The microbiome and metabolomics - an intersection of interdisciplinary research
Web of Science database publications analysis assessed on February 5, 2022, www.webofscience.com

The microbiome and metabolomics - an intersection of interdisciplinary research

The microbiome has become a hot topic for research recently, and metabolomics plays its important piece in the microbiome puzzle. Metabolites can be derived from host and/or microbiome metabolism, ingested through diet or medication, and/or environmental sources and are not limited to a single source (i.e., some metabolites may be produced by both host and microbe). Number of publications on “microbiome” with “metabolomics” grows annually by 30-50%, and the split between various research areas is shown in the title picture [1].

Comprehensive characterization of metabolites from the microbiome possesses significant challenges and require significant expertise in the powerful analytical methods, such as mass-spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. In the meantime, traditional microbiologists look into the microbe-microbe and microbe-host interactions from the biological point of view, trying to elucidate the functional role of metabolites and their impact on human, animal and environmental health. This creates a gap between microbiome scientists that want to understand the role of microbial metabolites in microbiome systems and the skills required to generate and interpret complex metabolomics data sets.

"Better communication across the chemistry and biology disciplines will further reveal the "dark matter" within microbiomes"
Quinn et al. [2]
Metabolite Quantification: from absolute to qualitative

Depending on the metabolomics approach, metabolite identification can range from highly certain to less certain, which impacts biological interpretation of data. Depending on the research goals, extensive validation of a chemical structure may not always be required. The same applies to the quantification: accurate quantification comes at the cost of measuring only a few compounds at a time [2].

Thus, training researchers with microbiome/ biological background in interpreting the technical language of metabolomics data would be highly beneficial. As an example, such a training is offered by The Metabolomics Innovation Centre (Canada). The program known as ‘Research Hotel’ for visiting scientists offers access to metabolomics facilities, as well as active mentoring for national and international visitors.

Integration of multiomics - from https://www.biomech.ulg.ac.be/project/multi-omics/

The examples of microbiome-metabolomics research vary from studying their cross-talk in human diseases to environmental and agricultural applications. The growth of ‘omic techniques to microbiome studies includes genomics/metagenomics, transcriptomics/meta-transcriptomics, proteomics/meta-proteomics, and metabolomics to generate multiple datasets from a single sample. Moving forward, with the cost of ‘omics decrease, and more tools are developed for data integration, storage, sharing, analysis and visualization, multi-omic strategies become more routine approach in the microbiome studies [3].

Going forward, the value of metabolome analysis transforms into the technology for the discovery of active drivers of biological processes (so called 'activity metabolomics').

"It is now clear that the metabolome affects cellular physiology through modulation of other 'omics' levels, including the genome, epigenome, transcriptome and proteome"
Rinschen et al. [4]

It is an interesting journey ahead, and the metabolomics - microbiome discussions will continue to bring together top researchers in both chemistry and biology.

[1] Web of Science database publications analysis assessed on February 5, 2022,

[2] “Bridging the gap between analytical and microbiobial sciences in microbiome research

[3] “Multi ‘omic data integration: A review of concepts, considerations, and approaches

[4] "Identification of bioactive metabolites using activity metabolomics"

Edgar N.

Chief Data Officer | Gen AI Products Innovation & Strategy | Advisory Board | Tech Health

3 年
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