A functional, genome-wide evaluation of liposensitive yeast identifies the "ARE2 required for viability" (ARV1) gene product as a major component of eukaryotic fatty acid resistance.

The toxic subcellular accumulation of lipids predisposes several human metabolic syndromes, including obesity, type 2 diabetes, and some forms of neurodegeneration. To identify pathways that prevent lipid-induced cell death, we performed a genome-wide fatty acid sensitivity screen in Saccharomyces cerevisiae. We identified 167 yeast mutants as sensitive to 0.5 mm palmitoleate, 45% of which define pathways that were conserved in humans. 63 lesions also impacted the status of the lipid droplet; however, this was not correlated to the degree of fatty acid sensitivity. The most liposensitive yeast strain arose due to deletion of the "ARE2 required for viability" (ARV1) gene, encoding an evolutionarily conserved, potential lipid transporter that localizes to the endoplasmic reticulum membrane. Down-regulation of mammalian ARV1 in MIN6 pancreatic ß-cells or HEK293 cells resulted in decreased neutral lipid synthesis, increased fatty acid sensitivity, and lipoapoptosis. Conversely, elevated expression of human ARV1 in HEK293 cells or mouse liver significantly increased triglyceride mass and lipid droplet number. The ARV1-induced hepatic triglyceride accumulation was accompanied by up-regulation of DGAT1, a triglyceride synthesis gene, and the fatty acid transporter, CD36. Furthermore, ARV1 was identified as a transcriptional of the protein peroxisome proliferator-activated receptor α (PPARα), a key regulator of lipid homeostasis whose transcriptional targets include DGAT1 and CD36. These results implicate ARV1 as a protective factor in lipotoxic diseases due to modulation of fatty acid metabolism. In conclusion, a lipotoxicity-based genetic screen in a model microorganism has identified 75 human genes that may play key roles in neutral lipid metabolism and disease.

Utilising a Clinical Metabolomics LC-MS Study to Determine the Integrity of Biological Samples for Statistical Modelling after Long Term -80 °C Storage: A TOFI_Asia Sub-Study.

Biological samples of lipids and metabolites degrade after extensive years in -80 °C storage. We aimed to determine if associated multivariate models are also impacted. Prior TOFI_Asia metabolomics studies from our laboratory established multivariate models of metabolic risks associated with ethnic diversity. Therefore, to compare multivariate modelling degradation after years of -80 °C storage, we selected a subset of aged (≥5-years) plasma samples from the TOFI_Asia study to re-analyze via untargeted LC-MS metabolomics. Samples from European Caucasian (n = 28) and Asian Chinese (n = 28) participants were evaluated for ethnic discrimination by partial least squares discriminative analysis (PLS-DA) of lipids and polar metabolites. Both showed a strong discernment between participants ethnicity by features, before (Initial) and after (Aged) 5-years of -80 °C storage. With receiver operator characteristic curves, sparse PLS-DA derived confusion matrix and prediction error rates, a considerable reduction in model integrity was apparent with the Aged polar metabolite model relative to Initial modelling. Ethnicity modelling with lipids maintained predictive integrity in Aged plasma samples, while equivalent polar metabolite models reduced in integrity. Our results indicate that researchers re-evaluating samples for multivariate modelling should consider time at -80 °C when producing predictive metrics from polar metabolites, more so than lipids.

The impact of ethnicity and intra-pancreatic fat on the postprandial metabolome response to whey protein in overweight Asian Chinese and European Caucasian women with prediabetes.

The "Thin on the Outside Fat on the Inside" TOFI_Asia study found Asian Chinese to be more susceptible to Type 2 Diabetes (T2D) compared to European Caucasians matched for gender and body mass index (BMI). This was influenced by degree of visceral adipose deposition and ectopic fat accumulation in key organs, including liver and pancreas, leading to altered fasting plasma glucose, insulin resistance, and differences in plasma lipid and metabolite profiles. It remains unclear how intra-pancreatic fat deposition (IPFD) impacts TOFI phenotype-related T2D risk factors associated with Asian Chinese. Cow's milk whey protein isolate (WPI) is an insulin secretagogue which can suppress hyperglycemia in prediabetes. In this dietary intervention, we used untargeted metabolomics to characterize the postprandial WPI response in 24 overweight women with prediabetes. Participants were classified by ethnicity (Asian Chinese, n=12; European Caucasian, n=12) and IPFD (low IPFD < 4.66%, n=10; high IPFD ≥ 4.66%, n=10). Using a cross-over design participants were randomized to consume three WPI beverages on separate occasions; 0 g (water control), 12.5 g (low protein, LP) and 50 g (high protein, HP), consumed when fasted. An exclusion pipeline for isolating metabolites with temporal (T0-240mins) WPI responses was implemented, and a support vector machine-recursive feature elimination (SVM-RFE) algorithm was used to model relevant metabolites by ethnicity and IPFD classes. Metabolic network analysis identified glycine as a central hub in both ethnicity and IPFD WPI response networks. A depletion of glycine relative to WPI concentration was detected in Chinese and high IPFD participants independent of BMI. Urea cycle metabolites were highly represented among the ethnicity WPI metabolome model, implicating a dysregulation in ammonia and nitrogen metabolism among Chinese participants. Uric acid and purine synthesis pathways were enriched within the high IPFD cohort's WPI metabolome response, implicating adipogenesis and insulin resistance pathways. In conclusion, the discrimination of ethnicity from WPI metabolome profiles was a stronger prediction model than IPFD in overweight women with prediabetes. Each models' discriminatory metabolites enriched different metabolic pathways that help to further characterize prediabetes in Asian Chinese women and women with increased IPFD, independently.

Phenotypic Screening for Small Molecules that Protect ß-Cells from Glucolipotoxicity.

Type 2 diabetes is marked by progressive ß-cell failure, leading to loss of ß-cell mass. Increased levels of circulating glucose and free fatty acids associated with obesity lead to ß-cell glucolipotoxicity. There are currently no therapeutic options to address this facet of ß-cell loss in obese type 2 diabetes patients. To identify small molecules capable of protecting ß-cells, we performed a high-throughput screen of 20,876 compounds in the rat insulinoma cell line INS-1E in the presence of elevated glucose and palmitate. We found 312 glucolipotoxicity-protective small molecules (1.49% hit rate) capable of restoring INS-1E viability, and we focused on 17 with known biological targets. 16 of the 17 compounds were kinase inhibitors with activity against specific families including but not limited to cyclin-dependent kinases (CDK), PI-3 kinase (PI3K), Janus kinase (JAK), and Rho-associated kinase 2 (ROCK2). 7 of the 16 kinase inhibitors were PI3K inhibitors. Validation studies in dissociated human islets identified 10 of the 17 compounds, namely, KD025, ETP-45658, BMS-536924, AT-9283, PF-03814735, torin-2, AZD5438, CP-640186, ETP-46464, and GSK2126458 that reduced glucolipotoxicity-induced ß-cell death. These 10 compounds decreased markers of glucolipotoxicity including caspase activation, mitochondrial depolarization, and increased calcium flux. Together, these results provide a path forward toward identifying novel treatments to preserve ß-cell viability in the face of glucolipotoxicity.