Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future

Abstract

Journal of MASS SPECTROMETRYMetabolomics is perhaps the most challenging of the -omics fields, given the complexity of an organism's metabolome and the rapid rate at which it changes. When one sets out to study metabolism there are numerous dynamic variables that can influence metabolism that must be considered. Recognizing the experimental challenges confronting researchers who undertake metabolism studies, workshops like the one at University of Alabama at Birmingham have been established to offer instructional guidance. A summary of the UAB course training materials is being published as a two-part Special Feature Tutorial. In this month's Part I the authors discuss details of good experimental design and sample collection and handling. In an upcoming Part II, the authors discuss in detail the various aspects of data analysis. in 2006, where her research focused on dietary and physical activity education interventions in adolescents. As a dietitian, a researcher and scientist her research team has conducted various clinical studies in the pediatric population investigating the contribution of dietinduced metabolic alterations on the interface between bone, muscle and fat. Employing strength training intervention during the critical developmental stage surrounding puberty to optimize the protective effect of the musculoskeletal system on feed forward effects across systems shifts the focus from the dogmatic concept of adiposity reduction. Most recently, she has begun to investigate the integral interactions encompassing the metabolome. She organized the young investigators' section of the workshop. Sara J. Cooper, Ph.D. Dr. Cooper is a Faculty Investigator at the HudsonAlpha Institute for Biotechnology. Her area of expertise lies at the intersection of metabolomics and genomics -her graduate work was focused on genomics, genetics, gene regulation, and development of high-throughput assays and data analysis pipelines for the large datasets. As a postdoctoral fellow with Stan Fields, she applied this experience to the new and growing field of metabolomics. Her current research projects include metabolomics-based methods for biomarker identification in pancreatic cancer, characterization of heritability of metabolite levels in yeast and human populations, and the use of yeast and human cell culture models to understand metabolic changes in human disease. She provided training in the use of GC-MS and 2D-GC in the workshop. identifying novel lipid-based mechanisms of immune regulation in autoimmunity and chronic inflammatory disease. He has established a method for lipid imaging in cryo-sections by MALDI-Imaging Mass Spectrometry using vacuum sublimation for matrix application. This technology is being applied to a number of areas, including identifying lipids modulating inflammatory processes in response to acute kidney injury, autoimmunity and kidney disease in Lupus, as well as those involved in the deterioration of ocular function with aging.Shuzhao Li, Ph.D. Dr. Li is an assistant professor at Emory University ...

Evaluation of a ketogenic diet for improvement of neurological recovery in individuals with acute spinal cord injury: a pilot, randomized safety and feasibility trial

“…As an adjunct or alternative to neurological assessments, we have performed an untargeted metabolomics via liquid chromatography-mass spectrometry (LC-MS)/MS global analysis on serum samples to identify potential biomarkers that can predict neurological recovery and explain the differences between groups. LC-MS/MS analysis and data processing (via MetaboAnalyst-www.metaboanalyst.ca and METLIN-http://metlin.scripps.edu) have been performed at UAB Targeted Metabolomics and Proteomics Laboratory with established procedures published elsewhere [31][32][33].…”

Accelerated, untargeted metabolomics analysis of cutaneous T‐cell lymphoma reveals metabolic shifts in plasma and tumor adjacent skins of xenograft mice

“…Last but not least, the applied metabolomics data analysis strategy “Mummichog” herein presented a greatly accelerated interpretation solution for HRLC‐MS analysis. This tool had been cited in several metabolomics review articles . It also had been integrated in the XCMS online workflow to operate directly on the entire metabolic features table .…”

Targeted Blood Metabolomic Study on Retinopathy of Prematurity

“…It is summed over all components and weighted to the Y accounted for by every single component. 43 Therefore, VIP ranking reflects the metabolites' contribution to the model. In this study, we select metabolites with VIP >1 as major discriminant metabolite to expand our selection, this criteria is similar to other studies.…”