ARTICLE

DOI: 10.1038/s41467-018-04602-0 OPEN Oxidized phospholipids regulate amino acid metabolism through MTHFD2 to facilitate nucleotide release in endothelial cells

Juliane Hitzel1,2, Eunjee Lee3,4, Yi Zhang 3,5,Sofia Iris Bibli2,6, Xiaogang Li7, Sven Zukunft 2,6, Beatrice Pflüger1,2, Jiong Hu2,6, Christoph Schürmann1,2, Andrea Estefania Vasconez1,2, James A. Oo1,2, Adelheid Kratzer8,9, Sandeep Kumar 10, Flávia Rezende1,2, Ivana Josipovic1,2, Dominique Thomas11, Hector Giral8,9, Yannick Schreiber12, Gerd Geisslinger11,12, Christian Fork1,2, Xia Yang13, Fragiska Sigala14, Casey E. Romanoski15, Jens Kroll7, Hanjoong Jo 10, Ulf Landmesser8,9,16, Aldons J. Lusis17, 1234567890():,; Dmitry Namgaladze18, Ingrid Fleming2,6, Matthias S. Leisegang1,2, Jun Zhu 3,4 & Ralf P. Brandes1,2

Oxidized phospholipids (oxPAPC) induce endothelial dysfunction and atherosclerosis. Here we show that oxPAPC induce a gene network regulating serine-glycine metabolism with the mitochondrial methylenetetrahydrofolate dehydrogenase/cyclohydrolase (MTHFD2) as a cau- sal regulator using integrative network modeling and Bayesian network analysis in human aortic endothelial cells. The cluster is activated in human plaque material and by atherogenic lipo- proteins isolated from plasma of patients with coronary artery disease (CAD). Single nucleotide polymorphisms (SNPs) within the MTHFD2-controlled cluster associate with CAD. The MTHFD2-controlled cluster redirects metabolism to glycine synthesis to replenish purine nucleotides. Since endothelial cells secrete purines in response to oxPAPC, the MTHFD2- controlled response maintains endothelial ATP. Accordingly, MTHFD2-dependent glycine synthesis is a prerequisite for angiogenesis. Thus, we propose that endothelial cells undergo MTHFD2-mediated reprogramming toward serine-glycine and mitochondrial one-carbon metabolism to compensate for the loss of ATP in response to oxPAPC during atherosclerosis.

1 Institute for Cardiovascular Physiology, Goethe University, Frankfurt am Main 60590, Germany. 2 German Center for Cardiovascular Research (DZHK) (Partner site Rhine-Main), Frankfurt am Main 60590, Germany. 3 Icahn Institute of Genomics and Multiscale Biology, Mount Sinai Icahn School of Medicine, New York 10029 NY, USA. 4 Sema4 Genomics (a Mount Sinai venture), Stamford 06902 CT, USA. 5 Department of Mathematics, Hebei University of Science and Technology, Shijiazhuang 050018 Hebei, China. 6 Institute for Vascular Signalling, Centre for Molecular Medicine, Goethe University, Frankfurt am Main 60590, Germany. 7 Department of Vascular Biology and Tumor Angiogenesis, European Center for Angioscience (ECAS), Medical Faculty Mannheim, Heidelberg University, Mannheim 68167, Germany. 8 Department of Cardiology, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin 12203, Germany. 9 German Center for Cardiovascular Research (DZHK) (Partner site Berlin), Berlin 13316, Germany. 10 Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta 30332 GA, USA. 11 Institute of Clinical Pharmacology, Pharmazentrum Frankfurt/ZAFES, Faculty of Medicine, Goethe University, Frankfurt am Main 60590, Germany. 12 Fraunhofer Institute of Molecular Biology and Applied Ecology—Project Group Translational Medicine and Pharmacology (IME-TMP), Frankfurt am Main 60596, Germany. 13 Department of Integrative Biology and Physiology, University of California, Los Angeles 90095 CA, USA. 14 1st Department of Propaedeutic Surgery, University of Athens Medical School, Hippocration Hospital, Athens 11364, Greece. 15 Department of Cellular and Molecular Medicine, University of Arizona, Tucson 85724 AZ, USA. 16 Berlin Institute of Health (BIH), Berlin 10178, Germany. 17 Departments of Medicine, Microbiology and Human Genetics, University of California, Los Angeles 90095 CA, USA. 18 Institute of Biochemistry I, Goethe University, Frankfurt am Main 60590, Germany. Correspondence and requests for materials should be addressed to J.Z. (email: [email protected]) or to R.P.B. (email: [email protected])

NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0

he endothelium maintains the vascular homeostasis and (Fig. 1c, d, Supplementary Tables 1, 2). Gain of connectivity Tlimits atherosclerosis development1. Activation of the cluster 6 was significantly enriched for genes involved in amino endothelium leads to a vicious cycle of reactive oxygen acid-related biological processes (Fisher’s exact test (FET) species (ROS) formation, inflammation and recruitment and p value = 1.63E-09) (Supplementary Table 3), hereafter termed activation of monocytes. ROS generated by inflammatory cells amino acid cluster. The applied differential connectivity clustering and the endothelium promote the oxidation of lipids contained in approach suggests that amino acid metabolism experiences a lipoproteins that further promotes endothelial activation2. The massive remodeling in response to oxidized phospholipids. process of lipid oxidation has been well studied for poly- unsaturated fatty acid side chains of phospholipids in membranes MTHFD2 is a key driver for the HAEC Bayesian network.To and lipoproteins. Oxidized 1-palmitoyl-2-arachidonoyl-sn-gly- explore the mechanisms underlying deregulated amino acid cero-3-phosphocholine (oxPAPC) is a mixture of oxidized metabolism in oxPAPC-treated endothelial cells, we constructed phospholipids commonly found in oxidized low density lipo- molecular Bayesian networks. This approach allows for the proteins (oxLDL). OxPAPC accumulates in atherosclerotic identification of corresponding causal regulators. For network lesions and at sites of chronic inflammation3. construction, we integrated the above used expression profiles OxPAPC disturbs endothelial cells by activating both pro- and and previously published expression quantitative trait loci10 of anti-inflammatory pathways4. Exposure to oxPAPC alters the the same cohort. This allowed us to construct two Bayesian endothelial transcriptome5 and the complex changes are a con- networks for HAEC: one for the control situation without sequence of various regulatory circuits acting in concert. If ana- oxPAPC (Fig. 2a, Supplementary Data 1) and one for oxPAPC lyzed at a single time point, the endothelial responses to oxPAPC exposure (Fig. 2b, Supplementary Data 2). Assessment of the are overwhelmingly complex. To address this, we went beyond control and oxPAPC Bayesian network against widely used traditional transcriptome analyses of the endothelial response to databases showed that the estimated accuracy of these Bayesian oxPAPC and applied a systems level network approach. networks is significantly higher than that of random networks Network models have been used for the identification of genes (Supplementary Fig. 2a). Also, the proposed networks showed and gene clusters causal to cardiovascular pathology6, yet a significantly better prediction of gene−gene interactions in comprehensive network model for endothelial cells is lacking. endothelial cells as compared to global gene networks from the Here, we constructed molecular causal network models, based on Human Protein Reference Database (Supplementary Fig. 2b, c). a Bayesian method7, for human aortic endothelial cells (HAEC). To identify causal regulators and the biological processes targeted Compared to other methods, Bayesian networks have several by oxPAPC, we identified key drivers7,11 in the two networks and advantages for modeling complex biological processes. They analyzed their associated subnetworks for enriched canonical model a causal predictive component for regulatory relationships pathways (Fig. 2c, d). The identified top ranked key drivers and as well as reveal key molecular drivers and they provide flexible their associated subnetworks (>100 nodes in subnetwork) are platforms to incorporate various -omics data as prior knowledge8. listed in the supplement (Supplementary Tables 4,5). MTHFD2 Here, we apply these techniques to study endothelial cell was identified as a key driver specific for the oxPAPC Bayesian metabolic reprogramming in response to oxPAPC. We propose network (Fig. 2d). The subnetwork regulated by MTHFD2, that oxPAPC targets amino acid metabolism governed by termed MTHFD2 network, was significantly enriched for genes MTHFD2 to replenish endothelial purine pools. Based on this, a involved in amino acid metabolism (FET p value = 7.32E-08) key role of MTHFD2 in angiogenesis as well as human athero- (Supplementary Table 6) and significantly overlapped with the sclerosis and CAD development could be inferred. identified amino acid cluster (FET p value = 2.33E-28). Thus, MTHFD2 may facilitate a shift in amino acid metabolism in Results HAEC in response to oxidized phospholipids. Differential connectivity clusters in response to oxPAPC.To determine gene clusters and key drivers that shape the response of MTHFD2-associated amino acid metabolic gene cluster. The endothelial cells to pro-atherogenic lipids, an integrative network endothelial MTHFD2 network comprised 114 genes and was approach was applied (Supplementary Fig. 1). In the first step, significantly enriched for cytosolic tRNA-aminoacylation (FET p expression profiles of HAEC obtained from 147 heart transplant value = 2.53E-06), membrane transport proteins of the solute donors were reanalyzed. In the initial experiments by Romanoski carrier family (FET p value = 1.82E-04), the majority of which are − et al., HAECs of this cohort were exposed to oxPAPC (40 µg ml 1) involved in the import of amino acids, and transcriptional reg- and vehicle control for 4 h5. Rather than focusing on canonical ulation in response to stress (FET p value = 2.17E-05) (Fig. 3a). analysis of differentially expressed genes or co-expression modules Importantly, the MTHFD2 network was also enriched for genes we went further and identified differentially connected gene pairs9 involved in glycine-serine metabolism (FET p value = 2.53E-06). under the two conditions. This differential co-expression analysis The genes within the overlap of the MTHFD2 network and this is more sensitive to identify disease- or treatment-induced gene set category control mitochondrial folate cycle, glycine and deregulation among interacting genes9. In total, 26,759 differen- serine metabolism and contribute to aspartate, asparagine, tially connected gene pairs were significantly differentially co- methionine, and cysteine interconversion (Fig. 3b). expressed, among them 50.4% showed gain of connectivity MTHFD2 is highly induced in many cancers and is essential for (GOC), meaning enhanced co-regulation between genes with mitochondrial one-carbon metabolism—the highest scoring meta- oxPAPC treatment. In all, 49.5% showed loss of connectivity bolic pathway across human cancers12. MTHFD2 is a mitochon- (LOS). Clustered differentially connected gene pairs yielded nine drial enzyme with 5,10-methylene-tetrahydrofolate (5,10-meTHF) significant GOS clusters (Fig. 1a) and 11 significant LOS clusters dehydrogenase and cyclohydrolase activity. The mitochondrial (Fig. 1b) with co-regulations elicited by oxPAPC. Gain of con- folate cycle generates glycine from serine, which is catalyzed by the nectivity cluster 6 showed the most coherent differential con- enzyme mitochondrial serine hydroxymethyltransferase 2 (SHMT2) nectivity changes compared to all other clusters. Thus, cluster 6 (Fig. 3b). The serine consumed for this reaction is synthesized by contains and reflects the strongest endothelial responses to the cytosolic phosphoglycerate dehydrogenase (PHGDH)andthe oxPAPC. To identify differentially regulated biological processes, phosphoserine aminotransferase 1 (PSAT1) from the glycolysis we compared each cluster with canonical pathways for enrichment intermediate 3-phosphoglycerate13. During the reaction of SHMT2

2 NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 ARTICLE

a c

–Log10 (p-value) Gain of connectivity Cluster 1 2 3 4 5 6 7 8 9 04812

REACTOME_S_PHASE REACTOME_G1_S_TRANSITION REACTOME_MITOTIC_G1_G1_S_PHASES REACTOME_CELL_CYCLE_CHECKPOINTS REACTOME_APC_C_CDC20_MEDIATED_DEGRADATION_OF_MITOTIC_PROTEINS REACTOME_CYCLIN_E_ASSOCIATED_EVENTS_DURING_G1_S_TRANSITION REACTOME_CELL_CYCLE_MITOTIC REACTOME_CELL_CYCLE REACTOME_DNA_REPLICATION REACTOME_AMINO_ACID_TRANSPORT_ACROSS_THE_PLASMA_MEMBRANE REACTOME_AMINO_ACID_AND_OLIGOPEPTIDE_SLC_TRANSPORTERS REACTOME_AMINO_ACID_SYNTHESIS_AND_INTERCONVERSION_TRANSAMINATION PID_ATF2_PATHWAY KEGG_LYSOSOME KEGG_AMINOACYL_TRNA_BIOSYNTHESIS REACTOME_TRNA_AMINOACYLATION REACTOME_CYTOSOLIC_TRNA_AMINOACYLATION Cluster 6 Cluster 5 Cluster 1 Cluster 7 Cluster 2 Cluster 3 Cluster 8 Cluster 9

b d –Log10 (p-value) Loss of connectivity

Cluster 1 2 3 4 5 6 7 8 9 10 11 0246

PID_P53DOWNSTREAMPATHWAY REACTOME_S_PHASE REACTOME_HIV_INFECTION REACTOME_TELOMERE_MAINTENANCE REACTOME_CHROMOSOME_MAINTENANCE REACTOME_EXTENSION_OF_TELOMERES REACTOME_CELL_CYCLE REACTOME_DARPP_32_EVENTS REACTOME_KERATAN_SULFATE_DEGRADATION REACTOME_CELL_SURFACE_INTERACTIONS_AT_THE_VASCULAR_WALL REACTOME_GLYCOSPHINGOLIPID_BIOSYNTHESIS_GANGLIO_SERIES PID_FRA_PATHWAY PID_S1P_S1P3_PATHWAY PID_INTEGRIN3_PATHWAY PID_S1P_S1P1_PATHWAY REACTOME_SIGNAL_TRANSDUCTION_BY_L1 KEGG_TGF_BETA_SIGNALING_PATHWAY Cluster 6 Cluster 2 Cluster 7 Cluster 1 Cluster 9 Cluster 11 Cluster 10 Fig. 1 Differential connectivity clusters of HAEC reveal the emergence of novel gene clusters in response to oxidized phospholipids. a, b Topological overlap matrix of nine clusters with significant gain of connectivity (a) and 11 clusters with significant loss of connectivity (b) identified in a comparison of genome- wide gene−gene co-expression relationships between oxPAPC treated and control HAEC. c, d Heatmap of significantly overrepresented canonical pathways of gain of connectivity clusters (c) without cluster 4 (Supplementary Table 1) and loss of connectivity clusters (d) without clusters 3–5 and 8 (Supplementary Table 2) according to Fisher’s exact test are shown the co-factor tetrahydrofolate (THF) is converted to 5,10-meTHF. and in an additive manner, increased the expression of the The enzyme MTHFD2 uses 5,10-meTHF to produce the highly transcription factor CEBPB (Fig. 3g), the aminoacyl-tRNA syn- reactive 1-C donor 10-formylTHF (10-fTHF) which can be recycled thetases for glycine (GARS) and cysteine (CARS) (Fig. 3h, i) and to THF by MTHFD1L. Both 10-fTHF and glycine are indispensable the solute carrier transporters SLC7A5 and SLC7A1 (Fig. 3j, k). for the de novo synthesis of purines14. Interestingly, the function of Expression of genes in the MTHFD2 network was similarly but to MTHFD2 in differentiated cells has been widely overlooked and its a lesser extent affected by PSAT1 knockdown. Importantly, role in endothelial biology or in lipid signaling remains, to our MTHFD1L, which contributes to mitochondrial one-carbon cycle, knowledge, unknown. Given the important role of metabolism for but does not belong to the MTHFD2 network, was unaffected by endothelial cell reprogramming15, we further analyzed this oxPAPC and unaltered by siRNA against PSAT1 or MTHFD2 interesting subnetwork. (Fig. 3l). These results validate MTHFD2 as a key regulator of the MTHFD2 network in oxPAPC-exposed HAEC. The data indicate that oxPAPC elicits a metabolic shift promoting the cellular MTHFD2 mediated oxPAPC-dependent changes. To better uptake of amino acids and the de novo synthesis of glycine. understand and validate the MTHFD2 network, we assessed the role of MTHFD2 in endothelial cells. MTHFD2 expression was decreased by siRNAs in HAEC and gene expression changes were MTHFD2 regulates 18 genes related to amino acid metabolism. determined with and without oxPAPC. To determine the hier- To address the importance of MTHFD2 for endothelial gene archical position of MTHFD2 within the subnetwork, we addi- expression, we performed RNAseq of HAEC with and without tionally silenced PSAT1, one of its direct downstream nodes siRNA against MTHFD2 (Fig. 4a). Gene set enrichment analysis (Fig. 3a). Expression of MTHFD2 was induced by oxPAPC as well of the MTHFD2 RNAseq signature confirmed a strong enrich- as by knockdown of PSAT1 (Fig. 3c). Importantly, also the ment for amino acid metabolism (FET p value = 7.54E-14) expression of the key enzymes of the serine-glycine synthesis (Supplementary Data 3). We then projected the MTHFD2 pathway (SHMT2, PSAT1, and PHGDH) was increased by RNAseq signature onto the MTHFD2 network. This demon- oxPAPC, and this effect was potentiated by knockdown of strated that MTHFD2′s close neighbors were upregulated by MTHFD2 (Fig. 3d–f). OxPAPC and MTHFD2 knockdown, both MTHFD2 siRNA (Fig. 4b). Furthermore, the MTHFD2 RNAseq

NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications 3 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0

a Control Bayesian network c

INPP4BRP11-35N6.1 GLG1 PPM1H ACP6 PLTP ALDH1A2 KCNK1PTHLHUGDH FST ALPK3 DENND1A LAP3HYAL1 MBOAT2CXADRSLC35F2IL7RZNF215 SRC TBX1 DOK5CPA3 CHN1IQGAP1TCF4LIMCH1UCHL1 GIMAP4PMAIP1ASB9LRRC6AP1G2 PLIN2SLC25A4TBC1D4 FKBP10HJURPPTSC10orf10 PLS1 CLDN11LTBP1SERTAD2 FOXO3 DCHS1 PPP1R16B POPDC3C12orf35PXMP2 MAB21L2 CTSZACTR2 PLAT CLIC3 SPTBN1 VAMP8 FAM46A BSG PHEX MGST2 TPM2MAN2A1H2AFXALDH1A1DST TAGLN2FLJ42627PPP3R1RPS6KB2PPAN KIF5B COMT CDCA8 FAM124BMACF1 LPIN1 NRN1 ATF3FOSL2 MMRN2ZNF185TPD52L1 HTR2B UBE2CPDE4B TLE4KLF10 YPEL1 CCDC68CLIP2 SMYD2 C7orf10ANKRD55 ATP10DENTPD5 PPP2R5ACAPGIRS2MYL9 NID1RNF144ASVILZNF195 NOTCH2TSPYL5BTN3A3LXNVDR ZFPM2 C10orf88OSTM1RIT1RRAS2KIAA0649 CENPTHNMTCHST12 DSE DHRS3 C9orf95NUDT4SSFA2LOXL1AHNAKBEX1 HEY2SOCS2PEG10 NBN BAG2 HSPG2 FSTL1 JUPTHSD7ASLC7A7MAPKAPK3 IRF6SFT2D2STC1FAM189A2NFIL3AP1S2ENOX1MCL1 MYO5A DLGAP4TWF1CCNE1 GABBR2 SKILRIN2HIVEP1DLC1 Module SLC39A8TMEM43PGAP1GYPCITPR2ECM1ETV1 IGFBP4WWTR1FCF1 PVRL2TNFSF10 SPRY4 HOMER1AMMECR1ALCAMCBFBGALNT12PLCL2CAV2 TNFRSF12AEPAS1LPAR6 RRBP1FILIP1L DBN1HSPA4UBXN7 PBX3ITGA10CNPY2 ARHGAP11A MED28ISOC1ATP6V0E2 SYNCSLC19A1 ODZ3 CADPS2 CD99FAT1 PALMDARHGAP24MGAT4A TNK2ASS1 NAMPT STC2 PABPN1 MARCH3 KD Top functional category p value GNAI1 BNIP3LACSL5 PSMB8RHOBTB3SNCA RHOF DOCK9PLCB1 GRB14 SEH1LERI2 TSPAN12IL27RA CDKN1A GMIP BTG1 NEIL1NRIP3 VCAN PCSK1SH3BP5 TSPAN31FERMT1 EVI2B MEF2C CEBPB TWIST1 DOCK4COLEC12SEMA5AGDF5 PDE2A CASP1 PELI2 B4GALT1C19orf28C12orf24 POLMC17orf68 BET1CASP7RRP1BKANK2 COL4A6COL4A5PIK3C2B PDLIM7 ATP2B1 CSGALNACT1GIMAP6TAGLN PSTPIP2TACC1WIPF1FLNB NOX4FAM131AC4orf18FKBP11 CCND2RGS5 DDX60PTGS1 SFRS5 LRIG1 DIAPH2 KIAA0922 SYNGR1 size DBF4 TNFSF12PHKA1 C20orf27MDM2 DISC1EDC3MAMLD1LPXN JUNB ANGPTL2CSTF3 IER3 UBE2N ARMCX1PNMA2 CD44 TMEM47HSD17B11 APOL3 RCBTB1 SLC48A1KIF13BSCO2 GRB2SCARB2 PLSCR4 DPYSL3 FOXO1 C17orf91 OSBPL10 TFPI2GNG11CYB5R2 OSGIN2 MN1 PPM1F PRRC1 PAPOLAMEIS2COL4A3BP TBC1D8 DDR1 ESPL1FBXO5 NESPLEC1 ATP11A DPYSL2SP110IFITM1 IFIH1CYP1A1 ITPKB C10orf116CXCR7 ATP6V1A TCEB3 IL15RAARMCX3 MAP1B SLC1A1 PPP2R3ASTAT1 HMGA2PDLIM3TRAPPC2 KIAA0494 GRK5 NRGNSULF1 ENAH CYBA TGFBI PTPRA VEGFA MYH10 RPS28 PRNP STK32B MLECPHLDA2 CTDSPL RNF41 RGL1ZDHHC14 PAPSS2IGFBP3 AHNAK2CROT PGRMC2PHF10 LTA4HCCNJ TGIF1CD40 BOP1 ME3 SNED1 CHST3 TNIK EPB41L3PTCH1 TDG PIGT APOL1 LYPD1NAV3 ZC3H12A SLC2A1PRSS23RRP8 ARMCX2 SLC4A7RECKIL15EVL TBC1D15 SAT1 CDC2L6 ALAD ALDH1A3ANO10 IPO4TOXMEST ERCC6SPATA7 SERPINB1 LYN GCDH CD55SLIT3 BST1 SLIT2 ASAP2 TGFB1NFKBIABACE2 CENPA KANK1ULK1 C15orf39 EPB49 TGFBR2JAK1NRP2 PHF15 POP1 IL8 TNFAIP3 MYO1D TMEM35ST3GAL1 PFTK1 PDE4DIP HERC6STOM INPP5D BAMBI CNNM3 FAM63A FOSL1 NOL6 IL1R1 PAPOLG AKAP1 TP53I11OPN3 CLCN4MARCH8TRIM34 ASPH VCAM1 SHROOM2TPST2 GDPD5 STX1ALYVE1 GLYR1KLF5 IFI44 TAF7LLGALS3 YIPF3 AMDHD2UAP1PHTF2CXCL1 PTX3 CRAT PEX12 MINPP1SRPXTSPAN5 CHAF1ASLC12A2 GMFG NOL12 IFRD1 ABLIM3 MYO1E CDCA3 589 GO_DNA_REPLICATION 6.58E-19 NDST1DYSFRORA COX7A1 C15orf63 MYST2 ATP9AGNB5GYS1IL6 TCN2 CXCL3CFDP1 KIAA1462PTPRD POSTN PPID ACYP2TNFRSF10CVAMP5TP53TG1 ABHD2PLVAPNFIC PTGS2 SULT1B1 SETBP1 ZKSCAN1ZMYND8HSPBP1 ASB1PTGIR CDK5RAP2KDRIFIT1 GPATCH2 DDR2 TRIM14 CD93 CFHPRKAB1ZNF277 VGLL4 EXD2ST3GAL5CD82 SERPINB9 KLF6 HNRNPUL2NBEALYST RANGAP1SSX2IP EFTUD1 CRIP1 IFI35 METTL8 VIPR1OGG1TEAD4ENPP1PHF11NT5E LMCD1 IL33 RCC1NUP98PGLS ZNF14APPBP2PDLIM5C8orf30A ITGA2ATRN SEPT6 IL1RL1DRAM1DAG1 SCN1B KLF2 NRG1 IRF7TNFRSF10D MID2 SEC22B EHD1 APOO GNA14 TRIB1PCSK5HEG1 ENSA EIF2S2 ISG20APOOLIFIT3ADM KCNJ2 ZNF688ATRXACDLY96HMBS ATF6B SLC25A32 HMOX1 SOX18 CDH5 NRCAM RP11-345P4.4 ZNF274 CXCL2 DOCK6 KLRG1 NUDT11ZNF467 CCPG1 CYR61 PLA2G4A ROBO4WFS1UNC13BCTNNB1 TRIM22 C1orf27 RABL4 TNFRSF14MME NPEPL1HSPD1 MARCH5ADAM10SGCE NR2F1 SLC11A2LDLRPDGFDPLCL1DFNA5 C14orf139 PAIP1ORAI3 LIMA1FGF2 FAM107A HP1BP3SLC35A1 TMEM30A AOX1 IGF2BP3 MYO6IL1B OSBPL3RELBHDAC9BMPR1A NR1D1 MYLK DARS2 RAB22A PDSS1 544 GO_RIBOSOME_BIOGENESIS 5.83E-10 TMEM2PIK3CA AMACRDNMT1 THOP1WRAP53 RIPK2 DIDO1 NUP155 NRP1 TCFL5 TUBG1 TXNIP NR3C1 CDC5L COL18A1 MRPL12EPHA4 TRIB2RBL2RBM19FTSJ3 CUTC ABCB1 VWA5A WBP2 IDE PTPLAD1 NAV2 PLXNA2 GPC1 PLK2 CAMK2N1PHACTR2 MSX1 KLHL3 DAB2FGFR1OP TECPR2 STARD13ROBO1 AHI1MX1 NFE2L3EEF1A2 NTHL1TESNEDD4LPDE8ACOPZ2 SLC7A6KCNN3BRCC3TCTN1INPP5F CLDN5SERPINB8 VPS13D RRP1 MKNK2KIF22 SLC17A5ECHDC3GGT5SERINC1XPNPEP1 IGF2R CTSS GLS CDH11 SORT1LMO2 PRMT2ANKRD46 UBE2J1PTPN18KIF3ATNFRSF1BARG2SLC26A2SFN IL1AGALNT7RND1 ELOVL6 KIAA0427 HPSE ZNF22MERTKFHL2DUSP1 ITGAV YIPF5 EXT1 JAG2PFAS GDF15 SPA17 MNT BCR PIP5K1CARRB1 C14orf143BCL2L13 METAP2NOC4L CUX1 CRTAPENTPD1 ERLIN1 MALT1SGK1TLE1SMARCD3OAS2SMURF2ISG15RCAN1 CENPM SIL1 LMNA CXCL6 NELF TAP1 KIFC1 CYTL1 ZNF175CHD7EMP2SATB2 C10orf119 CBR1 DDX3X RUNX1C3orf64CD46GALNT1 FSTL3 IFI6 FKBP14 PRMT3 GO_INORGANIC_ION_TRANSMEMBRANE_ TCF15 C12orf5PDP1 ICAM1 WASF3 DNAJC4 RBM28TIE1 ETS2 PPP1R13LPLAU SPATS2L GEMIN4DEF8LRP12TBRG4APEHEBNA1BP2ABLIM1 FAM136AHSPE1POLR3GTTC4LAS1LARHGEF17 HOMER3 RBCK1 GPR176 NDRG1ABCC5 PTPN22NPTX1PIK3CDEIF3C UTRN SAMD4A NOP2 ESM1 EXOSC2 LAMA5 BHLHE40ACO1GALNT10IRF9 DCBLD2P4HA1 SLC39A6KPNB1PAK1IP1PHBCLDN7 SNRPD1 GLAATP1B1 DTYMK C2CD2NPAS2 OAS1BMP4 ZCCHC2MIR21 CALU GLRXUTP20SLC27A3KANK3 ARHGEF15SLC5A6FAH KDM4B BBS1 PDSS1 KDM3A SIN3B PAWRXAF1 MFSD1NLGN1 C18orf22PILRBFNBP1LPDE4D PXMP3 TMEM48CCDC88A GRIK5 LAMA4CALHM2 TIMM8A TSR1 OAZ3 PGRMC1 DOCK9 348 5.85E-06 NOS3 ACAT2 HAUS7 PIK3CGNPR2 IL13RA2 GCHFRRRAS ATP2C1 ABHD5C14orf109 LRP5 C14orf106EXOSC5LHFPL2NXT2 CCNF ARL4A IL3RA SLC16A7 HRH1NEDD9 ARHGEF6ADCY9 SNNAGLMPDZMED12 SYNMTPST1 LIAS TFEC FAM64A C16orf88TFRC HK2 C1RL USP18MACROD1KIF23TNFRSF21FN1 SATB1ARSE FEZ1 CTSF ODC1 SEMA3AMOSC2 FNDC4 STAG2 PVR BCL2A1TRIM24TRIM16TMEM140 HSPA4LTSC22D1CCDC91YES1 FASTKD3WARSSDC4 GEMIN6 MAP1ACTSO RRP15FBXW7PTPLA CIDEB CHKBNAPGRHOB SPG11CSNK2A2TTC23BBC3 GUF1 TIMP2 TIPIN ERCC6L SLC41A3 MXI1 CPS1 TRANSPORT PLOD2RPL39LPECIING3TRAPPC6A PPP2R1B NARG1NQO2HSPA14 C9orf16 LOC729580LRP8STEAP3BIRC5 IMP4 RTN2TM7SF2 SPSB3 MAGOHBPHYH C7orf49 RAB32CHEK1 ABCG2 LDB2CNN2 TMX1CALCOCO1SNRNP25SEPT9 ASRGL1FZD5 PPP1R3CPLCD1 GNPTAB UCK2RNASEH2A NINL TTC27 UNC5B EPHB4 NIPSNAP1 SIP1 DOCK1 ASAP3GPR126 METTL13RAB38 PIP4K2C LBA1 ZWILCHNNMTABCC4DNAJC9 HOXA1 ACOT1 MTUS1 DKC1 SIGIRRACVRL1DDX21 MOCOSSPHK1 FOXM1FAM149B1BCL6 LMBR1LZMAT3 KLHL24 OGFRL1CFI TBC1D2 QSOX1LOXL2 PCIF1SERPINE1 MINA PNO1 TPRKB NDUFAF4 INF2 CBLB ZNF593 LIMS2 FNDC3B KIF20B ANXA4 DEAF1 AK2 PSME3 RCL1RASA2 C17orf90 PDE3A EFHD2NR2F2CCDC69ADRB2ZNF532RFK INHBA TM9SF2 ARL2C14orf159RARRES3SOD2 DMDNUP88 SCN8A PNPLA4 WDR5B C6orf145 SCARA3 ADAM9KIF14 ZCCHC24C10orf26 FCGRT KTN1 SEC63 SLC22A18 ABHD11 SYNGR3CD58 CCRL1 BGLAPARHGAP19RP11-138L21.1CIT FJX1 BCCIPSNAPC1SGPL1C16orf53 FAF2 NR2C1TMC6 ALDH3A2 PDE10AKIF4ACCL2C1orf107 C1orf54TPM1RPP40SLC35D1NOLC1 PRPF31 DLEU1 C5orf54 C18orf10 KIF1B TCEA2 PIK3R3TMEM45ARPS6KA2MRPL42GBP2IGFBP7 AGFG1PLXND1SFRS8 SLC17A9MPZL2FAM115AOSMRHCFC1R1CTSC LOC65998 NEK2 317 HALLMARK_E2F_TARGETS 5.28E-24 B3GNT2 PA2G4 SYNJ2 ZNF395 ADD3 HSPB8 GAPVD1 PRND GABPA MRTO4 MPHOSPH8GATA3 EXOC2 CSF2RB ICA1HNRNPM APITD1IP6K2 SORBS2GSN C16orf35 FGGY PBX1 MPPE1 POP5MDN1 PLCG2 GALCMCCTMEM22 RPRD1A SOLHMEIS1CTSH TAOK2 BMX LOC100291393SEPHS1MAGT1 MYLIP CHPF2 SLC25A37PAICS C19orf6 LASS6POLR1EPPIFGBA WSB2 SEMA3F TSEN2ATR NCK1 COPANDRG3CNOT8 C11orf48 SYNGR2SMAD3 GLT8D2SRPX2 MMRN1 LY6G5C WDR77 COQ3DLATPPP1R10PAAF1 CCNG2ALDH3A1 RNF19A PLEKHA5 HNRNPDRNFT2 SLC16A3GALNT2 RSRC1DMWD LETMD1 SLC29A1LIPA C2orf18 FADS3 DKK1 GGA2 DLG5 QPCTMDK SLFN12 IL10RB NEAT1PINK1NRAS PCMTD2STK39 MSTO1GLDC GPR4 HOXA4 IQCK DUS4L CCNA2 MAPK8COG5MIER2ALDH2ENG PDS5B GATAD2A NOP56FAR2 MEGF9 PLA2G4CTLX1 PRC1 TTC3 SLC25A15 RAB40BPOLR2D ARNTL2 SURF2 NPC2NUPR1 MORC4CLEC1ADNAJB1 TRPV2 EIF4G1 CEBPD NENF PRKAR1A TRAK1 DOHH RCBTB2 GCA RBMS2 TNFAIP2 TSPYL2 SACS GADD45A SRM RGS4CCDC86ARMC9 GPR172AC11orf67KIAA0141 TRAM1 281 KEGG_WNT_SIGNALING_PATHWAY 4.73E-05 F11RPRKCH MAGEH1IFI27 LRRC32C7orf44 OSBPL1A TSPAN9G3BP2 PLK1 HOXB6KLC1CEBPGEIF5BNP RNF38MagmasESF1IL4RTM4SF1C1GALT1C1 SNX1UTP14C UBA7 SLC2A10MR1 CALD1C1S GPR125SECISBP2L UBE2O ARFGEF1 VARS RRP12 SNX27 ATF7IPHNRPDL RAC2 UCHL5NPM3DCAF16 SMARCC1AP3D1EEF1D STX16BCL2L1 TUBB2A ME2 ETNK1HOXA5 MYRIP CLDN15P4HTM CHD4 GGH RNF146MAT2A TM6SF1 SMAGP MOSPD2 COX16 FANCGVPS13C RNF24 SLC16A1 PLXNA1CENPBNOP16 ABCB6PDCD11 ELMO1 RAB11A ILF3 CBR3SPENZNF609 DDX39 DCTN4KLHL20 OXA1L NCLN BNC2UBE2HROBO3 ME1 JARID2 PKP4 SFRS2IPNEK1 DNAJB6 CLASP2 PWP2 GFOD2RNF103 ZFYVE21DCAF10C2orf42 EMG1 DDAH2 HIRA MYO10CCNB1 MAP4K5UBR5 MICAL2 FKBP1A PIGL SLC5A3HS3ST1ITGA6 PRDM2MTR H2AFV RBMS1 GPATCH8 FKBP4 CYB5B PRRX1 C19orf42MCFD2 ADA RECQL IFFO1 MEGF6 SP100 GMPPB HYI C1orf163 HOXB7 TMEM41BATP2A2 EMCN MSRB2 STAB1 C9orf46MICAL1MRC2 TNFSF18 FZD6ARIH2 PDXK TIMM13 UBAP2LHOXB5SKAP2 CDC42EP3PDLIM4 ARHGEF3ITGB4 RBM4B SLC25A13ABCC10 CWF19L1LTBP3WASLERBB2 ATICTBL1XINTS1GIPC2EGFR URB2 HMGN4STAP2C3orf14PCTK2 TFPI NUP107 EFEMP2EZH1 AMIGO2LTBP2 COL6A1 CASD1 CREBL2 RRS1ZNF226 EMG1 243 GO_TRNA_PROCESSING 1.13E-04 TRIB3 SPRY2 CLEC2B ADAM23 HNRNPH3 GOLT1B EPS8 SDPR UROS HMGCLSGSM2MAN2C1 NARS2 LIPGOBSL1ZEB1 PPP3CA DEGS1 PGM3 CKAP4 DAPK1 UBE2L6 SQSTM1 FAM57A NPDC1 MAP2K6FAM190BRAB8B LOC201229APCMIPEP GAL3ST4 JHDM1D HSPA1AMEF2A CPD FLJ10404 MYST4SPTAN1 CD164 TNS1STON1MAN1A1 NF2 CHCHD7 IL17RAFOLR1RBM3 FLI1 LEPR SPG7CTDSP2 SART3 MGAT4B KIAA0100 KPNA1 CCNA1TSKU CUL7 EDN1AMT KIAA0562CD59RCOR3GATA6 RBMS3 MAOA HHEXTPCN1 USP34 CLU SLC7A5PLLP KIF15 PIGV LRDD ABHD14A UBXN4 EGFL7 TAF15C20orf30 FNTBNUP50GSR CTPSNCBP1GPER GPX3 SLC1A5 FGFR1 U2AF2LOC728392GABBR1 NFAT5 UBE2S SENP2 MSH2C1orf115 DPH2PRKCDBPPOU4F1 ADAM15 ADORA2AZSCAN18TMOD1 RAI2 C19orf54 GPR56 MZF1 FARS2 CDC42BPAEEA1 ACP1 ID2 DEDD SNRNP40ZBTB20DNAJC3CCT2SENP3ZNF358 MYOFTJP1 KIAA1199 ITFG1 PSMB9SETD8 ASMTL ISYNA1 ZC3H11A MBD3 LGR4 ANGPT2SDF2L1 GALK2 NFKB2DICER1 DHRS4 SIPA1L3 AEBP1 LRRC17 SMARCA4 TUBGCP4 ARHGAP1 SLC16A5 LIMD1 RGS12 C14orf132 LARGE AGRNTSC22D3 HERC1 VAMP2CES2 LOC100292189 MTMR11TNFRSF10B BMPR2 GSTZ1 TGM2 SLC9A3R2 KIAA1305 HMGCRLCAT CSNK2A1 PSEN1SMARCA1STIP1TACC2TSPAN3 ITGAV 230 HALLMARK_INFLAMMATORY_RESPONSE 1.70E-06 FAM49A TM9SF4RAB4A WWC3 CHST15 ETV5 SLC7A8 TRIM38 ARPC4 MAXADAMTS1NEK7 ANKRD28TEK BEX4 DUSP6ADSS ZNF93 ZMYM6 PSMB10 EXOC5 ITM2B OGT PRR3 KAL1 CSNK1A1SOS2CRYL1 CHMP1B MBTPS1 MARCH6STK10 CYFIP2 TPK1 IL13RA1BST2ALG6PDIA6 GPR116CTSL1 SH3BGRL CANX STX6 SDHC DCP2 IDH3A PHLDA3 DPP4PALM2-AKAP2 XPO7 RPL37A ABHD4 EHD2 NBR1 FUT4 FDXR UBE3BNAGALIMD2ETV4SPRED2 GJA4 DNAJB9TIPARPPIK3IP1XBP1 RANBP1 MEX3D EIF2B3 ANKHD1-EIF4EBP3HS1BP3 LMBRD1 ACTA2FAS IFNGR1 FKTNPRKAR2B NISCHYWHAH SEL1LTRIP11 CEP350DHRS1EPS15L1PPIC RNF13 SRPK2 ACVR1 THOC6 ZNF862 GINS3 STYK1 PTK7DIP2C LRRC8BNMD3TMCO3 GPR137B HDAC5 TERF2ZNF337 CUL4BRNASEH1 TTLL12 UBE2I PEX3 CRELD1 EFNB2 HERPUD1 MTDH ZMYM1SMN1EFEMP1CYBRD1 MTHFD1 PTGER4TMEM187 PON2SRGAP2HEXA XRCC4 TIMP1 CHST2 ZHX2 METTL7A VWF PTK2 PTRF BANP ZDHHC13SNCAIPHPCAL1INSRD4S234EHEPH EPHX1C1orf21 CKS1B ID3SPAG9KIAA1033EXOSC8 THBD BARD1AKAP2 MAGED4 STARD8SLC43A3 DDIT3 CSE1L CLCN3NNT EWSR1SLC38A10 POLA2PRRG1 BCAM PARD6A LARP1PXN PLCB2 PPM1F 150 GO_MEMBRANE_REGION 1.05E-05 FBXO38ARFRP1 CLIC4 C1orf156 YKT6 C1orf112 MDC1KIAA0513SRI FAM117ARNASE1 KIAA0746 TP53 ID1 PREB AMD1 RALB DZIP3 RAD54LSUV39H1TK1 GULP1 CDC42EP2 DCN C17orf48 ERMP1CREG1 CEPT1MMD PDLIM1 NUSAP1 CALM1DIMT1LNUDT1 EFNA1 ACSL3DDIT4 HGSNAT TRAM1TFAP2A CHST7 FLOT2 ECE1MLLT3 SMARCD2HIPK2 C12orf4 JAG1 SPC25 GAS6COL5A2 ABCA1IL32 SSH1C8orf4 UCP2 UBTD1 CSNK1E FLRT2 EHBP1L1GCKR AKR1B1 SCRN1 PGGT1B FBXW11 SLC38A2 TCOF1 NUP205 BAT2L CHAC1STYXL1PGCPC1QTNF1 SERPINH1ADD2 FANCI GPR107 TP53I3APOBEC3GSLC7A1 PBKMGP TNFSF4EPHB2 UBE2G2 C22orf29TGFBRAP1NRXN3LRCH4 MAD1L1SLC27A5 CDKN2C AURKBLSM5 C11orf61 LIMS1KIAA0586 TPD52 NOVA1 MLLSLC24A1TRIP13 SF3A2 GFPT1 HIPK1 PBXIP1 C21orf45 CDKN1C CAMK1ITPR3APLP2 IDUA MKI67 CCDC99 PTBP1 SLC3A2PRUNE2ZBTB1 INPP1 CCDC15DYNC1I1 PDGFRLSECTM1 CASP2 GOLGB1 PVRL3FICDBTK TGOLN2 EXT2 TPP1TM2D1 LAMP2 MBOAT7CNTNAP1ABAT PSMG1 SIX1 CTBS TOR1AIP1THBS1 SPAG5 NCAPD2 CLIC2 TSPAN7DHCR24 MARCH7SLC7A11OCRLRASA1 TPP1 140 GO_VACUOLAR_LUMEN 1.76E-06 SEPT10 ZNF124 SREBF2 TAPBP PPAP2A CCL23 FBN1 RPA3 YPEL5MARCKS SQLESC4MOLPPARD C11orf24 LAMB2PPM1D ASB13 RPP25SDF4LMAN2L NUAK1 GPRC5B DHCR7INSIG1 PRKD2ANKRD11 MTSS1 HOXA2 KPNA6MAPK1 CLPTM1PNPLA6PPIH ABCA8CCL14 CDCP1STK38L PDCD4 HMGCS1 BRD4 C6orf62 RIOK3 TMBIM6DKFZp434H1419KPNA4MAP3K7IP2 KLF4LRRFIP2 HLA-E PYCARD RRM2 KCTD9 TTLL1MREGFUT8ECT2 FLJ34077 RUNX1T1ENPP4 CORO2B HIP1 PCOLCE ISOC2CYP51A1 SRRM2DNAJC10CREB1PPFIA1 MAN1B1FAM35AFTH1 NEK3 LY75RALGDS GALNT6 SEC14L1CCDC47 ABCG1TCF7L2TRA2A LAMB1 SNAP23HIST1H2BKSEC23ASELT CYB5R1TMEM8AKLHL7KIAA1609 UBE4BLIPT1HIP1RSH3TC1 TSPAN6 TFAM CLIP3 STT3A RNF216SCAMP1 PLXNB2RBBP4SMPDL3A LMAN1 MTFR1 EDEM2 NEK9 TGFBR3 NCAPH SSRP1 TMEM158 SEMA3G CYP1B1 ERP44 PRKCSH LTBR TMED2 SPTLC2LRRFIP1NMT2PAM AIPZFP36L2SIRPACITED2 PROS1 MGLL STRA13 SDC1 ANGEL1AP1S1 PRPS2 PDK2 SS18 OS9 FAM171A1NOD1GLUL MAGOH POP7 JAM2 RAB20GALNS TBL1XR1 SLC35E2 MYCBPMMP16 EGR1 DAZAP2 KNTC1 AIM1 FLNA CHST1 SLC22A4 UBFD1CYLDHHLA3PICALM NUCB1LRP10NCSTN RIN3C1orf144 MANF MORC2SERINC3PARP12 ZFP36 NET1ATF2MAP4K4 TWSG1AGPS PHTF1 C1orf135SHCBP1 DUT SPATA2L SPTLC1CEP250 TAF9B 131 GO_TRANSCRIPTION_FACTOR_COMPLEX 5.06E-05 TCF7L1 KIF20APAMR1 BLM NEFH MTHFD2TMEM51 SSR1 ELL2 PCDHGA1 MAD2L1 FUCA1PDGFAPCK2 ASNSNDRG4 CC2D1A CLINT1TOP1PRKAG2DAPK3 TMEM159 CHST11 EDIL3 SRPRB RFC3 MYO1B BAT2D1DDA1 MYBL2NOVA2PHF17GMFBHIST1H2ACCDV3 ALDH4A1 CENPF CDC20 ROGDI PFKFB3 SYT11 ACP2ADARB1 CENPE NCOA3RAB4BARSA SLC38A1LOC100289848 TIA1 PSMC3MIA3 HSPA13SPCS3TBC1D9 DNASE2CTSD GRN PTPRM TOP2AIDS SKA1 PCDH17 ARMCX5 PGF NBEAL2 MELK RNF14INSIG2CENPICYB561 EFNA5KLF13SRPK1MAP3K7ATG5 MEGF8WWOX CIRBP NDC80 ABCC1 F2R TMPO PHGDH ATP13A2 FNDC3A PRDM10FLRT3LIN7C SGSH NUCB2 CDKN3 TSPAN13 RAD1 SLC2A14 RPP38CTSAGLB1 ORAI2 SLC39A14 NCAPG GDF11MAFF SHMT1 CAPRIN1THOC2MFN1 MAN2B1PSAPNEU1RPL28 BUB1MCM10WDR45 NRIP1 C11orf71 MAPK8IP3PIGZ PTPN14CRKFLNC MAN2B2TTC38 CDC25B PDIA4 AGXT2L1 TSPAN4 RPL31 MBNL1 ZNF200 SCD NFYA UGCG TAF5 ENC1CDS2PTPN12GPHN CTSB HSPA5 SELL RABEP2NTM IDI1 FDFT1 CD34 GNA13CUEDC1 CRTAC1GNS KDELC1SYNPO NEK2WDFY3 CEP76 PALM ANXA3PSMC3IP NTSR1 NFYB USP13 PARD3 ALG13 PLEKHF1SOX13 RNF6 ALDOC ATP5SFKBP1B CUBN SMC1A CBS CDCA3ITGB1BP1 KLF12 SMAD4FYN PDIA5 CEP55 TMOD3SYPL1 PNN LAMP1CLN5 CRNKL1CRELD2 EIF4B FBXO42 CYP26B1FADS2 TINAGL1 ATXN10H6PD SEPT11 P4HA2 DLGAP5 MAP3K11 SLC2A3 GBAPPCDH1 RAD21 LOC729046POLA1 LUC7L3 UPF3ALOC653390PTPRERAB1AKDM6A HEXB HSP90B1SLC30A5PRKD3CCNB2 RACGAP1 DEPDC1ANP32ARHOBTB1 KIAA0182 SMAD5 C1RTENC1EML1 PRPF39 CLDND1 ZNF692RSL1D1FRMD4B APBA2OIP5 KIF2C DOCK10PCYOX1L TBC1D5 AK3L1 SNX5DET1 NKTR APP MIS12 ANKRD12 RDX SELP F5 RNF219 DCUN1D4POLRMT MAGED2FABP4 DENND3 DKK3 COQ2 CARD10NSDHL LRRC16APLEKHA1 KRIT1NID2CXCR4RPL10 RBBP6 NUP160HYOU1 TNIP1CKAP2 BUB1B ZYXSOX17 FAM18B ZNF227 SMAD7 SCAMP4CLCN7PLEKHO2MED16AKAP13 AHDC1 FZD2 ABCA3 SCHIP1EIF2B2 ZWINTLAPTM4BTTK PKIA RP1-21O18.1 COMMD10 DACH1LYL1 FAM176B SSR3 PKNOX1 FABP5 SMAD1 ARL6IP1 STILCDC25C CALCRL RARAFAM3A PSAT1 PBX2 MDM1 SFXN3VASH1PCDH12 AKAP8L ATP6AP2 KIAA0564VPS13B TROAP AMPH TPX2 LMNB2C1orf103 NADSYN1MCAM GM2APPP3CC EHD3 KIF11 GPRC5A NR1H3 CASP4 C1orf63 LGMNPYCR1 IGFBP2LBR NCOR2 MPP1 ASPM STRN3PTP4A1 CARHSP1FADS1 CCNL1 KIT MID1 LEPRE1 PLOD1 MET THAP10 PXMP4ARF6 PDGFB RASSF2NOTCH4MYO5C UXS1 MMP10 GINS1SNX19CCHCR1 MFNG FKBP5 FUSIP1 ARVCF SCPEP1 C9orf125SMPD1 SOX4 FBXL18 IPO8TRRAP CCNL2 TMEM106CHSPH1 RAD51AP1 PKMYT1 UBE2L3CCRL2NT5DC2 C13orf34RWDD2ANXN JAM3 ANXA11ZNF83FUBP1 CASKSYNE2ITGA5 TMEM132A E2F8 SLC9A1 PPP2R5DPIGF PTPN11 CASP8AP2 SNAPC4SC65 ANGPTL4 CERK NCAPD3 ---NFIBBCL3ATP2B4 EXOSC4 PCF11APH1B SLC25A20HAUS4 TMEM194A PLK4 SSBP2 RGS2 H2AFYWSB1 BCAT1 DHX9 HLX NSBP1MYL5 ZNF271FBN2 GMPRPCTP GTSE1 CGGBP1SFRS1 GLE1DDX18 LSS NCAPG2 VRK1 RAGE CHORDC1 BMP1TRPM4 PSRC1 KIAA0101RRM1 KIAA0323C13orf15 PXDN RBM39ANKLE2TRAF3IP2LOX EIF1AXPBLDFASTKD1 COL5A1LARP6 BASP1 SMC2BDNFSIDT2EBP GNAQRFC2 TRMT2BPKIGSMCHD1 PAQR4 MCM3 WHSC1POFUT2 C1GALT1 PKN1 ANP32E SMC3 SEMA3C PRKAR1BMGEA5 ZFR TOPBP1PPM1BPMS1 PLD3 MAP1SAURKAKDELR2 RAD51 ACYP1LOC81691HELLSBRCA1TACC3 ROCK2 PMP22 MNS1 NFATC1SAFB NMU SLC2A6THBS3 SMOX ANKRD10 ATP5OEZRCRKRS MARK4 B3GALNT1 DR1 ARID5B TYMSTSN DKK2LPHN2 CDC27ITGB3BPRASSF7 DEKAPLP1 CBX5 COL13A1 PTGIS CDC45L FERMT2 CLK4 HYAL2C1orf9KIAA0907USP10HIRIP3NLRX1SPIN1 EFNA4 PTPRKTULP4 POT1 TAF9B ZFC3H1SDC3RCN3 SMC4CDR2LTMEM204TBC1D16USP1 KIF18BFHOD1EFHC1CACYBP BRCA2FRYRFC5 SLC23A2OPA1HMMRLOC100272216TIMELESSPDS5AAPI5 PTPROWTAPSELENBP1AKAP12 ADAM19C1orf50 GPR161ZDHHC24RANBP17BGN PLK3 PMEPA1 TMEM50BPTDSS2RUFY2 CDCA4HN1L ZC3H7BPRKAA1LAMB3ENO2PRKCA RGNEFEIF2C3 HRASLSPSIP1 TRIO LEPREL1NUP62BTN3A2 MCM2PRKDCTFDP1 RBM38PELI1 MCM7SF3B1TMCC1 STMN1 CYB5R4 JAK2 EVI5 PDGFC SAP30CDC25ANASP DHRS7HSPA2 N4BP2L2GABREFBXO17 MCM6ANPEP SFRP1WDR76CDK2 POLD3HES1 YAP1PARP2LPPSERPINE2 RPS6KA5 FSD1 STK17A WIPI1SOBP EZH2 CDC2 MMP1 WHAMML1 MCM4 LOC729222 PAFAH1B1FAM108B1ARGLU1ATP6AP1 MED6NACA SAMHD1HMGB2CCNE2 CTTNPOLE2 AACSPTPRFLOC100132247 LITAF SFPQ GINS2RBP1 CLMN JMJD6 PSME4 TBC1D8B TANK CKS2 MBNL2 RANBP9 GINS4 RBBP8TUBD1 LHFP ZNF193 PSMD11 CTNNBIP1CLEC11ABMP2K H1F0 H1FX PTPRG CHAF1B SMAD6 TRAF4 PKD2 VAMP1 MAPK14 MCM5 GIT2WEE1RNF121IMPA2LTBP4 MDFIGMNN CDH2RAD51CDUSP3 DNAJC12 GPSM2 MED21 GLT25D1TNS3 PCNAGCH1 FEN1RFC4 RND3 ITGBL1 ELF1SMC5 SLC39A7COL4A2FRMD4AMMP14PCDH9 TLE2 MMP2 HAT1 BTG3APBB2CDC6 COL3A1 SKP2PPPDE2B4GALT6SMTN ATP6V1C1 MGMT MAP4 GFPT2TMEM97RGS3SPSB1 DTL KIAA0040KCTD13WDR1 KCTD20SFRS18 NAGLU ARAP3 ORC6LATAD2 HEY1 RBM14 ZNF419DUSP4LRP3 CLK1 FH SALL2NDNSNX2PRIM1 PSMD9SNW1TFF3SNHG3 SLC25A12TMSB15BTMSB15A TRAM2HTRA1 ENTPD4DSCC1APOBEC3BPOLECDT1RAD54BTNFRSF25METTL3SFRS14 EML4 FBLN2 RBM8AANGEL2DDX58ASAP1 MGC87042COL4A1KLF9 GPR124PCDH7 PLCXD1MSH6ORC1LNUP85DCLRE1BRMI1SYNE1KDM5BMTERFD1 GLCE CLEC3BCADM1CPE PPFIBP1SMEK1H3F3B C11orf75SAC3D1 PATZ1BMP2 HSD17B14 TMEM185BATP13A3 POLD1 GMDS ATF5RANBP2REST PRKD1C9orf3PCYOX1CUGBP2 SPOCK1FAM111AASF1B UNGSHMT2ING1 NQO1MPDU1ANKFY1SLK NUDT21 NME5 TMEM39A TRIM2LRRC49CSRP2ARL4CPAXIP1HBEGFSH3BP4SLCO3A1 NUPL1RFWD3TMEFF1CETN3MYBL1 FANCL RBM9LDB1 MAST4 CREMCCND1 E2F1 SFRS3 TMEM135 FAM178A ERCC2MXD3 ARHGEF7GADD45BDLG1 HNRNPA1 ERLIN2EIF2AK3 MAP3K5RTEL1ATP6V0A1KHDRBS3POLQ INO80BEML2PALLD PRPF4B RPGR AIDA FBXO9 CEP70HADHEXO1 TUFT1 LYRM1SPARC ICAM3GABPB1IKZF5 SFRS7PIK3R1PHLPP2 NCRNA00094 COBLL1 CTGF HMGB3RAB5CJUN GLI3SPTBN5 LONP2 ITGA4 PPAP2BPLEKHO1RNF10 PLSCR1 POLDIP3hCG_2024410IVNS1ABPHADHAKCTD12 SERPINB2 GBP1 YRDCSCN5A TRA2BPROSCSFRS2SRD5A1TUSC3 RAPGEF5 SCYL2 SASH1 NINJ1 C16orf45 ASF1A RALABSCL2C5orf13 LAMA3 BZW1NFATC2IPFNBP4YWHAZ LMF1CDKN2AFAM50BTSC22D2KAT2B FAM102AEPORNETO2ITM2A NAB1ROD1 DBNDD2IPO5 TAF1D ARHGAP22PRPF6NBL1 FAM38BARFIP1 C21orf66CPSF6SEC23IP CAPRIN2 DMXL2 ARPP19RNGTTHIST1H1C SMARCA2 CDC42EP4CTSKSORBS3SORD GPR162SRPR ANAPC5CAPN7GTF2IRAB5AEPRS VAMP3 SCARB1LANCL1MTMR1PRKACBADD1 DGKA MAZARHGDIA

b oxPAPC Bayesian network d

MDFI KCTD12ZNF467 MID1IP1 CBSRWDD2ANENFIFIT3 GSTZ1ARHGEF3 SPRED2EHD1BASP1 KLF13FOXO1 SLC47A1CDC42EP2 CARD10CLEC11A OAS2 MX1ARMC9UNKL MRS2 DNAJC12 KLF2 STYK1SYNPO SLC1A5PHGDHCDKN1ASHMT2INPP4BISG15 IP6K2 MERTKCUBN NSDHL CTH C15orf39 IL7R IFI6 OSGIN1 DOLK SLC7A8 KLF4 NBL1LIMS1 CSTF2TLIMS2QTRTD1SUOX IDEADA SERPINB9 GOT1PLEKHA5ZNF14 GDF15FOSL1CD55 CCNJPDCD4RNF219 JUND SLC17A5EPHA4DEAF1 PDGFCMOSPD2PSAT1THG1L RYBPITGB4SRD5A1YARS SLC7A1PITPNC1 EIF2C2DBNDD2 C16orf45 FAM164A IL15RALTA4HHIVEP2SETXMPZL2RMND1LYST EDC3 IFIH1 CEBPGKLHL3 PCK2 RANBP6 ARHGEF2KLHL21RCAN1 PRDM10EMP2 PTCH1 HOMER1 TINAGL1 SGPL1 GSPT2 PCMTD2WASF3 C6orf120ABHD5 LBR OXA1L SUPT7L SLC25A12 BMP2 AARS TIMM44FOSL2 MALT1MAP1BCYP1A1DLATMETTL7AEFNA1 SERTAD2 CXCL3 ESM1 MEIS2 FANCF TRIB3 TICAM1SLC46A3GPR126IER2 Module EFNB2 SLC3A2MARS TSEN2 ABCG2NAV2 NCK1 ANP32AFNDC3AGPR37CDH5 RHOBTB1 NFIL3VEGFA HBEGF CARS RCOR3 TGIF2PELI2 PDE3APHF15CD302 NR3C2ATP9A IFNGR1 IFRD1 UBR2MAFF CSTF1F3STON1 CLEC2BOAZ3 KIAA1609CCNG2CALD1 MPP1 MEIS1 PCTP INHBA TDG SCN5A PLSCR4 SMURF1SLC35A1ANKRD46TRIP11 FADS1MLLT3YRDC CLU RND3 MAFG SLC7A5MMRN2 KLF9PPP1R15A PPP3CC GIPC2 KD Top functional category p value STX1A LSSFAT4 TMEM39B TRIM68RANBP2 CIDEB TTC17 PLXNA1GYS1NR1D1DHCR24MEF2CSLC9A1 SLC2A3 MANSC1 SLC4A7 CCL14CHST7GJA4 RARA IFI44PDLIM4MAP1ANMT2PLA2G4AMARK1ZNF238 ZNF395 MTHFD2 NPC1 LY75 SPTLC2CASP3 MEGF9 TNFSF10 ZCCHC2MTUS1 GTPBP2 ZDHHC24 UGGT1 DCBLD2SCO2 PIK3C2BZFP36L2GARS GLDCMET ALDH1A3 TNFSF18PCSK7 SERPINE1JAG2RHOBTB3 PEX12 CEBPB PCYOX1PPARDTPD52 MAN1A1KITFLT1 size ANKFY1IMPA2 ZCCHC8 MMP14 FLRT2 BCL2A1GCA RWDD2B MME ACAA1GDF11EVI2BAGGF1PLXNA2 CSNK1A1 DDIT3 SSFA2ENO2 FBXO42 FAM179BLIPA MAX KIF5B SLC39A14SORT1 TACSTD2NAV3VIPR1 DACH1SOX18 FAM171A1ARHGDIAARFGEF1FADS2C17orf90AKAP1PTGS2 IL8 SIAH2 NLGN1 NRCAM GPX3TTLL7 EHBP1L1 CENPT SCARA3GMIP CALCRLRDXABL2ATP13A3SMAD5FBXW11 SOX17 ASNS MAMLD1SETBP1 FILIP1L LIPT1 STC2 TNFRSF1B C1orf163 EDIL3PXNDKK3DZIP3 CSNK2A1VCAM1 KIF3AC1GALT1 ZMYM6 TUFT1 CCL23 IL1RL1 SSBP2 TOR3A PRKAG2TMEFF1 UNGOGFRL1 MAPK1 TSC22D3TFB1M PBX1C22orf29BCL6 CDC5LCYP51A1 ICAM3 RBBP4 SLC2A14 ZNF419SORBS2 CTSO ABCA8 BHLHE40EGR1 UBE2G2 MAPK8PRKD3 HERPUD1 ITPR1 NPR2 PDGFDFHOD1NR2C1CES2 GLT8D2 FKBP1AVWA5ASLC38A1 LRRC32 XPO7TM9SF4ATP10D RPS6KA5 TNFSF9XBP1CASD1 PYCARD EPAS1 DAPK1 STYXL1 USP34 SERPINB8MAP3K7 MMRN1 DDIT4 C16orf5ZNF226 FRMD4B NR1H3 TWIST1 TNFRSF10C PGM3 CPT2 PPP3CASMAD1KIAA0922CORO2B LYPD1 SDPRODZ3 MYST2 A2M PTPN14HN1L PMAIP1 SOS2 GNAI1PRPF4BTHBS1PLAURIOK3 CHST11 FUT8 PIK3R4 RRS1 PLCB1 PRNPSCAMP1ARPC4SPASTTRAM1 SPTLC1TMCO3 LDB2 EML4ENSA ISOC2LRCH4CHST15NRXN3SULT1B1 PCF11FAM108B1HRH1 STX16 FAM124BIL6 SORDHSPA13 CAMK2N1 PLCL1 FAM117A CLIP1UBE2HDHCR7MED28TJP1NBEAFLOT2KIAA1033 PDCD1LG2PPM1DATF5 ATP6V0E2GDI2 TM9SF2 LDLRNPTX1 SLC25A4 THOC6 DOK4MTMR11ANKRD12 ADSS ENTPD5HIPK3RAB1AATP6V1AMBTPS1SMCHD1 RBMS2NDRG3RNF146 TBC1D4 PRKCH SREBF2 PRKAR1A RBMS3CCDC88AMINK1 DUSP4EHD4 CHCHD7 IGFBP2ITPKB UGDH CD40 PLVAP CNN3MYOF FOXC1PTP4A1 SMURF2PXMP3PHTF1 LHFP PROS1SMARCD2 MBNL1 CSGALNACT1 THSD7A CCNB2 513 HALLMARK_E2F_TARGETS 1.52E-20 RBM38 CLIC4 ETS1 DLG1 PDE10ARANGAP1TESSATB2 TCF15 FDFT1SDHC ACP1 MYCT1 DNAJC10 LAMA3PDE2A APOO VASH1 MGST2 HMGCR ANAPC5 BTG2 EXOC2 TNFRSF10DMBD3 AFF4 PARVBTMEM51CCDC69PTGIR CREMHMGCS1 PTPRDCOPA RAB23 CRTAP BCAT1 TACC1 TP53I11 KIAA0040CITED2 ANKMY2 NMD3 GMFB FHL1 QPCTSTC1PPM1F SC4MOL ZNF277INTS1 DICER1 CALU YIPF5 LOX MAP4K4 TOXAAK1 ZC3H12A PLOD2 CAPRIN1 TLR1 EIF4EBP1 B3GNT2BAG2 STK38L WWOX TPST2TCF7L1 BBC3ZMYM1GRIK5EMP1 HNRNPUL2 MBNL2 SF3A2LMF2 FAR2 PIGB NFE2L3IKZF5LMNA CHAC1 C21orf7 CAPN7 KIAA0427JUPWDR45 LYL1 MAD1L1ELMO1 SFT2D2 KIAA1462 ATP6V1C1 GABPB1 RNF14 RIT1 ARFGEF2 MYLK STK32B GLE1 ZFYVE21CC2D1A FKBP5ARF6DCTN4 MDM2 SEC23A MAP3K3CREBZF TEAD4 DIAPH2 MED20IDI1 SQLELEPREL1 FBXO38 RCN3 ERO1L LIMD1 EPORMID2 SLC17A9 NKX3-1ZNF124 ALG6PMS1 PHACTR2 FYN TMEM161A TRRAP TM6SF1 RIPK2MSX1 SCRN1DUSP6 PTBP1 LARP6 WFS1 SLC7A6RPP25 GNAQ TTC38PRKAA1NCOA3NQO1 ITM2B MINASLC7A7 ABCB6 UBXN4 318 GO_GOLGI_ORGANIZATION 2.85E-05 IVNS1ABPKCNN3 PRKCDBP DEGS1 ATF2 SMAD4DKFZp434H1419PIGK BMPR1A CD44 IL15NEK7 SCD C6orf62MAT2ARABEP2TSNDEDDDET1 HIPK2 PTK2SPCS3SLC16A1 ITGA6 CNOT8 DAG1 MTMR1 POLDIP3 PRPF31 CLINT1NRAS SLC26A2 ITGA2 ALCAM EVI5 QSOX1SLC19A2RHBDF2 PSMD11SLC30A1 IL33 ELL2 CHST2 GABPA ETNK1ROCK2LRRC8D NOC3L SLIT2 RPAP3 INSIG1 SCYL2 NFKB2 PHF11 CDH2PRKDCNRIP1 SLC25A13GNPDA1 HERC4 C1orf144PPFIA1KIAA0100 PDLIM5TNFRSF10B ZFPM2 PHTF2PLSCR1 ORAI2GPRC5ABDNF C5orf13CCDC91MXD4 LOC100272216AP1S1TENC1 PAWRARNTL2 PRKAR1BDNAJB4 ANGPTL4 WDR1CXCL1LRRFIP1 MAP3K7IP2 KPNA4TOX4 CLEC1A SEMA3C GCH1 MARCH7DNASE1L1NOP16 SCRN1ARHGAP22 GIT1 SESN1 PRPF6 SELT CANXRNF6LOC653390 GMFGBGNROD1 LAMA5 SLC30A5 LIN7C DPP4 SRPR SRPK1 UBTD1 BMPR2 RANBP9 USP18ANXA3 RPS28 EIF3C LYN IRF9 C20orf111 ARAP3 SLCO3A1ASF1A CRKGNB5 MGMT GPR176KIAA0913 UCP2 TBL1XR1 HYI CLCN4HK2NEDD9 GCKR FUT1 KCTD20ARHGAP1 TCIRG1 ATP2B1MGP STX6 TRAF4 TGFBRAP1 ARFIP1 BST1CFDP1 PTPN4 ITPR3 IL13RA2CYHR1 CCDC68HES1RAB40B SOX4 C19orf6CDV3 PAPOLAPGGT1B DHRS7 COPZ2TMOD3 TPST1 PCSK5 PCDH12 261 GO_ANGIOGENESIS 4.85E-05 SPSB1 MFNG DYRK3 IMPAD1 OCRLDIMT1L SPAG9 EPHA2TLE1 TBXA2RINPP5FPPFIBP2TSPAN13 RGS2 MMP2RBM9 PDGFRLCFI SLC2A1 LPIN1IKBKB EGFRTGFBICTDSPL SLC43A3 GALNT10CBR1 FH MAP3K11 UBXN4 KIAA0090 D4S234ELRP12NUPR1ATP2B4 ATF7IP RAB6APTPN12LMAN1CYR61 CHST3 GOLT1B PALLD STARD8 RALA FAM18B C12orf5 PLCD1NFIB SMG6MAP1S ARID5B TWSG1 COL4A1 KLF5 AIDAFUSIP1 CPD SAV1WARSGALNT1 PIK3CDCCRL2ARL4DASRGL1KLF6 JAG1 hCG_2024410BRCC3GPHNFGF2 TSPAN7 ESYT1 SLC16A7SSR1 TAGLN SCRN1 TRIM34PIGF LYRM2PPP2R5D NOVA1RAGEARNTLCOL4A2NXN CXCL2 CLIP3USE1 CBFB SNAP23 TRAK1 KIAA1539 CDC42EP3 ZNF195STX3DFNA5SHROOM2CXCL6ADAM9GTF2H2NFKBIANEFHST3GAL1 MAP4K5 NNMT LXN PMP22NINJ1 F2R PPIDRNGTTASPH DENND3 TMED2 RAB5A TOR1AIP1 FKBP10MGAT4ANRP1TACC2PLEKHO1 CASP7 PCDH1 AKR1B10NUAK1 H2AFY TWF1 MYO1EGBP1 LOC100292189 UAP1 SMOXGLT25D1OSBPL10 EIF2B2 ASPM 242 GO_ORGANELLE_FISSION 1.96E-09 CCL2 MRPL42 GALNS PTGIS PIGZ DCUN1D4 FOXO3 SFXN3 RGS3 DOCK4DPYDMID1 NRG1IL1BLMCD1 JUNB IL6ST SLC7A11NCOR2 BNIP3L KIAA0247 EPRS CRATSS18 NPEPL1 AZIN1CLDND1PPP1R13LSPHK1 MEST BTKCHST1 PIK3R3 SEC23IP HTRA1 GNA13 BMP4 DNAJC6 SCHIP1RASSF2 FBN1PIR TFRC ACTR2 POLR2L AKAP12 ATF3 PDGFB JAM3 ABR ICAM1 SFRS7 NOTCH2 GRK5IL32PGF CXADR IFT57 TRA2B HYAL1 THAP7 KIAA0494C10orf88LRP5RECQLIL1AFAM89BRANBP1 TRIB1DOCK1 WIPF1 GEMIN4 SEMA5A BTG3 NOP2IDSSH3BP5 FAM38B CALM1NDST1ORAI3 GPR124PIP5K1CCDCA4 EEF1D OAS1 RAB22A PCDH12 KIAA0355CREB3L1MYO1B COL5A2KRR1TBC1D16 RNF216 LPXN TNFSF12 PDXKFERMT1 SYNJ2NQO2PON2EZH2SYNGR1 EML1 CERK CASP8AP2 CRTAC1HNMTFUT4IRS2 SLC39A8 JHDM1DENTPD7 RGS12TMEM159FBXL2SDC4 MGC87042 NFYB SNED1MMP16 MYO5CMMP10CTSSKANK3 GRN 138 KEGG_LYSOSOME 8.22E-11 GADD45ANFKBIEC12orf24GPRC5BSSRP1 RFC3 RSRC1 ROBO4ST3GAL5LRRC16ATNFRSF14 FCF1 FKBP11ADM HDAC9 MCM7 SLC41A3 ITGA10 RBL2 PGRMC1 F8A1 NDRG1ITFG1H2AFXSERPINE2NOTCH1 C1orf103 TFF3 PLCG2 ZBTB20 TM9SF1 MMP1RRP8 TRIM2 C22orf9 PNPLA6 TGFBR3 ABLIM1 PLEK2 NFYA RNASEH2ASUV39H1 POLD1 TTLL12 ARHGEF6GSN HTR2BSCN1B JAM2 HLX MXRA7 IFFO1CDK5RAP2FOLR1ABATCHAF1APDP1TACC3 GMNN POLRMTAKAP9 RUNX1T1 CALHM2 STK39 DPYSL2 CXCR4MYO1D SDC1GTSE1 HIST3H2ACOL18A1ISG20 ZMIZ1 MCM5 SEC22B CCDC86TBRG4RRP12 ZCCHC24 SLC23A2TMEM140 ERLIN2 MAST4 ROR1 LGR4IQCK TIE1 TRA2A ESF1 C13orf15 CTSK RHOFSCRN1 NOTCH4ANGPT2SEMA3G PPP2R5A SFRS3LETMD1ABHD2GPR4 PIGO DOCK9 NME5TSPYL5 SPATS2L PHKA1 TMOD1 FAM176B PPP2R1BIRGQ NARG1FAM136A C14orf159CRIP1RPS6KA2 PPP1R16B HEPH NDN SCRN1 RGL1 CD34 SCRN1 DNMT1PIK3R1WHAMML1 COL3A1 RPL37ANUDT21FKTN BBS4 TCF4 HEXB RAC2 CCND2EPB41L3 MNT MCM2 CDC45LMAD2L1 GPR162YAP1 GIMAP6APEHEXOSC5EBNA1BP2 LMBRD1GBP2 CYB5B ATP6AP2MAGEH1CTSB PFKFB3 GO_REGULATION_OF_PHOSPHORUS_ CHKBTIMM8AMCM3TOP2A PXDN USP13 NUP98 ATP2C1 NID1 BTG1 SLC12A2PTPRM PROCRH6PD PLTP SACS TP53I3CHAF1BTPD52L1HSPA4LDDAH2CDKN2C C1orf135 UCHL5 NADSYN1 PPIC HS2ST1 CLN5LAMP1 SECTM1 PODXLPRRG1PRNDKIF1B HIRATYMSNAGLUZCCHC6 HSPD1 KIF11 PAICS GPR107 NFE2L1 PRKAR2B ROBO3 CPA3 SCRN1 MDN1 TNFRSF21 MCM6MCM4 HIRIP3CLIP2 ENC1 C10orf10PRKACB ARPP19 GALNT7 PNMA2RP1-21O18.1EHD3 CCNA2SEC63 SLFN12 TMX1 SERPINB1 TIMP2 ADAMTS1 KIAA0513TMEM132A WDFY3 EZR TM7SF2C19orf54RNF144A MN1TMPO GADD45B ALPK3NBN PYCR1 SLKGNSNEU1 PALMDOCK10 INPP5D AGL KIAA1462 136 3.95E-06 INF2 NLRP1C12orf51 GINS2 C6orf211RPRD1A ZKSCAN1 THOP1 SLC24A6 DDX18 ALDOCJAK1 ASMTL LEPR YES1NSBP1DUSP3 ADAM19 PNO1MITF C3orf64 TANKGPR116 RBPMS KIF15 DMWD SIP1 LDB1 KDR JARID2 UAP1L1 MCFD2ATRX TAF9B RAB11A ATP6AP1 KIAA0746 ANO10RTEL1 N4BP1RBCK1TSR1 CPSF6 SCPEP1 CHMP1B TEKDENND1ANCAPH MYCBPHMGB2FAM129A FAM149B1TSPAN14EPM2AIP1 MAN2A1 ICA1 PCDH17 GLYR1 GYPC METABOLIC_PROCESS EXOSC2 PRMT2 RTN2 CCNB1 UCK2 EMG1 SGCENET1 BACE2 STAB1 SLC25A20EIF5B CLDN5VWF SYNC S100A2 MXI1DKC1PGCP FLJ42627 C19orf28 ERLIN1 PINK1 TRAPPC2 SEPT6 GABBR2 TCF7L2 ZFP36 C21orf45 HSD17B14FEZ1 PSAPPDIA5FAM57ATP53 C9orf125 TSPAN4CDKN1CIGF2BP3FTH1 HMGCL PAM CKS1B TMEM22POP5LGALS3 CSNK2A2 ERMP1HGSNATBCCIP COX7A1LAPTM4BIL3RA LPHN2CLASP2 STRA13 CENPA CCDC99EXT2 C17orf68FARS2ODF2NPAS2PHYHLPP APOL3 GM2ATMEM30ANUCB1MAN2B2TCEA2SERINC3 MYL9 CD93 IDH3A F5 C13orf34 CALCOCO1PLXND1 SELL HNRNPMTTC3CTDSP2NUP88GGA2AK2 LPAR6 TRAPPC6ANPDC1MAN2B1ISOC1 ECM1 ERCC2 ARL6IP5TCFL5 NDC80 ARHGAP11A TTLL1SSSCA1TPCN1SPATA2LARL4ASNRNP25TFDP1 SFRS1 DNAJB9 SEPT11NT5E RIN2 FCGRTBBS1 TPM2 ZNF692 MGLL CXCR7 TBC1D2BRRP15RASA2ADARB1 VPS13CSERPINB2RPS6KB2 CHD7 PBXIP1 BSCL2APPBP2 SMEK1 CTPS DVL3DKK1ME1 CLDN7 KIAA0020 ZCCHC14 C1orf54CD99 TXNRD2NIPSNAP1 KIAA0564 THOC2 ARHGAP12PARP12 RPL31 FICD RUFY1C1QTNF1 HS1BP3 CTSACD59 GNG11 PTPRE CTNNB1TUBG1 SRMZNF593BOP1 GTF2IRD1 TSPAN9EDEM2TCN2 ARMCX2 PAPSS2 SEMA3F PVRL3 FAF2 WRAP53 SELP MSTO1OGG1 PARD6A TRIM38 ABLIM3MTSS1 ANPEP CENPNADD3 C12orf35SMC4 SH3BGRLFAM64A ALDH7A1OSBPL3 SCARB1XRCC4 ITGB1BP1 FABP4 DNAJB1 129 GO_PROTEIN_FOLDING 6.55E-07 H1FX UBE2S EIF4G1 PLK4 DUS4L COBLL1 RP11-35N6.1 IL10RBC19orf66PLP2 PBX3 CSE1LCDC20 PHLDA3 SOBP SAT1 TNIK NCAPD3 RCBTB1 GALK2 RPA3 PLK1 IER3MCAM HMGN4 EIF2AK3SLC33A1 RNF130 FAM189A2 C1orf115 RND1 FAM102AAK3L1 MARCKS CNN2SMC3 FLOT1 C6orf130 PEG10 RUNX1 FDXR MYO5A SCRN1 B4GALT1 P4HA1SMC1ACRYL1TRIM22 MKI67CROT TNFAIP2 DKK2 KIAA1305 UBE2L6 GRN ABHD4 OSGIN2MLLT11PDE4BFABP5TNFSF4GSDMD PMCH LAMA4 GMPPBPXMP4CEP76 ANGPTL2 SRI ANKRD28 AGXT2L1 NME3 ARMC8 TMEM8ADHRS12KIAA0586 EFEMP1SPA17 TXNIP SMAD6 APOL1 TPP1 COQ2 PDLIM1 NRGNTFPI2 TST PPP1R3CCDK10 RARRES3PSMB10 PGLS PREB DCHS1STAT1 SMARCA1 STIP1 PPM1B DDX60MDK PSMB8 LOC729580 MAP2K6POT1 CST3 AIM1LRRC6 TMEM158 FGFR1OP BIRC5 THBD CEBPD PLEKHF1 PTPN18 GDPD5 LAMP2 UBE2I CYFIP2 RORA ITPR2CYBA NP TRAF3IP2CYB5R2 STEAP3 GRINACDK2 BTN3A2PSMB9 ENPP1HDAC5NOL6 ZSCAN18 LAP3FRMD4A HIST1H1C MAP4 ERCC6L OS9 UBA7VAMP5 PPAP2A CTSD TUSC3FBLN2 RBP1 SNRK HSD17B8HIPK1 ECE1 PCDH7 ACSL5 HLA-E TIMP1 IGFBP6 POP1 BPGM APP LY96 APOBEC3G SULF1 HSPB8 EMG1 129 GO_NCRNA_PROCESSING 3.68E-05 FNBP1L TBC1D2 RPGR CHD4 CASP1 CEP170SNX19KLC1 PIP4K2C STOML1 CDC42EP4MREG TGIF1 CCNB2 TK1 RP11-138L21.1ITM2CPRIM2 CLIC2 C16orf35 CDCP1 INPP1VARS MPDZBTN3A3 SGSH FLNCMAOACCND1 ASS1 RECK THBS3 GLA HMGB3 WHSC1 DDX3Y FNBP1 ARHGEF15 RCBTB2SP110 MGAT4B CLSTN1 ID2 MAPKAPK3ABCB1 TMEM47 GSR UBE2C RNF10 NUCB2 RNF121 AACS UBE4B XIST USP33 ACP2 IRF6 ALDH1A1HPSEEFHD2RAI14 CREB1 STMN1DHRS1RAD21 BAT2D1 GATA6SPSB3 RP11-345P4.4 ADH5PLATBCAMNUDT11 SECISBP2L KDM5DGPSM2 MYL5AURKBPTPRG GALT IL4R APBA2 SPTBN5NTMZNF185 GALNT2 SLC11A2 DDX58 TFPI CDCA8 APOBEC3BC9orf3 UTRN SLC29A1 PCDHGA1 C18orf10 CDKN2AWWTR1 SLIT3 PGRMC2 SAMHD1 RGS4 DEK ZEB1UMPS CD164 PLOD1 SLC2A10 C14orf143 CPE CADM1PRRX1 GATA2AMPHMAPRE2ID3OSTM1 TGOLN2 LIN37IDUA TECPR2 HMOX2IGFBP4 RGS5 BNC2DBF4 CDR2L BGLAP LRP10 TGM2 AHNAK2LPCAT4 SRPX2 CCNE1 APOOL MYO10CHPF2 PTDSS2 GLI3 JUNFAM190B ZDHHC13ISYNA1 ASB9 EPS8 NCLN PSIP1 GO_CELLULAR_AMINO_ACID_METABOLIC_ NOC4L RASIP1 SDF2L1 ID1 SIRPASEMA3A RRAS YIPF3 EIF1AY PPP2R5BNUPL1 KLHL7 DIP2C ITGA4C14orf132NAP1L2 E2F8 SMARCC1 CUEDC1 ROGDI TRAF5 NBEAL2 DDR2 ENTPD1PHF17 MAN1B1 SOD2TTC4RMI1ST7CDC2L6 ADAM10 RIN3PPP3R1 TAF7LSPOCK1BCL3 CLMN SLC2A6 UGGT2LGMNPTPRA RCL1 DLGAP4 PRDM2 YWHAZ CUX1 RAI2PRSS23 PDCD11 GABARAPL1 HSPG2 C7orf44NOL12 PHKB MIR21PIGG SCRN1ALDH3A1 LMO2 OPTN GLS LIAS ZBTB1TGFBR2 ARFGAP1 ECHDC2 PDIA4 ZDHHC14 ABHD14AMYRIP GPR56 UCHL1HIST1H2ACABHD11 GGT5 MTHFD2 114 7.32E-08 TNPO2RAB35 TNNT1 FGFR1SUB1 TBC1D9 RPA2 JRK CGGBP1 TAOK2COQ3POLR3GPAFAH1B1 API5 TMEM149 ATP13A2CSNK1EDAPK3 C11orf67 VGLL4 TSPAN5TOP1 NUDT4PRMT3 TLN1 BZW1 BCL2L1 ITGBL1TBC1D8B CCT2 BMP1C14orf109C10orf119CLDN15LTBRTBC1D15USP46 USP1MYBL1MARK4TNFAIP8 SORBS3FERMT2MAP2K3 MANF PSMG1 GPER SQSTM1 ADRB2 LHFPL2 TM4SF1SRRM2 IGFBP7 RAB32 CYLD IPO4 ANXA4ZNF83 PROCESS FBXO9 NAB1 STAG2SGCBPRPS2 RHOB TSPAN6 NOLC1 CEP57 TIPIN KPNA1 HNRPDL TPM1 CSRP2 HHLA3 EDN1 HDHD1ANNT KIF23TNS3 SLC22A4 ATN1 OBFC1AKAP13FNDC4 C11orf24PTPRF LIPGPVR SSH1 PTPLAD1DNAJC9RFC2 DCLRE1C NAMPTTLE2YAF2 SLC39A6 HPCAL1 ITGAV COX16 PELI1 FANCL RAD54B RAD51AP1SART3 RAB4A DDR1EXT1 SLC48A1 WTAP CBLBSLC27A3 TMEM48 MMD PRPF39 ANXA6 MON1B COL6A1VAMP2C1RLC3orf14RNF24 TSKU HSPE1 CD46 IGFBP3 NCBP1 AMMECR1 TFAM HYAL2 SLC16A3 PDSS1TMEM45AU2AF2 PRUNE2 EIF2B3 NETO2 AGPS MPPE1 CDC25CHEXANEK2 PRIM1 MRC2 TAPBPPLK3 NPC2 POPDC3 KANK1MagmasTCOF1HIVEP1C19orf42TSC22D1 FUCA1PLXNB2 NUP155 SCARB2 ARHGEF7 LANCL1CYP26B1PCIF1 OIP5HYOU1 TAP1 SYNE1 SURF2ACOT1DIS3 ECHDC3TM2D1 MTFR1TAF5EPHB2ZWINT CEP55 ARVCF CACYBP PLCB2PSMD9 ING3 ZNF532 CCNFSFRP1 KIF14 MBOAT7PCTK2HMMR POLE2 AVL9 CARHSP1 ASAP1 TPK1 EFNA4 C19orf61KCTD9BSDC1 TTC37 FAM38A C14orf139 DAAM1 PDE4DIP CENPF PFASPLEKHM1 NMU RAD51C LOC100287515 FAM111A CCDC47EML2 KIF20B MCM10 SMN1 PHF10 C9orf46PLD3 HRASLS CKS2SYNE2 TERF2 NLRX1 CCDC15 ETV4 CTBS GO_NEGATIVE_REGULATION_OF_ERBB_ STIL MAZ LAS1L F11R RPL39L DR1 LTBP2 FRY PAIP1 KNTC1 SLC19A1 ZMAT3 DCAF10MEX3D PDE4D RCC1 DLEU1GGH ECT2 LMBR1LKIAA0101STK10 EEF1A2 PDGFA PLEKHO2 SFRS18 MSH6BARD1 ACAT2CKAP2RACGAP1 CASK AP3D1 SYNM RBM3 SRPRB LOXL1 HIST1H2BK BLM CIT HSPA14PBKPOLA2 NUP160 ZNF22LTBP3EPHB4LTBP4 GTF2I ARMCX3 RRM1 MCC NCAPH2FLJ34077NOP56 TUBGCP4MTHFD1 NUDT1 KTN1 CWF19L1SDC3RAB8BARG2 ANKHD1-EIF4EBP3 FBXO17 ETV5 MED21CENPI THAP10 MAGT1 FBXW7 RPP38 MYBL2BUB1 GFPT1 CSF2RB SYPL1 102 5.86E-05 COMMD10ARHGAP19 DGKA MACROD1 KIF20A ZNF609CLIC3 FKBP1B MAPK14ARMCX1 GNPTABCRELD2DNAJC3MEGF6 GOLGB1 FANCA TMEM187 ACACAMETAP2 MRPL22 ARHGEF12 HIP1 SNX27UBE3BMORC4 MOGSTNIP1 PKMYT1MDC1 UTP20 ORC2LMNS1MED6DLGAP5 ADORA2A VAMP3ELK3APC PPCDC DSCC1 PSMC3IP CDKN1B NEK1 TRIM16 TMEM194A ACSL3LRRC49 MAGED4 SMPD1EXOSC8 NPM3ATIC SKA1 TOPBP1 PA2G4 TTK AURKAARL6IP1PSRC1VPS13B FN1 HEY2 FANCILAMB1TNS1 ASPMHERC1CUGBP2SIDT2 KIAA0141NR5A2 CDYL CREBL2KIF4A NCRNA00094 GLCE TCTN1 FAS ZNF227GDE1ANP32E LRP8 TRMT2B GEM ACYP2 SIGNALING_PATHWAY MOCOSANGEL2 PCNA KIF18BPOLQ TSPAN12 DDX3X TMSB15A RAD51 C1orf27 MICAL1HOMER3 PKNOX1 BAG3 SLC5A3 VRK1 C20orf27 SSR3 GINS1 BUB1B PPP1R10CEPT1PIGL FKBP4 ACYP1ATP5ORFC4 MAGOHB BRCA1ART4 NXT2 SKILGPATCH8 UXS1 MECOM SNW1 PIGT GPR137B ITGB3BP RBM28ACTA2 UPF3ACEP350 KDM4B KDM6B TMEM41BC2orf42MTR TSC22D2C9orf95 TMSB15B TSPAN31TPX2 UNC13B ORC6L GRSF1DNAJB6SNX2 RFC5 ARRB1ATRN RFK MPHOSPH8TP53TG1 HMBS CEP70NCAPG SR140 CLK4 ZNF232PTER SKP2 PRKAB1 CDC2 CAPG TROAP TMEM106CCENPM DARS2 HJURP FSTL3 MARCH3MELK KRIT1C17orf48 SATB1REEP4 SNAPC4TMEM2 TMEM35 IGF2R PARP2 SLC9A3R2 PHLDB1 RHBDF1 SAMSN1 CDC25B DEPDC1 NCAPD2 NCAPG2 NUP107CYB561 MIS12 SNX5ASF1BDNASE2CDC25A GLB1 GBAP LOC100132247 C7orf49 SPAG5 DNAJC4 FANCGOGTEZH1 ATP6V0A1TMEM97ATG5 LRP6EPS15 SHCBP1 CDKN3 KDM5B PRCPNUP205TIMM13 TMEM135CRNKL1CDC6EXO1 STK17AC20orf30C17orf91DSCR3 B3GALNT1 DNAJB1 RAB31 RRM2LOC81691CBX5 KLF7MCL1 PSEN1EIF4B ZBTB11 PPIH RGNEF NRIP3 NUSAP1PGAP1 NF2 GLUL DHRS3 ST6GAL1 CENPE GFPT2 RAD1RESTATAD2CYB5R4 C1orf112 HP1BP3 HAUS4 HNRNPH3 WDR76 FEN1 NOD1APBB2ERI2 APITD1 BEX1 DTYMK LOXL2 ME3 APLP2TMEM185B TFDP2 RARB RUFY2 DTLTMCC1RBBP8 PTPRK ARFRP1 DPYSL3 BET1 TIMELESSKIF2C SYNCRIPLRRC17STARD13 SYNGR3HELLSPDS5A DAZAP2ADNP CNTNAP1 HSP90B1 COLEC12 LMF1TRPM4 TRIP13 GOLM1GINS3 C12orf4PABPN1BAT2L SGPP1SYT11 BMP2K ANKLE2 ANGEL1SPC25AKR1B1 CCNL2ATP1B1FNBP4 CTNNBIP1GPR161PLEKHA1RAPGEF3 ZHX2NFATC1 SAFBDMTF1 KIAA0649INSR PECI GSK3B GBA CDCA3 SMTNTFECIL13RA1EVLABCA3 FBXO5CCNE2POR ASXL2C11orf71MLEC SYPL1 ZFC3H1 DDX39 AGRN NEAT1 AHDC1 GRB10 PYGL JMJD6FAM49AIL17RAACVRL1 ORC5L MED4 SMPDL3AING1ARHGAP26 SNCAFLI1 G3BP2 EIF2C3CHN1 CTSL1ITGA5 KIF22 SNCAIPTNFRSF25DCNC6orf106EFEMP2GRB14 NEIL1 SH3TC1 CKAP4 ALG13 HSPA1A SPATA20 ALAD LRDDNINLPOLMPKIGETV1ABCC10MAN2C1 PRKD2OBSL1 ASB13GLRX AIP KCTD13ERBB2PMM1 POLA1 GALNT12NISCH FBXL18SPG7SMARCD3 SFNRALGDSBSG SMARCA4 HSPA5AMACRBANP NOS3FGGY PCYOX1LABCC1P4HTM SOX13 TRIM24 LOC100289848 MSRB2ELP3 SFRS14 YPEL1LOC728392 AMTPNNXPC MYO6 ZC3H7BCSRNP2TBC1D8 INSIG2 TSPYL2 MYH10 DYNC1I1EPB49 TRPV2 HSD17B11SGSM2 B4GALT6 PBX2 HERC6TMEM204 MORC2 SEC24D PRC1 ADD2 MICALL2GPATCH2 ME2 C1S ADAM23 CHORDC1 IFI35 ABCC5 LCAT DOCK6 CPS1PLS1SIN3BHIP1R C8orf30AEWSR1 CDH11 SEL1LLMAN2LKHDRBS3POSTN SS18L1ZNF432VAMP1 DUTPOFUT2H2AFVBTDDSEZNF589 EDNRBPROSC EPS15L1BMX ELOVL6 LRIG1 NRN1 DHX9 SERPINH1TFAP2A DMPKCRELD1C20orf19ZNF337 RRBP1 CSNK1DPSTPIP2MOSC2 SNAPC1PVRL2 PARD3 LIMA1 SEPT10LRP3 CTTNSLC38A10 ENGWEE1 LEPRE1CRKRS ESPL1 HNRNPDLAMB2AOX1TIA1 KANK2 SSX2IP UBE2J1 SEC24AKIAA0907 PTPRORBBP6 EIF2S2IFI27SAP30 KCNK1 DISC1PPIF PPP2R3AC4orf18 TBL1X TMEM39A SC65 ZNF264 EXTL2 SLC12A7 FAM114A1BST2PIK3IP1CCNL1 CTSZ RALB EXOC5 ITCH MAP3K5 PTPN22RPL10P4HA2ZNF586 LMO4 FLJ10404 C3 TGFB1SNHG3 LMNB2FADS3 DRAM1FAM46A WWC3 LAMP3 TBX1 ZYX C11orf80 MAGED2 FOXM1 PLA2G4C RNF41NR3C1 PMEPA1 HSPH1 RBMS1PCBD1FST CYP1B1 USP10 DNAJA1DIDO1 ZNF767 CREG1 TCEB2 SRBD1 ATP11ABEX4 NBR1 PHLDA2 ALDH1A2 FNDC3B HAUS7COL4A5MLXIPCOL4A6ARSA MKNK2ADAM15 GIMAP4 HEY1C5orf54 SH3BP4 CAPRIN2SFRS5--- POLR1E PTPN11 KAL1 ZNF193 UBE2L3 CUL4B THAP11 CLDN11 C1GALT1C1 PDLIM7 BRD4 SF3B1 EFNA5 SFRS17A ABCG1RBM8AC21orf66 TUBB2ASIL1 CAMSAP1L1 H1F0 ZNF862ELF1PALMD HNRNPA1FAT1 SH3GLB2 NT5DC2 ZFR METTL3AHI1CCRL1SPATA7FASTKD1 PDK1OPA1N4BP2L2 C11orf61 C18orf22 PKP4 LTBP1 PSME4 UBFD1 AKAP8LLPCAT1 ADCY9 FSD1 IER5 CFHARMCX5 C1orf63 AEBP1 ABCA1SLC25A37 APOLD1 RYKC1R HHEXSMARCA2ZC3H11ALAMB3 FSTL1 AHSA1CSTF3GFOD2 ARHGAP24 TRIM8SIPA1L1 SRPK2ADD1KLF3EHD2 KIAA0323 SPRY4ALDH3A2ARGLU1 CCNA1ZNF274 CDC27 IL1R1 ZC3HAV1 AVPI1 APPL2 ANKRD11 BAMBI RAPGEF5NEK3 DUSP1NKTRANKRD10LUC7L3 NFATC2IPCASP4TAF1D SELENBP1SEC14L1 FUBP1 LOC729046 CSGALNACT2ADAT1 ACD MINPP1 PTGS1 OPN3 WDR5B LONP2 GABBR1SFPQ LYRM1PGM1 IFITM1 VAMP8 NFICSAMD9 MED16 CD58GIT2 NACAWSB1GABREAP1G2 CLCN3CLEC3B LARP1 MTDHPRKCSH CDS2 PDIA6ATP2A2 LITAF ZNF271 TBC1D5 DIXDC1 EPHX1CYBRD1SOCS2ENAH PTGER4OFD1 ZNF217EXOSC4 SRCTLE4 GATA3 CBR3 SMC5PPAP2B MZF1TARDBP SEPT9BNC1ANKRD6SMAGP KIAA0182JAK2 PDLIM3HEG1 HEXIM1AP1S2 NAGA CLK1 FJX1 TIPARP GALNT6 C10orf116 ENOX1SMYD2 MGEA5SIPA1L3 MTIF2SPRY2 PALM2-AKAP2MICAL2HMGA2 RSL1D1PTPLAGARNL1GNB2L1 PXMP2C8orf55 FLNAGPR172AMIER2 CLCN7MBOAT2 PRKCDMETTL13RRP1B RGS10KDM3AMFSD10 SAC3D1 FAM3AAGAP1ANKRD55RRAGCGAB2ASB1 DCAF16 COMTFZD2 CPT1A MEF2A NIT1 S1PR1 PNPLA4PLAUR PLEC1SASH1STT3AMED12C1orf50SMCR7L SLC24A1 TRIB2AKAP2SGK1 SCAMP4

Fig. 2 Bayesian networks of HAEC reveal novel key drivers in response to oxidized phospholipids. a, b Network view of HAEC Bayesian network of control state (a) and oxPAPC-treated state (b). Key drivers with more than 100 downstream nodes are indicated and ten top-ranked subnetworks according to strength of enrichment and subnetwork size are colored. Edges are colored according to source node. c, d List of ten subnetworks colored within control (c) and oxPAPC (d) Bayesian network with most top key driver, number of nodes, most significant overrepresented functional category and p value are listed signature overlapped with the MTHFD2 network as compared to (Fig. 4d), suggesting that the de novo mitochondrial glycine the whole oxPAPC Bayesian network (FET p value = 8.34E-16). synthesis is highly active in endothelial cells and more important Finally, the MTHFD2 RNAseq signature also significantly over- than cellular uptake or cytosolic glycine synthesis. Importantly, lapped with the amino acid cluster as compared to all other oxPAPC decreased the intracellular glycine level, even though it differential connectivity clusters (FET p value = 1.19E-17). induced the expression of MTHFD2 (Fig. 4d). To identify indispensable pathway genes, an integrative analysis of all three data sets, the amino acid cluster, the Regulatory pathways contributing to MTHFD2 expression. MTHFD2 network and the MTHFD2 RNAseq signature, was Amino acid metabolic reprogramming was not the only response carried out. This yielded 18 commonly shared genes, which activated by oxPAPC and MTHFD2 siRNA. The amino acid included key enzymes of the glycine-serine-synthesis pathway, cluster, the MTHFD2 Bayesian network and the MTHFD2 aminoacyl-tRNA synthetases, solute carrier transporters as well as RNAseq signature were also enriched for mTOR and amino acid the transcription factor CEBPB and the mitochondrial phosphoe- deprivation and ER stress (Supplementary Fig. 3). Nrf2 signaling nolpyruvate carboxykinase 2 (PCK2) (Fig. 4c). Collectively, these was also activated as oxPAPC increases ROS in endothelial data further support the role of MTHFD2 in amino acid cells16. Interestingly, the ROS scavenger N-acetylcysteine (NAC) metabolic reprogramming. but not glycine supplementation prevented the oxPAPC- mediated induction of MTHFD2 (Fig. 4e). Induction of OxPAPC and MTHFD2 siRNA deplete intracellular glycine MTHFD2 by the activator of the unfolded protein response pools.Wenextidentified the physiological function of this tunicamycin was affected neither by glycine nor by Nrf2. Nrf2 MTHFD2 response. Knockdown of MTHFD2 decreased intracel- orchestrates the cellular redox-defense system and was shown to lular glycine and increased the intracellular serine concentrations be activated by oxidized phospholipids17. The Nrf2 activator tert-

4 NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 ARTICLE butylhydroquinone (tBHQ) indeed induced MTHFD2 expression, serum (FCS) in the culture medium, MTFHD2 induction was suggesting that both compounds act in part through similar massively attenuated upon serum addition (Supplementary cascades (Fig. 4f). Indeed, the Nrf2 inhibitor ML385 prevented Fig. 4a−c). This suggests that ingredients of the serum satisfy the oxPAPC-mediated induction of MTHFD2 expression (Fig. 4g). cellular needs of substrates otherwise generated by the MTFHD2 However, whereas the Nrf2 target gene glutathione synthesizing network. The MTHFD2 network was also enriched for mTOR enzyme Glutamate-Cysteine Ligase Modifier Subunit (GCLM)17 signaling. Application of the mTOR inhibitor rapamycin also was induced by oxPAPC in the presence or absence of fetal calf inhibited expression of MTHFD2 and genes of the MTHFD2

a ISOC2 PIK3R4

NR2C1

RCOR3 TTLL7 FAM179B PCMTD2 SLC2A14 MOSPD2

TRIP11 MDFI SLC2A3 HSPA13 TIMM44 FOSL2 PDCD4 ANKRD46 CDC42EP2 FAM164A F3 CSTF1 MAFG XBP1 DAPK1 NLGN1 MARS FOSL1 DDIT3 MTUS1 TTC17 HERPUD1 KIF3A MAFF MET ZFP36L2 GTPBP2 VEGFA GOT1 IFRD1 LTA4H TNFSF9 SLC39A14 LIPT1 NAV3 YARS NFIL3 PPP1R15A CCNJ CEBPG SLC4A7 GARS C1GALT1 SOX18 SIAH2 BCL2A1 CEBPB MTHFD2 ZCCHC8 FLRT2 RARA EPAS1

MEIS1 PSAT1 C16orf5 STC2 THG1L LDB2 SORBS2 SORT1 SYNPO

TUFT1 RWDD2A KLF9 SLC47A1 EHD1 TFB1M SLC3A2 ITPR1 CBS PPARD SPRED2 PHGDH OSGIN1 SHMT2

GJA4 SLC7A5 MID1IP1 PIK3C2B ARMC9 ARHGEF3 UNKL KCTD12 NENF TRIB3 PCK2 ZCCHC2 CHST7 ZNF467 SLC35A1 AARS SLC1A5 PCYOX1 NPC1 SLC7A1 GLDC CARS FOXO1 UBR2 SETX PLSCR4 ARHGEF2 LYST

IER2 WASF3

b Glycolysis Key driver Cytosol KEGG_GLYCINE_SERINE_ Gluconeogenesis AND_THREONINE_METABOLISM (2.53E-06) GOT1 ASNS Asn Asp REACTOME_CYTOSOLIC_ TRNA_AMINOACYLATION (2.53E-06) Mitochondria PCK2 PHGDH TCA REACTOME_SLC_MEDIATED_ 5,10-meTHF TRANSMEMBRANE_TRANSPORT (1.82E-04) GLDC GO_REGULATION_OF_DNA_TEMPLATED_ TRANSCRIPTION_IN_RESPONSE_TO_STRESS (2.17E-05) Ser Gly PSAT1 SHMT2

THF 5,10-meTHF Formate 10-fTHF MTHFD2 MTHFD1L CBS Cystathione Cys Met Homocysteine CTH cdefg MTHFD2 SHMT2 PSAT1 PHGDH CEBPB 10 25 10 Ct # # 25 # 6 # 8 oxP 20 * * * 20 8 * 6 # # 4 15 15 6 # 4 * * # 10 10 4 # * 2 * * 2 5 * # 5 # 2 Rel. mRNA expr. * 0 0 0 * * 0 0 h i j k l GARS CARS SLC7A5 SLC7A1 MTHFD1L 6 6 10 2 25 # # # # 8 * 20 * * 4 4 * 15 6 # 1 * # 4 # 2 2 * 10 # 5 * 2 * Rel. mRNA expr. 0 0 0 0 0 siRNA Control +––+–– +––+–– +––+–– +––+–– +––+–– siRNA MTHFD2 –+––+– –+––+– –+––+– –+––+– –+––+– siRNA PSAT1 ––+––+ ––+––+ ––+––+ – –+––+ ––+––+

NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications 5 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 network in HAEC (Supplementary Fig. 4d–f). Indeed, oxPAPC derivatives which are then released from HAEC. OxPAPC-treated activated mTOR signaling as assessed from phosphorylated HAEC showed comparatively more heavy labeled extracellular ribosomal protein S6 (S6) (Fig. 4h, i) and inhibition of mTOR AMP which was decreased after silencing of MTHFD2 (Fig. 5l). In signaling by torin also prevented oxPAPC-mediated MTHFD2 contrast, the purine-derivatives NAD and inosine showed only induction (Fig. 4g). Since both, Nrf2 and mTOR activate the about 20% incorporation of heavy serine-derived carbon units transcription factor ATF418, we tested whether the oxPAPC- (Supplementary Fig. 5c, d) and NAD showed only about 10% mediated MTHFD2 expression was ATF4 dependent. ATF4 incorporation of heavy glycine derived carbons (Supplementary siRNA indeed partially prevented the oxPAPC-mediated induc- Fig. 5e). The incorporation of heavy carbons was decreased upon tion of MTHFD2 (Fig. 4j, Supplementary Fig. 4g) and over- oxPAPC treatment. This suggests that serine-glycine metabolism in expression of ATF4 increased PHGDH and MTHFD2 expression HAEC contributes to the synthesis of adenosine nucleotide deri- (Supplementary Fig. 4h−k). Thus, oxPAPC induced MTHFD2 vatives for release which is enhanced by oxPAPC. We therefore expression by a complex response in part mediated by ATF4 hypothesized that oxPAPC activates HAEC to synthesize purine comprising redox as well as mTOR signaling. nucleotides. Conforming to this hypothesis, oxPAPC exposure increased the metabolic activity of HAEC as scored by the mito- OxPAPC elicit endothelial purine nucleotide release.Whydo chondrial oxygen consumption rate (OCR) (Supplementary Fig. 5f). endothelial glycine levels decrease upon oxPAPC stimulation? Glycine is an important substrate for numerous pathways including Blockade of purine release prevents MTFHD2 induction.If heme synthesis, glutathione synthesis and for protein de novo purine release was indeed the mechanism driving the cellular synthesis but particularly important for purine synthesis. Purines, in responses to oxPAPC, blockade of ATP release should attenuate the form of ATP and GTP, are essential for the cellular energy the effects of oxPAPC. Flufenamic acid (FFA) blocks ATP homeostasis and for DNA and RNA de novo synthesis. Purines are release21 and inhibits nucleotide transporter (VNUT)-mediated also important signaling transmitters and endothelial cells release ATP transport22. Indeed, FFA not only blocked the oxPAPC- purines as signaling autacoids in response to numerous stimuli mediated increase in extracellular purines (Fig. 5m), but also including shear stress19. Through the activation of purinergic prevented the induction of MTHFD2 and PHGDH in response to receptors, purines impact on vascular homeostasis, coagulation, oxPAPC (Fig. 5n, o). Similarly, the VNUT inhibitors α- inflammation and on the control of vascular tone20.Thus,we glycyrrhetinic acid and A438079 prevented oxPAPC-mediated speculated that oxPAPC induces the release of ATP and other ATP release (Supplementary Fig. 5g). Moreover, all inhibitors nucleotides and thereby depletes endothelial cells of these mole- partially restored sprouting after oxPAPC treatment of human cules. Indeed, exposure to oxPAPC reduced the endothelial intra- umbilical vein endothelial cells (HUVEC) (Fig. 5p, q, Supple- cellular purine but not pyrimidine nucleoside pools (Fig. 5a–d). mentary Fig. 5h−j). In contrast, glycine alone could not rescue Moreover, the extracellular degradation products of ATP and GTP, oxPAPC-inhibited sprouting (Supplementary Fig. 5k-m). but not of pyrimidines, were increased in response to oxPAPC exposure in the cell culture supernatant of HAEC (Fig. 5e–h). Amino acid deprivation induces the MTHFD2 network. Our MTHFD2 contributes to purine synthesis in the form of glycine and observations raise the possibility that the MTHFD2 network 10-fTHF: Two carbon units are derived from serine which is con- induction in response to oxPAPC is a direct consequence of verted into glycine and incorporated into the purine backbone glycine depletion. To address this, we deprived HAECs of glycine (Fig. 5i). Two additional single carbon units are derived from two and serine which induced the expression of MTHFD2 and serine molecules and are incorporated into the purine backbone as PHGDH (Fig. 6a, b). Additionally, we elicited amino acid depri- 10-fTHF. Additionally, the mitochondrial glycine cleavage system vation by asparaginase which depletes cells of asparagine23 and can cleave glycine into CO2 and 5,10-meTHF which both can be determined the effect of the histidine analog L-histidinol which incorporated into the purine backbone. We therefore analyzed the inhibits activation of histidine by histidyl-tRNA synthetase24. flux of serine- and glycine-derived carbons in response to oxPAPC Indeed, both treatments induced the expression of genes in the by heavy isotope tracing. With and without oxPAPC, labeled serine MTHFD2 network (Supplementary Fig. 6a, b). These findings was detected intracellularly in serine labeled cells and labeled gly- suggest that the MTHFD2 network constitutes an amino acid cine was detected to a lesser extent intracellularly in glycine labeled response that compensates for oxPAPC-induced loss of glycine. cells, indicating that HAEC take up serine as well as glycine (Supplementary Fig. 5a, b). Extracellular AMP, a degradation pro- duct of ATP, contained roughly 90% heavy carbons in heavy serine MTHFD2-knockdown-impaired angiogenesis is glycine labeled as well as in heavy glycine labeled cells (Fig. 5j, k). This dependent. In line with this conclusion, we hypothesized that indicates that HAEC incorporated imported serine as well as supplementation of glycine should overcome the effects of imported glycine into the purine backbone of adenosine nucleotide MTHFD2 siRNA. Indeed, glycine but not serine or asparagine,

Fig. 3 Key driver MTHFD2 and oxPAPC induce endothelial Bayesian amino acid subnetwork. a Network view of the oxPAPC Bayesian subnetwork with MTHFD2 as key driver. Nodes that belong to indicated significantly overrepresented canonical gene set categories are highlighted respectively. Node size reflects out-degree. b Schematic diagram of enzymes within the MTHFD2 network (blue) that are directly or indirectly involved in serine, glycine, cysteine, methionine, aspartate, and asparagine (orange) interconversion as well as interconversion of tetrahydrofolates (THF) inside mitochondria (green). CBS: Cystathionine-Beta-Synthase, PCK2: Phosphoenolpyruvate Carboxykinase 2, GOT1 Glutamic-Oxaloacetic Transaminase 1, GLDC: Glycine Decarboxylase, ASNS: Asparagine Synthetase. c−l Experimental validation of the MTHFD2 network as assessed by quantitative RT-PCR. HAEC with and without knockdown of the key driver MTHFD2 or the downstream node PSAT1 were exposed to medium (1% FCS) with (oxP) or without (Ct) oxPAPC for 4 h (n ≥ 4). Genes belonging to the MTHFD2 network are framed by the color of the corresponding gene set category as in a. Data are represented as mean ± SEM, *p ≤ 0.05 (MTHFD2 or PSAT1 vs Control siRNA), #p ≤ 0.05 (oxP vs Ct) (ANOVA with Bonferroni post-hoc test). MTHFD2: Methylenetetrahydrofolate Dehydrogenase (NADP + Dependent) 2-Methenyltetrahydrofolate Cyclohydrolase, SHMT2: serine hydroxymethyltransferase 2, PHGDH: phosphoglycerate dehydrogenase, PSAT1: phosphoserine aminotransferase 1, CEBPB: CCAAT/Enhancer Binding Protein Beta, GARS: Glycyl-TRNA Synthetase, CARS Cysteinyl-TRNA Synthetase, SLC7A5: Solute Carrier Family 7 Member 5, SLC7A1: Solute Carrier Family Member 1, MTHFD1L: Methylenetetrahydrofolate Dehydrogenase (NADP + Dependent) 1-Like

6 NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 ARTICLE fully prevented the expression of the tested genes belonging to the prevented by glycine, but not by folate or formate supplementa- MTHFD2 network as well as ATF4 in HUVEC (Fig. 6c–f). To tion (Fig. 6h, i, Supplementary Fig. 6f−i). Importantly, pro- determine the importance of this response we measured endo- liferation was only slightly decreased upon knockdown of thelial migration in a scratch wound assay and the angiogenic MTHFD2 and this effect was rescued by glycine whereas oxPAPC capacity as determined by spheroid outgrowth in response to inhibited proliferation in an MTHFD2-independent manner VEGFA. MTHFD2 siRNA impaired migration of HUVECs which (Supplementary Fig. 6j). To confirm the importance of MTHFD2 was prevented by glycine supplementation (Fig. 6g, Supplemen- for angiogenesis, we tested the contribution of MTHFD2 in an tary Fig. 6c). Interestingly, also folate but not formate restored ex vivo organoid mouse model of angiogenesis. Murine aortic normal migration upon knockdown of MTHFD2 (Supplementary rings with siRNA-mediated knockdown of Mthfd2 showed Fig. 6d, e). Impairment of sprouting by silencing MTHFD2 was decreased vessel formation which was restored by glycine

a b Row Z-score ISOC2 PIK3R4 Log2FC –2 0 2 NR2C1 –2.0 0 2.3 RCOR3 FDR < 0.05 TTLL7 GARS MARS FAM179B SLC1A4 PCMTD2 PCK2 SLC2A14 PHGDH YARS MOSPD2 CLIP4 SLC7A5 TRIP11 MDFI SLC2A3 HSPA13 IGFBP5 TIMM44 NAV3 FOSL2 PDCD4 PSAT1 ANKRD46 ALDH1L2 CDC42EP2 FAM164A TUBE1 F3 CSTF1 MAFG XBP1 SLC6A9 ASNS DAPK1 ANKFN1 NLGN1 MARS FOSL1 AARS DDIT3 SHMT2 MTUS1 TTC17 HERPUD1 CBS KIF3A MAFF NDUFA4L2 ZFP36L2 MET VEGFA SLC3A2 IFRD1 NUPR1 GTPBP2 GOT1 JDP2 LTA4H SLC39A14 CARS TNFSF9 PSPH LIPT1 NAV3 CCNJ YARS NFIL3 CHAC1 PPP1R15A PAPPA2 SLC4A7 GARS CEBPG ADM2 EDNRB C1GALT1 SOX18 SIAH2 IL13RA2 BCL2A1 MTHFD2 SLC7A11 CEBPB WARS ZCCHC8 SERPINB2 FLRT2 RARA EPAS1 STC2 LACC1 MEIS1 VLDLR PSAT1 SYNE1 C16orf5 STC2 THG1L HMGA2 LDB2 CBS CCND2 SORBS2 SORT1 SYNPO STMN3 NPTX1 BIRC3 TUFT1 RWDD2A MAGED1 KLF9 SLC47A1 EHD1 GJA4 TFB1M SLC3A2 MRAP2 ITPR1 POSTN FADS2 PPARD PHGDH SPRED2 ADCY4 SEMA6C OSGIN1 MRC2 SHMT2 CLDN5 ACE GJA4 SLC7A5 MID1IP1 EXOC3L1 PIK3C2B ARMC9 CXorf36 REEP1 ARHGEF3 TRIB3 KCTD12 SNORD30 UNKL PCK2 NENF SNORD43 C11orf95 ZCCHC2 CHST7 MTHFD2 ZNF467 SLC1A5 SLC4A5 SLC35A1 AARS RBP1 PCYOX1 NPC1 SLC7A1 GLDC FOXO1 UBR2 SETX CARS PLSCR4 ARHGEF2 LYST

IER2 WASF3 siRNA Control #1 siRNA Control #2 siRNA Control #3 siRNA MTHFD2 #2 siRNA MTHFD2 #3 siRNA MTHFD2 #1

c d Log2 Arginine MTHFD2 Lysine MTHFD2 61 network Cysteine-Homocysteine RNAseq Methionine 11 –120 2 Phenylalanine signature Histidine Seleno-Methionine 348 18 24 Ornithine Asparagine Serine Aminoacid Glycine-Proline 22 Proline-Hydroxyproline 211 cluster Homocystine Hydroxyproline Cystathionine Core genes Cysteine MTHFD2 SHMT2 PHGDH PSAT1 Homocysteine Thiaproline SLC1A5 SLC3A2 SLC7A1 SLC7A5 Aminoadipic acid GARS CARS MARS AARS YARS Threonine Trypthophane CEBPB PCK2 STC2 VEGFA TRIB3 Citrulline Glutamine Glutamate e Aspartate MTHFD2 Methionine-Sulfoxide Beta-Alanine 15 Leucine DMSO * Proline oxP * Valine Tunica * Alanine 10 Cystine Tyrosine Glycine

5 * * #1 #2 #3 #1 #2 #3 #1 #2 #3 #1 #2 #3 #1 #2 #3 #1 #2 #3 #1 #2 #3 #1 #2 #3 #1 #2 #3 #1 #2 #3 # siRNAs Control siRNAs MTHFD2siRNAs siRNAs Rel. mRNA expr. 0 Control MTHFD2 Glycine ––+––+– oxPAPC oxPAPC NAC –––+––+ f ghi j MTHFD2 MTHFD2 pS6 MTHFD2 10 10 10 Ct Ct 6 Ct 8 oxP 8 oxP S6 8 oxP * 4 * 6 * 6 * 6 * MTHFD2 # 4 # 4 4 2 # pS6 / S6 * 2 2 # # 2 β-actin Rel. mRNA expr. Rel. mRNA expr. 0 0 0 * Rel. mRNA expr. 0 tBHQ –+–+ Torin –+––+– –++oxP oxP –++ siCtr +–+– ML385 ––+––+ ––+Rapa Rapa ––+ siATF4 –+–+

NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications 7 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 supplementation (Fig. 6j, k). Furthermore, zebrafish embryos atherosclerotic samples. To identify whether the MTFHD2 net- exposed to oxPAPC showed deregulated vessel formation and work has any association with cardio-vascular disease we increased mRNA expression of mthfd2 (Fig. 6l–n). Additionally, obtained the data set of the CARDIoGRAMplusC4D genome- zebrafish embryos with a morpholino-mediated knockdown of wide association (GWAS) study26. For our analysis, we searched − mthfd2 showed deregulated vasculature morphology (Fig. 6o–r, for SNPs (p value from logistic regression <1×10 4) significantly Supplementary Fig. 6k). Collectively, our findings indicate that associated with CAD and identified that genes of the MTHFD2 oxPAPC induced endothelial glycine depletion; that MTHFD2 is network contained several CAD-associated SNPs (Table 2, Sup- induced to compensate for glycine deprivation; and that the plementary Data 5). Moreover, the CAD risk loci were enriched MTHFD2-dependent glycine production is essential for endo- for genes of the MTHFD2 network (FET p value < 0.0077). Col- thelial cell function. We suggest that oxidized phospholipids lectively, the data raise the possibility that the MTHFD2 network induce a metabolic reprogramming response of endothelial cells contributes to CAD development. which allows for the replenishment of cellular nucleotide pools To address whether the expression of the MTHFD2 network is that become depleted as a consequence of oxPAPC-induced changed in human atherosclerosis, we reanalyzed data from a nucleotide release (Fig. 6s). study comparing carotid artery gene expression between 32 healthy and 32 plaque-carrying specimens (GSE43292)27. Expres- MTHFD2 sion changes of the MTHFD2 network genes in the carotid impacts on plasma metabolites in humans. To sup- arteries in response to atherosclerosis were similar to those of port the role of the MTHFD2 network and serine-glycine meta- endothelial cells in response to oxPAPC (Supplementary Fig. 7a). bolism, we speculated that alterations of the MTHFD2 network The majority of the MTHFD2 network genes that were induced in might impact on the plasma concentrations of relevant metabo- response to oxPAPC were also increased in atherosclerosis. lites in humans. It should be mentioned that this approach would fi fi Moreover, an association was also observed for oxPAPC- and not allow us to link the ndings to any speci c vascular altera- atherosclerosis-mediated gene repression. In line with this tions. We obtained data from a human genome-wide association 25 observation, expression of MHTFD2 in 126 human carotid study that provides the plasma abundance of 400 metabolites plaque samples of the BiKE study (GSE21545)28 was positively allowing us to test whether genes in the MTHFD2 network were correlated with genes of the MTHFD2 network as well as Nrf2 associated with the metabolite abundances. For this, we searched −4 fi and ATF4 but not with MTHFD1L which does not belong to the for SNPs (meta-analysis p value < 1×10 ) signi cantly associated MTHFD2 network (Fig. 7b, Supplementary Fig. 7b). with human plasma metabolites. An SNP rs10174907 in fi fi To correlate our ndings with late stage atherosclerosis, we MTHFD2 was signi cantly associated with plasma N-acet- tested carotid endo-atherectomy specimens from the same ylglycine concentration, SNPs associated with N-acetylglycine human cohort as in Fig. 7a (patient characteristics, Supplemen- concentration were enriched for the genes in the MTHFD2 net- tary Table 7). The tissue samples were classified as stable plaques work (FET p value < 0.0045) and genes of the MTHFD2 network (n = 20) or unstable plaques (n = 20). SHMT2 expression was showed associations with plasma metabolites directly or indirectly increased in plaque material of subjects with unstable plaques and related to glycine metabolism (Table 1). In total, 60 SNPs in 28 MTHFD2 expression was increased in plaque material of both genes in the MTHFD2 network were associated with plasma subpopulations (stable and unstable plaques) compared to metabolite concentrations (Supplementary Data 4). This analysis healthy arteries (Fig. 7c, d). Conforming to the mRNA expression suggests that the MTHFD2 network, as constructed by us for pattern, MTHFD2 expression was increased in vessels of subjects HAECs, is essential in the regulation of plasma metabolite con- with atherosclerotic disease as compared to subjects without centrations. To address a link to vascular disease, the plasma plaque (Fig. 7e, f). Subjects with unstable plaques exhibited a glycine to serine ratio in a human cohort with carotid artery significantly decreased plasma glycine to serine ratio and had a disease was determined. Interestingly, the plasma glycine to serine stronger increase in MTHFD2 expression than subjects with ratio was decreased in subjects with unstable atherosclerotic fl = stable plaques. Unstable plaques are in ammatory activated but plaques (n 26) and decreased by tendency in subjects with are also enriched in endothelial cells compared to stable plaque stable atherosclerotic plaques (n = 26) compared to plaque-free = and thus are characterized by increased angiogenesis. Taken subjects (n 26) (Fig. 7a). together, these data support the notion that MTHFD2 is expressed and upregulated in human atherosclerosis and seems MTHFD2 expression is increased in cardiovascular diseases. to affect the amino acid glycine and serine metabolism. Since atherosclerosis is driven in part by oxidized lipids, we A problem of these human studies, however, is that the hypothesized that the MTHFD2 network is active in human analyses focused on a rather late time point-established vascular

Fig. 4 Knockdown of MTHFD2 and oxPAPC drains the intracellular glycine pool. a Heatmap for fragments per kilobase of transcript per million mapped reads (FPKM) of significantly differentially expressed genes (FDR < 0.01, Benjamini−Hochberg). RNAseq was performed in HAEC with three different siRNAs against MTHFD2 or scrambled control. b Projection of RNAseq signature (FDR < 0.01, Benjamini−Hochberg) in a onto the MTHFD2 network. Direction of expression of nodes of the MTHFD2 network in RNAseq signature is indicated by the node color. Node size reflects out-degree. c Venn diagram of genes in the amino acid cluster, MTHFD2 network and MTHFD2 RNAseq signature (FDR < 0.01, Benjamini−Hochberg). Genes belonging to all three gene sets are listed. d Heatmap of amino acid profile. HAEC were treated with three different siRNAs against MTHFD2 or scrambled control and exposed to medium (1% FCS) with or without oxPAPC for 4 h. Amino acids in cell lysates were measured by mass spectrometry (n = 6–9). e Relative mRNA expression of MTHFD2 in HAEC pretreated with N-acetylcysteine (NAC) (5 mM) and glycine (500 µM) for 1 h and then exposed to medium (1% FCS) with (oxP) or without (Ct) oxPAPC or tunicamycin (10 µgml−1) for 4 h (n = 5). f qRT-PCR detection of MTHFD2 in HAEC exposed to medium (1% FCS) with or without oxPAPC and treated with tBHQ (20 µM) or DMSO as control for 24 h (n = 4). g HAEC were exposed to medium (1% FCS) with or without oxPAPC and additionally treated with torin (100 nM), ML385 (10 µM) or DMSO as control (n = 4). h, i Western blot detection (h) and quantification (i)of phosphorylated S6, S6 and MTHFD2 in HAEC pretreated with rapamycin (20 nM) or DMSO as control overnight and exposed to medium (1% FCS) with or without oxPAPC for 4 h (n = 4). j HAEC were treated with scrambled control siRNA (siCtr) or siRNA against ATF4 and exposed to oxPAPC or control medium for 4 h (n = 5). Data are represented as mean ± SEM, *p ≤ 0.05 (oxP or tunicamycin vs Ct), #p ≤ 0.05 (inhibitor present vs absent or ATF4 vs Control siRNA) (ANOVA with Bonferroni post-hoc test)

8 NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 ARTICLE

a AdenosinebcdGuanosineCytosine Uridine e Adenosine fGuanosine ghCytosine Uridine 2.0 2.0 2.0 2.0 6 * 2.0 * 1.5 1.5 1.5 1.5 1.5 1.5 1.5 4 1.0 1.0 1.0 1.0 1.0 1.0 1.0 * * * 2 0.5 0.5 0.5 * 0.5 0.5 0.5 0.5 Relative conc. Intracellular Relative conc. Extracellular 0.0 0.0 0.0 0.0 0 0.0 0.0 0.0 oxP – + – + – + – # oxP–+ – + – + – +

ij13 k 13 l 13 Ser C3-Serine C2-Glycine C3-Serine AMP AMP AMP GCS SHMT2 5,10-meTHF 100 m 100 m 100 m 80 m+1 m+1 m+2 80 m+1 60 m+2 m+2 CO2 m+3 60 Glycine m+3 50 m+3 MTHFD2 25 25 20 N 20 20 N 15 15 10 10 10 Rel. fraction (%) Rel. fraction (%) 5 Rel. fraction (%) 5 0 0 0 N N 10-fTHF oxP – + oxP – + oxP ++ siRNA Control +– Gln siRNA MTHFD2 –+ m n o p q ATP MTHFD2 PHGDH CTL oxP oxP + FFA 6 8 2.5 DMSO 5 DMSO DMSO oxP oxP 2.0 VEGFA 4 6 * CTL 4 3 1.5 $ * * 4 2 1.0 # 2 # # #

# length (mm) 2 Cum. sprout 0.5

Rel. luminesc. 1 VEGFA Rel. mRNA expr. * * 0 0 0 0.0 FFA – – + FFA – – + – – + oxP –++–++ FFA ––+––+

Fig. 5 OxPAPC elicits ATP release and inhibition of ATP release prevents induction of MTHFD2. a−d Nucleoside measurement in HAEC exposed to medium (1% FCS) with (oxP) or without (Ct) oxPAPC for 24 h. Cell lysates were measured by mass spectrometry (n = 6). (*p ≤ 0.05 Student’s t test). e−h Nucleoside measurement in supernatants of HAEC exposed to medium (1% FCS) with or without oxPAPC for 24 h. Supernatants were measured by mass spectrometry (n = 4) (*p ≤ 0.05 Student’s t-test) i Scheme of flow of serine- and glycine-derived carbons which can be incorporated into the purine 13 13 backbone. j, k HAEC were treated with C3-serine (j)or C2-glycine (k) and oxPAPC or control for 24 h and supernatants were measured by mass spectrometry (n = 3). Relative fractions of extracellular AMP containing no (m), one (m + 1), two (m + 2) or three (m + 3) heavy carbons are shown. l 24 h 13 flux analysis with C3-serine labeling in HAEC with or without siRNA mediated knockdown of MTHFD2 (n = 3). m ATP measurement of supernatants of HAEC exposed to medium (1% FCS) with or without oxPAPC and flufenamic acid (FFA, 50 µM) for 8 h. ATP was measured by luminescence and normalized to intracellular RNA concentration (n = 7). n, o qRT-PCR detection of MTHFD2 and PHGDH in HAEC exposed to medium (1% FCS) with or without oxPAPC and flufenamic acid (FFA, 50 µM) for 24 h (n = 5). p, q Spheroid outgrowth assay (p) and quantification (q) of the cumulative sprout length of HUVEC treated with combinations of oxPAPC, flufenamic acid (FFA, 50 µM) and VEGF-A165 (10 ng ml−1) as indicated (n = 6). Scale bar: 50 µM. Data are represented as mean ± SEM, *p ≤ 0.05 (oxP vs Ct), #p ≤ 0.05 (inhibitor present vs absent), $p ≤ 0.05 (VEGFA vs Ct), (ANOVA with Bonferroni post-hoc test if not otherwise indicated) disease in a heterocellular context (whole organ) whereas our and not only observed upon direct stimulation with oxPAPC. To initial experiments were carried out in endothelial cells at an early test this hypothesis, we subjected ApoE−/− mice to a brief course time point. To bridge this gap, we returned to mouse models. of an atherogenic high-fat Paigen diet. Paigen diet is a specific Exposure of the murine thoracic aorta to oxPAPC in organ high fat diet that contains not only triacylglycerides (15.5%) and culture increased the expression of the network genes Mthfd2, cholesterol (1.25%) but also cholate (0.5%). When administered, Phgdh, Shmt2 and Slc3a2, an effect prevented by rapamycin high plasma lipid and cholesterol levels, as well as systemic (Fig. 7g–j). Moreover, the MTHFD2 network was induced in inflammation, are induced and massively accelerate atherosclero- endothelial cells harvested from carotid arteries in the partial sis development. ApoE−/− mice are particularly sensitive to this ligation model, an in vivo mouse model of blood flow withdrawal- diet as these mice already exhibit high VLDL levels under basal induced accelerated atherosclerosis29. Mthfd2 and Shmt2 were conditions30. Importantly, already 4 days after the initiation of significantly induced in the endothelium of partially ligated the diet, the expression of Mthfd2 was increased in the arteries compared to non-ligated arteries (Fig. 7k, l). Importantly, endothelium of the murine carotid artery (Fig. 7m). Encouraged endothelial expression of genes within the MTHFD2 network was by this finding, we wondered whether also atherogenic lipopro- already induced 24 and 48 h after partial ligation in a previously teins obtained from human subjects with vascular disease would published data set29 (Supplementary Fig. 7c). induce the MTHFD2 network in endothelial cells. To study this, These findings may suggest that the MTHFD2 network we obtained high-density lipoproteins (HDL) from healthy induction is fundamental to the atherosclerotic disease at large subjects (n = 10) or stable CAD patients (n = 10) (patient

NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications 9 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 characteristics, Supplementary Table 8). It was previously Discussion established that HDL from CAD patients loses its protective Using an integrative network modeling approach, we identified effects and becomes atherogenic31. Indeed, HDL derived from an unexpected association of atherogenic lipids and athero- CAD patients compared to HDL from healthy subjects induced sclerosis with the mitochondrial one-carbon metabolism. In the network genes MTHFD2, PHGDH, CEBPB, and PCK2 in human endothelial cells, oxidized phospholipids activated a net- HAEC (Fig. 7n–q). This effect was sufficiently strong to translate work in which MTHFD2 was identified as a key driver to increase into protein expression: As determined by western blot analysis, the generation of glycine. Glycine was required for the formation MTHFD2 protein abundance was increased in HAEC exposed to of purines to compensate for their loss from endothelial cells in CAD patient-derived HDL (Fig. 7r, s). response to oxidized phospholipids.

acb dh VEGFA MTHFD2 PHGDH PHGDH PSAT1 H O VEGFA Glycine + Glycine 10 2 6 siRNA MTHFD2 6 Ct # # # -Glycine 8 * 6 siRNA Control # 4 -Serine # # 4 * siRNA

* Control 6 4 * * 4 * * * 2 2 2 2 Rel. mRNA expr. Rel. mRNA expr. 0 0 0 0 siRNA Gly ––++––++––++ ––++––++––++ MTHFD2#1 Ser ––––++++–––– ––––++++–––– Asp ––––––––++++ ––––––––++++ siRNA MTHFD2#2

e f g siRNA Control i DDIT3 ATF4 siRNA MTHFD2 4 4 # siRNA MTHFD2 + Glycine 2.5 # # siRNA Control # # 0.4 siRNA MTHFD2#1 # 2.0 3 3 siRNA MTHFD2#2 * * * * * 0.3 1.5 # # 2 * 2 $ $ 0.2 # 1.0 $$ 1 1 length (mm) Cum. sprout 0.5 *

Rel. mRNA expr. 0.1 *

0 0 Distance (mm) 0.0 Gly ––++––++––++ ––++––++––++ 0.0 VEGFA –+–+–+–+–+–+ Ser ––––++++–––– ––––++++–––– 0 5 10 15 Glycine ––++––++––++ Asp ––––––––++++ ––––––––++++ Time (h)

j siRNA Control siRNA Mthfd2 siRNA Mthfd2 + Glycine k l

siRNA Control siRNA Mthfd2 30 Control # 20 * Pecam1 10 length (mm) oxPAPC Cum. sprout

0 Glycine – – +

Mthfd2

m n o Morpholino control Morpholino control mthfd2

20 Ct * 3 oxP * 15 * Control 2 oxPAPC 10 * 1 5 Morpholino mthfd2 Morpholino mthfd2 Vessels / embryo Rel. mRNA expr. 0 0 Hyper ++–––– oxP – +

P-ISV ––++–– Control oxPAPC I-ISV ––––++

pqr s oxPAPC

10 Morpholino control 15 # 15 mTOR ATF4 NRF2 8 Morpholino mthfd2 * Gly 10 10 # * 6 # Ser MTHFD2 MTHFD2 Gly 4 * network 5 5 C C N 2 N Angiogenesis

I-ISV / embryo C P-ISV / embryo Hyper / embryo C C ATP N 0 0 0 N oxP – – + + oxP – – + + oxP – – + + FFA

10 NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 ARTICLE

Endothelial metabolism has been recognized as an important were also members of the MTHFD2 network. This observation is determinant of endothelial cell function32, controlling angiogen- in line with the fact that ER stress is present in atherosclerotic esis and the adaptation of endothelial cells to different environ- plaques and promotes the atherosclerotic process through apop- mental conditions33. Oxidized phospholipids, however, have not tosis44. Important pro-atherosclerotic lipids like 7-ketocholesterol yet been linked to endothelial metabolism. Deregulated amino through this mechanism fuel the atherosclerotic process45.ER acid metabolism and in particular overexpression of serine- stress is also present in regions of the arterial endothelium sus- glycine-synthesizing enzymes and mitochondrial one-carbon ceptible to atherosclerosis46. This and the inflammatory activa- metabolism is associated with rapid proliferation of cancer tion of the endothelium in the atherosclerotic process explain cells34. Thus, MTHFD2 is highly expressed in many cancers or why we observed an activation of the MTHFD2 network in the embryo35, whereas expression is low in most postmitotic atherosclerotic plaques. Moreover, our finding that decreasing cells12,36. We show that MTHFD2 contributes to glycine synthesis MTHFD2 expression induces endothelial cell dysfunction could in endothelial cells in a disease-relevant manner. Plasma glycine is serve as an explanation of why genetic variations in genes of the inversely associated with myocardial infarction risk37 and in our MTHFD2 network were associated with CAD risk. present work we found an association between plasma amino Oxidation of lipoproteins which has been best studied for LDL acids, the MTHFD2 genotype and cardiovascular risk. Moreover, occurs in the intima of the arterial wall and thus oxLDL is knockdown of MTHFD2 reduced the angiogenic function of scarcely found in the plasma47. Nevertheless, we observed that the cultured cells. Importantly, glycine prevented this effect and also highly inflammatory and atherogenic lipid- and cholate-rich blocked MTHFD2 network induction in response to MTHFD2 Paigen diet in ApoE−/− mice as well as HDL particles obtained siRNA. Currently, MTHFD2 is tested as a potential drug target from the plasma of patients with CAD increased endothelial for cancer therapy38. Our data suggest that MTHFD2 inhibition MTHFD2 expression. Although these data link MTHFD2 to the might also attenuate tumor angiogenesis. development of atherosclerosis, they must not raise the impres- MTHFD2 contributes to NADPH production that is required sion that this response is mediated through oxPAPC. As we for nucleic acid and lipid synthesis and to glutathione and observed in the present study, MTHFD2 is a highly stress- thioredoxin recycling39. Glycine is also needed for glutathione sensitive gene and induced by numerous pathways. In fact, the synthesis. In line with this, the MTHFD2 network comprised dysfunctional HDL from CAD patients induces endothelial oxi- genes responsive to amino acid starvation, ER stress, mTORC1, dative stress31 and also any high cholesterol diet increases and Nrf2 activation. This response pattern reflects the central endothelial ROS formation48. Thus, although the present work on position of glycine in cellular metabolism. oxPAPC-mediated induction of MTHFD2 was instrumental in Purines are products of glycine in the intermediate metabolism linking signaling of oxidized lipids to amino acid metabolism in and induction of the MTHFD2 network facilitated the endothelial endothelial cells, the findings extend beyond this pathway: production of purines in response to oxPAPC. In fact, purine Endothelial cell activation in general appears to induce MTHFD2 nucleotides are important autacoids which, if released from which is a meaningful response given that ATP release is a ste- endothelial cells, elicit a plethora of responses. The local release of reotypic response of endothelial cells to stress. purine nucleotides from atherosclerotic plaques and the sub- In conclusion, by taking advantage of an integrative network sequent activation of cellular purinergic receptors is thought to modeling approach we unveiled a new reaction pattern of promote the development of atherosclerosis40. Nucleotide release endothelial cells. Our work not only demonstrates the power of is an endothelial stress reaction and occurs in response to Bayesian network analysis to uncover novel signaling mechan- thrombin, shear stress, and oxidative stress induced by copper- isms in vascular disease, it also illustrates the enormous secretory oxidized LDL19,41,42. The mechanism of stress-induced purine capacity of endothelial nucleotide release in the signaling context. nucleotide release is not fully understood but a role of gap It appears that endothelial cells prioritize autacoid release to such junctions has been suggested41,43. Indeed, gap junction blockers an extent that they would rather become deprived of vital prevented ATP release in response to oxPAPC in the present metabolic components than neglect their signaling function. study. The compounds also prevented the induction of the MTHFD2 network in response to oxPAPC suggesting that the induction of the network is a compensatory reaction to the loss of Materials and methods purines. Reagents. The following reagents were used: NAC (Sigma-Aldrich, Cat# A7250), tunicamycin (Enzo Life Sciences, Cat# BML-CC104), glycine (VWR, Cat# OxPAPC and knockdown of MTHFD2 induced ATF4 and 10119CU), tBHQ (Sigma-Aldrich, Cat# 19986), ML385 (Sigma-Aldrich, Cat# several ER stress response genes like DDIT3 and sXBP1 which SML1833), Rapamycin (Sigma-Aldrich, Cat# R0395), Torin 2 (Selleckchem, Cat#

Fig. 6 MTHFD2-dependent glycine is crucial for angiogenesis. a, b qRT-PCR detection of MTHFD2 and PHGDH in HAEC treated with (Ct) or without serine (300 µM) and glycine (30 µM) for 16 h (n = 4). (*p ≤ 0.05 Student’s t test) c−f HUVEC treated with the indicated siRNAs were supplemented with or without glycine, serine or asparagine (500 µM) for 16 h (n = 8). DDIT3 DNA damage inducible transcript 3 (also known as CHOP). g Scratch wound migration assay of HUVEC treated with the indicated siRNAs and supplemented with or without glycine (500 µM). Migration distance after application of scratch is depicted (n = 5). (ANOVA with repeated measures) h, i Spheroid outgrowth assay (h) and quantification of the cumulative sprout length (i)of HUVEC treated with or without the siRNAs indicated and VEGF-A165 (10 ng ml−1) or glycine (500 µM) (n = 6). Scale bar: 50 µM. j, k Immunofluorescence (j) and quantification of cumulative sprout length (k) of aortic ring outgrowth in organ culture treated with the indicated siRNAs and glycine (500 µM) (n = 6–12). Pecam1 was used as a marker for endothelial cells. Scale bars: 500 µM (overall image), 100 µM (zoom) l, m Confocal microscopic image (l)of zebrafish vasculature of tg(fli1:EGFP) embryos at 72 h post-fertilization (hpf) injected without or with 1 µg µl−1 oxPAPC into yolk at 0.5 hpf. White arrows indicate hyperbranches and yellow arrows indicate partial normal intersegmental vessels. Quantitative morphological analysis (m) in control (n = 30) and oxPAPC (n = 31) group shows hyperbranches (Hyper), partial normal (P-ISV) and intact (I-ISV) intersegmental vessels per embryo. The experiment was performed two times. Scale bar: 100 µM. n qRT-PCR of zebrafish embryos in m normalized to elongation factor 1-alpha (elfa)(4–5 embryos pooled per sample) (n = 7). o–r Confocal microscopic image (o) and quantification (p−r)oftg(fli1:EGFP) embryos at 72 hpf injected with control (n = 20) or mthfd2 morpholino (n = 20) at 0.5 hpf with (n = 19) and without 1 µg µl−1 oxPAPC (n = 20). Data are represented as mean ± SEM; c−i *p ≤ 0.05 (MTHFD2 vs Control siRNA), #p ≤ 0.05 (with vs without amino acid), $p ≤ 0.05 (VEGFA vs Ct) (ANOVA with Bonferroni post-hoc test); m−r *p ≤ 0.05 (oxP vs Ct), #p ≤ 0.05 (mthfd2 vs control morpholino) (ANOVA with Newman−Keuls post-hoc test). s Proposed model of findings

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Table 1 Association between MTHFD2 network gene loci and plasma metabolites directly or indirectly associated with glycine metabolism

Gene Metabolite SNP p value MTHFD2 N-acetylglycine rs10174907 1.43E-05 EPAS1 N-acetylglycine rs1530628, rs2197698, rs1530627 8.69E-05, 9.45E-05, 9.76E-05 GLDC Glycine rs2297442 2.94E-05 AARS Tyrosine rs9936903 1.89E-08 LTA4H Methionine rs12579455 4.99E-05 SETX Citrulline rs612169, rs545971, rs674302, rs514659 5.91E-05, 6.35E-05, 6.39E-05, 6.86E-05 EPAS1 Tryptophane rs1530628 8.13E-05 PCK2 Glycerol 3-phosphate rs1062230 2.60E-05

Q ð Þ¼ ð ij ð iÞÞ ð iÞ S2817), serine (Sigma-Aldrich, Cat# S4500), asparagine (Sigma-Aldrich, Cat# decomposed as p X i p X Pa X , where Pa X represents the parent set of i A4159), VEGF-A 165 (R&D, Cat# 293-VE), Asparaginase (Sigma-Aldrich, Cat# X . In our networks, each node represents transcription expression of a gene. These fl A3809), L-Histidinol (Sigma-Aldrich, Cat# H6647), FFA (Sigma-Aldrich, Cat# conditional probabilities re ect not only relationships between genes, but also the F9905), α-glycyrrhetinic acid (Sigma-Aldrich, Cat# G10105), A438079 (Sigma- stochastic nature of these relationships, as well as noise in the data used to Aldrich, Cat# A9736), Oligomycin A (Sigma-Aldrich, Cat# 75351), CCCP (Sigma- reconstruct the network. Aldrich, Cat# C2759), antimycin A (Sigma-Aldrich, Cat# A8674), rotenone Bayes formula allows us to determine the likelihood of a network model M (Sigma-Aldrich, Cat# R8875), formate (Sigma-Aldrich, Cat# 06473), folate (Enzo given observed data D as a function of our prior belief that the model is correct and Life Sciences, Cat# ALX-460-006). The following antibodies were used: pS6 (Cell the probability of the observed data given the model: P(M|D) ~P(D|M)*P(M). The Signaling, Cat# #2215, dilution 1:1000), S6 (Cell Signaling, Cat# 2317, dilution number of possible network structures grows super-exponentially with the number fi 1:1000), MTHFD2 (Proteintech, Cat# 12270-1-AP, WB dilution 1:1000, IF dilution of nodes, so an exhaustive search of all possible structures to nd the one best 1:200), SHMT2 (Bethyl, Cat# A305-351A, dilution 1:2000), β-actin (Cell Signaling, supported by the data is not feasible, even for a relatively small number of nodes. 56 Cat# 4970S, dilution 1:1000), Pecam-1 (BD Biosciences, Cat# 553370, dilution We employed Monte Carlo Markov Chain (MCMC) simulation to identify 1:200), FLAG (Sigma-Aldrich, Cat# F3165, dilution 1:1500). Primers for qRT-PCR potentially thousands of different plausible networks, which are then combined to are listed in Supplementary Table 9. obtain a consensus network. Each reconstruction begins with a null network. Small random changes are then made to the network by flipping, adding, or deleting individual edges, ultimately accepting those changes that lead to an overall Gene set enrichment analysis. Genes of interest (e.g. genes within each subnet- improvement in the fit of the network to the data. We assess whether a change work or differential connectivity cluster compared to whole network or all dif- improves the network model using the Bayesian Information Criterion (BIC)57 ferential connectivity clusters) compared against a collection of canonical and non- which avoids overfitting by imposing a cost on the addition of new parameters. canonical gene sets (MSigDB v6.0)49 by using Fisher’s exact test in R (p values This is equivalent to imposing a lower prior probability PðMÞ on models with correspond to Fisher’s exact test). Overlaps between the MTHFD2 RNAseq sig- larger numbers of parameters. nature, the amino acid cluster, and the MTHFD2 network were computed using Even though edges in Bayesian networks are directed, we can’t infer causal Fisher’s exact test in R. relationships from the structure directly in general. For example, in a network with two nodes, X1 and X2, the two models X1 ! X2 and X2 ! X1 have equal probability distributions as pðX1;X2Þ¼pðX2jX1ÞpðX1Þ¼pðX1jX2ÞpðX2Þ. Thus, RNA sequencing and data analysis. RNA isolated from HAEC was treated with by data itself, we can’t infer whether X1 is causal to X2, or vice versa. In a more DNase (Qiagen, Cat# 79254). Library construction (LncRNA library, Ribo-Zero), general case, a network with three nodes, X1, X2, and X3, there are multiple groups quality assessment, and sequencing (HiSeqSE50) were performed by Novogene. of structures that are mathematically equivalent. For example, the following three Differentially expressed genes were identified using the following procedure: firstly, different models, M1 : X1 ! X2; X2 ! X3,M2: X2 ! X1; X2 ! X3, and sequencing reads were aligned to the human reference genome hg19 using M3 : X2 ! X1; X3 ! X2, are Markov equivalent (which means that they all TopHat50. Next, the mapped sequences were aligned with htseq-count to quantify encode for the same conditional independent relationships). In the above case, all the read count for each gene51. The edgeR package52 was then used to identify three structures encode the same conditional independent relationship, differentially expressed genes between control and siRNA treatment. We detected X1 6?X3jX2, X1 and X3 are independent conditioning on X2, and they are 399 differentially expressed genes at FDR of 0.05 (Benjamini−Hochberg). mathematically equal

Differential connectivity clusters. Differentially co-expressed gene pairs and pðXÞ¼pðM1jDÞ¼pðX2jX1ÞpðX1ÞpðX3jX2Þ differential connectivity (DC) clusters were computed as the following: In short, ¼ pðM2jDÞ¼pðX1jX2ÞpðX2ÞpðX3jX2Þ : fi Spearman correlation coef cients of each gene pair were computed and trans- ¼ ð j Þ¼ ð 2j 3Þ ð 3Þ ð 1j 2Þ formed into Fisher’s Z-statistics9. Next, Q statistics were computed and 997 per- p M3 D p X X p X p X X mutations were conducted by randomly assigning sample labels. A final cutoff of = = 1 2 Q0 22.5 that corresponds to FDR 4.89% was used to detect DC pairs. In Thus, we can’t infer whether X is causal to X or vice versa from these types of addition a given gene pair had to be significantly co-expressed (Spearman’s cor- structures. However, there is a class of structures, V-shape structure (e.g. relation p value< 0.01) in either control or oxPAPC group to be called a differ- Mv : X1 ! X2; X3 ! X2), which has no Markov equivalent structure. In this case, entially co-expressed DC gene pair. If the differentially co-expressed gene pair was we can infer causal relationships. There are more parameters to estimate in the Mv significantly co-expressed in control group but not oxPAPC group it was assigned model than M1, M2, or M3, which means a large penalty in BIC score for the Mv to the LOC category and if the DC gene pair was significantly co-expressed in model. In practice, a large sample size is needed to differentiate the Mv model from oxPAPC but not control group it was assigned to the GOC category. the M1, M2, or M3 models.

HAEC Bayesian networks. The accuracy of Bayesian networks is highly dependent Incorporating genetic data as a structure prior in the HAEC Bayesian net- on the number of samples used in the network construction process. We showed in works. In general, Bayesian networks can only be solved to Markov equivalent a series of simulation studies that accuracy of reconstructed networks significantly structures, so that it is often not possible to determine the causal direction of a link improves when sample size increases from 100 to 100053. In the same paper, we between two nodes even though Bayesian networks are directed graphs. However, showed that integration of genetic information as structure prior can significantly the Bayesian network reconstruction algorithm can take advantage of the experi- improve accuracy of constructed Bayesian networks when sample size is between mental design by incorporating genetic data to break the symmetry among nodes 100 and 300. Experimentally, we systematically validated networks constructed in the network that lead to Markov equivalent structures, thereby providing a way with genetic priors and inferred key drivers in yeast7, mouse54 and human55 with to infer causal directions in the network in an unambiguous fashion58. We mod- sample sizes in the above range. In this study, we constructed HAEC Bayesian ified the reconstruction algorithm to incorporate eSNP data as prior as following: networks based on 147 samples with genetic data integrated as priors. genes with cis-eSNP59 are allowed to be parent nodes of genes without cis-eSNPs, Bayesian networks are directed acyclic graphs in which the edges of the graph but genes without cis-eSNPs are not allowed to be parents of genes with cis-eSNPs, are defined by conditional probabilities that characterize the distribution of states pðtrans À > cisÞ¼0. We have shown that integrating genetic data such as cis- of each node given the state of its parents. The network topology defines a acting eSNP or eQTLs (excluding edges into certain nodes) improves the quality of partitioned joint probability distribution over all nodes in a network, such that the the network reconstruction by simulations53 and by experimental validations7,58. probability distribution of states of a node depends only on the states of its parent We note that in applying this particular version of the Bayesian network recon- nodes: formally, a joint probability distribution pðXÞ on a set of nodes X can be struction algorithm (incorporating genetic information as a prior); if genetic

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ab 8 r = 0.344 9 r = 0.413 10 r = 0.348 9 r = 0.276 9 r = 0.326 r = 0.424 14 P = 8.01e-05 P = 1.568e-06 P = 6.392e-05 P = 0.0018 P = 0.0002 P = 7.522e-07 7 8 9 8 8 6 12 * 6 7 ns 7 8 7 5 6 10 4 mRNA 4 6 7 5 6 8 PSAT1 SHMT2 SLC3A2 SLC7A5 VEGFA CEBPB 6 ratio 3 5 4 5 6

Plasma 2 8 r = 0.415 12 r = 0.548 10 r = 0.427 7 r = 0.250 8 r = 0.378 r = 0.345

glycine / serine 12 P = 1.357e-06 P = 3.124e-11 P = 6.34e-07 P = 0.0047 P = 1.294e-05 P = 7.592e-05 0 7 10 8 6 7 10 NP +––

SP –+– mRNA 6 8 6 5 6 8 UP ––+ CARS GARS PCK2 TRIB3 NFE2L2 ATF4 5 6 4 4 5 5 6 7 8 9 5 6 7 8 9 5 6 7 8 9 5 6 7 8 9 5 6 7 8 9 5 6 7 8 9 MTHFD2 (mRNA) MTHFD2 (mRNA) MTHFD2 (mRNA) MTHFD2 (mRNA) MTHFD2 (mRNA) MTHFD2 (mRNA) ced f MTHFD2 SHMT2 * 5 * * 6 * 4 4 * * * * -actin

3 MTHFD2 β 4

2 2 2 1 β-actin MTHFD2/ Rel. mRNA expr. 0 0 0 NP +–– +–– NP +–– SP –+– –+ – NP SP UP Ct SP –+– UP ––+ ––+ UP ––+ gkh i j l m Mthfd2 Phgdh Shmt2 Slc3a2 Mthfd2 Shmt2 Mthfd2 4 * * 3 * * 3 3 15 10 5 * * * 3 * * * * 8 4 2 2 2 10 6 3 2 4 2 1 1 1 5 1 2 1 Rel. mRNA expr. Rel. mRNA expr. Rel. mRNA expr. 0 0 0 0 0 0 0 oxP –++ –++ –++ –+ + RCA +– +– HFD (d) 0 1 4 Rapa ––+ ––+ ––+ ––+ LCA –+ –+ n o p q r s

MTHFD2 PHGDH CEBPB PCK2 2.0 2.0 4 4 4 * * * * 1.5 1.5 3 * 3 3 -actin β 1.0 1.0 2 2 2 MTHFD2 0.5 0.5 1 1 1

Rel. mRNA expr. β -actin MTHFD2 / 0.0 0.0 0 0 0 HDLH +– +– +– +– HDL H +– HDLC –+ –+ –+ –+ HDL healthy HDL CAD HDL C – +

Fig. 7 MTHFD2 is deregulated in cardiovascular disease. a Glycine to serine ratio in plasma of human subjects with no atherosclerotic plaque (NP) (n = 26), stable atherosclerotic plaque (SP) (n = 26), and unstable atherosclerotic plaque (UP) (n = 26) as assessed by mass spectrometry. b Scatter plots showing expression correlation in 126 human carotid plaque samples between MTHFD2 and genes of the MTHFD2 network (colored according to Fig. 3a) as well as Nrf2 (NFE2L2) and ATF4 as calculated by Pearson correlation. c, d Relative mRNA expression of MTHFD2 and SHMT2 in plaque material of human subjects with unstable atherosclerotic plaque (UP) (n = 20), stable atherosclerotic plaque (SP) (n = 20), or non-atherosclerotic artery (NP) (n = 8) (normalized to 18SrRNA)(n = 8). e, f Western blot analysis of MTHFD2 expression (e) and quantification (f) of plaque material from human subjects with unstable atherosclerotic plaque (SP) (n = 20), stable atherosclerotic plaque (SP) (n = 20), or non-atherosclerotic artery (NP) (n = 8). g–j Relative mRNA expression of Mthfd2, Phgdh, Shmt2, and Slc3a2 in mouse thoracic aortic rings kept in organ culture and exposed to medium (1% FCS) with or without oxPAPC and rapamycin as indicated for 8 h (normalized to 18SrRNA)(n ≥ 4). k, l Relative mRNA expression of Mthfd2 and Shmt2 in the endothelium of partially ligated left carotid artery (LCA) compared to healthy right carotid artery (RCA) 48 h post ligation (normalized to 18S rRNA)(n = 3). (*p ≤ 0.05 Student’s t test). m Relative mRNA expression of Mthfd2 in the endothelium of the left carotid artery of ApoE−/− mice which were fed with high fat diet (HFD) for 0, 1, or 4 days (normalized to 18S rRNA)(n = 5). n–q Relative mRNA expression of MTHFD2, PHGDH, CEBPB and PCK2 in HAEC exposed to HDL from healthy human subjects (n = 10) or human subjects with CAD (n = 10) for 4 h. (*p ≤ 0.05 Mann Whitney test). r, s Western blot analysis of MTHFD2 (r) and quantification (s) of HAEC treated as in f for 24 h (n = 10) (*p ≤ 0.05 Mann Whitney test). Data are represented as mean ± SEM, *p ≤ 0.05 (ANOVA with Newman−Keuls post-hoc test if not otherwise indicated)

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Table 2 Association between genes within the MTHFD2 Human carotid atheroma, Biobank-of-Karolinska-Endarterectomy, and partial carotid artery ligation data. We retrieved human atherosclerotic plaque data27, network and CAD risk loci which included 32 paired samples of atheroma plaque and macroscopically intact tissue. The mRNA expression levels were downloaded from Gene Expression Gene SNP p value Omnibus (GEO) with the corresponding GEO accession ID GSE43292. Each platform’s probe ID was mapped to the corresponding gene symbol and the SORT1 rs7528419, rs12740374, 7.05E-08, 1.25E-07, expression levels were averaged over multiple probes mapped to the same gene rs4970834, rs611917 1.04E-06, 1.45E-06 symbol. The significance level of differentially expressed genes was calculated by SLC7A1 rs9551751 7.93E-08 Wilcoxon rank sum test. SHMT2 rs11172113 1.72E-06 Similarly, mRNA expression levels in 126 human carotid plaque samples from DDIT3 rs11172113 1.72E-06 the Biobank Each (BiKE) were downloaded (GSE21545)28. For correlation analysis MARS rs11172113 1.72E-06 of gene expression comparing MTHFD2 and other genes within the MTHFD2 fi CEBPB rs6095611, rs1034056, 9.14E-06, 1.38E-05, network, Pearson correlation coef cient was calculated in R by using the cor.test rs6067199, rs6091031 1.59E-05, 1.75E-05 function. Our previously published microarray29 was reanalyzed for expression levels of FOXO1 rs9594389, rs7323896 1.68E-05, 1.78E-05 genes within the MTHFD2 network 24, 48 h and 2 weeks after partial carotid artery GJA4 rs1336624 2.42E-05 ligation surgery. CDC42EP2 rs12419237 4.82E-05 PIK3C2B rs16854023 5.57E-05 Genome-wide association studies (GWAS) of plasma metabolites and cor- onary artery disease. We collected significant SNPs (meta-analysis p value < 1×10 − 4) associated with one of more than 400 metabolites in human blood in a information is not available or is ignored, the population is simply treated as a genome-wide association study (http://metabolomics.helmholtz-muenchen.de/ population with random genetic perturbations. gwas/)25. Candidate SNPs were mapped to genes if their physical locations were within ±5 kb of gene bodies. We also compared candidate SNPs in CARDIo- GRAMplusC4D (Coronary ARtery DIsease Genome wide Replication and Meta- Averaging network models. Searching optimal Bayesian network (BN) structures analysis (CARDIoGRAM) plus The Coronary Artery Disease (C4D) Genetics) − given a data set is an NP-hard problem. We employed an MCMC method to do consortium. In particular, we collected significant SNPs with p value < 1×10 4 local search of optimal structures as described above. As the method is stochastic, based on CARDIoGRAMplus4D 1000 Genome-based GWAS study, which is a the resulting structure will be different for each run. In our process, 1000 BNs were meta-analysis of GWAS studies using 1000 genomes with 38 million variants26.We reconstructed using different random seeds to start the stochastic reconstruction searched significant SNPs whose physical location is within ±500 kb of coding process. From the resulting set of 1000 networks generated by this process, edges region of genes within our MTHFD2 network. that appeared in greater than 30% of the networks were used to define a consensus network. A 30% cutoff threshold for edge inclusion was based on our simulation study53, where a 30% cutoff yields the best tradeoff between recall rate and pre- Cell culture. Human aortic endothelial cells (PeloBiotech, Cat# 304-05a, Lot No. cision. The consensus network resulting from the averaging process may not be a 2366) and pooled HUVEC (Lonza, Cat# CC-2519, Lot No. 0000371074, fi BN (a directed acyclic graph). To ensure the consensus network structure is a 0000369146, 0000314457) were cultured in a humidi ed atmosphere of 5% CO2 at directed acyclic graph, edges in this consensus network were removed if and only if 37 °C on gelatin (Sigma-Aldrich, Cat# 61890)-coated dishes. Cells were grown in the edge was involved in a loop and the edge was the most weakly supported of all enhanced endothelial cell growth medium (PeloBiotech, Cat# PB-C-MH-100- edges making up the loop. 2199), consisting of endothelial basal medium (EBM) supplemented with gluta- mine, bFGF, hEGF, VEGF from this kit and 8% FCS (Biochrom, Cat# S0113), − − penicillin (50 U ml 1) and streptomycin (50 µg ml 1) (ThermoFisher, Cat# 15140- 122). HUVEC were used at passages 3−5. HAEC were used at passages 3–10. Identification of key drivers and associated subnetworks . For each Bayesian During oxPAPC treatment cells were starved in EBM containing 1% FCS. For network, we further identified the key causal regulators by examining the number 53 glycine and serine starvation, RPMI-1640 media without glucose, glycine and of N-hob downstream nodes (NHDN) for each gene in the directed network . For −1 μ serine (Teknova, Cat# R9660-02) was used and supplemented with 1 g l glucose a given network, let be the numbers of N-hop downstream nodes and d be the (Sigma-Aldrich, Cat# 16301). As primary cells were used at low passage, myoplasm out degrees for all the genes. The genes with the number of N-hop downstream testing was not performed. nodes (NHDN) greater than μ þ σðμÞ are nominated as key drivers. The key drivers with degree above d þ 2σðdÞ, where d denote the number of downstream genes, become key drivers. These criteria identified genes with number of down- OxPAPC treatment. OxPAPC was either derived from Invivogen (Cat# tlrl-oxp1) stream nodes and number of outlinks significantly above the corresponding or Avanti Polar Lipids (Cat# 870604) or produced from PAPC (Avanti Polar average value. Based on the causal networks which we constructed, we identified 29 Lipids, Cat#, 850459) by 24–74 h autoxidation of the nitrogen-air-dried PAPC- key drivers in control Bayesian network and 27 key drivers in oxPAPC Bayesian lipid film. OxPAPC was dissolved in EBM containing 1% FCS and cells were network. The subnetwork associated with each key driver was defined as down- treated in EBM containing 1% FCS. Since the activity of oxPAPC varies, con- − stream nodes (i.e. neighbors in outdegree direction) with the key drivers as the centrations in the range of 40–65 µg ml 1 were used. Where indicated low oxPAPC − − seeding point. Edges remained the same as in the complete network. Cytoscape 3.4 refers to 40–50 µg ml 1 and high oxPAPC refers to 50–65 µg ml 1. was used for network visualization. SiRNA transfection and overexpression and proliferation. For siRNA treat- ment, endothelial cells (80–90% confluent) were transfected with Lipofectamine Assessment of Bayesian networks. To assess the accuracy of the HAEC Bayesian RNAiMAX transfection reagent (Thermo Fisher, Cat# 13778150) according to the networks, we compared the BNs with several widely used databases of gene net- instructions provided by Thermo Fisher. The target-specific siRNAs for MTHFD2 works and gene sets: (1) 37,080 interactions covering 9465 genes from Human and PSAT1 were obtained from Invitrogen (Stealth RNAi, Cat# 1299001) and for Protein Reference Database (HPRD) database60, (2) 195,859 high confident 61 ATF4 from Sigma-Aldrich (Cat# NM_001675). The scrambled siRNAs were interactions covering 12,427 genes from STRING database , (3) 1329 canonical obtained from Invitrogen (Stealth RNAi, siRNA Negative Control Med GC pathways covering 8439 genes from MsigDB databases62, and (4) 11,174 Gene ≥ Duplex). Plasmid overexpression in endothelial cells was performed with the Neon Ontology (GO) annotation sets (sets with size 200 are excluded) covering 11,508 electroporation system (Invitrogen) with FLAG-tagged ATF4 (gift from Yihong Ye, genes. In particular, we calculated the percentage of our inferred gene-gene con- Addgene plasmid pRK-ATF4 #26114)64. Cells were lysed 24 h after electroporation. nections that are in existing protein/gene network databases, or within the same For proliferation assay cells were counted 48 h after transfection with a CASY cell pathway in gene set databases. For comparison, we generated 100 random net- counter (OMNI Life Sciences). works for corresponding BNs by using the degree.sequence.game function in the igraph R package, and estimated the accuracy of random networks. Additionally, we assessed the predictive power of our BNs by using gene sets RNA isolation and qRT-PCR in endothelial cells. Total RNA isolation was closely regulated in endothelial cells. In particular, we used two independent gene performed with an RNA Mini Kit (Bio&Sell, Cat# BS67.311). Reverse transcription sets, which include 77 gene sets related with endothelial cell from MsigDB, and was done with SuperScript III Reverse Transcriptase (Thermo Fisher, Cat# 400 siRNA gene signatures in HUVEC63. For siRNA gene signatures, we 18080044) and oligo(dT) (Sigma-Aldrich, Cat# O4387) together with random downloaded and preprocessed microarray data as previously described63, and genes primers (Promega, Cat #C118A). CopyDNA amplification was measured with with a z-score >2 and <−2 were defined as significantly upregulated and qRT-PCR using SYBR Green Master Mix and ROX as reference dye (BioRad, Cat# downregulated genes, respectively. Based on these gene sets, we compared accuracy 172-5125) in a PikoReal cycler (ThermoFisher). Relative expression of target genes of our BNs to that of widely used gene networks including HRPD database by was, if not otherwise indicated, normalized to β-Actin and analyzed by the delta calculating the percentage of gene−gene connections that are within the same −delta Ct method with the PikoReal software (ThermoFisher). In siRNA experi- gene set. ments RNA was isolated 48–72 h after transfection.

14 NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 ARTICLE

Protein isolation and western analyses in endothelial cells. Cells were washed ATP measurement. Extracellular ATP was measured in cell supernatant cen- two times with Hanks solution (Applichem) and lysed with RIPA lysis buffer trifuged for 3 min at 5000 × g and then 10 min at 17,000 × g using CellTiter-Glo supplemented with Benzonase (Sigma-Aldrich, Cat# E1014), sodium orthovana- Luminescent Cell Viability Assay (Promega, Cat# G7570). Luminescence was date (Applichem, Cat# A2196), PhosStop (Sigma-Aldrich, Cat# PHOSS-RO), Beta- detected using an Infinite 200Pro plate reader (Tecan) and normalized to intra- glycerophosphate (Sigma-Aldrich, Cat# G9422), Sodium fluoride (Sigma-Aldrich, cellular RNA concentration. Cat# S7920) for 5–10 min. Cell extracts were boiled in Laemmli buffer, equal amounts of protein were separated with SDS-PAGE and gels were blotted onto a Cell migration. A scratch wound-healing assay was performed in 24-well plates. nitrocellulose membrane. After blocking in Rotiblock (Carl Roth, Germany), first HUVEC were scratched and cultured in EBM containing 1% FCS. Endothelial cell antibody was applied. Infrared-fluorescent-dye-conjugated secondary antibodies migration into the scratched area was monitored by live cell imaging (Zeiss TIRF were purchased from Licor (Bad Homburg, Germany). Signals were detected with System LASOS77). The distance migrated was calculated using ImageJ software. an infrared-based laser scanning detection system (Odyssey Classic, Licor, Bad Homburg, Germany). Uncropped scans are provided in the supplement (Supple- mentary Fig. 8). Spheroid outgrowth assay. HUVEC spheroids were generated as described65. Images were acquired with an Axiovert135 microscope (Zeiss). For quantification of the cumulative sprout number, ten spheroids per condition were analyzed with Oxygen consumption rate. The cellular OCR was analyzed using a Seahorse 96 the help of the AxioVision software (Zeiss). Treatments with VEGF-A 165 were − extracellular flux analyzer (Agilent). HAEC were plated in Seahorse 96-well cell performed for 16 h with a concentration of 10 ng ml 1. culture plates 1×104 cells/well 1 day before the assay and equilibrated for 1 h in Krebs Henseleit buffer (111 mM NaCl, 4.7 mM KCl, 1.25 mM CaCl ,2mM 2 Animal experiments. All animal experiments were performed in accordance with MgSO , 1.2 mM NaH PO ) supplemented with 11 mM L-Glucose and 2 mM L- 4 2 4 − Glutamine. Cells were treated with 2.5 µM oligomycin A, 1 µM CCCP, 1 µg ml 1 the National Institutes of Health Guidelines on the Use of Laboratory Animals. All antimycin A and 1 µM rotenone as indicated. OCR was normalized to protein animal procedures were approved by the local committees or regulatory autho- content of the wells. rities. Mouse experiments were carried out in the C57BL/6 strain and only male mice were used (Jackson Laboratory, Bar Harbor). Mice were fed ad libitum with standard chow diet (unless otherwise indicated) and experiments were carried out at an age of 8–12 weeks. Amino acid profiling by mass spectrometry. For amino acid profiling, HAEC were lysed in 85% Ultra LC-MS methanol (Roth, Cat# HN41.1). Lysates were centrifuged for 10 min at 17,000 × g and 50 µl of supernatants were processed using Aortic ring assay. Aortic ring assay was conducted as the following: aortae from the EZ:faast LC-MS free amino acid analysis kit (Phenomenex, Cat# AL0-7500) ten male wild-type 6–8-week-old mice were removed, cleaned, and embedded in a according to the manufacturer’s instructions with minor modifications. An internal collagen type I gel (BD Biosciences, Heidelberg, Germany) in a 48-well plate standard (10 µl) was applied to all samples and to the standard curve. The internal containing EBM medium supplemented with murine orthologous serum (2%). For standards included homoarginine, methionine-D3 and homophenylalanine. Ana- Mthfd2 knockdown, scrambled control siRNA (Ambion) and Mthfd2 siRNA lysis of metabolites was performed by LC-MS/MS using an Agilent 1290 Infinity (Sigma-Aldrich) in a final concentration of 100 µM were added in the growth LC system (Agilent) coupled to a QTrap 5500 mass spectrometer (Sciex). The media for 24 h by use of the Lipofectamine RNAi reagent (Invitrogen). Glycine intensity of the measured metabolite was normalized to internal standards and treatment was performed in 500 µM final concentration every 48 h. Tube-like protein content of cell lysate pellets. Analyst 1.6.2 and MultiQuant 3.0 (Sciex, structures were allowed to develop over 5 days. Thereafter, the samples were fixed Darmstadt, Germany) were used for data acquisition and analysis. (4% paraformaldehyde) and endothelial cells were visualized using antibody against Pcam1. The knockdown was evaluated by immunostaining against Mthfd2.

HILIC-LC-MS/MS analysis of metabolomics flux. For serine heavy isotope High-fat diet and oxPAPC ex vivo treatment. All animal procedures were tracking, HAEC were washed twice with glycine and serine-free EBM. HAEC were approved by the local government authority Regierungspräsidium Darmstadt. For treated with or without oxPAPC in EBM without serine and supplemented with high-fat diet male ApoE−/− mice (C57BL/6 background) were purchased from 300 µM 13C -Serine (Cambridge Isotope Laboratories, #201595-68-8) and 1% 3 Taconis M&B A/S (Ry, Denmark, strain B6.129P2-Apoetm1Unc N6) and bred at dialyzed FBS (ThermoFisher Scientific, Cat# A3382001) for 24 h. For glycine heavy the local facility. Paigen-type (19.6% protein, 15.8% fat, 4.3% fiber, 5% ash, 24.4% isotope tracking, HAEC were washed twice in glycine and serine free EBM. HAEC starch, 7.9% sugar; 1.25% cholesterol, 0.5% Cholate) diet was purchased from Ssniff were treated with or without oxPAPC in EBM without glycine and supplemented Spezialdiäten (Soest, Germany). Animals received paigen-type diet ad libitum for 1 with 30 µM 1,2-13C -Glycine (Cambridge Isotope Laboratories, #67836-01-5) and 2 or 4 days. After diet feeding, endothelial-specific RNA of carotid arteries were 1% dialyzed FBS and for 24 h. Medium was harvested and centrifuged for 10 min at isolated29. 17,000 × g and supernatant was subjected to mass spectrometry analysis. HAEC For ex vivo oxPAPC treatment C57BL/6J mice were euthanized with isoflurane. were lysed in 85% Ultra LC-MS methanol, centrifuged for 10 min at 17,000 × g and Mice were coated with 70% ethanol to decontaminate the incision area and then supernatant was subjected to mass spectrometry. Adenosine monophosphate perfused with cold HANKS solution. The thoracic aorta was detached from the (Sigma-Aldrich, Cat# A2002), NAD (Sigma-Aldrich, Cat# N1636), Inosine (Sigma- thoracic vertebrae and cleaned from adipose tissue. Vessels were cut into 1 mm Aldrich, Cat# I4125), glycine (VWR, Cat# 10119CU), and serine (Sigma-Aldrich, segments and incubated in EBM 1% FCS (endothelial basal medium + 1% fetal calf Cat# S4500) were used as authentic reference standards. Liquid chromatography serum). Each vessel was split into 12 × 1 mm segments, after which four segments was performed using an Agilent 1290 Infinity LC system (Agilent, Waldbronn, were used for each treatment group. All vessels were incubated overnight in EBM Germany) coupled to a QTrap 5500 mass spectrometer (Sciex, Darmstadt, Ger- + 1% FCS and treated the following day. RNA was isolated according to the many). Electro spray ionization in positive and negative mode was employed, manufacturer instructions (Bio&Sell RNA Isolation Kit). respectively. HILIC separation was achieved using a Nucleoshell HILIC column (Macherey-Nagel, Düren, Germany) 100 × 2 mm, 2.7 µm particle size, equipped with a HILIC guard column. The mobile phases were acetonitrile and 20 mM Mouse partial carotid ligation and RNA isolation and qRT-PCR. All animal − ammonium acetate (pH 9.1) at a flow rate of 450 µl min 1. Column temperature procedures were approved by the Animal Care and Use Committee at Emory was set to 40 °C. The injection volume was 2.5 µl. The gradient started with 85% University. Mice were anesthetized with 3.5% isoflurane initially and then anes- acetonitrile. Analyst 1.6.2 and MultiQuant 3.0 (Sciex, Darmstadt, Germany) were thesia was maintained with 1.5−2% during the entire procedure. Partial carotid used for data acquisition and analysis, respectively. ligation surgery was performed on the left carotid artery. Briefly, the LCA bifur- cation was exposed by blunt dissection and three of four caudal LCA branches (left external carotid, internal carotid, and occipital arteries) were ligated with 6–0 silk Nucleoside measurement by mass spectrometry. HAEC were lysed and cen- sutures, leaving the superior thyroid artery patent. The contralateral RCA was left trifuged for amino acid profiling. Additionally, cell culture supernatant was col- intact as an internal control. Mice were monitored post-surgery and were allowed − lected and centrifuged for 10 min at 17,000 × g. 200 µl of samples were analyzed by to recover. Following surgery, analgesic buprenorphine (0.1 mg kg 1) was admi- liquid chromatography-tandem mass spectrometry (LC-MS/MS). The LC-MS/MS nistrated. Post procedure, d-flow in the LCA of all animals was confirmed by system consisted of an Agilent 1260 Series binary pump (Agilent Technologies) ultrasonography to verify the success of partial ligation surgery. and a triple quadrupole mass spectrometer 5500 QTRAP (Sciex). Calibration was After 48 h of partial carotid ligation surgery, endothelial-enriched RNA was done using the following standard substances: Adenosine (Sigma-Aldrich, Cat# collected from the carotids by flushing the lumen quickly with Qiazol. Briefly, LCA A9251), guanosine (Sigma-Aldrich, Cat# G6752), cytidine (Sigma-Aldrich, Cat# and RCA were quickly flushed with 150 μl of QIAzol lysis reagent (Qiagen) using 13 C4654), and uridine (Sigma-Aldrich, Cat# U3750). C5-adenosine (Alsachim, 29G insulin syringe into a microfuge tube. The eluate was then used for total 13 13 Cat# C2291), C5-guanosine (Alsachim, Cat# C2240), C5-cytidine (Omicron, intimal RNA isolation using the miRNeasy mini kit (Qiagen) following the 13 Cat# NUC-056), and C5-uridine (Alsachim, Cat# M436) were used as internal manufacturer’s protocol. standards. Analyst Software 1.6 (Sciex) was used for data acquisition and analysis. Total RNA was polyadenylated and reverse transcribed for use in a two-step The intensity of measured nucleosides was normalized to internal standards and qPCR setup using High-capacity cDNA synthesis kit (ABI) and using Brilliant II protein content of cell lysate pellets for intracellular nucleoside measurement and SYBR Green QPCR Master Mix (Stratagene) with custom-designed primers on a to intracellular RNA content for extracellular nucleoside measurement. Real-Time PCR System (StepOne Plus, Applied Biosystems). Fold changes between

NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications 15 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0 endothelial enriched RNAs from LCA and RCA were determined for all target 0.1% SDS as well as protease and phosphatase inhibitors. Proteins were then − genes using the ΔΔCt method. Initial quality control for endothelial-enrichment of precipitated in acetone (4/1 v v 1) overnight at −80 °C. Following centrifugation the intimal RNA extracted was determined by qPCR for endothelial markers gene (16,000 × g, 15 min, 4 °C) the pellets were resuspended in ice-cold RIPA buffer − (Pcam1) and non-endothelial marker gene, Acta2 (smooth muscle cell marker) and containing 1% SDS and protease and phosphatase inhibitors. Samples (1 mg ml 1) Cd11b (leukocyte marker gene). We also tested the expression of well-known flow- were passed through desalting columns (Thermo Scientific) and the proteins sensitive genes, such as Klf2 and Klf4. All samples that passed our initial quality recovered were used for subsequent evaluation. control check were used for subsequent qPCR analysis. Statistics for wet-laboratory experiments. For wet-laboratory experiments, a Zebrafish experiments. All experimental procedures on animals were approved group size of n = 6 was chosen for most of the cell functional assays due to their by the local government authority Regierungspräsidium Karlsruhe (license no.: 35- larger variability and on the basis of previous experiences. For more accurate 9185.64) and carried out in accordance with the approved guidelines. Embryos of methods or for supportive data or when similar experiments were carried out in the Tg(fli1:EGFP)y1 line were raised and staged while kept in E3 medium (5 mM different subgroups samples sizes for n = 3 to 4 were considered sufficient. A total – NaCl, 0.17 mM KCl, 0.33 mM CaCl2,5 10% methylene blue) at 28.5 °C with or of four different batches of HUVEC was used throughout the study. Unless without 0.003% 1-phenyl-2-thiourea (Sigma) to suppress pigmentation and staged otherwise indicated, data are given as mean ± standard error of the mean. Calcu- according to somite number or hours post-fertilization (hpf). The experimental lations were performed with Prism 5.0 or BiAS.10.12. The latter was also used to groups were not blinded and all relevant data are available from the authors. test for normal distribution and similarity of variance. In the case of multiple Morpholinos (Gene Tools) were diluted in 0.1 M KCl and injected through the testing, Bonferroni correction was applied. For multiple group comparisons, ana- chorion of one-cell or two-cell stage embryos. Morpholino mhfd2 (5′- lysis of variance followed by post-hoc testing was performed (ANOVA with TGTAATAGAGAGTGTCTTACCAACT-3′) or standard control morpholino (5′- Bonferroni for normally distributed data and ANOVA with Newman-Keuls test for CCTCTTACCTCAGTTACAATTTATA -3′) were used and dose escalation studies non-normal distributions). Individual statistics of dependent samples were per- were performed to determine submaximal morpholino concentrations. formed by paired t test, of unpaired samples by unpaired t test, and, if not normally Knockdown was confirmed by RT-PCR with the primers 5′- distributed, by Mann–Whitney test. p values of <0.05 were considered as sig- GCGATTTAGCCGTTTGTGAG-3′ and 5′-TCAAGATGGTCTCGCTGCTG-3′ nificant. Unless otherwise indicated, n indicates the number of individual experi- for mthfd2 and 5′-ACGGTCAGGTCATCACCATC-3′ and 5′- ments. Calculations of cohort size for animal experiments were based on an alpha- TGGATACCGCAAGATTCCAT-3′ for β-actin. PCR was conducted at 95 °C for 3 error of 0.05, beta of 0.2 and a relative difference of 0.3. According to RRR prin- min (95 °C for 30 s, 60 °C for 30 s, 72 °C for 30 s)×32 cycles and 72 °C for 5 min and ciples, experiments were terminated either when significance was reached or when PCR products were loaded on an agarose gel. OxPAPC was diluted in 0.1% BSA/ there was obviously no effect. Assignment to treatment groups in animal experi- PBS and injected in the one-cell stage66. Tg(fli1:EGFP)y1 embryos were manually ments was based on random selection of the animals. Sham and intervention dechorionated and anesthetized with 0.05% tricaine (Sigma). Morphological studies were also performed side by side and not consecutively. Blinding was not analysis of vessels was performed using a CTR 6000 microscope (Leica) or a TCS performed. SP5 system (Leica). For quantitative morphological analysis the number of intact and partial normal intersegmental vessels (ISV) and dorsal longitudinal Data availability. The validation data set (RNA sequencing of siRNA control and anastomotic vessel (DLAV) connections between the investigated ISVs in the trunk siRNA MTHFD2 in HAEC) has been deposited in GEO and is accessible with the vasculature was determined at 72 hpf. Seventeen consecutive ISVs and 16 DLAV accession code GSE100261 at (https://www.ncbi.nlm.nih.gov/geo/). The Bayesian connections per embryo were analyzed for the anterior part between head and anus control and oxPAPC networks are available in the supplement (Supplementary starting at the sixth ISV. The number of embryos per experimental conditions was Data 1,2). The Bayesian network reconstruction methods are implemented in the used as previously described67. Results are given as mean number of vessels per – fi software suite RIMBANET (Reconstructing Integrative Molecular BAyesian embryo ± SE. For RT-qPCR analysis of mthfd2,4 5 zebra sh embryos were pooled NETworks)68 which is available at (http://research.mssm.edu/integrative-network- per sample and homogenized in RNA-Lysis buffer (Bio&Sell) using a canula. RNA biology/RIMBANET/RIMBANET_overview.html). The gene expression data of isolation and RT-qPCR was conducted as described above for HAEC. HAECs are described in Romanoski et al.5 and is available as the GEO data set GSE30169. The expression data were adjusted for batch effect before inputting into HDL isolation. Samples were collected according to the study approved by the differential connectivity analysis and Bayesian network constructions. The HAECs ethics committee in Zurich (Kantonale Ethik-Kommission Zürich (KEK), Swit- SNP genotype data are described in Romanoski et al.69. The genotype data are zerland, KEK-ZH-Nr. 2012-0321). HDL was separated from LDL and albumin via available upon request. two ultracentrifugation steps using a potassium bromide (KBr) density solution. In particular, 500 µL serum from age-matched healthy subjects and stable CAD − Received: 2 August 2017 Accepted: 11 May 2018 patients were centrifuged for 6 h after adding 500 µl KBr (d = 1.245 g cm 3) and 1 ml 0.150 M sodium chloride in 1 mM EDA solution. After removal of LDL the − remaining HDL was added to KBr (d = 1.32 g cm 3) in order to reach a final − density of 1.21 g cm 3 and was then centrifuged for 16 h at 4 °C (full protocol available on demand). The isolated HDL was purified by dialysis with 0.9% NaCl and 30 K Amicon Ultra Centrifugal Filters (Millipore). Dialyzed HDL samples were resuspended in 300 µl of 0.9% NaCl and protein concentration was determined References using Pierce BCA Protein Kit. Samples were overlaid with Argon after isolation and 1. Gimbrone, M. A. & García-Cardeña, G. 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NATURE COMMUNICATIONS | (2018) 9:2292 | DOI: 10.1038/s41467-018-04602-0 | www.nature.com/naturecommunications 17 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04602-0

Author contributions Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in R.P.B. and J.Z. supervised the project and edited the manuscript. J.H. performed most published maps and institutional affiliations. wet-laboratory experiments and wrote the manuscript. J.Z. constructed the Bayesian networks. Y.Z. computed the differential connectivity clusters. E.L. and J.H. conducted computational analyses. S.I.B. and F.S. contributed to the human atherosclerosis cohort experiments. X.L. performed zebrafish experiments. J.Hu., C.S., A.E.V., and S.K. con- Open Access This article is licensed under a Creative Commons ducted ex vivo experiments. A.K. and H.G. contributed to the HDL cohort experiments. Attribution 4.0 International License, which permits use, sharing, M.S.L., B.P., F.R., J.A.O., I.J., C.F., S.Z., D.N., D.T., Y.S., G.G., J.K., H.J., U.L., and I.F. adaptation, distribution and reproduction in any medium or format, as long as you give designed or conducted in vitro experiments. C.E.R., X.Y., and A.J.L. contributed to the appropriate credit to the original author(s) and the source, provide a link to the Creative HAEC data sets underlying the networks. All authors participated in editing the Commons license, and indicate if changes were made. The images or other third party manuscript. material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the Additional information article’s Creative Commons license and your intended use is not permitted by statutory Supplementary Information accompanies this paper at https://doi.org/10.1038/s41467- regulation or exceeds the permitted use, you will need to obtain permission directly from 018-04602-0. the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. Competing interests: The authors declare no competing interests. © The Author(s) 2018 Reprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/

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