The overall goal of this proposal is to help define key metabolic changes in the liver metabolome to aid research into a variety of diseases including hepatic steatosis, inflammation, and drug toxicity. These diseases of the liver are an increasing burden on the healthcare system with growing prevalence of obesity, type II diabetes, and drug and alcohol abuse. Metabolomics, or the study of chemical fingerprints that biological processes leave behind, is a rapidly advancing discipline that has great promise to improve our understanding of these pathological conditions. However, there remain significant gaps in our understanding of how extraction methodologies and separation approaches influence the data used in downstream chemometric analyses. Therefore, we have designed the four specific aims that address fundamentally essential aspects of any metabolomic study based on liquid chromatography coupled with mass spectrometry: extraction, separation, and identification with specific reference to the mammalian liver. We hypothesize that reproducible extraction and separation methodologies can be developed that are independent of disease state. To date, there has not been an organized, concerted effort to optimize and standardize these most essential steps when conducting a metabolomic study. While here we focus on liver tissue, these approaches will serve as a foundation for other tissues and biofluids as well as platforms including nuclear magnetic resonance spectroscopy and gas chromatography coupled with mass spectrometry. Based on the efforts of three independent laboratories with well-recognized expertise in metabolomics (Griffin Lab at the University of Cambridge and the UK Medical Research Council, Gonzalez Lab at the National Cancer Institute, and the Patterson Lab at Penn State University) we plan to systematically address and optimize each step (metabolite extraction, separation by liquid chromatography, and identification by mass spectrometry) across a range of metabolite classes, polarities and metabolic pathways, thus ensuring the delivery of high quality data to the vast array of already existing metabolomic data analysis platforms. Furthermore, in addition to publication in peer-reviewed journals, we will make our protocols and data freely available to the wider scientific community, including both academia and pharma, in an open format by making use of community-led open source facilities such as the European Bioinformatics Institute's MetaboLight (central repository for experimental metabolomics data) and the ISA-TAB initiative (a unified tool for meta data description of omic experiments).
There remain significant gaps in our understanding of how extraction methodologies and separation approaches influence the data used in downstream chemometric analyses. Therefore, we have designed the four specific aims that address fundamentally essential aspects of any metabolomic study based on liquid chromatography coupled with mass spectrometry: extraction, separation, and identification with specific reference to the mammalian liver.
|Cai, Jingwei; Nichols, Robert G; Koo, Imhoi et al. (2018) Multiplatform Physiologic and Metabolic Phenotyping Reveals Microbial Toxicity. mSystems 3:|
|Pathak, Preeti; Xie, Cen; Nichols, Robert G et al. (2018) Intestine farnesoid X receptor agonist and the gut microbiota activate G-protein bile acid receptor-1 signaling to improve metabolism. Hepatology 68:1574-1588|
|Belton, Kerry R; Tian, Yuan; Zhang, Limin et al. (2018) Metabolomics Reveals Aryl Hydrocarbon Receptor Activation Induces Liver and Mammary Gland Metabolic Dysfunction in Lactating Mice. J Proteome Res 17:1375-1382|
|Sanders, Francis W B; Acharjee, Animesh; Walker, Celia et al. (2018) Hepatic steatosis risk is partly driven by increased de novo lipogenesis following carbohydrate consumption. Genome Biol 19:79|
|Maan, Meenu; Peters, Jeffrey M; Dutta, Mainak et al. (2018) Lipid metabolism and lipophagy in cancer. Biochem Biophys Res Commun 504:582-589|
|Xie, Cen; Jiang, Changtao; Shi, Jingmin et al. (2017) An Intestinal Farnesoid X Receptor-Ceramide Signaling Axis Modulates Hepatic Gluconeogenesis in Mice. Diabetes 66:613-626|
|Zhang, Limin; Nichols, Robert G; Patterson, Andrew D (2017) The aryl hydrocarbon receptor as a moderator of host-microbiota communication. Curr Opin Toxicol 2:30-35|
|Li, Guolin; Xie, Cen; Lu, Siyu et al. (2017) Intermittent Fasting Promotes White Adipose Browning and Decreases Obesity by Shaping the Gut Microbiota. Cell Metab 26:672-685.e4|
|Murray, Iain A; Nichols, Robert G; Zhang, Limin et al. (2016) Expression of the aryl hydrocarbon receptor contributes to the establishment of intestinal microbial community structure in mice. Sci Rep 6:33969|
|Ament, Zsuzsanna; West, James A; Stanley, Elizabeth et al. (2016) PPAR-pan activation induces hepatic oxidative stress and lipidomic remodelling. Free Radic Biol Med 95:357-68|
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