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Non-alcoholic fatty liver disease (NAFLD) is often associated with obesity and type 2 diabetes. To disentangle etiological relationships between these conditions and identify genetically-determined metabolites involved in NAFLD processes, we mapped 1 H nuclear magnetic resonance (NMR) metabolomic and disease-related phenotypes in a mouse F2 cross derived from strains showing resistance (BALB/c) and increased susceptibility (129S6) to these diseases. Quantitative trait locus (QTL) analysis based on single nucleotide polymorphism (SNP) genotypes identified diet responsive QTLs in F2 mice fed control or high fat diet (HFD). In HFD fed F2 mice we mapped on chromosome 18 a QTL regulating liver micro- and macrovesicular steatosis and inflammation, independently from glucose intolerance and adiposity, which was linked to chromosome 4. Linkage analysis of liver metabolomic profiling data identified a QTL for octopamine, which co-localised with the QTL for liver histopathology in the cross. Functional relationship between these two QTLs was validated in vivo in mice chronically treated with octopamine, which exhibited reduction in liver histopathology and metabolic benefits, underlining its role as a mechanistic biomarker of fatty liver with potential therapeutic applications.

The influence of the gut microbiome on metabolic and behavioral traits is widely accepted, though the microbiome-derived metabolites involved remain unclear. We carried out untargeted urine 1 H-NMR spectroscopy-based metabolic phenotyping in an isogenic C57BL/6J mouse population (n = 50) and show that microbial-host co-metabolites are prodromal (i.e., early) markers predicting future divergence in metabolic (obesity and glucose homeostasis) and behavioral (anxiety and activity) outcomes with 94%-100% accuracy. Some of these metabolites also modulate disease phenotypes, best illustrated by trimethylamine-N-oxide (TMAO), a product of microbial-host co-metabolism predicting future obesity, impaired glucose tolerance (IGT), and behavior while reducing endoplasmic reticulum stress and lipogenesis in 3T3-L1 adipocytes. Chronic in vivo TMAO treatment limits IGT in HFD-fed mice and isolated pancreatic islets by increasing insulin secretion. We highlight the prodromal potential of microbial metabolites to predict disease outcomes and their potential in shaping mammalian phenotypic heterogeneity., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Maintaining homeostasis in higher organisms involves a complex interplay of multiple ubiquitous and organ-specific molecular mechanisms that can be characterized using functional genomics technologies such as transcriptomics, proteomics, and metabonomics and dissected out through genetic investigations in healthy and diseased individuals. We characterized the genomic, metabolic, and physiological divergence of several inbred rat strains--Brown Norway, Lewis, Wistar Kyoto, Fisher (F344)--frequently used as healthy controls in genetic studies of the cardiometabolic syndrome. Hierarchical clustering of (1)H NMR-based metabolic profiles (n = 20 for urine, n = 16 for plasma) identified metabolic phenotype (metabotype) divergence patterns similar to the phylogenetic variability based on single nucleotide polymorphisms. However, the observed urinary metabotype variation exceeded that explainable by genetic polymorphisms. To understand further this natural variation, we used an integrative, knowledge-based network biology metabolic pathway analysis approach, coined Metabolite-Set Enrichment Analysis (MSEA). MSEA reveals that homeostasis and physiological plasticity can be achieved despite widespread divergences in glucose, lipid, amino acid, and energy metabolism in the host, together with different gut microbiota contributions suggestive of strain-specific transgenomic interactions. This work illustrates the concept of natural metabolomic variation, leading to physiologically stable albeit diverse strategies within the range of normality, all of which are highly relevant to animal model physiology, genetical genomics, and patient stratification in personalized healthcare.

Insulin resistance plays a central role in type 2 diabetes and obesity, which develop as a consequence of genetic and environmental factors. Dietary changes including high fat diet (HFD) feeding promotes insulin resistance in rodent models which present useful systems for studying interactions between genetic background and environmental influences contributing to disease susceptibility and progression. We applied a combination of classical physiological, biochemical and hormonal studies and plasma (1)H NMR spectroscopy-based metabonomics to characterize the phenotypic and metabotypic consequences of HFD (40%) feeding in inbred mouse strains (C57BL/6, 129S6, BALB/c, DBA/2, C3H) frequently used in genetic studies. We showed the wide range of phenotypic and metabonomic adaptations to HFD across the five strains and the increased nutrigenomic predisposition of 129S6 and C57BL/6 to insulin resistance and obesity relative to the other strains. In contrast mice of the BALB/c and DBA/2 strains showed relative resistance to HFD-induced glucose intolerance and obesity. Hierarchical metabonomic clustering derived from (1)H NMR spectral data of the strains provided a phylometabonomic classification of strain-specific metabolic features and differential responses to HFD which closely match SNP-based phylogenetic relationships between strains. Our results support the concept of genomic clustering of functionally related genes and provide important information for defining biological markers predicting spontaneous susceptibility to insulin resistance and pathological adaptations to fat feeding.

Aims/hypothesis: Complex changes in gene expression are associated with insulin resistance and non-alcoholic fatty liver disease (NAFLD) promoted by feeding a high-fat diet (HFD). We used functional genomic technologies to document molecular mechanisms associated with diet-induced NAFLD., Materials and Methods: Male 129S6 mice were fed a diet containing 40% fat (high-fat diet, HFD) for 15 weeks. Glucose tolerance, in vivo insulin secretion, plasma lipid profile and adiposity were determined. Plasma metabonomics and liver transcriptomics were used to identify changes in gene expression associated with HFD-induced NAFLD., Results: In HFD-fed mice, NAFLD and impaired glucose and lipid homeostasis were associated with increased hepatic transcription of genes involved in fatty acid uptake, intracellular transport, modification and elongation, whilst genes involved in beta-oxidation and lipoprotein secretion were, paradoxically, also upregulated. NAFLD developed despite strong and sustained downregulation of transcription of the gene encoding stearoyl-coenzyme A desaturase 1 (Scd1) and uncoordinated regulation of transcription of Scd1 and the gene encoding sterol regulatory element binding factor 1c (Srebf1c) transcription. Inflammatory mechanisms appeared to be stimulated by HFD., Conclusions/interpretation: Our results provide an accurate representation of subtle changes in metabolic and gene expression regulation underlying disease-promoting and compensatory mechanisms, collectively contributing to diet-induced insulin resistance and NAFLD. They suggest that proposed models of NAFLD pathogenesis can be enriched with novel diet-reactive genes and disease mechanisms.

Characterizing the relationships between genomic and phenotypic variation is essential to understanding disease etiology. Information-dense data sets derived from pathophysiological, proteomic and transcriptomic profiling have been applied to map quantitative trait loci (QTLs). Metabolic traits, already used in QTL studies in plants, are essential phenotypes in mammalian genetics to define disease biomarkers. Using a complex mammalian system, here we show chromosomal mapping of untargeted plasma metabolic fingerprints derived from NMR spectroscopic analysis in a cross between diabetic and control rats. We propose candidate metabolites for the most significant QTLs. Metabolite profiling in congenic strains provided evidence of QTL replication. Linkage to a gut microbial metabolite (benzoate) can be explained by deletion of a uridine diphosphate glucuronosyltransferase. Mapping metabotypic QTLs provides a practical approach to understanding genome-phenotype relationships in mammals and may uncover deeper biological complexity, as extended genome (microbiome) perturbations that affect disease processes through transgenomic effects may influence QTL detection.