Machine learning for data integration in human gut microbiome
Review article, 2022

Recent studies have demonstrated that gut microbiota plays critical roles in various human diseases. High-throughput technology has been widely applied to characterize the microbial ecosystems, which led to an explosion of different types of molecular profiling data, such as metagenomics, metatranscriptomics and metabolomics. For analysis of such data, machine learning algorithms have shown to be useful for identifying key molecular signatures, discovering potential patient stratifications, and particularly for generating models that can accurately predict phenotypes. In this review, we first discuss how dysbiosis of the intestinal microbiota is linked to human disease development and how potential modulation strategies of the gut microbial ecosystem can be used for disease treatment. In addition, we introduce categories and workflows of different machine learning approaches, and how they can be used to perform integrative analysis of multi-omics data. Finally, we review advances of machine learning in gut microbiome applications and discuss related challenges. Based on this we conclude that machine learning is very well suited for analysis of gut microbiome and that these approaches can be useful for development of gut microbe-targeted therapies, which ultimately can help in achieving personalized and precision medicine.

Precision medicine

Multi-omics

Gut microbiome

Machine learning

Data integration

Author

Peishun Li

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Hao Luo

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Boyang Ji

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

BioInnovation Institute

Jens B Nielsen

BioInnovation Institute

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Microbial Cell Factories

14752859 (eISSN)

Vol. 21 1 241

Gut microbiome effects on cardiometabolic disease through metabolism-modifying metabolites (Gut-MMM)

Novo Nordisk Foundation (NNF15OC0016798), 2016-07-01 -- 2022-12-31.

Subject Categories

Language Technology (Computational Linguistics)

Bioinformatics (Computational Biology)

Bioinformatics and Systems Biology

DOI

10.1186/s12934-022-01973-4

PubMed

36419034

More information

Latest update

12/1/2022