Abstract Methylation is a widely occurring modification that requires the methyl donor S-adenosylmethionine (SAM) and acts in regulation of gene expression and other processes. SAM is synthesized from methionine, which is imported or generated through the 1-carbon cycle (1CC). Alterations in 1CC function have clear effects on lifespan and stress responses, but the wide distribution of this modification has made identification of specific mechanistic links difficult. Exploiting a dynamic stress-induced transcription model, we find that two SAM synthases in Caenorhabditis elegans , SAMS-1 and SAMS-4, contribute differently to modification of H3K4me3, gene expression and survival. We find that sams-4 enhances H3K4me3 in heat shocked animals lacking sams-1 , however, sams-1 cannot compensate for sams-4 , which is required to survive heat stress. This suggests that the regulatory functions of SAM depend on its enzymatic source and that provisioning of SAM may be an important regulatory step linking 1CC function to phenotypes in aging and stress.
Emerging evidence suggests the microbiome critically influences the onset and progression of neurodegenerative diseases; however, the identity of neuroprotective bacteria and the molecular mechanisms that respond within the host remain largely unknown. We took advantage of
Methylation is a widely occurring modification that requires the methyl donor S-adenosylmethionine (SAM) and acts in regulation of gene expression and other processes. SAM is synthesized from methionine, which is imported or generated through the 1-carbon cycle (1 CC). Alterations in 1 CC function have clear effects on lifespan and stress responses, but the wide distribution of this modification has made identification of specific mechanistic links difficult. Exploiting a dynamic stress-induced transcription model, we find that two SAM synthases in Caenorhabditis elegans, SAMS-1 and SAMS-4, contribute differently to modification of H3K4me3, gene expression and survival. We find that sams-4 enhances H3K4me3 in heat shocked animals lacking sams-1, however, sams-1 cannot compensate for sams-4, which is required to survive heat stress. This suggests that the regulatory functions of SAM depend on its enzymatic source and that provisioning of SAM may be an important regulatory step linking 1 CC function to phenotypes in aging and stress.
Abstract Coordination of adaptive metabolism through cellular signaling networks and metabolic response is essential for balanced flow of energy and homeostasis. Post-translational modifications such as phosphorylation offer a rapid, efficient, and dynamic mechanism to regulate metabolic networks. Although numerous phosphorylation sites have been identified on metabolic enzymes, much remains unknown about their contribution to enzyme function and systemic metabolism. In this study, we stratify phosphorylation sites on metabolic enzymes based on their location with respect to functional and dimerization domains. Our analysis reveals that the majority of published phosphosites are on oxidoreductases, with particular enrichment of phosphotyrosine (pY) sites in proximity to binding domains for substrates, cofactors, active sites, or dimer interfaces. We identify phosphosites altered in obesity using a high fat diet (HFD) induced obesity model coupled to multiomics, and interrogate the functional impact of pY on hepatic metabolism. HFD induced dysregulation of redox homeostasis and reductive metabolism at the phosphoproteome and metabolome level in a sex-specific manner, which was reversed by supplementing with the antioxidant butylated hydroxyanisole (BHA). Partial least squares regression (PLSR) analysis identified pY sites that predict HFD or BHA induced changes of redox metabolites. We characterize predictive pY sites on glutathione S-transferase pi 1 (GSTP1), isocitrate dehydrogenase 1 (IDH1), and uridine monophosphate synthase (UMPS) using CRISPRi-rescue and stable isotope tracing. Our analysis revealed that sites on GSTP1 and UMPS inhibit enzyme activity while the pY site on IDH1 induces activity to promote reductive carboxylation. Overall, our approach provides insight into the convergence points where cellular signaling fine-tunes metabolism. Summary Statement By employing a multi-disciplinary approach we stratify structural features of phosphorylation sites on metabolic enzymes, map the systems level changes induced by obesity, identify key pathways with sex specific phosphoproteomic responses, and validate the functional role of phosphorylation sites for select enzymes.
Highlights•RQ is present in mitochondria isolated from certain mouse and human tissues•RQ carries electrons to fumarate as the electron acceptor, independently of O2 levels•The ETC can be reprogrammed to the RQ/fumarate pathway using genetic and pharmacologic tools•Reprogramming the ETC mitigates hypoxia-induced damage in vitro and in vivoSummaryUbiquinone (UQ), the only known electron carrier in the mammalian electron transport chain (ETC), preferentially delivers electrons to the terminal electron acceptor oxygen (O2). In hypoxia, ubiquinol (UQH2) diverts these electrons onto fumarate instead. Here, we identify rhodoquinone (RQ), an electron carrier detected in mitochondria purified from certain mouse and human tissues that preferentially delivers electrons to fumarate through the reversal of succinate dehydrogenase, independent of environmental O2 levels. The RQ/fumarate ETC is strictly present in vivo and is undetectable in cultured mammalian cells. Using genetic and pharmacologic tools that reprogram the ETC from the UQ/O2 to the RQ/fumarate pathway, we establish that these distinct ETCs support unique programs of mitochondrial function and that RQ confers protection upon hypoxia exposure in vitro and in vivo. Thus, in discovering the presence of RQ in mammals, we unveil a tractable therapeutic strategy that exploits flexibility in the ETC to ameliorate hypoxia-related conditions.Graphical abstract
Obesity poses a global health challenge, demanding a deeper understanding of adipose tissue (AT) and its mitochondria. This study describes the role of the mitochondrial protein Methylation-controlled J protein (MCJ/DnaJC15) in orchestrating brown adipose tissue (BAT) thermogenesis. Here we show how MCJ expression decreases during obesity, as evident in human and mouse adipose tissue samples. MCJKO mice, even without UCP1, a fundamental thermogenic protein, exhibit elevated BAT thermogenesis. Electron microscopy unveils changes in mitochondrial morphology resembling BAT activation. Proteomic analysis confirms these findings and suggests involvement of the eIF2α mediated stress response. The pivotal role of eIF2α is scrutinized by in vivo CRISPR deletion of eIF2α in MCJKO mice, abrogating thermogenesis. These findings uncover the importance of MCJ as a regulator of BAT thermogenesis, presenting it as a promising target for obesity therapy. How adipose mitochondria activity is fine-tuned in response to obesity is an active area of study. Here, the authors show that mitochondrial protein MCJ can block thermogenesis and that silencing this gene can correct obesity-related comorbidities.
Pulmonary hypertension (PH) can affect both pulmonary arterial tree and cardiac function, often leading to right heart failure and death. Despite the urgency, the lack of understanding has limited the development of effective cardiac therapeutic strategies. Our research reveals that MCJ modulates mitochondrial response to chronic hypoxia. MCJ levels elevate under hypoxic conditions, as in lungs of patients affected by COPD, mice exposed to hypoxia, and myocardium from pigs subjected to right ventricular (RV) overload. The absence of MCJ preserves RV function, safeguarding against both cardiac and lung remodeling induced by chronic hypoxia. Cardiac-specific silencing is enough to protect against cardiac dysfunction despite the adverse pulmonary remodeling. Mechanistically, the absence of MCJ triggers a protective preconditioning state mediated by the ROS/mTOR/HIF-1α axis. As a result, it preserves RV systolic function following hypoxia exposure. These discoveries provide a potential avenue to alleviate chronic hypoxia-induced PH, highlighting MCJ as a promising target against this condition.
Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Methylation is a widely occurring modification that requires the methyl donor S-adenosylmethionine (SAM) and acts in regulation of gene expression and other processes. SAM is synthesized from methionine, which is imported or generated through the 1-carbon cycle (1 CC). Alterations in 1 CC function have clear effects on lifespan and stress responses, but the wide distribution of this modification has made identification of specific mechanistic links difficult. Exploiting a dynamic stress-induced transcription model, we find that two SAM synthases in Caenorhabditis elegans, SAMS-1 and SAMS-4, contribute differently to modification of H3K4me3, gene expression and survival. We find that sams-4 enhances H3K4me3 in heat shocked animals lacking sams-1, however, sams-1 cannot compensate for sams-4, which is required to survive heat stress. This suggests that the regulatory functions of SAM depend on its enzymatic source and that provisioning of SAM may be an important regulatory step linking 1 CC function to phenotypes in aging and stress. Editor's evaluation The manuscript by Godbole et al. proposes a novel mechanism by which different S-adenosylmethionine (SAM) synthase enzymes exhibit specificity towards target sequences, establishing a layer of control over H3K4 trimethylation (H3K4me3). The authors demonstrate that the loss of two SAMs (sams-1 and sams-4) differentially impacts stress response phenotypes, histone methylation, and gene expression profiles. This work suggests a role of enzyme provisioning in selecting specific targets for epigenetic modification. https://doi.org/10.7554/eLife.79511.sa0 Decision letter Reviews on Sciety eLife's review process Introduction The 1-Carbon cycle (1 CC) is a group of interconnected pathways that link essential nutrients such as methionine, folate, and vitamin B12 to the production of nucleotides, glutathione, and S-adenosylmethionine (SAM), the major methyl donor (Ducker and Rabinowitz, 2017; Figure 1A). SAM is important for the production of polyamines and phosphatidylcholine (PC), a methylated phospholipid, and is also essential for the methylation of RNA, DNA and proteins such as histones (Mato et al., 2008). Thus, 1 CC connects nutrients with the production of a key cellular regulator of epigenetic function, SAM. Figure 1 with 3 supplements see all Download asset Open asset acquisition of H3K4me3 in heat-shocked animals. (A) Methionine intake through diet enters the 1 carbon cycle and is used by SAM synthases for the synthesis of SAM which is used by methyltransferases to add methyl moieties to proteins, nucleic acids and lipids. (B) Representative confocal images of animals co-expressing RFP::SAMS-1and GFP::SAMS-4 in the germline and intestine. Scale bar represents 50 microns. Kaplan-Meier survival plots of sams-1(lof) (C) or sams-4(ok3315) (D) following heat shock. Statistical significance is shown by Log-rank test. Each graph represents the compiled data from three biologically independent repeats; data is compiled in Supplementary file 2. Representative immunofluorescence images of intestinal nuclei stained with H3K4me3-specific antibody and quantification in sams-1(lof) animals (E, H), sams-4(RNAi) (F, I) or in sams-1(lof); sams-4(RNAi) animals (G, J). sams-3 may also be targeted; see also (Figure 3E). Scale bar represents 25 microns. Error bars show average and standard deviation. Statistical significance was calculated using unpaired Student’s t-test. ns = not significant, ****=p < 0.0001, ***=p < 0.001. Graph represents compiled data from three biologically independent repeats per condition with each point representing a single animal. Alterations in 1 CC function can cause a variety of defects (Ducker and Rabinowitz, 2017), including intriguing connections between this cycle, stress responses and aging. Lifespan lengthens in yeast, C. elegans, Drosophila and rodent models when methionine is restricted, genes in the methionine-SAM (Met-SAM) cycle are mutated, or polyamines are supplemented (Parkhitko et al., 2019). While multiple aspects of 1 CC function could affect aging, the Met-SAM cycle has particularly strong links. For example, a C. elegans SAM synthase, sams-1, was identified in a screen for long-lived animals (Hansen et al., 2005) and multiple SAM-utilizing histone methyltransferases are also implicated as aging regulators (Han and Brunet, 2012; Greer et al., 2010; Han et al., 2017). Of bioactive molecules, SAM is second only to ATP in cellular abundance (Ye and Tu, 2018), which raises the question of how such an abundant metabolite can exert specific phenotypic effects. Strikingly, studies in multiple organisms from a variety of labs have shown that reduction in SAM levels preferentially affects H3K4me3 levels (Mentch et al., 2015; Shyh-Chang et al., 2013; Kraus et al., 2014; Ding et al., 2015). However, changes in SAM production may affect other histone modifications as well. For example, the Gasser lab showed that sams-1 and sams-3 have distinct roles in heterochromatin formation, which involves H3K9me3 (Towbin et al., 2012) A yeast SAM synthase has also been shown to act as part of the SESAME histone modification complex (Li et al., 2015) or to cooperate with the SIN3 repressor (Liu and Pile, 2017). In addition, most eukaryotes have more than one SAM synthase, which could allow partitioning of enzyme output by developmental stage, tissue type or cellular process and underlie specific phenotypic effects. Indeed, in budding yeast, SAM1 and SAM2 are co-expressed but regulated by different metabolic events, have distinct posttranslational modifications, and act differently in phenotypes such as genome stability (Hoffert et al., 2019). The two SAM synthases present in mammals are expressed in distinct tissues: MAT2A is present throughout development and in most adult tissues, whereas MAT1A is specific to adult liver (Maldonado et al., 2018). MAT2A may be present in distinct regulatory conformations with its partner MAT2B (Maldonado et al., 2018). However, the distinct molecular mechanisms impacted by these synthases are less clear. Studies exploring specificity of metazoan SAM synthase function have been difficult, as MAT1A expression decreases ex vivo and MAT2A is essential for cell viability (Mato et al., 2002). Finally, the high methionine content of traditional cell culture media has limited functional studies (Sullivan et al., 2021). We have explored SAM synthase function in C. elegans, where the gene family has undergone an expansion. In C. elegans, genetic and molecular assays allow separation of SAM synthase expression and function in vivo. Furthermore, no single SAM synthase is required for survival in normal laboratory conditions or diets. sams-1 and the highly similar sams-3/sams-4 are expressed in adult animals, whereas sams-5 is present at low levels in adults and sams-2 is a pseudogene (Harris et al., 2020). We previously found that sams-1 had multiple distinct functions, contributing to PC pools and stimulating lipid synthesis through a feedback loop involving sbp-1/SREBP-1 (Walker et al., 2011) as well as regulating global H3K4me3 levels in intestinal nuclei Ding et al., 2015. Our studies also showed that loss of sams-1 produced different phenotypes in bacterial or heat stress. While sams-1 was necessary for pathogen challenge, promoter H3K4me3 and expression of immune genes, animals surprisingly survived better during heat shock when they lacked sams-1 (Ding et al., 2015). Because heat shocked animals require the H3K4me3 methyltransferase set-16/MLL for survival, we hypothesized that SAM from a different source may be important for histone methylation and survival in the heat shock response. Here, we find that SAM source impacts the functional outputs of methylation. While the SAM and the 1 CC are well associated with regulation of lifespan and stress responses, direct molecular connections have been difficult to discover. Mechanisms controlling provisioning of SAM, therefore, could provide a critical level of regulation in these processes. We show that sams-1 and sams-4 differentially affect different populations of histone methylation and thus gene expression in the heat shock response, and that their loss results in opposing phenotypes. Our study demonstrates that SAM synthases have a critical impact on distinct methylation targets and phenotypes associated with the stress response. Thus, defining the specificity of SAM synthases may provide a method to identify from broad effects methylation events that are specific phenotypic drivers. Results sams-1 and sams-4 have overlapping and distinct expression patterns and gene regulatory effects Animals respond to stress by activating specialized protective gene expression programs (de Nadal et al., 2011). While these programs depend on specific signaling and transcriptional activators, they may also be impacted by histone methylation and the production of SAM. For example, we found that C. elegans lacking sams-1 die rapidly on pathogenic bacteria, have low global H3K4me3 and fail to upregulate immune response genes (Ding et al., 2015). In contrast, heat shocked animals survive better without sams-1 (Ding et al., 2018). sams-1(RNAi) animals induced heat shock genes to normal levels and acquired additional changes in the transcriptome, including downregulation of many metabolic genes. However, the H3K4me3 methyltransferase set-16/MLL was essential for survival (Ding et al., 2018), suggesting that methylation was required. We hypothesized that other SAM synthases could play an important role in mediating survival during heat shock (Figure 1A). In order to test these hypotheses, we first compared expression of each synthase, SAM levels and gene expression after RNAi in adult unstressed animals. ModEncode data Gerstein et al., 2010 from young adult animals shows that in young adult levels, sams-1 is expressed at the highest levels, comparable to the metabolic enzyme GAPDH (gpdh-1) (Figure 1, Figure 1—figure supplement 1A). sams-3 and sams-4 are expressed at lower levels, but comparable to other enzymes of the 1-Carbon cycle such as metr-1, whereas sams-5 is minimally expressed (Figure 1—figure supplement 1A). In order to determine the tissue-specific patterns of the SAM synthases expressed in adult animals, we obtained strains where each protein was tagged with RFP, GFP or mKate, via CRISPR (Figure 1B, Figure 1—figure supplement 1B, C). RFP::sams-1 and GFP::sams-4 animals were also crossed to allow visualize expression of both synthases (Figure 1B). RFP::SAMS-1fluorescence was evident in much of the adult animal, including intestine, hypodermis and cells in the head (Figure 1B, Figure 1—figure supplement 1B), in line with mRNA expression patterns derived from tissue-specific RNA seq (Kaletsky et al., 2018). However, RFP::SAMS-1was not present in the germline, which did express GFP::SAMS-4 and SAMS-3::mKate (Figure 1B, Figure 1—figure supplement 1C). GFP::SAMS-4 and SAMS-3::mKate was also present in intestinal and hypodermal cells (Figure 1B, Figure 1—figure supplement 1C), demonstrating that these tissues, which are major contributors to the stress response (McGhee, 2007) contain each of these SAM synthases. sams-3 and sams-4 are expressed bidirectionally from the same promoter and share 95% sequence identity at the nucleotide level thus RNAi targeting is likely to affect both genes. Indeed SAMS-3::mKate and GFP::SAMS-4 were reduced after either RNAi (Figure 1—figure supplement 1C). Next, we used mass spectrometry to compare SAM levels after sams-3 and sams-4 RNAi and found that like sams-1 (Ding et al., 2015; Walker et al., 2011), reduction in any synthase significantly reduced but did not eliminate SAM (Figure 1—figure supplement 1D). In order to compare gene expression after RNA of each SAM synthase in basal conditions, we used RNA sequencing (RNAseq). Principal component analysis showed that sams-1(RNAi) and sams-5 formed distinct clusters on the first two principal components; however, sams-3 and sams-4 were overlapping (Figure 1—figure supplement 2A; Supplementary file 1: Tabs A-C). About half of the genes upregulated after sams-4 knockdown also increased in sams-1(RNAi) animals (Figure 1—figure supplement 2B). To determine if genes related to distinct biological processes were present, we compared genes upregulated after sams-1 RNAi (Ding et al., 2018) with those changing in sams-4 RNAi with WormCat (Holdorf et al., 2020), which provides enrichment scores for three category levels (Cat1, Cat2, Cat3) for broad to more specific comparisons. WormCat finds that gene function categories at the Cat1 and Cat 2 level, such as METABOLISM: Lipid (Figure 1—figure supplement 2C) or STRESS RESPONSE: Pathogen (Figure 1—figure supplement 2D–F), are enriched at lower levels and contain different genes in sams-4(RNAi) animals (Supplementary file 1: Tabs D-F). Notably, fat-7 and other lipid synthesis genes that respond to low PC in sams-1 animals are not upregulated after sams-4(RNAi) (Supplementary file 1:Tab:B). These findings strengthen the idea that these SAM synthases could have distinct functions. Opposing roles and requirements for sams-1 and sams-4 in the heat shock response In order to determine if other SAM synthases expressed in adult animals contributed to survival in heat shock (Figure 1—figure supplement 3A), we compared the heat shock survival phenotypes of C. elegans with deletions in sams-1, sams-3 and sams-4 to avoid effects of co-targeting by RNAi. sams-1(ok3033) has a deletion covering the majority of the open reading frame and extracts from these animals lack SAMS-1 protein in immunoblots (Ding et al., 2015); therefore, we refer to this allele as sams-1(lof). sams-4(ok3315) animals have a deletion that removes around a third of the open-reading frame. Strikingly, sams-4(ok3315) mutants had the opposite phenotype from sams-1(lof), and died rapidly after heat shock (Figure 1C and D, Supplementary file 2:Tabs B, C). sams-3(2932) harbors a deletion removing most of the ORF, but in contrast to sams-4 and sams-1, is indistinguishable from wild type animals in a heat shock response (Figure 1—figure supplement 3B). Although sams-3 may be co-targeted in RNAi experiments, we will refer solely to sams-4 in our discussion because it has the most direct link to the heat shock phenotypes. Finally, sams-4(RNAi) phenotypes in the heat stress response were not linked to a general failure to thrive, as sams-4(RNAi) animals under basal conditions had modestly enhanced lifespan (Figure 1—figure supplement 3C; Supplementary file 2: Tab A). Next, we used immunostaining to compare global levels of H3K4me3 in sams-1 and sams-4 RNAi nuclei during heat shock. In contrast to the reduction in H3K4me3 in basal conditions in sams-1(lof), sams-4(ok 3315) or RNAi animals (Figure 1E–F–), we detected robust levels of H3K4me3 in sams-1(lof) nuclei after heat shock (2 hr at 37 °C) (Figure 1E and H), suggesting that sams-1-independent mechanisms act on H3K4me3 during heat shock. These increases in H3K4me3 did not appear in heat shocked sams-4(RNAi) intestinal nuclei Figure 1F, I, raising the possibility that sams-4 contributed to the effects in sams-1(lof) animals. Next, we wanted to test effects of reducing both sams-1 and sams-4 levels on H3K4me3 during heat shock. Loss of multiple SAM synthases reduces viability in C. elegansTowbin et al., 2012. In order to circumvent this, we used dietary choline to rescue PC synthesis and growth of sams-1(RNAi) or (lof) animals during development (Ding et al., 2015; Walker et al., 2011). sams-1(lof); sams-4(RNAi) animals were raised on choline until the L4 stage, then moved to normal media for 16 hr before heat shock. Immunostaining of sams-1(lof); sams-4(RNAi) intestines showed that sams-4 is required for the H3K4me3 in heat shocked sams-1(lof) nuclei (Figure 1G and J). These results were identical when we used RNAi to reduce sams-1 in sams-4(ok3315) animals (Figure 1—figure supplement 3D). We also asked if sams-4 was necessary for the increased survival of sams-1 animals after heat shock and found that the survival advantage in sams-1(RNAi) was decreased in sams-4(ok3315) animals (Figure 1—figure supplement 3E). These results suggest that H3K4me3 may be remodeled during heat shock with SAM from distinct synthases and that sams-4-dependent methylation is critical for survival. Previously, it was shown that H3K4me3 deposition is independent of sams-4 in embryonic nuclei (Towbin et al., 2012), however, our finding that it is broadly decreased in sams-4(RNAi) intestinal nuclei suggests it may have important roles in H3K4 methylation in adults. Increases in H3K4me3 have also been shown to occur in budding yeast when blocks in phospholipid synthesis relieve a drain on SAM and increase levels (Ye et al., 2017), which we have confirmed in C. elegans (Ding et al., 2018). In order to determine if SAM levels could explain differences in H3K4me3 in sams-1 and sams-4 animals during heat shock, we used targeted LC/MS to compare SAM, it’s precursor methionine and S-adenosylhomocysteine (SAH), the product after methyl transfer, before and after heat shock. As in our previous assays, SAM decreased significantly after sams-1 or sams-4(RNAi) in basal conditions (Figure 1—figure supplement 3F), whereas SAM levels increased in each population as sams-1 or sams-4 animals were shifted to 37 °C for 2 hr (Figure 1—figure supplement 3F). Levels of methionine and SAH also decreased when comparing control, sams-1 or sams-4(RNAi) animals in basal vs heat-shocked conditions (Figure 1—figure supplement 3G, H), consistent with increased production and utilization of SAM. The increase in SAM in heat-shocked animals is consistent with our data showing the contribution of SAMS-4 to H3K4me3 and survival in heat-shocked sams-1 animals; however, a reduction in demand for SAM if other metabolic processes are reduced after heat shock could also contribute. Finally, levels of SAM in heat-shocked sams-4(RNAi) animals also rise to levels comparable to control animals at basal temperatures; however, H3K4me3 remains low in these conditions. Histone methyltransferase and histone demethylation machinery have modest, separable effects on sams mutant heat shock phenotypes SAM is necessary for histone methylation; however, histone methylation dynamics are also influenced by methyltransferase (KMT) or demethylase (KDMT) activity (Bannister and Kouzarides, 2011). Therefore, changes in histone methylation dynamics could also impact H3K4me3 patterns during heat shock. H3K4me3 is catalyzed by multiple versions of the COMPASS complex, which each consist of one of several SET domain histone methyltransferases and several shared accessory subunits (Shilatifard, 2012). In mammals, seven methyltransferases in the SET1, MLL or THX groups can methylate H3K4. C. elegans contain single orthologs from two of these groups: set-2/SET1 and set-16/MLL, respectively, with roles in embryonic development (Li and Kelly, 2011; Xiao et al., 2011; Wenzel et al., 2011), lipid accumulation and transgenerational inheritance (Greer et al., 2010; Han et al., 2017). In adult C. elegans, set-2 RNAi results in extensive loss of H3K4me3 in intestinal nuclei and although set-16(RNAi) causes an intermediate reduction in bulk H3K4me3 levels, it has a broader requirement for survival during stress (Ding et al., 2018). Because specificity for H3K4 mono, di or trimethylation has not been verified on a genome-wide scale for KDMTs, we examined multiple members of the H3K4 KDM family. In order to determine if KMTs or KDMT dynamics played a role in the change of H3K4me3 during heat shock, we used RNAi to deplete them in sams-1(lof) or sams-4(ok3315) animals and measured survival after heat shock and intestinal H3K4me3 levels. RNAi of set-2/SET1 (Figure 2A) or set-16/MLL (Figure 2B) increased survival in sams-1(lof) animals after heat shock (also Supplementary file 2:Tabs:C, E) and did not limit heat shock-induced H3K4me3 in sams-1(RNAi) nuclei (Figure 2D and E; GH). RNAi of two KDMTs, rbr-2 (Figure 2C) and spr-5 (Figure 2—figure supplement 1A) had opposite effects from the KMTs, moderately reducing survival (Supplementary file 2: Tab F), whereas amx-1 and lsd-1 had no effect (Figure 2—figure supplement 1B, C; Supplementary file 2: Tabs I, J). RNAi of set-2 or set-16 had slight, but statistically significant effects, increasing survival of sams-4(ok3315) animals (Figure 2—figure supplement 1D and E; Supplementary file 2: Tabs G, H). However, survival was still significantly below controls in sams-4(ok3315) with or without the KMT RNAi. Taken together, this suggests that set-2 and set-16 may act redundantly in the deposition of H3K4me3 after heat shock and are important to survival in sams-1(lof) animals. Furthermore, our data illustrate that the context is critical for understanding role of SAM and H3K4me3 in stress; sams-4 and set-16 are generally required for survival after heat shock, but loss of either H3K4 KTM enhances survival in sams-1(lof) animals. Figure 2 with 1 supplement see all Download asset Open asset H3K4me3 demethylases modulate SAM synthase phenotypes. Kaplan-Meier plots of survival assays comparing basal and heat shocked wild type (N2) or sams-1(lof) animals grown on RNAi for the histone methyltransferases set-2 (A) and set-16 (B), or demethylases rbr-2 (C) and spr-5 (D).Scale bar is 25 microns. Heat shock survival assays for sams-4(ok3315) animals exposed to set-2 or set-16 RNAi are shown in (E, F). Statistical significance is shown by Log-rank test. Each graph represents compiled data from 3 biologically independent repeats. Data for each replicate is compiled in Supplementary file 2. Black bars show mean and standard deviation. Statistical significance is determined by Student T test. Distinct patterns of H3K4me3 and gene expression in sams-1(RNAi) versus sams-4(RNAi) animals during heat shock H3K4me3 is a prevalent modification enriched near the transcription start sites (TSSs) of actively expressed genes (Eissenberg and Shilatifard, 2010). Differing global patterns of H3K4me3 in sams-1(RNAi) and sams-4(RNAi) nuclei suggest this histone modification at specific sites could also be distinct. In order to identify loci that might link H3K4me3 to these phenotypes, we used CUT&Tag, (Cleavage Under Targets and Tagmentation, C&T) (Kaya-Okur et al., 2019), to determine genome-wide H3K4me3 levels in Control RNAi, sams-1 and sams-4(RNAi) in basal (15 °C) and after heat shock (37 °C/2 hr) from two biologically independent replicates along with no antibody controls. C&T is uniquely suited to the small sample sizes available from these stressed populations. In this approach, a proteinA-Tn5 transposase fusion protein binds to the target antibody in native chromatin and DNA libraries corresponding to antibody binding sites are generated after transposase activation. After sequencing of libraries, we used the HOMER analysis suite Heinz et al., 2010 to analyze reads mapped to the C. elegans genome and called peaks using ChIPSeqAnno Zhu et al., 2010 for more detailed peak annotation. Bar plots from ChIPSeqAnno annotations and TSS plots generated with HOMER show robust mapping of H3K4me3 to promoter-TSS regions, validating this approach (Figure 3A; Supplementary file 3: Tabs A-F). While promoter-TSS regions were the largest feature in each sample, heat shocked sams-4(RNAi) animals had fewer overall peaks (Figure 3A). Correlation plots also show strong similarity between replicates (Figure 3—figure supplement 1A). Because C&T has not been extensively used in C. elegans, we compared data from basal conditions in our study to three previously published ChIP-Seq data sets (Ho et al., 2014; Pu et al., 2015; Wan et al., 2022). We compared our C&T data from wild type young adult animals grown at 15 °C on control RNAi food (HT115) against ModEncode (L3 animals), glp-1(e2141) mutants from Pu et al., 2018 and wild type adults grown at 20 °C on OP50 bacteria from Wan et al., 2022 by computing a pair-wise Pearson correlation. We found our C&T clustered most closely with the ChiPSeq from wild type animals in Wan et al., along with one of the modEndode replicates (Figure 3—figure supplement 1B) with moderate correlation scores. Both our C&T data and the Wan ChiPseq data correlated poorly with the Pu et al. ChIP seq, which is likely due to the lack of germline nuclei in these animals. The moderate correlation between our data and ChiP seq from Wan et al may be due to differences in growth temperature and bacterial diet. As a part of our quality control, we visually inspected browser tracks around the pcaf-1 gene, which is a long gene and has been used by our labs and others as a positive control for H3K4me3 localization in the five prime regions (Ding et al., 2015; Xiao et al., 2011). H3K4me3 peaks are prominent upstream of the transcript as expected and the no antibody libraries showed few reads (Figure 3—figure supplement 1C). Figure 3 with 3 supplements see all Download asset Open asset H3K4me3 modifying enzymes modulate SAM synthase phenotypes. (A) Bar graph showing the distribution of the enrichment of H3K4me3 over different genomic loci in animals fed control RNAi, sams-1(RNAi) or sams-4(RNAi) at 15°C and 37°C. (B) Aggregation plots showing TSS enrichment in the H3K4me3 peaks identified in animals fed control RNAi at 15°C and 37°C. The Y axis on TSS plots shows Peaks per base pair of gene. (C) Venn diagram comparing the overlap in the H3K4me3 peaks identified in animals fed control RNAi at 15°C and 37°C. (D) Aggregation plots showing TSS enrichment in the H3K4me3 peaks identified in animals fed control RNAi or sams-1(RNAi) or sams-4(RNAi) at 15 °C and Venn diagram comparing the overlap in the H3K4me3 peaks identified in animals fed control RNAi or sams-1(RNAi) or sams-4(RNAi) at 15 °C. (E) Aggregation plots showing TSS enrichment in the H3K4me3 peaks identified in animals fed control RNAi or sams-1(RNAi) or sams-4(RNAi) at 15 °C and Venn diagram comparing the overlap in the H3K4me3 peaks identified in animals fed control RNAi or sams-1(RNAi) or sams-4(RNAi) at 37 °C. (F) Bubble chart showing enriched gene categories in differential peaks as determined by WormCat in animals fed control RNAi at 15 °C only, 37 °C only and common between 15°C and 37°C (G) or sams-1(RNAi) and sams-4(RNAi) at 37 °C. Aggregation plots showing TSS enrichment of Control peaks that did not change after sams-1(RNAi) and sams-4(RNAi) (independent) (H) 15 °C or (I) 37 °C. Shaded areas in the Venn diagrams indicate the population of genes used for plotting the TSS enrichment plots. Aggregation plots showing TSS enrichment of Control peaks that were dependent on sams-1(RNAi) or sams-4(RNAi) (J) 15 °C or (K) 37 °C. Shaded areas in the Venn diagrams indicate the population of genes used for plotting the TSS enrichment plots. Next, we compared TSS distributions and examined overlap between H3K4me3 peaks in Control RNAi animals in basal and heat shock conditions and found moderate reductions occurred with heat shock (Figure 3B). Around 20–30% of peaks were specific to at either at basal (15 °C) vs. heat shock (37 °C) temperature (Figure 3C), suggesting that H3K4me3 could be remodeled upon heat shock in C. elegans. TSS enrichment of H3K4me3 was sharply reduced in both sams-1 and sams-4 samples at 15 °C; however, this difference was less marked in heat-shocked animals, in line with lower TSS localization in Control animals (Figure 3D and E). While aggregate TSS enrichment for H3K4me3 was similar for sams-1 and sams-4 RNAi animals, this analysis could miss distinct sets of H3K4me3 marked genes in each condition. Indeed, Control, sams-1 and sams-4(RNAi) animals each showed 500–1000 specific peaks in basal conditions, with moderate increases in these numbers after heat shock (Figure 3D and E). As H3K4me3 is a widely occurring modification, we hypothesized that we might better understand potential SAM synthase-specific requirements if we focused on peaks that change in the Control RNAi heat shock response and asked how they are affected by loss of sams-1 or sams-4. We used two different methods for comparing potential SAM synthase requirements for H3K4me3 in the heat shock response. First, we used differential peak calling ChIPPeakAnno Zhu et al., 2010 followed by WormCat category enrichment to determine the classes of genes which might be affected (Figure 3—figure supplement 2A–F; Supplementary file 3; Tabs G-I). Peaks present in both basal and heat shocked conditions were enriched for genes in the METABOLISM category (including Lipid: phospholipid, sphingolipid, sterol and lipid binding, along with mitochondrial genes) as well as in core function categories such as those involved in trafficking, DNA or mRNA functions (Figure 3F, Figure 3—figure supplement 2D–E; Supplementary file 3: Tabs G-I). There was no significant category enrichment specific to 15 °C animals, but after heat shock, Control RNAi animals gain enrichment in peaks at the Category 1 level in PROTEOSOME PROTEOLYSIS (Figure 3F). This enrichment was driven by increases in H3K4me3 at E3: Fbox genes (Figure 3—figure supplement 2A, B; Supplementary file 3:Tab A,B), which could be important for eliminating mis-folded proteins during heat shock. Comparison of peaks differentially present in sams-1 and sams-4 RNAi animals showed that only sams-1(RNAi) exhibited a similar enrichment to Control RNAi in the PROTEOLYSIS PROTEOSOME category (Figure 3G, Figure 3—figure supplement 2C, D), which could
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