Gene network based analysis identifies a coexpression module involved in regulating plasma lipids with high-fat diet response.

Plasma lipids are modulated by gene variants and many environmental factors, including diet-associated weight gain. However, understanding how these factors jointly interact to influence molecular networks that regulate plasma lipid levels is limited. Here, we took advantage of the BXD recombinant inbred family of mice to query weight gain as an environmental stressor on plasma lipids. Coexpression networks were examined in both nonobese and obese livers, and a network was identified that specifically responded to the obesogenic diet. This obesity-associated module was significantly associated with plasma lipid levels and enriched with genes known to have functions related to inflammation and lipid homeostasis. We identified key drivers of the module, including Cidec, Cidea, Pparg, Cd36, and Apoa4. The Pparg emerged as a potential master regulator of the module as it can directly target 19 of the top 30 hub genes. Importantly, activation of this module is causally linked to lipid metabolism in humans, as illustrated by correlation analysis and inverse-variance weighed Mendelian randomization. Our findings provide novel insights into gene-by-environment interactions for plasma lipid metabolism that may ultimately contribute to new biomarkers, better diagnostics, and improved approaches to prevent or treat dyslipidemia in patients.

Integrative systems analysis identifies genetic and dietary modulators of bile acid homeostasis.

Bile acids (BAs) are complex and incompletely understood enterohepatic-derived hormones that control whole-body metabolism. Here, we profiled postprandial BAs in the liver, feces, and plasma of 360 chow- or high-fat-diet-fed BXD male mice and demonstrated that both genetics and diet strongly influence BA abundance, composition, and correlation with metabolic traits. Through an integrated systems approach, we mapped hundreds of quantitative trait loci that modulate BAs and identified both known and unknown regulators of BA homeostasis. In particular, we discovered carboxylesterase 1c (Ces1c) as a genetic determinant of plasma tauroursodeoxycholic acid (TUDCA), a BA species with established disease-preventing actions. The association between Ces1c and plasma TUDCA was validated using data from independent mouse cohorts and a Ces1c knockout mouse model. Collectively, our data are a unique resource to dissect the physiological importance of BAs as determinants of metabolic traits, as underscored by the identification of CES1C as a master regulator of plasma TUDCA levels.

PCfun: a hybrid computational framework for systematic characterization of protein complex function.

In molecular biology, it is a general assumption that the ensemble of expressed molecules, their activities and interactions determine biological function, cellular states and phenotypes. Stable protein complexes-or macromolecular machines-are, in turn, the key functional entities mediating and modulating most biological processes. Although identifying protein complexes and their subunit composition can now be done inexpensively and at scale, determining their function remains challenging and labor intensive. This study describes Protein Complex Function predictor (PCfun), the first computational framework for the systematic annotation of protein complex functions using Gene Ontology (GO) terms. PCfun is built upon a word embedding using natural language processing techniques based on 1 million open access PubMed Central articles. Specifically, PCfun leverages two approaches for accurately identifying protein complex function, including: (i) an unsupervised approach that obtains the nearest neighbor (NN) GO term word vectors for a protein complex query vector and (ii) a supervised approach using Random Forest (RF) models trained specifically for recovering the GO terms of protein complex queries described in the CORUM protein complex database. PCfun consolidates both approaches by performing a hypergeometric statistical test to enrich the top NN GO terms within the child terms of the GO terms predicted by the RF models. The documentation and implementation of the PCfun package are available at https://github.com/sharmavaruns/PCfun. We anticipate that PCfun will serve as a useful tool and novel paradigm for the large-scale characterization of protein complex function.

GCN5 maintains muscle integrity by acetylating YY1 to promote dystrophin expression.

Protein lysine acetylation is a post-translational modification that regulates protein structure and function. It is targeted to proteins by lysine acetyltransferases (KATs) or removed by lysine deacetylases. This work identifies a role for the KAT enzyme general control of amino acid synthesis protein 5 (GCN5; KAT2A) in regulating muscle integrity by inhibiting DNA binding of the transcription factor/repressor Yin Yang 1 (YY1). Here we report that a muscle-specific mouse knockout of GCN5 (Gcn5skm-/-) reduces the expression of key structural muscle proteins, including dystrophin, resulting in myopathy. GCN5 was found to acetylate YY1 at two residues (K392 and K393), disrupting the interaction between the YY1 zinc finger region and DNA. These findings were supported by human data, including an observed negative correlation between YY1 gene expression and muscle fiber diameter. Collectively, GCN5 positively regulates muscle integrity through maintenance of structural protein expression via acetylation-dependent inhibition of YY1. This work implicates the role of protein acetylation in the regulation of muscle health and for consideration in the design of novel therapeutic strategies to support healthy muscle during myopathy or aging.

Multiomic profiling of the liver across diets and age in a diverse mouse population.

We profiled the liver transcriptome, proteome, and metabolome in 347 individuals from 58 isogenic strains of the BXD mouse population across age (7 to 24 months) and diet (low or high fat) to link molecular variations to metabolic traits. Several hundred genes are affected by diet and/or age at the transcript and protein levels. Orthologs of two aging-associated genes, St7 and Ctsd, were knocked down in C. elegans, reducing longevity in wild-type and mutant long-lived strains. The multiomics data were analyzed as segregating gene networks according to each independent variable, providing causal insight into dietary and aging effects. Candidates were cross-examined in an independent diversity outbred mouse liver dataset segregating for similar diets, with ∼80%-90% of diet-related candidate genes found in common across datasets. Together, we have developed a large multiomics resource for multivariate analysis of complex traits and demonstrate a methodology for moving from observational associations to causal connections.

Gene-by-environment modulation of lifespan and weight gain in the murine BXD family.

How lifespan and body weight vary as a function of diet and genetic differences is not well understood. Here we quantify the impact of differences in diet on lifespan in a genetically diverse family of female mice, split into matched isogenic cohorts fed a low-fat chow diet (CD, n = 663) or a high-fat diet (HFD, n = 685). We further generate key metabolic data in a parallel cohort euthanized at four time points. HFD feeding shortens lifespan by 12%: equivalent to a decade in humans. Initial body weight and early weight gains account for longevity differences of roughly 4-6 days per gram. At 500 days, animals on a HFD typically gain four times as much weight as control, but variation in weight gain does not correlate with lifespan. Classic serum metabolites, often regarded as health biomarkers, are not necessarily strong predictors of longevity. Our data indicate that responses to a HFD are substantially modulated by gene-by-environment interactions, highlighting the importance of genetic variation in making accurate individualized dietary recommendations.

Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial.

Advancements in mass spectrometry-based proteomics have enabled experiments encompassing hundreds of samples. While these large sample sets deliver much-needed statistical power, handling them introduces technical variability known as batch effects. Here, we present a step-by-step protocol for the assessment, normalization, and batch correction of proteomic data. We review established methodologies from related fields and describe solutions specific to proteomic challenges, such as ion intensity drift and missing values in quantitative feature matrices. Finally, we compile a set of techniques that enable control of batch effect adjustment quality. We provide an R package, "proBatch", containing functions required for each step of the protocol. We demonstrate the utility of this methodology on five proteomic datasets each encompassing hundreds of samples and consisting of multiple experimental designs. In conclusion, we provide guidelines and tools to make the extraction of true biological signal from large proteomic studies more robust and transparent, ultimately facilitating reliable and reproducible research in clinical proteomics and systems biology.

Molecular pathways behind acquired obesity: Adipose tissue and skeletal muscle multiomics in monozygotic twin pairs discordant for BMI.

Tissue-specific mechanisms prompting obesity-related development complications in humans remain unclear. We apply multiomics analyses of subcutaneous adipose tissue and skeletal muscle to examine the effects of acquired obesity among 49 BMI-discordant monozygotic twin pairs. Overall, adipose tissue appears to be more affected by excess body weight than skeletal muscle. In heavier co-twins, we observe a transcriptional pattern of downregulated mitochondrial pathways in both tissues and upregulated inflammatory pathways in adipose tissue. In adipose tissue, heavier co-twins exhibit lower creatine levels; in skeletal muscle, glycolysis- and redox stress-related protein and metabolite levels remain higher. Furthermore, metabolomics analyses in both tissues reveal that several proinflammatory lipids are higher and six of the same lipid derivatives are lower in acquired obesity. Finally, in adipose tissue, but not in skeletal muscle, mitochondrial downregulation and upregulated inflammation are associated with a fatty liver, insulin resistance, and dyslipidemia, suggesting that adipose tissue dominates in acquired obesity.

A platform for experimental precision medicine: The extended BXD mouse family.

The challenge of precision medicine is to model complex interactions among DNA variants, phenotypes, development, environments, and treatments. We address this challenge by expanding the BXD family of mice to 140 fully isogenic strains, creating a uniquely powerful model for precision medicine. This family segregates for 6 million common DNA variants-a level that exceeds many human populations. Because each member can be replicated, heritable traits can be mapped with high power and precision. Current BXD phenomes are unsurpassed in coverage and include much omics data and thousands of quantitative traits. BXDs can be extended by a single-generation cross to as many as 19,460 isogenic F1 progeny, and this extended BXD family is an effective platform for testing causal modeling and for predictive validation. BXDs are a unique core resource for the field of experimental precision medicine.

SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles.

Protein-protein interactions (PPIs) play critical functional and regulatory roles in cellular processes. They are essential for macromolecular complex formation, which in turn constitutes the basis for protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we extend co-fractionation and mass spectrometric data analysis to perform quantitative, network-based studies of proteome organization, via the size-exclusion chromatography algorithmic toolkit (SECAT). This framework explicitly accounts for the dynamic nature and rewiring of protein complexes across multiple cell states and samples, thus, elucidating molecular mechanisms that are differentially implemented across different experimental settings. Systematic analysis of multiple datasets shows that SECAT represents a highly scalable and effective methodology to assess condition/state-specific protein-network state. A record of this paper's transparent peer review process is included in the Supplemental Information.

Body weight and high-fat diet are associated with epigenetic aging in female members of the BXD murine family.

DNA methylation (DNAm) is shaped by genetic and environmental factors and modulated by aging. Here, we examine interrelations between epigenetic aging, body weight (BW), and life span in 12 isogenic strains from the BXD family of mice that exhibit over twofold variation in longevity. Genome-wide DNAm was assayed in 70 liver specimens from predominantly female cases, 6-25 months old, that were maintained on normal chow or high-fat diet (HFD). We defined subsets of CpG regions associated with age, BW at young adulthood, and strain-by-diet-dependent life span. These age-associated differentially methylated CpG regions (age-DMRs) featured distinct genomic characteristics, with DNAm gains over time occurring in sites such as promoters and exons that have high CpG density and low average methylation. CpG regions associated with BW were enriched in introns, tended to have lower methylation in mice with higher BW, and were inversely correlated with gene expression (i.e., higher mRNA levels in mice with higher BW). CpG regions associated with life span were linked to genes involved in life span modulation, including the telomerase reverse transcriptase gene, Tert, which had both lower methylation and higher expression in long-lived strains. An epigenetic clock defined from age-DMRs revealed accelerated aging in mice belonging to strains with shorter life spans. Both higher BW and the HFD were associated with accelerated epigenetic aging. Our results highlight the age-accelerating effect of heavier BW. Furthermore, we demonstrate that the measure of epigenetic aging derived from age-DMRs can predict genotype and diet-induced differences in life span among female BXD members.

Mitochondrial translation and dynamics synergistically extend lifespan in C. elegans through HLH-30.

Mitochondrial form and function are closely interlinked in homeostasis and aging. Inhibiting mitochondrial translation is known to increase lifespan in C. elegans, and is accompanied by a fragmented mitochondrial network. However, whether this link between mitochondrial translation and morphology is causal in longevity remains uncharacterized. Here, we show in C. elegans that disrupting mitochondrial network homeostasis by blocking fission or fusion synergizes with reduced mitochondrial translation to prolong lifespan and stimulate stress response such as the mitochondrial unfolded protein response, UPRMT. Conversely, immobilizing the mitochondrial network through a simultaneous disruption of fission and fusion abrogates the lifespan increase induced by mitochondrial translation inhibition. Furthermore, we find that the synergistic effect of inhibiting both mitochondrial translation and dynamics on lifespan, despite stimulating UPRMT, does not require it. Instead, this lifespan-extending synergy is exclusively dependent on the lysosome biogenesis and autophagy transcription factor HLH-30/TFEB. Altogether, our study reveals the mechanistic crosstalk between mitochondrial translation, mitochondrial dynamics, and lysosomal signaling in regulating longevity.

A Conserved Mito-Cytosolic Translational Balance Links Two Longevity Pathways.

Slowing down translation in either the cytosol or the mitochondria is a conserved longevity mechanism. Here, we found a non-interventional natural correlation of mitochondrial and cytosolic ribosomal proteins (RPs) in mouse population genetics, suggesting a translational balance. Inhibiting mitochondrial translation in C. elegans through mrps-5 RNAi repressed cytosolic translation. Transcriptomics integrated with proteomics revealed that this inhibition specifically reduced translational efficiency of mRNAs required in growth pathways while increasing stress response mRNAs. The repression of cytosolic translation and extension of lifespan from mrps-5 RNAi were dependent on atf-5/ATF4 and independent from metabolic phenotypes. We found the translational balance to be conserved in mammalian cells upon inhibiting mitochondrial translation pharmacologically with doxycycline. Lastly, extending this in vivo, doxycycline repressed cytosolic translation in the livers of germ-free mice. These data demonstrate that inhibiting mitochondrial translation initiates an atf-5/ATF4-dependent cascade leading to coordinated repression of cytosolic translation, which could be targeted to promote longevity.

Diet modulates cecum bacterial diversity and physiological phenotypes across the BXD mouse genetic reference population.

The BXD family has become one of the preeminent genetic reference populations to understand the genetic and environmental control of phenotypic variation. Here we evaluate the responses to different levels of fat in the diet using both chow diet (CD, 13-18% fat) and a high-fat diet (HFD, 45-60% fat). We studied cohorts of BXD strains, both inbred parents C57BL/6J and DBA/2J (commonly known as B6 and D2, respectively), as well as B6D2 and D2B6 reciprocal F1 hybrids. The comparative impact of genetic and dietary factors was analyzed by profiling a range of phenotypes, most prominently their cecum bacterial composition. The parents of the BXDs and F1 hybrids express limited differences in terms of weight and body fat gain on CD. In contrast, the strain differences on HFD are substantial for percent body fat, with DBA/2J accumulating 12.5% more fat than C57BL/6J (P < 0.0001). The F1 hybrids born to DBA/2J dams (D2B6F1) have 10.6% more body fat (P < 0.001) than those born to C57BL/6J dams. Sequence analysis of the cecum microbiota reveals important differences in bacterial composition among BXD family members with a substantial shift in composition caused by HFD. Relative to CD, the HFD induces a decline in diversity at the phylum level with a substantial increase in Firmicutes (+13.8%) and a reduction in Actinobacteria (-7.9%). In the majority of BXD strains, the HFD also increases cecal sIgA (P < 0.0001)-an important component of the adaptive immunity response against microbial pathogens. Host genetics modulates variation in cecum bacterial composition at the genus level in CD, with significant quantitative trait loci (QTLs) for Oscillibacter mapped to Chr 3 (18.7-19.2 Mb, LRS = 21.4) and for Bifidobacterium mapped to Chr 6 (89.21-89.37 Mb, LRS = 19.4). Introduction of HFD served as an environmental suppressor of these QTLs due to a reduction in the contribution of both genera (P < 0.001). Relations among liver metabolites and cecum bacterial composition were predominant in CD cohort, but these correlations do not persist following the shift to HFD. Overall, these findings demonstrate the important impact of environmental/dietary manipulation on the relationships between host genetics, gastrointestinal bacterial composition, immunological parameters, and metabolites-knowledge that will help in the understanding of the causal sources of metabolic disorders.

A new class of protein biomarkers based on subcellular distribution: application to a mouse liver cancer model.

To-date, most proteomic studies aimed at discovering tissue-based cancer biomarkers have compared the quantity of selected proteins between case and control groups. However, proteins generally function in association with other proteins to form modules localized in particular subcellular compartments in specialized cell types and tissues. Sub-cellular mislocalization of proteins has in fact been detected as a key feature in a variety of cancer cells. Here, we describe a strategy for tissue-biomarker detection based on a mitochondrial fold enrichment (mtFE) score, which is sensitive to protein abundance changes as well as changes in subcellular distribution between mitochondria and cytosol. The mtFE score integrates protein abundance data from total cellular lysates and mitochondria-enriched fractions, and provides novel information for the classification of cancer samples that is not necessarily apparent from conventional abundance measurements alone. We apply this new strategy to a panel of wild-type and mutant mice with a liver-specific gene deletion of Liver receptor homolog 1 (Lrh-1hep-/-), with both lines containing control individuals as well as individuals with liver cancer induced by diethylnitrosamine (DEN). Lrh-1 gene deletion attenuates cancer cell metabolism in hepatocytes through mitochondrial glutamine processing. We show that proteome changes based on mtFE scores outperform protein abundance measurements in discriminating DEN-induced liver cancer from healthy liver tissue, and are uniquely robust against genetic perturbation. We validate the capacity of selected proteins with informative mtFE scores to indicate hepatic malignant changes in two independent mouse models of hepatocellular carcinoma (HCC), thus demonstrating the robustness of this new approach to biomarker research. Overall, the method provides a novel, sensitive approach to cancer biomarker discovery that considers contextual information of tested proteins.

Mild inborn errors of metabolism in commonly used inbred mouse strains.

Inbred mouse strains are a cornerstone of translational research but paradoxically many strains carry mild inborn errors of metabolism. For example, α-aminoadipic acidemia and branched-chain ketoacid dehydrogenase deficiency are known in C57BL/6J mice. Using RNA sequencing, we now reveal the causal variants in Dhtkd1 and Bckdhb, and the molecular mechanism underlying these metabolic defects. C57BL/6J mice have decreased Dhtkd1 mRNA expression due to a solitary long terminal repeat (LTR) in intron 4 of Dhtkd1. This LTR harbors an alternate splice donor site leading to a partial splicing defect and as a consequence decreased total and functional Dhtkd1 mRNA, decreased DHTKD1 protein and α-aminoadipic acidemia. Similarly, C57BL/6J mice have decreased Bckdhb mRNA expression due to an LTR retrotransposon in intron 1 of Bckdhb. This transposable element encodes an alternative exon 1 causing aberrant splicing, decreased total and functional Bckdhb mRNA and decreased BCKDHB protein. Using a targeted metabolomics screen, we also reveal elevated plasma C5-carnitine in 129 substrains. This biochemical phenotype resembles isovaleric acidemia and is caused by an exonic splice mutation in Ivd leading to partial skipping of exon 10 and IVD protein deficiency. In summary, this study identifies three causal variants underlying mild inborn errors of metabolism in commonly used inbred mouse strains.

Multi-omic measurements of heterogeneity in HeLa cells across laboratories.

Reproducibility in research can be compromised by both biological and technical variation, but most of the focus is on removing the latter. Here we investigate the effects of biological variation in HeLa cell lines using a systems-wide approach. We determine the degree of molecular and phenotypic variability across 14 stock HeLa samples from 13 international laboratories. We cultured cells in uniform conditions and profiled genome-wide copy numbers, mRNAs, proteins and protein turnover rates in each cell line. We discovered substantial heterogeneity between HeLa variants, especially between lines of the CCL2 and Kyoto varieties, and observed progressive divergence within a specific cell line over 50 successive passages. Genomic variability has a complex, nonlinear effect on transcriptome, proteome and protein turnover profiles, and proteotype patterns explain the varying phenotypic response of different cell lines to Salmonella infection. These findings have implications for the interpretation and reproducibility of research results obtained from human cultured cells.

Quantifying and Localizing the Mitochondrial Proteome Across Five Tissues in A Mouse Population.

We have used SWATH mass spectrometry to quantify 3648 proteins across 76 proteomes collected from genetically diverse BXD mouse strains in two fractions (mitochondria and total cell) from five tissues: liver, quadriceps, heart, brain, and brown adipose (BAT). Across tissues, expression covariation between genes' proteins and transcripts-measured in the same individuals-broadly aligned. Covariation was however far stronger in certain subsets than others: only 8% of transcripts in the lowest expression and variance quintile covaried with their protein, in contrast to 65% of transcripts in the highest quintiles. Key functional differences among the 3648 genes were also observed across tissues, with electron transport chain (ETC) genes particularly investigated. ETC complex proteins covary and form strong gene networks according to tissue, but their equivalent transcripts do not. Certain physiological consequences, such as the depletion of ATP synthase in BAT, are thus obscured in transcript data. Lastly, we compared the quantitative proteomic measurements between the total cell and mitochondrial fractions for the five tissues. The resulting enrichment score highlighted several hundred proteins which were strongly enriched in mitochondria, which included several dozen proteins were not reported in literature to be mitochondrially localized. Four of these candidates were selected for biochemical validation, where we found MTAP, SOAT2, and IMPDH2 to be localized inside the mitochondria, whereas ABCC6 was in the mitochondria-associated membrane. These findings demonstrate the synergies of a multi-omics approach to study complex metabolic processes, and this provides a resource for further discovery and analysis of proteoforms, modified proteins, and protein localization.

Genetic Regulation of Plasma Lipid Species and Their Association with Metabolic Phenotypes.

The genetic regulation and physiological impact of most lipid species are unexplored. Here, we profiled 129 plasma lipid species across 49 strains of the BXD mouse genetic reference population fed either chow or a high-fat diet. By integrating these data with genomics and phenomics datasets, we elucidated genes by environment (diet) interactions that regulate systemic metabolism. We found quantitative trait loci (QTLs) for ∼94% of the lipids measured. Several QTLs harbored genes associated with blood lipid levels and abnormal lipid metabolism in human genome-wide association studies. Lipid species from different classes provided signatures of metabolic health, including seven plasma triglyceride species that associated with either healthy or fatty liver. This observation was further validated in an independent mouse model of non-alcoholic fatty liver disease (NAFLD) and in plasma from NAFLD patients. This work provides a resource to identify plausible genes regulating the measured lipid species and their association with metabolic traits.