# Dietary intake and glutamine-serine metabolism control pathologic vascular stiffness

Nesrine S Rachedi, Ying Tang, Yi-Yin Tai, Jingsi Zhao, Caroline Chauvet, Julien Grynblat, Kouamé Kan Firmin Akoumia, Leonard Estephan, Stéphanie Torrino, Chaima Sbai, et al.

► To cite this version:

Nesrine S Rachedi, Ying Tang, Yi-Yin Tai, Jingsi Zhao, Caroline Chauvet, et al. Dietary intake and glutamine-serine metabolism control pathologic vascular stiffness. Cell Metabolism, 2024, 36 (6), pp.1335-1350.e8. 10.1016/j.cmet.2024.04.010. hal-05267388

HAL Id: hal-05267388

https://hal.science/hal-05267388v1

Submitted on 18 Sep 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Dietary intake and glutamine-serine metabolism control pathologic vascular stiffness

Nesrine S. Rachedi¹,*, Ying Tang²,³,*, Yi-Yin Tai²,³, Jingsi Zhao²,³, Caroline Chauvet¹,
Julien Grynblat⁴,⁵, Kouamé F. Akoumia⁴, Leonard Estephan²,³, Stéphanie Torrino¹, Chaima
Sbai¹, Amel Ait-Mouffok¹, Joseph D. Latoche⁶, Yassmin Al Aaraj²,³, Frederic Brau¹, Sophie
Abélanet¹, Stephan Clavel¹, Yingze Zhang²,⁷, Christelle Guillermier⁸, Naveen VG Kumar⁹,
Sina Tavakoli³,¹⁰, Olaf Mercier⁴,¹¹, Michael G. Risbano²,⁷, Zhong-Ke Yao¹², Guangli Yang¹²,
Ouathek Ouerfelli¹², Jason S. Lewis¹², David Montani⁵,¹¹, Marc Humbert⁴,¹¹, Matthew L.
Steinhauser⁸,⁹, Carolyn Anderson¹³, William M. Oldham¹⁴, Frédéric Perros⁴,¹⁵, Thomas
Bertero¹,§,#,$, Stephen Y. Chan²,³,$#

(1)Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA Valbonne, France;

(2)Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute,

(3)Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA;

(4)Université Paris-Saclay, AP-HP, INSERM UMR_S 999, Service de Pneumologie et Soins Intensifs Respiratoires, Hôpital de Bicêtre, Le Kremlin Bicêtre, France

(5)Pôle Thoracique, Vasculaire et Transplantations, Hôpital Marie Lannelongue, Le Plessis-Robinson, France;

<footnote>*Corresponding Authors: Thomas Bertero, Ph.D., Université Côte d'Azur, Institute of Molecular and Cellular Pharmacology, CNRS UMR 7275 - INSERM U1323, 660, route des Lucioles, Sophia Antipolis, 06560 Valbonne, France, thomas.bertero@univ-cotedazur.fr, Stephen Y Chan, M.D., Ph.D., Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, 200 Lothrop Street BST E1240, Pittsburgh, PA USA 15261, chansy@pitt.edu.</footnote>

<footnote>*denotes equal contribution by these authors.</footnote>

<footnote>$^§$denotes equal contribution by these authors.</footnote>

<footnote>$^#$Lead contact</footnote>

<footnote>**Author contributions:** S.Y.C. and T.B. conceived and designed the experiments. S.Y.C., W.M.O., F.P. and T.B., provided experimental infrastructure. N.R., Y.T., C.C., S.T. C.S., A.A.M., Y-Y.T., J.Z., W.M.O., and T.B. performed the *in vitro* experiments. F.B., S.C. and S.A. performed confocal imaging experiments. Y.T., Y-Y.T., J.Z., J.G., K.F.A., F.P., and S.Y.C. performed the *in vivo* rat and mouse experiments. L.E., Y.T., Y-Y.T., S.Y.C., and M.L.S. performed the MIMS study. G.Y., Z.-K.Y, and O.O. synthesized the 18F-Gln precursor and FGln standard. Y.T., M.T., J.D.L., S.T., S.Y.C., and C.A. performed the PET imaging studies. Y.A.A., M.G.R., and Y.Z. provided human plasma samples and clinical phenotyping data. O.M., D.M., F.P., and M.H., provided human PAAF and clinical phenotyping data. W.M.O. performed and analyzed the metabolomic experiments. S.Y.C. and T.B. wrote the manuscript. All authors participated in interpreting the results and revising the manuscript.</footnote>

<footnote>**Declaration of Interests:** S.Y.C. has served as a consultant for Merck, Janssen, and United Therapeutics. S.Y.C. is a director, officer, and shareholder in Synhale Therapeutics. S.Y.C. has held research grants from WoodNext, Bayer, and United Therapeutics. S.Y.C. and T.B. have filed patent applications regarding the targeting of metabolism in pulmonary hypertension. G.Y. Z.-K.Y and O.O. are listed as inventors in patents, not related to this work, that are filed by MSKCC. O.O. receives royalties from MSKCC, Johnson & Johnson, Jazz, and Y-mAbs and owns shares of Angiogenex for which he is an unpaid member of the SAB, all of which are not related to this work. The other authors declare no competing interests.</footnote>

<footnote>**Publisher's Disclaimer:** This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.</footnote>
(6)Hillman Cancer Center, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA;

(7)Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA;

(8)Center for Nanolmaging, Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA

(9)Aging Institute, Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA;

(10)Department of Radiology, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA;

(11)Assistance Publique-Hôpitaux de Paris (AP-HP), Service de Pneumologie et Soins Intensifs Respiratoires, Centre de Référence de l'Hypertension Pulmonaire, Hôpital Bicêtre, 94270 Le Kremlin-Bicêtre, France;

(12)Molecular Pharmacology and Chemistry Program and Organic Synthesis Core Facility, Memorial Sloan Kettering Cancer Center, New York, USA;

(13)Department of Chemistry, University of Missouri, Columbia, MO USA;

(14)Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA USA

(15)Laboratoire CarMeN, UMR INSERM U1060/INRA U1397, Université Claude Bernard Lyon1, F-69310 Pierre-Bénite

## Summary

Perivascular collagen deposition by activated fibroblasts promotes vascular stiffening and drives cardiovascular diseases such as pulmonary hypertension (PH). Whether and how vascular fibroblasts rewire their metabolism to sustain collagen biosynthesis remain unknown. Here, we found that inflammation, hypoxia, and mechanical stress converge on activating the transcriptional coactivators YAP and TAZ (WWTR1) in pulmonary arterial adventitial fibroblasts (PAAF). Consequently, YAP and TAZ drive glutamine and serine catabolism to sustain proline and glycine anabolism and promote collagen biosynthesis. Pharmacologic or dietary intervention on proline and glycine anabolic demand decreases vascular stiffening and improves cardiovascular function in PH rodent models. By identifying the limiting metabolic pathways for vascular collagen biosynthesis, our findings provide guidance for incorporating metabolic and dietary interventions for treating cardiopulmonary vascular disease.

## Graphical Abstract
Pulmonary hypertension

<figure><img src="image_2.png" /></figure>

eTOC blurb

Rachedi et al. identify the precise metabolic requirements for pathogenic vascular fibroblast activation, using pulmonary arterial hypertension as an example. Inflammation, hypoxia, and mechanical stress converge on YAP and TAZ activation. YAP and TAZ control glutamine and serine catabolism to generate proline and glycine for collagen biosynthesis. Pharmacologic or dietary intervention on those metabolic pathways decreases collagen production and vascular stiffening and improves pulmonary vascular function.

Keywords

Cardiovascular Disease; Metabolism; Nutrition; Vascular Fibroblast; Fibrosis; Collagen Metabolism

INTRODUCTION

Cardiac and vascular diseases (CVDs) constitute the leading cause of death worldwide¹. Vascular remodeling and stiffening are hallmarks of CVDs and primarily contribute to CVD severity². Dysregulated balance between collagen deposition and degradation has been reported to promote vascular stiffening. Recently, we and others have shown that activated vascular fibroblasts promote collagen biosynthesis in CVDs³⁻⁵. For instance, in pulmonary hypertension (PH), a deadly enigmatic disease of the pulmonary vasculature, as well as in a particularly deadly subtype pulmonary arterial hypertension (PAH), hormonal, inflammatory, and environmental stresses such as hypoxia/ischemia, or mechanical cues
activate resident adventitial fibroblasts at early stages of disease³. Such activation is characterized by increases in cellular proliferation in the expression of contractile proteins as well as in the secretion of extracellular matrix (ECM) proteins, chemokines, cytokines, growth, and angiogenic factors -- all processes that require energy. However, beyond glycolysis, the metabolic requirement of activated pulmonary artery adventitial fibroblasts (PAAF) remains unknown⁵. Thus, deciphering the metabolic circuits of PAAF activation will offer much needed insight into the molecular underpinnings of this disease and provide diagnostic and therapeutic entry points for identifying and treating disease more effectively.

Under the control of adventitial fibroblasts are the hundreds of ECM proteins and fibrillar collagens that have been shown to provide the scaffold and give mechanical properties to the vascular wall structure⁶⁻⁸. Dysregulation of the mechanical properties of vascular cells microenvironment is increasingly recognized as a driver of aberrant vascular cell reprogramming. As such changes in vascular collagen metabolism is capable of directly affecting resident vascular cell wall behaviors in a manner that influences overall vascular tone and wall structure. The amino acid composition of collagen is atypical for proteins. The most common motifs in the amino acid sequence of collagen are glycine-proline-X and glycine-X-hydroxyproline, where X is any amino acid other than glycine, proline or hydroxyproline. As such, around 33% of collagen amino acids are glycine, while proline and hydroxyproline account for 20% of collagen amino acids⁹. Consequently, the massive collagen secretion by activated fibroblasts observed during PH progression must require these cells to adapt their metabolism to match their energetic needs.

The dynamic metabolism of vascular adventitial fibroblasts suggests an important link between these cells and vascular stiffening with diet and nutrition. The central role of diet in cardiovascular health and disease is well documented¹⁰. For instance, both population-level and wet bench research have connected obesity and dietary consumption with increased CVD risk, while a low carbohydrate, low-fat diet promotes reduced CVD incidence¹¹. Emerging evidence has emphasized the importance of timed and intermittent dietary ingestion in influencing global metabolic health in CVD¹²,¹³. Yet, the specific dietary components that control vascular stiffening and downstream cardiopulmonary vascular phenotypes in health and disease are poorly defined. This is particularly true in pulmonary vascular diseases, where the impact of diet on risk and severity of PH has not been studied in depth at a molecular level¹⁴.

Here, using metabolomic discovery platforms across primary diseased vascular cells, *in vivo* rodent models of PH, and lung tissue of patient with PH, we sought to define the precise metabolic requirements of pulmonary adventitial fibroblast (PAAF) during pathogenic activation. In doing so, we developed both targeted pharmacologic and dietary interventions on those metabolic circuits that reduced collagen production and vascular stiffening, thus improving vascular function in PH *in vivo*.
# RESULTS

## PAAF activation rewires glutamine and serine metabolism to sustain proline and glycine biosynthesis.

To determine whether activation of PAAFs rewires cellular metabolism to sustain ECM production, we performed a series of metabolomic studies on PAAF culture on soft or stiff matrices and exposed to PH triggers. Here, a soft matrix was defined by a Young's (elastic) modulus of 1 kPa, stiff matrix was defined as 12 kPa consistent with our prior studies of the stiffness of non-diseased and diseased pulmonary arterioles in rodents³,¹⁵. Multiple PH triggers, including exposure to interleukin-6 (IL-6) and transforming growth factor beta (TGF-β), matrix stiffening (12kPa), and hypoxia, activated PAAFs, as reflected by increased contractility (increased myosin light chain 2 phosphorylation, P-MLC2; Figure S1A–C). Steady-state metabolic cell profiles of activated PAAFs (Figure S1D–F) or PAAFs from PH donors (Table S1; Figure 1A and S1G) demonstrated that activation promoted substantial global alterations of cell metabolism. Consistent with the notion that collagen production by fibroblasts requires proline and glycine anabolism, pathway analysis revealed that fibroblast activation significantly altered the steady-state levels of metabolites highly enriched in pathways related to proline and glycine metabolism (Figures 1B and S1E). Consistent with these results, the expression levels of several genes involved in proline and serine biosynthesis were upregulated in activated PAAFs (Figure S1H–I). To determine any preferential carbon sources for proline and glycine biosynthesis, we sought for metabolites that are increasingly taken up by activated fibroblasts or diseased lungs. Steady-state metabolomic analysis of conditioned media from either PH-PAAFs (Figure 1C) or activated-PAAFs (Figure S1J) revealed a reduction of glutamine, serine, glucose (and, to lesser extents, proline and glutamate), suggesting that these cells exhibit increased uptake of these amino acids. Correspondingly, metabolic analysis of the trans-pulmonary plasma gradient of monocrotaline-treated rats showed that diseased lungs increased their consumption of glutamine, serine, and glucose (Figures 1D–E). Similar results were obtained in the plasma of patients with PH (Table S2) comparing amino acid levels between right atrial and pulmonary capillary wedge positions (Figure 1F–G).

To discriminate between carbon sources (Figure 2A) that are taken up by cells from the media and to determine if at least a portion of the metabolic rewiring observed in activated PAAFs provides carbons for proline and glycine biosynthesis, we employed stable isotope tracing studies, using [U-13C]-glucose, [U-13C]-glutamine, [U-13C]-glutamate, or [U-13C]-serine (Figures 2B–E and S2). Cells were incubated with labeled metabolite for 4 hours. These tracing experiments demonstrated that glucose, glutamine, and serine catabolism were increased upon PAAF activation. Moreover, both glutamine-derived proline (M+5) and serine-derived glycine (M+3) levels increased in response to PAAF activation (Figures S2B and S2D). In contrast, glucose and glutamate did not significantly account for proline and glycine biosynthesis (Figures S2A and S2C). To derive further insight into the metabolic rewiring of activated fibroblasts in vivo, we performed complementary experiments quantifying glutamine and serine uptake. ¹⁸F-labeled fluoroglutamine (¹⁸F-FGln)¹⁶ coupled with positron emission tomography (PET) scanning correspondingly revealed increased glutamine absorption by diseased lungs and lung vasculature in monocrotaline-exposed rats
with experimental PH (Figure 2F–H). To complement such PET imaging of glutamine uptake at tissue-scale resolution with glutamine and serine imaging at cellular resolution, we leveraged a multi-isotope imaging mass spectrometry (MIMS), merging *in vivo* stable isotope tracer methodology with nanoscale secondary ion mass spectrometry (Figure 2I–M). Consistent with the *in vitro* tracing studies and ¹⁸F-FGln PET imaging, significantly elevated glutamine and serine uptake was observed in the adventitia of diseased pulmonary arterioles in monocrotaline-exposed PH rats. Together, our results indicate that activated-PAAFs increase their glutamine and serine uptake, with these amino acids serving as substrates for production of proline and glycine and consequent collagen biosynthesis and vascular stiffening in PH.

**Metabolic rewiring of activated fibroblast promotes the building of a diseased vascular niche.**

To investigate whether glutamine and serine catabolism are required for vascular collagen biosynthesis, we tested whether inhibition of glutaminase (GLS1) (the enzyme that converts glutamine to glutamate, the first step of glutamine conversion to proline) and/or the serine hydroxymethyltransferase (SHMT1) (the enzyme that converts the serine to glycine and is the key isoform as compared to SHMT2 that is responsive to PH triggers, Figure S1) controls collagen production by activated PAAFs. GLS1 inhibition, achieved via siRNA (Figure S3A–C) or the small molecule CB-839 (Figure S3D–E), reduced proline biosynthesis, while SHMT1 inhibition achieved via siRNA or the small molecule SHIN1 blunted glycine biosynthesis. Inhibition of both GLS1 and SHMT1 drastically rewired the metabolism of activated PAAFs and diseased PAAFs and decreased both proline and glycine biosynthesis (Figure S3A–E). Consistent with our hypothesis, siRNA knockdown of GLS1 or SHMT1, and to a greater extent siRNA knockdown of GLS1 and SHMT1, decreased collagen production by PAAFs activated by PH triggers such as IL-6 (Figure 3A), stiffness (Figure S3F) or hypoxia (Figure S3G). Supplementation with permeant α-ketoglutarate rescues collagen production (Figure S3H). Similar results were obtained in PH-PAAFs treated with CB-839 and SHIN1 (Figure 3B and S3I).

Perivascular collagen remodeling by vascular fibroblast promotes a pro-proliferative vascular niche, thus activating vascular cell proliferation in CVD. To investigate whether glutamine and serine catabolism are required for these pathogenic processes, we leveraged a matrix-derived cell culture platform. PAAFs were transfected with siRNAs for GLS1 and SHMT1 and allowed to produce and remodel ECM for five days. Then, fibroblasts were removed, and the ECM was either analyzed for the quantity and quality of their fibrillar collagen or used to plate naïve vascular cells (Figure 3C). siRNA knockdown of GLS1 or SHMT1, and to a greater extent siRNA knockdown of GLS1 and SHMT1, decreased fibrillar collagen deposition and assembly, thereby decreasing vascular cells proliferation (Figure 3D–E). Similar results were observed in PH-PAAFs treated with GLS1 and SHMT1 pharmacologic inhibitors (Figure 3F–G). Next, to determine whether the PAEC and PASMC proliferation observed rely on the mechanical qualities of the collagen-rich environment or the molecular content we performed a series of complementary experiments. First, we analyzed the proliferation of vascular cells cultivated on soft or stiff matrices and supplemented with or without proline and glycine. While matrix stiffening increased
the proliferation of both PAEC and PASMC, proline/glycine supplementation did not affect cell proliferation (Figure S3J). Second, we investigated whether proline and glycine supplementation can increase the proliferation rate of PAEC or PASMC cultivated on a matrix from non-activated PAAFs (control-PAAFs). Consistent with our results showing that proline and glycine did not increase the proliferation of cells cultivated on soft matrix, supplementation with proline/glycine did not increase the proliferation of vascular cells (Figure 3I). Together, these results offer evidence against a predominant role for the ECM molecular content of these specific amino acids in controlling vascular cell proliferation. To demonstrate the role of matrix stiffness in vascular cell proliferation, we cultivated vascular cells on matrix produced by IL6-activated fibroblast and treated with or without BAPN, an inhibitor of lysyl-oxidases (LOXs), the enzymes that crosslink the collagen. Consistent with previous reports³,¹⁵,¹⁷, BAPN treatment reduced the matrix stiffness as measured by AFM, (Figure 3H) and decreased the proliferation of vascular cells plated on top of the matrices (Figure 3I). Together, our results define glutamine and serine catabolism as crucial metabolic processes, essential for fibroblast-driven vascular stiffening and remodeling.

YAP and TAZ are overarching regulators of vascular remodeling by diseased PAAFs.

To delineate the molecular mechanism controlling vascular remodeling by PAAFs during PH progression, we sought to identify the overarching molecular regulator(s) of glutamine and serine catabolism in activated fibroblasts. Recently, we and others have reported the ability of the co-transcriptional factors YAP and TAZ to control both cell activities and cell metabolism and thus adjust the metabolic needs of cells with their activities¹⁵,¹⁸,¹⁹. Furthermore, several studies have reported the involvement of YAP and TAZ in CVD²⁰,²¹ and fibroblast activation³,²². Therefore, to test whether YAP and TAZ globally control fibroblast metabolism and especially glutamine/proline and serine/glycine metabolism, we analyzed the reported binding sites of TEADs (the transcriptional factors to which YAP and TAZ bind to mediate their transcriptional effect²³,²⁴) as determined by chromatin immunoprecipitation and DNA sequencing²⁵,²⁶ (ChIP-seq). Pathway enrichment analysis revealed that, beyond cell proliferation and DNA/RNA metabolism, TEADs control a large set of genes involved in cell metabolism and included genes involved in glutamine/proline and serine/glycine metabolism (Figure 4A). To gain further insights on the role of YAP/TAZ in the coordination of collagen production and the metabolic rewiring required for collagen biosynthesis, we searched for TEAD binding sites in promoters of genes involved in the metabolism-dependent circuit of collagen biosynthesis (Figure 4B–C). TEAD ChIP seq analysis revealed that TEADs bind upstream to many genes from the glutamine-to-proline and serine-to-glycine metabolic pathways (Figure 4C). To confirm these results, we performed YAP ChIP-qPCR experiments in PH-PAAFs (Figure 4D). We demonstrated that YAP binds the promoter region of a large set of genes involved in glutamine and serine rewiring as well as genes involved in collagen metabolism (Figure 4D). Moreover, manipulating YAP and TAZ expression (Figure S4A) modulated these genes at the transcriptional level (Figure S4B) and at the protein level for GLS1 and SHMT1 (Figure S4A). Together, these results demonstrate that YAP and TAZ coordinate the transcription of a large pool of genes involved in glutamine to proline and serine to glycine metabolism, as well as collagen metabolism, indicating that YAP and TAZ may orchestrate collagen biosynthesis via control of amino acid metabolism.
To investigate more precisely whether YAP and TAZ metabolically control collagen biosynthesis, we analyzed the steady-state metabolic profile of YAP and TAZ knockout cells (Figures 4E–F and S5A–B). Modulating YAP and TAZ expression in activated PAAFs promoted a substantial global alteration of cell metabolism. Beyond pathways related to glucose metabolism, the analysis revealed that siRNA knockdown of YAP and TAZ in activated-PAAFs modulated the steady-state levels of metabolites highly enriched in proline and glycine metabolism pathways (Figures 4F and S4B). Consistent with the role of YAP and TAZ in the control of the glutamine to proline and glycine to serine metabolism, siRNA knockdown of YAP and TAZ in activated-PAAFs decreased the glutamine-derived proline (M+5) and the serine-derived glycine (M+3) levels (Figures 4G–H and S5C–F) and decreased collagen production (Figures 4I and S4C–D). Furthermore, we demonstrated that manipulating YAP and TAZ expression in activated fibroblasts decreased fibrillar collagen deposition and assembly in the ECM (Figures 4J–L and S4E), thereby decreasing the proliferation of naive vascular cells (Figures 4J–L and S4E). Together, these results showed that YAP and TAZ directly control the rewiring of glutamine and serine into proline and glycine metabolism to sustain collagen biosynthesis.

Next, we investigated whether YAP and TAZ metabolically control collagen biosynthesis in vascular fibroblast *in vivo* to build a diseased vascular niche promoting PH. Specific conditional knockdown of YAP and TAZ in fibroblasts of pulmonary-specific IL-6 transgenic mice (Figure 5A) – an inflammatory mice model of PH<sup>27</sup>—decreased GLS1 (Figure 5B) and SHMT1 (Figure 5C) expression in the pulmonary arteries, decreased the pulmonary vascular collagen content (total and fibrillar; Figure 5D–F), thereby decreasing pulmonary arterial stiffness as measured by atomic force microscopy (AFM; Figure 5G). Given the alterations occurring in the pulmonary vascular ECM, the deletion of YAP and TAZ in fibroblasts decreased vascular mural cell proliferation (Figure 5H) and improved downstream histologic (Figure 5I), hemodynamic (Figure 5J), and right ventricular indices (Figure 5K) of PH. Similar results were observed in a second rodent model of PH where PH is induced by chronic exposure to hypoxia (Figure S6). Together, our results demonstrate that YAP and TAZ coordinate the metabolic needs of activated vascular fibroblasts with their collagen remodeling activities to build a diseased vascular niche that favors vascular mural cell proliferation.

**Targeting proline and glycine anabolism decreases collagen production and vascular stiffening, thus improving PH *in vivo*.**

We next investigated whether targeting glutamine and serine catabolism is sufficient to decrease vascular stiffening and improve pulmonary vascular function in a pre-clinical model of PH. Monocrotaline-exposed rats were treated with either CB-839 or SHIN1 or the combination of inhibitors (Figure 6A). Pharmacologic inhibition of both GLS1 and SHMT1 decreased the pulmonary vascular collagen content (Figure 6B–C), decreased the pulmonary arterial stiffness (Figure 6D), thus decreasing vascular cell proliferation (Figure 6E). As a result, GLS1 and SHMT1 inhibition significantly decreased pulmonary arteriolar remodeling and muscularization (Figure 6F), right ventricular systolic pressure (Figure 6G), and right ventricular remodeling (Figure 6H). In comparison, while CB-839 alone was effective in reducing vascular collagen content, vascular stiffness, proliferation as well as histologic and
hemodynamic parameters of PH, SHIN1 alone was only modestly active alone across these parameters. Notably, SHIN1 decreased the total amount of fibrillar collagen in the lungs but did not modulate the soluble/insoluble ratio (Figure 6B). Together, these drugs demonstrated a more robust improvement than either drug alone, particularly across collagen quality, stiffness, proliferation, and muscularization.

Based on these results demonstrating the glutamine and serine metabolic requirement for collagen biosynthesis *in vivo* during PH development, we investigated whether decreasing glutamine and serine bio-availability via dietary intervention (Figure 7A) could reduce collagen biosynthesis and thus improve cardiopulmonary function. We first studied whether decreasing glutamine and serine ingestion chronically reduced glutamine and serine bioavailability (Figure 7B). Indeed, we found rapid and sustained decreases in circulating levels of glutamine and serine in the plasma of rats fed with glutamine- and serine-free diets, while displaying minimal or inconsistent impact on glucose (Figure 7B), Second, to assess the effect of dietary serine and glycine (SG) restriction in a pre-clinical PH model, we transferred 12-week old rats from a normal chow diet to experimental diets (synthetic diet, Ctrl; or Gln-/ser- synthetic diet) 18 days before monocrotaline injection. Three weeks later, we analyzed for alterations of amino acid metabolism, vascular stiffening, and PH. Transferring rats from normal chow diet to an experimental glutamine- and serine-free diet significantly reduced plasma levels of glutamine and serine (Figure 7C), pulmonary vascular collagen content (Figure 7D-E), pulmonary arterial stiffness (Figure 7F), and vascular cell proliferation (Figure 7G-H). Consequently, such an amino-acid restricted diet significantly decreased pulmonary arteriolar remodeling and muscularization (Figure 7I), right ventricular systolic pressure (Figure 7J), and right ventricular remodeling (Figure 7K). Together, our results, offer foundational support for dietary intervention targeting glutamine and serine to improve pulmonary vascular stiffening, remodeling, and downstream PH.

DISCUSSION

Our findings delineate a YAP/TAZ-dependent metabolic circuit controlling collagen biosynthesis by activated vascular fibroblasts. Specifically, our results establish glutamine and serine catabolism as crucial steps for collagen biosynthesis. These results carry broad implications for our fundamental understanding of collagen metabolism - a dysregulated process in several diseases such as cancer and across CVDs such as PH. Furthermore, our study reveals a much broader and more complex regulation of the extracellular vascular niche that could be metabolically targeted. As such, our findings provide scientific guidance for incorporating pharmacologic and dietary interventions as amino acid-based therapies in these deadly diseases.

Interplay among the transcriptional coactivators YAP and TAZ with cell metabolism has recently gained traction<sup>19,28</sup>. YAP and TAZ are activated by various stimuli inherent to the Hippo signaling pathway, glucose metabolism, as well as mechanical signals. YAP/TAZ control cell growth, stem cell maintenance, and tissue homeostasis<sup>23</sup>. Given the energy requirement of cell proliferation and survival, YAP and TAZ are inhibited when the energy level is low<sup>29-31</sup>. Conversely, YAP and TAZ control several metabolic pathways, including glutaminolysis and anaplerosis, to sustain the metabolic needs of cellular proliferation<sup>15,18</sup>.
Moreover, YAP and TAZ are activated during tissue repair processes and sustain fibroblast activation in fibrosis<sup>21,22</sup>. Consistent with the role of YAP/TAZ and the Hippo signaling pathway in PH<sup>3,32</sup>, our findings highlight a much more complex regulation of metabolism by YAP and TAZ in tissue fibrosis – whereby both glutamine and serine catabolism conspire to generate proline and glycine that ultimately are crucial for de novo synthesis of collagen. It remains to be seen if glutamine and serine pathways can also act in a reciprocal feedback loop to further activate YAP/TAZ and reinforce this metabolic reprogramming in activated PAAFs. Recent data have shown that extracellular uptake rather than synthesis of proline may be a primary mechanism by which pulmonary vascular endothelium can generate collagen<sup>33</sup>. Our data indicate that activated PAAFs – cell types that carry the bulk of responsibility for collagen deposition – rely more prominently on proline biosynthesis for new collagen synthesis and vascular stiffening. Given the increasing appreciation of molecular communication and interdependence between the endothelium and adventitia<sup>34,35</sup>, an intriguing mechanism could include a process by which proline taken up by diseased endothelium ultimately originates from proline synthesized from glutamine in fibroblasts. Furthermore, given the key roles of endothelial-to-mesenchymal transition and smooth muscle transition between contractile and synthetic states in PH pathogenesis, it will be important to determine whether dynamic changes in glutamine and serine metabolism (observed across the vessel wall, can contribute to these or other phenotypic transitions of vascular cells. Development of approaches allowing metabolic assessment at single-cell level such as MIMS coupled to spatial transcriptomics may be necessary to fully decipher such putative metabolic interactions.

Beyond PH, these findings may carry important implications for diseases where ECM deposition and/or remodeling by tissue-resident fibroblasts drive pathogenesis, such as peripheral vascular diseases, heart failure with preserved ejection fraction (HFpEF), cancer, and tissue fibrosis (i.e., lung, liver, kidney), in general. Future work is warranted to define whether non-vascular and vascular fibroblasts in other anatomic compartments also rely predominantly on glutamine and serine catabolism for collagen synthesis. In particular, intracellular glutamine content may serve as a central rheostat of diverse cellular function – one that is even more versatile than currently characterized. For example, recent findings have emerged regarding the mechano-induced glutamylation and stabilization of microtubules that can drive cancer cell migration<sup>36</sup>. Since glutamine levels define a limiting metabolic requirement for collagen synthesis and fibrosis, an intriguing hypothesis now may emerge whereby shunting of glutamine to microtubule glutamylation vs. to collagen deposition may either facilitate metastatic cancer invasion or more dense tissue fibrosis. In vascular diseases beyond PH, the balance of such fundamental processes may otherwise define the extent of angiogenesis vs. scar or infarct size across a variety of vascularized tissues experiencing ischemic or hypoxic insults.

Beyond glutamine metabolism, our study emphasized the YAP/TAZ-dependent control over serine/glycine metabolism. Although often associated with glucose catabolism, here we demonstrate that glycine biosynthesis relies on exogenous serine catabolism. Whereas non-activated cells exhibit lower demands for serine and glycine, hyperproliferative cancer cells demonstrate hyperactive intracellular serine and glycine synthesis and are addicted to *de novo* production<sup>37,38</sup>. Our findings demonstrate that similar metabolic processes are at play
in diseased vasculature, furthering the notion of parallel features of cancer and peripheral and pulmonary vascular disease³⁹,⁴⁰. Namely, our findings implicate SHMT1 as a crucial mediator of PH pathogenesis, similar to our understanding in cancer³⁸.

In identifying the crucial metabolic pathways required for collagen biosynthesis in fibrotic disease, our work offers the potential for non-invasive imaging tools for diagnosis and prognosis in PH. Despite its morbid prognosis, PH, and particularly PAH, is often misdiagnosed or ignored, with an average time of >40 months between onset of symptoms to diagnosis and progression of PAH severity⁴¹. A crucial need exists to develop non-invasive diagnostic imaging tools, particularly that can detect early disease stages and reflect molecular alterations that drive disease in the lung, vasculature, and right ventricle (RV)⁴². While our use of MIMS offered research applicability, this technique is too specialized, time-consuming, and low-throughput to offer a viable diagnostic platform for widespread clinical use. In contrast, based on our advanced insights into glutamine metabolism in PH, positron emission tomography (PET) may offer a clinically available platform for imaging changes in the metabolic state of the vasculature and right ventricle in PH. PET has been applied in PAH to image ¹⁸F-fluorodeoxyglucose (¹⁸FDG) uptake as a reflection of increased glycolysis⁴² particularly in the RV⁴³. However, this specific PET tracer in PAH is limited by inconsistent results⁴² and inability to detect early stages of disease. Beyond ¹⁸FDG, highly glutaminolytic tissue are avid for glutamine, as shown by its uptake in cancers⁴⁴, and this process is quantifiable by PET. ¹⁸F-(2S,4R)-4-fluoroglutamine (¹⁸F-FGln) is a single stereoisomer analog of glutamine with promising results for imaging of tumors⁴⁵ such as gliomas¹⁶ and breast cancer⁴⁴. When coupled with our published findings that glutamine levels decrease in the pulmonary circulation in human patients with PAH¹⁵, our preclinical data with this tracer strengthen the notion that ¹⁸F-FGln and glutamine uptake could be a feasible modality to track in patients with PAH. Given the dearth of effective imaging tests for PAH and PH in general, a first-in-human trial of ¹⁸F-FGln PET in PH could offer a translational avenue to pursue glutamine imaging to define disease severity and risk, including at early disease time points. ¹⁸F-FGln PET could offer a clinical trial outcome surrogate, reflecting the molecular pathogenesis of PH. It could also aid in clinical trial recruitment of “super-responder” patients with PH, thus decreasing patient numbers for recruitment and potentiating an era of precision medicine for PH.

Coupled with furthering such non-invasive platforms of identifying patients with PH avid for glutamine uptake, our findings also offer a roadmap toward more effective and precise pharmacologic therapies for PH. Previously we have shown that glutaminolysis supports PAEC and PASMC proliferation, migration, and contractility via anaplerosis. By now identifying glutamine metabolism as key step for collagen biosynthesis in PAAF, our findings highlight the pleiotropic activity of glutamine across the pulmonary vasculature. It remains unclear if serine metabolism carries as many roles, perhaps serving as an explanation as to why targeting GLS1 appears consistently more effective than targeting serine metabolism alone. Yet, the interconnected nature of these metabolic pathways opens up the possibility of combinatorial therapies. Namely, while isolated inhibition of GLS1 can improve PAH¹⁵, the synergism of inhibiting both YAP1 and GLS1 in PH has been described⁴⁶. We now further define the therapeutic benefit of simultaneous delivery of GLS1 and SHMT1 inhibitors in the diseased pulmonary vasculature. These findings set the stage
for the clinical development of combination of such synergistic agents for more robust and metabolic control of PH manifestations. However, dosing strategies would be complex and likely would necessitate more targeted administration. Given the strong track record of poly(lactic-co-glycolytic) acid (PLGA) microparticles for inhalation⁴⁷ including in PH⁴⁸ recently, an inhaled microparticle for local, controlled release of these metabolic therapies may be appealing.

Finally, by defining the limiting carbon sources for collagen biosynthesis, our study reveals a unique opportunity to introduce dietary modulation in the management of PH and CVDs, in general. It is well known that dietary changes play a dominant role⁴⁹,⁵⁰ in a number of CVDs. Beyond CVDs, dietary intervention has been proposed to ameliorate tissue fibrosis, such as in fatty liver diseases⁵¹. Moreover, altering the timing of daily food ingestion in the form of intermittent fasting has increasingly been identified as an effective modulator of cellular and physiologic metabolic parameters, with robust implications on aging and a variety of chronic diseases⁵². More recently, intermittent fasting has been proposed as a potential intervention for right ventricular dysfunction in PAH¹⁴. However, a diet aimed at modulating specific ingested amino acid content has not been tested to our knowledge as a precise therapeutic intervention for fibrosis or cardiopulmonary diseases. Although both glutamine and serine (as well as proline and glycine) can be synthesized from sources other than the diet, our preclinical data indicate that targeted dietary restriction of glutamine and serine are effective in reducing these amino acid levels in lung tissue, suggesting a decrease of their overall bioavailability. Future studies are warranted to determine whether dietary sources of these amino acids predominantly and directly contribute to lung vascular fibrosis in PH or whether dietary alterations may also serve as a primary but indirect trigger to altered specific amino acid production and/or degradation in lung as PH progresses. Furthermore, it is possible that genetic variability in the enzymes that transport and metabolize these dietary amino acids in the gut may influence the therapeutic effects of such dietary restriction. Translating this approach to human patients would also necessitate greater insight into the complex cooking and processing that could alter the amino acid composition of any prescribed dietary prescription. Progress toward network medicine⁵³ and artificial intelligence could help us to systematically define the complex link between the diet with the genome and disease and thus prepare for feasible dietary interventions in PH and beyond.

In sum, we identify the precise metabolic and amino acid requirements for vascular fibroblast activity. This study provides a fundamental insight into the regulation of collagen metabolism and fibrosis, which is critical for managing PH and holds relevance for other fibrotic diseases across other CVDs and beyond. Moreover, our study offers the potential for metabolic PET imaging platforms for more effective non-invasive diagnostic and prognostic testing in PH and vascular stiffening. It also guides developing pharmacologic and dietary therapies targeting metabolic crosstalk in the diseased vasculature.

**Limitations of study:**

Limitations to this study should be acknowledged. When interpreting transpulmonary gradient analyses from rats and humans, we acknowledge that streaming from hepatic veins
may confound collection from either the inferior vena cava (rat) or right atria (human). To demonstrate the role of YAP and TAZ in vascular fibroblasts *in vivo*, a cell type-enriched deletion of YAP and TAZ was accomplished using mice expressing the Cre transgene driven by a tamoxifen-inducible Col1a2 promoter. Although Col1a2 is primarily expressed in fibroblasts⁵⁴, smooth muscle cells also express this gene. Thus, we cannot rule out that at least a portion of the downstream phenotype may be driven by smooth muscle deletion of YAP and TAZ and that cell type's contribution to collagen deposition. Our experiments with dietary restriction also do not account for the kinetics of endogenously produced and non-diet administered amino acids, which could confound an interpretation of direct cause-effect in diet restriction with PH. More broadly, our study is not set up to define the dynamic and likely bidirectional contribution of total metabolite content across the plasma, lung vasculature, and other tissue or dietary sources. To address this point, future metabolomic studies of the lung in PAH could be envisioned that are designed similarly to prior work quantifying fuel use in the failing human heart⁵⁵.

# STAR METHODS

## RESOURCE AVAILABILITY

**Lead contact**—Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Thomas Bertero, PhD (thomas.bertero@univ-cotedazur.fr).

**Materials Availability**—All unique/stable reagents generated in this study are available from the Lead Contact without restriction.

## Data and Code Availability

* All of the data supporting this study are included in the article. All raw data used to generate the figures throughout the manuscript can be found within the Data S1 document

* This paper does not report original code

* Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

## EXPERIMENTAL MODELS AND SUBJECT DETAILS

**Cell culture**—Primary human pulmonary arterial adventitial fibroblasts (PAAF) were purchased from Sciencell. Cells used in this study were within 7 passages and were cultured (37°C, 5% CO2) in Dulbecco's Modified Eagle's Medium (DMEM, Gibco) supplemented with 10% fetal bovine serum (Gibco), Glutamine (2mM, Gibco) and Penicillin/Streptomycin (1%, Gibco). A triple gas incubator set at 1% oxygen, 94% nitrogen, and 5% carbon dioxide was used for hypoxic conditions. PAAFs from patients with PH (PH-PAAF) were isolated from explanted lungs at Marie Lannelongue Hospital. To isolate PAAFs, vascular cells from dissected pulmonary arteries were cultured in DMEM supplemented with 0.5% FCS. In this condition, PH-PAAFs that outgrew PAEC and PASMC in culture were isolated by differential trypsinization. These cells were cultured in DMEM supplemented with
10% FCS, 2mM glutamine, 1% Pen/Strep and insulin-transferrin-selenium (Invitrogen). Constitutive activation of PH-PAAFs was verified by measuring Vimentin and α-SMA expression as well as by their ability to contract a collagen I rich gel in the absence of serum. PH-PAAFs from at least five different patients were randomly used throughout the experiments. All cells were grown in collagen-coated plastic (50 µg/mL) at 37°C in a humidified 5% CO2 atmosphere. Experiments were performed at passages 2–10. All cells were routinely tested for mycoplasma by PCR and were carefully maintained in a centralized cell bank. Primary human (Lonza) pulmonary arterial endothelial cells (PAECs) were grown in EBM-2 basal medium supplemented with EGM-2 MV BulletKit (Lonza). Primary human (Lonza) pulmonary arterial smooth muscle cells (PASMCs) were grown in SmGM-2 (Lonza) For the studies dependent on matrix stiffness, collagen-coated hydrogel pre-plated in culture wells (Matrigen) was generated from a mix of acrylamide and bis-acrylamide coated with collagen. Cells were cultured, passaged, and harvested while on top of the hydrogel, using standard cell culture techniques.

**Human studies**—Patients with PAH from whom PAAFs were isolated were part of the French Network on Pulmonary Hypertension, a program approved by our institutional Ethics Committee, and gave written informed consent (Protocol N8CO-08-003, ID RCB: 2008-A00485-50, approved on June 18, 2008). Patients with PAH and controls from whom plasma was obtained were part of a University of Pittsburgh School of Medicine cohort. All patients gave written informed consent. The protocol was approved by the institutional review board at the University of Pittsburgh (IRB: STUDY19050364).

**In vivo animal studies**

**Mouse strains.**: Col1a2-Cre-ER, Yap1fl/fl/Tazfl/fl; and IL-6 transgenic mice (C57/Bl6 background) have been previously described²⁷ or imported from the NCI mouse repository and the Jackson Laboratories.

**Rodent models of PH**

* *Inducible cell-specific YAP and TAZ knockout mice.* Col1a2-Cre-ER mice were crossed onto Yap1fl/fl/Tazfl/fl mice. Tamoxifen was diluted at 20 mg/ml in corn oil (Sigma). Three daily intraperitoneal injection (IP) doses of 30 mg/kg of tamoxifen were administered to ten-week-old mice (C57Bl6) in order to knockout YAP and TAZ in cells expressing Col1a2 – a marker enriched in fibroblasts. Two weeks after injection, exposure to hypoxia commenced.

* *Hypoxia-induced PH.* Mice were exposed to normobaric hypoxia (10% O2; OxyCycler chamber, Biospherix Ltd, Redfield, NY) or normoxia (21% O2) for 3 weeks. In all cohorts, on day 21 after hypoxia exposure, right heart catheterization was performed followed by harvesting of lung tissue, paraffin embedding, or cryopreservation with OCT (Sigma-Aldrich).

* *Monocrotaline-induced PH.* Male Sprague-Dawley rats (10–14 week old) were injected with 60 mg/kg monocrotaline at time 0. At 3 weeks' post-exposure, right heart catheterization was performed followed by harvest of lung tissue, paraffin embedding, or cryopreservation with OCT.
**Trans-pulmonary plasma gradient of monocrotaline-treated rats.:** Male Sprague-Dawley rats, aged 10–14 weeks, were divided into two groups: the PH rats, which received an injection of 60 mg/kg monocrotaline, and the control rats, which received a saline injection. After a three-week period, 200 µl of blood was collected from the left common carotid artery and the inferior vena cava into EDTA tubes. The blood samples were then centrifuged, and the resulting plasma was stored at –80°C for future use.

**Inhibition of GLS1 and/or SHMT1 in PH rats.:** To induce PH, male Sprague-Dawley rats (10–14 weeks old) were injected i.p. with 60 mg/kg monocrotaline (Sigma-Aldrich). After 7 days, serial i.p. injections were given daily of CB-839 (10 mg/kg; Selleck Chemicals) and/or SHIN1 (5mg/kg; Cayman chemical) versus vehicle control. In all cohorts, on day 21 after monocrotaline injection, right heart catheterization was performed followed by harvesting of lung tissue, paraffin embedding, or cryopreservation with OCT (Sigma-Aldrich).

**Diets.:** On standard chow, dietary amino acids are derived from whole proteins contained in the raw ingredients (wheat, wheatfeed, barley, de-hulled extracted toasted soya, maize and fish meal), with a small amount of purified lysine added as a supplement. Two sets of experimental diets were used, both based on Purified Amino Acid Diet from SAFE Nutrition Service: control synthetic diet contained all essential amino acids plus serine, glutamate, proline, and glycine; Glutamine and serine-free diet was the same as synthetic diet-control, but without serine, glutamate, proline, and glycine, with the other amino acid levels increased proportionally to achieve the same total amino acid content. From weaning, rats received standard chow. Male Sprague-Dawley rats, aged 10–14 weeks, were assigned to three distinct groups: standard chow; synthetic control diet; or glutamine and serine-free diet. After 18 days, Sprague-Dawley rats were injected i.p. with 60 mg/kg monocrotaline (Sigma-Aldrich). Right heart catheterization was conducted at day 21 following monocrotaline injection in all experimental groups. Subsequently, lung tissue was harvested and either paraffin embedded or cryopreserved using OCT (Sigma-Aldrich).

**Human plasma harvesting:** To collect blood from subjects from the main pulmonary artery, clinically indicated right heart catheterization procedures were performed by standard protocol via a right internal jugular approach under fluoroscopic guidance. The catheter was positioned into the main pulmonary artery, as confirmed by fluoroscopy and hemodynamic waveforms. Blood was drawn from the distal port and collected in vacutainer tubes with K+-EDTA. Plasma was extracted after centrifugation of blood, followed by storage at –80°C.

## METHOD DETAILS

**Plasmids, antibodies, and reagents—**The YAP1 coding sequence was purchased (Addgene; Plasmid #18881) and sub-cloned in the pCDH-CMV-MCS-EF1-copGFP (System Biosciences) using EcoRI and NotI restriction sites. The lentiviral parent vector expressing GFP was used as a control. Stable expression of these constructs in PAAFs was achieved by lentiviral transduction. Constructs were verified by sequencing. CB-839 (S7655) and SHIN1 (Cat. No. 6998) were purchased from Selleckchem and Tocris respectively. The following commercially available antibodies were used for western blotting and immunofluorescence:
HRP-conjugated donkey anti-mouse IgG (715-035-150) and HRP-conjugated anti-rabbit IgG (711-035-152) were purchased from Jackson ImmunoResearch Laboratories.

**siRNA and plasmid transfection**—Cells were plated on collagen-coated plastic (50µg/mL) and transfected 24h later at 70–80% confluence using siRNA (25nM) and Lipofectamine 2000 reagent (Life Technologies), according to the manufacturers’ instructions. Eight hours after transfection, cells were trypsinized and re-plated on hydrogel. Forty-eight after transfection cells were harvest for analysis. siRNA ON-TARGETplus Human or non-targeting control siRNAs (D-001810-01) were purchased from Horizon Discovery). siRNA ON-TARGETplus Human sequences are provided in the key resources table.

**Lentivirus production**—HEK293T cells were transfected using Lipofectamine 2000 (Thermo Scientific) with lentiviral plasmids along with packaging plasmids (pPACK, System Biosciences), according to the manufacturer’s instructions. Virus was harvested, sterile filtered (0.45 µm), and utilized for subsequent infection of PAAFs (24–48-hour incubation) for gene transduction.

**Immunoblot assays**—Forty-eight hours after plaiting, cells were lysed in RIPA buffer (Pierce) or directly in Laemmli’s buffer. After denaturation, protein lysates were resolved by SDS-PAGE and transferred onto a PVDF membrane (Millipore). Membranes were blocked with 2% BSA in TBS tween20 0.1% and incubated in the presence of the primary and then secondary antibodies. After washing, immunoreactive bands were visualized with ECL (Millipore) and analyzed on Fusion-FX Imager (Vilber).

**Targeted LC-MS**—Metabolite extraction was performed essentially as described¹⁸,³⁶ with minor modifications. Briefly, metabolites were extracted from cultured cells on dry ice using 80% aqueous methanol precooled at –80°C. Insoluble materials from both cell and supernatant extractions was removed by centrifugation at 20,000 g for 15 minutes at 4°C. The supernatant was evaporated to dryness by SpeedVac at 42 °C, the pellet was resuspended in LC-MS water, and metabolites were analyzed by LC-MS.

LC-MS analysis was performed on a Vanquish ultra-high performance liquid chromatography system coupled to a Q Exactive mass spectrometer (Thermo) that was equipped with an Ion Max source and HESI II probe. External mass calibration was performed every seven days. Metabolites were separated using a ZIC-pHILIC stationary phase (150 mm × 2.1 mm × 3.5 mm; Merck) with guard column. Mobile phase A was 20 mM ammonium carbonate and 0.1% ammonium hydroxide. Mobile phase B was acetonitrile. The injection volume was 1 µL, the mobile phase flow rate was 100 µL/min, the column compartment temperature was set at 25 °C, and the autosampler compartment was set at 4 °C. The mobile phase gradient (%B) was 0 min, 80%; 5 min 80%; 30 min, 20%; 31 min, 80%; 42 min, 80%. The column effluent was introduced to the mass spectrometer with the following ionization source settings: sheath gas 40, auxillary gas 15, sweep gas 1, spray voltage +/– 3.0 kV, capillary temperature 275 °C, S-lens RF level 40, probe temperature 350 °C. The mass spectrometer was operated in polarity switching full scan mode from 70–1000 m/z. Resolution was set to 70,000 and the AGC target was 1×10⁶ ions. Data were acquired
and analysed using TraceFinder software (Thermo) with peak identifications based on an in-house library of authentic metabolite standards previously analysed utilizing this method. For all metabolomic experiments, the quantity of the metabolite fraction analysed was adjusted to the corresponding cell number calculated upon processing a parallel experiment.

**Stable isotopic tracing analysis**—To trace the effect of glucose or glutamine or glutamate or serine on amino acid and glucose metabolism, PAAFs were grown 48h on 10 cm plate in DMEM containing 10% FBS, 20mM glucose, 2mM glutamine and then transferred into glucose-free (with 2 mM glutamine) or glutamine free (with 20mM glucose) or serine free (with 2 mM glutamine and 20mM glucose) DMEM containing 10% dialyzed FBS and supplemented with either 20mM U-¹³C-glucose or 2mM U-¹³C-glutamine, or 5mM U-¹³C-glutamate, or 0.5mM U-¹³C-serine respectively for 4 hours prior to metabolite collection. All media were removed, and plates were kept tilted for few seconds to allow any additional media collection in corner of plate. Cells were immediately treated with 4 ml of 80% ice-cold methanol (−80°C) and transferred to −80°C freezer for 20 minutes. Cell plates were resuspended on dry ice and the collected lysate/methanol suspension was transferred to 15 ml conical tubes kept on dry ice. Suspension was centrifuged at full speed (21,000 g) for 5 minutes at 4°C. Supernatants were then transferred to 50 ml conical tubes on dry ice. The pellets were resuspended with 500 µl 80% methanol (−80°C) and a combination of vortexing and pipetting up and down. The suspension was centrifuged at full speed (21,000 g) for 5 minutes at 4°C. Supernatant were transferred to 50 ml conical tubes on dry ice. Pellets obtained after centrifugation were dissolved in urea 8 M (Tris 10 mM pH 8.0) at 60°C, to later measure protein concentration for normalization. After pooling the metabolite extractions, the samples are completely dried under a nitrogen gas apparatus (N-EVAP) and submitted for LC-MS analysis.

Samples were analyzed by High-Performance Liquid Chromatography and High-Resolution Mass Spectrometry and Tandem Mass Spectrometry (HPLC-MS/MS). Specifically, system consisted of a Thermo Q-Exactive in line with an electrospray source and an Ultimate3000 (Thermo) series HPLC consisting of a binary pump, degasser, and auto-sampler outfitted with a Xbridge Amide column (Waters; dimensions of 4.6 mm × 100 mm and a 3.5 µm particle size). The mobile phase A contained 95% (vol/vol) water, 5% (vol/vol) acetonitrile, 20 mM ammonium hydroxide, 20 mM ammonium acetate, pH = 9.0; B was 100% Acetonitrile. The gradient was as following: 0 min, 15% A; 2.5 min, 30% A; 7 min, 43% A; 16 min, 62% A; 16.1–18 min, 75% A; 18–25 min, 15% A with a flow rate of 400 µL/min. The capillary of the ESI source was set to 275 °C, with sheath gas at 45 arbitrary units, auxiliary gas at 5 arbitrary units and the spray voltage at 4.0 kV. In positive/negative polarity switching mode, an m/z scan range from 70 to 850 was chosen and MS1 data was collected at a resolution of 70,000. The automatic gain control (AGC) target was set at 1 × 10⁶ and the maximum injection time was 200 ms. The top 5 precursor ions were fragmented, in a data-dependent manner, using the higher energy collisional dissociation (HCD) cell set to 30% normalized collision energy in MS2 at a resolution power of 17,500. The sample volumes of 10 µl were injected. Data acquisition and analysis were performed by Xcalibur 4.0 software and Tracefinder 2.1 software, respectively (both from Thermo Fisher Scientific).
**4-¹⁸F-(2S,4R)-fluoroglutamine (¹⁸F-FGln) PET imaging**—Synthesis of the precursor for ¹⁸F-FGln was performed as previously described⁵⁶. Production of 4-¹⁸F-(2S,4R)-fluoroglutamine (¹⁸F-FGln) was performed as previously described¹⁶. At 3 weeks' post-treatment, PBS- or monocrotaline-treated rats were anesthetized with 3% isoflurane and injected with 1 mCi of ¹⁸F-FGln via the lateral tail vein. Immediately after injection, PET data were collected during a 60-minute dynamic acquisition with a medium-low magnification CT (full rotation, 220 projections, 80kV and 500 mA with a 550 ms exposure and 2x2 binning) following the PET. PET data were reconstructed using a 2D filtered back-projection (2DFBP) algorithm. CT data were reconstructed at a down sample of 2 with the Siemens Feldkamp algorithm. Using Siemens Inveon Research Workplace software (IRW), individual region of interest (ROI) slices were drawn across relevant tissue compartments (left and right ventricles, lung space and muscle), and the slices for each compartments were interpolated to give a volumetric ROI for that compartment. In the case of the lung space, the volumetric ROI was thresholded to give representations of both airspace and bronchovasculature. The SUV<sub>mean</sub> was determined for each tissue compartment. The SUV values in these regions were each normalized against the SUV<sub>mean</sub> in muscle.

**Multi-isotope Imaging Mass Spectrometry**—Pulmonary vessels were analyzed with a NanoSIMS 50L instrument (Cameca), an ion microscope which enables visualization and quantification of stable isotope tagged metabolic tracers at subcellular resolution along with histologic information. Incorporation of ¹⁵N-serine or ¹⁵N-glutamine, and ²H-glutamine were derived from the simultaneous recording of ¹²C₂¹H⁻, ¹²C¹⁴N⁻, ¹²C₂²H⁻, and ¹²C¹⁵N⁻ images using previously developed analytical approaches³³,⁵⁵. Ratio images, ¹²C¹⁵N⁻/¹²C¹⁴N⁻ (a proxy for ¹⁵N/¹⁴N) and ¹²C₂²H/¹²C₂¹H (a proxy for ²H/¹H) were analyzed using a custom plugin to ImageJ: OpenMIMS 3.0: https://github.com/BWHCNI/OpenMIMS⁵⁷. Isotope ratio data are shown as hue saturation intensity (HSI) images. The lower bound of the scale (blue) is set at natural background. The upper bound is set to visually demonstrate differential labeling. Scaling changes affect the color pattern; however, the underlying quantitative isotopic ratio data is unaffected. ¹⁵N-glutamine image acquisition (Figure 2I–J) was performed with ‘mosaic imaging.’ Alternatively, targeted vessel imaging was pursued in Figure 2K–L. Specifically, vessels were identified based on size, the coordinates were recorded, and higher resolution images were then acquired by directly analyzing individual vessels without capturing surrounding lung parenchyma. This was done to minimize analytical ‘dead space.’

**Messenger RNA extraction**—Cells were homogenized in 1 mL of QiaZol reagent (QIAGEN). Total RNA content was extracted using the miRNeasy kit (QIAGEN) according to the manufacturer's instructions. Total RNA concentration was determined using a ND-1000 micro-spectrophotometer (NanoDrop Technologies).

**Quantitative RT-PCR of messenger RNAs**—Messenger RNAs were reverse transcribed using the Multiscript RT kit (Life Technologies) to generate cDNA. cDNA was amplified via fluorescently labeled Taqman primer sets using an Applied Biosystems 7900HT Fast Real Time PCR device. Fold-change of RNA species was calculated using the formula (2-ΔΔCt), normalized to RPLP0 expression.
**ChIP-qPCR**—PH-PAAF were cultivated on plastic for 48h. Cells were dual cross-linked with 2 mM disuccinimidylglutarate (DSG) for 45 minutes and then in 1% paraformaldehyde for 15 minutes at room temperature. Fixed cells were lysed in 10 ml of Lysis Buffer 1 [50 mM HEPES (pH 7.5), 140 mM NaCl, 1 mM EDTA, 0.1% IGEPAL 630 (Sigma Aldrich)], containing 0.05% Triton X100, 2.5 % glycerol and supplemented with 1X protease inhibitor cocktail (Roche) for 10 minutes on ice, followed by incubation in Buffer 2 [0.1 M Tris HCl (pH 8) and 200 mM NaCl with protease inhibitors] for 15 minutes at room temperature. Chromatin was sonicated at 30% of amplitude for 10 minutes (10 cycles of 1 minute). The samples were centrifuged (2X 14,000 g for 5 minutes each), and soluble chromatin was transferred to a fresh tube. Crosslinked DNA after sonication was precipitated with 5µg of anti-YAP1 antibody (sc-15407X, Santa Cruz Biotechnology) or non-immune rabbit IgG (ab27472, Abcam) overnight at 4°C. Chromatin/antibody complex was pulled down with PureProteome™ Protein G Magnetic Beads (Millipore) and washed in the low- and high-salt buffers. After crosslinking reversion (65°C for 4 hours) and Proteinase K treatment, chromatin was purified by phenol-chloroform extraction and ethanol precipitation. Precipitated DNA was analyzed by qPCR using primers generated for predicted TEAD binding sites or a non-relevant genomic region (Control).

**ChIP-Seq Analysis**—Human gene coordinates from genome assembly GRCh38 were obtained from Ensembl BioMart²⁵. Publicly available conservative IDR-thresholded ChIP-Seq peak calls for TEAD1, TEAD3, and TEAD4 in cells were downloaded from the ENCODE Project²⁶. Genes were considered to have a TEAD binding site if at least one ChIP-Seq peak overlapped with the region beginning 1kb upstream of the gene start and ending 100 (m1000-p100) bases downstream of the gene start. Plots were created in R v4.0.2 using the *ggplot* package; y axes show fold change of TEAD factor binding versus control from ChIP-Seq data, also obtained from ENCODE; x axes show genomic coordinates. The promoter region is shown in gray and the gene region is shown in black. Calculated peaks are shown in red. Hypergeometric enrichment p-values were calculated in Python 3.8 using the *scipy* package.

**KEGG Analysis**—KEGG gene sets were downloaded from the Broad Institute's Molecular Signatures Database (MSigDB). Hypergeometric p-values for enrichment of gene sets for predicted TEAD targets (as defined above) were calculated in Python 3.8 using the *scipy* package.

**Matrix remodeling experiments**—Following treatment, PAAFs were plated in normal growth medium supplemented with 0.5% FBS and 50 µg/ml of ascorbic acid. Medium was changed every day. After five days, PAAF were removed by adding 1 ml of pre-warmed (37°C) extraction buffer (PBS/0.5% Triton X100/20 mM NH4OH). Matrices were washed 3 times (PBS). Naïve PAECs or PASMCs were then plated on top of these matrices supplemented with normal growth medium 0.5% FBS or harvested for assessment of collagen (Sircol assay) or fibrillar collagen content (Picrosirius Red stain). Twenty-four hours later, cells were harvested for immunofluorescence experiments.
**Immunofluorescence**—After the different treatment cells were fixed with PBS/PFA 4% for 10 min and permeabilized with PBS/Triton 100X 0.1% for 10min. Then cells were incubated with anti-P-MLC2 (#3671; 1/100; Cell signaling) or anti-Ki67 (ab15580; 1/300; Abcam) at room temperature for 2 hours. Secondary antibodies coupled with Alexa-594 (Thermo Scientific) or Alexa-488 were used at 1:500. Nuclei were counterstained with DAPI (Sigma-Aldrich). Pictures were obtained using a ZEISS LSM Exciter confocal microscope.

**Measurement of collagen content in matrix**—PAAF-derived matrix was harvested and collagen concentration of the ECM was assessed using Sircol Soluble Collagen Assay Kit (Biocolor) with a colorimetric reaction (measured at 550 nm) and a collagen reference standard curve.

**Measurement of collagen content in lung tissue**—This protocol was adapted from a previously published protocol³. Rodent lung was weighed, minced, and incubated in 0.5 M acetic acid at 4°C. After overnight digestion, the acetic acid-soluble and insoluble fractions were isolated by centrifugation. The soluble fraction was stored at -80°C, while the insoluble fraction was digested by overnight incubation in 6M hydrochloric acid at 85°C. Concentrations of soluble and insoluble (gelatinous) collagen fractions were determined using a Sircol Soluble Collagen Assay Kit (Biocolor) with a colorimetric reaction (measured at 550 nm) and a collagen reference standard curve.

**Picrosirius red stain and quantification**—Picrosirius red stain was achieved through the use of 5µm paraffin sections stained with 0.1% picrosirius red (Direct Red80, Sigma-Aldrich) and counterstained with Weigert's hematoxylin to reveal fibrillar collagen. The sections were then serially imaged using an analyzer and polarizer oriented parallel and orthogonal to each other. Microscope conditions (lamp brightness, condenser opening, objective, zoom, exposure time, and gain parameters) were constant throughout the imaging of all samples. A minimal threshold was set on appropriate control sections for each experiment in which only the light passing through the orthogonally-oriented polarizers representing fibrous structures (i.e., excluding residual light from the black background) was included. The threshold was maintained for all images across all conditions within each experiment. The area of the transferred regions that was covered by the thresholded light was calculated and at least 10 sections/vessel per condition were averaged together (Image J software).

**Atomic force microscopy**—Rodent lungs were inflated with 0.025g of OCT by g of body weight, frozen on liquid nitrogen vapor and store at -80°C. Rodent lung slices (10 µm thickness) were cut out from their glass slide and the fragment of glass containing the sample was glued on the bottom of a 50 mm dish (Willco Glass Bottom Dish). Before measurements the sample was first rinsed and after covered with 4 ml of PBS 1x. The mechanical properties of the samples were studied using a BioScope Catalyst atomic force microscope (Bruker) coupled with an optical microscope (Leica DMI6000B) that enables, by phase contrast, to pinpoint the areas of interest. For each sample, 8-12 vessels per rodent (< 100 µm diameter) were analyzed using the “Point and Shoot” method, collecting
from 80 to 120 force-distance curves at just as many discrete points. The experiments of microindentation were performed in PBS using a probe with a Borosilicate Glass spherical tip (5 µm of diameter) and a cantilever with a nominal spring constant of 0.06 N/m (Novascan). Indentations were carried out using a velocity of 2 µm/s, in relative trigger mode and by setting the trigger threshold to 2 nN. The apparent Young's (elastic) modulus was calculated using the NanoScope Analysis 1.50 software (Bruker), fitting the force curves to the Hertz spherical indentation model and using a Poisson's ratio of 0.4. To avoid large indentation, a minimum and a maximum Force Fit Boundary of 5% and 25% respectively of the whole force curve was taken into account for the fit.

**Statistical analysis**—Numerical quantifications of experiments using cultured cells represents mean ± standard deviation (SD), while numerical quantifications of experiments using rodent or human reagents represent mean ± standard error of the mean (SEM). Atomic force microscopy data are represented by Tukey box-and-whisker plots. Normality of data distribution was determined by Shapiro Wilk testing. Means of 2 sample groups were compared by paired (when appropriate) and unpaired two-tailed Student's T-test for normally distributed data, while Mann-Whitney U non-parametric testing was used for non-normally distributed data. For comparisons among different groups, analysis of variance tests (ANOVA) followed by Bonferroni's *post-hoc* analysis or Kruskal Wallis tests with Dunn's post-hoc analysis (where appropriate for non-normally distributed data) were performed. A P-value less than 0.05 was considered significant.

**Supplementary Material**

Refer to Web version on PubMed Central for supplementary material.

**Acknowledgements:**

We thank the B. Mari team members for advice and discussions as well as F. Aguila for artwork. The authors acknowledge the "Microscopie Imagerie Côte d'Azur" (MICA), GIS-IBISA multi-sites platform and particularly the IPMC, C3M and IRCAN (Molecular and Cellular Imaging facility PICMI) partners. This platform is supported by the GIS IBiSA, Conseil Départemental 06, Région PACA ARC, Cancerôpole PACA,)." We thank the Organic Synthesis Core (Dr George Sukenick and Ms. Rong Wang) and the NMR Analytical Core (MSKCC) for help with NMR and LC-MS experiments.

**Funding:**

This work was supported by: the French National Research Agency ANR-18-CE14-0025, ANR-21-CE44-0036 (for T.B.) and ANR-20-CE14-0006 (for T.B. and F.P.); NIH grants R01 HL124021, HL122596, HL151228 as well as the AHA grant 18EIA33900027 (S.Y.C.). The Organic Synthesis Core at MSKCC was supported in part by NCI R50 CA243895-03 and NCI P30 CA008748-55.

**REFERENCES**

1. Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, Barenko NC, Beaton AZ, Benjamin EJ, Benziger CP, et al. (2020). Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019: Update From the GBD 2019 Study. J Am Coll Cardiol 76, 2982–3021. 10.1016/j.jacc.2020.11.010. [PubMed: 33309175]

2. Cecelja M, and Chowienczyk P (2012). Role of arterial stiffness in cardiovascular disease. JRSM Cardiovasc Dis 1. 10.1258/cvd.2012.012016.

3. Bertero T, Cottrill KA, Lu Y, Haeger CM, Dieffenbach P, Annis S, Hale A, Bhat B, Kaimal V, Zhang Y-Y, et al. (2015). Matrix Remodeling Promotes Pulmonary Hypertension through
Feedback Mechanoactivation of the YAP/TAZ-miR-130/301 Circuit. Cell Rep 13, 1016-1032. 10.1016/j.celrep.2015.09.049. [PubMed: 26565914]

4. Kothapalli D, Liu S-L, Bae YH, Monslow J, Xu T, Hawthorne EA, Byfield FJ, Castagnino P, Rao S, Rader DJ, et al. (2012). Cardiovascular protection by apoE and apoE-HDL linked to suppression of ECM gene expression and arterial stiffening. Cell Rep 2, 1259-1271. 10.1016/j.celrep.2012.09.018. [PubMed: 23103162]

5. Zhang H, Wang D, Li M, Plecitá-Hlavatá L, D'Alessandro A, Tauber J, Riddle S, Kumar S, Flockton A, McKeon BA, et al. (2017). Metabolic and Proliferative State of Vascular Adventitial Fibroblasts in Pulmonary Hypertension Is Regulated Through a MicroRNA-124/PTBP1 (Polypyrimidine Tract Binding Protein 1)/Pyruvate Kinase Muscle Axis. Circulation 136, 2468-2485. 10.1161/CIRCULATIONAHA.117.028069. [PubMed: 28972001]

6. Mouw JK, Ou G, and Weaver VM (2014). Extracellular matrix assembly: a multiscale deconstruction. Nat. Rev. Mol. Cell Biol. 15, 771-785. 10.1038/nrm3902. [PubMed: 25370693]

7. Xu J, and Shi G-P (2014). Vascular wall extracellular matrix proteins and vascular diseases. Biochim Biophys Acta 1842, 2106-2119. 10.1016/j.bbadis.2014.07.008. [PubMed: 25045854]

8. WAGENSEIL JE, and MECHAM RP (2009). Vascular Extracellular Matrix and Arterial Mechanics. Physiol Rev 89, 957-989. 10.1152/physrev.00041.2008. [PubMed: 19584318]

9. Shoulders MD, and Raines RT (2009). COLLAGEN STRUCTURE AND STABILITY. Annu Rev Biochem 78, 929-958. 10.1146/annurev.biochem.77.032207.120833. [PubMed: 19344236]

10. Willett W (2012). Nutritional Epidemiology Third Edition. (Oxford University Press).

11. Powell-Wiley TM, Poirier P, Burke LE, Després J-P, Gordon-Larsen P, Lavie CJ, Lear SA, Ndumele CE, Neeland IJ, Sanders P, et al. (2021). Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation 143, e984-e1010. 10.1161/CIR.0000000000000973. [PubMed: 33882682]

12. Bartholomew CL, Muhlestein JB, May HT, Le VT, Galenko O, Garrett KD, Brunker C, Hopkins RO, Carlquist JF, Knowlton KU, et al. (2021). Randomized controlled trial of once-per-week intermittent fasting for health improvement: the WONDERFUL trial. Eur Heart J Open 1, oeab026. 10.1093/ehjopen/oeab026. [PubMed: 35919268]

13. Dong TA, Sandesara PB, Dhindsa DS, Mehta A, Arneson LC, Dollar AL, Taub PR, and Sperling LS (2020). Intermittent Fasting: A Heart Healthy Dietary Pattern? Am J Med 133, 901-907. 10.1016/j.amjmed.2020.03.030. [PubMed: 32330491]

14. Prisco SZ, Eklund M, Moutsoglou DM, Prisco AR, Khoruts A, Weir EK, Thenappan T, and Prins KW (2021). Intermittent Fasting Enhances Right Ventricular Function in Preclinical Pulmonary Arterial Hypertension. J Am Heart Assoc 10, e022722. 10.1161/JAHA.121.022722. [PubMed: 34747187]

15. Bertero T, Oldham WM, Cottrill KA, Pisano S, Vanderpool RR, Yu Q, Zhao J, Tai Y, Tang Y, Zhang Y-Y, et al. (2016). Vascular stiffness mechanoactivates YAP/TAZ-dependent glutaminolysis to drive pulmonary hypertension. J. Clin. Invest 126, 3313-3335. 10.1172/JCI86387. [PubMed: 27548520]

16. Venneti S, Dunphy MP, Zhang H, Pitter KL, Zanzonico P, Campos C, Carlin SD, La Rocca G, Lyashchenko S, Ploessl K, et al. (2015). Glutamine-based PET imaging facilitates enhanced metabolic evaluation of gliomas in vivo. Sci Transl Med 7, 274ra17. 10.1126/ scitranslmed.aaa1009.

17. Levental KR, Yu H, Kass L, Lakins JN, Egeblad M, Erler JT, Fong SFT, Csiszar K, Giaccia A, Weninger W, et al. (2009). Matrix crosslinking forces tumor progression by enhancing integrin signaling. Cell 139, 891-906. 10.1016/j.cell.2009.10.027. [PubMed: 19931152]

18. Bertero T, Oldham WM, Grasset EM, Bourget I, Boulter E, Pisano S, Hofman P, Bellvert F, Meneguzzi G, Bulavin DV, et al. (2019). Tumor-Stroma Mechanics Coordinate Amino Acid Availability to Sustain Tumor Growth and Malignancy. Cell Metab 29, 124-140.e10. 10.1016/ j.cmet.2018.09.012. [PubMed: 30293773]

19. Torrino S, and Bertero T (2022). Metabo-reciprocity in cell mechanics: feeling the demands/ feeding the demand. Trends Cell Biol 10.1016/j.tcb.2022.01.013.
20. Zheng A, Chen Q, and Zhang L (2022). The Hippo-YAP pathway in various cardiovascular diseases: Focusing on the inflammatory response. Front Immunol 13, 971416. doi: 10.3389/fimmu.2022.971416 [PubMed: 36059522]

21. Panciera T, Azzolin L, Cordenonsi M, and Piccolo S (2017). Mechanobiology of YAP and TAZ in physiology and disease. Nat. Rev. Mol. Cell Biol 10.1038/nrm.2017.87.

22. Calvo F, Ege N, Grande-Garcia A, Hooper S, Jenkins RP, Chaudhry SI, Harrington K, Williamson P, Moeendarbary E, Charras G, et al. (2013). Mechanotransduction and YAP-dependent matrix remodelling is required for the generation and maintenance of cancer-associated fibroblasts. Nat. Cell Biol 15, 637–646. 10.1038/ncb2756. [PubMed: 23708000]

23. Totaro A, Panciera T, and Piccolo S (2018). YAP/TAZ upstream signals and downstream responses. Nat. Cell Biol 20, 888–899. 10.1038/s41556-018-0142-z. [PubMed: 30050119]

24. Meng Z, Moroishi T, and Guan K-L (2016). Mechanisms of Hippo pathway regulation. Genes Dev 30, 1–17. 10.1101/gad.274027.115. [PubMed: 26728553]

25. Yates AD, Achuthan P, Akanni W, Allen J, Allen J, Alvarez-Jarreta J, Amode MR, Armean IM, Azov AG, Bennett R, et al. (2020). Ensembl 2020. Nucleic Acids Res 48, D682–D688. 10.1093/nar/gkz966. [PubMed: 31691826]

26. Partridge EC, Chhetri SB, Prokop JW, Ramaker RC, Jansen CS, Goh S-T, Mackiewicz M, Newberry KM, Brandsmeier LA, Meadows SK, et al. (2020). Occupancy maps of 208 chromatin-associated proteins in one human cell type. Nature 583, 720–728. 10.1038/s41586-020-2023-4. [PubMed: 32728244]

27. Steiner MK, Syrkina OL, Kolliputi N, Mark EJ, Hales CA, and Waxman AB (2009). Interleukin-6 overexpression induces pulmonary hypertension. Circ Res 104, 236–244, 28p following 244. 10.1161/CIRCRESAHA.108.182014. [PubMed: 19074475]

28. Romani P, Valcarcel-Jimenez L, Frezza C, and Dupont S (2020). Crosstalk between mechanotransduction and metabolism. Nat Rev Mol Cell Biol 1–17. 10.1038/s41580-020-00306-w. [PubMed: 31676888]

29. Enzo E, Santinon G, Pocaterra A, Aragona M, Bresolin S, Forcato M, Grifoni D, Pession A, Zanconato F, Guzzo G, et al. (2015). Aerobic glycolysis tunes YAP/TAZ transcriptional activity. EMBO J 34, 1349–1370. 10.15252/embj.201490379. [PubMed: 25796446]

30. Mo J-S, Meng Z, Kim YC, Park HW, Hansen CG, Kim S, Lim D-S, and Guan K-L (2015). Cellular energy stress induces AMPK-mediated regulation of YAP and the Hippo pathway. Nat. Cell Biol 17, 500–510. 10.1038/ncb3111. [PubMed: 25751140]

31. Wang W, Xiao Z-D, Li X, Aziz KE, Gan B, Johnson RL, and Chen J (2015). AMPK modulates Hippo pathway activity to regulate energy homeostasis. Nat Cell Biol 17, 490–499. 10.1038/ncb3113. [PubMed: 25751139]

32. Kudryashova TV, Goncharov DA, Pena A, Kelly N, Vanderpool R, Baust J, Kobir A, Shufesky W, Mora AL, Morelli AE, et al. (2016). HIPPO-Integrin-linked Kinase Cross-Talk Controls Self-Sustaining Proliferation and Survival in Pulmonary Hypertension. Am. J Respir. Crit. Care Med 194, 866–877. 10.1164/rccm.201510-2003OC. [PubMed: 27119551]

33. Wertheim BM, Wang R-S, Guillermier C, Hütter CVR, Oldham WM, Menche J, Steinhauser ML, and Maron BA (2023). Proline and glucose metabolic reprogramming supports vascular endothelial and medial biomass in pulmonary arterial hypertension. JCI Insight 8. 10.1172/jci.insight.163932.

34. Stenmark KR, Yeager ME, El Kasmi KC, Nozik-Grayck E, Gerasimovskaya EV, Li M, Riddle SR, and Frid MG (2013). The Adventitia: Essential Regulator of Vascular Wall Structure and Function. Annu Rev Physiol 75, 23–47. 10.1146/annurev-physiol-030212-183802. [PubMed: 23216413]

35. Song M, Kim S-H, Im CY, and Hwang H-J (2018). Recent Development of Small Molecule Glutaminase Inhibitors. Curr Top Med Chem 18, 432–443. 10.2174/1568026618666180525100830. [PubMed: 29793408]

36. Torrino S, Grasset EM, Audebert S, Belhadj I, Lacoux C, Haynes M, Pisano S, Abélanet S, Brau F, Chan SY, et al. (2021). Mechano-induced cell metabolism promotes microtubule glutamylation to force metastasis. Cell Metab 33, 1342–1357.e10. 10.1016/j.cmet.2021.05.009. [PubMed: 34102109]
37. Amelio I, Cutruzzolá F, Antonov A, Agostini M, and Melino G (2014). Serine and glycine metabolism in cancer. *Trends Biochem Sci* 39, 191–198. 10.1016/j.tibs.2014.02.004. [PubMed: 24657017]

38. Geeraerts SL, Heylen E, De Keersmaecker K, and Kampen KR (2021). The ins and outs of serine and glycine metabolism in cancer. *Nat Metab* 3, 131–141. 10.1038/s42255-020-00329-9. [PubMed: 33510397]

39. DiRenzo D, Owens GK, and Leeper NJ (2017). Attack of the Clones. *Circ Res* 120, 624–626. 10.1161/CIRCRESAHA.116.310091. [PubMed: 28209794]

40. Boucherat O, Vitry G, Trinh I, Paulin R, Provencher S, and Bonnet S (2017). The cancer theory of pulmonary arterial hypertension. *Pulm Circ* 7, 285–299. 10.1177/2045893217701438. [PubMed: 28597757]

41. Hoeper MM, Humbert M, Souza R, Idrees M, Kawut SM, Sliwa-Hahnle K, Jing Z-C, and Gibbs JSR (2016). A global view of pulmonary hypertension. *Lancet Respir Med* 4, 306–322. 10.1016/S2213-2600(15)00543-3. [PubMed: 26975810]

42. van de Veerdonk MC, Marcus JT, Bogaard H-J, and Vonk Noordegraaf A (2014). State of the art: advanced imaging of the right ventricle and pulmonary circulation in humans (2013 Grover Conference series). *Pulm Circ* 4, 158–168. 10.1086/675978. [PubMed: 25006434]

43. Chan SY, and Rubin LJ (2017). Metabolic dysfunction in pulmonary hypertension: from basic science to clinical practice. *Eur Respir Rev* 26, 170094. 10.1183/16000617.0094-2017. [PubMed: 29263174]

44. Zhou R, Pantel AR, Li S, Lieberman BP, Ploessl K, Choi H, Blankemeyer E, Lee H, Kung HF, Mach RH, et al. (2017). [18F](2S,4R)4-Fluoroglutamine PET Detects Glutamine Pool Size Changes in Triple-Negative Breast Cancer in Response to Glutaminase Inhibition. *Cancer Res* 77, 1476–1484. 10.1158/0008-5472.CAN-16-1945. [PubMed: 28202527]

45. Lieberman BP, Ploessl K, Wang L, Qu W, Zha Z, Wise DR, Chodosh LA, Belka G, Thompson CB, and Kung HF (2011). PET imaging of glutaminolysis in tumors by 18F-(2S,4R)4-fluoroglutamine. *J Nucl Med* 52, 1947–1955. 10.2967/jnumed.111.093815. [PubMed: 22095958]

46. Acharya AP, Tang Y, Bertero T, Tai Y-Y, Harvey LD, Woodcock C-SC, Sun W, Pineda R, Mitash N, Königshoff M, et al. (2021). Simultaneous Pharmacologic Inhibition of Yes-Associated Protein 1 and Glutaminase 1 via Inhaled Poly(Lactic-co-Glycolic) Acid-Encapsulated Microparticles Improves Pulmonary Hypertension. *J Am Heart Assoc* 10, e019091. 10.1161/JAHA.120.019091. [PubMed: 34056915]

47. Acharya AP, Clare-Salzler MJ, and Keselowsky BG (2009). A high-throughput microparticle microarray platform for dendritic cell-targeting vaccines. *Biomaterials* 30, 4168–4177. 10.1016/j.biomaterials.2009.04.032. [PubMed: 19477505]

48. Roscigno R, Vaughn T, Anderson S, Wargin W, Hunt T, and Hill NS (2020). Pharmacokinetics and tolerability of LIQ861, a novel dry-powder formulation of treprostinil. *Pulm Circ* 10, 2045894020971509. 10.1177/2045894020971509. [PubMed: 33282202]

49. Schroeder SA (2007). We Can Do Better — Improving the Health of the American People. *New Engl J Med* 357, 1221–1228. 10.1056/NEJMsa073350. [PubMed: 17881753]

50. Khera AV, Emdin CA, Drake I, Natarajan P, Bick AG, Cook NR, Chasman DI, Baber U, Mehran R, Rader DJ, et al. (2016). Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease. *New Engl J Med* 375, 2349–2358. 10.1056/NEJMoa1605086. [PubMed: 27959714]

51. Ozlu T, Yilmaz Y, and Gunes FE (2022). The effects of dietary intervention on fibrosis and biochemical parameters in metabolic-associated fatty liver disease. *Minerva Gastroenterol (Torino)* 68, 426–433. 10.23736/S2724-5985.21.02809-9. [PubMed: 33829726]

52. de Cabo R, and Mattson MP (2019). Effects of Intermittent Fasting on Health, Aging, and Disease. *N Engl J Med* 381, 2541–2551. 10.1056/NEJMra1905136. [PubMed: 31881139]

53. Barabási A-L, Menichetti G, and Loscalzo J (2020). The unmapped chemical complexity of our diet. *Nature Food* 1, 33–37. 10.1038/s43016-019-0005-1.

54. Swonger JM, Liu JS, Ivey MJ, and Tallquist MD (2016). Genetic Tools for Identifying and Manipulating Fibroblasts in the Mouse. *Differentiation* 92, 66–83. 10.1016/j.diff.2016.05.009. [PubMed: 27342817]
55. Murashige D, Jang C, Neinast M, Edwards JJ, Cowan A, Hyman MC, Rabinowitz JD, Frankel DS, and Arany Z (2020). Comprehensive quantification of fuel use by the failing and nonfailing human heart. Science 370, 364–368. 10.1126/science.abc8861. [PubMed: 33060364]

56. Qu W, Zha Z, Ploessl K, Lieberman BP, Zhu L, Wise DR, B. Thompson C., and Kung HF. (2011). Synthesis of Optically Pure 4-Fluoro-Glutamines as Potential Metabolic Imaging Agents for Tumors. J. Am. Chem. Soc 133, 1122–1133. 10.1021/ja109203d. [PubMed: 21190335]

57. Guillermier C, Poczatek JC, Taylor WR, and Steinhauser ML (2017). Quantitative imaging of deuterated metabolic tracers in biological tissues with nanoscale secondary ion mass spectrometry. Int J Mass Spectrom 422, 42–50. 10.1016/j.ijms.2017.08.004. [PubMed: 29276427]
## Highlights

* YAP/TAZ control glutamine and serine catabolism for collagen biosynthesis

* Such amino acid metabolism promotes pathogenic activation of vascular fibroblasts

* Pharmacologic or dietary intervention improves pulmonary vascular stiffness and disease
<figure><img src="image_3.png" /><figcaption>**Figure 1: In vitro and in vivo evidence of proline and glycine metabolic rewiring in PH.**

(A-B) Heatmap (A) and pathway enrichment analysis (B) of significantly (FDR<0.1; P<0.05) modulated intracellular metabolites in PH-PAAFs, with log₂(fold change) range between -4 to 4. (C) Heatmap of significantly (FDR<0.1; P<0.05) modulated metabolites in PH-PAAF conditioned media, with log₂(fold change) range between -2 to 2. (D) Schema of blood sampling for measurement of transpulmonary gradient of metabolites in rat (yellow, site of blood collection). (E) Heat map of significantly (FDR<0.1; P<0.05) modulated metabolites in the transpulmonary gradient of monocrotaline-exposed rats (N=8</figcaption></figure>
per group), with log₂(fold change) range between −1 to 1. (F) Schema of blood sampling for measurement of transpulmonary gradient of metabolites in human. (G) Level of indicated metabolites in the transpulmonary gradient of patients with PH (N=8) and control (N=5). P values calculated by paired two-tailed Student's T-test. Mono: Monocrotaline. PCW: Pulmonary capillary wedge. N' numbers indicate biological replicates.
<figure><img src="image_4.png" /><figcaption>Figure 2: Glutamine and serine catabolism sustain proline and glycine anabolism in activated pulmonary arterial adventitial fibroblasts (PAAFs).</figcaption></figure>

(A) Schematic representation of glucose, glutamine, and serine pathways. (B-E) PAAFs plated on the indicated substrate and treated as indicated. Heatmap of ¹³C₆-glucose (B), ¹³C₅-glutamine (C), ¹³C₅-glutamate (D) and ¹³C₃-serine (E) incorporation in intracellular metabolites. (F) ¹⁸F-FGln-PET imaging displayed increased tracer uptake in RV (white arrow) and lung (red arrow) of MCT PAH rats. (G-H) ¹⁸F-FGln uptake in regions of bronchovasculature (G), and lung parenchyma (H) in monocrotaline-exposed rats (N=6)
as compared with PBS control (N=6). Data are expressed as standard uptake value ratios (SUVr). (I-M) After treating monocrotaline-exposed rats vs. controls (N=3-4 per group) with ¹⁵N-labeled glutamine, ¹⁵N-labeled serine, or ¹⁵N-labeled serine and ²H-labeled glutamine administered simultaneously, rats were sacrificed, and fixed lung was analyzed by multi-isotope imaging mass spectrometry (MIMS). Representative images (I, K and L) and quantification of ¹⁵N-glutamine (J), and ¹⁵N-serine and ²H-glutamine (M) incorporation by pulmonary arteriolar mural cells, expressed as percent above background ratio. The rainbow scale is set from 0% above background ratio in blue to 100% for glutamine or 150% for serine in red (2 to 2.5 fold above background ratio). Scale=10 µm. In all the panels *P<0.05; **P<0.01; two-tailed Student's t-test was used; data show mean ± s.e.m. N' numbers indicate biological replicates.
<figure><img src="image_5.png" /><figcaption>**Figure 3: Glutamine and serine catabolism sustain the metabolic needs of collagen biosynthesis. (A-B) Collagen concentration (media) of IL-6-activated PAAFs (A) and PH-PAAFs (B) treated as indicated. (C-I) Schema of the experimental procedure (C). Representative image (D and F) and quantification (E, G and I) of fibrillar collagen and vascular (PAEC and PASMC) cell proliferation. (H) Matrix stiffness assessed by atomic force microscopy. Data are represented by Tukey box-and-whisker plots. Median represents measures from n=3 matrices/group. In all panels **P<0.01; ***P<0.001; ANOVA with Bonferroni's multiple comparison test was used in (A-G, I); Kruskal-Wallis with Dunn's post-hoc testing was**</figcaption></figure>
used in (H); data show mean ± s.d. Scale=20 µm. For all the panels, each dot represents a
biological replicates.
<figure><img src="image_6.png" /><figcaption>Figure 4: YAP and TAZ metabolically control collagen biosynthesis.</figcaption></figure>

(A) Pathway enrichment analysis of genes with TEAD biding sites (ENCODE Project) in their promoter regions. (B) Schematic of the collagen metabolism pathway. (C) TEAD binding enrichment in the promoter region of indicated genes. (D) ChIP-qPCR confirmed the presence of TEAD/YAP binding sites in the promoter regions of indicated genes. Results are expressed as percentage of total input DNA prior to immunoprecipitation with anti-YAP or anti-IgG control. (E-F) Heatmap with log2(fold change) range between -2 to 2 (E) and pathway enrichment analysis (F) of significantly (FDR<0.1; P<0.05) modulated
intracellular metabolites in PAAFs treated as indicated. (G-H) PAAFs were treated as indicated. Heatmap of ¹³C₅-glutamine (G) and ¹³C₃-serine (H) incorporation in intracellular metabolites. (I) Matrix collagen concentration of PAAFs treated as indicated. (J-L) Schema of the experimental procedure (J). Representative image (K) and quantification (L) of fibrillar collagen and vascular (PAEC and PASMC) cell proliferation. Scale=20 µm. In all panels *P*<0.05; **P*<0.01; ****P*<0.0001; Mann-Whitney test was used in (D:SLC6A9-E; SHMT1:E); two-tailed Student's T-test was used in remaining panels of (D); ANOVA with Bonferroni's multiple comparison test was used in (I, L: Ki67 graphs); Kruskal-Wallis with Dunn's post-hoc testing was used in (L: area thresholded). Data show mean ± s.d. For all the panels, each dot represents a biological replicates.
A

<figure><img src="image_7.png" /></figure>

B

<figure><img src="image_8.png" /></figure>

C

<figure><img src="image_9.png" /></figure>

D

<figure><img src="image_10.png" /></figure>

E

<figure><img src="image_11.png" /></figure>

F

<figure><img src="image_12.png" /></figure>

G

<figure><img src="image_13.png" /></figure>

H

<figure><img src="image_14.png" /></figure>

I

<figure><img src="image_15.png" /></figure>

J

<figure><img src="image_16.png" /></figure>

K

<figure><img src="image_17.png" /><figcaption>Figure 5: Genetic deletion of YAP and TAZ in vascular fibroblast prevents collagen biosynthesis and ameliorates PH.</figcaption></figure>

(A) Protocol for conditional YAP/TAZ deletion (cKO) in IL-6 transgenic mice. (B-C, E, and H) Immunostaining and quantification for GLS1 (B), SHMT1 (C), collagen I (Col1; E) and Ki67 (H) in pulmonary artery from YAP/TAZ<sup>cKO</sup> mice or control mice (Ctrl).

(D) Collagen concentration (Total and fibrillar) of lungs from YAP/TAZ<sup>cKO</sup> mice or Ctrl mice. (F) Representative images and quantification of picrosirius red staining in pulmonary artery from YAP/TAZ<sup>cKO</sup> mice or Ctrl mice. (G) Pulmonary vascular stiffness assessed by atomic force microscopy. Data are represented by Tukey box-and-whisker plots. Median represents measures from n=3 mice/group. (I-K) Pulmonary arteriolar muscularization (I), right ventricular systolic pressure (J), and right ventricular hypertrophy (Fulton index, RV/LV+S; K) of YAP/TAZ<sup>cKO</sup> mice or Ctrl mice. Scale=50 µm. In all panels, *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001; Mann-Whitney test was used in (F:Orthogonal; G-I); two-tailed Student's T-test was used in (B-E; F:Parallel; J-K). Data show mean ± s.e.m. Panel B-C, E-F, and H-I: each dot represents a single artery from N=5 Control mice and N=6 cKO mice. Panel D and J-K each dot represents a single mouse
A

<figure><img src="image_18.png" /></figure>

B

<figure><img src="image_19.png" /></figure>

C

<figure><img src="image_20.png" /></figure>

D

<figure><img src="image_21.png" /></figure>

E

<figure><img src="image_22.png" /></figure>

F

<figure><img src="image_23.png" /></figure>

G

<figure><img src="image_24.png" /></figure>

H

<figure><img src="image_25.png" /><figcaption>Figure 6: Pharmacologic inhibition of glutamine and serine catabolism decreases collagen biosynthesis and vascular stiffening in PH.</figcaption></figure>

(A) In a protocol of disease reversion, rats were subjected to monocrotaline injection, and seven days later, they received daily i.p. injections of either GLS1 inhibitor (CB-839, N=8), or SHMT1 inhibitor (SHIN1, N=9), or both CB-839 + SHIN1 (N=9) or vehicle (Ctrl; N=9). (B) Collagen concentration (Total and fibrillar) of lungs from rats treated as indicated. (C) Immunostaining and quantification for collagen I (Col1) in pulmonary artery from rats treated as indicated. (D) Pulmonary vascular stiffness assessed by atomic
force microscopy. Data are represented by Tukey box-and-whisker plots. Median represents
measures from n=4 rats/group for (SHIN1 and CB-839+SHIN1) and n=7 rats/group for (Ctrl
and CB-839). (E) Immunostaining and quantification for Ki67 in pulmonary artery from
rats treated as indicated. (F-H) Pulmonary arteriolar muscularization (F), right ventricular
systolic pressure (G), and right ventricular hypertrophy (Fulton index, RV/LV+S; H) of rats
treated as indicated. Each dot represents a single rat. Scale=50 µm. In all panels *P<0.05;
**P<0.01; ***P<0.001; ****P<0.0001; ANOVA with Bonferroni's multiple comparison test
was used in (B, C, E, H); Kruskal-Wallis with Dunn's post-hoc testing was used in (D, F, G).
Data show mean ± s.e.m. In panels B-C, and E-H each dot represents a single rat
<figure><img src="image_26.png" /><figcaption>Figure 7: A glutamine- and serine-free diet prevents pulmonary vascular stiffening and PH.</figcaption></figure>

(A) Rats received normal chow until 12 weeks of age; they were then transferred to either a control diet (synthetic diet, containing glutamine and serine) or a matched diet lacking glutamine and serine (Gln⁻/Ser⁻ diet). Eighteen (18) days after diets were initiated, rats were injected with monocrotaline. At Day 39, rats were euthanized and assessed for PH. (B) Serum levels of glutamine, serine, and glucose were analyzed at serial time points. Mean expression in control group was assigned a fold change of 1, to which relevant samples were compared. (C) At D39, serum levels of the indicated metabolites were analyzed. Unpaired
two-tailed Student's T-test and Mann-Whitney test. (D) Collagen concentration (total and fibrillar) of lungs from rats treated as indicated. (E) Immunostaining and quantification for collagen I (Col1) in pulmonary artery from rats treated as indicated. (F) Pulmonary vascular stiffness assessed by atomic force microscopy. Data are represented by Tukey box-and-whisker plots. Median represents measures from n=7 rats/group for (standard diet) and n=4 rats/group for (synthetic diet and Gln⁻/Ser⁻ diet). (G-H) Immunostaining (G) and quantification (H) for Ki67 in pulmonary artery from rats treated as indicated. (I-K) Pulmonary arteriolar muscularization (I), right ventricular systolic pressure (J), and right ventricular hypertrophy (Fulton index, RV/LV+S; K) of rats treated as indicated. Each dot represents a single rat. Scale=50 µm. In all panels, *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001; Mann-Whitney test was used in (C:glutamine/glutamate; phenylalanine/ tyrosine; D:soluble/insoluble collagen); two-tailed Student's T-test was used in remaining panels of (C) as well as (D: collagen). ANOVA with Bonferroni's multiple comparison test was used in (E, G, H, I, J); Kruskal-Wallis with Dunn's post-hoc testing was used in (F). Data show mean ± s.e.m. In panels C-E and G-J each dot represents a single rat.
KEY RESOURCES TABLE

<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td colspan="3"><strong>Antibodies</strong></td></tr><tr><td>Rabbit Polyclonal anti-MLC2</td><td>Cell Signaling Technology</td><td>Cat# 3672S; RRID: AB_10692513</td></tr><tr><td>Mouse Monoclonal anti-P-MLC2</td><td>Cell Signaling Technology</td><td>Cat# 3675S; RRID: AB_2250969</td></tr><tr><td>Mouse Monoclonal anti-HIF1-α</td><td>Abcam</td><td>Cat# ab1; RRID: AB_296474</td></tr><tr><td>Mouse Monoclonal anti-Tubulin</td><td>Santa Cruz Biotechnology</td><td>Cat# sc-398937</td></tr><tr><td>Mouse Monoclonal anti-Hsp90</td><td>Santa Cruz Biotechnology</td><td>Cat# sc-69703; RRID: AB_2121191</td></tr><tr><td>Rabbit Polyclonal anti-GLS1</td><td>Abcam</td><td>Cat# ab156876; RRID: AB_2721038</td></tr><tr><td>Rabbit Monoclonal anti-SHMT1</td><td>Cell Signaling Technology</td><td>Cat# 80715; RRID: AB_2799957</td></tr><tr><td>Rabbit Monoclonal anti-YAP</td><td>Cell Signaling Technology</td><td>Cat# 14074; RRID: AB_2650491</td></tr><tr><td>Rabbit Polyclonal anti-YAP</td><td>Santa Cruz Biotechnology</td><td>Cat# sc-15407; RRID: AB_2273277</td></tr><tr><td>Rabbit Polyclonal anti-TAZ</td><td>Santa Cruz Biotechnology</td><td>Cat# sc-48805; RRID: AB_2216639</td></tr><tr><td>Rabbit Polyclonal anti-Ki67</td><td>Abcam</td><td>Cat# ab15580; RRID: AB_443209</td></tr><tr><td>Goat Polyclonal anti-αSMA</td><td>Abcam</td><td>Cat# ab21027; RRID: AB_1951138</td></tr><tr><td>Mouse Monoclonal anti-αSMA</td><td>Sigma-Aldrich</td><td>Cat# A5228-200; RRID: AB_262054</td></tr><tr><td>Rabbit Monoclonal anti-αSMA</td><td>Abcam</td><td>Cat# ab32575; RRID: AB_722538</td></tr><tr><td>Mouse Monoclonal anti-Vimentin</td><td>Abcam</td><td>Cat# ab20346; RRID: AB_445527</td></tr><tr><td>Goat Monoclonal anti-CD31</td><td>R&amp;D Systems</td><td>Cat# AF3628; RRID: AB_2161028</td></tr><tr><td>Rabbit Monoclonal anti-Collagen I</td><td>Abcam</td><td>Cat# ab260043</td></tr><tr><td>Peroxidase-AffiniPure Donkey Anti-Mouse IgG (H+L)</td><td>Jackson ImmunoResearch Labs</td><td>Cat# 715-035-150; RRID: AB_2340770</td></tr><tr><td>Peroxidase-AffiniPure Donkey Anti-Rabbit IgG (H+L)</td><td>Jackson ImmunoResearch Labs</td><td>Cat# 711-035-152; RRID: AB_10015282</td></tr><tr><td>Donkey anti-Goat IgG (H+L) Antibody, Alexa Fluor 488</td><td>Thermo Fisher Scientific</td><td>Cat# A11055; RRID: AB_2534102</td></tr><tr><td>Donkey anti-Rabbit IgG (H+L) Antibody, Alexa Fluor 594</td><td>Thermo Fisher Scientific</td><td>Cat# A21207; RRID: AB_141637</td></tr><tr><td>Donkey anti-Mouse IgG (H+L) Antibody, Alexa Fluor 647</td><td>Thermo Fisher Scientific</td><td>Cat# A31571; RRID: AB_162542</td></tr><tr><td colspan="3"><strong>Bacterial and virus strains</strong></td></tr><tr><td>/</td><td>/</td><td>/</td></tr><tr><td colspan="3"><strong>Biological samples</strong></td></tr><tr><td colspan="3"><strong>Chemicals, peptides, and recombinant proteins</strong></td></tr><tr><td>Monocrotaline</td><td>Sigma-Aldrich</td><td>Cat# PHL89251</td></tr><tr><td>Tamoxifen</td><td>Sigma-Aldrich</td><td>Cat# T5648</td></tr><tr><td>Sirius red (Direct Red 80)</td><td>Sigma-Aldrich</td><td>Cat# 365548</td></tr><tr><td>DAPI</td><td>Sigma-Aldrich</td><td>Cat# D9542</td></tr><tr><td>Recombinant Human TGF-β1</td><td>PeproTech</td><td>Cat# 100-21</td></tr><tr><td>Recombinant Human IL-6</td><td>PeproTech</td><td>Cat# 200-06</td></tr><tr><td>CB-839 glutaminase inhibitor</td><td>Selleckchem</td><td>Cat# S7655</td></tr><tr><td>SHIN 1 SHMT inhibitor</td><td>Tocris</td><td>Cat# 6998</td></tr><tr><td>D-Glucose U-13C<sub>6</sub></td><td>Cambridge Isotope Laboratories</td><td>Cat# CLM-1396-1</td></tr></tbody></table>
<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td>L-Glutamine <sup>13</sup>C<sub>5</sub></td><td>Cambridge Isotope Laboratories</td><td>Cat#CLM-1822-H-0.1</td></tr><tr><td>L-Glutamate <sup>13</sup>C<sub>5</sub></td><td>Cambridge Isotope Laboratories</td><td>Cat#CLM-1800-H-0.5</td></tr><tr><td>L-Serine <sup>13</sup>C<sub>3</sub></td><td>Cambridge Isotope Laboratories</td><td>Cat#CLM-1574-H-0.1</td></tr><tr><td>L-Proline <sup>13</sup>C<sub>5</sub></td><td>Cambridge Isotope Laboratories</td><td>Cat#CLM-2260-H-0.1</td></tr><tr><td>Lipofectamine 2000</td><td>Thermo Fisher Scientific</td><td>Cat#11668500</td></tr><tr><td>Pierce RIPA Buffer</td><td>Thermo Fisher Scientific</td><td>Cat#89900</td></tr><tr><td>2x Laemmli Sample Buffer</td><td>Bio-Rad</td><td>Cat#1610737</td></tr><tr><td>Immobilon Western (HRP Substrate)</td><td>Merck</td><td>Cat#WBKLS0500</td></tr><tr><td>QIAzol Lysis Reagent</td><td>Qiagen</td><td>Cat#79306</td></tr><tr><td colspan="3"><strong>Critical commercial assays</strong></td></tr><tr><td>Sircol Soluble Collagen assay kit</td><td>Biocolor</td><td>Cat#S1000</td></tr><tr><td>miRNeasy Kit</td><td>Qiagen</td><td>Cat#217084</td></tr><tr><td>MultiScribe Reverse Transcriptase Kit</td><td>Thermo Fisher Scientific</td><td>Cat#4311235</td></tr><tr><td colspan="3"><strong>Deposited data</strong></td></tr><tr><td colspan="3"><strong>Experimental models: Cell lines</strong></td></tr><tr><td>Human Pulmonary Artery Adventitial Fibroblasts (hPAAF)</td><td>Sciencell</td><td>Cat#3120</td></tr><tr><td>Human Pulmonary Artery Smooth Muscle Cells (hPASMC)</td><td>Lonza</td><td>Cat#CC-2581</td></tr><tr><td>Human Pulmonary Artery Endothelial Cells (hPAEC)</td><td>Lonza</td><td>Cat#CC-2530</td></tr><tr><td>hPAAF from Pulmonary Hypertension donors (PH-PAAF)</td><td>French Network on Pulmonary Hypertension</td><td>/</td></tr><tr><td>HEK293T</td><td>ATCC</td><td>CRL-3216</td></tr><tr><td colspan="3"><strong>Experimental models: Organisms/strains</strong></td></tr><tr><td>Mouse: Col1a2-Cre-ER</td><td>The Jackson Laboratory</td><td>Strain # 029235</td></tr><tr><td>Mouse: Yap1 fl/fl/Tazfl/fl</td><td>The Jackson Laboratory</td><td>Strain #:030532</td></tr><tr><td>Mouse: CC10-IL-6 Tg(+) × C57/BL6 Tg(−)</td><td>Gift from Dr Aaron B. Waxman</td><td></td></tr><tr><td>Rat: Male Sprague-Dawley rat</td><td>Charles River Laboratories</td><td></td></tr><tr><td colspan="3"><strong>Oligonucleotides</strong></td></tr><tr><td>siRNA Negative control</td><td>Horizon Discovery</td><td>Cat#D-001810-10</td></tr><tr><td>siRNA GLS1_pool</td><td>Horizon Discovery</td><td>Cat#L-004548-01</td></tr><tr><td>siRNA GLS1_1: CCUGAAGCAGUUCGAAAU</td><td>Horizon Discovery</td><td>Cat#J-004548-09</td></tr><tr><td>siRNA GLS1_2: CUGAAUAUGUGCAUCGAUA</td><td>Horizon Discovery</td><td>Cat#J-004548-10</td></tr><tr><td>siRNA SHMT1_pool</td><td>Horizon Discovery</td><td>Cat#L-004617-00</td></tr><tr><td>siRNA SHMT1_1: GAGCUGGCAUGAUCUUCUA</td><td>Horizon Discovery</td><td>Cat#J-004617-05</td></tr><tr><td>siRNA SHMT1_2: CCUAGGCUCUUGCUUAAAU</td><td>Horizon Discovery</td><td>Cat#J-004617-06</td></tr><tr><td>siRNA YAP1_pool</td><td>Horizon Discovery</td><td>Cat#L-012200-00</td></tr><tr><td>siRNA YAP1_1: GGUCAGAGAUACUUCUUA</td><td>Horizon Discovery</td><td>Cat#J-012200-07</td></tr><tr><td>siRNA YAP1_2: GAACAUAGAAGGAGAGGAG</td><td>Horizon Discovery</td><td>Cat#J-012200-08</td></tr><tr><td>siRNA TAZ_pool</td><td>Horizon Discovery</td><td>Cat#L-016083-00</td></tr></tbody></table>
<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td>siRNA TAZ_1: GACAUGAGAUCCAUCACUA</td><td>Horizon Discovery</td><td>Cat#J-016083-05</td></tr><tr><td>siRNA TAZ_2: GGACAAACACCCAUGAACA</td><td>Horizon Discovery</td><td>Cat#J-016083-06</td></tr><tr><td colspan="3"><strong>Recombinant DNA</strong></td></tr><tr><td>Human: pcDNA Flag Yap1</td><td>Levy et al., 2008</td><td>Addgene; Plasmid #18881</td></tr><tr><td>Vector: pCDH-CMV-MCS-EF1-copGFP</td><td>System Biosciences</td><td>Cat#CD511B-1</td></tr><tr><td colspan="3"><strong>Software and algorithms</strong></td></tr><tr><td>GraphPad Prism 6</td><td>GraphPad software</td><td>https://www.graphpad.com/scientific-software/prism/</td></tr><tr><td>ImageJ</td><td>NIH</td><td>https://imagej-nih-gov.gate2.inist.fr/ij/</td></tr><tr><td>TraceFinder 2.1</td><td>Thermo Fisher Scientific</td><td>/</td></tr><tr><td>Xcalibur 4.0</td><td>Thermo Fisher Scientific</td><td>/</td></tr><tr><td>NanoScope Analysis 1.50</td><td>Bruker</td><td>/</td></tr><tr><td colspan="3"><strong>Other (Diets)</strong></td></tr><tr><td>Synthetic diet-control</td><td>SAFE</td><td>/</td></tr><tr><td>Glutamine and Serine-free diet (Glycine (-)/Proline (-)/Glutamine (-)/Serine (-))</td><td>SAFE</td><td>/</td></tr><tr><td colspan="3"><strong>Deposited Data</strong></td></tr><tr><td>Data S1</td><td>This paper</td><td></td></tr></tbody></table>