Project description:Purpose: To reveal molecular mechanisms of diabetic retinopathy (DR) in Asians and facilitate the identification of new therapeutic targets through untargeted metabolomics. To determine the differences in serum metabolites and metabolic pathways between different stages of diabetic retinopathy in patients with type 2 diabetic mellitus (T2DM) and proliferative DR (PDR) and non-proliferative DR (NPDR) and identify differential metabolites between T2DM and DR (NPDR and PDR) patients. Methods: This prospective observational registration study described the differential metabolites between 45 T2DM patients and 15 control cases with no significant differences in clinical characteristics. Their biospecimens and clinical information were collected and recorded in their medical reports. DR phenotypes of the subjects were verified by retina specialists. Serum metabolites were analyzed using high-resolution mass spectrometry with liquid chromatography. Untargeted metabolomics was performed on serum samples from 15 T2DM patients, 15 non-proliferative diabetic retinopathy patients, 15 proliferative diabetic retinopathy patients, and 15 diabetic controls. Discriminatory metabolic features were identified through partial least squares discriminant analysis (PLS-DA), hierarchical clustering analysis (HCA), and generalized linear regression models. Result: Through untargeted metabolomics, 931 features (523 in positive and 408 in negative modes) with 102 common metabolites highly relevant to the presence of DR were detected. In the adjusted analysis, 67 metabolic features differed significantly between T2DM and NPDR patients. Pathway analysis revealed alterations in metabolisms of amino acids and fatty acids. Glutamate, phosphatidylcholine, and 13-hydroperoxyoctadeca-9,11-dienoic acid (13-PHODE) were key contributors to these pathway differences. A total of 171 features distinguished PDR patients from T2DM patients, and pathway analysis revealed alterations in amino acid metabolism, fatty acid metabolism, nitrogen metabolism, and tricarboxylic acid cycle. Aspartate, glutamate, glutamine, ornithine, N-acetyl-l-glutamate, N-acetyl-l-aspartate, citrate, succinate, N-(L-arginino)succinate, 2-oxoglutarate, 13-hydroperoxyoctadeca-9,11-dienoic acid, methionine, lysine, threonine, phenylalanine, N(pi)-methyl-l-histidine, phosphatidylcholine, and linoleate were major contributors to the pathway differences. Between NPDR patients and PDR patients, there were 79 significant differential metabolites. Enrichment pathway analysis showed changes in amino acid metabolism, fatty acid metabolism, pantothenate, and CoA biosynthesis. Aspartate, glutamine, N-acetyl-l-glutamate, N-acetyl-l-aspartate, pantothenate, dihomo-gamma-linolenate, docosahexaenoic acid, and icosapentaenoic acid were key factors for the differences of these pathways. Conclusion: This study demonstrated that the pathways of arginine biosynthesis metabolism, linoleic acid metabolism, alanine, aspartate, and glutamate metabolism, as well as d-glutamine and d-glutamate metabolism, were dysregulated in DR patients of the Asian population. Increased levels of glutamate, aspartate, glutamine, N-acetyl-l-glutamate, and N-acetyl-l-aspartate and decreased levels of dihomo-gamma-linolenate, docosahexaenoic, and icosapentaenoic were considered as the metabolic profile that could distinguish PDR from NPDR in Asians. Phosphatidylcholine and 13-PHODE were identified as two major novel metabolite markers in advanced stages of DR in our study.

Project description:The interplay between pathogens and hosts has been studied for decades using targeted approaches such as the analysis of mutants and host immunological responses. Although much has been learned from such studies, they focus on individual pathways and fail to reveal the global effects of infection on the host. To alleviate this issue, high-throughput methods such as transcriptomics and proteomics have been used to study host-pathogen interactions. Recently, metabolomics was established as a new method to study changes in the biochemical composition of host tissues. We report a metabolomics study of Salmonella enterica serovar Typhimurium infection. We used Fourier Transform Ion Cyclotron Resonance Mass Spectrometry with Direct Infusion to reveal that dozens of host metabolic pathways are affected by Salmonella in a murine infection model. In particular, multiple host hormone pathways are disrupted. Our results identify unappreciated effects of infection on host metabolism and shed light on mechanisms used by Salmonella to cause disease, and by the host to counter infection. Female C57BL/6 mice were infected with Salmonella enterica serovar Typhimurium SL1344 cells by oral gavage. Feces and livers were collected and metabolites extracted using acetonitrile. For experiments with feces, samples were collected from 4 mice before and after infection. For liver experiments, 11 uninfected and 11 infected mice were used. Samples were combined into 3 groups of 3-4 mice each, resulting in the analysis of 3 group samples of uninfected and 3 of infected mice. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140 [PMID 19081807]). To identify differences in metabolite composition between uninfected and infected samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from uninfected and infected mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org). Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.

Project description:Production of PFAS has shifted from the most-studied PFAS, longer-chain perfluorinated alkyl acids, to shorter-chain or other alternative moieties including fluoroethers like HFPO-DA (“GenX chemicals”), Nafion Byproducts, and the PFOx homologous series that includes PFO4DA and PFO5DoA. In contaminated study areas, the fluoroethers PFO4DA and PFO5DoA, although detected at relatively low levels in surface water, have been detected in serum and/or tissues with high frequency in humans, wildlife including fish and alligators, and pets including horses. Although these compounds have been detected, there are extremely limited toxicity data available and no developmental toxicology studies that could be used to inform risk assessment or regulatory actions. To address these data gaps, Sprague-Dawley rat dams were exposed via oral gavage from GD18-22 to PFO4DA or PFO5DoA across a series of doses ranging from 0.1 to 62.5 mg/kg/day and, in conjunction with apical measures of toxicity, hepatic transcriptomics in both dam and offspring and serum metabolomics in dams were performed. Differential expression analysis was performed for transcriptomics and metabolomics, and pathway analysis, including a multi-omic integrative analysis, was performed. For PFO5DoA, overt toxicity (substantial body weight loss, fetal mortality) was observed at the highest dose, so data only include up to 30 mg/kg/day. Dimensionality reduction measures including principal components analysis and heatmaps revealed strong separation of clustering between maternal and fetal samples and between chemicals (PFO4DA vs PFO5DoA). Both dams and fetuses exhibited dose-responsive patterns of hepatic gene expression in response to PFO4DA or PFO5DoA. Of the 14,928 genes included in differential expression analysis, PFO4DA exposure in dams resulted in a maximum of 367 differentially expressed genes (DEG) at the highest dose (62.5 mg/kg/d) whereas PFO5DoA resulted in 4,506 DEG at the highest dose (30 mg/kg/d). Even at 10 mg/kg/d, PFO5DoA resulted in 1,915 DEG in dam liver. Fetuses were more affected at lower doses, but the pattern was similar, with PFO4DA resulting in 1,378 DEG at 62.5 mg/kg/d and PFO5DoA 3,653 DEG at 30 mg/kg/d. Several DEG were changed by every dose of PFO5DoA (≥ 0.3 mg/kg/d) in both maternal and fetal samples, including multiple acyl-coA thioesterases (Acot1, Acot2, Acot3, Acot4) and related enzymes that hydrolyze acyl-coA to free fatty acids, as well as Vnn1, a corticosteroid-responsive gene. Hallmark and Reactome pathway analyses of fetal and maternal livers revealed remarkable changes in metabolism of bile acids and salts, fatty acid metabolism, metabolism of lipids and lipoproteins, PPARα activation of gene expression, and phospholipid metabolism. In maternal serum metabolomics, PFO4DA did not result in significant changes at doses up to 62.5 mg/kg/d. In contrast, PFO5DoA exposure resulted in differential metabolite abundance for 149 unique metabolites, with 4 significantly altered at 0.3 mg/kg, 31 metabolites at 1 mg/kg, 51 at 3 mg/kg, 58 at 10mg/kg, and 119 at 30 mg/kg/d. Multi-omics KEGG and Reactome pathway analyses of integrated maternal liver transcriptomics and serum metabolomics revealed significant convergent pathway-level changes as low as 3 mg/kg/d PFO4DA and 0.3 mg/kg/d PFO5DoA exposure. Notable multi-omics pathway level changes include fatty acid metabolism at all doses of PFO5DoA and at PFO4DA ≥ 10 mg/kg/d, with PFO4DA changes driven by the magnitude of transcriptomic changes and low/null detection of metabolites. Striking pathway-level changes identified for hepatic transcriptome and serum metabolome in exposed dams included metabolism, metabolism of lipids, hemostasis, signaling by G-protein coupled receptors (GPCRs), neuronal system, immune and innate immune system, PPARα activation of gene expression, and regulation of lipid metabolism by PPARα. The transcriptomic and metabolomic effects of PFO4DA and PFO5DoA appear consistent with other carboxylic acid PFAS, with primary changes related to lipid metabolism, bile acids, cholesterol, and cellular stress. Although PFO4DA and PFO5DoA are structurally similar, separated by only a CF2O, the potency of transcriptomic and metabolomic effects of developmental exposure to each was significantly different, with 5-day exposure to PFO5DoA causing changes in glucose and lipid metabolism and stress signals at much lower doses than PFO4DA in both dams (~ 35-fold more potent at inducing hepatic DEG) and fetuses (~ 11.6-fold more potent at inducing hepatic DEG). Although it is likely that some differences in toxicity between PFO4DA and PFO5DoA are caused by accumulation differences resulting in different dosimetry, PFO5DoA demonstrated much greater transcriptomic and metabolomic toxicity at equivalent oral doses.

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