Recent Advances of Microbiome-Associated Metabolomics Profiling in Liver Disease: Principles, Mechanisms, and Applications

Int J Mol Sci. 2021 Jan 25;22(3):1160. doi: 10.3390/ijms22031160.

Abstract

Advances in high-throughput screening of metabolic stability in liver and gut microbiota are able to identify and quantify small-molecule metabolites (metabolome) in different cellular microenvironments that are closest to their phenotypes. Metagenomics and metabolomics are largely recognized to be the "-omics" disciplines for clinical therapeutic screening. Here, metabolomics activity screening in liver disease (LD) and gut microbiomes has significantly delivered the integration of metabolomics data (i.e., a set of endogenous metabolites) with metabolic pathways in cellular environments that can be tested for biological functions (i.e., phenotypes). A growing literature in LD and gut microbiomes reports the use of metabolites as therapeutic targets or biomarkers. Although growing evidence connects liver fibrosis, cirrhosis, and hepatocellular carcinoma, the genetic and metabolic factors are still mainly unknown. Herein, we reviewed proof-of-concept mechanisms for metabolomics-based LD and gut microbiotas' role from several studies (nuclear magnetic resonance, gas/lipid chromatography, spectroscopy coupled with mass spectrometry, and capillary electrophoresis). A deeper understanding of these axes is a prerequisite for optimizing therapeutic strategies to improve liver health.

Keywords: discriminations; gut microbiome; liver therapies; metabolic engineering; metabolomics; scientific applications.

Publication types

  • Review

MeSH terms

  • Animals
  • Biomarkers
  • Computational Biology / methods
  • Disease Susceptibility*
  • Energy Metabolism
  • Gene Expression Profiling
  • Genomics / methods
  • Humans
  • Liver Diseases / diagnosis
  • Liver Diseases / etiology*
  • Liver Diseases / metabolism*
  • Liver Diseases / therapy
  • Metabolome*
  • Metabolomics* / methods
  • Microbiota*
  • Phenomics

Substances

  • Biomarkers