Thomas O. Metz

Temporal Proteome and Lipidome Profiles Reveal Hepatitis C Virus-Associated Reprogramming of Hepatocellular Metabolism and Bioenergetics

Proteomic and lipidomic profiling was performed over a time course of acute hepatitis C virus (HCV) infection in cultured Huh-7.5 cells to gain new insights into the intracellular processes influenced by this virus. Our proteomic data suggest that HCV induces early perturbations in glycolysis, the pentose phosphate pathway, and the citric acid cycle, which favor host biosynthetic activities supporting viral replication and propagation. This is followed by a compensatory shift in metabolism aimed at maintaining energy homeostasis and cell viability during elevated viral replication and increasing cellular stress. Complementary lipidomic analyses identified numerous temporal perturbations in select lipid species (e.g. phospholipids and sphingomyelins) predicted to play important roles in viral replication and downstream assembly and secretion events. The elevation of lipotoxic ceramide species suggests a potential link between HCV-associated biochemical alterations and the direct cytopathic effect observed in this in vitro system. Using innovative computational modeling approaches, we further identified mitochondrial fatty acid oxidation enzymes, which are comparably regulated during in vitro infection and in patients with histological evidence of fibrosis, as possible targets through which HCV regulates temporal alterations in cellular metabolic homeostasis.

A Perspective on the Maillard Reaction and the Analysis of Protein Glycation by Mass Spectrometry: Probing the Pathogenesis of Chronic Disease

The Maillard reaction, starting from the glycation of protein and progressing to the formation of advanced glycation end-products (AGEs), is implicated in the development of complications of diabetes mellitus, as well as in the pathogenesis of cardiovascular, renal, and neurodegenerative diseases. In this perspective review, we provide an overview on the relevance of the Maillard reaction in the pathogenesis of chronic disease and discuss traditional approaches and recent developments in the analysis of glycated proteins by mass spectrometry. We propose that proteomics approaches, particularly bottom-up proteomics, will play a significant role in analyses of clinical samples leading to the identification of new markers of disease development and progression.

Dengue Virus Infection Perturbs Lipid Homeostasis in Infected Mosquito Cells

Dengue virus causes ∼50–100 million infections per year and thus is considered one of the most aggressive arthropod-borne human pathogen worldwide. During its replication, dengue virus induces dramatic alterations in the intracellular membranes of infected cells. This phenomenon is observed both in human and vector-derived cells. Using high-resolution mass spectrometry of mosquito cells, we show that this membrane remodeling is directly linked to a unique lipid repertoire induced by dengue virus infection. Specifically, 15% of the metabolites detected were significantly different between DENV infected and uninfected cells while 85% of the metabolites detected were significantly different in isolated replication complex membranes. Furthermore, we demonstrate that intracellular lipid redistribution induced by the inhibition of fatty acid synthase, the rate-limiting enzyme in lipid biosynthesis, is sufficient for cell survival but is inhibitory to dengue virus replication. Lipids that have the capacity to destabilize and change the curvature of membranes as well as lipids that change the permeability of membranes are enriched in dengue virus infected cells. Several sphingolipids and other bioactive signaling molecules that are involved in controlling membrane fusion, fission, and trafficking as well as molecules that influence cytoskeletal reorganization are also up regulated during dengue infection. These observations shed light on the emerging role of lipids in shaping the membrane and protein environments during viral infections and suggest membrane-organizing principles that may influence virus-induced intracellular membrane architecture.

Chelation: A Fundamental Mechanism of Action of AGE Inhibitors, AGE Breakers, and Other Inhibitors of Diabetes Complications

This article outlines evidence that advanced glycation end product (AGE) inhibitors and breakers act primarily as chelators, inhibiting metal-catalyzed oxidation reactions that catalyze AGE formation. We then present evidence that chelation is the most likely mechanism by which ACE inhibitors, angiotensin receptor blockers, and aldose reductase inhibitors inhibit AGE formation in diabetes. Finally, we note several recent studies demonstrating therapeutic benefits of chelators for diabetic cardiovascular and renal disease. We conclude that chronic, low-dose chelation therapy deserves serious consideration as a clinical tool for prevention and treatment of diabetes complications.

A statistical framework for protein quantitation in bottom-up MS-based proteomics

MOTIVATION Quantitative mass spectrometry-based proteomics requires protein-level estimates and associated confidence measures. Challenges include the presence of low quality or incorrectly identified peptides and informative missingness. Furthermore, models are required for rolling peptide-level information up to the protein level. RESULTS We present a statistical model that carefully accounts for informative missingness in peak intensities and allows unbiased, model-based, protein-level estimation and inference. The model is applicable to both label-based and label-free quantitation experiments. We also provide automated, model-based, algorithms for filtering of proteins and peptides as well as imputation of missing values. Two LC/MS datasets are used to illustrate the methods. In simulation studies, our methods are shown to achieve substantially more discoveries than standard alternatives. AVAILABILITY The software has been made available in the open-source proteomics platform DAnTE (http://omics.pnl.gov/software/).

Deletion of GPR40 Impairs Glucose-Induced Insulin Secretion In Vivo in Mice Without Affecting Intracellular Fuel Metabolism in Islets

OBJECTIVE The G-protein–coupled receptor GPR40 mediates fatty acid potentiation of glucose-stimulated insulin secretion, but its contribution to insulin secretion in vivo and mechanisms of action remain uncertain. This study was aimed to ascertain whether GPR40 controls insulin secretion in vivo and modulates intracellular fuel metabolism in islets. RESEARCH DESIGN AND METHODS Insulin secretion and sensitivity were assessed in GPR40 knockout mice and their wild-type littermates by hyperglycemic clamps and hyperinsulinemic euglycemic clamps, respectively. Transcriptomic analysis, metabolic studies, and lipid profiling were used to ascertain whether GPR40 modulates intracellular fuel metabolism in islets. RESULTS Both glucose- and arginine-stimulated insulin secretion in vivo were decreased by ∼60% in GPR40 knockout fasted and fed mice, without changes in insulin sensitivity. Neither gene expression profiles nor intracellular metabolism of glucose and palmitate in isolated islets were affected by GPR40 deletion. Lipid profiling of isolated islets revealed that the increase in triglyceride and decrease in lyso-phosphatidylethanolamine species in response to palmitate in vitro was similar in wild-type and knockout islets. In contrast, the increase in intracellular inositol phosphate levels observed in wild-type islets in response to fatty acids in vitro was absent in knockout islets. CONCLUSIONS These results indicate that deletion of GPR40 impairs insulin secretion in vivo not only in response to fatty acids but also to glucose and arginine, without altering intracellular fuel metabolism in islets, via a mechanism that may involve the generation of inositol phosphates downstream of GPR40 activation.

Model-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation.

Macrophages are central players in immune response, manifesting divergent phenotypes to control inflammation and innate immunity through release of cytokines and other signaling factors. Recently, the focus on metabolism has been reemphasized as critical signaling and regulatory pathways of human pathophysiology, ranging from cancer to aging, often converge on metabolic responses. Here, we used genome‐scale modeling and multi‐omics (transcriptomics, proteomics, and metabolomics) analysis to assess metabolic features that are critical for macrophage activation. We constructed a genome‐scale metabolic network for the RAW 264.7 cell line to determine metabolic modulators of activation. Metabolites well‐known to be associated with immunoactivation (glucose and arginine) and immunosuppression (tryptophan and vitamin D3) were among the most critical effectors. Intracellular metabolic mechanisms were assessed, identifying a suppressive role for de‐novo nucleotide synthesis. Finally, underlying metabolic mechanisms of macrophage activation are identified by analyzing multi‐omic data obtained from LPS‐stimulated RAW cells in the context of our flux‐based predictions. Our study demonstrates metabolisms role in regulating activation may be greater than previously anticipated and elucidates underlying connections between activation and metabolic effectors.

Proteomic profiling of nonenzymatically glycated proteins in human plasma and erythrocyte membranes.

Nonenzymatic glycation of peptides and proteins by d-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. In this work, we report the first proteomics-based characterization of nonenzymatically glycated proteins in human plasma and erythrocyte membranes from individuals with normal glucose tolerance, impaired glucose tolerance, and type 2 diabetes mellitus. Phenylboronate affinity chromatography was used to enrich glycated proteins and glycated tryptic peptides from both human plasma and erythrocyte membranes. The enriched peptides were subsequently analyzed by liquid chromatography coupled with electron transfer dissociation-tandem mass spectrometry, resulting in the confident identification of 76 and 31 proteins from human plasma and erythrocyte membranes, respectively. Although most of the glycated proteins could be identified in samples from individuals with normal glucose tolerance, slightly higher numbers of glycated proteins and more glycation sites were identified in samples from individuals with impaired glucose tolerance and type 2 diabetes mellitus.

A reversed-phase capillary ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for comprehensive top-down/bottom-up lipid profiling

Lipidomics is a critical part of metabolomics and aims to study all the lipids within a living system. We present here the development and evaluation of a sensitive capillary UPLC-MS method for comprehensive top-down/bottom-up lipid profiling. Three different stationary phases were evaluated in terms of peak capacity, linearity, reproducibility, and limit of quantification (LOQ) using a mixture of lipid standards representative of the lipidome. The relative standard deviations of the retention times and peak abundances of the lipid standards were 0.29% and 7.7%, respectively, when using the optimized method. The linearity was acceptable at >0.99 over 3 orders of magnitude, and the LOQs were sub-fmol. To demonstrate the performance of the method in the analysis of complex samples, we analyzed lipids extracted from a human cell line, rat plasma, and a model human skin tissue, identifying 446, 444, and 370 unique lipids, respectively. Overall, the method provided either higher coverage of the lipidome, greater measurement sensitivity, or both, when compared to other approaches of global, untargeted lipid profiling based on chromatography coupled with MS.

GIM3E: condition-specific models of cellular metabolism developed from metabolomics and expression data

MOTIVATION Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been developed. RESULTS GIM(3)E (Gene Inactivation Moderated by Metabolism, Metabolomics and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics and cellular metabolomics data. GIM(3)E establishes metabolite use requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions and provides calculations of the turnover (production/consumption) flux of metabolites. GIM(3)E was used to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. AVAILABILITY GIM(3)E has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/ CONTACTS brianjamesschmidt@gmail.com