Research ArticleFibrosis

mTORC1 amplifies the ATF4-dependent de novo serine-glycine pathway to supply glycine during TGF-β1–induced collagen biosynthesis

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Science Signaling  21 May 2019:
Vol. 12, Issue 582, eaav3048
DOI: 10.1126/scisignal.aav3048

Glucose supports fibrosis

Transforming growth factor–β (TGF-β) stimulates fibrosis by promoting the differentiation of fibroblasts into collagen-secreting myofibroblasts, a process associated with alterations in cellular metabolism. Selvarajah et al. found that TGF-β1 promoted the expression of glycine biosynthesis genes in primary human lung fibroblasts, which depended on Smad3 signaling and mTORC1-dependent generation of the transcription factor ATF4. ATF4 stimulated the expression of genes encoding the glucose transporter GLUT1 and enzymes for the biosynthesis of glycine from glucose. Interfering with the mTOR-ATF4 axis reduced the incorporation of glucose-derived glycine into collagen in TGF-β1 stimulated fibroblasts. The mTORC1-ATF4 axis therefore enhances the de novo glycine pathway to meet the biosynthetic requirements associated with TGF-β1–induced collagen production and could potentially be therapeutically targeted as an anti-fibrotic strategy.

Abstract

The differentiation of fibroblasts into a transient population of highly activated, extracellular matrix (ECM)–producing myofibroblasts at sites of tissue injury is critical for normal tissue repair. Excessive myofibroblast accumulation and persistence, often as a result of a failure to undergo apoptosis when tissue repair is complete, lead to pathological fibrosis and are also features of the stromal response in cancer. Myofibroblast differentiation is accompanied by changes in cellular metabolism, including increased glycolysis, to meet the biosynthetic demands of enhanced ECM production. Here, we showed that transforming growth factor–β1 (TGF-β1), the key pro-fibrotic cytokine implicated in multiple fibrotic conditions, increased the production of activating transcription factor 4 (ATF4), the transcriptional master regulator of amino acid metabolism, to supply glucose-derived glycine to meet the amino acid requirements associated with enhanced collagen production in response to myofibroblast differentiation. We further delineated the signaling pathways involved and showed that TGF-β1–induced ATF4 production depended on cooperation between canonical TGF-β1 signaling through Smad3 and activation of mechanistic target of rapamycin complex 1 (mTORC1) and its downstream target eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1). ATF4, in turn, promoted the transcription of genes encoding enzymes of the de novo serine-glycine biosynthetic pathway and glucose transporter 1 (GLUT1). Our findings suggest that targeting the TGF-β1–mTORC1–ATF4 axis may represent a novel therapeutic strategy for interfering with myofibroblast function in fibrosis and potentially in other conditions, including cancer.

INTRODUCTION

Fibrosis is the concluding pathological outcome and major cause of morbidity and mortality in many common chronic inflammatory, immune-mediated, and metabolic diseases (1). The perpetual and relentless deposition of a collagen-rich matrix is the cornerstone of the fibrotic response and eventually leads to organ failure and premature death. Despite the rising incidence of fibrotic disease and intense research efforts, there remains a paucity of effective treatment options. Idiopathic pulmonary fibrosis (IPF) is the most rapidly progressing and lethal of all fibrotic diseases and is associated with a median survival of only 3 years from diagnosis (2, 3). Although the approval of pirfenidone and the small-molecule tyrosine kinase inhibitor, nintedanib, for the treatment of IPF represented a watershed moment for the development of anti-fibrotic therapeutics, these agents slow but do not halt disease progression (4, 5). Therefore, there remains a pressing need to identify novel anti-fibrotic therapeutic strategies (6).

Myofibroblasts are the key effector cells responsible for the synthesis and deposition of a collagen-rich extracellular matrix (ECM) during normal wound healing, as well as during the development of pathological tissue fibrosis (7). Myofibroblasts can be derived from multiple cell types, including tissue-resident fibroblasts, and are characterized by the production of α-smooth muscle actin (α-SMA), which assimilates into stress fibers, giving rise to a contractile phenotype [reviewed in (8)]. The excessive accumulation and persistence of these ECM-producing myofibroblasts, as a result of a dysregulated wound healing response perpetuated by a network of proliferation and differentiation signals within a homeostatically dysregulated tissue microenvironment, represent a key common mechanism underlying the development of pathological fibrosis. Myofibroblasts are also integral to the epithelial-mesenchymal cross-talk that characterizes the stromal reaction in epithelial tumors (9), and evidence suggests that the presence of stromal myofibroblasts is generally associated with poor prognosis in solid cancers (10).

Metabolic reprogramming is a hallmark of cancer but is also increasingly recognized to play a key role in dictating cell fate and function in the context of inflammation and immunity (11). Evidence for altered metabolism in the context of fibrosis has also emerged. 18F-fluorodeoxyglucose ([18F]FDG) uptake by positron emission tomography (PET), a commonly used imaging marker of enhanced glycolysis in cancer, has been reported to be increased in patients with IPF (12, 13) and is predictive of progression-free survival (14). Although multiple cell types might be responsible for the increased uptake of [18F]FDG in IPF, glycolysis is increased during transforming growth factor–β1 (TGF-β1)–induced myofibroblast differentiation in vitro, and targeting glycolysis attenuates experimental lung fibrosis in mice (15, 16). However, the mechanisms that regulate metabolic reprogramming in fibrosis remain poorly understood.

The serine-threonine kinase mechanistic target of rapamycin (mTOR) plays a key role in regulating cell metabolism, along with other key cellular processes, including cell cycle progression, proliferation, growth, autophagy, and protein synthesis. mTOR is central to two distinct complexes, mTORC1 and mTORC2, both of which integrate critical environmental and intracellular cues provided by nutrients, energy, oxygen, and growth factors [reviewed in (17)]. mTOR signaling is commonly dysregulated in human disease and has been strongly implicated in coordinating metabolic reprogramming in cancer cells to optimize nutrient uptake and utilization and to meet the biosynthetic needs of proliferative cancer cells (1820). This has led to a major interest in targeting mTOR in the setting of cancer, as reflected by the growing number of mTOR inhibitors that are either approved or in clinical development (17, 21, 22). The most widely used mTOR inhibitors are rapamycin and the rapalogs (rapamycin analogs), but several adenosine 5′-triphosphate (ATP)–competitive mTOR inhibitors are also in advanced clinical development. Whereas the latter block the phosphorylation of all mTORC1 and mTORC2 substrates, rapamycin is a partial mTORC1 inhibitor that preferentially inhibits phosphorylation of target sites that are weakly phosphorylated by mTORC1 [Thr389 of ribosomal protein S6 kinase β-1 (p70S6K) and Ser65 of eukaryotic translation initiation factor 4E–binding protein 1 (4E-BP1)]. In contrast, mTORC1 target sites that are avidly phosphorylated by mTORC1 (Thr37 and Thr46 of 4E-BP1) are largely insensitive to rapamycin treatment (23, 24).

mTOR signaling has also been implicated in fibrosis (2527); however, whether mTOR contributes to the development of fibrosis as a result of its well-recognized immunomodulatory functions or by influencing fibroblast ECM deposition directly is still unclear. Studies from our laboratory provided strong scientific rationale for progressing omipalisib, a potent pan-phosphoinositide 3-kinase (PI3K)–mTOR inhibitor, to a first-in-human proof-of-mechanism trial in patients with IPF (https://clinicaltrials.gov/ct2/show/NCT01725139), based on the potential of this compound to interfere with fibroblast function, including collagen deposition induced in response to the potent fibrogenic mediator, TGF-β1 (28). We further showed that the mTORC1 and 4E-BP1 axis is critical for TGF-β1–induced collagen synthesis in fibroblasts (23). However, the downstream mechanisms by which this axis influences this response remain poorly understood.

In the current study, we used an unbiased bioinformatics approach to identify key transcriptional modules that are induced in human lung fibroblasts in response to TGF-β1 and modulated by mTOR inhibition. We report a critical mechanistic pathway linking mTORC1 activation to altered myofibroblast metabolism through the transcriptional master regulator of amino acid metabolism, activating transcription factor 4 (ATF4), to fuel ECM biosynthesis. These findings shed light on the signaling pathways by which TGF-β1 influences collagen deposition with important implications for the future development of novel therapeutic strategies for multiple conditions associated with the abnormal accumulation of myofibroblasts and excessive matrix deposition.

RESULTS

mTOR enhances expression of glycine biosynthesis genes in TGF-β1–stimulated fibroblasts

We have shown that rapamycin-insensitive mTOR signaling is critical for TGF-β1–induced collagen deposition (23, 28). To define the underlying mechanism, we applied weighted gene coexpression network analysis (WGCNA) using MetaCore to interrogate our existing RNA sequencing (RNA-seq) dataset (GSE102674), which compares the global transcriptomic effect of the highly selective ATP-competitive dual mTORC1 and mTORC2 inhibitor, AZD8055, to the partial mTORC1 inhibitor, rapamycin, in human lung fibroblasts exposed to TGF-β1.

WGCNA revealed 65 independent sets of highly correlated genes (also referred to as coexpression modules). For each of these modules, the measure of central tendency (the eigengene) correlated to a requisite profile showing complete reversal of the TGF-β1 response by AZD8055 and no reversal by rapamycin. This led to the identification of a single module with the highest correlation (r = 0.99) (Fig. 1A). Pathway analysis revealed that this module was enriched for genes encoding components of three amino acid synthesis pathways (serine-glycine, alanine-cysteine, and cysteine-glutamine), with the serine-glycine biosynthesis pathway representing the most enriched pathway (Fig. 1B and table S1). Expression of the serine-glycine biosynthetic pathway genes phosphoglycerate dehydrogenase (PHGDH), phosphoserine aminotransferase 1 (PSAT1), phosphoserine phosphatase (PSPH), and serine hydroxymethyltransferase 2 (SHMT2) was increased after TGF-β1 treatment. This increase was inhibited by AZD8055 treatment, whereas rapamycin had no effect (Fig. 1C), indicating that rapamycin-insensitive mTOR signaling may play a critical role in enhancing the expression of genes involved in serine and glycine biosynthesis in response to TGF-β1 stimulation.

Fig. 1 Identification of a rapamycin-insensitive, mTOR-dependent serine-glycine biosynthetic signature during TGF-β1–induced collagen deposition.

(A) Plot showing scaled gene expression intensities from the rapamycin-insensitive mTOR module eigengene as calculated by WGCNA. The module eigengene is defined as the first principal component of the genes contained within the module and is representative of the gene expression profiles in the module. All expression values have been z-transformed, and signals that are negatively correlated to the module eigengene have been inverted for plotting (n = 4 independent experiments). (B) Bar plot showing the top 10 most significantly enriched pathways for the genes in the rapamycin-insensitive mTOR module. The serine-glycine biosynthesis pathway was most enriched (P = 5.45 ×10−5). (C) Heat map representing the genes from the top 20 most enriched pathways in the rapamycin-insensitive mTOR module, listed in order of the most to the least statistically significant. Genes that map to more than one pathway only appear for the pathway with the most significant P value. Scaled counts were used to generate the heat map, where darker red indicates higher number of counts. The black arrowheads indicate the genes belonging to the glycine metabolism pathway, and the clear arrowhead indicates SLC2A1 (n = 4 independent experiments). (D) Confluent primary human lung fibroblasts (pHLFs) were stimulated with media alone or media plus TGF-β1, and extracts were immunoblotted for the indicated proteins. Representative data are shown (n = 3 independent experiments). (E) Confluent pHLFs were preincubated with media plus vehicle [dimethyl sulfoxide (DMSO)] or AZD8055 and stimulated for 48 hours with or without TGF-β1. Collagen I deposition was assessed by high-content imaging. Half-maximal inhibitory concentration (IC50) value was calculated using four-parameter nonlinear regression. Each data point shown is the mean ± SEM of the fold change to baseline of three technical replicates per condition. Data are representative of three independent experiments. (F) Immunofluorescence staining showing collagen I deposition in pHLFs treated as in (E). Scale bar, 100 μm. DAPI, 4′,6-diamidino-2-phenylindole. (G) Confluent pHLFs were preincubated with media plus vehicle or rapamycin and stimulated for 48 hours with or without TGF-β1. Collagen I deposition was assessed by high-content imaging. Each data point shown is the mean ± SEM of the fold change relative to baseline of three technical replicates per condition. Data are representative of three independent experiments.

The original RNA-seq dataset and our previous work demonstrating a key role for rapamycin-insensitive mTORC1 signaling during TGF-β1–stimulated collagen deposition were generated in pHLFs cultured in standard medium containing 25 mM glucose and 2 mM glutamine (23). Because mTOR is sensitive to environmental signals, including energy and nutrient abundance, and in view of the profound effects of mTOR inhibition on the transcriptome of multiple metabolic genes [reviewed in (29)], we performed all subsequent functional studies at physiological concentrations of glucose (5 mM) and glutamine (0.7 mM). We confirmed that under these conditions, TGF-β1 caused a marked increase in mTORC1 signaling in pHLFs as evidenced by p70S6K(Thr389) and 4E-BP1(Ser65) phosphorylation (Fig. 1D and fig. S1, A and B). TGF-β1 also increased collagen deposition by 251 ± 8.6%, as determined in a well-characterized quantitative assay based on high-content imaging of collagen I immunostaining at 48 hours (Fig. 1, E and F) (28). ATP-competitive mTOR inhibition with AZD8055 attenuated TGF-β1–induced collagen deposition in a concentration-dependent manner with an IC50 of 340 nM (Fig. 1E), whereas rapamycin had no effect (Fig. 1G). We also investigated whether mTOR affected TGF-β1–induced myofibroblast differentiation, based on the assessment of α-SMA by high-content imaging. As expected, TGF-β1 increased fibroblast α-SMA production, but AZD8055 did not block this response (fig. S1, C and D).

In agreement with our RNA-seq dataset, under physiological glucose and glutamine concentrations, the abundances of transcripts encoding all the enzymes involved in serine-glycine biosynthesis—PHGDH, PSAT1, PSPH, and SHMT2—were significantly increased in response to TGF-β1 stimulation at 24 hours (Fig. 2, A to D). In contrast, SHMT1, which preferentially converts glycine to serine (30), was not influenced by TGF-β1 treatment (fig. S1E). The TGF-β1–induced increase in mRNA abundance of the serine-glycine pathway enzymes was sensitive to inhibition by AZD8055 but insensitive to rapamycin treatment (Fig. 2, A to D, and fig. S1, F to I). Evaluation of the effect of TGF-β1 at the protein level confirmed that the rate-limiting enzymes, PHGDH and PSPH, were increased in response to TGF-β1 stimulation at 24 hours and that these increases were inhibited by AZD8055 (Fig. 2, E and F).

Fig. 2 TGF-β1 amplifies the serine-glycine biosynthesis pathway in an mTOR-dependent manner.

Confluent pHLFs were incubated in media alone or media plus TGF-β1 with AZD8055 or vehicle control (DMSO) for 24 hours. (A to D) Quantification of the relative abundance of PHGDH (A), PSAT1 (B), PSPH (C), and SHMT2 (D) mRNAs by real-time quantitative polymerase chain reaction (RT-qPCR). Data are presented as means ± SEM from three technical replicates per condition and representative of three independent experiments. (E and F) Immunoblots of protein lysates and densitometric quantification of PHGDH (E) and PSPH (F). Data are representative of three independent experiments with three technical replicates per condition. Differences between groups were evaluated by two-way analysis of variance (ANOVA) test with Tukey post hoc test. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. a.u., arbitrary units.

mTORC1 promotes ATF4 protein production in TGF-β1–stimulated fibroblasts

We next explored the potential mechanism by which rapamycin-insensitive mTOR signaling promotes the de novo serine-glycine synthesis pathway in response to TGF-β1 stimulation. To this end, we first used overconnected node (OCN) analysis based on the MetaCore database of gene and protein interactions curated from the literature to identify potential master regulators of gene expression. Using the principles of enrichment analysis (Fisher’s exact test), we calculated a P value for each gene in the database by comparing the overlap of its known interactors with the gene list of interest. OCN analysis of the RNA-seq dataset revealed a cluster of transcription factors associated with the serine-glycine metabolism module of enriched mRNAs, including that encoding the transcription factor ATF4 (Fig. 3A). ATF4 is a known mTOR-responsive gene, and ATF4 is a key effector of the stress response that triggers increased gene transcription by binding to the CCAAT/enhancer binding protein (C/EBP)–ATF response element in specific genes, including all enzymes of the de novo serine-glycine synthesis pathway (31, 32). We therefore examined whether ATF4 was the downstream target of mTOR involved in mediating the TGF-β1–induced increase in de novo glycine biosynthesis and collagen deposition.

Fig. 3 mTOR plays a key role in promoting ATF4 protein production.

(A) OCN analysis of the RNA-seq data revealed a cluster of transcription factors associated with the serine-glycine module of enriched mRNAs. (B) Confluent pHLFs were incubated with or without TGF-β1, and the relative abundance of ATF4 mRNA over time was measured by RT-qPCR. (C) Immunoblots and densitometric quantification of ATF4 protein abundance in pHLF lysates over time after TGF-β1 stimulation. The immunoblot shows ATF4 at 8 hours after TGF-β1 addition. (D) Relative abundance of ATF4 mRNA measured 24 hours after TGF-β1 addition. (E) Immunoblot and densitometric quantification of ATF4 abundance at 24 hours after TGF-β1 addition. (F) Immunoblot and densitometric quantification of ATF4 abundance at the indicated times after TGF-β1 addition. (G) Confluent pHLFs were transfected with scrambled control siRNA (small interfering RNA) (siCTRL) or Smad3 siRNA (siSMAD3) and incubated with or without TGF-β1. Relative abundance of ATF4 mRNA at 24 hours was measured by RT-qPCR. (H and I) ATF4 immunoblots and densitometric quantification for samples treated as in (G) analyzed at 8 hours (H) and 24 hours (I). (J) pHLFs were pretreated with TGF-β1 for 13 hours before treatment with lactimidomycin (LTM) plus either vehicle (DMSO) or AZD8055. Lysates were harvested at indicated times after treatment, and ATF4 abundance was measured by immunoblotting and densitometric quantification. (K) pHLFs were modified by CRISPR-Cas9 gene editing of RPTOR or RICTOR and stimulated with TGF-β1. Immunoblot for ATF4 and densitometric quantification were performed at 24 hours. (L) pHLFs expressing a 4E-BP1-4A dominant-negative phospho-mutant were induced with doxycycline or media alone for 24 hours before TGF-β1 stimulation. Immunoblotting for ATF4 and densitometric quantification were performed at 18 hours after TGF-β1 addition. All data are expressed as means ± SEM from three technical replicates per condition and representative of three independent experiments. Differences between groups were evaluated by two-way ANOVA test with Tukey post hoc test (B to I and L), repeated-measures two-way ANOVA (J), or one-way ANOVA with Tukey post hoc test (K). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

We first examined the relationship between ATF4 and TGF-β1 because ATF4 is not known to be a TGF-β1–responsive gene in fibroblasts. ATF4 mRNA abundance was significantly increased by 2.60 ± 0.37–fold and by 2.02 ± 0.12–fold in cells stimulated with TGF-β1 relative to cells treated with media alone at 12 and 24 hours, respectively (Fig. 3B). At the protein level, ATF4 was barely detectable in untreated cells by immunoblotting. In contrast, ATF4 was abundant in TGF-β1–stimulated cells at all time points examined from 8 hours onward (Fig. 3C).

We next examined whether TGF-β1–induced ATF4 was sensitive to ATP-competitive mTOR inhibition. AZD8055 had no effect on TGF-β1–induced ATF4 mRNA abundance (Fig. 3D) but completely blocked ATF4 protein production at all time points examined (Fig. 3, E and F). We also examined the contribution of canonical TGF-β1 signaling through the Smad pathway. Silencing Smad3 using siRNA completely inhibited the increase in ATF4 mRNA abundance at 24 hours and protein production assessed at 8 and 24 hours (Fig. 3, G to I, and fig. S2A). Furthermore, our in silico analysis of the ATF4 promoter for Smad binding sequences using three different web-based platforms identified putative binding sites for Smads 2, 3, and 4 in the ATF4 promoter with a predicted Smad3 binding site located at base pairs −283 to −275 from the transcription start site (fig. S2B). Together, these data led us to conclude that TGF-β1–induced ATF4 production is both Smad3- and mTOR-dependent and that TGF-β1 acts at the transcriptional level, whereas mTOR acts posttranscriptionally.

We next explored the possibility that mTOR might influence ATF4 protein stability. To this end, we assessed the effect of AZD8055 on the rate of decline of ATF4 abundance in the presence of the translation inhibitor lactimidomycin (LTM). Both compounds were added at 13 hours after the onset of TGF-β1 stimulation to allow ATF4 protein to accumulate. ATF4 protein abundance was then monitored at different time points over an hour. These experiments revealed that AZD8055 did not influence the rate at which ATF4 protein abundance declined in the presence of LTM and therefore allowed us to conclude that mTOR did not promote ATF4 protein stability (Fig. 3J and fig. S2C), implying that mTOR may instead promote the accumulation of ATF4 by stimulating ATF4 translation.

We also sought to identify the mTOR complex involved in mediating the TGF-β1–induced ATF4 response. To this end, we generated pHLFs that lacked the mTOR accessory proteins RPTOR or RICTOR by CRISPR-Cas9 gene editing to specifically disrupt either mTORC1 or mTORC2 signaling, respectively. Efficient RPTOR and RICTOR gene editing was confirmed by Western blotting (fig. S2D). TGF-β1–induced ATF4 protein accumulation was significantly reduced in RPTOR-knockout fibroblasts but fully maintained in RICTOR-knockout fibroblasts, indicating that TGF-β1 exerts its stimulatory effects on ATF4 production exclusively through an mTORC1-dependent mechanism (Fig. 3K). We next interrogated the role of 4E-BP1 downstream of mTORC1 by generating pHLFs expressing a doxycycline-inducible 4E-BP1 dominant-negative phospho-mutant in which the mTORC1 phosphorylation sites were replaced by alanine residues, abbreviated as 4E-BP1-4A (23). We have previously confirmed that doxycycline treatment induces 4E-BP1-4A expression in transduced pHLFs and leads to inhibition of cap-dependent translation (23). Here, we found that TGF-β1–induced ATF4 protein production was completely abrogated in pHLFs expressing 4E-BP1-4A (Fig. 3L). These effects were not related to inhibition of ATF4 by doxycycline treatment because doxycycline treatment did not inhibit TGF-β1–induced ATF4 protein production in nontransduced pHLFs (fig. S2E). Together, these data demonstrate that the translation-regulating mTORC1–4E-BP1 axis is critical for TGF-β1–induced ATF4 protein synthesis.

We also examined whether the ATF4 response to TGF-β1 was downstream of the classical stress response involving the activation of protein kinase R–like endoplasmic reticulum kinase (PERK) and subsequent PERK-mediated phosphorylation of eukaryotic initiation factor 2α (eIF2α). However, this possibility was ruled out on the evidence that TGF-β1 had no effect on eIF2α phosphorylation compared to unstimulated fibroblasts over 12 hours (fig. S2F). Furthermore, the PERK inhibitor, GSK2656157, did not inhibit TGF-β1–induced collagen deposition (fig. S2G).

Having demonstrated that ATF4 production is enhanced in TGF-β1–activated myofibroblasts in vitro, we questioned whether this observation holds potential translational importance in the clinical setting of fibrosis in humans. To this end, we used double immunofluorescence to determine whether ATF4 and the myofibroblast differentiation marker α-SMA were coexpressed by the same cells in IPF fibrotic foci, the cardinal lesions and leading edge of the fibrotic response. These studies revealed that ATF4 immunofluorescence was consistently and widely present in the IPF lung and was associated with both α-SMA–positive myofibroblasts within fibrotic foci and in the hyperplastic alveolar epithelial cells overlying fibrotic foci (Fig. 4, A to C). In control lung parenchyma, ATF4 was mainly found in the alveolar epithelium (Fig. 4D). Myofibroblasts are generally not found in normal lung, but high-magnification images of myofibroblasts within IPF fibrotic foci demonstrate that ATF4 in myofibroblasts was localized to both the cytoplasm and the nucleus (Fig. 4, E to H).

Fig. 4 ATF4 colocalizes with α-SMA–positive myofibroblasts within IPF fibrotic foci.

(A to C) Immunofluoresence showing ATF4 (A, green), α-SMA (B, red), and the overlay of ATF4 and α-SMA (C, yellow) in a representative IPF fibrotic focus. The arrow indicates myofibroblasts within the fibrotic focus, and the arrowhead points to the hyperplastic epithelium. (D) Overlay of ATF4 and α-SMA in non-IPF lung tissue. (E to G) Corresponding high-magnification images of ATF4 (E), α-SMA (F), and the overlay (G) in myofibroblasts within the fibrotic focus indicated by the arrow in (A). (H) Mid-level noncomposite confocal overlay image, of the same capture region in (G), showing nuclear localization of ATF4 (green) in an α-SMA–positive myofibroblast cell. All images were counterstained with DAPI (blue). Scale bars, 50 μm (A to D) and 25 μm (E to H). n = 3 patients with IPF; n = 2 control subjects. Representative images are shown.

ATF4-dependent modulation of the serine-glycine pathway is critical for TGF-β1–induced collagen deposition

We next examined whether ATF4 played a role in influencing glycine biosynthesis during TGF-β1–induced collagen deposition. Using chromatin-bound protein fractionation, we first confirmed that ATF4 was predominantly associated with the chromatin fraction in TGF-β1–stimulated cells (Fig. 5A). Silencing ATF4 using siRNA (Fig. 5B) suppressed the TGF-β1–induced increase in PHGDH, PSAT1, PSPH, and SHMT2 transcripts and protein (Fig. 5, C to G, and fig. S3, A to E) as well as TGF-β1–induced collagen deposition (Fig. 5, H to I). To control for potential off-target effects of the siRNA, we also used CRISPR-Cas9 gene editing to knock out ATF4. This approach similarly demonstrated that ATF4-deficient cells were unable to increase collagen production in response to TGF-β1 stimulation (Fig. 5J and fig. S3F). Together, these data suggest that ATF4 mediates the fibrogenic effects of TGF-β1 by enhancing the de novo serine-glycine pathway.

Fig. 5 ATF4-dependent modulation of the serine-glycine pathway is critical for TGF-β1–induced collagen deposition.

(A) Confluent pHLFs were incubated with media plus TGF-β1 or media alone for 8 or 24 hours before cell lysis and separation into cytoplasmic (Cyto), nuclear (Nuc), and chromatin (Chrom) fractions that were immunoblotted for ATF4 and histone H3. (B to F) Confluent pHLFs were transfected with ATF4 siRNA (siATF4) or scrambled control (siCTRL) before exposure to media plus TGF-β1 or media alone. The relative abundances of ATF4, PHGDH, PSAT1, PSPH, and SHMT2 mRNAs were measured after 24 hours by RT-qPCR. (G) Representative immunoblots of protein lysates treated as indicated in (B) to (F). Data are representative of three independent experiments with three technical replicates per condition. (H) Confluent pHLFs were transfected with ATF4 siRNA (siATF4) or scrambled control (siCTRL) before exposure to media plus TGF-β1 or media alone. Collagen deposition was assayed by high-content imaging after 48 hours. Each data point shown is the mean ± SEM of the fold change relative to baseline of three to four technical replicates per condition, and data are representative of three independent experiments. (I) Representative immunofluorescence images showing collagen production by cells in (H). Scale bar, 100 μm. (J) Confluent wild-type and ATF4−/− pHLFs were exposed to media plus TGF-β1 or media alone. Collagen deposition was assayed by high-content imaging after 48 hours. Each data point shown is the mean ± SEM of the fold change relative to baseline of three technical replicates per condition, and data are representative of three independent experiments. Differences between groups were evaluated by two-way (B to F, H, and J) ANOVA test with Tukey post hoc test. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

mTOR amplifies glucose metabolism during TGF-β1–induced fibroblast collagen synthesis through an ATF4-dependent mechanism

In addition to increased expression of genes encoding serine-glycine biosynthetic enzymes, increased substrate availability is also necessary for increased metabolic pathway activity. Glycine can be synthesized de novo from glucose (33), and SLC2A1, which encodes the facilitative glucose transporter GLUT1, was present in the same WGCNA module as the serine-glycine pathway genes and followed the same pattern of induction with TGF-β1, inhibition of induction in the presence of AZD8055, and insensitivity to rapamycin in our RNA-seq dataset (Fig. 1C). We therefore next considered whether rapamycin-insensitive mTOR signaling downstream of TGF-β1 increased glucose uptake to support increased glycine biosynthesis during TGF-β1–induced collagen deposition.

TGF-β1 stimulation of pHLFs led to an increase in glycolytic flux, extracellular acidification rate (ECAR), and oxygen consumption rate (OCR) (Fig. 6, A to C). This was associated with increased glucose uptake, SLC2A1 mRNA abundance, GLUT1 protein production, and expression of genes encoding the glycolytic enzymes 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) and lactate dehydrogenase A (LDHA) (fig. S4, A to E). The TGF-β1–induced collagen response was decreased by 82 ± 11% in media devoid of glucose (Fig. 6D) and by 90 ± 7% in the presence of the glycolytic inhibitor 2-deoxyglucose (2DG) (fig. S4F), indicating that glycolysis was required for TGF-β1–induced collagen deposition. In contrast, the combination of mitochondrial complex I and III inhibitors rotenone and antimycin A had no effect on TGF-β1–induced collagen deposition (Fig. 6E) despite inhibiting the TGF-β1–induced increase in OCR (Fig. 6C). Together, these data led us to conclude that glycolysis, but not mitochondrial respiration, was necessary for TGF-β1–induced collagen deposition.

Fig. 6 mTOR amplifies glucose metabolism during TGF-β1–induced collagen synthesis through an ATF4-dependent mechanism.

(A) Confluent pHLFs were exposed to media plus TGF-β1 or media only for 24 hours. The area under the curve (AUC) of lactate relative to that of glucose in cell supernatants was measured by nuclear magnetic resonance (NMR) spectroscopy at the indicated time points. Data are representative of three independent experiments with three technical replicates per condition. ppm, parts per million. (B and C) Confluent pHLFs were exposed to media plus TGF-β1 or media only for 24 hours. ECAR and OCR were measured using the Seahorse XFe96 assay. Data are representative of three independent experiments with 46 technical replicates per condition. FCCP, carbonyl cyanide p-trifluoromethoxyphenylhydrazone. (D and E) Confluent pHLFs were incubated in glucose-depleted media (D) or preincubated with rotenone and antimycin A (E) before stimulation for 48 hours with or without TGF-β1. Collagen deposition was assessed by high-content imaging. Each data point shown is the mean ± SEM of the fold change relative to baseline of three technical replicates per condition. Data are representative of three independent experiments. (F) Confluent pHLFs were preincubated with AZD8055 or vehicle control (DMSO) before exposure to media plus TGF-β1 or media alone. The AUC of the lactate peak relative to the AUC of the glucose peak in cell supernatant was measured by NMR spectroscopy after 24 hours. Data are representative of three independent experiments with three technical replicates per condition. (G) The ECAR was assayed by Seahorse XF96e after 24 hours with or without TGF-β1 stimulation Data are representative of three independent experiments with three technical replicates per condition. (H to K) Confluent pHLFs were preincubated with AZD8055 or vehicle control before stimulation with TGF-β1 or media alone. Relative mRNA abundances of PFKFB3 at 3 hours after TGF-β1 (H), LDHA (I), and SLC2A1 (J) at 24 hours after TGF-β1 was measured by RT-qPCR. Cell extracts were subjected to immunoblotting and densitometric quantification for GLUT1 (K) (n = 3 independent experiments). (L) Confluent pHLFs were transfected with ATF4 siRNA (siATF4) or scrambled control (siCTRL) and then exposed to media plus TGF-β1 or media only. Relative abundance of SLC2A1 mRNA at 24 hours was measured by RT-qPCR. Data are representative of three independent experiments with three technical replicates per condition. (M) Representative immunoblot and densitometric quantification of GLUT1 in lysates from pHLFs treated as in (L), and data are representative of three independent experiments with three technical replicates per condition. (N) Confluent pHLFs were transfected with PHGDH siRNA (siPHGDH) or scrambled control (siCTRL) and exposed to media plus TGF-β1 or media only for 48 hours. Collagen deposition was assessed by high-content imaging. Each data point shown is the mean ± SEM of the fold change relative to baseline of three technical replicates per condition and is representative of three independent experiments. (O) pHLFs were treated with the PHGDH inhibitor NCT-503 or vehicle control and stimulated with or without TGF-β1 for 48 hours. Collagen deposition was assessed by high-content imaging. Each data point represents the mean ± SEM of the fold change relative to baseline of five technical replicates per condition and is representative of three independent experiments. Differences between groups were evaluated by unpaired t test (B) or two-way ANOVA test with Tukey post hoc test (A and C to O). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Next, we examined the effect of mTOR inhibition on TGF-β1–induced changes in glucose metabolism. ATP-competitive mTOR inhibition with AZD8055 significantly inhibited the TGF-β1–induced increase in glycolytic flux, represented by the ratio of lactate to glucose measured in cell-conditioned media by 1H-NMR spectroscopy (Fig. 6F), and the TGF-β1–induced increase in ECAR (Fig. 6G). However, the TGF-β1–induced increase in the expression of the key glycolytic genes LDHA and PFKFB3 (fig. S4, D and E) was insensitive to AZD8055 treatment (Fig. 6, H and I). In contrast and in agreement with our RNA-seq dataset (Fig. 1C), AZD8055 significantly inhibited the TGF-β1–induced increase in SLC2A1 mRNA abundance and GLUT1 protein abundance (Fig. 6, J and K). The increase in SLC2A1 mRNA abundance was Smad3 dependent but rapamycin insensitive (fig. S4, G and H). Lastly, silencing ATF4 using siRNA inhibited the TGF-β1–induced increase in SLC2A1 mRNA abundance and GLUT1 protein abundance (Fig. 6, L and M).

The observation that AZD8055 attenuated TGF-β1–induced collagen deposition, de novo serine-glycine pathway gene expression, and glucose metabolism led us to speculate that mTOR signaling augmented TGF-β1–induced collagen deposition by providing the glycolytic intermediates required for enhanced glycine and collagen synthesis. PHGDH is the first rate-limiting enzyme in converting 3-phosphoglycerate (3-PG) from glycolysis into 3-phosphohydroxypyruvate (3-PHP). Disrupting PHGDH using siRNA or inhibition of PHGDH with a selective pharmacological inhibitor (NCT-503) (34) blocked TGF-β1–induced collagen deposition (Fig. 6, N and O, and fig. S4I). Moreover, glycine supplementation partially rescued the inhibitory effect of glucose deprivation on TGF-β1–induced collagen deposition by 70 ± 12% (Fig. 7A). Furthermore, glycine supplementation partially rescued the inhibitory effect of AZD8055 on the TGF-β1–induced collagen response by 58 ± 5% (Fig. 7B). In contrast, supplementation with a glycine precursor, serine, did not rescue this inhibitory effect (fig. S5A).

Fig. 7 mTOR promotes glycine biosynthesis from glucose to support TGF-β1–induced collagen synthesis.

(A) Confluent pHLFs were deprived of glucose for 24 hours in the presence or absence of glycine, followed by TGF-β1 stimulation for 48 hours before assessment of collagen deposition by high-content imaging. Each data point shown is the mean ± SEM of the fold change relative to baseline of three technical replicates per condition. Data are representative of three independent experiments. (B) Confluent pHLFs were incubated with AZD8055, supplemented 30 min later with or without glycine, and then incubated with or without TGF-β1 for 48 hours before assessment of collagen deposition by high-content imaging. Each data point shown is the mean ± SEM of the fold change relative to baseline of three technical replicates per condition. Data are representative of three independent experiments. (C) Confluent pHLFs were incubated with AZD8055 or vehicle (DMSO) and exposed to media plus TGF-β1 or media alone in the presence of glucose for 48 hours. Collagen α1(I) was isolated by immunoprecipitation and immunoblotted. (D) Confluent pHLFs were incubated with AZD8055 or vehicle and then exposed to media plus TGF-β1 or media alone in the presence of U-14C-glucose for 48 hours. U-14C-glucose incorporation into immunoprecipitated collagen α1(I) was assessed by scintillation counting. Data are presented as means ± SEM from three technical replicates per condition and are representative of three independent experiments. (E) Confluent pHLFs were incubated with AZD8055 or vehicle and then stimulated with TGF-β1 in the presence of U-14C-glycine for 48 hours. U-14C-glycine incorporation into immunoprecipitated collagen α1(I) was assessed by scintillation counting and expressed relative to immunoprecipitated collagen α1(I) abundance quantified in a parallel immunoblot. Data are presented as means ± SEM from three technical replicates per condition and are representative of three independent experiments. Differences between groups were evaluated by unpaired t test (E) or one-way (A, B, and D) ANOVA test with Tukey post hoc test. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

We also performed experiments with exogenous radiolabeled glucose and glycine to determine whether they are incorporated into collagen α1(I), which was isolated by immunoprecipitation (fig. S5B), in response to TGF-β1 stimulation. After pHLFs were incubated with TGF-β1 and either U-14C-glucose or U-14C-glycine, incorporation of the radiolabel was assessed by scintillation counting of immunoprecipitated collagen. The expected pattern of collagen α1(I) production in fibroblasts exposed to TGF-β1 and the impact of AZD8055 were observed by immunoprecipitation and Western blotting (Fig. 7C). Analysis of U-14C-glucose incorporation into collagen α1(I) mirrored this pattern, with a fivefold increase in U-14C-glucose incorporation into isolated collagen α1(I) in TGF-β1–stimulated fibroblasts compared to unstimulated fibroblasts (Fig. 7D). U-14C-glucose incorporation into collagen α1(I) was reduced to baseline values in TGF-β1–stimulated fibroblasts treated with AZD8055 (Fig. 7D). We also examined whether exogenous U-14C-glycine was incorporated into collagen α1(I) under conditions where the TGF-β1–induced serine-glycine biosynthesis pathway was inhibited by AZD8055. Exogenous U-14C-glycine incorporation into collagen α1(I) was low in TGF-β1–stimulated cells in the absence of AZD8055 but increased sixfold in the presence of AZD8055, indicating that TGF-β1–stimulated fibroblasts used exogenous glycine to mount a collagen response when the de novo serine-glycine pathway was inhibited by AZD8055 (Fig. 7E).

Together, our data support the conclusion that TGF-β1–Smad3 signaling and the mTORC1–4E-BP1 axis cooperate to enhance the production of ATF4, which, in turn, influences key ATF4 target genes to promote the biosynthesis of glycolysis-derived glycine to meet the collagen biosynthetic requirements of TGF-β1–activated myofibroblasts.

DISCUSSION

Excessive ECM deposition by myofibroblasts is a key feature of fibrosis and has also been implicated in promoting cancer progression. Previous data from our laboratory demonstrated a critical role for the mTORC1–4E-BP1 axis during TGF-β1–induced collagen deposition (23). In the present study, we report a critical role for this axis, acting in cooperation with Smad3 to promote the production of ATF4, which, in turn, orchestrates the subsequent transcriptional amplification of the glucose-derived serine-glycine biosynthetic pathway (Fig. 8). As well as furthering our understanding of the signaling and transcriptional events by which TGF-β1 reprograms fibroblast metabolism to promote collagen biosynthesis, these observations have important implications for the development of future therapeutic strategies.

Fig. 8 Model for ATF4-mediated metabolic and biosynthetic network reprogramming to support enhanced collagen biosynthesis in TGF-β1–stimulated myofibroblasts.

TGF-β1–induced activation of the TGF-β receptor complex leads to a Smad3-dependent increase in ATF4 mRNA abundance and mTOR activation. Activated mTORC1–4E-BP1 signaling, in turn, promotes ATF4 protein production through a translational mechanism. ATF4 subsequently promotes the transcription of key serine-glycine pathway genes and SLC2A1 and, therefore, an increase in the abundance of the SLC2A1 gene product, GLUT1. The serine-glycine biosynthesis enzymes and GLUT1 act together to promote glucose-derived glycine biosynthesis to support enhanced collagen synthesis rates in activated myofibroblasts. G6P, glucose 6-phosphate; 3-PG, 3-phosphoglycerate; 3-PHP, 3-phosphohydroxypyruvate; 3-PS, 3-phosphoserine; OXPHOS, oxidative phosphorylation.

WGCNA analysis of our existing RNA-seq dataset comparing the effect of ATP-competitive mTOR inhibition versus rapamycin on TGF-β1–induced human lung fibroblasts provided key insights into the potential mechanism by which mTOR influences collagen deposition. The initial motivation to exploit these pharmacological differences was predicated on previous studies that demonstrated that collagen deposition in activated fibroblasts and mesenchymal cells is sensitive to ATP-competitive mTOR inhibition but not to rapamycin treatment (23, 35, 36). Whereas the latter block phosphorylation of all downstream mTORC1 and mTORC2 substrates, rapamycin preferentially inhibits mTORC1 sites that are weakly phosphorylated by mTORC1 [p70S6K (Thr389) and 4E-BP1 (Ser65)].

The WGCNA module representing the profile of genes modulated by TGF-β1 treatment and sensitive to AZD8055, but insensitive to rapamycin, comprised all four genes encoding the enzymes of the serine-glycine synthetic pathway (PHGDH, PSAT, PSPH, and SHMT2), which were present in the top 20 most correlated genes overall. This finding merited further investigation, given that glycine is present in every third amino acid position of the helical region of collagen molecule and is integral to the composition and stability of its oligomerized triple helical structure (37). The observation that TGF-β1 stimulated the serine-glycine biosynthetic pathway to provide additional glycine needed for increased collagen synthesis is further in agreement with a report that TGF-β stimulates de novo serine biosynthesis in fibroblasts (38) and with the observation that pharmacologic inhibition of PHGDH attenuates fibrogenesis in vivo and reduces TGF-β1–induced collagen deposition in vitro (39).

In cancer cells, it is well established that mTORC1 and its downstream substrate 4E-BP1 play critical roles in regulating metabolic pathways through the eukaryotic initiation factor 4F (eIF4F) complex–dependent translation of key transcription factors, including hypoxia-inducible factor 1α (HIF1α) and c-MYC (40). In our study, OCN identified several potential transcriptional regulators of interest, including ATF4. ATF4, a basic leucine zipper transcription factor, is a transcriptional master regulator of amino acid metabolism and stress responses and is classically enhanced as part of the integrated stress response as a result of the activation of kinases, such as PERK and eukaryotic translation initiation factor 2 alpha kinase 4 (GCN2), that phosphorylate the translation factor eIF2α, leading to global reduction in mRNA translation except for select mRNAs, including ATF4 (41, 42). ATF4, in turn, increases gene transcription by binding to the C/EBP-ATF response element in the promoters of specific target genes (4345). However, to the best of our knowledge, ATF4 had not previously been linked to TGF-β1–induced collagen deposition.

In our fibroblast studies, we provide evidence that TGF-β1 increases ATF4 production through the cooperation of both canonical Smad3 and mTOR signaling pathways. Combining data obtained from kinetic studies of the signaling response with our data obtained in function-blocking studies based on pharmacological inhibition (AZD8055), siRNA for Smad3 and ATF4, CRISPR-Cas9 gene editing of RICTOR and RPTOR, and 4E-BP1 phospho-mutants, we propose a model in which the Smad3 pathway plays a critical role in regulating ATF4 mRNA abundance in an mTOR-independent manner, whereas the mTORC1–4E-BP1 axis is critical for ATF4 translation. Moreover, the early increase in ATF4 protein abundance is likely explained by the Smad3-dependent, mTOR-mediated translation of existing ATF4 mRNA and is consistent with our previous report that Smad3 is critical for TGF-β1–mediated mTORC1 activation (23). This model is also consistent with our subsequent in silico analysis of the ATF4 promoter for Smad binding sequences. Furthermore, the activation of ATF4 in the absence of the eIF2α kinase–mediated integrated stress response has also been reported in mouse embryonic fibroblasts (46).

To the best of our knowledge, a key role for the mTORC1–4E-BP1 axis in mediating the stimulatory effects of TGF-β1 on ATF4 translation has not been previously reported but is in agreement with reports demonstrating a role for either mTORC1 (46) or both mTORC1 and 4E-BP1 (47) in regulating the translation of ATF4 in other cell contexts. ATF4 gene disruption further demonstrated that ATF4 was necessary for TGF-β1–induced collagen deposition. Together with our previous report showing a role for mTORC1 and 4E-BP1 during TGF-β1–induced collagen deposition (23), the data herein provide strong evidence for a key role for ATF4 downstream of the mTORC1–4E-BP1 axis in mediating the potent fibrogenic effects of TGF-β1.

In terms of potential relevance of our findings to the human disease setting, we further provide evidence that ATF4 is present in α-SMA–positive myofibroblasts within IPF fibrotic foci, as well as in the overlying epithelium. This latter observation is broadly in agreement with a previous report focusing on the role of ATF4 in the context of epithelial endoplasmic reticulum stress and apoptosis in IPF using a polyclonal antibody against ATF4 (48). The ATF4 staining pattern in control lung is predominantly epithelial and is in agreement with the pattern reported in the Human Protein Atlas (https://www.proteinatlas.org/ENSG00000128272-ATF4/tissue/lung). Our data therefore extend our current understanding of the role of ATF4 in the transcriptional regulation of the serine-glycine pathway beyond the cancer setting, where this pathway has been strongly implicated in supporting cell growth and proliferation, as well as clinical aggressiveness in non–small cell lung cancer (32, 49).

We also herein provide evidence for the importance of both mTOR and ATF4 in regulating TGF-β1–induced increases in glycolysis. The first enzyme of the serine-glycine biosynthetic pathway (PHGDH) converts the glycolytic intermediate 3-phosphoglycerate (3-PG) to 3-phosphohydroxypyruvate (3-PHP). Previous studies have shown that glycolysis is increased in myofibroblasts (16, 38), but whether mTOR signaling in response to TGF-β1 stimulation contributes to this glycolytic response in fibroblasts was not known. We confirmed that TGF-β1–stimulated myofibroblasts adopt a glycolytic phenotype and provide further evidence that mTOR signaling plays a critical role in mediating these metabolic changes. However, although the mTOR-ATF4 axis was found to stimulate the expression of SLC2A1 transcripts and GLUT1 protein, we found no role for mTOR in regulating the expression of the TGF-β1–induced glycolytic genes PFKFB3 and LDHA. The finding that TGF-β1 promotes GLUT1 production is in agreement with a previous study in the context of the autocrine activation of the receptor tyrosine kinases, platelet-derived growth factor and epidermal growth factor receptors, in murine embryonic ankyrin repeat domain-containing protein 2B (AKR-2B) fibroblasts stimulated with high concentrations of TGF-β1, although in this context, the increase in GLUT1 was attributed to mTORC2 rather than to mTORC1 signaling (50). In terms of linking enhanced glycolysis to TGF-β1–induced collagen deposition, extracellular glycine supplementation partially rescued the inhibitory effect of glucose deprivation, as well as mTOR inhibition, on TGF-β1–induced collagen deposition. An enhanced demand for glucose to meet the biosynthetic demands of collagen production after TGF-β1 stimulation is further supported by our observation that U-14C-glucose incorporation into collagen I was increased in TGF-β1–stimulated fibroblasts. U-14C-glycine tracing experiments further demonstrated that exogenous glycine enabled fibroblasts to generate a TGF-β1–induced collagen response when the de novo serine-glycine pathway was suppressed by mTOR inhibition with AZD8055. Together, these data support the notion that mTOR promotes glycolysis to generate the necessary glycine to support enhanced collagen production. The observation that ATF4 mediates the stimulatory effects of TGF-β1 on SLC2A1 expression is further potentially in agreement with a previous study that identified two enhancer binding elements in the regulatory elements of the SLC2A1 gene that contain the same cyclic adenosine monophosphate response element consensus binding site shared by ATF4 (51).

The mechanism by which mTOR influences glycolysis in myofibroblasts contrasts with its role in cancer cells, where mTOR has been reported to promote the expression of multiple glycolytic genes by enhancing the translation of HIF1α and c-MYC (5254). Although there is a degree of mechanistic overlap between cancer and fibrosis, the mutational landscapes are very different. mTOR is one of the most frequently mutated signaling hubs in cancer as a consequence of PI3K amplification or mutation; PTEN (phosphatase and tensin homolog) loss of function; AKT overexpression; or S6 kinase 1, 4E-BP1, or eIF4E overexpression (55). In contrast, mTOR pathway activation is likely to be a consequence of the altered tissue microenvironment in pathological fibrosis and in the stromal response in cancer, because in both settings, fibrogenesis is generally considered a reactive rather than a malignant process (56, 57). Although the mechanism is not known, IPF myofibroblasts have been reported to display evidence of PTEN deficiency (58).

In contrast to an absolute requirement for extracellular glucose, mitochondrial respiration was found to be dispensable for TGF-β1–induced collagen deposition, suggesting that glycolytic flux in response to TGF-β1 stimulation is sufficient to meet both the biosynthetic and energetic requirements of the complex multistage process of collagen biosynthesis in primary adult lung fibroblasts over the course of our experiments (48 hours). In addition, increased mitochondrial biogenesis has been reported to be important for the maintenance of the differentiated and contractile myofibroblast state in the fetal lung fibroblast line IMR-90 (15). These studies report that the TGF-β1–induced production of the matrix glycoprotein fibronectin also did not depend on mitochondrial biogenesis. We further provide herein evidence that mTOR inhibition does not interfere with TGF-β1–induced myofibroblast differentiation, which is also in agreement with a previous report (59). Together, a picture now seems to be emerging in which TGF-β1–induced fibroblast differentiation and matrix synthesis, the two cardinal features that define the myofibroblast phenotype, may have distinct metabolic requirements that could be targeted separately or in combination to slow both the restrictive physiologic impairment and the gas exchange impairment that characterize the fibrotic lung in IPF.

In conclusion, we present a mechanistic model in which ATF4 reconfigures the fibroblast biosynthetic and metabolic network to meet the collagen synthetic demands of highly activated myofibroblasts after TGF-β1 stimulation. As well as providing insight into the signaling and transcriptional pathways by which the major pro-fibrotic mediator TGF-β1 exerts its pro-fibrotic effects, our findings suggest that targeting the mTORC1-ATF4 axis might represent a novel approach for the future development of anti-fibrotic strategies.

MATERIALS AND METHODS

Primary human fibroblast culture

pHLFs were grown from explant cultures of healthy control lung tissue, as previously described (60). Human tissues were sourced ethically, and their research use was in accord with the terms of informed consents. Institutional research ethics committee approval for this work was obtained from the University College London (UCL) Research Ethics Committee (12/EM/0058). To avoid exposing cells to supraphysiological glucose and glutamine concentrations in standard Dulbecco’s modified Eagle’s medium (DMEM), pHLFs (passages 4 to 8) were cultured in glucose and glutamine-free DMEM (Thermo Fisher Scientific) that was supplemented with 10% fetal calf serum (FCS) (Sigma-Aldrich), 5 mM glucose, 0.7 mM glutamine (Thermo Fisher Scientific), and 1% penicillin (100 U/ml)–streptomycin (100 μg/ml) (Thermo Fisher Scientific) (referred throughout the manuscript as “growth media”). All fibroblast cultures tested negative for mycoplasma.

A pHLF cell line expressing a dominant-negative mutant form of 4E-BP1 was generated as described previously (23). Cells were selected with puromycin (2 μg/ml) (Sigma-Aldrich) for 4 days. Expression of the mutant 4E-BP1 was induced with doxycycline (1 μg/ml) (Sigma-Aldrich) for 24 hours before treatment with or without TGF-β1. After 24 hours, pHLF lysates were analyzed for ATF4 abundance by immunoblotting.

Real-time qPCR analysis of gene expression

Total RNA was extracted from adherent cells using the RNeasy Mini kit (Qiagen) according to the manufacturer’s instructions. Real-time PCR was performed using a Mastercycler ep realplex gradient S (Eppendorf). Specific primers were designed to detect the expression of various genes (table S2). PCR amplification was carried out for 40 cycles at a melting temperature of 95°C for 15 s and an annealing temperature of 60°C for 60 s. A dissociation curve was analyzed for each PCR experiment to assess primer-dimer formation or contamination. Relative expression was calculated using 2−ΔCt, and ΔCt was calculated from the mean of two reference genes, ATP5B and β2 microglobulin (PrimerDesign Ltd.).

Immunoblotting

Adherent fibroblasts were washed with ice-cold phosphate-buffered saline and then lysed using PhosphoSafe extraction reagent (Merck Millipore) supplemented with protease inhibitor (Merck Millipore). Equal protein quantities of lysate were separated by SDS–polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to nitrocellulose, and protein levels were assessed by Western blotting with the following antibodies: p70S6K [Cell Signaling Technology (CST) #9202], phospho-p70S6KThr389 (CST #9234), 4E-BP1 (CST #9644), phospho-4E-BP1Ser65 (CST #9451), SMAD3 (CST #9523), Rictor (CST #2114), Raptor (CST #2280), GLUT1 (Abcam #EPR3915), PHGDH (CST #13428), PSAT (Thermo Fisher Scientific #PA522124), PSPH (Insight Biotechnology #GTX109163-S), SHMT2 (CST #12762), ATF4 (CST #11815), α-tubulin (CST #9099), histone H4 (Abcam #16483), phospho-eIF2α (Ser51) (CST #3597), and eIF2α (#9722). The dilutions of primary and secondary antibodies were according to the manufacturer’s instructions. Tunicamycin (2 μg/ml; MP Biomedicals) was used as a positive control for immunostaining of p-eIF2α. Protein band intensity was measured by densitometry in ImageQuant TL v8.1 (GE Healthcare) after electrochemiluminescence. All densitometries are presented relative to α-tubulin unless otherwise stated.

Determination of collagen type I deposition by high-content imaging

Extracellular collagen biosynthesis was measured in 96-well format by a high-content imaging–based macromolecular crowding assay as described previously (23). Briefly, confluent pHLFs were cultured in DMEM containing 0.4% FCS, 5 mM glucose, 0.7 mM l-glutamine, and ascorbic acid (16.6 μg/ml) in the presence of mixed Ficoll 70 and Ficoll 400 to facilitate molecular crowding. After serum starvation for 24 hours, pHLFs were treated in the presence or absence of TGF-β1 (1 ng/ml) (R&D Systems) with compounds AZD8055 (1 μM used unless otherwise stated; supplied by GSK), rapamycin (100 nm used unless otherwise stated; Millipore), NCT-503 (20 μM; Sigma-Aldrich), GSK2656157 (Cambridge Bioscience), 2DG (3 mM used; Sigma-Aldrich), or vehicle (0.1% DMSO). For rescue experiments, glycine (450 μM; Sigma-Aldrich) and serine (Sigma-Aldrich) were used. After 48 hours, pHLFs were methanol-fixed and stained with antibodies to either human collagen I (Sigma, C2456) or α-SMA (Thermo Fisher Scientific, M085101-2) followed by Alexa Fluor 488 secondary antibody (Life Technologies, A11001) and nuclear DAPI counterstain. Fluorescent signal was captured and quantified using ImageXpress Micro XLS high-content imaging system at 20× magnification (Molecular Devices), with four fields of view imaged per well and signal intensity normalized to cell count.

Histology and immunohistochemistry

All human samples were obtained with informed signed consent and with research ethics committee approval (10/H0504/9, 10/H0720/12, and 12/EM/0058). Patients with IPF were diagnosed in accordance with current international guidelines (61). Immunostaining for ATF4 and α-SMA was conducted on 10-μm formalin-fixed paraffin-embedded serial sections of human lung biopsy material (n = 3 patients with IPF and n = 2 control subjects). Confocal dual immunofluorescence for ATF4 (Sigma, WH0000468M1) was enhanced with streptavidin conjugated with Alexa Fluor 488 (Thermo Fisher Scientific) and colocalized with primary goat polyclonal α-SMA (Thermo Fisher Scientific #PA5–18292) labeled with donkey anti-goat Alexa Fluor 647 (Abcam) and counterstained with DAPI. Digitized images were captured on a Leica DM6000 CS microscope fitted with a Leica TCS SP8 confocal head and the Leica LAS X software suite (Leica Microsystems GmbH). All images are representative, and final images were prepared with ImageJ.

NMR spectroscopy

pHLFs were seeded in six-well plates at 2 × 105 cells/ml and incubated in growth media for 3 days. Media were then replaced with serum-free media, and cells were further cultured for 24 hours, at which point they were treated with or without TGF-β1 at 1 ng/ml. Cell supernatant was then collected and supplemented with 10% D2O for shift lock and 1 mM total soluble protein (TSP) standard (Sigma). Using a 500-MHz Bruker machine, 1H-spectra were obtained using a presaturation method after 128 scans. The resulting spectra were analyzed using ACD Labs software (Advanced Chemistry Development UK Ltd.), and integrals of the 5.2 ppm peak and 1.3 ppm peak, corresponding to glucose and lactate, respectively, were quantified relative to the internal TSP peak (0 ppm) standard.

3H-2DG uptake

pHLFs were seeded in six-well plates at 1 × 105 per ml and incubated in growth media for 3 days. Media were then replaced with serum-free media for 24 hours. The next day, cells were treated with or without TGF-β1 at 1 ng/ml. After 22 hours of stimulation, media were changed to glucose-free media for 2 hours. Cells were then washed with 0.5 ml of Krebs-Ringer-Hepes (KRH) buffer. Cells were incubated in KRH buffer (2 ml per well) that contained 5 mM 2DG and 2-deoxy-[3H]glucose (0.625 μCi per well) (PerkinElmer) for 5 min. The cells were washed four times with KRH buffer and lysed with 0.05 mM NaOH for 2 hours at 37°C. Incorporated radioactivity in the cell lysate was determined by liquid scintillation counting.

Assessment of extracellular acidification and oxygen consumption

The Seahorse Bioscience XFe96 extracellular flux analyzer was used to measure OCR and ECAR. Briefly, pHLFs were seeded in XFe96 microplates at 1 × 105 per well and incubated for 3 days in growth media. Media were then replaced with DMEM containing 0.4% FCS for 24 hours. The next day, cells were treated with or without TGF-β1 at 1 ng/ml, in the presence (or absence) of AZD8055. The following day, media were replaced with assay media prewarmed to 37°C supplemented with 5 mM glucose, 0.7 mM glutamine, and 1 mM pyruvate (Sigma, S8636). Measurements of OCR and ECAR were performed after equilibration in assay medium (lacking supplemental CO2) for about 45 min. Oligomycin (Sigma, O4876), FCCP (Sigma, C2920), antimycin A (Sigma, A8674), and rotenone (Sigma, R8875) were added to perform a mitochondrial stress test as per the manufacturer’s instructions.

Transcriptomic analysis by RNA-seq

Confluent fibroblast monolayers were untreated (“media alone”) or stimulated with TGF-β1 (and media) (1 ng/ml; porcine origin; R&D Systems, USA) for 24 hours with or without AZD8055 (1 μM; synthesized and provided by GSK) or rapamycin (100 nM; Merck Chemicals) in standard DMEM (n = 4 biological replicates per condition). Total RNA was extracted with miRCURY RNA Isolation Kit (Exiqon). Polyadenylate-tailed RNA enrichment and library preparation were performed using the KAPA Stranded mRNA-Seq Kit with KAPA mRNA Capture Beads (KAPA Biosystems, Wilmington, MA, USA). Paired-end RNA-seq was performed with the NextSeq sequencing platform (Illumina, San Diego, CA, USA). Read preprocessing and alignment to the genome (Homo sapiens UCSC hg19) were performed using STAR aligner. Counts were normalized using the R package DESeq2, then log2-transformed with an offset of 1, and filtered to remove genes with an average count <1 across all samples. This left 15,959 genes that were then interrogated using the WGCNA package in R. Briefly, gene coexpression similarity was estimated by generating an absolute Pearson product moment correlation matrix. Using a soft threshold of 20, an adjacency matrix was calculated and used to estimate the topological overlap and assign genes to modules. Highly correlated modules were merged using a cut height of 0.06 on the topological matrix dendrogram. Sixty-five modules were returned and assigned colors as names. MetaCore (Thomson Reuters) was used to run pathway enrichment analyses and interaction network analyses on each of the 65 modules. OCN analysis was performed using the MetaBase R packages licensed from Clarivate Analytics and identifies one-step away direct regulators of the dataset that are statistically overconnected with the objects from the dataset. The P value of overconnectivity was calculated using hypergeometric distribution.

In silico prediction of SMAD2/3/4 binding sites in the ATF4 promoter

The ATF4 promoter sequence was obtained from the eukaryotic promoter database (EPD) (Homo sapiens version 6; https://epd.vital-it.ch/human/human_database.php) (62). SMAD2/3/4 binding site prediction was performed using web-based applications: EPD Search Motif Tool (using a cutoff P value of 0.001), PROMO (http://alggen.lsi.upc.es/cgi-bin/promo_v3/promo/promoinit.cgi?dirDB=TF_8.3) (63) (selecting eukaryote for factor’s and site’s species), and ConTra V3 (http://bioit2.irc.ugent.be/contra/v3/#/step/1) (64) (selecting visualization as type of analysis, human as reference organism, and ATF4 sequence under identification number NM_182810). The consensus binding site was obtained from the JASPAR database (http://jaspar.genereg.net/matrix/MA0513.1/).

ATF4 protein stability

Lysates were prepared from pHLFs stimulated with TGF-β1 (1 ng/ml) for 13 hours before pretreatment with DMSO or LTM (1 μM; Merck Millipore #506291) for 5 min, followed by exposure to DMSO or AZD8055 (1 μM) for 0, 10, 20, 30, or 60 min before lysis. Immunoblotting was used to analyze the abundance of ATF4 normalized to α-tubulin.

Chromatin-bound protein fractionation

Cell lysis and cytosolic extraction were performed following the manufacturer’s instructions (NE-PER, Thermo Fisher Scientific). Nuclear extraction was performed by cell lysis in Buffer B (3 mM EDTA, 0.2 mM EGTA, 1 mM dithiothreitol, and protease inhibitor cocktail) for 30 min, followed by separation of soluble (nucleosoluble) and pellet (chromatin-bound) fractions by centrifugation at 1700g at 4°C for 5 min. Chromatin-bound protein pellet was washed in Buffer B before resuspension in Laemmli buffer [4% SDS, 20% glycerol, 10% 2-Mercaptoethanol (2-ME), 0.004% bromophenol blue, and 0.125 M tris-HCl].

RNA interference

For the determination of collagen deposition by molecular crowding assay, pHLFs were grown to confluence in our standard growth media in 96-well plates. During the serum starvation period in growth media containing 0.4% FCS, cells were transfected with 10 nM siRNAs (Dharmacon, SMARTpool) targeting ATF4, PHGDH, and SMAD3 using RNAiMAX Lipofectamine (Invitrogen) according to the manufacturer’s instructions. The following day, the media were replaced by Ficoll-containing media, and the macromolecular crowding assay was performed as described above.

For Western blotting and qPCR experiments, confluent pHLFs in 12-well plates were starved in serum-free media and transfected with 10 nM siRNA (Dharmacon) using RNAiMAX Lipofectamine (Invitrogen) according to the manufacturer’s instructions. The following day, the media were replaced with fresh serum-free media with or without TGF-β1 (1 ng/ml) for the indicated time points.

CRISPR-Cas9 gene editing

pHLFs were electroporated with a CRISPR ribonucleoprotein complex using the 4D-Nucleofector System (Lonza). The guide RNA (gRNA) sequence targeting ATF4 (AGGTCTCTTAGATGATTACCTGG), RPTOR exon 26 (CCGCGTCTACGACACAGAAGGATGG), or RICTOR exon 29 (AATATCGGCTCATCAAATTGGGG) was designed using a combination of previously published work (47), the DeskGen design platform (https://www.deskgen.com/landing/#/documentation), and the Integrated DNA Technologies online tool (https://eu.idtdna.com/site/order/designtool/index/CRISPR_CUSTOM). A predesigned control gRNA sequence (Integrated DNA Technologies) was used to generate matched wild-type pHLFs.

Incorporation of U-14C-glucose and U-14C-glycine into collagen I

pHLFs were grown to confluence in 12-well plates and quiesced in serum-free media for 24 hours. Cells were then incubated in fresh serum-free media containing 5 mM 12C-glucose with or without 2 μCi U-14C-D-glucose (1 nM; PerkinElmer). For glycine tracing studies, media containing 1 mM 12C-glycine, 1 mM 12C-glycine plus 2 μCi U-14C-glycine (3.9 nM; PerkinElmer), or media alone were added to cells with either AZD8055 (1 μM) or vehicle (0.1% DMSO). For TGF-β1–treated cells, TGF-β1 was added at 1 ng/ml. After 48 hours, cell layers were lysed [lysis buffer: 300 mM NaCl, 10 mM tris (pH 7.4), 1% NP-40, and protease inhibitor] and precleared with protein G agarose beads (CST #37478) for 4 hours at 4°C. Cleared lysates were immunoprecipitated with 1 μg of anti-collagen α1(I) primary antibody (CST #84336) followed by protein G agarose bead incubation overnight at 4°C. Immunoprecipitated material was then eluted in lithium dodecyl sulfate (LDS)–containing sample buffer at 93°C for 5 min and incorporated radioactivity in the eluate determined by liquid scintillation counting in a Beckman Coulter LS6500 using Ecoscint A (National Diagnostics) scintillation fluid. pHLF lysates incubated with corresponding treatments in the presence of 12C-glucose or 12C-glycine were also subjected to SDS-PAGE, transferred to polyvinylidene difluoride, and immunoblotted to determine collagen α1(I) abundance. To demonstrate immunoprecipitation efficiency, representative input (10%) and unbound (10%) portions were immunoblotted for collagen α1(I) alongside immunoprecipitated protein, antibody alone (0.4 μg), and beads alone (10% slurry).

Statistical analysis

All data are expressed as means ± SEM, and figures were constructed using GraphPad Prism version 7.00. All experiments were repeated at least three times. Statistical differences between two groups were analyzed using a standard two-tailed t test (assuming unpaired datasets and unequal variances). When more than two groups were compared, either one-way or two-way ANOVA was used with post hoc application of the Tukey method. Four-parameter nonlinear regression analyses were used to generate IC50 values from concentration-response curves. The alpha level was set at 0.05 for all tests (GraphPad Prism).

SUPPLEMENTARY MATERIALS

stke.sciencemag.org/cgi/content/full/12/582/eaav3048/DC1

Fig. S1. Lack of effect of mTOR inhibition on α-SMA induction and the serine-glycine biosynthetic pathway, respectively.

Fig. S2. Knockdown and knockout controls and evidence that TGF-β1 stimulation in fibroblasts is not associated with PERK activation.

Fig. S3. ATF4 knockdown abrogates the TGF-β1–induced increase in glycine biosynthesis enzymes.

Fig. S4. TGF-β1 stimulation increases glucose uptake and abundance of SLC2A1 transcripts, GLUT1, and glycolytic enzymes.

Fig. S5. Exogenous serine does not rescue the inhibitory effects of ATP-competitive mTOR inhibition on TGF-β1–induced collagen deposition.

Table S1. MetaCore pathways enriched in the rapamycin-insensitive mTOR module.

Table S2. Primer sequences.

REFERENCES AND NOTES

Acknowledgments: We acknowledge helpful discussions with L. Edwards (GSK), J. MacRae (Francis Crick Institute), and S. Marciniak (Cambridge Institute for Medical Research) and give thanks to H. Jones (UCL Digital Media) for assistance with the production of data figures. Funding: The authors gratefully acknowledge major funding support received for this work from the NIHR University College London Hospitals Biomedical Research Centre/NIMR (training fellowship to B.S.) and Fonds de la Recherche en Santé—Québec (training fellowship to I.A.). Support was also received from the Medical Research Council, UK (training fellowship MR/K024078/1 to H.V.W.), the Biotechnology and Biological Research Council (BBSRC), and GlaxoSmithKline (GSK) (iCASE studentships BB/M502844/1 and BB/P504440/1 awarded to R.C.C.). R.C.C. acknowledges funding from GSK under a collaborative framework agreement. D.A.’s laboratory was funded by the MRC (MC_UP_1202/1) and by the Francis Crick Institute, which receives its core funding from Cancer Research UK, the UK Medical Research Council, and the Wellcome Trust (FC001033). Author contributions: Conceptualization: R.C.C., B.S., I.A., and D.A.; methodology: R.C.C., P.F.M., D.A., G.B., and A.D.B.; investigation: B.S., I.A., M.P., D.G., H.V.W., G.C., E.J.F., P.F.D., R.R., and M.R.; writing (original draft): B.S., I.A., and R.C.C.; writing (review and editing): R.C.C. and D.A.; funding acquisition: R.C.C., D.A., B.S., I.A., P.F.M., and A.D.B.; data curation: A.T.; resources: R.C.C. and G.B.; supervision: R.C.C. and D.A. Competing interests: R.C.C. declares receiving research funding for some of this work from a collaborative framework agreement from GSK. A.T., G.B., and A.D.B. are employees of GlaxoSmithKline with a commercial interest in the area of investigation. Data and materials availability: The RNA-seq dataset has been deposited in the Gene Expression Omnibus database (www.ncbi.nlm.nih.gov/geo/) with the identifier GSE102674. All other data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials.
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