metabolomische

Metabolomische, in English commonly referred to as metabolomics, is the systematic study of the repertoire of small-molecule metabolites in a biological system. It aims to identify, quantify, and interpret the dynamic metabolome in cells, tissues, biofluids, or entire organisms, reflecting genetic background, environmental influences, and physiological state. The field emphasizes phenotype through metabolism and complements genomics, transcriptomics, and proteomics.

Analytical methods center on high-throughput platforms, notably mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. These techniques are often coupled with chromatographic separations such as gas chromatography (GC) and liquid chromatography (LC) to improve metabolite coverage. Researchers pursue untargeted metabolomics to profile as many metabolites as possible, or targeted metabolomics to precisely quantify a defined set of compounds. Sample preparation, data acquisition, and careful experimental design are essential to reduce variability.

Data processing requires peak detection, alignment, normalization, and annotation. Metabolite identification relies on spectral libraries and reference standards, which can present challenges of confidence levels and unknowns. Statistical analyses, multivariate modeling, and pathway analysis enable interpretation, often integrated with genomics and microbiome data. Reporting and data sharing are guided by community standards and repositories like the Metabolomics Standards Initiative (MSI) and MetaboLights.

Applications span biomedical research, biomarker discovery, pharmacometabolomics, nutrition, environmental and toxicological studies, and plant and microbial metabolism. The field supports systems biology by linking genotype to phenotype through metabolic pathways. Ongoing challenges include coverage gaps, metabolite identification confidence, reproducibility, and data integration, with ongoing efforts toward standardization and comprehensive metabolite databases.