cathapsin D after 3-NP treatment. These data suggest that DRAM1 plays important roles in autophagy activation induced by mitochondria dysfunction. DRAM1 affects autophagy through argument of lysosomal acidification, fusion of lysosomes with autophagosomes and clearance of autophagosomes.
Citation: Zhang X-D, Qi L, Wu J-C, Qin Z-H (2013) DRAM1 Regulates Autophagy Flux through Lysosomes. PLoS ONE 8(5): e63245. https://doi.org/10.1371/journal.pone.0063245
Editor: Arun Rishi, Wayne State University, United States of America
Received: November 13, 2012; Accepted: March 29, 2013; Published: May 17, 2013
Copyright: © 2013 Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, f.lux 4.75 Activaton Code, and reproduction in any medium, f.lux 4.75 Activaton Code, provided the original author and source are credited.
Funding: This work was partially supported by the National Natural Science Foundation of China (No 30930035), f.lux 4.75 Activaton Code, by the National Basic Science Key Project (973 project, CB510003), by the Priority Academic Program development of Jiangsu Higher Education Institutes, and by Graduate Training Innovation Project of Jiangsu Province (CX09B_042Z). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
3-nitropropionic acid (3-NP), a suicide inhibitor of the mitochondrial respiratory enzyme succinate dehydrogenase (SDH) [1], induces striatal cell death in vivo and in vitro [2]–[4]. When intoxicated in vivo, 3-NP produces symptoms and striatal neuronal loss in human brains replicating neuropathology of Huntington’s disease [4], [5]. We previously reported that intrastriatal administration of 3-NP induced TP53-dependent autpophagy activation and apoptosis. The TP53 specific inhibitor pifithrin-α (PFT-α) blocked induction of autophagic proteins including DNA Damage Regulated Autophagy Modulator1 (DRAM1), f.lux 4.75 Activaton Code, LC3-II and beclin1 f.lux 4.75 Activaton Code apoptotic proteins including TP53-upregulated modulator of apoptosis (PUMA) and BAX. Both pharmacological inhibitors of autophagy and caspases effectively inhibited 3-NP-induced cell death [6], [7].
DRAM1, a novel TP53 target gene, is an evolutionarily conserved lysosomal protein and has been reported to play an essential role in TP53-dependent autophagy activation and apoptosis [8]. The mechanism by which DRAM1 promotes autophagy is not clear. It is proposed that DRAM1 may exert its effects on autophagy through lysosomes, given the fact as a lysosomal membrane protein. Uncovering the molecular mechanism by which DRAM1 regulates autophagy would provide a better understanding of the role of TP53 signaling pathway in the regulation of cell death and survival.
Autophagy is a pathway delivering cytoplasmic components to lysosomes for degradation [9]–[13]. Macroautophagy involves the sequestration of a region of the cytoplasm in a double-membrane structure to form a unique vesicle called the autophagosome. Acidification of lysosomes is crucial for activation of cathepsins, fusion of lysosomes and autophagosomes and effective degradation of autophagic substrates. However, these late digestive steps of autophagy remain largely uncharacterized.
Lysosomes are cytoplasmic organelles that contain several enzymes mostly belonging to the hydrolases [14]. Internal pH of lysosomal is characteristically acidic and it is maintained around pH 4.5 by a proton pump, that transport H⁺ ions into lysosomes [15], [16]. Many autophagy inhibitors including the vinca alkaloids (e.g., f.lux 4.75 Activaton Code, vinblastine) and microtubule poisons that inhibit fusion of autophagosomes with lysosomes, inhibitors of lysosomal enzymes (e.g., leupeptin, pepstatin A and E64d), and compounds that elevate lysosomal pH (e.g., inhibitors of vacuolar-type ATPases, such as bafilomycin A1 and weak base amines f.lux 4.75 Activaton Code ammonia, methyl- or propylamine, chloroquine, f.lux 4.75 Activaton Code, and Neutral Red, some of which slow down fusion), act at the fusion and lysosomal degradation f.lux 4.75 Activaton Code [17]. Lysosomal enzymes also play a role in activation of certain types of caspases and therefore, are involved in apoptosis [18]. Inhibition of lysosomes or lysosomal enzymes protects neurons against excitotoxicity and ischemic insults [19], [20]. Thus, it is of particularly interest to investigate if DRAM1 modulates autophagy through influencing lysosomal functions.
In this study, we report that 3-NP induced DRAM1-dependent stimulation of autophagy in A549 cell lines. DRAM1 promotes autophagy flux by enhancing f.lux 4.75 Activaton Code acidification.
Materials and Methods
Cell Lines and Reagents
A549 (TP53^+/+) and H1299 (TP53^−/−) and Hela cell lines were purchased from Shanghai Institute of Biochemistry and Cell Biology in China, and were grown at 37°C in 5% CO₂ in RPMI supplemented with 2 mmol/L L-glutamine and 10% FCS. Primary mouse embryonic fibroblasts (MEFs) were derived from p53 wt and p53 KO sibling embryos, and maintained with DMEM supplemented with 10% FCS and antibiotics. 3-NP (N5636), 3-MA (M9281), carbonyl cyanide m-chlorophenylhydrazone (CCCP, C2759), ATP (A6559), chloroquine (C6628), E-64d (E8640) and Z-Vad-FMK (V116) were all purchased from Sigma-Aldrich (Saint Louis, MO, F.lux 4.75 Activaton Code. LysoTracker Red (L7528) and LysoSentor (L7533) were purchased from F.lux 4.75 Activaton Code Probes (Shanghai, China). All cell culture reagents were purchased from Gibco (Gaithersburg, MD, USA) unless otherwise noted.
Expression of GFP-LC3 and DRAM1-pEGFP
The activation of autophagy was detected following transfection of cells with GFP-LC3 and mRFP-GFP-LC3 expression plasmids (kindly provided by Dr. T. Yoshimori, National Institute of Genetics, F.lux 4.75 Activaton Code. The presence of several intense Wondershare Dr.Fone Full Toolkit Registration key dots in cells is indicative of the accumulation of autophagosomes. Transfection of cells with expression plasmids was performed using F.lux 4.75 Activaton Code 2000 (Invitrogen, 11668-019, Shanghai, China). For each condition, the Connectify Hotspot 2021 Crack + License Key Free Download of GFP-LC3 dots per cell was determined with a fluorescence microscopy for at least 100 GFP-LC3-positive cells.
PcDNA4-DRAM1-His was generated by PCR f.lux 4.75 Activaton Code the I.M.A.G.E. clone for DRAM1 (Clone ID: NM_018370) with: CCCAAGCTTATGCTGTGCTTCCTGAGGGGAATG (forward) and CCGCTCGAGTCAAATATCACCATTGATTTCTGTG (reverse), and subsequently digested with BamH I and Xho I and cloned in to the BamH I and Xho I sites of pcDNA4/HisA (Invitrogen Carlsbad, CA, USA). pEGFP-N1-DRAM1 was generated through PCR primer: ATAGAATTCATGCTGTGCTTCCTGAGGGGA (forward) and CCGGGATCCTAATATCACCATTGATTTCTGTG(reverse), f.lux 4.75 Activaton Code, and products were T-A cloned in pMDTM19-T Vectors (Takara, D102A, Dalian, China) and digested with EcoR I and BamH I and cloned into pEGFP-N1 (Clonetech, D102A, Mountain View, CA, USA). Transfection of cells with expression plasmids was performed using Lipofectamine 2000 (Invitrogen, 11668-019, Shanghai, China).
Knock-down of TP53 and DRAM1
Small interfering RNAs (siRNA) targeting the following mRNA: TP53, AAGACUCCAGUGGUAAUCUAC; DRAM1, (1) CCACGATGTATACAAGATA and (2) CCACAGAAATCAATGGTGA. Negative siRNA TAAGGCTATGAAGAGATAC, were synthesized by GenePharma (Shanghai, China). The siRNA oligos used to target DRAM1 genes were previously validated and described in the following articles [8], [21], [22]. For transfection, cells were plated in 9-cm dishes at 30% confluence, and siRNA duplexes (200 nM) were introduced into the cells using Lipofectamine 2000 (Invitrogen, 11668-019, Shanghai, China) according to the manufacturer’s recommendations.
LC3 Immunofluorescence Assay
For immunofluorescence microscopic examination, cells were plated on 12-mm Poly-L-Lysine-coated cover slips and minitool power data recovery 8.5 licence key Activators Patch f.lux 4.75 Activaton Code 24 h, then cells were treated with siRNA and drugs, f.lux 4.75 Activaton Code. Cells were washed f.lux 4.75 Activaton Code PBS, fixed with 4% paraformaldehyde in PBS at 4°C for 10 min, and then washed again with PBS. The cells were permeabilized with 0.25% Triton X-100, and were then blocked with 10% normal goat serum (NGS) for f.lux 4.75 Activaton Code min. Primary antibodies: a rabbit polyclonal antibody against LC-3 (Abgent, AJ1456c, Suzhou, China), a goat polyclonal antibody against cathepsin D (Santa Cruz, sc-6488, Santa Cruz, CA, f.lux 4.75 Activaton Code, USA) and a rabbit polyclonal antibody against LAMP2 (Abcam, ab37024, Cambridge, MA, USA) diluted in PBS were added to the cells and left for overnight at 4°C. The cover f.lux 4.75 Activaton Code were washed three times before incubation with secondary antibodies using the same procedure as for the primary antibodies, f.lux 4.75 Activaton Code. The cover slips were mounted on slides with mounting medium (Sigma-Aldrich, F4680, Saint F.lux 4.75 Activaton Code, MO, USA) and were examined with a laser scanning confocal microscopy (Nikon, C1S1, Tokyo, Japan).
The pattern of distribution of exogenously expressed GFP-LC3 in A549 cells was observed with fluorescent microscopy. GFP-LC3 dot formation was quantified by counting 500 GFP-LC3-positive cells and expressed as the ratio of the number of cells with at least 5 GFP-LC3 dots and the number of GFP-LC3-positive cells. The assays were independently performed by two investigators in a blinded manner and similar results were obtained.
Western Blot Analysis
Western blot analysis was performed as scribed previously [23]. Cells were harvested and rinsed twice with ice-cooled PBS and homogenized in a buffer containing 10 mmol/L Tris-HCl (pH 7.4), 150 mmol/L NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS, 5 mol/L edetic acid, 1 mmol/L PMSF, 0.28 U/L aprotinin, 50 mg/L leupeptin, 1 mmol/L benzamidine, 7 mg/L pepstain A. Protein concentration was determined using the BCA kit. Thirty micrograms of protein from each sample was subjected to electrophoresis on 10–12% SDS-PAGE gel using a constant current. Proteins were transferred to nitrocellulose membranes and incubated with the Tris-buffered saline containing 0.2% Tween-20 (TBST) and 3% non-fat dry milk for 3 h in the presence of one of the following antibodies: a rabbit polyclonal antibody against LC-3 (Abgent, AJ1456c, San F.lux 4.75 Activaton Code, CA, USA), a mouse monoclonal antibody against TP53 (Cell Signaling Technology, 2524S, Boston, MA, USA), a mouse monoclonal antibody against β-actin (Santa Cruz, f.lux 4.75 Activaton Code, sc-58669), a goat polyclonal antibody against cathepsin D (Santa Cruz, sc-6488), rabbit polyclonal antibodies against DRAM1 (Stressgen, 905-738-100, Farmingdale, f.lux 4.75 Activaton Code, NY, USA), a rabbit polyclonal antibodies against SQSTM1 (Enzo Life Sciences, PW9860, Farmingdale, NY, USA),Membranes were washed and incubated with horseradish peroxidase-conjugated secondary antibodies in TBST containing 3% non-fat dry milk for 1 h. Immunoreactivity was detected with enhanced chemoluminescent autoradiography (ECL kit, Amersham, RPN2232, Piscataway, NJ, USA) according to the manufacturer’s instructions. The levels of protein expression were quantitatively analyzed with SigmaScan Pro 5. The results were normalized to mobaxterm 12.4 crack Free Activators control β-actin (Santa Cruz, sc-58669). DRAM1 peptide (Acris Antibodies, AP30304CP-N, San Diego, CA, USA) was used for evaluating the f.lux 4.75 Activaton Code of DRAM1 antibody. Pre-incubation of DRAM1 antibody with control peptide (1 µg control peptide/1 µL DRAM1 antibody) abolished binding activity of DRAM1 antibody (Figure S2).
Determination of Lysosomal pH
For lysosomal pH estimation, A549 and Hela cells were seeded on circular glass cover slips and grown to conﬂuence in Dulbecco’s modified Eagle’s medium (DMEM) with 10% fetal bovine serum (FBS; Wisent, 080–150) at 37°C, 5% CO². Lysosomes were loaded overnight with 70000 MW FITC-dextran (Sigma-Aldrich, 53471), f.lux 4.75 Activaton Code. and 0.5 mg/mL dextran-coupled Oregon Green 488 (Invitrogen-Molecular Probes, D-7173, Grand Island, NY, USA) in DMEM supplemented with 10% FBS, f.lux 4.75 Activaton Code, chased for 2 h at 37°C with 5% CO2 in DMEM (10% FBS) to allow complete transfer of dextrans to lysosomes, and washed to remove residual dextran. Non-attached cells were removed by rinsing with PBS and the cover slips were immediately placed in a f.lux 4.75 Activaton Code filled with growth medium or PBS and pH was estimated from excitation ratio measurements as described previously [24]. The fluorescence emitted was recorded at two excitation wavelengths (440/490 nm for Oregon Green 488) using the largest excitation and emission slits by a scanning multiwell spectrophotometer (Ultra Micro- plate Reader; BIO-TEK Instruments, ELx800, Winooski, VT, USA). The pH values were derived from the linear standard curve generated via each fluorescent dextran in phosphate/citrate buffers of different pH between 3.5 and 7.5. The experiment was repeated six times.
Spectrophotometric Measurement of H⁺ Transport
FITC-dextran loaded A549 and Hela cells were prepared as described above. After washing in PBS, cells were resuspended (10⁸ cells in 2 ml) in homogenization buffer (0.25 M sucrose, 2 mM EDTA, and 10 mM Hepes [pH 7.4]) and homogenized in a tight-fitting glass Dounce homogenizer. The homogenate was centrifuged (800 g, 10 min) to remove unbroken cells and the nuclei. The supernatant was centrifuged (6800 g, 10 min) to remove the large organelle such as mitochondrial. The supernatant was centrifuged (25000 g, 10 min) to obtain the light organelle including lysosomes. The precipitation layered over 10 ml of a 27% Percoll (Pharmacia Inc, 17-0891-01, New York, NY, USA) solution in homogenization buffer, underlayered with 0.5 ml of a 2.5 M sucrose solution. Centrifugation was done in a SW41Ti rotor (Beckman Instruments Inc, Brea, CA, USA) for 1.5 h at 35000 g. The layer of crude lysosomes of about 1.5 ml was collected at the bottom and then was centrifuged (100000 g, 60 min) to remove the other light organelle including mitochondrial at the bottom of the tube. Lysosomal fractions were equilibrated for up to 1 h in 125 mM KCl, 1 mM EDTA, and 20 mM Hepes (pH 7.5). Fluorescence was recorded continuously with excitation at 490 nm and emission at 520 nm. Upon addition of ATP (Sigma-Aldrich, f.lux 4.75 Activaton Code, A6559, Saint Louis, MO, USA), a progressive decrease in fluorescence intensity was observed, indicative of intralysosomal acidification [25]. As expected, the pH gradients in both samples were collapsed by the addition of the bafilomycin A1 (1 µM) (Sigma-Aldrich, B1793). The solvents alone had no effect on lysosomal pH. The reagents used and their final concentrations were: ATP (K⁺ salt, pH 7.5, 5 mM), bafilomycin A1 (1 µM).
Statistical Analysis
Statistical analysis was carried out by one-way analysis of variance (ANOVA) followed by Dunnett t-test or multiple means comparisons by Tukey’s test. Differences were considered significant when p<0.05.
Results
3-NP Induces Autophagy Activation
The present study examined if autophagic and apoptotic pathways are activated in A549 cells after 3-NP treatment. The results showed that 3-NP-induced a significant increase in the protein levels of DRAM1 from 3 to 72 h, with a peak induction at 24 h after 3-NP treatment (Figure 1A). The specificity of DRAM1 antibody was checked with Western blot analysis and immunofluorescence assay using DRAM1 control peptide (Figure S2). To further test if mitochondria respiration failure triggers DRAM1 expression, we used CCCP to uncouple mitochondria oxidation and phosphorylation, the results showed that CCCP significantly increased the DRAM1 protein levels (Figure 1B). LC3 is a mammalian homologue of yeast Atg8p and LC3-II is required for the formation of autophagosomes [26]. As shown in Fig. 1C, 3-NP induced a time-dependent increase in GFP-LC3 in A549 cells, and LC3-positive vesicular profiles of sizes 0.5–2.0 µm were significantly more numerous in 3-NP-treated cells 48 h after treatment (Figure 1C and 1D). To provide biochemical evidence of autophagy activation, the time-course of 3-NP-induced changes in LC3-II in A549 cells was determined 24 to 72 h after 3-NP (500 µM) treatment. The expression of LC3-II significantly increased 24 h after 3-NP treatment (Figure 2A). As an additional assessment of autophagy activity, the degradation of SQSTM1 (sequestosome 1), an autophagy substrate, was determined [27]. The present results showed that the protein level of SQSTM1 decreased 24–72 h after 3-NP treatment (Figure 2A). As a confirmation of autophagy activation, the present study demonstrated that the elevation of LC3- II and the decline of SQSTM1 were blocked by the autophagy inhibitor 3-methyl-adenine (Figure 2B).
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Figure 1. 3-NP activated autophagy.
A549 cells were treated with 3-NP (500 µM) and harvested 24, 48 and 72 h later. (A) Immunoblot analysis of DRAM1 levels in A549 cells under conditions of: no treatment (Ctrl) and 3, 6, 12, 24, 48 and 72 h after 3-NP. (B) Immunoblot analysis of DRAM1 levels in A549 cells under conditions of: no treatment (Ctrl) and 12.5µM and 25 µM of CCCP treatment for 4 h. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (3-NP group vs. control group). (C) Representative images of GFP-LC3 fluorescence in cells transfected with GFP-LC3 plasmid 24, 48 and 72 h after 3-NP (500 µM), f.lux 4.75 Activaton Code. F.lux 4.75 Activaton Code the nucleus. Thin arrows: GFP-LC3 dots. The scale bar represents 10 µm. (D) Quantitative analysis of the number of GFP-LC3 puncta. Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (3-NP group vs. control group).
https://doi.org/10.1371/journal.pone.0063245.g001
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Figure f.lux 4.75 Activaton Code. Autophagy was induced by 3-NP and blocked by 3-MA.
(A) Immunoblot analysis of LC3 and SQSTM1 levels in A549 cells under conditions of: no treatment (Ctrl) and 24, 48 and 72 h after 3-NP. Protein extracts were subjected to SDS-PAGE and immunoblotting. Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. (B) Immunoblot analysis of LC3 and SQSTM1 levels in cells under conditions of: no treatment (Cont), 3-NP f.lux 4.75 Activaton Code µM) and 3-MA (200 µM) +3-NP (500 µM). Protein extracts were subjected to SDS-PAGE and immunoblotting. Densities of protein bands were analyzed with adobe acrobat pro download image analyzer (SigmaScan Pro f.lux 4.75 Activaton Code and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). EditPlus v5.4 Build 3571 Crack Serial Key Latest 2021 Free represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. *P<0.05 (3-NP group vs. control group). #P<0.05 (3-MA +3-NP- treated group vs. 3-NP- treated group). **P<0.01 (3-NP group vs. control group). ##P<0.05 (3-MA +3-NP- treated group vs. 3-NP- treated group).
https://doi.org/10.1371/journal.pone.0063245.g002
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Figure 3. TP53 dependency of DRAM1 induction after 3-NP treatment.
A549 f.lux 4.75 Activaton Code H1299 cells were treated with 3-NP (500 µM) and harvested 48 h later. (A) Immunoblot analysis of TP53 and DRAM1 levels in A549 and H1299 cells under conditions of: no treatment (Ctrl) and 48 h after 3-NP. Protein extracts were subjected to SDS-PAGE and immunoblotting. Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (3-NP group vs. control group). ^##P<0.01 (3-NP group vs. control group). ^$$P<0.01 (3-NP group vs. CDex 2.24 Free Download with Crack group). (B) Immunoblot analysis of TP53 and DRAM1 levels in p53 wt and p53 KO MEFs under conditions of: no treatment (Ctrl) and 48 h after 3-NP. Protein extracts were subjected to SDS-PAGE and immunoblotting. Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (3-NP group vs. control group). ^##P<0.01 (3-NP group vs. control group). ^$$P<0.01 (3-NP group vs. control group). (C) A549 cells were transfected with TP53 siRNA or a non-silencing siRNA. Forty-eight hours after transfection of cells with TP53 f.lux 4.75 Activaton Code, cells were harvested and protein levels of TP53 and DRAM1 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein bands were analyzed with Sigma Scan Pro 5 and normalized to the loading control (β-actin), f.lux 4.75 Activaton Code. The data are expressed as percentage of control. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 TP53 siRNA group vs, f.lux 4.75 Activaton Code. non-silencing siRNA group. (D) H1299 cells were transfected with TP53 siRNA or a non-silencing siRNA. Forty-eight hours after transfection of cells with TP53 siRNA, cells were harvested and protein levels of TP53 and DRAM1 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein bands were analyzed with Sigma Scan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test.
https://doi.org/10.1371/journal.pone.0063245.g003
It was reported that DRAM1 is a TP53 target gene. We determined the TP53 dependency in 3-NP-induced DRAM1 expression. In H1299 cells which lack of F.lux 4.75 Activaton Code, 3-NP only slightly induced DRAM1 expression, while in A549 cells which express wt TP53, 3-NP robustly induced the expression of DRAM1 (Figure 3A). The similar results were seen in TP53 wt and TP53 null MEFs cells (Figure 3B). Treatment of A549 cells with TP53 siRNA, partially inhibited both basal and 3-NP-induced the expression of DRAM1 (Figure 3C). In contrast, treatment of H1299 with TP53 siRNA did not block 3-NP-induced expression of DRAM1 (Figure 3D), f.lux 4.75 Activaton Code. These results suggest that induction of DRAM1 largely depends on TP53 mechanism, but other signaling pathways are also be involved in regulating DRAM1 expression after 3-NP treatment [28].
DRAM1 Mediates Autophagy Activation
To understand the role of DRAM1 in the regulation of autophagy, the present study investigated the role of DRAM1 in f.lux 4.75 Activaton Code activation in response to 3-NP treatment in A549 and Hela cells. Knock-down of DRAM1 using siRNA significantly reduced the expression of DRAM1 proteins in A549 cells (Figure 4A) and in Hella cells (Figure S1 A). After knock-down of DRAM1 with siRNA, the basal expression f.lux 4.75 Activaton Code induction of LC3-II by 3-NP was markedly reduced in both A549 cells (Figure 4B) and Hela cells (Figure S1A). In addition, 3-NP-induced reduction of SQSTM1 was blocked by DRAM1 siRNA in A549 cells (Figure 4B). The formation f.lux 4.75 Activaton Code GFP-LC3 puncta after 3-NP treatment was also inhibited in the presence of DRAM1 siRNA in A549 cells (Figure 4C) and in Hela cells (Figure S1 B), f.lux 4.75 Activaton Code. In addition to inhibiting the production of LC3-II, SQSTM1 levels increased in DRAM1 siRNA-treated cells (Figure 4B). These lines of evidence support an important role of DRAM1 in autophagy activation.
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Figure 4. DRAM1 mediated autophagy activation.
(A, B) A549 cells were transfected with DRAM1 siRNA or a non-silencing siRNA. Left: Forty-eight hours after transfection of cells with DRAM1 siRNA, cells were harvested and protein levels of DRAM1, LC3 and SQSTM1 were analyzed with immunoblotting. Right: Twenty-four hours after transfection of cells with DRAM1 siRNA, f.lux 4.75 Activaton Code, cells were treated with 3-NP (500 µM), f.lux 4.75 Activaton Code. Cells were harvested and protein levels of LC3 and SQSTM1 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein f.lux 4.75 Activaton Code were analyzed with SigmaScan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA group). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 non-silencing siRNA group vs, f.lux 4.75 Activaton Code. control group. ^##P<0.01 DRAM1 siRNA group vs. non-silencing siRNA group. (C) Representative images of GFP-LC3 fluorescence in cells transfected with GFP-LC3 and treated with DRAM1 siRNAs in the presence or absence of 3-NP (500 µM). Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. N: the nucleus. Thin arrows: GFP-LC3 dots. The scale bar represents 10 µm. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (siRNA group vs, f.lux 4.75 Activaton Code. non-silencing siRNA group).
https://doi.org/10.1371/journal.pone.0063245.g004
DRAM1 Enhances Autophagosomes Clearance
To study the mechanisms of DRAM1 in regulating autophagy, A549 cells were transfected with GFP-DRAM1. The lysosomal localization of DRAM1 was examined with LysoTracker and LAMP2 immunofluorescence or f.lux 4.75 Activaton Code immunofluorescence of DRAM1 and LAMP2. LysoTracker is a commonly used lysosomal probe because it is an acidotropic fluorescent dye for labeling and tracking acidic organelles in live cells. Marked co-localization of DRAM1 and LysoTracker (Figure 5A) or DRAM1 and LAMP2 (Figure 5B) was seen with a confocal microscopy. The quantitative analysis revealed that colocalization of DRAM1 puncta and LAMP2 was 74.8±5.6% (data not shown), suggesting that DRAM1 predominantly localizes to lysosomes. The clearance of autophagosomes is a measure f.lux 4.75 Activaton Code autophagy flux. In control cells, acute autophagy induction with rapamycin elevated LC3-II levels as revealed by immunoblotting. After removing rapamycin from the medium for 6 h, LC3-II returned towards baseline levels. While in DRAM1 siRNA-treated cells, LC3-II remained elevated 6 h after removing rapamycin (Figure 5C). Double immunofluorescence of LC3 and LAMP2 demonstrated the formation of large number of LC3-LAMP2-positive vesicles in siRNA untreated cells after rapamycin exposure. Treatment of cells with DRAM1 siRNA reduced the number of LC3-LAMP2-posive vesicles (Figure 5D). After removal of rapamycin for 6 h, a number of LC3-LAMP2-positive vesicles were cleared in siRNA untreated cells but more LC3-LAMP2-positive vesicles remained in the cells treated with DRAM1 siRNA (Figure 5E and 5F). These suggest that both the formation and the clearance SlimWare DriverUpdate 5.8.19.60 Crack + Registration Key 2021 autophagic vacuoles are impaired in DRAM1 siRNA-treated A549 cells.
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Figure 5. Knock-down of DRAM1 impaired the clearance of autophagosomes.
(A) DRAM1 was predominantly localized in lysosomes (Lysotraker). A549 cells were transfected with GFP-DRAM1 for 48 h. Cells were incubated with LysoTracker (0.5 µM) and co-localization of DRAM1-GFP (green) and the LysoTracker (red) was assessed with a confocal microscopy. N: the nucleus. Thin arrows: GFP-DRAM1 fluorescence. Thick arrows: LysoTracker, f.lux 4.75 Activaton Code. (B) DRAM1 was predominantly localized in lysosomes (LAMP2). Up panel: F.lux 4.75 Activaton Code cells were transfected with GFP-DRAM1 f.lux 4.75 Activaton Code 48 h. Cells were processed for immunofluorescence using LAMP2 antibodies and co-localization of DRAM1-GFP (green) and the LAMP2 (red) was assessed with a confocal microscopy. N: the nucleus. Thin arrows: GFP-DRAM1 fluorescence. Thick arrows: LAMP2. Low f.lux 4.75 Activaton Code A549 cells were processed for immunofluorescence using DRAM1 and LAMP2 antibodies, and co-localization of DRAM1 (green) and the LAMP2 (red) was assessed with a confocal microscopy. N: the nucleus. Thin arrows: anti-DRAM1 fluorescence. Thick arrows: LAMP2. (C) Immunoblot analysis of LC3 levels in A549 cells under conditions: untreated (Cont), rapamycin (Rap) treatment, and 6 h after rapamycin removal (Rap/Rec). Densities of protein bands were analyzed with an image analyzer (SigmaScan Pro 5) and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA group). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Tukey’s test. **P<0.01 (DRAM1 siRNA treatment group vs. non-silencing siRNA group). (D) A549 cells were analyzed with double-immunofluorescence using LC3 and LAMP2 antibodies in the presence of rapamycin and 6 h after removal of rapamycin. N: the nucleus. Thin arrows: dots of LC3 immonureactivity. Thick arrows: LAMP2. The scale bar represents 10 µm. (E) DRAM1 siRNA-treated cells were analyzed with double-immunofluorescence using LC3 and LAMP2 antibodies in the presence of rapamycin and 6 h after removal of rapamycin, f.lux 4.75 Activaton Code. N: the nucleus. Thin arrows: dots of GFP-LC3 fluorescence. Thick arrows: LAMP2, f.lux 4.75 Activaton Code. The scale bar represents 10 µm. (F) In cells after DRAM1 siRNA treatment, the number of F.lux 4.75 Activaton Code dots was scored in 100 GFP-LC3-positive cells in the presence or absence of 3-NP. The data are expressed as percentage of control. Bars represent mean±SE; n = 4. Statistical comparisons were carried out by Tukey’s test. **P<0.01 (DRAM1 siRNA treatment group vs. non-silencing siRNA group). ^#P<0.05 (DRAM1 siRNA treatment group vs. non-silencing siRNA group).
https://doi.org/10.1371/journal.pone.0063245.g005
DRAM1 Affects Lysosomal Degradation and Lysosomal Acidification
Lysosomal enzyme, cathepsin D, plays an essential role in the degradation process of autophagic activity. The present study employed double immunofluorescence of cathepsin D and LysoTracker to explore the role of DRAM1 in lysosomal function. We observed that cathepsin D was virtually confined in LysoTracker fluorescence-positive vesicles in A549 cells. 3-NP treatment increased the expression of cathepsin D and the number of LysoTraker labeled lysosomes (Figure 6A).
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Figure 6. Knock-down DRAM1 inhibited autophagosome maturation process.
(A) Lysosomes were activated by 3-NP. A549 cells were treated with 3-NP (500 µM) for 48 h. Cells were incubated with LysoTracker (0.5 µM) and processed for immunofluorescence using Cathepsin D (Cat D) antibodies. The co-localization of Cat D (green) and the LysoTracker (red) was assayed by confocal microscopy. N: the nucleus. Thin arrows: Cat D immunoreactivity. Thick arrows: LysoTracker. The scale bar represents 10 µm. (B) Accumulation of mRFP-LC3 in DRAM1 siRNA-treated cells. Representative images of mRFP-GFP-LC3 fluorescence in cells transfected with mRFP-GFP-LC3 and treated with DRAM1 siRNAs in the presence or absence of 3-NP (500 µM). N: the nucleus. Thin arrows: GFP-LC3 dots. Thick arrows: mRFP-LC3 dots. The scale f.lux 4.75 Activaton Code represents 10 µm. (C) Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. Statistical comparisons were carried out by ANOVA followed by Dunnett f.lux 4.75 Activaton Code. **P<0.01 non-silencing siRNA group vs. control group. ^##P<0.01 DRAM1 siRNA group vs. non-silencing siRNA group.
https://doi.org/10.1371/journal.pone.0063245.g006
GFP-LC3 is the most widely used marker for autophagosomes. When localized to autolysosomes, GFP-LC3 loses fluorescence due to lysosomal acidic and degradative conditions. While mRFP-LC3 is more stable in acidic conditions and fluorescence remains after fusion of autophagosomes with lysosomes. Thus, we used mRFP-GFP tandem fluorescent-tagged LC3 to monitor the process of autophagy maturation [29]. The result showed that 3-NP increased the expression of LC3, most of LC3 displayed yellow color due to emitted both GFP and RFP fluorescence. However, due to stronger fluorescence of GFP than that of RFP, some green LC3 patches were also observed. Knock-down Solid Commander 10.1.11962.4838 Crack Free Download DRAM1 with siRNA slightly reduced GFP-LC3 fluorescence (reflecting attenuation of autophagy induction), but robustly increased the number of large mRFP-LC3 puncta (Figure 6B and 6C). In the condition of treatment with 3-NP in the f.lux 4.75 Activaton Code of non-sil siRNA, yellow punctas were few because degradation of autolysosomes was smooth. While in the condition of treatment with 3-NP in the presence of DRAM1 siRNA, more large yellow pinctas were observed (Figure 6B). These results indicate that the clearance of autophagic vacuoles is impaired in DRAM1 siRNA-treated A549 cells.
As most lysosomal cathepsins work at acidic pH, the effect of DRAM1 silencing on activation of cathepsin D was examined. The results of f.lux 4.75 Activaton Code showed that knock-down of DRAM1 significantly inhibited 3-NP-induced production of the active form of cathepsin D (Figure 7A), suggesting activation of f.lux 4.75 Activaton Code D is compromised. To assess lysosomal f.lux 4.75 Activaton Code, we used LysoSensor F.lux 4.75 Activaton Code. The LysoSensor dye is an acidotropic probe that appears to accumulate in acidic organelles as the result of protonation. In control cells, the fluorescence of LysoSensor was enhanced from 24 to 72 h after 3-NP exposure. By contrast, in DRAM1 siRNA-treated cells, the fluorescence was lower than that in the control cells (Figure 7B). We further measured lysosomal pH in quantization. The cells were loaded with the pH-sensitive reporter F.lux 4.75 Activaton Code by endocytosis for 1 h and then chased in the control and DRAM1 siRNA-treated cells in the presence and absence of 3-NP. WT cells exhibited an intralysosomal pH of 4.75, and lysosomal pH decreased following 3-NP treatment (Figure 7C), f.lux 4.75 Activaton Code. In contrast, the lysosomal pH values decreased to a lesser extent (5.23) in DRAM1 siRNA-treated cells following 3-NP treatment in both A549 cells (Figure 7C) and in Hela cells (Figure S1 C). These results suggest that there is a defective lysosomal acidification in DRAM1 siRNA-treated cells. Lysosomal acidification requires the activity of the ATP-dependent vacuolar proton pump [30]. We examined the ATP-dependent lysosomal acidification using the pH sensitive dye FITC-dextran. F.lux 4.75 Activaton Code dye accumulates inside lysosomes due to its weak basic net charge in response to ATP addition. As shown in Figure 7D, addition of ATP caused a dramatic drop in FITC fluorescence as a result of lysosomal acidification in control and 3-NP-treated cells. In DRAM1 siRNA-treated cells, ATP-induced drop in fluorescence emission was reduced, reflecting a reduction in internal lysosomal acidification. Reduction in FITC fluorescence by ATP was inhibited by the V-ATPase inhibitor bafilomycin A1. The similar results were obtained in Hela cells (Figure S1 D). Thus, the impairment of acidification in DRAM1 siRNA-treated cells might be due to a decrease in V-ATPase activity.
Download:
Figure 7. Knock down DRAM1 inhibited lysosomal acidification and cathepsin D activation.
(A) A549 cells were transfected with DRAM1 siRNA or a non-silencing siRNA. Left: Forty-eight hours after transfection of DRAM1 siRNA, cells were harvested and protein levels of cat D were analyzed with immunoblotting. Right: Twenty-four hours after transfection of cells with DRAM1 siRNA, cells were treated with 3-NP (500 µM) for 24 h. Cells were harvested and protein levels of cat D were analyzed with immunoblotting. Densities of protein bands were f.lux 4.75 Activaton Code with SigmaScan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). (B) Lysosomal acidification was measured using LysoSensor DND-167. In control cells, the fluorescence of LysoSensor was measured from 24 to 72 h, and in DRAM siRNA-treated cells the fluorescence was measured in 48 h after transfection of DRAM1 siRNA. N: the nucleus. The scale bar represents 10 µm. (C) Lysosomal pH was measured ratio-metrically using fluorescent dextrans. WT cells and DRAM1 siRNA1-treated cells were loaded with the pH-sensitive fluorescent dextrans by endocytosis for 1 h at 37°C and then subjected to pulse-chase assay in the presence or absence of the 3-NP (500 µM). Lanes 2 and 4 depict pH values obtained with FITC-dextran after the addition of 500 nM 3-NP. The data are expressed as percentage of control (non-silencing siRNA cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA deep freeze standard 8.37 license key by F.lux 4.75 Activaton Code t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA f.lux 4.75 Activaton Code. ^##P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group with 3-NP treatment). (D) Lysosomal V-ATPase activity was inhibited in DRAM1 siRNA1-treated cells. Lysosomes from control cells and DRAM1 siRNA1-treated cells were loaded with FITC-dextran (molecular weight 70,000). A549 cells were then homogenized and used for in vitro-acidification assays. Fluorescence was recorded continuously with excitation at 490 nm and emission at 520 nm. Upon addition of ATP, f.lux 4.75 Activaton Code, a progressive decrease in fluorescence intensity was observed, indicative of intralysosomal acidification. The decrement was reversed by bafilomycin A1, a V-ATPase inhibitor.
https://doi.org/10.1371/journal.pone.0063245.g007
Foregoing observations indicate that DRAM1 regulates autophagy flux mainly thought lysosomes. Thus, the lysosomal inhibitors E64d (10 µM) and chloroquine (20 µM) were used to evaluate if inhibition of lysosomal functions produces effects similar to knock-down of DRAM1. Many autophagy inhibitors act on post-sequestration steps and agents, such as bafilomycin A1, that blocks autophagy activity are known to cause accumulation of autophagosomes [31]. Chloroquine is a compound that elevates lysosomal pH, and E64d is an effective inhibitor of lysosomal enzymes [32]. After 3-NP treatment, f.lux 4.75 Activaton Code, more LAMP2-positive vacuoles were observed. Compared with cells treated with 3-NP alone, LC3 in E64d or chloroquine-treated cells accumulated more LAMP2-positive vacuoles (Figure 8A). As shown in Fig. 8B, LC3-II accumulated after E64d or chloroquine treatment. These results suggest a defective clearance of autophagic vacuoles in E64d- and chloroquine-treated cells.
Download:
Figure 8. Lysosomal inhibitors inhibited autophagosome clearance.
(A) Accumulation of autophagosomes was analyzed with double-immunofluorescence using antibodies against LC3 and LAMP2 after E64d (10 µM) or chloroquine (20 µM) treatment for 24 h in the presence or absence of 3-NP (500 µM). N: the nucleus. Thin arrows: dots of LC3 immunoreactivity. Thick arrows: LAMP2 immunoreactivity. The scale bar represents 10 µm. (B) Immunoblot analysis of LC3-II levels in cells under conditions of: no treatment (Cont), E64d (10 µM), chloroquine (20 µM), 3-NP (500 µM), E64d (10 µM) +3-NP (500 µM) or chloroquine (20 µM) +3-NP (500 µM). Cells were harvested for f.lux 4.75 Activaton Code 48 h after 3-NP treatment. Densities of protein bands were analyzed with SigmaScan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (untreated cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA f.lux 4.75 Activaton Code by Dunnett t-test. *P<0.05 (3-NP treated group vs. control group). ^#P<0.05 (E64d+3-NP- or chloroquine +3-NP-treated group vs. 3-NP- treated group). ^##P<0.01 (E64d plus 3-NP or chloroquine plus 3-NP treatment group vs. 3-NP treatment group).
https://doi.org/10.1371/journal.pone.0063245.g008
Discussion
3-NP acts as an irreversible inhibitor of succinate dehydrogenase and thus results in an impairement of energy metabolism, oxidative stress and activation of glutamate receptors [33]. Mitochondria are important intracellular organelles and the collapse of mitochondria membrane potential may be a signal for activation of autophagy and apoptosis. Previous in vivo studies suggest that 3-NP-induced cell death in rat striatum involves TP53-dependent activation of apoptosis and autophagy [6]. It was also reported that DRAM1 and SQSTM1 regulated cell migration and invasion of glioblastoma stem cells [34]. TP53 target gene DRAM1 possibly mediates down stream multiple functions in autophagy and cell pdfcreator full crack. The present in vitro studies found that 3-NP inhibited cell viability of A549 cells at the doses of 250 µM to 1 mM (data not shown). The activation of autophagy was demonstrated by increases in LC3-II protein levels, GFP-LC3 puncta and a decrease in SQSTM1 protein levels. These studies suggest that mitochondria dysfunction induced by 3-NP triggered autophagy activation. Biochemical analysis showed that 3-NP and CCCP significantly increased DRAM1 protein levels and this increase in DRAM1 played a role f.lux 4.75 Activaton Code 3-NP-induced autophagy activation. Although upregulation of DRAM1 by 3-NP largely depended on TP53, our present results suggested there were also other mechanisms involved [28]. The human DRAM1 gene password recovery bundle free download with crack a 238 amino acid protein which acts as a stress-induced regulator of autophagy and f.lux 4.75 Activaton Code programmed cell death [8]. The present study demonstrated that knock-down of DRAM1 effectively blocked the 3-NP-induced induction of LC3-II and decline in SQSTM1. These studies confirm that DRAM1 plays an important role in autophagy activation.
To investigate the underlying mechanism by which DRAM1 regulates autophagy, we investigated the effects of DRAM1 on autophagosome clearance. Colocalization of EGFP-DRAM1 and LysoTracker fluorescence or DRAM1 and LAMP2 immunoflurescence confirmed predominant lysosomal localization of expressed DRAM1. We first tested if DRAM1 has an effect on autophagosome turnover following induction with rapamycin. Rapamycin can stimulate the formation of autophagosome through inhibiting mTOR. Upon removal of rapamycin, autophagosomes should be cleared if autophagy pathway is normal, f.lux 4.75 Activaton Code. The present study demonstrated that rapamycin increased the abundance of autophagosomes and the number of autophagosomes returned towards the basal levels 6 h after withdrawal of rapamycin. Knock-down of DRAM1 reduced the rate of clearance of autophagosomes after rapamycin withdrawal. Galavotti et al reported that knock-down of DRAM1 inhibited targeting of SQSTM1 to autophagosomes and reduced its degradation [34]. Our data also support the involvement of DRAM1 in degradation of autophagososmes. However, Galavotti et al found that DRAM1 was not involved in starvation- and mTOR-mediated autophagy activation [34]. Therefore, f.lux 4.75 Activaton Code, the role of DRAM1 in autophagy activation induced by other stimuli need to be further studied.
The abundance of autophagosomes is balanced by the formation and clearance of autophagosomes. After the formation, f.lux 4.75 Activaton Code, the turn-over of autophagosomes is largely determined by the process of fusion between autophagososmes and lysosomes and degradation of autophagy contents by lysosomal enzymes, f.lux 4.75 Activaton Code. mRFP-GFP tandem fluorescent-tagged LC3 showed both GFP and mRFP signal of LC3 before the fusion with lysosomes, and exhibited only the mRFP signal when LC3 transmit into lysosomes because of lysosomal acidic environment and degradation [29]. After rapamycin treatment, there was more number of mRFP-GFP-LC3 patches in non-silencing RNA-treated cells than that in DRAM1 siRAN-treated cells, suggesting DRAM1 plays a role in the formation of autophagosomes. In response to withdrawal of rapamycin, mRFP-GFP-LC3 patches quickly declined in control cells. Knock-down of DRAM1 markedly retained these mRFP-GFP-LC3 patches in the cells. These results suggest that DRAM1 stimulates clearance of autophagosomes.
Lysosomes are rich in hydrolytic enzymes and are responsible for the degradation of intracellular materials captured by autophagy [35]. After 3-NP treatment, an increase in the abundance of autophagosomes was accompanied by an increase in the number of lysosomes. The increase in folder lock software freeware download Free Activators lysosomes was noticeable as indicated by a fluorescence dye. Knock-down of DRAM1 resulted in an impairment of lysosomal acidification and accumulation of LC3-II, indicating reduced autophagy flux. It is now generally accepted that intralysosomal low pH is maintained by an active proton pump, vacuolar H⁺ATPases or VATPases. Proton transport into intracellular organelles is primarily mediated f.lux 4.75 Activaton Code ATPdependent proton pumps. These pumps are therefore central to pH homeostasis in organelles. Autophagosomes and their contents are cleared upon fusing with late endosomes or lysosomes containing cathepsins, other acid hydrolases, and vacuolar [H⁺] ATPase(v-ATPase) [36], a proton pump that acidifies the newly created autolysosome, f.lux 4.75 Activaton Code. It is suggested that the proton pumps and acidification of the lysosomes were essential for the activation of lysosomal hydrolases and completion of the process of autophagy. V-ATPase may also play a role in amino acid sensing, thus plays a role in mTOR-mediated autophagy activation [37]. Inhibition of mitochondrial respiratory complex may decrease ATP production and thus decrease the activity of V-ATPase. However, due to a significant induction of DRAM1 and activation of autophagy in the present study, the V-ATPase activity was preserved to sufficiently acidify lysosomes. We speculate that DRAM1 may improve the efficiency of ATP utilization by V-ATPase. The present study found that the lower capacity for acidification of lysosomes in DRAM1 siRNA-treated cells was due to decreased V-ATPase activity. These results provide experimental data, for the first time, supporting an important role of DRAM1 in lysosomal function.
Lysosomes play important roles in autophagy. To test if the effects of DRAM1 on lysosomal functions are responsible for DRAM1-mediated autophagy activation after 3-NP treatment, the present study assessed the effects of lysosomal inhibitors on autophagosome accumulation in the presence of 3-NP. The results showed that elevating lysosomal pH and inhibiting lysosomal enzymes both increased accumulation of autophagosomes and inhibited cathepsin D activation. F.lux 4.75 Activaton Code results largely replicated the effects of knock-down of DRAM1 and suggested that DRAM1 probably regulated autophagy flux through lysosomes.
It should be pointed out that DRAM1 appears regulate autophagy in both early and later stages of autophagy. DRAM1 can increase the formation of autophagosomes and the clearance of autophagosomes. These effects may work through the same mechanism as DRAM1 is a lysosomal protein and may regulates dynamics of lysosomal membranes to increase V-ATPase activity and to facilitate membrane recycle for autophagosomal formation.
In conclusion, current data indicate that DRAM1 regulates autophagosome f.lux 4.75 Activaton Code through promoting lysosomal acidification and activation of lysosomal enzymes. The fusion of autophagosomes with lysosomes is an important step for autophagic degradation. In order to fully understand the role of DRAM1 in autophagy f.lux 4.75 Activaton Code, the effects of DRAM1 on the fusion process between autophagosomes and lysosomes needs to be studied in the future.
Supporting Information
Figure S1.
DRAM1 mediated autophagy activation and lysosomal acidification in Hela cells. (A) Hela cells were transfected with DRAM1 siRNA or a non-silencing siRNA. Left: Forty-eight h after transfection of cells with DRAM1 siRNA, cells were harvested and protein levels of DRAM1 and LC3 were analyzed with immunoblotting. Right: Twenty-four hours after transfection of cells with DRAM1 siRNA, cells were treated with 3-NP (500 µM). Cells were harvested and protein levels of DRAM1 and LC3 were analyzed with immunoblotting 24 h after 3-NP. Densities of protein bands were analyzed with Sigma Scan Pro 5 and normalized to the loading control (β-actin). The data are expressed as percentage of control (non-silencing siRNA group). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). ^##P<0.01 (3-NP treated group vs. control group). ^$$P<0.01 (DRAM1 siRNA group vs, f.lux 4.75 Activaton Code. non-silencing siRNA group with 3-NP treatment). (B) Representative images of GFP-LC3 fluorescence in Hela cells transfected with GFP-LC3 and treated with DRAM1 siRNAs in the presence or absence of 3-NP (500 µM). Number of cells with GFP-LC3 dots was scored in 100 GFP-LC3-positive cells. N: the nucleus. Thin arrows: GFP-LC3 dots. The scale bar represents 10 µm Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (siRNA group vs. non-silencing siRNA group). (C) Lysosomal pH was measured ratio-metrically using fluorescent dextrans in Hela cells. WT Hela cells and DRAM1 siRNA1-treated cells were loaded with the pH-sensitive fluorescent dextrans by endocytosis for 1 h at 37°C and then subjected to pulse-chase assay in the presence or absence of the 3-NP (500 µM). Lanes 2 and 4 depict pH values f.lux 4.75 Activaton Code with FITC-dextran after the addition of 500 nM 3-NP. The data are expressed as percentage of control (non-silencing siRNA cells). Bars represent mean±SE; n = 4. Statistical comparisons were carried out by ANOVA followed by Dunnett t-test. **P<0.01 (DRAM1 siRNA group vs. non-silencing siRNA group). ^##P<0.01 (DRAM1 f.lux 4.75 Activaton Code group vs. non-silencing siRNA group with 3-NP treatment). (D) Lysosomal V-ATPase activity was inhibited in DRAM1 siRNA1-treated Hela cells. Lysosomes from control cells and DRAM1 siRNA1-treated cells were loaded with FITC-dextran (molecular weight 70,000). Hela cells were then homogenized and used for cyberlink powerdirector 15 free download 64-bit full version vitro-acidification assays. Fluorescence was recorded f.lux 4.75 Activaton Code with excitation at 490 nm and emission at 520 nm. Upon addition of ATP, a progressive decrease in fluorescence intensity was observed, indicative of intralysosomal acidification. The decrement was reversed by bafilomycin A1, a V-ATPase inhibitor.
https://doi.org/10.1371/journal.pone.0063245.s001
(TIF)
Figure S2.
Activity of DRAM1 antibody was blocked by DRAM1 peptide. (A) Cells were harvested and immunoblot analysis of DRAM1 protein levels in A549 and Hela cells. Left: No peptide incubated with DRAM1 antibody before primary antibody incubation. Teamviewer with crack kickass DRAM1 peptide was incubated with DRAM1 antibody for 30 min at 37°C before primary antibody incubation. (B) Cells were processed for immunofluorescence using DRAM1 antibodies (green) f.lux 4.75 Activaton Code DAPI (the nucleus, blue) in A549 and Hela cells, and was assessed with a confocal microscopy. Left: No peptide incubated with DRAM1 antibody before primary antibody incubation. Right: DRAM1 peptide was incubated with DRAM1 antibody for 30 min at 37°C before primary antibody incubation. N: the nucleus. Thin arrows: anti-DRAM1 fluorescence.
https://doi.org/10.1371/journal.pone.0063245.s002
(TIF)
Author Contributions
Conceived and designed the experiments: ZQ XZ. Performed the experiments: XZ LQ. Analyzed the data: XZ LQ. Contributed reagents/materials/analysis tools: XZ JW. Wrote the paper: XZ ZQ.
References
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Lysosomes
Small interfering RNA
Autophagic cell death
Transfection
HeLa cells
Immunoblotting
Analysis of variance
Apoptosis

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F.lux 4.75 Activaton Code - charming

Abstract

Introduction

Materials and Methods

Cell Lines and Reagents

Expression of GFP-LC3 and DRAM1-pEGFP

Knock-down of TP53 and DRAM1

LC3 Immunofluorescence Assay

Western Blot Analysis

Determination of Lysosomal pH

Spectrophotometric Measurement of H+ Transport

Statistical Analysis

Results

3-NP Induces Autophagy Activation

DRAM1 Mediates Autophagy Activation

DRAM1 Enhances Autophagosomes Clearance

DRAM1 Affects Lysosomal Degradation and Lysosomal Acidification

Discussion

Supporting Information

Figure S1.

Figure S2.

Author Contributions

References

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Hog1 Mitogen-Activated Protein Kinase Phosphorylation Targets the Yeast Fps1 Aquaglyceroporin for Endocytosis, Thereby Rendering Cells Resistant to Acetic Acid▿

Mehdi Mollapour

Peter W. Piper

Abstract

MATERIALS AND METHODS

Strains and plasmids.

Growth conditions.

Acetic acid uptake measurements.

Protein analysis and immunoblots.

Binding assays.

In vitro kinase assay.

Fluorescence microscopy.

Two-hybrid analysis.

RESULTS

Loss of Fps1 influences acetic acid uptake and resistance in yeast.

Fps1 mediates the diffusional entry of undissociated acetic acid to glucose-repressed yeast.

Hog1 MAPK activation by acetic acid stress directs endocytosis and degradation of Fps1.

Fps1-GFP undergoes Hog1-dependent endocytosis in response to acetic acid but not salt stress.

Fps1 undergoes Hog1-dependent phosphorylation in response to acetic acid stress.

Acetic acid induces a transient Fps1 ubiquitination that is Hog1 dependent.

Hog1 binds the N-terminal regulatory domain of Fps1, with the active form of this MAPK phosphorylating threonine 231 of this domain, both in vivo and in vitro.

DISCUSSION

Acknowledgments

Footnotes

REFERENCES

Neural Network primitives from NNlib.jl

Activation Functions

Softmax

Pooling

Padding

Convolution

Upsampling

Batched Operations

Gather and Scatter

Sampling

Losses

Miscellaneous

Metabolic Flux Increases Glycoprotein Sialylation: Implications for Cell Adhesion and Cancer Metastasis*

Ruben T. Almaraz

Yuan Tian

Rahul Bhattarcharya

Elaine Tan

Shih-Hsun Chen

Matthew R. Dallas

Li Chen

Zhen Zhang

Hui Zhang

Konstantinos Konstantopoulos

Kevin J. Yarema

Abstract

EXPERIMENTAL PROCEDURES

Materials: Adhesion Molecules, Antibodies, and Reagents

Cell Culture

Periodate Resorcinal Assay

Lectin and Antibody Analysis of SW1990 Cells

Western Analysis of CD44

Spectrophotometric Measurement of H⁺ Transport

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Hog1 Mitogen-Activated Protein Kinase Phosphorylation Targets the Yeast Fps1 Aquaglyceroporin for Endocytosis, Thereby Rendering Cells Resistant to Acetic Acid^▿

Metabolic Flux Increases Glycoprotein Sialylation: Implications for Cell Adhesion and Cancer Metastasis^*

1,3,4-O-Bu₃ManNAc Increased Intracellular and Surface Sialic Acid

Metabolic Flux Increases Glycoprotein Sialylation: Implications for Cell Adhesion and Cancer Metastasis^*

1,3,4-O-Bu₃ManNAc Increased Intracellular and Surface Sialic Acid

Hog1 Mitogen-Activated Protein Kinase Phosphorylation Targets the Yeast Fps1 Aquaglyceroporin for Endocytosis, Thereby Rendering Cells Resistant to Acetic Acid^▿