Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts

Metabolic profiling reveals disorder of amino acid metabolism in four brain regions from a rat model of chronic unpredictable mild stress

Chronic stress is closely linked to clinical depression, which could be assessed by a chronic unpredictable mild stress (CUMS) animal model. We present here a GC/MS-based metabolic profiling approach to investigate neurochemical changes in the cerebral cortex, hippocampus, thalamus, and remaining brain tissues. Multi-criteria assessment for multivariate statistics could identify differential metabolites between the CUMS-model rats versus the healthy controls. This study demonstrates that the significantly perturbed metabolites mainly involving amino acids play an indispensable role in regulating neural activity in the brain. Therefore, results obtained from such metabolic profiling strategy potentially provide a unique perspective on molecular mechanisms of chronic stress.

1H NMR metabonomics approach to the disease continuum of diabetic complications and premature death

Subtle metabolic changes precede and accompany chronic vascular complications, which are the primary causes of premature death in diabetes. To obtain a multimetabolite characterization of these high-risk individuals, we measured proton nuclear magnetic resonance (1H NMR) data from the serum of 613 patients with type I diabetes and a diverse spread of complications. We developed a new metabonomics framework to visualize and interpret the data and to link the metabolic profiles to the underlying diagnostic and biochemical variables. Our results indicate complex interactions between diabetic kidney disease, insulin resistance and the metabolic syndrome. We illustrate how a single 1H NMR protocol is able to identify the polydiagnostic metabolite manifold of type I diabetes and how its alterations translate to clinical phenotypes, clustering of micro- and macrovascular complications, and mortality during several years of follow-up. This work demonstrates the diffuse nature of complex vascular diseases and the limitations of single diagnostic biomarkers. However, it also promises cost-effective solutions through high-throughput analytics and advanced computational methods, as applied here in a case that is representative of the real clinical situation.

1H NMR metabolite fingerprinting and metabolomic analysis of perchloric acid extracts from plant tissues

Metabolite fingerprinting provides a powerful method for discriminating between biological samples on the basis of differences in metabolism caused by such factors as growth conditions, developmental stage or genotype. This protocol describes a technique for acquiring metabolite fingerprints from samples of plant origin. The preferred method involves freezing the tissue rapidly to stop metabolism, extracting soluble metabolites using perchloric acid (HClO4) and then obtaining a fingerprint of the metabolic composition of the sample using 1D 1H NMR spectroscopy. The spectral fingerprints of multiple samples may be analyzed using either unsupervised or supervised multivariate statistical methods, and these approaches are illustrated with data obtained from the developing seeds of two genotypes of sunflower (Helianthus annuus). Preparation of plant extracts for analysis takes 2-3 d, but multiple samples can be processed in parallel and subsequent acquisition of NMR spectra takes approximately 30 min per sample, allowing 24-48 samples to be analyzed in a week.