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. Author manuscript; available in PMC: 2017 Mar 15.
Published in final edited form as: J Immunol. 2016 Feb 3;196(6):2541–2551. doi: 10.4049/jimmunol.1501345

GAPDH Binding to TNF-α mRNA Contributes to Post-Transcriptional Repression in Monocytes: A Novel Mechanism of Communication between Inflammation and Metabolism

Patrick Millet *, Vidula Vachharajani §,, Linda McPhail †, Barbara Yoza #, Charles McCall §
PMCID: PMC4779706  NIHMSID: NIHMS750799  PMID: 26843329

Abstract

Expression of the inflammatory cytokine TNF is tightly controlled. During endotoxin tolerance, transcription of TNF mRNA is repressed, although not entirely eliminated. Production of TNF cytokine, however, is further controlled by post-transcriptional regulation. In this study, we detail a mechanism of post-transcriptional repression of TNF mRNA by GAPDH binding to the TNF 3’UTR. Using RNA immunoprecipitation, we demonstrate that GAPDH-TNF mRNA binding increases when THP-1 monocytes are in a low glycolysis state, and that this binding can be reversed by knocking down GAPDH expression or by increasing glycolysis. We show that reducing glycolysis decreases TNF mRNA association with polysomes. We demonstrate that GAPDH-TNF mRNA binding results in post-transcriptional repression of TNF and that the TNF mRNA 3’UTR is sufficient for repression. Finally, after exploring this model in THP-1 cells, we demonstrate this mechanism affects TNF expression in primary human monocytes and macrophages. We conclude that GAPDH-TNF mRNA binding regulates expression of TNF based on cellular metabolic state. We believe this mechanism has potentially significant implications for treatment of various immunometabolic conditions, including immune paralysis during septic shock.

INTRODUCTION

The link between glycolysis and inflammation is well established. Many innate immune cell types specifically require glycolysis in order to perform their effector functions. When glycolysis is inhibited, leukocytes show decreased adhesion, mobility, and bacterial clearance (1-4). Monocytes produce less TNF cytokine when treated with the glycolysis inhibitor 2-deoxyglucose, but not when treated with the mitochondrial inhibitor rotenone (4). Additionally, macrophages express greater levels of pro-inflammatory cytokines when forced to rely on glycolysis, but express much lower levels when fatty acid oxidation is upregulated (5). This relationship between inflammation and glycolysis appears in certain disease states, as well. As the endotoxin response proceeds to tolerance, monocytes downregulate glycolysis and upregulate fatty acid oxidation (6-8). This shift in metabolism occurs simultaneously with the onset of immunosuppression.

Recent findings indicate that glycolysis and inflammation communicate in ways not previously appreciated. One of the key enzymes in glycolysis is GAPDH, which converts glyceraldehyde-3-phosphate (G3P) into 1,3-bisphosphoglycerate in the sixth step of the glycolysis pathway (9). GAPDH also has a lesser known capacity as an RNA-binding protein (10). Specifically, GAPDH binds to AU-rich elements (ARE) found in the 3’UTR of many mRNAs. AU-rich elements are present in many inflammatory genes, including cytokines like IFN-γ and TNF (11-13). GAPDH binding to a generic ARE is inhibited by G3P (14), and NAD+, a necessary cofactor for its enzymatic activity (10). Recently, it was shown GAPDH-ARE binding is responsible for post-transcriptional regulation of IFN-γ expression in T-cells (15). This binding is disrupted by the metabolite G3P, making this mechanism sensitive to cellular metabolism. Some argue that these types of RNA-enzyme-metabolite interactions broadly affect gene expression (16), however, these mechanisms remain largely unexplored.

Expression of TNF is tightly regulated in immune cells. During endotoxin tolerance, much of this regulation occurs at the level of chromatin (17-24). Tolerant monocytes and other immune cells fail to generate TNF mRNA in response to an additional stimulus while they are in the immunosuppressed state. This repression of TNF expression also occurs at the post-transcriptional level (25-27). Even if transcription of TNF mRNA is restored to tolerant monocytes, they continue to show deficiencies in TNF cytokine production. Post-transcriptional repression mediated by microRNA accounts for part of this deficiency (25, 26). A number of reports describe other post-transcriptional mechanisms which regulate TNF expression (28-32), however none of these mechanisms propose that cellular metabolic state informs the regulation process. In this study, we propose a mechanism where glycolysis directly affects TNF expression through post-transcriptional regulation.

With our previous work in the background in regards to post-transcriptional repression of TNF mRNA and immunometabolic shifts in monocytes during the endotoxin response, we speculated that GAPDH-ARE binding might contribute to regulation of TNF expression in monocytes. We hypothesized that if glycolysis was limited, GAPDH would bind the AU-rich element of TNF mRNA, thereby limiting its translation. To test this, we first cultured our THP-1 cells in media where glucose was replaced by galactose. Since galactose is metabolized more slowly than glucose (33), these cells adopted a less glycolytic, more oxidative metabolism. We not only found GAPDH binding to TNF mRNA in galactose-fed monocytic cells, but that this binding also occurs in endotoxin tolerant cells following the natural downregulation of glycolysis monocytes exhibit during tolerance. Furthermore, we found that GAPDH-TNF mRNA binding is affected by pharmacological manipulation of glycolysis. Our results indicate this mechanism allows leukocyte cell metabolism to fine-tune TNF gene expression. These findings have potential implications for any number of disease states involving inflammation and metabolism, such as immunoparalysis during septic shock.

MATERIALS AND METHODS

Cell Culturing

THP-1 cells were grown in RPMI 1640 with 10% FBS, L-glutamine, and penn-strep media. Cells were kept in a 5% CO2 incubator at 37°C and subcultured every 1-3 days to maintain a density of 20-80(10)4 cells/mL (34). THP-1 cells were maintained in an undifferentiated state. Galactose-fed cells were taken from standard glucose-fed cultures, spun down, washed with PBS, and grown in RPMI 1640 (no glucose, 2g/L galactose) for five or more days before use in any experiments.

THP-1 cells were tolerized with addition of 1ug/mL LPS for 24 hours. For experiments involving second dose exposure of LPS, cells were spun down and resuspended in fresh media for 1 hour before proceeding with second doses of LPS, also at 1ug/mL.

Preparation of human primary monocytes/macrophages

Primary monocytes/macrophage cells were collected from heparinized venous blood samples donated by healthy adult volunteers according to the IRB protocol approved by Wake Forest University (35). RBCs, platelets, and PMNs were removed through Isolymph (Gallard-Schlesinger Industries) centrifugation of whole blood. Monocytes were then enriched through a 2 hour adherence step, after which non-adherent cells were removed. Cells were then cultured overnight in fresh RPMI containing 10% FBS and either glucose or galactose, with or without 100ng/mL LPS to induce ex-vivo endotoxin tolerance. Brightfield analysis of morphology showed resulting cultures had >90% monocytes and macrophages.

Metabolic Assays

Assessment of oxygen consumption rate (OCR) and extracellular acidification rates (ECAR) were made using the Seahorse XF24 Extracellular Flux Analyzer (Seahorse Bioscience) (36). Plates were coated with Cell-Tak (BD Biosciences) (37) and dried overnight before addition of 25(10)4 cells/well in unbuffered DMEM (10% FBS, 2g/L glucose or galactose) and 1 hour incubation in a CO2-free 37°C incubator. Plates were assayed according to manufacturer’s instructions.

Lactate assays were performed using L-Lactate Assay Kit (Eton Bioscience) according to manufacturer’s instructions (38). Cells were kept in phenol-red free DMEM with 2g/L glucose or galactose during the assay.

ELISA

Quantikine TNF ELISA kit (R&D Systems) was used according to manufacturer’s instructions for measuring TNF protein concentration (39). Cells were washed twice with PBS and resuspended to a density of 80(10)4 cell/mL in appropriate media before incubation with or without LPS. Supernatant of resulting cultures was collected when indicated and used for assay.

RT-qPCR

RNA was isolated using STAT60 (Tel-Test Inc.) when isolation was required outside the context of RNA Immunoprecipitation (40). RNA quality was measured on a NanoDrop 1000 (Thermo Scientific) before reverse transcription using the qScript cDNA Synthesis (Quanta Bioscience) system (41). Quantitative PCR was done using Taqman reagents and probe/primer mixes (Applied Biosystems) on the ABI7500 Fast.

For RNA stability assay, cells were stimulated with LPS for 1 hour, then given 5ug/mL actinomycin D for indicated time. Cells were then pelleted and RNA isolated as described above (23).

RNA Immunoprecipitation

RNA Immunoprecipitation was performed using the Magna RIP kit (Millipore) according to manufacturer’s instructions (42). Briefly, cultures of 10(10)6 cells were prepared as described above, spun down, washed, and lysed with −80°C freezing. Lysates were then spun down and supernatants transferred to tubes with magnetic beads that were previously treated with 5ug of anti-GAPDH antibody (Sigma) or non-specific IgG. Lysates were rotated with beads overnight, washed the next day, eluted (alongside input RNA), isolated with phenol-chloroform-isoamyl alcohol, ethanol precipitated, and resuspended in RNase free water. Quality of input RNA was assessed and all samples measured through RT-qPCR as described above.

Western Blotting

THP-1 cells were cultured and treated as indicated in text. Cells were pelleted and lysed in RIPA buffer. 50ug protein was loaded into each well of a 4-20% Precise Protein gel (Thermo-Fisher). Blot was run and transferred according to gel manufacturer’s instructions (43).

RNA interference

5(10)6 THP-1 cells were transfected with 1 μM siRNA targeting either GAPDH mRNA or not targeting any mRNA (control). Transfection was done using the Amaxa Nucleofector II according to manufacturer’s instructions (23). Cells were cultured in appropriate media for 3 days following transfection before use in Western blot or ELISA experiments.

Polysome Fractionation Profiling

Polysome fractionation analysis was performed as previously described (44). Briefly, 10(10)6 THP-1 cells were incubated with 100 μg/mL cyclohexamide before lysis in hypotonic buffer. Lysates were pelleted, and the supernatant placed on top a 10-45% continuous sucrose gradient. Samples were then centrifuged at 222,228 × g for 2 hours at 4°C. After ultracentrifugation, tubes were pierced at the bottom and fractions were collected. UV absorbance was measured for each fraction using a NanoDrop 1000 (Thermo Scientific). RNA was extracted from each fraction using STAT50 (Tel-Test Inc.). RT-qPCR analysis was then performed as previously described.

Luciferase Reporter

THP-1 cells were plated in white 96-well plates in phenol-red free DMEM (5% FBS, 2g/L glucose or galactose). Cells were then transfected with FuGENE Transfection reagent and GoClone plasmids (SwitchGear Genomics) encoding Renilla luciferase with 3’UTR regions indicated in figure legends. Transfections included Cypridina TK loading control plasmid. Transfection procedure followed manufacturer’s instructions. Assay of luciferase activity was done 24 hours after transfection using LightSwitch Dual Assay reagents (Active Motif) and the MicroLumat Plus LB96V (Berthold Technologies) plate luminometer. Relative luciferase units were calculated by subtracting background signal and normalizing Renilla signal to loading plasmid.

Statistics

Statistical analysis and graphical presentations were performed using Microsoft Excel 2010. Significance was calculated using unpaired Student’s t-test. All data shown represent results from 3 or more independent observations, expressed as mean ± SEM.

RESULTS

Tolerance and Galactose both affect metabolism and TNF-α expression

As our lab has previously reported (17, 22), endotoxin tolerance includes two distinct phenotypic characteristics in THP-1 monocytic cells. One characteristic of tolerance is an inability to produce TNF-α mRNA or protein in response to LPS restimulation. The other characteristic is a preference for fatty acid oxidation over glycolysis (8). To test our hypothesis that the latter influences the former, we compared responsive and tolerant cells to those grown in galactose-based media. Literature suggests that when glucose is replaced by galactose in cell culture media, cells use more mitochondrial oxidation and less glycolysis (15, 45, 46). Thus, this model allowed us to separate the metabolic impact of tolerance from its other effects on gene expression.

We first measured expression of TNF in three different culturing conditions: responsive (glucose-based media), tolerant (glucose-based media, prior overnight exposure to 1ug/mL LPS), and galactose-fed (galactose-based, glucose-free media). At the RNA level, we observed no significant difference between responsive vs. galactose-fed cultures, with or without addition of LPS (Fig. 1A). TNF mRNA levels were significantly different in tolerant cultures, in line with previous reports (17). Despite showing no difference in TNF mRNA, however, galactose-fed cultures did show a significant reduction in TNF protein expression, as measured by ELISA (Fig. 1B). Culturing conditions did not appear to significantly impact stability of TNF transcript (Fig. 1C).

Figure 1. Tolerance and Galactose both affect TNF expression.

Figure 1

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A) RT-qPCR assay comparing TNF mRNA expression in responsive, tolerant, and galactose-fed cultures, with or without a 1 hour stimulation of 1ug/mL LPS. Bars show average of 5 independent experiments ± standard error of the mean (SEM). **: p<0.01 compared to responsive counterpart, calculated by unpaired t-test.

B) ELISA assay comparing TNF cytokine expression in responsive, tolerant, and galactose-fed cultures, with or without a 4 hour stimulation with 1ug/mL LPS. Bars show mean of n=3 ± SEM. *: p<0.05; **: p<0.01 compared to responsive counterpart.

C) RT-qPCR assay comparing rates of TNF mRNA decay in responsive, tolerant, and galactose-fed cultures following 1 hour stimulation with 1ug/mL LPS and incubation with 5ug/mL actinomycin D for indicated time. Points represent average of 3 independent experiments, shown as percentage of (−)actinomycin D(0h).

We next compared the differences in glycolysis between cells grown in responsive, tolerant, or galactose-fed culturing conditions. This was done in two ways. Lactate concentration following addition of LPS was measured using a commercial biochemical lactate assay (Fig. 2A). Responsive cells showed the highest concentration of lactate, followed by tolerant and galactose-fed cells, respectively. We also measured the extracellular acidification rate (ECAR) of responsive, tolerant, and galactose-fed cells using the Seahorse XF24 (Fig. 2B). As a measurement of the rate of proton output by live cells, ECAR serves as an indicator of lactic acid production and glycolysis (36). Basal ECAR was the highest in responsive cells, followed respectively by tolerant and galactose-fed cells. Interestingly, responsive cells showed a sharp increase in ECAR after an injection of LPS into the assay wells, while neither tolerant nor galactose cells showed any significant change in ECAR in response to LPS. These differences in lactate (Fig. 2A) and ECAR (Fig. 2B) both indicate that galactose-fed THP-1 cells have a lower rate of glycolysis than their glucose-fed counterparts.

Figure 2. Tolerance and Galactose both affect metabolism.

Figure 2

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A) Lactate assay of responsive, tolerant, and galactose-fed cultures after addition of LPS (n=3 ± SEM).

B) Seahorse XF assay of extracellular acidification rate (ECAR) of responsive, tolerant, and galactose-fed cultures before and after injection of 1ug/mL LPS. Representative graph, n=3.

GAPDH binds to TNF mRNA in THP-1 cells with low glycolysis

Our observation that TNF protein but not mRNA was reduced in galactose-fed cells (Fig. 1A-B) suggests a mechanism of post-transcriptional repression. These data are consistent with our hypothesis that low glycolysis causes GAPDH to bind the AU-rich element of TNF mRNA. To determine if this was the case, we used RNA-immunoprecipitation (RNA-IP) with an anti-GAPDH antibody to probe for an interaction between GAPDH protein and TNF-α mRNA.

Our initial RNA-IP experiments compared responsive, glucose-fed cells with responsive, galactose-fed cells. As shown in Figures 1 and 2, these cultures differed in metabolism, but not TNF mRNA. After stimulation with LPS for 1 hour, significantly more TNF mRNA was pulled down by the GAPDH antibody in galactose-fed cultures than in glucose-fed cultures (Fig. 3A). This indicates greater GAPDH protein-TNF mRNA binding occurs in galactose-fed cells.

Figure 3. GAPDH binds to TNF-α mRNA in galactose-fed cells.

Figure 3

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A) TNF-α mRNA expression in glucose-fed or galactose-fed cells, relative to actin, with or without addition of LPS (1ug/mL) for 1 hour. Both the table and the blackened portions of bars (GAPDH-IP) show percentage of TNF-α mRNA captured by GAPDH antibody during RNA-IP, relative to total RNA as determined from input. Bars show mean, n=5 ± SEM. P-values are compared to glucose-fed counterpart, calculated by unpaired t-test. Non-significant values (p>0.05) not shown.

B) GAPDH mRNA expression of same cells previously described. Bars show mean, n=5 ± SEM. Table and blackened portion of bars (GAPDH-IP) show percentage of GAPDH mRNA captured by GAPDH antibody during RNA-IP. No significant change in GAPDH protein binding to its own RNA was observed, as expected.

C) Western blot of GAPDH, actin in glucose- and galactose-fed cells. Blots are representative of 3 independent observations. No significant difference was observed with media or LPS treatment.

Additionally, GAPDH showed no off-target binding to its own mRNA (Fig 3B). GAPDH mRNA is constitutively expressed and lacks an ARE, making it an unlikely target for GAPDH protein to bind. This made GAPDH mRNA a suitable negative indicator of non-specific RNAs isolated by the RNA-IP. As Figure 3B shows, minimal GAPDH mRNA was pulled down during the RNA-IP. This indicates there is specificity to the GAPDH protein-TNF-α mRNA interaction. To test whether the increase in GAPDH-TNF mRNA binding reflected an increase in total GAPDH protein, we measured GAPDH protein levels by Western blotting (Fig. 3C). We observed no significant change in GAPDH protein concentration in response to galactose-based media, or in response to stimulation with LPS.

Comparison of glucose-fed and galactose-fed cultures indicated that our hypothesized mechanism of metabolism-sensitive RNA binding took place in monocytes, but under idealized and artificial conditions. We next sought to investigate whether it also took place during endotoxin tolerance. Tolerant THP-1 cells show reduced glycolysis (Fig 2A-B) and serve as a model for septic shock (47-49).

To determine if this mechanism participated in tolerance we again used RNA-IP to probe for interactions between GAPDH protein and TNF-α mRNA. Tolerant cultures were stimulated with LPS for 24 hours prior to assay, while responsive cultures were not exposed to any LPS prior to assay.

Real-time PCR analysis of the RNA pulled down by the GAPDH antibody shows GAPDH binds to TNF mRNA in tolerant cells (Fig. 4A). The amount of TNF mRNA bound by GAPDH was significantly greater in tolerant cells than responsive cells, despite the repression of TNF mRNA in tolerant cells. As in the glucose vs. galactose model, no significant off-target binding to GAPDH mRNA is observed (Fig. 4B). We also observed no significant change in total GAPDH protein level (Fig. 4C).

Figure 4. GAPDH binds to TNF-α mRNA in endotoxin tolerant cells.

Figure 4

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A) TNF-α mRNA expression in responsive or tolerant cultures, relative to actin, with or without addition of LPS (1ug/mL) for 1 hour. Both the table and the blackened portions of bars (GAPDH-IP) show percentage of TNF-α mRNA captured by GAPDH antibody during RNA-IP, relative to total RNA as determined from input. Bars show mean, n=4 ± SEM. P-values are compared to Responsive counterpart, calculated by unpaired t-test. Non-significant values (p>0.05) not shown.

B) GAPDH mRNA expression of same cells previously described. Bars show mean, n=4 ± SEM. Table and blackened portion of bars (GAPDH-IP) show percentage of GAPDH mRNA captured by GAPDH antibody during RNA-IP. No significant change in GAPDH protein binding to its own RNA was observed, as expected.

C) Western blot of GAPDH, actin in responsive and tolerant cell cultures. Blots are representative of 3 independent observations. No significant difference in GAPDH density was observed.

GAPDH is responsible for post-transcriptional repression

Our observation that GAPDH binds to TNF mRNA when TNF protein, but not mRNA, is reduced immediately suggests a mechanism of post-transcriptional repression. To test this potential mechanism, we used siRNA to knock down GAPDH expression in both glucose and galactose-fed cells (Fig. 5A). We observed that while the GAPDH knockdown had no significant effect on glucose-fed cells, the knockdown increased production of TNF protein in galactose-fed cells (Fig. 5B). This supports our hypothesis that GAPDH protein limits production of TNF protein in cells with reduced glycolysis.

Figure 5. TNF cytokine expression increases in galactose-fed GAPDH knockdown cells.

Figure 5

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A) Western blot of GAPDH, actin in glucose or galactose-fed cultures, following transfection with either GAPDH or control (ctrl) siRNA. Blots are representative of 3 independent assays.

B) ELISA assay comparing TNF cytokine expression in glucose and galactose-fed cultures following transfection with GAPDH or control (ctrl) siRNA, after 4 hour stimulation with 1ug/mL LPS. Bars show mean of n=3 ± SEM. *: p<0.05 compared to control knockdown counterpart.

We next sought to verify that post-transcriptional repression was, in fact, responsible for the loss of TNF protein. To test this, we used polysome fractioning to determine if TNF mRNA ceased associating with polyribosomes when glycolysis was limited. Lysates from glucose and galactose-fed cells were separated over a 10-45% sucrose gradient and fractionated by density. Polysome fractions were determined by UV absorbance at 254nm (Fig. 6A). We observed that in glucose-fed cells, a greater portion of the TNF mRNA was present in the polysome fractions (Fig. 6B-C). In galactose-fed cells, TNF mRNA was found in less dense fractions, indicating fewer associated ribosomes. Neither media affected the density actin mRNA (Fig. 6D-E).

Figure 6. TNF mRNA is not present in polysomes in galactose-fed cells.

Figure 6

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A) Absorbance of glucose and galactose cultures, following separation by density on sucrose gradient. Gradients were fractionated and measured for absorbance at 254nm to identify 40S, 60S, 80S, and polysome fractions. Graph shows representative of 3 independent experiments.

B) Distribution of TNF mRNA in fractions. Total RNA was extracted from each fraction, then TNF mRNA measured by qPCR. Graph shows representative of 3 independent experiments.

C) Relative portion of TNF mRNA from B found in translated polysome fractions versus non-translated fractions.

D) Distribution of actin mRNA in fractions. Total RNA was extracted and measured by qPCR, as in B. Graph shows representative of 3 independent experiments.

E) Relative portion of actin mRNA from D found in translated polysome fractions versus non-translated fractions.

GAPDH binding to TNF mRNA is sensitive to changes in glycolysis

After demonstrating GAPDH binding to TNF mRNA in two conditions with low glycolysis, we sought to further establish that glycolysis regulated the level of this binding. We also sought to determine whether this binding was reversible. To test this, we treated tolerant THP-1 cells with different substances which alter glycolysis. We then used RNA-IP to study corresponding changes in GAPDH-TNF mRNA binding.

Based on the literature and our past experience, we selected four substances, each with a distinct mechanism of affecting glycolysis (Fig. 7A). To block glycolysis, we used 2-deoxyglucose, an inhibitor of hexokinase and phosphoglucose isomerase (50). To promote glycolysis, we used EX527, a sirtuin 1 (SIRT1) inhibitor which limits the ability of cells to transition from glycolysis to fatty acid oxidation (8); human insulin, which increases glucose uptake and phosphorylation (51, 52); and oligomycin, an ATP synthase inhibitor which blocks mitochondrial ATP production (53) and causes an acute increase in glycolysis.

Figure 7. Glycolysis is subject to artificial manipulation in tolerant THP-1 cells.

Figure 7

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A) Table of drugs used to block or increase glycolysis, with brief description of mechanism.

B) Extracellular acidification rate (ECAR) of Tolerant cell cultures, with or without drug treatments as indicated. Changes in ECAR were consistent with expected effects on glycolysis. Data representative of n=3. **: p<0.01 compared to Tolerant.

The effects of these four substances on glycolysis were verified by Seahorse XF analysis (Fig. 7B). Tolerant cell cultures were treated with 2-DG (5mM, 1 hour before assay), EX527 (5uM, 18 hours before assay), human insulin (100nM, 18 hours before assay), or oligomycin (10uM, 15 minutes before assay) as indicated. Cultures were then lysed and analyzed by RNA-IP. Inhibition of glycolysis using 2-DG resulted in a greater level of TNF-α mRNA in the resulting GAPDH RNA-IP (Fig. 8A). Similarly, promotion of glycolysis with any of the other three treatments decreased the level of TNF mRNA isolated by RNA-IP. This indicates that lowering glycolysis increases GAPDH-TNF mRNA binding, while increasing glycolysis reduces that binding. This reciprocal relationship is predicted by our hypothesis. No significant binding to GAPDH mRNA was observed (Fig. 8B), again indicating that the GAPDH-TNF mRNA interaction is specific. Additionally, we saw no significant change in total GAPDH protein in response to the treatments (Fig. 8C).

Figure 8. GAPDH binding to TNF mRNA is sensitive to changes in glycolysis.

Figure 8

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A) TNF mRNA expression in Tolerant cells, relative to actin, with or without addition of drugs as indicated. Table and shaded portions of bars (GAPDH-IP) show percentage of TNF-α mRNA captured by GAPDH antibody during RNA-IP, relative to total RNA as determined from input. Bars show mean, n=3 ± SEM. P-values are compared to Tolerant, calculated by unpaired t-test.

B) GAPDH mRNA expression of same cells previously described. Bars show mean, n=3 ± SEM. Table and shaded portion of bars (GAPDH-IP) show percentage of GAPDH mRNA captured by GAPDH antibody during RNA-IP.

C) Western blot of GAPDH, actin in tolerant cell cultures, with or without indicated treatments. Blots are representative of 3 independent assays. No significant difference in GAPDH density was observed.

We next explored whether these changes in glycolysis produced measurable changes TNF protein. If GAPDH-TNF mRNA binding truly represents a mechanism of post-transcriptional repression, we would expect that treatments which increase glycolysis and decrease GAPDH-TNF binding would increase TNF protein production. To test this, we measured expression of TNF mRNA and protein in tolerant THP-1 cells treated with either EX527 or insulin vs. untreated. We were unable to use 2-DG or oligomycin here due to higher toxicity and the longer incubation period required for ELISA.

TNF mRNA levels were not increased by addition of insulin or EX527 to tolerant cultures (Fig. 9A), however, we observed small but statistically significant increases in TNF protein levels following treatment with either substance (Fig. 9B). Since the increase in cytokine production cannot be explained by an increase in RNA, it follows that a greater amount of the transcript is translated. This supports our hypothesis that GAPDH binding represses translation of TNF mRNA.

Figure 9. Changes in GAPDH binding TNF mRNA correlate with changes in TNF protein levels in tolerant cells.

Figure 9

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A) RT-qPCR of TNF mRNA, with or without second dose of LPS for 1 hour, expressed as Relative Fold of Tolerant (−)LPS(0h). No significant differences observed. Bars show mean, n=3 ± SEM.

B) ELISA of TNF-α cytokine, with or without second dose of LPS for 22 hours. *: p<0.05 compared to respective tolerant cultures without drug treatment, calculated by unpaired t-test.

Transcripts with the 3’UTR of TNF mRNA are repressed in a metabolism-sensitive manner

Our data indicate that GAPDH-TNF mRNA binding correlates with a decrease in TNF-α protein expression. To further demonstrate that this decrease in cytokine production is due to post-transcriptional repression, we utilized a luciferase reporter system (Fig. 10A). We used plasmids encoding a Renilla luciferase transcript, with or without the TNF 3’UTR present. Since the plasmids contained the same constitutive promoter, and since Renilla luciferase is not affected by ATP, changes in luminescence should be directly attributable to post-transcriptional regulation. We reasoned that if GAPDH-TNF mRNA binding results in post-transcriptional repression, altering glycolysis should alter luciferase signal in a consistent manner.

Figure 10. Transcripts with the 3’UTR of TNF-α mRNA are repressed in a metabolism-sensitive manner.

Figure 10

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A) Schematic of luciferase reporter plasmids used. Plasmids encoded Renilla luciferase, which does not require ATP for luminescence. Transcripts contained either the TNF-α 3’ untranslated region, or had no 3’UTR (Control). Reporter plasmid transcription was controlled by a constitutive promoter (RPL10). Cells were also transfected with a Cypridina loading control plasmid, which uses a different substrate.

B) Relative luciferase activity of reporter plasmids, normalized to loading plasmid. Data shown in log scale. Bars show mean, n=3 ± SEM. *: p<0.05; **: p<0.01 compared to respective tolerant wells without drug treatment, calculated by unpaired t-test

We observed a significant reduction in luciferase signal in tolerant cells transfected with the TNF 3’UTR reporter, compared to those with the control 3’UTR (Fig. 10B). This immediately demonstrated the importance of post-transcriptional repression of TNF, which has been previously shown (25, 26). When cells transfected with the TNF 3’UTR reporter were treated with substances that affected both glycolysis and GAPDH-TNF mRNA binding (Fig. 7B, Fig. 8A), luciferase signal was also affected (Fig. 10B). Addition of 2-DG caused a decrease in luciferase signal, while addition of insulin or oligomycin resulted in increased signal. These results match the RNA-IP data (Fig. 8A) which indicated the treatments respectively increased or decreased post-transcriptional repression of TNF mRNA.

GAPDH binds to TNF-α mRNA in primary cells

After characterizing this mechanism of post-transcriptional repression in THP-1 cells, we tested whether this mechanism was also present in primary human monocytes. Primary monocytes were isolated from whole blood samples collected from healthy donors. Donor monocytes were either cultured overnight in glucose-based media, tolerized ex-vivo, or cultured overnight in galactose-based media. Examination of cell morphology the following day by Brightfield staining showed >90% of isolated cells were monocyte/macrophage cell types (data not shown).

We first measured the effect of our responsive, tolerant, and galactose-fed culturing conditions on glycolysis. As in our THP-1 model, responsive cultures showed the highest level of glycolysis before and after the addition of LPS (Fig. 11A). Tolerant and galactose-fed cell cultures both showed reduced concentration of lactate, indicating a reduced rate of glycolysis.

Figure 11. GAPDH binds to TNF-α mRNA in primary cells.

Figure 11

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A) Lactate assays of primary cells kept in responsive, tolerant, and galactose-fed culturing conditions, before and after addition of LPS (100ng/mL). Points show mean of n=4 ± SEM.

B) ELISA assay comparing TNF cytokine expression of primary cells kept in responsive, tolerant, and galactose-fed culturing conditions, with or without 5 hour stimulation with 100ng/mL LPS. Bars show mean of n=3 ± SEM. *: p<0.05 compared to responsive cells

C) TNF-α mRNA expression in responsive, tolerant, or galactose-fed primary cultures, relative to actin, with or without addition of LPS (100ng/mL) for 1 hour. Both the table and the blackened portions of bars (GAPDH-IP) show percentage of TNF-α mRNA captured by GAPDH antibody during RNA-IP, relative to total RNA as determined from input. Bars show mean, n=5 ± SEM. P-values are compared to responsive culture counterpart, calculated by unpaired t-test. Non-significant values (p>0.05) not shown.

We next determined whether culturing conditions affected production of TNF cytokine. ELISA analysis of cell supernatant revealed cells in Tolerant and Galactose cultures produced less cytokine in response to LPS than their Responsive counterparts (Fig. 11B). These results are consistent with THP-1 results (Fig. 1B), supporting the hypothesis that a similar mechanism was responsible. When analyzed by RNA immunoprecipitation, GAPDH binding to TNF mRNA was confirmed (Fig. 11C). We found significantly greater GAPDH-TNF mRNA binding in Tolerant and Galactose-cultured cells than in Responsive-cultured cells. This difference is particularly prominent when Responsive and Galactose cultures are compared.

DISCUSSION

In this study, we show that TNF mRNA is post-transcriptionally repressed by GAPDH binding to the 3’UTR. As summarized in Figure 12, this mechanism of repression is sensitive to changes in cellular metabolism, specifically the rate of glycolysis. When the rate of glycolysis is high, GAPDH binds TNF mRNA at a relatively low level. If glycolysis is downregulated due to limited availability of glucose or endotoxin tolerance, GAPDH binds TNF mRNA to a greater degree. This binding inhibits translation of the transcript, thus limiting TNF cytokine production.

Figure 12. Experimental model of post-transcriptional repression of TNF-α by GAPDH.

Figure 12

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Schematic of experimental model. Left portion represents high glucose, high glycolysis conditions such as those found in responsive, glucose-fed monocytes. Right portion represents conditions of low glycolysis, such as those found in endotoxin tolerance or in galactose-fed monocytes.

When monocytes are stimulated by a molecule such as LPS, they respond by upregulating transcription of inflammatory genes like TNF-α. The 3’ untranslated region of TNF-α mRNA contains an AU-rich element (ARE). Depending on the cellular environment, GAPDH can bind this ARE and repress translation of the TNF-α mRNA. In our experimental model, the rate of glycolysis determines whether or not TNF-α mRNA is post-transcriptionally repressed by GAPDH.

In a high glycolysis environment, such as the one depicted on the left side of Figure 8, the high concentration of GAPDH’s metabolic substrates outcompetes the interaction between the enzymatic site of GAPDH and the ARE of TNF-α mRNA. With GAPDH occupied with glycolysis, TNF-α mRNA is free to be translated.

In low glycolysis environments, such as the one on the right side of Figure 8, there is a relatively low concentration of metabolic substrates for GAPDH. Without those substrates present, GAPDH is better able to associate with the ARE of TNF-α mRNA. Once bound, translation of the transcript is repressed. This mechanism is likely meant to prevent the production of the TNF-α cytokine when monocytes are not acting as effector cells.

This study further demonstrates that GAPDH binding to TNF mRNA can be reversed by increasing glycolysis. Others have shown that GAPDH metabolic substrates G3P and NAD+ interfere with GAPDH binding to AU-rich elements (10, 14, 15). As neither G3P nor NAD+ is membrane permeable, however, these data were observed in ex vivo experiments or in saponin-permeabilized cells. We believe our approach of reversing binding by increasing glycolysis better illustrates the central role of metabolism in regulating translation.

We propose this mechanism of post-translational repression through GAPDH-TNF mRNA binding represents a way of fine-tuning the inflammatory response. Our data indicate glycolysis affects production of TNF cytokine, although only modestly (Fig. 7). When compared to mechanisms regulating production of TNF mRNA (54), the effects we observe are relatively small. Although this mechanism is not a primary determinant of TNF expression, we argue it makes a unique contribution.

We suggest GAPDH-TNF mRNA binding refines expression of TNF depending on the metabolic environment. We imagine this mechanism of regulation is advantageous in a number of biological situations. For example, endothelial cell responses to TNF signaling allow for immune cell migration to a site of infection (55). Effector immune cells require glucose for effector functions like phagocytosis and generating reactive oxygen species for the respiratory burst (56). Since GAPDH binding limits TNF mRNA translation when glycolysis decreases, we propose this mechanism essentially helps keep the demand for glucose from exceeding the microenvironment supply.

In this report, we describe how glycolysis influences TNF protein expression, through a mechanism not previously observed in monocytes. These findings may have implications for any number of immunometabolic conditions. One such condition of great clinical significance is sepsis. Endotoxin tolerant mechanisms are closely aligned with the immunosuppressed state observed in septic shock (57). This state increases risk of secondary infection and overall patient mortality (58, 59). Following the failure of anti-TNF therapies to decrease patient mortality, there is increasing reason to explore stimulation of the immune system to improve survival patients with severe sepsis or septic shock (60, 61). Our findings underscore the importance of approaching such efforts metabolically, as well as immunologically.

ACKNOWLEDGEMENTS

We would like to acknowledge Mr. David Long and Dr. Michael Seeds for their technical assistance during this project, as well as Dr. Martha Alexander-Miller and Dr. Anthony Molina for their guidance during this project.

This research was supported by NIH grants R01AI079144, R01AI065791, R01GM099807, and R01GM102497.

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