Machine Learning-Boosted Docking Enables the Efficient Structure-Based Virtual Screening of Giga-Scale Enumerated Chemical Libraries.

The emergence of ultra-large screening libraries, filled to the brim with billions of readily available compounds, poses a growing challenge for docking-based virtual screening. Machine learning (ML)-boosted strategies like the tool HASTEN combine rapid ML prediction with the brute-force docking of small fractions of such libraries to increase screening throughput and take on giga-scale libraries. In our case study of an anti-bacterial chaperone and an anti-viral kinase, we first generated a brute-force docking baseline for 1.56 billion compounds in the Enamine REAL lead-like library with the fast Glide high-throughput virtual screening protocol. With HASTEN, we observed robust recall of 90% of the true 1000 top-scoring virtual hits in both targets when docking only 1% of the entire library. This reduction of the required docking experiments by 99% significantly shortens the screening time. In the kinase target, the employment of a hydrogen bonding constraint resulted in a major proportion of unsuccessful docking attempts and hampered ML predictions. We demonstrate the optimization potential in the treatment of failed compounds when performing ML-boosted screening and benchmark and showcase HASTEN as a fast and robust tool in a growing arsenal of approaches to unlock the chemical space covered by giga-scale screening libraries for everyday drug discovery campaigns.

PP2A-based triple-strike therapy overcomes mitochondrial apoptosis resistance in brain cancer cells.

Mitochondrial glycolysis and hyperactivity of the phosphatidylinositol 3-kinase-protein kinase B (AKT) pathway are hallmarks of malignant brain tumors. However, kinase inhibitors targeting AKT (AKTi) or the glycolysis master regulator pyruvate dehydrogenase kinase (PDKi) have failed to provide clinical benefits for brain tumor patients. Here, we demonstrate that heterogeneous glioblastoma (GB) and medulloblastoma (MB) cell lines display only cytostatic responses to combined AKT and PDK targeting. Biochemically, the combined AKT and PDK inhibition resulted in the shutdown of both target pathways and priming to mitochondrial apoptosis but failed to induce apoptosis. In contrast, all tested brain tumor cell models were sensitive to a triplet therapy, in which AKT and PDK inhibition was combined with the pharmacological reactivation of protein phosphatase 2A (PP2A) by NZ-8-061 (also known as DT-061), DBK-1154, and DBK-1160. We also provide proof-of-principle evidence for in vivo efficacy in the intracranial GB and MB models by the brain-penetrant triplet therapy (AKTi + PDKi + PP2A reactivator). Mechanistically, PP2A reactivation converted the cytostatic AKTi + PDKi response to cytotoxic apoptosis, through PP2A-elicited shutdown of compensatory mitochondrial oxidative phosphorylation and by increased proton leakage. These results encourage the development of triple-strike strategies targeting mitochondrial metabolism to overcome therapy tolerance in brain tumors.

Development of actionable targets of multi-kinase inhibitors (AToMI) screening platform to dissect kinase targets of staurosporines in glioblastoma cells.

Therapeutic resistance to kinase inhibitors constitutes a major unresolved clinical challenge in cancer and especially in glioblastoma. Multi-kinase inhibitors may be used for simultaneous targeting of multiple target kinases and thereby potentially overcome kinase inhibitor resistance. However, in most cases the identification of the target kinases mediating therapeutic effects of multi-kinase inhibitors has been challenging. To tackle this important problem, we developed an actionable targets of multi-kinase inhibitors (AToMI) strategy and used it for characterization of glioblastoma target kinases of staurosporine derivatives displaying synergy with protein phosphatase 2A (PP2A) reactivation. AToMI consists of interchangeable modules combining drug-kinase interaction assay, siRNA high-throughput screening, bioinformatics analysis, and validation screening with more selective target kinase inhibitors. As a result, AToMI analysis revealed AKT and mitochondrial pyruvate dehydrogenase kinase PDK1 and PDK4 as kinase targets of staurosporine derivatives UCN-01, CEP-701, and K252a that synergized with PP2A activation across heterogeneous glioblastoma cells. Based on these proof-of-principle results, we propose that the application and further development of AToMI for clinically applicable multi-kinase inhibitors could provide significant benefits in overcoming the challenge of lack of knowledge of the target specificity of multi-kinase inhibitors.

Phosphoproteome and drug-response effects mediated by the three protein phosphatase 2A inhibitor proteins CIP2A, SET, and PME-1.

Protein phosphatase 2A (PP2A) critically regulates cell signaling and is a human tumor suppressor. PP2A complexes are modulated by proteins such as cancerous inhibitor of protein phosphatase 2A (CIP2A), protein phosphatase methylesterase 1 (PME-1), and SET nuclear proto-oncogene (SET) that often are deregulated in cancers. However, how they impact cellular phosphorylation and how redundant they are in cellular regulation is poorly understood. Here, we conducted a systematic phosphoproteomics screen for phosphotargets modulated by siRNA-mediated depletion of CIP2A, PME-1, and SET (to reactivate PP2A) or the scaffolding A-subunit of PP2A (PPP2R1A) (to inhibit PP2A) in HeLa cells. We identified PP2A-modulated targets in diverse cellular pathways, including kinase signaling, cytoskeleton, RNA splicing, DNA repair, and nuclear lamina. The results indicate nonredundancy among CIP2A, PME-1, and SET in phosphotarget regulation. Notably, PP2A inhibition or reactivation affected largely distinct phosphopeptides, introducing a concept of nonoverlapping phosphatase inhibition- and activation-responsive sites (PIRS and PARS, respectively). This phenomenon is explained by the PPP2R1A inhibition impacting primarily dephosphorylated threonines, whereas PP2A reactivation results in dephosphorylation of clustered and acidophilic sites. Using comprehensive drug-sensitivity screening in PP2A-modulated cells to evaluate the functional impact of PP2A across diverse cellular pathways targeted by these drugs, we found that consistent with global phosphoproteome effects, PP2A modulations broadly affect responses to more than 200 drugs inhibiting a broad spectrum of cancer-relevant targets. These findings advance our understanding of the phosphoproteins, pharmacological responses, and cellular processes regulated by PP2A modulation and may enable the development of combination therapies.

UBR5 Is Coamplified with MYC in Breast Tumors and Encodes an Ubiquitin Ligase That Limits MYC-Dependent Apoptosis.

For maximal oncogenic activity, cellular MYC protein levels need to be tightly controlled so that they do not induce apoptosis. Here, we show how ubiquitin ligase UBR5 functions as a molecular rheostat to prevent excess accumulation of MYC protein. UBR5 ubiquitinates MYC and its effects on MYC protein stability are independent of FBXW7. Silencing of endogenous UBR5 induced MYC protein expression and regulated MYC target genes. Consistent with the tumor suppressor function of UBR5 (HYD) in Drosophila, HYD suppressed dMYC-dependent overgrowth of wing imaginal discs. In contrast, in cancer cells, UBR5 suppressed MYC-dependent priming to therapy-induced apoptosis. Of direct cancer relevance, MYC and UBR5 genes were coamplified in MYC-driven human cancers. Functionally, UBR5 suppressed MYC-mediated apoptosis in p53-mutant breast cancer cells with UBR5/MYC coamplification. Furthermore, single-cell immunofluorescence analysis demonstrated reciprocal expression of UBR5 and MYC in human basal-type breast cancer tissues. In summary, UBR5 is a novel MYC ubiquitin ligase and an endogenous rheostat for MYC activity. In MYC-amplified, and p53-mutant breast cancer cells, UBR5 has an important role in suppressing MYC-mediated apoptosis priming and in protection from drug-induced apoptosis. SIGNIFICANCE: These findings identify UBR5 as a novel MYC regulator, the inactivation of which could be very important for understanding of MYC dysregulation on cancer cells. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/7/1414/F1.large.jpg.

PP2A inhibition is a druggable MEK inhibitor resistance mechanism in KRAS-mutant lung cancer cells.

Kinase inhibitor resistance constitutes a major unresolved clinical challenge in cancer. Furthermore, the role of serine/threonine phosphatase deregulation as a potential cause for resistance to kinase inhibitors has not been thoroughly addressed. We characterize protein phosphatase 2A (PP2A) activity as a global determinant of KRAS-mutant lung cancer cell resistance across a library of >200 kinase inhibitors. The results show that PP2A activity modulation alters cancer cell sensitivities to a large number of kinase inhibitors. Specifically, PP2A inhibition ablated mitogen-activated protein kinase kinase (MEK) inhibitor response through the collateral activation of AKT/mammalian target of rapamycin (mTOR) signaling. Combination of mTOR and MEK inhibitors induced cytotoxicity in PP2A-inhibited cells, but even this drug combination could not abrogate MYC up-regulation in PP2A-inhibited cells. Treatment with an orally bioavailable small-molecule activator of PP2A DT-061, in combination with the MEK inhibitor AZD6244, resulted in suppression of both p-AKT and MYC, as well as tumor regression in two KRAS-driven lung cancer mouse models. DT-061 therapy also abrogated MYC-driven tumorigenesis. These data demonstrate that PP2A deregulation drives MEK inhibitor resistance in KRAS-mutant cells. These results emphasize the need for better understanding of phosphatases as key modulators of cancer therapy responses.

Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men.

BACKGROUND: There is a need for early markers to track and predict the development of type 2 diabetes mellitus (T2DM) from the state of normal glucose tolerance through prediabetes. In this study we tested whether the plasma molecular lipidome has biomarker potential to predicting the onset of T2DM. METHODS: We applied global lipidomic profiling on plasma samples from well-phenotyped men (107 cases, 216 controls) participating in the longitudinal METSIM study at baseline and at five-year follow-up. To validate the lipid markers, an additional study with a representative sample of adult male population (n=631) was also conducted. A total of 277 plasma lipids were analyzed using the lipidomics platform based on ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry. Lipids with the highest predictive power for the development of T2DM were computationally selected, validated and compared to standard risk models without lipids. RESULTS: A persistent lipid signature with higher levels of triacylglycerols and diacyl-phospholipids as well as lower levels of alkylacyl phosphatidylcholines was observed in progressors to T2DM. Lysophosphatidylcholine acyl C18:2 (LysoPC(18:2)), phosphatidylcholines PC(32:1), PC(34:2e) and PC(36:1), and triacylglycerol TG(17:1/18:1/18:2) were selected to the full model that included metabolic risk factors and FINDRISC variables. When further adjusting for BMI and age, these lipids had respective odds ratios of 0.32, 2.4, 0.50, 2.2 and 0.31 (all p<0.05) for progression to T2DM. The independently-validated predictive power improved in all pairwise comparisons between the lipid model and the respective standard risk model without the lipids (integrated discrimination improvement IDI>0; p<0.05). Notably, the lipid models remained predictive of the development of T2DM in the fasting plasma glucose-matched subset of the validation study. CONCLUSION: This study indicates that a lipid signature characteristic of T2DM is present years before the diagnosis and improves prediction of progression to T2DM. Molecular lipid biomarkers were shown to have predictive power also in a high-risk group, where standard risk factors are not helpful at distinguishing progressors from non-progressors.

Drug Target Commons: A Community Effort to Build a Consensus Knowledge Base for Drug-Target Interactions.

Knowledge of the full target space of bioactive substances, approved and investigational drugs as well as chemical probes, provides important insights into therapeutic potential and possible adverse effects. The existing compound-target bioactivity data resources are often incomparable due to non-standardized and heterogeneous assay types and variability in endpoint measurements. To extract higher value from the existing and future compound target-profiling data, we implemented an open-data web platform, named Drug Target Commons (DTC), which features tools for crowd-sourced compound-target bioactivity data annotation, standardization, curation, and intra-resource integration. We demonstrate the unique value of DTC with several examples related to both drug discovery and drug repurposing applications and invite researchers to join this community effort to increase the reuse and extension of compound bioactivity data.

Rapalogs can promote cancer cell stemness in vitro in a Galectin-1 and H-ras-dependent manner.

Currently several combination treatments of mTor- and Ras-pathway inhibitors are being tested in cancer therapy. While multiple feedback loops render these central signaling pathways robust, they complicate drug targeting.Here, we describe a novel H-ras specific feedback, which leads to an inadvertent rapalog induced activation of tumorigenicity in Ras transformed cells. We find that rapalogs specifically increase nanoscale clustering (nanoclustering) of oncogenic H-ras but not K-ras on the plasma membrane. This increases H-ras signaling output, promotes mammosphere numbers in a H-ras-dependent manner and tumor growth in ovo. Surprisingly, also other FKBP12 binders, but not mTor-inhibitors, robustly decrease FKBP12 levels after prolonged (>2 days) exposure. This leads to an upregulation of the nanocluster scaffold galectin-1 (Gal-1), which is responsible for the rapamycin-induced increase in H-ras nanoclustering and signaling output. We provide evidence that Gal-1 promotes stemness features in tumorigenic cells. Therefore, it may be necessary to block inadvertent induction of stemness traits in H-ras transformed cells by specific Gal-1 inhibitors that abrogate its effect on H-ras nanocluster. On a more general level, our findings may add an important mechanistic explanation to the pleiotropic physiological effects that are observed with rapalogs.

Multi-Omics Studies towards Novel Modulators of Influenza A Virus-Host Interaction.

Human influenza A viruses (IAVs) cause global pandemics and epidemics. These viruses evolve rapidly, making current treatment options ineffective. To identify novel modulators of IAV-host interactions, we re-analyzed our recent transcriptomics, metabolomics, proteomics, phosphoproteomics, and genomics/virtual ligand screening data. We identified 713 potential modulators targeting 199 cellular and two viral proteins. Anti-influenza activity for 48 of them has been reported previously, whereas the antiviral efficacy of the 665 remains unknown. Studying anti-influenza efficacy and immuno/neuro-modulating properties of these compounds and their combinations as well as potential viral and host resistance to them may lead to the discovery of novel modulators of IAV-host interactions, which might be more effective than the currently available anti-influenza therapeutics.

Genomic prediction of coronary heart disease.

AIMS: Genetics plays an important role in coronary heart disease (CHD) but the clinical utility of genomic risk scores (GRSs) relative to clinical risk scores, such as the Framingham Risk Score (FRS), is unclear. Our aim was to construct and externally validate a CHD GRS, in terms of lifetime CHD risk and relative to traditional clinical risk scores. METHODS AND RESULTS: We generated a GRS of 49 310 SNPs based on a CARDIoGRAMplusC4D Consortium meta-analysis of CHD, then independently tested it using five prospective population cohorts (three FINRISK cohorts, combined n = 12 676, 757 incident CHD events; two Framingham Heart Study cohorts (FHS), combined n = 3406, 587 incident CHD events). The GRS was associated with incident CHD (FINRISK HR = 1.74, 95% confidence interval (CI) 1.61-1.86 per S.D. of GRS; Framingham HR = 1.28, 95% CI 1.18-1.38), and was largely unchanged by adjustment for known risk factors, including family history. Integration of the GRS with the FRS or ACC/AHA13 scores improved the 10 years risk prediction (meta-analysis C-index: +1.5-1.6%, P < 0.001), particularly for individuals ≥60 years old (meta-analysis C-index: +4.6-5.1%, P < 0.001). Importantly, the GRS captured substantially different trajectories of absolute risk, with men in the top 20% of attaining 10% cumulative CHD risk 12-18 y earlier than those in the bottom 20%. High genomic risk was partially compensated for by low systolic blood pressure, low cholesterol level, and non-smoking. CONCLUSIONS: A GRS based on a large number of SNPs improves CHD risk prediction and encodes different trajectories of lifetime risk not captured by traditional clinical risk scores.

Genomic, transcriptomic, and lipidomic profiling highlights the role of inflammation in individuals with low high-density lipoprotein cholesterol.

OBJECTIVE: Low high-density lipoprotein cholesterol (HDL-C) is associated with cardiometabolic pathologies. In this study, we investigate the biological pathways and individual genes behind low HDL-C by integrating results from 3 high-throughput data sources: adipose tissue transcriptomics, HDL lipidomics, and dense marker genotypes from Finnish individuals with low or high HDL-C (n=450). APPROACH AND RESULTS: In the pathway analysis of genetic data, we demonstrate that genetic variants within inflammatory pathways were enriched among low HDL-C associated single-nucleotide polymorphisms, and the expression of these pathways upregulated in the adipose tissue of low HDL-C subjects. The lipidomic analysis highlighted the change in HDL particle quality toward putatively more inflammatory and less vasoprotective state in subjects with low HDL-C, as evidenced by their decreased antioxidative plasmalogen contents. We show that the focal point of these inflammatory pathways seems to be the HLA region with its low HDL-associated alleles also associating with more abundant local transcript levels in adipose tissue, increased plasma vascular cell adhesion molecule 1 (VCAM1) levels, and decreased HDL particle plasmalogen contents, markers of adipose tissue inflammation, vascular inflammation, and HDL antioxidative potential, respectively. In a population-based look-up of the inflammatory pathway single-nucleotide polymorphisms in a large Finnish cohorts (n=11 211), no association of the HLA region was detected for HDL-C as quantitative trait, but with extreme HDL-C phenotypes, implying the presence of low or high HDL genes in addition to the population-genomewide association studies-identified HDL genes. CONCLUSIONS: Our study highlights the role of inflammation with a genetic component in subjects with low HDL-C and identifies novel cis-expression quantitative trait loci (cis-eQTL) variants in HLA region to be associated with low HDL-C.

T-cell activation induces selective changes of cellular lipidome.

Activation of naïve T helper cells by presentation of cognate antigen initiates a complex intracellular signaling process leading to development of functionally active effector cell population. The switch from quiescent naïve state to activated state involves a profound change of cellular metabolism, required for completion of multiple rounds of proliferation. Using ultra performance liquid chromatography mass spectrometry, we analyzed how this change is reflected on the cellular lipid composition in human umbilical cord blood T-cells. We found that considerable concentration changes take place during the first 72 hours after T-cell receptor activation, correlating with first rounds of activation-induced cell division. Most importantly, composition of phosphatidylcholines and phosphatidylethanolamines exhibited consistent trend towards shorter and more saturated molecular species. Together with related transcriptomics data, the results clearly suggested induction of de novofatty acid synthesis and accumulation of endogenously synthesized fatty acids into the cellular membranes, leading to partial remodeling of the cellular lipidome in the newly developed effector cell population.

Metabolic regulation in progression to autoimmune diabetes.

Recent evidence from serum metabolomics indicates that specific metabolic disturbances precede ß-cell autoimmunity in humans and can be used to identify those children who subsequently progress to type 1 diabetes. The mechanisms behind these disturbances are unknown. Here we show the specificity of the pre-autoimmune metabolic changes, as indicated by their conservation in a murine model of type 1 diabetes. We performed a study in non-obese prediabetic (NOD) mice which recapitulated the design of the human study and derived the metabolic states from longitudinal lipidomics data. We show that female NOD mice who later progress to autoimmune diabetes exhibit the same lipidomic pattern as prediabetic children. These metabolic changes are accompanied by enhanced glucose-stimulated insulin secretion, normoglycemia, upregulation of insulinotropic amino acids in islets, elevated plasma leptin and adiponectin, and diminished gut microbial diversity of the Clostridium leptum group. Together, the findings indicate that autoimmune diabetes is preceded by a state of increased metabolic demands on the islets resulting in elevated insulin secretion and suggest alternative metabolic related pathways as therapeutic targets to prevent diabetes.

High density lipoprotein structural changes and drug response in lipidomic profiles following the long-term fenofibrate therapy in the FIELD substudy.

In a recent FIELD study the fenofibrate therapy surprisingly failed to achieve significant benefit over placebo in the primary endpoint of coronary heart disease events. Increased levels of atherogenic homocysteine were observed in some patients assigned to fenofibrate therapy but the molecular mechanisms behind this are poorly understood. Herein we investigated HDL lipidomic profiles associated with fenofibrate treatment and the drug-induced Hcy levels in the FIELD substudy. We found that fenofibrate leads to complex HDL compositional changes including increased apoA-II, diminishment of lysophosphatidylcholines and increase of sphingomyelins. Ethanolamine plasmalogens were diminished only in a subgroup of fenofibrate-treated patients with elevated homocysteine levels. Finally we performed molecular dynamics simulations to qualitatively reconstitute HDL particles in silico. We found that increased number of apoA-II excludes neutral lipids from HDL surface and apoA-II is more deeply buried in the lipid matrix than apoA-I. In conclusion, a detailed molecular characterization of HDL may provide surrogates for predictors of drug response and thus help identify the patients who might benefit from fenofibrate treatment.

Association of lipidome remodeling in the adipocyte membrane with acquired obesity in humans.

Identification of early mechanisms that may lead from obesity towards complications such as metabolic syndrome is of great interest. Here we performed lipidomic analyses of adipose tissue in twin pairs discordant for obesity but still metabolically compensated. In parallel we studied more evolved states of obesity by investigating a separated set of individuals considered to be morbidly obese. Despite lower dietary polyunsaturated fatty acid intake, the obese twin individuals had increased proportions of palmitoleic and arachidonic acids in their adipose tissue, including increased levels of ethanolamine plasmalogens containing arachidonic acid. Information gathered from these experimental groups was used for molecular dynamics simulations of lipid bilayers combined with dependency network analysis of combined clinical, lipidomics, and gene expression data. The simulations suggested that the observed lipid remodeling maintains the biophysical properties of lipid membranes, at the price, however, of increasing their vulnerability to inflammation. Conversely, in morbidly obese subjects, the proportion of plasmalogens containing arachidonic acid in the adipose tissue was markedly decreased. We also show by in vitro Elovl6 knockdown that the lipid network regulating the observed remodeling may be amenable to genetic modulation. Together, our novel approach suggests a physiological mechanism by which adaptation of adipocyte membranes to adipose tissue expansion associates with positive energy balance, potentially leading to higher vulnerability to inflammation in acquired obesity. Further studies will be needed to determine the cause of this effect.

Novel theranostic opportunities offered by characterization of altered membrane lipid metabolism in breast cancer progression.

Activation of lipid metabolism is an early event in carcinogenesis and a central hallmark of many cancers. However, the precise molecular composition of lipids in tumors remains generally poorly characterized. The aim of the present study was to analyze the global lipid profiles of breast cancer, integrate the results to protein expression, and validate the findings by functional experiments. Comprehensive lipidomics was conducted in 267 human breast tissues using ultraperformance liquid chromatography/ mass spectrometry. The products of de novo fatty acid synthesis incorporated into membrane phospholipids, such as palmitate-containing phosphatidylcholines, were increased in tumors as compared with normal breast tissues. These lipids were associated with cancer progression and patient survival, as their concentration was highest in estrogen receptor-negative and grade 3 tumors. In silico transcriptomics database was utilized in investigating the expression of lipid metabolism related genes in breast cancer, and on the basis of these results, the expression of specific proteins was studied by immunohistochemistry. Immunohistochemical analyses showed that several genes regulating lipid metabolism were highly expressed in clinical breast cancer samples and supported also the lipidomics results. Gene silencing experiments with seven genes [ACACA (acetyl-CoA carboxylase α), ELOVL1 (elongation of very long chain fatty acid-like 1), FASN (fatty acid synthase), INSIG1 (insulin-induced gene 1), SCAP (sterol regulatory element-binding protein cleavage-activating protein), SCD (stearoyl-CoA desaturase), and THRSP (thyroid hormone-responsive protein)] indicated that silencing of multiple lipid metabolism-regulating genes reduced the lipidomic profiles and viability of the breast cancer cells. Taken together, our results imply that phospholipids may have diagnostic potential as well as that modulation of their metabolism may provide therapeutic opportunities in breast cancer treatment.

Composition and lipid spatial distribution of HDL particles in subjects with low and high HDL-cholesterol.

A low level of high density lipoprotein cholesterol (HDL-C) is a powerful risk factor for cardiovascular disease. However, despite the reported key role of apolipo-proteins, specifically, apoA-I, in HDL metabolism, lipid molecular composition of HDL particles in subjects with high and low HDL-C levels is currently unknown. Here lipidomics was used to study HDL derived from well-characterized high and low HDL-C subjects. Low HDL-C subjects had elevated triacylglycerols and diminished lysophosphatidylcholines and sphingomyelins. Using information about the lipid composition of HDL particles in these two groups, we reconstituted HDL particles in silico by performing large-scale molecular dynamics simulations. In addition to confirming the measured change in particle size, we found that the changes in lipid composition also induced specific spatial distributions of lipids within the HDL particles, including a higher amount of triacylglycerols at the surface of HDL particles in low HDL-C subjects. Our findings have important implications for understanding HDL metabolism and function. For the first time we demonstrate the power of combining molecular profiling of lipoproteins with dynamic modeling of lipoprotein structure.

The gut microbiota modulates host energy and lipid metabolism in mice.

The gut microbiota has recently been identified as an environmental factor that may promote metabolic diseases. To investigate the effect of gut microbiota on host energy and lipid metabolism, we compared the serum metabolome and the lipidomes of serum, adipose tissue, and liver of conventionally raised (CONV-R) and germ-free mice. The serum metabolome of CONV-R mice was characterized by increased levels of energy metabolites, e.g., pyruvic acid, citric acid, fumaric acid, and malic acid, while levels of cholesterol and fatty acids were reduced. We also showed that the microbiota modified a number of lipid species in the serum, adipose tissue, and liver, with its greatest effect on triglyceride and phosphatidylcholine species. Triglyceride levels were lower in serum but higher in adipose tissue and liver of CONV-R mice, consistent with increased lipid clearance. Our findings show that the gut microbiota affects both host energy and lipid metabolism and highlights its role in the development of metabolic diseases.

Adaptation and failure of pancreatic beta cells in murine models with different degrees of metabolic syndrome.

The events that contribute to the expansion of beta-cell mass and enhanced beta-cell function in insulin-resistant states have not been elucidated fully. Recently, we showed that beta-cell adaptation failed dramatically in adult, insulin-resistant POKO mice, which contrasts with the appropriate expansion of beta cells in their ob/ob littermates. Thus, we hypothesised that characterisation of the islets in these mouse models at an early age should provide a unique opportunity to: (1) identify mechanisms involved in sensing insulin resistance at the level of the beta cells, (2) identify molecular effectors that contribute to increasing beta-cell mass and function, and (3) distinguish primary events from secondary events that are more likely to be present at more advanced stages of diabetes. Our results define the POKO mouse as a model of early lipotoxicity. At 4 weeks of age, it manifests with inappropriate beta-cell function and defects in proliferation markers. Other well-recognised pathogenic effectors that were observed previously in 16-week-old mice, such as increased reactive oxygen species (ROS), macrophage infiltration and endoplasmic reticulum (ER) stress, are also present in both young POKO and young ob/ob mice, indicating the lack of predictive power with regards to the severity of beta-cell failure. Of interest, the relatively preserved lipidomic profile in islets from young POKO mice contrasted with the large changes in lipid composition and the differences in the chain length of triacylglycerols in the serum, liver, muscle and adipose tissue in adult POKO mice. Later lipotoxic insults in adult beta cells contribute to the failure of the POKO beta cell. Our results indicate that the rapid development of insulin resistance and beta-cell failure in POKO mice makes this model a useful tool to study early molecular events leading to insulin resistance and beta-cell failure. Furthermore, comparisons with ob/ob mice might reveal important adaptive mechanisms in beta cells with either therapeutic or diagnostic potential.