Succinate dehydrogenase/complex II is critical for metabolic and epigenetic regulation of T cell proliferation and inflammation

Succinate dehydrogenase/complex II is critical for metabolic and epigenetic regulation of T cell proliferation and inflammation Xuyong Chen1, Benjamin Sunkel1, Meng Wang1, Siwen Kang1, Tingting Wang1, JN Rashida Gnanaprakasam1, Lingling Liu1, Teresa A. Cassel2, David A. Scott3, Ana M. Muñoz-Cabello4, Jose Lopez-Barneo4, Jun Yang5, Andrew N. Lane2, Gang Xin6, Benjamin Stanton1,*, Teresa W.-M. Fan2,*, Ruoning Wang1,* 1Center for Childhood Cancer & Blood Diseases, Hematology/Oncology & BMT, Abigail Wexner Research Institute at Nationwide Children's Hospital, The Ohio State University, Columbus, OH, USA. 2Center for Environmental and Systems Biochemistry, Dept. of Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, Lexington, KY, USA. 3Cancer Metabolism Core, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA. 4Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario "Virgen del Rocío"/CSIC/ Universidad de Sevilla, Spain. 5Department of Surgery, St Jude Children’s Research Hospital, Memphis, TN, USA. 6Department of Microbial Infection and Immunity, The Ohio State University, Columbus, OH, USA. Abstract Effective T cell-mediated immune responses require the proper allocation of metabolic resources to sustain growth, proliferation, and cytokine production. Epigenetic control of the genome also governs T cell transcriptome and T cell lineage commitment and maintenance. Cellular metabolic programs interact with epigenetic regulation by providing substrates for covalent modifications of chromatin. By employing complementary genetic, epigenetic, and metabolic approaches, we revealed that tricarboxylic acid (TCA) cycle flux fueled biosynthetic processes while controlling the ratio of succinate/α-ketoglutarate(α-KG) to modulate the activities of dioxygenases that are critical for driving T cell inflammation. In contrast to cancer cells, where succinate dehydrogenase (SDH)/complex II inactivation drives cell transformation and growth, SDH/complex II deficiency in T cells caused proliferation and survival defects when the TCA cycle was truncated, blocking carbon flux to support nucleosides biosynthesis. Replenishing the intracellular nucleoside pool *Correspondence should be addressed to: Ruoning Wang, Phone: 614-335-2980; Fax: 614-722-5895. [email protected]g; Teresa W.-M. Fan, Phone: 858-218-1028, Fax: 859-257-1307. [email protected]; Benjamin Stanton, Phone: 614-355-2691; Fax: 614-722-5895. [email protected]g;. Author contributions: R. Wang conceptualized and supervised this work. X.C. carried out most of the experiments. B.S., B.S., and M.W. performed and analyzed the CD4 T cells ATAC seq and RNA seq data. S.K., T.W., J.R.G., L.L., T.A.C., D.A.S., Y.Y., A.N.L., and G.X. were involved in data collection, analysis, and review. B.S., and T.W.F., provided conceptual input into the study development. A.M.MC. and J.LB provided some experimental animals. X.C., B.S., A.N.L., T.W.F., and R. Wang wrote the manuscript. All authors discussed the results and provided feedback on the manuscript. Competing interests: All other authors declare no conflict of interest. HHS Public Access Author manuscript Sci Immunol . Author manuscript; available in PMC 2022 October 29. Published in final edited form as: Sci Immunol . 2022 April 29; 7(70): eabm8161. doi:10.1126/sciimmunol.abm8161. Author Manuscript Author Manuscript Author Manuscript Author Manuscript partially relieved the dependence of T cells on SDH/complex II for proliferation and survival. SDH deficiency induced a pro-inflammatory gene signature in T cells and promoted T helper 1 and T helper 17 lineage differentiation. An increasing succinate/α-KG ratio in SDH deficient T cells promoted inflammation by changing the pattern of the transcriptional and chromatinaccessibility signatures and consequentially increasing the expression of the transcription factor, PR domain zinc finger protein 1. Collectively, our studies revealed a role of SDH/complex II in allocating carbon resources for anabolic processes and epigenetic regulation in T cell proliferation and inflammation. One Sentence Summary The loss of SDH/complex II function blocks cell proliferation but enhances inflammation in T cells. Introduction T cell activation engages glycolysis, the pentose phosphate pathway (PPP), and the tricarboxylic acid (TCA) cycle to prepare T cells for growth, differentiation, and immune defense (1-3). This conversion is reminiscent of the characteristic metabolic switch during the transformation of normal cells to cancer cells (4, 5). In parallel, T cell activation is accompanied by a dynamic remodeling of chromatin accessibility and DNA modifications, which determine the transcriptional status of lineage-specifying genes. Comparative studies reveal epigenetic patterns in accessible, poised, and silenced gene loci in different CD4 subsets (6-8). Mapped permissive and repressive epigenetic modifications in lineage-restricting transcription factors and lineage-specific cytokine genes indicate that such a bivalent epigenetic state is critical for T cell lineage commitment (8-10). As such, a dynamic epigenetic regulation allows progeny cells to maintain lineage-specific transcription programs while retaining some level of plasticity in response to environmental cues. Also, central carbon metabolism allocates carbon inputs to metabolites that are substrates, antagonists, and cofactors of epigenetic-modifying enzymes. Thus, central carbon metabolism is instrumental in establishing and maintaining the epigenetic landscape for cell fate determination. However, how and which metabolic pathways control the epigenome for the proliferation and differentiation of Teff cells still remains elusive. While an essential function of the TCA cycle is to sustain the oxidative carbon flux to meet energy consumption needs, the TCA cycle also coordinates the carbon input (anaplerosis) and carbon output (cataplerosis) to ensure biosynthetic activities and epigenetic regulation (11-13). Specifically, α-ketoglutarate (α-KG), an intermediate of the TCA cycle, is an essential co-substrate of α-KG dependent dioxygenases such as specific histone and DNA demethylases. In contrast, succinate and fumarate are potent inhibitors of these enzymes (14). Therefore, the ratio changes of these metabolites can impact gene transcription through epigenetic mechanisms (15-17). Succinate dehydrogenase (SDH)/complex II consists of four subunits (SDHA-D) that function in both the TCA cycle and the electron transportation chain (ETC). Its enzymatic activities that convert succinate to fumarate are coupled with reducing FAD to FADH2 and transferring an electron (complex II) into the ETC. Thus, SDH -dependent metabolic reaction represents a critical branch point in the TCA cycle. SDH is Chen et al. Page 2 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript also a tumor-suppressor since inactivating SDH subunits leads to a spectrum of hereditary tumors, suggesting that inactivating this enzyme can confer survival and proliferation advantages to tumor cells (18, 19). As activated T cells share metabolic characteristics with tumor cells (1, 20), we sought to investigate the role of SDH in T cells. Here, we reported that the TCA cycle enzyme SDH was indispensable for driving T cell proliferation by funneling carbon to support anabolic processes. In addition, the TCA cycle flux was constricted based on the availability of succinate that promotes the expression of pro-inflammatory genes through changing the T cell epigenome. Our findings implicated a role of the SDH/complex II in coupling the central carbon metabolism to epigenetic regulation to regulate T cell proliferation and inflammation coordinately. Results SDHB is required for T cell proliferation and survival Loss-of-function mutations in SDH lead to a spectrum of hereditary tumors, suggesting that the resulting truncated TCA cycle can confer survival and proliferation advantages to tumor cells (18, 19). Active T cells share metabolic characteristics with tumor cells and, therefore, may survive and proliferate in the absence of SDH activities (21). The critical functions of the TCA cycle include producing energy through coupling with the oxidative phosphorylation and generating biosynthetic precursors through cataplerosis (11). Accordingly, activated T cells could rapidly incorporate glucoseand glutamine-derived carbons into the TCA cycle metabolites and amino acids, indicating a robust TCA cycle coupled with anaplerosis and cataplerosis (Fig. S1A-C). SDH inhibitors with distinct modes of inhibition (22, 23) significantly suppressed proliferation and decreased cell viabilities after T cells activation (Fig. S2A-D). To further illustrate the role of SDH in T cells, we generated a T cell-specific SDHB knockout mouse strain ( SDHB cKO) by crossing the SDHBfl mouse strain with the CD4-Cre mouse strain. qPCR and immune blot (IB) analyses validated the deletion of SDHB (Fig. 1A), and SDH ablation resulted in a partially truncated TCA cycle, as evidenced by the accumulation of succinate and reduction of fumarate (Fig. 1B). While SDHB deletion did not result in any defects in T cell development in the thymus, it did reduce the percentage of T cells, particularly CD8 T cells, in the spleen and lymph node (Fig. S3A). In addition, the percentage of naturally occurring interferon-γ (IFN-γ) producing, interleukin-17 (IL-17) producing, and Foxp3+ CD4+ T cells were comparable in both wild-type (WT) and SDHB cKO mice (Fig. S3B). SDHB deletion in T cells significantly delayed cell cycle progression from G0/1 to S phase (Fig. 1C), suppressed proliferation ( Fig.1D ), induced more cell death and reduced cell numbers (Fig. 1E-F, S3C), which were associated with moderately reduced cell surface activation markers (Fig. S3D), cell size (Fig. S3E), and protein content (Fig. S3F). To assess the impact of ablating SDHB on CD4+ T cells in vivo , we first employed a well-established competitive homeostatic proliferation assay to determine the ratio and carboxyfluorescein succinimidyl ester (CFSE) dilution pattern of purified WT (Thy1.1+) or SDHB cKO(Thy1.2+) CD4+ T cells in a lymphopenic host ( Rag−/− ). Both the ratio between wild type (WT ) and SDHB cKO CD4+ T cells and CFSE dilution patterns suggested that Chen et al. Page 3 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript the loss of SDHB dampens T cell proliferation in vivo (Fig.1G, S3G and S4A). Next, we measured antigen-specific, TCR-dependent proliferation of WT or SDHB cKO CD4+ T cells. We crossed Thy1.1 and CD4-Cre, SDHBfl mice with OT-II transgenic mice to generate WT( Thy1.1+ ) and SDHB cKO(Thy1.2+) donor OT-II strains in CD45.2+ background. We then adoptively transferred CFSE labeled WT and SDHB cKO CD4+ T cell into CD45.1+ mice immunized with chicken ovalbumin (OVA323-339). Consistent with the homeostatic proliferation results, SDHB cKO OT-II specific CD4+ T cells displayed a significant proliferation defect in an antigen-specific manner after immunization (Fig. 1H, S3H and S4B). Experimental autoimmune encephalomyelitis (EAE), an inflammatory demyelinating disease model, is induced by active immunization with myelin-oligodendrocyte-glycoprotein (MOG) (Fig. 1I). We used this well-characterized system to investigate the in vivo CD4+ T cell response in SDHB cKO mice. In line with our homeostatic and antigen-specific proliferation results, the genetic deletion of SDHB in T cells protected the pathogenic progression of mice (Fig. 1I) and dramatically reduced leukocyte infiltration (Fig. 1J), indicating that the dominant phenotype of SDH-deficient T cells in this model was the proliferation defect. Collectively, these findings suggested that ablating SDH/complex II activities significantly dampened T cell proliferation and survival in vitro and in vivo . SDH inactivation decouples the TCA cycle from nucleoside biosynthesis While an essential function of the TCA cycle is to sustain the oxidative carbon flux to meet energy consumption needs, the metabolic flux via the TCA cycle is also critical for carbon allocation, ensuring that biosynthetic precursors production is coupled with nutrient catabolism (11-12). Activated SDHB cKO T cells consistently displayed lower catabolic activities, such as glycolysis, pentose phosphate pathway (PPP), glutamine oxidation, but not fatty acid oxidation (FAO) as compared with WT active T cells (Fig. 2A-D). Since glutamine is a major carbon source for replenishing the TCA cycle intermediate metabolite α-ketoglutarate (α-kg) in T cells after activation (24), we supplied 13C5-glutamine as a metabolic tracer in T cell culture media and followed 13C incorporation into downstream metabolites in T cells after activation. The 13C4 isotopologue of succinate was accumulated, but the corresponding 13C4 or 3C3 isotopologues of downstream metabolites including fumarate, malate, aspartate, and pyrimidine nucleotides were significantly reduced in activated SDHB cKO T cells as compared with activated WT T cells (Fig. 2E). SDHB deficiency reduced the level of intracellular aspartate (Fig. 2E), which is produced from the TCA cycle metabolite (oxaloacetate) and consequently utilized for nucleotide and DNA/RNA biosynthesis (11-12). Notably, the incorporation of carbon from 14C-glutamine into RNA and DNA was significantly suppressed in activated SDHB cKO T cells as compared with activated WT T cells (Fig. 2F). Metabolite profiling also revealed a global decrease of intracellular pyrimidine nucleotides, purine nucleotides, and their precursors in activated SDHB cKO T cells (Fig. 2G). Finally, the overall DNA/RNA content was lower in SDHB cKO T cells than WT T cells after activation (Fig. 2H). Collectively, our metabolic experiments have shown that the carbon flux from glutamine to the TCA cycle intermediate metabolites, nucleotides and DNA/RNA biosynthesis was dampened in the absence of SDH/ complex II activity. Chen et al. Page 4 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Nucleosides supplementation partially compensates for the loss of de novo biosynthesis of nucleotides in SDHB cKO T cells We then sought to determine the importance of SDH in directing TCA cycle carbon flow to nucleotide biosynthesis for supporting T cell proliferation. Since cells could directly utilize nucleosides through salvage pathway, we reasoned that providing nucleosides could bypass the block in de novo synthesis and consequently overcome some of the T cell defects caused by SDHB deficiency. Indeed, supplementation with a mixture of nucleosides (adenosine, uridine, guanosine, thymidine, cytidine, inosine) partially restored the viability and proliferation of SDHB cKO T cells after activation (Fig. 3A-D), which was accompanied by partial restoration of DNA/RNA content (Fig. 3E) and promoted cell cycle progression from G0/1 to S phase (Fig. 3F). Nucleosides supplement did not affect WT cells growth and proliferation (Fig. 3A-D). In addition, adding inosine together with pyrimidines (thymidine, cytidine, and uridine) maximized the rescue effect (Fig. 3G-J), demonstrating the importance of SDH in supporting both purine and pyrimidine biosynthesis. Nucleotide pool imbalance can cause DNA damage and, consequently, induce apoptosis (25). In support of this concept, SDHB deletion led to high levels of DNA damage marker (phosphor-histone H2AX), and nucleosides supplementation reversed this effect (Fig. S5A-B). Accordingly, the pan-caspase inhibitor (QVD) enhanced the cell viability but not the proliferation of SDHB cKO T cells (Fig. S5C-E). The combination of nucleosides supplementation and QVD further enhanced the viability but not the proliferation of SDHB cKO T cells (Fig. S5C-E). A defective SDH/complex II can increase ROS production (26). However, we only observed a moderate induction of mitochondrial ROS in SDHB cKO T cells (Fig. S5F). ROS scavengers failed to rescue cell viability and proliferation defects in SDHB cKO T cells (Fig. S5G-I). To ensure no phenotypic discrepancies between genetic modulation of different subunits of SDH in T cells, we generated a T cell-specific SDHD knockout strain ( SDHD cKO) by crossing CD4-Cre mice with previously reported SDHDfl mice (27). Similar to the effect of SDHB deletion in T cells, SDHD deletion reduced the percentage of T cells in the spleen and lymph node without causing defects in T cell development in the thymus (Fig. S6A-B). SDHD deletion significantly suppressed proliferation and caused more death after T cells activation, which could be partially reversed by nucleosides supplementation (Fig. S6C-F). Next, we examined the effect of SDH deficiency on T cell survival and proliferation under polarization conditions. Both SDHB and SDHD deficiency resulted in cell survival and proliferation defects in T helper 1 (TH1) (Fig. S7 A-B) and T helper 17 (TH17) (Fig. S7 C-D) polarization conditions. Together, our data suggested that a crucial role of the TCA cycle in supporting T cell proliferation was to allocate carbon for nucleotides biosynthesis (Fig. S7E). SDH inactivation results in a pro-inflammatory gene signature in T cells after activation To gain more mechanistic insights into the effects of SDHB deletion on T cells, we performed RNA-seq in activated WT and SDHB cKO T cells, which revealed an enriched pro-inflammatory gene signature in SDHB cKO T cells after activation (Fig. 4A-C). Active SDHB cKO T cells, but not naïve, expressed higher levels of four representative proChen et al. Page 5 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript inflammatory genes, including Il17a , Il17f , Ifng , and Il22, than WT T cells, indicating that TCR activation is required to achieve an enriched pro-inflammatory gene signature in SDHB cKO T cells (Fig. 4D). Consistent with gene expression data, the culture media collected from SDHB cKO T cells contained significantly higher levels of pro-inflammatory cytokines than the culture media collected from WT T cells (Fig. S8A). Nucleosides supplementation, which could partially rescue cell proliferation and survival (Fig. 3A-D), failed to reduce the pro-inflammatory cytokine expression in SDHB cKO T cells (Fig. 4E). Also, the culture media collected from SDHB cKO T cells could not increase pro-inflammatory gene expression in WT T cells (Fig. 4F). Thus, a cell-intrinsic mechanism that is unrelated to changes in proliferation and survival or secretory molecules was responsible for the pro-inflammatory gene signature in SDHB cKO T cells after activation. The increasing intracellular succinate/α-KG ratio promotes the expression of proinflammatory genes in SDHB cKO T cells after activation SDHB deficiency reciprocally increased the level of succinate while reducing α-KG in T cells after activation (Fig. S8B). Such an increased succinate/α-KG ratio suppressed the enzymatic activities of the dioxygenase family, impacting the hypoxia signaling response and DNA/histone methylation pattern (Fig. 5A), both of which may lead to a proinflammatory response (28-30). Correspondingly, cell-permeable succinate (22) increased succinate/α-KG ratio (Fig. S8C) and partially mimicked the effect of SDHB-deficiency on upregulating pro-inflammatory genes in WT T cells after activation (Fig. 5B). Conversely, cell-permeable α-KG (dimethylα-KG) decreased the succinate/α-KG ratio (Fig. S8C) and reduced the level of pro-inflammatory genes in SDHB cKO T cells after activation (Fig. 5C). Similarly, a glutamate dehydrogenase inhibitor (R162), which could reduce glutamine-derived anaplerotic flux to attenuate succinate buildup, decreased the expression of pro-inflammatory genes in SDHB cKO T cells after activation (Fig. 5D). Finally, SDHD deficiency phenocopied SDHB deficiency in inducing pro-inflammatory gene expression, which was reversed by cell-permeable α-KG (Fig. S8D). Next, accessed the effects of changing the succinate/α-KG ratio on CD4+ T cell differentiation. The succinate/α-KG ratio in proinflammatory T cell lineages (TH1 and TH17) was higher than either uncommitted lineage (TH0) or anti-inflammatory lineage (iTreg) (Fig. S8E), indicating that increasing the succinate/α-KG ratio might promote TH1 and TH17 differentiation. Indeed, cell-permeable succinate enhanced pro-inflammatory TH1 and TH17 cell differentiation, which could be reversed by cell-permeable α-KG (Fig. 5E-F). Similarly, cell-permeable 2-hydroxyglutarate (L-octyl-L2HG) that increased intracellular 2-HG levels to antagonize α-KG dependent dioxygenases (31) enhanced TH1 and TH17 differentiation. Cell-permeable α-KG could partially reverse the effect of 2-HG on T cell differentiation (Fig. S9A-B). SDHB cKO T cells failed to proliferate and could not generate IFN-γ+ CD4+ T cells under TH1 polarization conditions or IL-17+ CD4+ T cells under TH17 polarization conditions (Fig. S9C). These results are in line with previous observations that cell proliferation is required to achieve optimized T cell polarization (32). Genomic deletion and RNA depletion of SDHB require a specific time after Cre activation. Also, the protein half-life of SDHB is around 10 hrs (33). We envisioned that a tamoxifen-inducible Cre recombinase (CreERT2) model might allow us to bypass the effect Chen et al. Page 6 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript of SDHB deficiency on T cell activation and proliferation if Cre functions during activation. Compared with WT cells, acute deletion of SDHB largely bypassed its requirement for driving cell proliferation but enhanced TH1 and TH17 differentiation (Fig. S9D-E). Cellpermeable α-KG eliminated the effects of acutely deleting SDHB on T cell differentiation (Fig. S9D-E). Using CreERT2 model, we have differentiated the role of SDH in regulating T cell activation and proliferation from its role in driving T cell differentiation. Together, our results suggested that increasing the succinate/α-KG ratio promoted pro-inflammatory gene expression and enhanced TH1 and TH17 differentiation in vitro . HIF1-α is dispensable for enhanced pro-inflammatory gene signature in SDHB cKO T cells An increased succinate/α-KG ratio suppressed enzymatic activities of the α-KG -dependent dioxygenases, which include prolyl hydroxylases, Ten-eleven translocation (TET) enzymes, and lysine demethylases, and may consequently impact inflammation via HIF-1a and/or epigenetic mechanism (Fig. 5A) (34, 35). HIF1-α plays a role in enhancing inflammation in T cells and other immune cells (36-38). To determine if HIF1-α is responsible for upregulating pro-inflammatory genes, we generated a T cell-specific SDHB and HIF1-α double knockout (dKO) strain by crossing the HIF1-αfl with CD4-Cre, SDHBfl strain. HIF1-α/SDHB dKO T cells displayed comparable phenotypes in T cell development, cell survival and proliferation compared with SDHB cKO T cells after activation (Fig. S10A-F). Pro-inflammatory gene expression was not reduced in HIF1-α/SDHB dKO T cells compared to SDHB cKO T cells after activation (Fig. S10G). Conversely, cell-permeable succinate could enhance TH1 and TH17 cell differentiation in a HIF1-α independent manner (Fig. S11A-B). Collectively, our results suggested that HIF1-α did not mediate pro-inflammatory phenotypes in SDHB cKO T cells after activation. SDHB deficiency promotes a pro-inflammatory gene signature through regulating chromatin accessibility and pro-inflammatory transcription factors Next, we measured succinate, α-KG, DNA, and histone methylation levels in WT and SDHB cKO naïve T cells. Compared with the WT T cells, the SDHB cKO naïve T cells contained a higher level of succinate but not α-KG than WT T cells (Fig. S12A). In contrast to control T cells, the SDHB and SDHD cKO T cells or T cells treated with cell-permeable succinate displayed higher levels of 5-methylcytosine (5-mC) and histone methylations in several key lysine residues that are often associated with transcriptional activities (39, 40) (Fig. S12 B-F). We reasoned that the DNA and histone methylations might work in concert to reprogram an epigenetic state via modulating chromatin accessibility, consequently leading to induction of inflammatory genes in activated T cells with succinate accumulation. To test this hypothesis, we examined the genome-wide transcriptomes and chromatinaccessibility by performing RNAseq and Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) in parallel in activated CD4+ WT and SDHB cKO T cells. Indeed, ATAC-seq revealed distinctive patterns of DNA accessibility that were associated with genomic loci of genes involved in T cell activation and inflammation in activated WT and SDHB cKO CD4+ T cells (Fig. 6A-B). After integrating the RNA-seq and ATAC-seq data, we found that the induction of pro-inflammatory genes and transcription factors known to regulate T cell differentiation and inflammation were concordant with the increase in chromatin accessibility of these genes in the activated SDHB cKO CD4+ T cells Chen et al. Page 7 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript (Fig. 6C). PR domain zinc finger protein 1 ( Prdm1 ) was among these genes with increased transcript and DNA accessibility. Prdm1 encodes B-lymphocyte-induced maturation protein (Blimp-1), a transcription factor known which is co-localized with STAT-3, p300, RORγt on the Il23r, Il17f, and Csf2 cytokine loci to regulate T cell differentiation and inflammation (41, 42). Analysis of transcriptional factor binding motifs in the differential accessibility regions revealed that Prdm1 was one of the top transcription factors that may gain increased chromatin accessibility at the regulatory elements of the T cell activation and inflammation genes in the activated SDHB cKO CD4+ T cells (Fig. 6D). In addition, ATAC-seq analysis of T cells of WT and SDHB cKO under naïve conditions also showed a significant motif enrichment of Prdm1 in the differential accessibility regions, portending the increased transcription of its target gene upon stimulation (Fig. S12G-H). We, therefore, hypothesized that transcription factors, such as Prdm1 that showed concordant increases in both their expression level and DNA accessibility, may play a key role in driving inflammation in SDHB cKO CD4+ T cells. Among a panel of transcription factors that displayed enhanced DNA accessibility in either activated or naïve SDHB cKO CD4+ T cells (Fig. 6D and S12G), Prdm1 ’s expression was enhanced by cell-permeable succinate and SDHB deletion (Fig. 6E-G). Moreover, cell-permeable α-KG reduced the expression of Prdm1 in SDHB cKO CD4+ T cells (Fig. 6E-F). Next, we employed a CRISPR-Cas9 approach to testing if Prdm1 was required for regulating the expression of inflammatory genes and T cell differentiation in the context of SDHB deletion and succinate accumulation. Indeed, the deletion of Prdm1 reduced the level of pro-inflammatory genes Il17a , Il17f , Ifng , but not Il22 in SDHB cKO T cells (Fig. 7A-B). Moreover, deletion of Prdm1 eliminated the effect of cell-permeable succinate on promoting TH1 and TH17 differentiation (Fig. 7C-D). Collectively, these results suggested that TCA cycle metabolites (succinate/α-KG) regulated T cell inflammation through a coordinated epigenetic and transcriptional control of inflammatory genes. Changing the succinate/α-KG ratio regulates Prdm1/Blimp-1 expression and T cell differentiation through an epigenetic mechanism Next, we assessed the effect of modulating the succinate/α-KG ratio on Prdm1 /Blimp-1 expression and T cell differentiation. Cell-permeable α-KG moderately reduced Prdm1 / Blimp-1 expression under TH1 and TH17 polarization conditions (Fig. S13A-B). Similarly, treating T cells with a competitive inhibitor of SDH (NV161) (22, 43) in a dose without significantly compromising cell proliferation (Fig. S13C) enhanced TH1 and TH17 differentiation and Prdm1 /Blimp-1 expression (Fig. S13D-G). In line with the effect of acutely deleting SDHB on T cell differentiation (Fig. S9D-E), acutely deleting SDHB increased Prdm1 /Blimp-1 expression under TH1 and TH17 polarization conditions, which could be reversed by cell-permeable α-KG (Fig. S13H-I). We reasoned that H3K4me3 might play a role in regulating Prdm1 . Indeed, chromatin immunoprecipitation (ChIP)-qPCR revealed that the H3K4me3 signal was higher in SDHB cKO than WT CD4+ T cells (Fig. S14A). The state of H3K4me3 is determined by the lysine-specific demethylase 5 (KDM5) family and the histone methyltransferase, mixed-lineage leukemia 1 (MLL1) (44, 45). Inhibiting KDM5 by C70 (46) increased the level of H3K4me3, accompanied by increased expression of Prdm1 in WT CD4+ T cells following activation (Fig. S14 B-D). Chen et al. Page 8 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Conversely, inhibiting MLL1 by MM102 (47) reduced the level of H3K4me3 and the expression of Prdm1 in SDHB cKO CD4+ T cells (Fig. S14B and S14E-F). Moreover, inhibiting KDM5 by C70 increased the level of H3K4me3 under TH1 and TH17 polarization conditions, accompanied by enhanced differentiation (Fig. S14G-J). Conversely, inhibiting MLL1 by MM102 reversed the effects of acutely deleting SDHB on H3K4me3 during TH1 and TH17 differentiation (Fig. S15A-H). Together, these results indicated that changing the succinate/α-KG ratio might regulate Prdm1 expression and T cell differentiation through modulating the level of H3K4me3. Discussion We revealed a critical role of SDH/complex II in allocating carbon resources for anabolic processes and epigenetic regulation in T cell proliferation and inflammation. Rapidly evolving pathogens impose selective pressures on host immune cells' metabolic fitness and metabolic plasticity, allowing immune cells to maintain homeostasis while remaining ready to mount rapid responses under diverse metabolic and immune conditions (48-51). Beyond this, the availability of specific metabolites and the pathways that process them interconnect with signaling events and epigenetic regulators in the cell, orchestrating metabolic checkpoints that influence T cell activation, differentiation, and immune function (1-3, 52-57). While the essential function of the TCA cycle is to sustain the oxidative carbon flux to meet energy consumption needs, the metabolic flux via the TCA cycle is also critical for carbon anabolism, ensuring that production of biosynthetic precursors of protein, lipids, and DNA/RNA is coupled with energy production from nutrients to sustain cell growth. Accordingly, the major role of the ETC in supporting cell proliferation is to regenerate nicotinamide adenine dinucleotide (NAD)+ and to permit aspartate synthesis in cancer cells (55, 58-60). Similarly, we found that carbon input (mainly through glutamine) to replenish TCA cycle intermediates (anaplerosis) was balanced with an output of 4-carbon intermediates from the TCA cycle to aspartate and nucleosides and nucleotides (cataplerosis) in T cells. These results suggest that active T cells share metabolic characteristics with tumor cells (1, 20). Unlike hyper-proliferative tumor cells, where inactivating the TCA cycle enzymes SDH can confer survival and proliferation advantages to tumor cells (18, 19), we found that SDHdependent steps were vital for carbon allocation via the TCA cycle in supporting anabolic processes to drive T cell proliferation. The additional genetic alterations may confer a high degree of metabolic adaptation to SDH/complex II deficient cancer cells (61, 62). Inhibiting SDH suppresses T-cell inflammation and macrophages(21, 63, 64). In contrast, we found that increasing the succinate/α-KG ratio by inhibiting SDH or providing cell-permeable metabolites promoted T cell inflammation and differentiation. Since different approaches, materials, and cell types were used and studied across our studies and previous studies, we reasoned that the combination of multiple factors, including differences in pharmacological reagents, genetic approaches, cellular and biological contexts, caused the discrepancies between our findings and previous findings. Succinate is necessary to promote inflammation during macrophage activation (65, 66). Endogenous metabolite itaconate regulates inflammatory cytokine production during Chen et al. Page 9 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript corrected for recovery of the internal standard and for 13C labeling to yield total (labeled and unlabeled) quantities in nmol per sample and then adjusted per cell number. Capillary electrophoresis–triple quadrupole/time-of-flight mass spectrometry (CE-QqQ/TOFMS) analysis—CD3+ T cells (around ~1 ×107 per sample) isolated from WT and SDHB cKO mice were activated for 30 hrs (Fig. 2G). T cells were collected by centrifugation (300 × g at 4°C for 5 min), washed twice with 5% mannitol solution (10 mL first and then 2 mL), then treated with 800 μL of methanol and vortexed for 30 sec to inactivate enzymes. The cell extract was treated with 550 μL of Milli-Q water containing internal standards (H3304-1002, Human Metabolome Technologies, inc., Tsuruoka, Japan) and vortexed for 30 sec. The extract was obtained and centrifuged at 2,300 × g and 4°C for 5 min, and then 700 μL of the upper aqueous layer was centrifugally filtered through a Millipore 5-kDa cutoff filter at 9,100 × g and 4°C for 180 min to remove proteins. For CE-MS analysis, the filtrate was centrifugally concentrated and resuspended in 50 μL of Milli-Q water. Cationic compounds were measured in the positive mode of CE-TOFMS, and anionic compounds were measured in the positive and negative modes of CE-MS/MS. Peaks detected by CE-TOFMS and CE-MS/MS were extracted using an automatic integration software (MasterHands, Keio University, Tsuruoka, Japan and MassHunter Quantitative Analysis B.04.00, Agilent Technologies, Santa Clara, CA, USA, respectively) to obtain peak information, including m/z , migration time (MT), and peak area. The peaks were annotated with putative metabolites from the HMT metabolite database based on their MTs in CE and m / z values determined by TOFMS. The tolerance range for the peak annotation was configured at ±0.5 min for MT and ±10 ppm for m/z . In addition, concentrations of metabolites were calculated by normalizing the peak area of each metabolite with respect to the area of the internal standard and by using standard curves, which were obtained by three-point calibrations. Metabolite extraction and analysis by ion chromatography-ultra high resolution-Fourier transform mass spectrometry (IC-UHR-FTMS)—CD3+ T Cells (Fig. 2E and S8B) were cultured in conditional media (glutamine-free RPMI-1640, 10%DFBS) containing 2 mM 13C5-Glutamine for 30 h. ~1 ×107 cells for each sample were collected and washed 3 times with cold PBS before being snap-frozen. Naïve CD4+ T cells were polarized under TH0, TH1, TH17, and iTreg culture for 72 h (Fig. S8E). Cells were collected and washed with cold PBS 3 times before snap freezing. The frozen cell pellets were homogenized in 60% cold CH3CN in a ball mill (Precellys24, Bertin Technologies) for denaturing proteins and optimizing extraction. Polar metabolites were extracted by the solvent partitioning method with a final CH3CN:H2O:CHCl3 (2:1.5:1, v/v) ratio, as described previously(79). The polar extracts were reconstituted in nanopure water before analysis on a Dionex ICS-5000+ ion chromatography system interfaced with a Thermo Fusion Orbitrap Tribrid mass spectrometer (Thermo Fisher Scientific) as previously described(80) using a m/z scan range of 80-700. Peak areas were integrated and exported to Excel via the Thermo TraceFinder (version 3.3) software package before natural abundance correction (81). The isotopologue distributions of metabolites were calculated as the mole fractions as previously described (82). The number of moles of each metabolite was determined by calibrating the natural abundance-corrected signal against authentic external Chen et al. Page 16 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript standards. The amount was normalized to the amount of extracted protein and is reported in nmol/mg protein. Succinate and α-KG quantification—CD4+ T cells were treated with 100μM NV118 or 10mM α-KG in a naive condition for 24 h (Fig.S8C). Cells were collected for quantifying succinate and α-KG using the succinate colorimetric assay kit (Abcam, ab204718) or α-KG assay kit (Abcam, ab83431). The optical density (OD) values were measured at 450 nm and 570 nm with a Synergy 2 microplate reader (BioTek). LEGENDplex™ Bead-Based Immunoassay—The supernatants from 36 hrs activated CD4+ T cells were collected for quantifying cytokines using LEGENDplex™ Mouse Th Cytokine Panel (13-plex) V02 kit (Cat. No 740741-V-bottom, Bio Legend, San Diego, USA). The data were collected by Novocyte (ACEA Biosciences) and analyzed using LEGENDplex™ Data Analysis Software V8.0 (BioLegend). RNA-seq analysis—For RNA sequencing analysis, total RNA was extracted using RNeasy Mini Kit (Qiagen) and treated with DNase I according to the manufacturer's instructions. After assessing the quality of total RNA using an Agilent 2100 Bioanalyzer and RNA Nanochip (Agilent Technologies), 150 ng total RNA was treated to deplete the levels of ribosomal RNA (rRNA) using target-specific oligos combined with rRNA removal beads. Following rRNA removal, mRNA was fragmented and converted into double-stranded cDNA. Adaptor-ligated cDNA was amplified by limit cycle PCR. After library quality was determined via Agilent 4200 TapeStation and quantified by KAPA qPCR, approximately 60 million paired-end 150 bp sequence reads were generated on the Illumina HiSeq 4000 platform. Quality control and adapter trimming were accomplished using the FastQC (version 0.11.3) and Trim Galore (version 0.4.0) software packages. Trimmed reads were mapped to the Genome Reference Consortium GRCm38 (mm10) murine genome assembly using TopHat2 (version 2.1.0), and feature counts were generated using HTSeq (version 0.6.1). Statistical analysis for differential expression was performed using the DESeq2 package (version 1.16.1) in R, with the default Benjamini-Hochberg p-value adjustment method. The Ingenuity Pathway Analysis (IPA) software (QIAGEN), the Gene Set Enrichment Analysis (GSEA) software (UC San Diego, BROAD Ins.), and the R Programming Language software were used to analyze gene signature and pathway enrichment. ATAC-seq analysis—ATAC-seq was performed as previously described (83) with only minor modifications. 5×104 cells per experiment were first washed with RSB buffer (10 mM Tris-HCl pH 8, 10 mM NaCl, 3 mM MgCl2) and gently permeabilized with RSB lysis buffer (10 mM Tris-HCl pH 8, 10 mM NaCl, 3 mM MgCl2, 0.1% NP-40) on ice. Cells were suspended in 50 μL of tagmentation master mix prepared from Illumina Tagment DNA TDE1 Enzyme and Buffer Kit components (#20034197), and transposition was performed for 30 minutes at 37°C. Tagmented DNA fragments were isolated using Qiagen MinElute PCR Purification columns prior to library amplification. ATAC-seq libraries were amplified with barcoded Nextera primers for 14 cycles, and excess primers were removed by size selection with AMPure XP beads. Libraries were sequenced on the HiSeq4000 Chen et al. Page 17 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript platform running in PEx150bp mode. The ENCODE ATAC-seq pipeline (https://github.com/ ENCODE-DCC/atac-seq-pipeline) with default parameters was used to process ATAC-seq data. First, reads are scanned for adaptor sequences and trimmed with cutadapt (version 2.3). Reads are then mapped to mm10 with bowtie2 (version 2.3.4.3). Properly aligned, non-mitochondrial read pairs were retained for peak calling with MACS2 (version 2.2.4). Differential ATAC peak analysis was completed using DiffBind (Bioconductor) and DESeq2 with an FDR < 0.05. Once differential peaks were called, heatmaps were generated with deeptools (version 3.3.1)(84), motif analysis was performed using HOMER (version 4.11.1) (85), and nearby genes were identified using GREAT (86). CHIP-qPCR—ChIP was performed as described previously(87). Briefly, ~107 cells were cross-linked with 1% methanol-free formaldehyde for 10 min at room temperature. The fixation was quenched by adding glycine to a final concentration of 125 mM and placed on ice for 5 minutes. Fixed cells were pelleted at 1,200 × g for 5 minutes at 4°C and resuspended in ice-cold PBS containing a protease inhibitor cocktail. Samples were sonicated with an Active Motif EpiShear probe sonicator. After sonication, a 5μL volume was aliquoted from each sample (input) and combined with 20μL TE, 1μL 10% SDS, and 1μL 20 mg/mL Proteinase K for overnight decrosslinking at 65°C. Input samples were purified using Qiagen MinElute PCR Purification columns, and chromatin fragmentation was assessed by gel electrophoresis on an E-Gel 2% EX agarose gel. The cleared chromatin solutions were immunoprecipitated with antibodies against H3K4me3 (ab8580; Abcam). The normal rabbit IgG (ab171870; Abcam) was used as a background control. Immunoprecipitated complexes were isolated with protein A Dynabeads. ChIP DNA was purified with Qiagen MinElute PCR Purification columns. The DNA was used for ChIPqPCR with specific Prdm1 PCR primers (supplemental Table 5). BIO-RAD CFX96™ RealTime PCR Detection System was used for SYBR green-based quantitative PCR. The data are presented as fold enrichment over the input control. CRISPR-Cas 9—All guide RNAs, Alt-R S.p. HIFI Cas9 Nuclease V3, and Alt-R S.p. HIFI electroporation enhancer were purchased from IDT. Mixed 60 pmol of Cas9 protein with 150 pmol of sgRNA and incubated for 20 minutes at room temperature for Cas9/RNP complex formation. Then, activated CD4+ T cells were resuspended in P4 Primary Cell buffer (Lonza) and mixed with the RNP complexes and 4 μM Electroporation Enhancer in P4 Primary Cell buffer (Lonza), transferred the cell/CRISPR mixture to the bottom hole of the wells of the Lonza nucleofector strip for electroporation by using Lonza nucleofector (Program CM137), electroporated cells were recovered in T cell culture medium for 2 h prior to activation with anti-CD3/CD28 antibodies, or under TH1 or TH17 polarization. Duplexes of two separate guides per target gene were used: Mm.Cas9. Prdm1 .1AA (ACACGCTTTGGACCCCTCAT), Mm.Cas9. Prdm1 .1AB (CATAGTGAACGACCACCCCT). Statistical analysis Statistical analysis was conducted using the GraphPad Prism software (GraphPad Software, Inc.). Unpaired two-tail Student’s t-test, multiple comparisons of one/ two-way ANOVA were used to assess differences in other experiments. P values smaller than 0.05 were Chen et al. Page 18 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript considered significant, with p < 0.05, p < 0.01, p < 0.001, and p < 0.0001 indicated as *, **, ***, and ****, respectively. Supplementary Material Refer to Web version on PubMed Central for supplementary material. Acknowledgments Funding: This work was supported by 1UO1CA232488-01 from the National Institute of Health (Cancer Moonshot program), 2R01AI114581-06, and RO1CA247941 from the National Institute of Health, V2014-001 from the V-Foundation, and 128436-RSG-15-180-01-LIB from the American Cancer Society (to RW). The Sanford Burnham Prebys Cancer Metabolism Core was supported by the SBP NCI Cancer Center Support Grant P30 CA030199. The Center for Environmental and Systems Biochemistry Core was supported by the Markey Cancer Center support grant P30CA177558. Data availability statement: The CD3+ T cells RNA-seq datasets generated for this study can be found in the GEO accession GSE184010. The CD4+ T cells RNA-seq datasets generated for this study can be found in the GEO accession GSE184743. The CD4+ T cells ATAC-seq datasets generated for this study can be found in the GEO accession GSE184742. SDHB-flox mouse strain is available from Dr. Ruoning Wang’s laboratory under a material transfer agreement with the Nationwide Children’s Hospital. All data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials. Reference and notes 1. Sena LA, Li S, Jairaman A, Prakriya M, Ezponda T, Hildeman DA, Wang CR, Schumacker PT, Licht JD, Perlman H, Bryce PJ, Chandel NS, Mitochondria are required for antigen-specific T cell activation through reactive oxygen species signaling. Immunity 38, 225–236 (2013). [PubMed: 23415911] 2. Gerriets VA, Rathmell JC, Metabolic pathways in T cell fate and function. 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(A) SDHB mRNA and protein levels of the indicated T cells were determined by qPCR and Immunoblot (n=3), *** p < 0.001, Student’s t test. (B) Metabolites of the indicated T cells were determined by CE-QqQ/TOFMS (n=3), ** p < 0.01, *** p < 0.001, Student’s t test. (C) The cell cycle profile of the indicated CD4+ T cells was analyzed by BrdU and 7AAD staining. The numbers indicate the percentage of cells in the cell cycle stage. (D) Cell proliferation of the indicated CD4+ T cells was determined by CFSE dilution. (E-F) Cell viability of the indicated CD4+ T cells was assessed by 7AAD uptake, n=3, data are representative of 3 independent experiments, n.s., not significant, *** p < 0.001, one-way ANOVA. T cells (B-F) were activated by the plate-bound anti-CD3/CD28 antibodies. (G) Chen et al. Page 25 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript are representative of 3 independent experiments, n.s., not significant, *** p < 0.001, one-way ANOVA. (F) Cell culture media from the indicated T cell groups (36 hrs after activation) were collected, mixed with fresh medium at 1:1 ratio, and then were used for culturing WT T cells for 36 hrs under activation condition (left panel), mRNA levels of indicated genes were measured by the qPCR (right panel), n=3, data are representative of 2 independent experiments, n.s., not significant, * p < 0.05, Student’s t test. Bar graphs, mean ± SEM. NS: nucleosides. T cells were activated by the plate-bound anti-CD3/CD28 antibodies. Chen et al. Page 32 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Figure 5. Increasing the intracellular succinate/α-KG ratio promotes pro-inflammatory signature in T cells after activation. (A) Schematic diagram of succinate-mediated metabolic, signaling, and epigenetic regulation of T cell proliferation and inflammation. (B) CD4+ T cells were cultured with 100μM cell permeable succinate (NV118) followed by activation as indicated in the experimental diagram (top panel), mRNA levels of indicated genes were measured by qPCR (bottom panel, n=3, data are representative of 3 independent experiments, * p < 0.05, ** p < 0.01, *** p < 0.001, student’s t test. (C) CD4+ T cells were activated for 36 hrs with or without 10mM α-KG, mRNA levels of indicated genes were measured by qPCR, n=3, data are representative of 3 independent experiments, *** p <0.001, one-way ANOVA. Chen et al. Page 33 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript (D) Schematic diagram of R162’s action and glutamine catabolism (left panel), CD4+ T cells were activated for 36 hrs with indicated treatments, mRNA levels of indicated genes were measured by the qPCR (right panel), n=3, data are representative of 2 independent experiments, *** p < 0.001, one-way ANOVA. T cells (B-D) were activated by the platebound anti-CD3/CD28 antibodies. (E-F) CD4+ T cells were polarized toward TH1 (E) and TH17 (F) lineages for 72 hrs with indicated treatments (2mM α-KG and 25μM NV118). The indicated proteins were quantified by intracellular staining by flow cytometry. Cell proliferation was determined by CFSE staining, n=3, data are representative of 3 independent experiments, * p <0.05, ** p <0.01, *** p <0.001, one-way ANOVA. Bar graphs, mean ± SEM. Chen et al. Page 34 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Figure 6. SDHB deficiency increases the level of succinate to enhance DNA accessibility and pro-inflammatory genes transcription. (A) Differential chromatin accessibility was measured by ATAC-seq in activated CD4+ T cells between indicated genotypes (n=3 replicates for each genotype), identifying 8,543 sites with accessibility gain and 1,521 sites with accessibility loss in activated SDHB cKO T cells. (B) ATAC-seq peaks with differential accessibility were linked to nearby genes, and ontology analysis was performed using GREAT. (C) Accessibility changes in differential ATAC-seq peaks were plotted against expression changes (CD4+ T cells RNAseq) in the nearby genes identified in (B), concordant changes (i.e., enhanced expression and accessibility) were observed among pro-inflammatory genes and master transcription factors mediating inflammation. (D) Motif analysis was performed on ATAC-seq peaks Chen et al. Page 35 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript showing enhanced accessibility in activated SDHB cKO CD4+ T cells. A volcano plot shows up-regulated expression of many cognate transcription factors by RNA-seq. Highlighted genes (C&D) were selected based on genes of interest. (E) mRNA levels of transcription factors in the indicated CD4+ T cells were depicted in the Heatmap, (n=3 replicates for each group). (F) CD4+ T cells were activated for 36 hrs with or without 10mM α-KG, Blimp1 protein levels were measured by intracellular staining by flow cytometry, MFI was analyzed, n=3, data are representative of 3 independent experiments, ** p <0.01, *** p <0.001, one-way ANOVA. (G) CD4+ T cells were maintained in naïve condition with 100μM NV118 for 72 hrs and then activated for 36 h, Blimp1 protein levels were measured by intracellular staining by flow cytometry, MFI was analyzed, n=3, data are representative of 3 independent experiments, ** p <0.01, student’s t test. Bar graphs, mean ± SEM. T cells were activated by the plate-bound anti-CD3/CD28 antibodies. Chen et al. Page 36 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Figure 7. Succinate-mediated Prdm1/Blimp1 expression contributes to proinflammatory signature in T cells. (A) CD4+ T cells were activated overnight, then electroporated with g Prdm1 and Cas9, cells were recovered in culture medium for 2 hrs prior to activation for 40 hrs (top panel), Blimp-1 protein levels were measured by intracellular staining by flow cytometry (bottle panel), n=3, data are representative of 2 independent experiments, **p < 0.01, one-way ANOVA. (B) CD4+ T cells were electroporated with g Prdm1 and Cas9, mRNA levels of indicated genes were determined by qPCR, n=3, data are representative of 2 independent experiments, n.s., not significant, **p < 0.01, ***p < 0.001, one-way ANOVA. (C-D) CD4+ T cells were activated overnight, then electroporated with g Prdm1 and Cas9. Cells were then polarized toward TH1 (C) and TH17 (D) lineages for 72 hrs with or without 25μM NV118. The indicated proteins were quantified by intracellular staining by flow cytometry, cell proliferation was determined by CFSE staining. n=3, data are representative Chen et al. Page 37 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript of 2 independent experiments, ***p < 0.001, one-way ANOVA. Bar graphs, mean ± SEM. T cells were activated by the plate-bound anti-CD3/CD28 antibodies. Chen et al. Page 38 Sci Immunol . Author manuscript; available in PMC 2022 October 29. Author Manuscript Author Manuscript Author Manuscript Author Manuscript