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The etiology of diabetic nephropathy in type 2 diabetes is multifactorial. Sustained hyperglycemia is a major contributor, but additional contributions come from the hypertension, obesity, and hyperlipidemia that are also commonly present in patients with type 2 diabetes and nephropathy. The leptin deficient BTBR ob/ob mouse is a model of type 2 diabetic nephropathy in which hyperglycemia, obesity, and hyperlipidemia, but not hypertension, are present. We have shown that reversal of the constellation of these metabolic abnormalities with leptin replacement can reverse the morphologic and functional manifestations of diabetic nephropathy. Here we tested the hypothesis that reversal specifically of the hypertriglyceridemia, using an antisense oligonucleotide directed against ApoC-III, an apolipoprotein that regulates the interactions of VLDL (very low density lipoproteins) with the LDL receptor, is sufficient to ameliorate the nephropathy of Type 2 diabetes. Antisense treatment resulted in reduction of circulating ApoC-III protein levels and resulted in substantial lowering of triglycerides to near-normal levels in diabetic mice versus controls. Antisense treatment did not ameliorate proteinuria or pathologic manifestations of diabetic nephropathy, including podocyte loss. These studies indicate that pathologic manifestations of diabetic nephropathy are unlikely to be reduced by lipid-lowering therapeutics alone, but does not preclude a role for such interventions to be used in conjunction with other therapeutics commonly employed in the treatment of diabetes and its complications.

Genetic susceptibility to type 2 diabetes is primarily due to β cell dysfunction. However, a genetic study to directly interrogate β cell function ex vivo has never been previously performed. We isolated 233,447 islets from 483 Diversity Outbred (DO) mice maintained on a Western-style diet, and measured insulin secretion in response to a variety of secretagogues. Insulin secretion from DO islets ranged greater than 1000-fold even though none of the mice were diabetic. The insulin secretory response to each secretagogue had a unique genetic architecture; some of the loci were specific for one condition, whereas others overlapped. Human loci that are syntenic to many of the insulin secretion quantitative trait loci (QTL) from mice are associated with diabetes-related SNPs in human genome-wide association studies. We report on 3 genes, Ptpn18, Hunk, and Zfp148, where the phenotype predictions from the genetic screen were fulfilled in our studies of transgenic mouse models. These 3 genes encode a nonreceptor type protein tyrosine phosphatase, a serine/threonine protein kinase, and a Krϋppel-type zinc-finger transcription factor, respectively. Our results demonstrate that genetic variation in insulin secretion that can lead to type 2 diabetes is discoverable in nondiabetic individuals.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a recently validated therapeutic target for lowering low-density lipoprotein cholesterol (LDL-C). Through phenotypic screening, we previously discovered a class of small-molecules with a 2,3′-diindolymethane (DIM) skeleton that can decrease the expression of PCSK9. But these compounds have low potency and low metabolically stability. After performing structure-activity relationship (SAR) optimization by nitrogen scan, deuterium substitution and fluorine scan, we identified a series of much more potent and metabolically stable PCSK9 modulators. A preliminary in vivo pharmacokinetic study was performed for representative analogues difluorodiindolyketone (DFDIK) 12 and difluorobenzoimidazolylindolylketone (DFBIIK-1) 13. The in vitro metabolic stability correlate well with the in vivo data. The most potent compound 21 has the EC50 of 0.15 nM. Our SAR studies also indicated that the NH on the indole ring of 21 can tolerate more function groups, which may facilitate the mechanism of action studies and also allow further improvement of the pharmacological properties.

In humans, nonalcoholic fatty liver disease (NAFLD) is the most prevalent liver disease due to the increased prevalence of obesity. While treatment of NAFLD is often geared toward lifestyle changes, such as diet and exercise, the use of dietary supplements such as probiotics is underinvestigated. Here, we report that probiotic Lactobacillus reuteri reduces fatty liver in a mouse model of diet-induced obesity. This phenotype was further enhanced upon delivery of recombinant interleukin-22 by engineered Lactobacillus reuteri. These observations pave the road to a better understanding of probiotic mechanisms driving the reduction of diet-induced steatosis and to development of next-generation probiotics for use in the clinic. Ultimately, these studies may lead to rational selection of (engineered) probiotics to ameliorate fatty liver disease., The incidence of metabolic syndrome continues to rise globally. In mice, intravenous administration of interleukin-22 (IL-22) ameliorates various disease phenotypes associated with diet-induced metabolic syndrome. In patients, oral treatment is favored over intravenous treatment, but methodologies to deliver IL-22 via the oral route are nonexistent. The goal of this study was to assess to what extent engineered Lactobacillus reuteri secreting IL-22 could ameliorate nonalcoholic fatty liver disease. We used a mouse model of diet-induced obesity and assessed various markers of metabolic syndrome following treatment with L. reuteri and a recombinant derivative. Mice that received an 8-week treatment of wild-type probiotic gained less weight and had a smaller fat pad than the control group, but these phenotypes were not further enhanced by recombinant L. reuteri. However, L. reuteri secreting IL-22 significantly reduced liver weight and triglycerides at levels that exceeded those of the probiotic wild-type treatment group. Our findings are interesting in light of the observed phenotypes associated with reduced nonalcoholic liver disease, in humans the most prevalent chronic liver disease, following treatment of a next-generation probiotic that is administered orally. Once biological and environmental containment strategies are in place, therapeutic applications of recombinant Lactobacillus reuteri are on the horizon. IMPORTANCE In humans, nonalcoholic fatty liver disease (NAFLD) is the most prevalent liver disease due to the increased prevalence of obesity. While treatment of NAFLD is often geared toward lifestyle changes, such as diet and exercise, the use of dietary supplements such as probiotics is underinvestigated. Here, we report that probiotic Lactobacillus reuteri reduces fatty liver in a mouse model of diet-induced obesity. This phenotype was further enhanced upon delivery of recombinant interleukin-22 by engineered Lactobacillus reuteri. These observations pave the road to a better understanding of probiotic mechanisms driving the reduction of diet-induced steatosis and to development of next-generation probiotics for use in the clinic. Ultimately, these studies may lead to rational selection of (engineered) probiotics to ameliorate fatty liver disease.

The majority of gene loci that have been associated with type 2 diabetes play a role in pancreatic islet function. To evaluate the role of islet gene expression in the etiology of diabetes, we sensitized a genetically diverse mouse population with a Western diet high in fat (45% kcal) and sucrose (34%) and carried out genome-wide association mapping of diabetes-related phenotypes. We quantified mRNA abundance in the islets and identified 18,820 expression QTL. We applied mediation analysis to identify candidate causal driver genes at loci that affect the abundance of numerous transcripts. These include two genes previously associated with monogenic diabetes (PDX1 and HNF4A), as well as three genes with nominal association with diabetes-related traits in humans (FAM83E, IL6ST, and SAT2). We grouped transcripts into gene modules and mapped regulatory loci for modules enriched with transcripts specific for α-cells, and another specific for δ-cells. However, no single module enriched for β-cell-specific transcripts, suggesting heterogeneity of gene expression patterns within the β-cell population. A module enriched in transcripts associated with branched-chain amino acid metabolism was the most strongly correlated with physiological traits that reflect insulin resistance. Although the mice in this study were not overtly diabetic, the analysis of pancreatic islet gene expression under dietary-induced stress enabled us to identify correlated variation in groups of genes that are functionally linked to diabetes-associated physiological traits. Our analysis suggests an expected degree of concordance between diabetes-associated loci in the mouse and those found in human populations, and demonstrates how the mouse can provide evidence to support nominal associations found in human genome-wide association mapping.

Hepatic stellate cell (HSC) activation occurs along with decreased Perilipin5 (Plin5) and liver fatty acid-binding protein (L-Fabp) expression and coincident lipid droplet (LD) depletion. Conversely, the activated phenotype is reversible in WT HSCs upon forced expression of Plin5. Here, we asked if L-Fabp expression is required for Plin5-mediated rescue of the quiescent phenotype. Lentiviral Plin5 transduction of passaged L-Fabp(−/−) HSCs failed to reverse activation markers or restore lipogenic gene expression and LD formation. However, adenoviral L-Fabp infection of lentiviral Plin5 transduced L-Fabp(−/−) HSCs restored both the quiescent phenotype and LD formation, an effect also mediated by adenoviral intestine-Fabp or adipocyte-Fabp. Expression of exogenous Plin5 in activated WT HSCs induced a transcriptional program of lipogenic gene expression including endogenous L-Fabp, but none of the other FABPs. We further demonstrated that selective, small molecule inhibition of endogenous L-Fabp also eliminated the ability of exogenous Plin5 to rescue LD formation and reverse activation of WT HSCs. This functional coordination of L-Fabp with Plin5 was 5′-AMP-activated protein kinase (AMPK)-dependent and was eliminated by AMPK inhibition. Taken together, our results indicate that L-Fabp is required for Plin5 to activate a transcriptional program that restores LD formation and reverses HSC activation.

The compensatory proliferation of insulin-producing β cells is critical to maintaining glucose homeostasis at the early stage of type 2 diabetes. Failure of β cells to proliferate results in hyperglycemia and insulin dependence in patients. To understand the effect of the interplay between β cell compensation and lipid metabolism upon obesity and peripheral insulin resistance, we eliminated LDL receptor–related protein 1 (LRP1), a pleiotropic mediator of cholesterol, insulin, energy metabolism, and other cellular processes, in β cells. Upon high-fat diet exposure, LRP1 ablation significantly impaired insulin secretion and proliferation of β cells. The diminished insulin signaling was partly contributed to by the hypersensitivity to glucose-induced, Ca2+-dependent activation of Erk and the mTORC1 effector p85 S6K1. Surprisingly, in LRP1-deficient islets, lipotoxic sphingolipids were mitigated by improved lipid metabolism, mediated at least in part by the master transcriptional regulator PPARγ2. Acute overexpression of PPARγ2 in β cells impaired insulin signaling and insulin secretion. Elimination of Apbb2, a functional regulator of LRP1 cytoplasmic domain, also impaired β cell function in a similar fashion. In summary, our results uncover the double-edged effects of intracellular lipid metabolism on β cell function and viability in obesity and type 2 diabetes and highlight LRP1 as an essential regulator of these processes.

O-Linked glycosylation often involves the covalent attachment of sugar moieties to the hydroxyl group of serine or threonine on proteins/peptides. Despite growing interest in glycoproteins, little attention has been directed to glycosylated signaling peptides, largely due to lack of enabling analytical tools. Here we explore the occurrence of naturally O-linked glycosylation on the signaling peptides extracted from mouse and human pancreatic islets using mass spectrometry (MS). A novel targeted MS-based method is developed to increase the likelihood of capturing these modified signaling peptides and to provide improved sequence coverage and accurate glycosite localization, enabling the first large-scale discovery of O-glycosylation on signaling peptides. Several glycosylated signaling peptides with multiple glycoforms are identified, including the first report of glycosylated insulin-B chain and insulin-C peptide and BigLEN. This discovery may reveal potential novel functions as glycosylation could influence their conformation and biostability. Given the importance of insulin and its related peptide hormones and previous studies of glycosylated insulin analogues, this natural glycosylation may provide important insights into diabetes research and therapeutic treatments.

Genetic variation in the FAM13A (Family with Sequence Similarity 13 Member A) locus has been associated with several glycemic and metabolic traits in genome-wide association studies (GWAS). Here, we demonstrate that in humans, FAM13A alleles are associated with increased FAM13A expression in subcutaneous adipose tissue (SAT) and an insulin resistance-related phenotype (e.g. higher waist-to-hip ratio and fasting insulin levels, but lower body fat). In human adipocyte models, knockdown of FAM13A in preadipocytes accelerates adipocyte differentiation. In mice, Fam13a knockout (KO) have a lower visceral to subcutaneous fat (VAT/SAT) ratio after high-fat diet challenge, in comparison to their wild-type counterparts. Subcutaneous adipocytes in KO mice show a size distribution shift toward an increased number of smaller adipocytes, along with an improved adipogenic potential. Our results indicate that GWAS-associated variants within the FAM13A locus alter adipose FAM13A expression, which in turn, regulates adipocyte differentiation and contribute to changes in body fat distribution., Genetic variants in the FAM13A locus have been associated with anthropometric and glycemic traits. Here, using fine-mapping, in vitro knockdown studies in pre-adipocytes and in vivo knockout in mice, the authors show that FAM13A is involved in regulating fat distribution and metabolic traits.

The microbial communities that inhabit the distal gut of humans and other mammals exhibit large inter-individual variation. While host genetics is a known factor that influences gut microbiota composition, the mechanisms underlying this variation remain largely unknown. Bile acids (BAs) are hormones that are produced by the host and chemically modified by gut bacteria. BAs serve as environmental cues and nutrients to microbes, but they can also have antibacterial effects. We hypothesized that host genetic variation in BA metabolism and homeostasis influence gut microbiota composition. To address this, we used the Diversity Outbred (DO) stock, a population of genetically distinct mice derived from eight founder strains. We characterized the fecal microbiota composition and plasma and cecal BA profiles from 400 DO mice maintained on a high-fat high-sucrose diet for ∼22 weeks. Using quantitative trait locus (QTL) analysis, we identified several genomic regions associated with variations in both bacterial and BA profiles. Notably, we found overlapping QTL forTuricibacter sp.and plasma cholic acid, which mapped to a locus containing the gene for the ileal bile acid transporter,Slc10a2. Mediation analysis and subsequent follow-up validation experiments suggest that differences inSlc10a2gene expression associated with the different strains influences levels of both traits and revealed novel interactions betweenTuricibacterand BAs. This work illustrates how systems genetics can be utilized to generate testable hypotheses and provide insight into host-microbe interactions.Author summaryInter-individual variation in the composition of the intestinal microbiota can in part be attributed to host genetics. However, the specific genes and genetic variants underlying differences in the microbiota remain largely unknown. To address this, we profiled the fecal microbiota composition of 400 genetically distinct mice, for which genotypic data is available. We identified many loci of the mouse genome associated with changes in abundance of bacterial taxa. One of these loci is also associated with changes in the abundance of plasma bile acids—metabolites generated by the host that influence both microbiota composition and host physiology. Follow up validation experiments provide mechanistic insights linking host genetic differences, with changes in ileum gene expression, bile acid-bacteria interactions and bile acid homeostasis. Together, this work demonstrates how genetic approaches can be used to generate testable hypothesis to yield novel insight into how host genetics shape gut microbiota composition.

Anti-silencing function 1 (ASF1) is a histone H3-H4 chaperone involved in DNA replication and repair, and transcriptional regulation. Here, we identify ASF1B, the mammalian paralog to ASF1, as a proliferation-inducing histone chaperone in human β-cells. Overexpression of ASF1B led to distinct transcriptional signatures consistent with increased cellular proliferation and reduced cellular death. Using multiple methods of monitoring proliferation and mitotic progression, we show that overexpression of ASF1B is sufficient to induce human β-cell proliferation. Co-expression of histone H3.3 further augmented β-cell proliferation, whereas suppression of endogenous H3.3 attenuated the stimulatory effect of ASF1B. Using the histone binding-deficient mutant of ASF1B (V94R), we show that histone binding to ASF1B is required for the induction of β-cell proliferation. In contrast to H3.3, overexpression of histone H3 variants H3.1 and H3.2 did not have an impact on ASF1B-mediated induction of proliferation. Our findings reveal a novel role of ASF1B in human β-cell replication and show that ASF1B and histone H3.3A synergistically stimulate human β-cell proliferation.

We recently identified human N-acetyltransferase 2 (NAT2) as an insulin resistance (IR) gene. Here we examine the cellular mechanism linking NAT2 to IR and find that Nat1 (mouse ortholog of NAT2) is co-regulated with key regulators of mitochondria. RNA-interference mediated silencing of Nat1 led to mitochondrial dysfunction characterized by increased intracellular reactive oxygen species and mitochondrial fragmentation as well as decreased mitochondrial membrane potential, biogenesis, mass, cellular respiration and ATP generation. These effects were consistent in 3T3-L1 adipocytes, C2C12 myoblasts and in tissues from Nat1 deficient mice including white adipose tissue, heart and skeletal muscle. Nat1 deficient mice had changes in plasma metabolites and lipids consistent with a decreased ability to utilize fats for energy and a decrease in basal metabolic rate and exercise capacity without altered thermogenesis. Collectively, our results suggest that Nat1 deficiency results in mitochondrial dysfunction, which may constitute a mechanistic link between this gene and IR.

In a Diversity Outbred mouse project with genotype data on 500 mice, including 297 with microbiome data, we identified three sets of sample mix-ups (two pairs and one trio) as well as at least 15 microbiome samples that appear to be mixtures of pairs of mice. The microbiome data consisted of shotgun sequencing reads from fecal DNA, used to characterize the gut microbial communities present in these mice. These sequence reads included sufficient reads derived from the host mouse to identify the individual. A number of microbiome samples appeared to contain a mixture of DNA from two mice. We describe a method for identifying sample mix-ups in such microbiome data, as well as a method for evaluating sample mixtures in this context.

The membrane transporter AT‐1/SLC33A1 translocates cytosolic acetyl‐CoA into the lumen of the endoplasmic reticulum (ER), participating in quality control mechanisms within the secretory pathway. Mutations and duplication events in AT‐1/SLC33A1 are highly pleiotropic and have been linked to diseases such as spastic paraplegia, developmental delay, autism spectrum disorder, intellectual disability, propensity to seizures, and dysmorphism. Despite these known associations, the biology of this key transporter is only beginning to be uncovered. Here, we show that systemic overexpression of AT‐1 in the mouse leads to a segmental form of progeria with dysmorphism and metabolic alterations. The phenotype includes delayed growth, short lifespan, alopecia, skin lesions, rectal prolapse, osteoporosis, cardiomegaly, muscle atrophy, reduced fertility, and anemia. In terms of homeostasis, the AT‐1 overexpressing mouse displays hypocholesterolemia, altered glycemia, and increased indices of systemic inflammation. Mechanistically, the phenotype is caused by a block in Atg9a‐Fam134b‐LC3β and Atg9a‐Sec62‐LC3β interactions, and defective reticulophagy, the autophagic recycling of the ER. Inhibition of ATase1/ATase2 acetyltransferase enzymes downstream of AT‐1 restores reticulophagy and rescues the phenotype of the animals. These data suggest that inappropriately elevated acetyl‐CoA flux into the ER directly induces defects in autophagy and recycling of subcellular structures and that this diversion of acetyl‐CoA from cytosol to ER is causal in the progeria phenotype. Collectively, these data establish the cytosol‐to‐ER flux of acetyl‐CoA as a novel event that dictates the pace of aging phenotypes and identify intracellular acetyl‐CoA‐dependent homeostatic mechanisms linked to metabolism and inflammation.

The mouse is a critical model in diabetes research, but most research in mice has been limited to a small number of mouse strains and limited genetic variation. Using the eight founder strains and both sexes of the Collaborative Cross (C57BL/6J (B6), A/J, 129S1/SvImJ (129), NOD/ShiLtJ (NOD), NZO/HILtJ (NZO), PWK/PhJ (PWK), WSB/EiJ (WSB), and CAST/EiJ (CAST)), we investigated the genetic dependence of diabetes-related metabolic phenotypes and insulin secretion. We found that strain background is associated with an extraordinary range in body weight, plasma glucose, insulin, triglycerides, and insulin secretion. Our whole-islet proteomic analysis of the eight mouse strains demonstrates that genetic background exerts a strong influence on the islet proteome that can be linked to the differences in diabetes-related metabolic phenotypes and insulin secretion. We computed protein modules consisting of highly correlated proteins that enrich for biological pathways and provide a searchable database of the islet protein expression profiles. To validate the data resource, we identified tyrosine hydroxylase (Th), a key enzyme in catecholamine synthesis, as a protein that is highly expressed in β-cells of PWK and CAST islets. We show that CAST islets synthesize elevated levels of dopamine, which suppresses insulin secretion. Prior studies, using only the B6 strain, concluded that adult mouse islets do not synthesize l-3,4-dihydroxyphenylalanine (l-DOPA), the product of Th and precursor of dopamine. Thus, the choice of the CAST strain, guided by our islet proteomic survey, was crucial for these discoveries. In summary, we provide a valuable data resource to the research community, and show that proteomic analysis identified a strain-specific pathway by which dopamine synthesized in β-cells inhibits insulin secretion.

Genotyping microarrays are an important resource for genetic mapping, population genetics, and monitoring of the genetic integrity of laboratory stocks. We have developed the third generation of the Mouse Universal Genotyping Array (MUGA) series, GigaMUGA, a 143,259-probe Illumina Infinium II array for the house mouse (Mus musculus). The bulk of the content of GigaMUGA is optimized for genetic mapping in the Collaborative Cross and Diversity Outbred populations, and for substrain-level identification of laboratory mice. In addition to 141,090 single nucleotide polymorphism probes, GigaMUGA contains 2006 probes for copy number concentrated in structurally polymorphic regions of the mouse genome. The performance of the array is characterized in a set of 500 high-quality reference samples spanning laboratory inbred strains, recombinant inbred lines, outbred stocks, and wild-caught mice. GigaMUGA is highly informative across a wide range of genetically diverse samples, from laboratory substrains to other Mus species. In addition to describing the content and performance of the array, we provide detailed probe-level annotation and recommendations for quality control.

Studies of the genetic loci that contribute to variation in gene expression frequently identify loci with broad effect on gene expression: expression quantitative trait locus (eQTL) hotspots. We describe a set of exploratory graphical methods as well as a formal likelihood-based test for assessing whether a given hotspot is due to one or multiple polymorphisms. We first look at the pattern of effects of the locus on the expression traits that map to the locus: the direction of the effects, as well as the degree of dominance. A second technique is to focus on the individuals that exhibit no recombination event in the region, apply dimensionality reduction (such as with linear discriminant analysis) and compare the phenotype distribution in the non-recombinants to that in the recombinant individuals: If the recombinant individuals display a different expression pattern than the non-recombinants, this indicates the presence of multiple causal polymorphisms. In the formal likelihood-based test, we compare a two-locus model, with each expression trait affected by one or the other locus, to a single-locus model. We apply our methods to a large mouse intercross with gene expression microarray data on six tissues., 40 pages, 6 figures, 3 supplemental figures, and a separate PDF file (FileS1.pdf) with an additional 35 pages of figures; made small changes to text on pages 26-31 in response to reviewers' comments; corrected a number of typographical errors and added acknowledgment of an additional grant

RNA editing refers to post-transcriptional processes that alter the base sequence of RNA. Recently, hundreds of new RNA editing targets have been reported. However, the mechanisms that determine the specificity and degree of editing are not well understood. We examined quantitative variation of site-specific editing in a genetically diverse multiparent population, Diversity Outbred mice, and mapped polymorphic loci that alter editing ratios globally for C-to-U editing and at specific sites for A-to-I editing. An allelic series in the C-to-U editing enzyme Apobec1 influences the editing efficiency of Apob and 58 additional C-to-U editing targets. We identified 49 A-to-I editing sites with polymorphisms in the edited transcript that alter editing efficiency. In contrast to the shared genetic control of C-to-U editing, most of the variable A-to-I editing sites were determined by local nucleotide polymorphisms in proximity to the editing site in the RNA secondary structure. Our results indicate that RNA editing is a quantitative trait subject to genetic variation and that evolutionary constraints have given rise to distinct genetic architectures in the two canonical types of RNA editing.

Identifying the genetic basis of complex traits is an important problem with the potential to impact a broad range of biological endeavors. A number of effective statistical methods are available for quantitative trait loci (QTL) mapping that allow for the efficient identification of multiple, potentially interacting, loci under a variety of experimental conditions. Although proven useful in hundreds of studies, the majority of these methods assumes a single model common to each subject, which may reduce power and accuracy when genetically distinct subclasses exist. To address this, we have developed an approach to enable latent class QTL mapping. The approach combines latent class regression with stepwise variable selection and traditional QTL mapping to estimate the number of subclasses in a population, and to identify the genetic model that best describes each subclass. Simulations demonstrate good performance of the method when latent classes are present as well as when they are not, with accurate estimation of QTL. Application of the method to case studies of obesity and diabetes in mouse gives insight into the genetic basis of related complex traits.

We previously demonstrated that micro-RNAs (miRNAs) 132 and 212 are differentially upregulated in response to obesity in two mouse strains that differ in their susceptibility to obesity-induced diabetes. Here we show the overexpression of miRNAs 132 and 212 enhances insulin secretion (IS) in response to glucose and other secretagogues including nonfuel stimuli. We determined that carnitine acyl-carnitine translocase (CACT; Slc25a20) is a direct target of these miRNAs. CACT is responsible for transporting long-chain acyl-carnitines into the mitochondria for β-oxidation. Small interfering RNA–mediated knockdown of CACT in β-cells led to the accumulation of fatty acyl-carnitines and enhanced IS. The addition of long-chain fatty acyl-carnitines promoted IS from rat insulinoma β-cells (INS-1) as well as primary mouse islets. The effect on INS-1 cells was augmented in response to suppression of CACT. A nonhydrolyzable ether analog of palmitoyl-carnitine stimulated IS, showing that β-oxidation of palmitoyl-carnitine is not required for its stimulation of IS. These studies establish a link between miRNA-dependent regulation of CACT and fatty acyl-carnitine–mediated regulation of IS.

Glucagon-like peptide-1 (GLP-1) is a natural agonist for GLP-1R, a G protein-coupled receptor (GPCR) on the surface of pancreatic β cells. GLP-1R agoinsts are attractive for treatment of type 2 diabetes, but GLP-1 itself is rapidly degraded by peptidases in vivo. We describe a design strategy for retaining GLP-1-like activity while engendering prolonged activity in vivo, based on strategic replacement of native α residues with conformationally constrained β-amino acid residues. This backbone-modification approach may be useful for developing stabilized analogues of other peptide hormones.

Massively parallel RNA sequencing (RNA-seq) has yielded a wealth of new insights into transcriptional regulation. A first step in the analysis of RNA-seq data is the alignment of short sequence reads to a common reference genome or transcriptome. Genetic variants that distinguish individual genomes from the reference sequence can cause reads to be misaligned, resulting in biased estimates of transcript abundance. Fine-tuning of read alignment algorithms does not correct this problem. We have developed Seqnature software to construct individualized diploid genomes and transcriptomes for multiparent populations and have implemented a complete analysis pipeline that incorporates other existing software tools. We demonstrate in simulated and real data sets that alignment to individualized transcriptomes increases read mapping accuracy, improves estimation of transcript abundance, and enables the direct estimation of allele-specific expression. Moreover, when applied to expression QTL mapping we find that our individualized alignment strategy corrects false-positive linkage signals and unmasks hidden associations. We recommend the use of individualized diploid genomes over reference sequence alignment for all applications of high-throughput sequencing technology in genetically diverse populations.

Current efforts in systems genetics have focused on the development of statistical approaches that aim to disentangle causal relationships among molecular phenotypes in segregating populations. Reverse engineering of transcriptional networks plays a key role in the understanding of gene regulation. However, transcriptional regulation is only one possible mechanism, as methylation, phosphorylation, direct protein–protein interaction, transcription factor binding, etc., can also contribute to gene regulation. These additional modes of regulation can be interpreted as unobserved variables in the transcriptional gene network and can potentially affect its reconstruction accuracy. We develop tests of causal direction for a pair of phenotypes that may be embedded in a more complicated but unobserved network by extending Vuong’s selection tests for misspecified models. Our tests provide a significance level, which is unavailable for the widely used AIC and BIC criteria. We evaluate the performance of our tests against the AIC, BIC, and a recently published causality inference test in simulation studies. We compare the precision of causal calls using biologically validated causal relationships extracted from a database of 247 knockout experiments in yeast. Our model selection tests are more precise, showing greatly reduced false-positive rates compared to the alternative approaches. In practice, this is a useful feature since follow-up studies tend to be time consuming and expensive and, hence, it is important for the experimentalist to have causal predictions with low false-positive rates.

Genetic variation drives phenotypic diversity and influences the predisposition to metabolic disease. Here, we characterize the metabolic phenotypes of eight genetically distinct inbred mouse strains in response to a high-fat/high-sucrose diet. We found significant variation in diabetes-related phenotypes and gut microbiota composition among the different mouse strains in response to the dietary challenge and identified taxa associated with these traits. Follow-up microbiota transplant experiments showed that altering the composition of the gut microbiota modifies strain-specific susceptibility to diet-induced metabolic disease. Animals harboring microbial communities with enhanced capacity for processing dietary sugars and for generating hydrophobic bile acids showed increased susceptibility to metabolic disease. Notably, differences in glucose-stimulated insulin secretion between different mouse strains were partially recapitulated via gut microbiota transfer. Our results suggest that the gut microbiome contributes to the genetic and phenotypic diversity observed among mouse strains and provide a link between the gut microbiome and insulin secretion.

Histone-modifying enzymes regulate transcription and are sensitive to availability of endogenous small-molecule metabolites, allowing chromatin to respond to changes in environment. The gut microbiota produces a myriad of metabolites that affect host physiology and susceptibility to disease, however the underlying molecular events remain largely unknown. Here we demonstrate that microbial colonization regulates global histone acetylation and methylation in multiple host tissues in a diet-dependent manner: consumption of a “Western-type” diet prevents many of the microbiota-dependent chromatin changes that occur in a polysaccharide rich diet. Finally, we demonstrate that supplementation of germ-free mice with short-chain fatty acids, major products of gut bacterial fermentation, is sufficient to recapitulate chromatin modification states and transcriptional responses of colonization on host epigenetic programming. These findings have profound implications for understanding the complex functional interactions between diet, gut microbiota, and host health.

SummaryMitochondria are dynamic organelles that play a central role in a diverse array of metabolic processes. Elucidating mitochondrial adaptations to changing metabolic demands and the pathogenic alterations that underlie metabolic disorders represent principal challenges in cell biology. Here, we performed multiplexed quantitative mass spectrometry-based proteomics to chart the remodeling of the mouse liver mitochondrial proteome and phosphoproteome during both acute and chronic physiological transformations in more than 50 mice. Our analyses reveal that reversible phosphorylation is widespread in mitochondria, and is a key mechanism for regulating ketogenesis during the onset of obesity and type 2 diabetes. Specifically, we have demonstrated that phosphorylation of a conserved serine on Hmgcs2 (S456) significantly enhances its catalytic activity in response to increased ketogenic demand. Collectively, our work describes the plasticity of this organelle at high resolution and provides a framework for investigating the roles of proteome restructuring and reversible phosphorylation in mitochondrial adaptation.

The mammalian intestinal tract contains a complex microbial ecosystem with many lysogens, which are bacteria containing dormant phages (prophages) inserted within their genomes. Approximately half of intestinal viruses are derived from lysogens, suggesting that these bacteria encounter triggers that promote phage production. We show that prophages of the gut symbiont Lactobacillus reuteri are activated during gastrointestinal transit and that phage production is further increased in response to a fructose-enriched diet. Fructose and exposure to short-chain fatty acids activate the Ack pathway, involved in generating acetic acid, which in turn triggers the bacterial stress response that promotes phage production. L. reuteri mutants of the Ack pathway or RecA, a stress response component, exhibit decreased phage production. Thus, prophages in a gut symbiont can be induced by diet and metabolites affected by diet, which provides a potential mechanistic explanation for the effects of diet on the intestinal phage community.

SummaryWe introduce neutron-encoded (NeuCode) amino acid labeling of mice as a strategy for multiplexed proteomic analysis in vivo. Using NeuCode, we characterize an inducible knockout mouse model of Bap1, a tumor suppressor and deubiquitinase whose in vivo roles outside of cancer are not well established. NeuCode proteomics revealed altered metabolic pathways following Bap1 deletion, including profound elevation of cholesterol biosynthetic machinery coincident with reduced expression of gluconeogenic and lipid homeostasis proteins in liver. Bap1 loss increased pancreatitis biomarkers and reduced expression of mitochondrial proteins. These alterations accompany a metabolic remodeling with hypoglycemia, hypercholesterolemia, hepatic lipid loss, and acinar cell degeneration. Liver-specific Bap1 null mice present with fully penetrant perinatal lethality, severe hypoglycemia, and hepatic lipid deficiency. This work reveals Bap1 as a metabolic regulator in liver and pancreas, and it establishes NeuCode as a reliable proteomic method for deciphering in vivo biology.

We surveyed gene expression in six tissues in an F2 intercross between mouse strains C57BL/6J (abbreviated B6) and BTBR T+ tf /J (abbreviated BTBR) made genetically obese with the Leptin(ob) mutation. We identified a number of expression quantitative trait loci (eQTL) affecting the expression of numerous genes distal to the locus, called trans-eQTL hotspots. Some of these trans-eQTL hotspots showed effects in multiple tissues, whereas some were specific to a single tissue. An unusually large number of transcripts (7% of genes) mapped in trans to a hotspot on chromosome 6, specifically in pancreatic islets. By considering the first two principal components of the expression of genes mapping to this region, we were able to convert the multivariate phenotype into a simple Mendelian trait. Fine-mapping the locus by traditional methods reduced the QTL interval to a 298 kb region containing only three genes, including Slco1a6, one member of a large family of organic anion transporters. Direct genomic sequencing of all Slco1a6 exons identified a non-synonymous coding SNP that converts a highly conserved proline residue at amino acid position 564 to serine. Molecular modeling suggests that Pro564 faces an aqueous pore within this 12-transmembrane domain-spanning protein. When transiently overexpressed in HEK293 cells, BTBR OATP1A6-mediated cellular uptake of the bile acid taurocholic acid (TCA) was enhanced compared to B6 OATP1A6. Our results suggest that genetic variation in Slco1a6 leads to altered transport of TCA (and potentially other bile acids) by pancreatic islets, resulting in broad gene regulation.

BTBR mice develop severe diabetes in response to genetically induced obesity due to a failure of the β-cells to compensate for peripheral insulin resistance. In analyzing BTBR islet gene expression patterns, we observed that Pgter3, the gene for the prostaglandin E receptor 3 (EP3), was upregulated with diabetes. The EP3 receptor is stimulated by prostaglandin E2 (PGE2) and couples to G-proteins of the Gi subfamily to decrease intracellular cAMP, blunting glucose-stimulated insulin secretion (GSIS). Also upregulated were several genes involved in the synthesis of PGE2. We hypothesized that increased signaling through EP3 might be coincident with the development of diabetes and contribute to β-cell dysfunction. We confirmed that the PGE2-to-EP3 signaling pathway was active in islets from confirmed diabetic BTBR mice and human cadaveric donors, with increased EP3 expression, PGE2 production, and function of EP3 agonists and antagonists to modulate cAMP production and GSIS. We also analyzed the impact of EP3 receptor activation on signaling through the glucagon-like peptide (GLP)-1 receptor. We demonstrated that EP3 agonists antagonize GLP-1 signaling, decreasing the maximal effect that GLP-1 can elicit on cAMP production and GSIS. Taken together, our results identify EP3 as a new therapeutic target for β-cell dysfunction in T2D.

Human genome-wide association studies (GWAS) have shown that genetic variation at >130 gene loci is associated with type 2 diabetes (T2D). We asked if the expression of the candidate T2D-associated genes within these loci is regulated by a common locus in pancreatic islets. Using an obese F2 mouse intercross segregating for T2D, we show that the expression of ~40% of the T2D-associated genes is linked to a broad region on mouse chromosome (Chr) 2. As all but 9 of these genes are not physically located on Chr 2, linkage to Chr 2 suggests a genomic factor(s) located on Chr 2 regulates their expression in trans. The transcription factor Nfatc2 is physically located on Chr 2 and its expression demonstrates cis linkage; i.e., its expression maps to itself. When conditioned on the expression of Nfatc2, linkage for the T2D-associated genes was greatly diminished, supporting Nfatc2 as a driver of their expression. Plasma insulin also showed linkage to the same broad region on Chr 2. Overexpression of a constitutively active (ca) form of Nfatc2 induced β-cell proliferation in mouse and human islets, and transcriptionally regulated more than half of the T2D-associated genes. Overexpression of either ca-Nfatc2 or ca-Nfatc1 in mouse islets enhanced insulin secretion, whereas only ca-Nfatc2 was able to promote β-cell proliferation, suggesting distinct molecular pathways mediating insulin secretion vs. β-cell proliferation are regulated by NFAT. Our results suggest that many of the T2D-associated genes are downstream transcriptional targets of NFAT, and may act coordinately in a pathway through which NFAT regulates β-cell proliferation in both mouse and human islets., Author Summary Genome-wide association studies (GWAS) and linkage studies provide a powerful way to establish a causal connection between a gene locus and a physiological or pathophysiological phenotype. We wondered if candidate genes associated with type 2 diabetes in human populations, in addition to being causal for the disease, could also be intermediate traits in a pathway leading to disease. In addition, we wished to know if there were any regulatory loci that could coordinately drive the expression of these genes in pancreatic islets and thus complete a pathway; i.e. Driver → GWAS candidate expression → type 2 diabetes. Using data from a mouse intercross between a diabetes-susceptible and a diabetes-resistant mouse strain, we found that the expression of ~40% of >130 candidate GWAS genes genetically mapped to a hot spot on mouse chromosome 2. Using a variety of statistical methods, we identified the transcription factor Nfatc2 as the candidate driver. Follow-up experiments showed that overexpression of Nfatc2 does indeed affect the expression of the GWAS genes and regulates β-cell proliferation and insulin secretion. The work shows that in addition to being causal, GWAS candidate genes can be intermediate traits in a pathway leading to disease. Model organisms can be used to explore these novel causal pathways.

Complex diseases result from molecular changes induced by multiple genetic factors and the environment. To derive a systems view of how genetic loci interact in the context of tissue-specific molecular networks, we constructed an F2 intercross comprised of >500 mice from diabetes-resistant (B6) and diabetes-susceptible (BTBR) mouse strains made genetically obese by the Leptinob/ob mutation (Lepob). High-density genotypes, diabetes-related clinical traits, and whole-transcriptome expression profiling in five tissues (white adipose, liver, pancreatic islets, hypothalamus, and gastrocnemius muscle) were determined for all mice. We performed an integrative analysis to investigate the inter-relationship among genetic factors, expression traits, and plasma insulin, a hallmark diabetes trait. Among five tissues under study, there are extensive protein–protein interactions between genes responding to different loci in adipose and pancreatic islets that potentially jointly participated in the regulation of plasma insulin. We developed a novel ranking scheme based on cross-loci protein-protein network topology and gene expression to assess each gene's potential to regulate plasma insulin. Unique candidate genes were identified in adipose tissue and islets. In islets, the Alzheimer's gene App was identified as a top candidate regulator. Islets from 17-week-old, but not 10-week-old, App knockout mice showed increased insulin secretion in response to glucose or a membrane-permeant cAMP analog, in agreement with the predictions of the network model. Our result provides a novel hypothesis on the mechanism for the connection between two aging-related diseases: Alzheimer's disease and type 2 diabetes., Author Summary Alzheimer's disease and type 2 diabetes are two common aging-related diseases. Numerous studies have shown that the two diseases are associated. However, the mechanisms of such connection are not clear. Both diseases are complex diseases that are induced by multiple genetic factors and the environment. To understand the molecular network regulated by complex genetic factors causing type 2 diabetes, we constructed an F2 intercross comprised of >500 mice from diabetes-resistant and diabetic mouse strains. We measured genotypes, clinical traits, and expression profiling in five tissues for each mouse. We then performed an integrative analysis to investigate the inter-relationship among genetic factors, expression traits, and plasma insulin, a hallmark diabetes trait, and developed a novel method for inferring key regulators for regulating plasma insulin. In islets, the Alzheimer's gene App was identified as a top candidate regulator. Islets from 17-week-old, but not 10-week-old, App knockout mice showed increased insulin secretion in response to glucose, in agreement with the predictions of the network model. Our result provides a novel hypothesis on the mechanism for the connection between two aging-related diseases: Alzheimer's disease and type 2 diabetes.

Genome-wide association studies (GWAS) have demonstrated the ability to identify the strongest causal common variants in complex human diseases. However, to date, the massive data generated from GWAS have not been maximally explored to identify true associations that fail to meet the stringent level of association required to achieve genome-wide significance. Genetics of gene expression (GGE) studies have shown promise towards identifying DNA variations associated with disease and providing a path to functionally characterize findings from GWAS. Here, we present the first empiric study to systematically characterize the set of single nucleotide polymorphisms associated with expression (eSNPs) in liver, subcutaneous fat, and omental fat tissues, demonstrating these eSNPs are significantly more enriched for SNPs that associate with type 2 diabetes (T2D) in three large-scale GWAS than a matched set of randomly selected SNPs. This enrichment for T2D association increases as we restrict to eSNPs that correspond to genes comprising gene networks constructed from adipose gene expression data isolated from a mouse population segregating a T2D phenotype. Finally, by restricting to eSNPs corresponding to genes comprising an adipose subnetwork strongly predicted as causal for T2D, we dramatically increased the enrichment for SNPs associated with T2D and were able to identify a functionally related set of diabetes susceptibility genes. We identified and validated malic enzyme 1 (Me1) as a key regulator of this T2D subnetwork in mouse and provided support for the association of this gene to T2D in humans. This integration of eSNPs and networks provides a novel approach to identify disease susceptibility networks rather than the single SNPs or genes traditionally identified through GWAS, thereby extracting additional value from the wealth of data currently being generated by GWAS., Author Summary Genome-wide association studies (GWAS) seek to identify loci in which changes in DNA are correlated with disease. However, GWAS do not necessarily lead directly to genes associated with disease, and they do not typically inform the broader context in which disease genes operate, thereby providing limited insights into the mechanisms driving disease. One critical task to providing further insights into GWAS is developing an understanding of the genetics of gene expression (GGE). We present the first empiric study demonstrating that SNPs in human cohorts that associate with gene expression in liver and adipose tissues are enriched for associating with Type 2 Diabetes (T2D) in humans. By filtering “eSNPs” based on causal gene networks defined in an experimental cross population segregating T2D traits, we demonstrate a dramatically increased enrichment of T2D SNPs that enhance our ability to assess T2D risk. We demonstrate the utility of this approach by identifying malic enzyme 1 (ME1) as a novel T2D susceptibility gene in humans and then functionally validating the causal connection between ME1 and T2D in a mouse knockout model for Me1. This approach provides a path to identifying disease susceptibility networks rather than single SNPs or genes traditionally identified through GWAS.

We previously mapped a type 2 diabetes (T2D) locus on chromosome 16 (Chr 16) in an F2 intercross from the BTBR T (+) tf (BTBR) Lepob/ob and C57BL/6 (B6) Lepob/ob mouse strains. Introgression of BTBR Chr 16 into B6 mice resulted in a consomic mouse with reduced fasting plasma insulin and elevated glucose levels. We derived a panel of sub-congenic mice and narrowed the diabetes susceptibility locus to a 1.6 Mb region. Introgression of this 1.6 Mb fragment of the BTBR Chr 16 into lean B6 mice (B6.16BT36–38) replicated the phenotypes of the consomic mice. Pancreatic islets from the B6.16BT36–38 mice were defective in the second phase of the insulin secretion, suggesting that the 1.6 Mb region encodes a regulator of insulin secretion. Within this region, syntaxin-binding protein 5-like (Stxbp5l) or tomosyn-2 was the only gene with an expression difference and a non-synonymous coding single nucleotide polymorphism (SNP) between the B6 and BTBR alleles. Overexpression of the b-tomosyn-2 isoform in the pancreatic β-cell line, INS1 (832/13), resulted in an inhibition of insulin secretion in response to 3 mM 8-bromo cAMP at 7 mM glucose. In vitro binding experiments showed that tomosyn-2 binds recombinant syntaxin-1A and syntaxin-4, key proteins that are involved in insulin secretion via formation of the SNARE complex. The B6 form of tomosyn-2 is more susceptible to proteasomal degradation than the BTBR form, establishing a functional role for the coding SNP in tomosyn-2. We conclude that tomosyn-2 is the major gene responsible for the T2D Chr 16 quantitative trait locus (QTL) we mapped in our mouse cross. Our findings suggest that tomosyn-2 is a key negative regulator of insulin secretion., Author Summary Humans carry many genetic variants that confer small effects on metabolic traits relevant to type 2 diabetes. These effects are amplified by environmental stressors like obesity. We used morbid obesity as a sensitizer to identify genes that contribute to the diabetes susceptibility of the BTBR mouse strain. Using mapping and breeding strategies, we were able to narrow a genetic region to one containing just 13 genes. One of these genes, tomosyn-2, emerged as a prime candidate. Our functional studies showed that tomosyn-2 is an inhibitor of insulin secretion, and it binds to the proteins involved in the fusion of insulin containing granules with the plasma membrane. We found a coding mutation and demonstrated that this mutation affects the stability of the protein product. Our work with Tomosyn-2 provides new insights into the regulation of insulin secretion and emphasizes that negative regulation is critical for avoiding insulin-induced hypoglycemia.

Although numerous quantitative trait loci (QTL) influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identification of the individual gene(s) and molecular pathways leading to those phenotypes is often elusive. One way to improve understanding of genetic architecture is to classify phenotypes in greater depth by including transcriptional and metabolic profiling. In the current study, we have generated and analyzed mRNA expression and metabolic profiles in liver samples obtained in an F2 intercross between the diabetes-resistant C57BL/6 leptinob/ob and the diabetes-susceptible BTBR leptinob/ob mouse strains. This cross, which segregates for genotype and physiological traits, was previously used to identify several diabetes-related QTL. Our current investigation includes microarray analysis of over 40,000 probe sets, plus quantitative mass spectrometry-based measurements of sixty-seven intermediary metabolites in three different classes (amino acids, organic acids, and acyl-carnitines). We show that liver metabolites map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal networks for control of specific metabolic processes in liver. As a proof of principle of the practical significance of this integrative approach, we illustrate the construction of a specific causal network that links gene expression and metabolic changes in the context of glutamate metabolism, and demonstrate its validity by showing that genes in the network respond to changes in glutamine and glutamate availability. Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes., Author Summary Although numerous quantitative trait loci (QTL) influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identifying individual genes and their potential roles in molecular pathways leading to disease remains a challenge. In this study, we include transcriptional and metabolic profiling in genomic analyses to address this limitation. We investigated an F2 intercross between the diabetes-resistant C57BL/6 leptinob/ob and the diabetes-susceptible BTBR leptinob/ob mouse strains that segregates for genotype and diabetes-related physiological traits; blood glucose, plasma insulin and body weight. Our study shows that liver metabolites (comprised of amino acids, organic acids, and acyl-carnitines) map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal, testable networks for control of specific metabolic processes in liver. We apply an in vitro study to confirm the validity of this integrative method, and thus provide a novel approach to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes.