Evan G. Williams

NCoR1 is a conserved physiological modulator of muscle mass and oxidative function.

Transcriptional coregulators control the activity of many transcription factors and are thought to have wide-ranging effects on gene expression patterns. We show here that muscle-specific loss of nuclear receptor corepressor 1 (NCoR1) in mice leads to enhanced exercise endurance due to an increase of both muscle mass and of mitochondrial number and activity. The activation of selected transcription factors that control muscle function, such as MEF2, PPARβ/δ, and ERRs, underpins these phenotypic alterations. NCoR1 levels are decreased in conditions that require fat oxidation, resetting transcriptional programs to boost oxidative metabolism. Knockdown of gei-8, the sole C. elegans NCoR homolog, also robustly increased muscle mitochondria and respiration, suggesting conservation of NCoR1 function. Collectively, our data suggest that NCoR1 plays an adaptive role in muscle physiology and that interference with NCoR1 action could be used to improve muscle function.

Murine Gut Microbiota Is Defined by Host Genetics and Modulates Variation of Metabolic Traits

The gastrointestinal tract harbors a complex and diverse microbiota that has an important role in host metabolism. Microbial diversity is influenced by a combination of environmental and host genetic factors and is associated with several polygenic diseases. In this study we combined next-generation sequencing, genetic mapping, and a set of physiological traits of the BXD mouse population to explore genetic factors that explain differences in gut microbiota and its impact on metabolic traits. Molecular profiling of the gut microbiota revealed important quantitative differences in microbial composition among BXD strains. These differences in gut microbial composition are influenced by host-genetics, which is complex and involves many loci. Linkage analysis defined Quantitative Trait Loci (QTLs) restricted to a particular taxon, branch or that influenced the variation of taxa across phyla. Gene expression within the gastrointestinal tract and sequence analysis of the parental genomes in the QTL regions uncovered candidate genes with potential to alter gut immunological profiles and impact the balance between gut microbial communities. A QTL region on Chr 4 that overlaps several interferon genes modulates the population of Bacteroides, and potentially Bacteroidetes and Firmicutes–the predominant BXD gut phyla. Irak4, a signaling molecule in the Toll-like receptor pathways is a candidate for the QTL on Chr15 that modulates Rikenellaceae, whereas Tgfb3, a cytokine modulating the barrier function of the intestine and tolerance to commensal bacteria, overlaps a QTL on Chr 12 that influence Prevotellaceae. Relationships between gut microflora, morphological and metabolic traits were uncovered, some potentially a result of common genetic sources of variation.

Tetracyclines Disturb Mitochondrial Function across Eukaryotic Models: A Call for Caution in Biomedical Research

In recent years, tetracyclines, such as doxycycline, have become broadly used to control gene expression by virtue of the Tet-on/Tet-off systems. However, the wide range of direct effects of tetracycline use has not been fully appreciated. We show here that these antibiotics induce a mitonuclear protein imbalance through their effects on mitochondrial translation, an effect that likely reflects the evolutionary relationship between mitochondria and proteobacteria. Even at low concentrations, tetracyclines induce mitochondrial proteotoxic stress, leading to changes in nuclear gene expression and altered mitochondrial dynamics and function in commonly used cell types, as well as worms, flies, mice, and plants. Given that tetracyclines are so widely applied in research, scientists should be aware of their potentially confounding effects on experimental results. Furthermore, these results caution against extensive use of tetracyclines in livestock due to potential downstream impacts on the environment and human health.

Systems proteomics of liver mitochondria function

Expanded proteomic analysis of metabolism Combined analysis of large data sets characterizing genes, transcripts, and proteins can elucidate biological functions and disease processes. Williams et al. report an exceptionally detailed characterization of mitochondrial function in a genetic reference panel of recombinant inbred mice. They measured the metabolic function of nearly 400 mice under various environmental conditions and collected detailed quantitative information from livers of the animals on over 25,000 transcripts. These data were integrated with quantitation of over 2500 proteins and nearly 1000 metabolites. Such analysis showed a frequent lack of correlation of transcript and protein abundance, enabled the identification of genomic variants of mitochondrial enzymes that caused inborn errors in metabolism, and revealed two genes that appear to function in cholesterol metabolism. Science, this issue p. 10.1126/science.aad0189 Advances in mass spectrometry yield insights into mitochondrial function. INTRODUCTION Over the past two decades, continuous improvements in “omics” technologies have driven an ever-greater capacity to define the relationships between genetics, molecular pathways, and overall phenotypes. Despite this progress, the majority of genetic factors influencing complex traits remain unknown. This is exemplified by mitochondrial supercomplex assembly, a critical component of the electron transport chain, which remains poorly characterized. Recent advances in mass spectrometry have expanded the scope and reliability of proteomics and metabolomics measurements. These tools are now capable of identifying thousands of factors driving diverse molecular pathways, their mechanisms, and consequent phenotypes and thus substantially contribute toward the understanding of complex systems. RATIONALE Genome-wide association studies (GWAS) have revealed many causal loci associated with specific phenotypes, yet the identification of such genetic variants has been generally insufficient to elucidate the molecular mechanisms linking these genetic variants with specific phenotypes. A multitude of control mechanisms differentially affect the cellular concentrations of different classes of biomolecules. Therefore, the identification of the causal mechanisms underlying complex trait variation requires quantitative and comprehensive measurements of multiple layers of data—principally of transcripts, proteins, and metabolites and the integration of the resulting data. Recent technological developments now support such multiple layers of measurements with a high degree of reproducibility across diverse sample or patient cohorts. In this study, we applied a multilayered approach to analyze metabolic phenotypes associated with mitochondrial metabolism. RESULTS We profiled metabolic fitness in 386 individuals from 80 cohorts of the BXD mouse genetic reference population across two environmental states. Specifically, this extensive phenotyping program included the analysis of metabolism, mitochondrial function, and cardiovascular function. To understand the variation in these phenotypes, we quantified multiple, detailed layers of systems-scale measurements in the livers of the entire population: the transcriptome (25,136 transcripts), proteome (2622 proteins), and metabolome (981 metabolites). Together with full genomic coverage of the BXDs, these layers provide a comprehensive view on overall variances induced by genetics and environment regarding metabolic activity and mitochondrial function in the BXDs. Among the 2600 transcript-protein pairs identified, 85% of observed quantitative trait loci uniquely influenced either the transcript or protein level. The transomic integration of molecular data established multiple causal links between genotype and phenotype that could not be characterized by any individual data set. Examples include the link between D2HGDH protein and the metabolite D-2-hydroxyglutarate, the BCKDHA protein mapping to the gene Bckdhb, the identification of two isoforms of ECI2, and mapping mitochondrial supercomplex assembly to the protein COX7A2L. These respective measured variants in these mitochondrial proteins were in turn associated with varied complex metabolic phenotypes, such as heart rate, cholesterol synthesis, and branched-chain amino acid metabolism. Of note, our transomics approach clarified the contested role of COX7A2L in mitochondrial supercomplex formation and identified and validated Echdc1 and Mmab as involved in the cholesterol pathway. CONCLUSION Overall, these findings indicate that data generated by next-generation proteomics and metabolomics techniques have reached a quality and scope to complement transcriptomics, genomics, and phenomics for transomic analyses of complex traits. Using mitochondria as a case in point, we show that the integrated analysis of these systems provides more insights into the emergence of the observed phenotypes than any layer can by itself, highlighting the complementarity of a multilayered approach. The increasing implementation of these omics technologies as complements, rather than as replacements, will together move us forward in the integrative analysis of complex traits. Model of the transomics analysis. A transomics approach was taken to analyze genetic and environmental variation in metabolic and mitochondrial phenotypes by measuring five distinct layers of biology in a diverse population of BXD mice. The combined analysis of all layers together provides additional information not yielded by any single omics approach. Recent improvements in quantitative proteomics approaches, including Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH-MS), permit reproducible large-scale protein measurements across diverse cohorts. Together with genomics, transcriptomics, and other technologies, transomic data sets can be generated that permit detailed analyses across broad molecular interaction networks. Here, we examine mitochondrial links to liver metabolism through the genome, transcriptome, proteome, and metabolome of 386 individuals in the BXD mouse reference population. Several links were validated between genetic variants toward transcripts, proteins, metabolites, and phenotypes. Among these, sequence variants in Cox7a2l alter its protein’s activity, which in turn leads to downstream differences in mitochondrial supercomplex formation. This data set demonstrates that the proteome can now be quantified comprehensively, serving as a key complement to transcriptomics, genomics, and metabolomics—a combination moving us forward in complex trait analysis.

Multilayered genetic and omics dissection of mitochondrial activity in a mouse reference population

The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study, we quantified the transcriptome--a subset of the metabolome--and, using targeted proteomics, quantified a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein, and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. These integrated molecular profiles also allowed further characterization of complex pathways, particularly the mitochondrial unfolded protein response (UPR(mt)). UPR(mt) shows strikingly variant responses at the transcript and protein level that are remarkably conserved among C. elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.

Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle

We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.

Systems Genetics of Metabolism: The Use of the BXD Murine Reference Panel for Multiscalar Integration of Traits

Metabolic homeostasis is achieved by complex molecular and cellular networks that differ significantly among individuals and are difficult to model with genetically engineered lines of mice optimized to study single gene function. Here, we systematically acquired metabolic phenotypes by using the EUMODIC EMPReSS protocols across a large panel of isogenic but diverse strains of mice (BXD type) to study the genetic control of metabolism. We generated and analyzed 140 classical phenotypes and deposited these in an open-access web service for systems genetics (www.genenetwork.org). Heritability, influence of sex, and genetic modifiers of traits were examined singly and jointly by using quantitative-trait locus (QTL) and expression QTL-mapping methods. Traits and networks were linked to loci encompassing both known variants and novel candidate genes, including alkaline phosphatase (ALPL), here linked to hypophosphatasia. The assembled and curated phenotypes provide key resources and exemplars that can be used to dissect complex metabolic traits and disorders.

Urolithin A induces mitophagy and prolongs lifespan in C. elegans and increases muscle function in rodents

The biological effects of urolithins remain poorly characterized, despite wide-spread human exposure via the dietary consumption of their metabolic precursors, the ellagitannins, which are found in the pomegranate fruit, as well as in nuts and berries. We identified urolithin A (UA) as a first-in-class natural compound that induces mitophagy both in vitro and in vivo following oral consumption. In C. elegans, UA prevented the accumulation of dysfunctional mitochondria with age and extended lifespan. Likewise, UA prolonged normal activity during aging in C. elegans, including mobility and pharyngeal pumping, while maintaining mitochondrial respiratory capacity. These effects translated to rodents, where UA improved exercise capacity in two different mouse models of age-related decline of muscle function, as well as in young rats. Our findings highlight the health benefits of urolithin A and its potential application in strategies to improve mitochondrial and muscle function.

Joint mouse-human phenome-wide association to test gene function and disease risk

Phenome-wide association is a novel reverse genetic strategy to analyze genome-to-phenome relations in human clinical cohorts. Here we test this approach using a large murine population segregating for ∼5 million sequence variants, and we compare our results to those extracted from a matched analysis of gene variants in a large human cohort. For the mouse cohort, we amassed a deep and broad open-access phenome consisting of ∼4,500 metabolic, physiological, pharmacological and behavioural traits, and more than 90 independent expression quantitative trait locus (QTL), transcriptome, proteome, metagenome and metabolome data sets—by far the largest coherent phenome for any experimental cohort (www.genenetwork.org). We tested downstream effects of subsets of variants and discovered several novel associations, including a missense mutation in fumarate hydratase that controls variation in the mitochondrial unfolded protein response in both mouse and Caenorhabditis elegans, and missense mutations in Col6a5 that underlies variation in bone mineral density in both mouse and human.

Evidence for a Direct Effect of the NAD+ Precursor Acipimox on Muscle Mitochondrial Function in Humans

Recent preclinical studies showed the potential of nicotinamide adenine dinucleotide (NAD+) precursors to increase oxidative phosphorylation and improve metabolic health, but human data are lacking. We hypothesize that the nicotinic acid derivative acipimox, an NAD+ precursor, would directly affect mitochondrial function independent of reductions in nonesterified fatty acid (NEFA) concentrations. In a multicenter randomized crossover trial, 21 patients with type 2 diabetes (age 57.7 ± 1.1 years, BMI 33.4 ± 0.8 kg/m2) received either placebo or acipimox 250 mg three times daily dosage for 2 weeks. Acipimox treatment increased plasma NEFA levels (759 ± 44 vs. 1,135 ± 97 μmol/L for placebo vs. acipimox, P < 0.01) owing to a previously described rebound effect. As a result, skeletal muscle lipid content increased and insulin sensitivity decreased. Despite the elevated plasma NEFA levels, ex vivo mitochondrial respiration in skeletal muscle increased. Subsequently, we showed that acipimox treatment resulted in a robust elevation in expression of nuclear-encoded mitochondrial gene sets and a mitonuclear protein imbalance, which may indicate activation of the mitochondrial unfolded protein response. Further studies in C2C12 myotubes confirmed a direct effect of acipimox on NAD+ levels, mitonuclear protein imbalance, and mitochondrial oxidative capacity. To the best of our knowledge, this study is the first to demonstrate that NAD+ boosters can also directly affect skeletal muscle mitochondrial function in humans.