Analytical approaches to metabolomics and applications to systems biology.
Phenotypic expression of renal diseases encompasses a complex interaction between genetic, environmental, and local tissue factors. The level of complexity requires integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate metabolites from biological samples. The small molecules represent the end result of complexity of biological processes in a given cell, tissue, or organ, and thus form attractive candidates to understand disease phenotypes. Metabolites represent a diverse group of low-molecular-weight structures including lipids, amino acids, peptides, nucleic acids, and organic acids, which makes comprehensive analysis a difficult analytical challenge. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled separation, characterization, detection, and quantification of such chemically diverse structures. Continued development of bioinformatics and analytical strategies will accelerate widespread use and integration of metabolomics into systems biology. Here, we will discuss analytical and bioinformatic techniques and highlight recent studies that use metabolomics in understanding pathophysiology of disease processes.
Department of Internal Medicine, Hennepin County Medical Center and University of Minnesota School of Medicine, Minneapolis, MN, USA.
Jeffrey H
JH
Wang
Jaeman
J
Byun
Subramaniam
S
Pennathur
D000818:Animals; D002318:Cardiovascular Diseases / Q000378:metabolism; D003627:Data Interpretation, Statistical; D057225:Data Mining; D003928:Diabetic Nephropathies / Q000378:metabolism; D006801:Humans; D016030:Kidney Transplantation; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D013058:Mass Spectrometry; D055432:Metabolomics; D011471:Prostatic Neoplasms / Q000378:metabolism; D049490:Systems Biology / Q000379:methods*