Hunting Gut Microbiota Metabolites

Elucidating the Metabolic Interplay with Their Human Host

  • Fig. 1: Representation of the formation of sulfated metabolites in the human gut microbiota and four microbiota derived sulfated molecules [9] - published by The Royal Society of Chemistry.Fig. 1: Representation of the formation of sulfated metabolites in the human gut microbiota and four microbiota derived sulfated molecules [9] - published by The Royal Society of Chemistry.
  • Fig. 1: Representation of the formation of sulfated metabolites in the human gut microbiota and four microbiota derived sulfated molecules [9] - published by The Royal Society of Chemistry.
  • Fig. 2: a) Chemical probe design. The reactive site (green) is connected by a linker (purple) to the Noc-cleavage site (red). This probe is conjugated to magnetic beads (orange) by a spacer (black). b) The general workflow for analysis of metabolic amines using the chemical probe [8].

Recent metagenomic studies have revealed the impact of dysregulated gut microbiota on human physiology and disease development. The fact that an altered gut microbiota composition is linked to non-bowel diseases can be explained through metabolic interaction of these microbes with their human host. Metabolomics is the method of choice to elucidate this metabolic interaction and new methods are required for selective investigation of this complex co-metabolism.

Metabolomics Techniques for Microbiota Metabolism Analysis in Human Samples

One of the most exciting scientific developments in the past decade has been the growing understanding that the microbiota is part of the human “ecosystem” and directly impacts physiology. This complex community of trillions of bacteria, fungi, and viruses is highly metabolically active and has co-evolved with the human host. Microbiota populate every surface of the human body, most notably the gastrointestinal tract and the skin. Not only do the microbes of the microbiota outnumber human cells by a factor of about two to five, they possess approximately one hundred times more genes than are present in the human genome. This large increase in human genetic information corresponds to a large number of additional enzyme classes with biochemical potentials which may differ radically from those of the host. These additional genes in turn give rise to a diverse range of biochemical and metabolic activities, producing a vast number of metabolites that are taken up by the human host and resulting in complex, intertwined metabolic networks (Fig. 1).

As a result of this shared metabolism, the human microbiota has been referred to as an additional organ or even a “second brain” as it significantly influences diverse human metabolic pathways including nutrition, detoxification, hormonal homeostasis, immune tolerance, and especially inflammation. Mounting evidence indicates that a dysregulated gut microflora initiates or contributes to a variety of diseases, including cancer, diabetes, obesity, cardiovascular diseases, and inflammatory bowel disease among others. Recently, several studies have begun to shed light on microbiota dysbiosis, however, our understanding of the overall metabolic interactions of microbial communities with their host with respect to disease development is still limited.

Detailed elucidation of the metabolic interplay between the host and its gut microbiota in the context of disease onset through analysis of the metabolome has a tremendous potential for discovery of diagnostic markers of disease, improved drug efficacy and clinical and lifestyle interventions. Moreover, greater understanding of the influence of the gut microbiota on the host’s metabolism will provide access to novel disease treatment and drug development opportunities.

Global Metabolomics Analysis

Mass spectrometric metabolomics is the method of choice for the investigation of metabolism due to its sensitivity to metabolites over several orders of magnitude. Global metabolomics analysis can be divided in three major parts, namely metabolite extraction, mass spectrometric detection, and data analysis. This standard workflow has become routine in the analysis of human samples, however, a detailed analysis of microbial metabolism requires more advanced techniques due to the low concentrations and potentially unusual structures of the metabolites involved. For this reason, analysis of metabolites produced or altered by microbes has generally required targeted metabolomics approaches, often dictated by the relative limitations and strengths of the analytical platform. Common classes of microbial metabolites are bile acids, short-chain fatty acids, trimethylamine N-oxide (TMAO), tryptophan metabolites, and anthocyanins [1,2]. Targeted analyses of bile acids, for example, has revealed numerous previously unknown metabolites. The use of germ-free mice has also proven fruitful in elucidating the physiological effects of certain microbes in the gut microbiota, for example, the link between obesity, short-chain fatty acids, and the gut microbiome. The availability of tools aimed at advancing the data analysis part of the metabolomics workflow has also improved dramatically, from open-source software packages for peak detection and alignment such as XCMS and MZmine to comprehensive and stratified databases of metabolites including Metlin, the Human Metabolome Database (HMDB), and Global Natural Product Social Molecular Networking (GNPS), which have significantly improved general metabolite identification [3-7].

Selective Chemical Biology Tools

Chemical biology tools have made major contributions to biological and medically relevant findings in proteomics, transcriptomics and genomics analysis. This is in stark contrast to metabolomics research, for which these tools are rare. We have recently published two new methods at the interface of chemistry and biology that permit a more informative analysis of biological samples [8,9]. Both methods have been developed for selective investigation of microbial metabolism in humans and aim to identify previously unknown metabolites. One approach was the development of chemoselective probes that combine immobilization to magnetic beads with a bioorthogonal cleavage site, which we have newly adapted from a protecting group that is labile under mild, palladium-catalyzed conditions (Fig. 2). This architecture allows metabolites to be captured, tagged with a strongly ionizable conjugate, removed from the sample matrix, and released.  The optimized probe was utilized on fecal samples, the sample type most directly influenced by metabolically active microbial communities. Analysis revealed previously unknown metabolites and due to conjugation of the mass-spectrometric tag and separation from the sample background, the sensitivity towards some metabolites increased more than 2000-fold.

A second approach focused on selective investigation of sulfated metabolites, which result from the phase II clearance of xenobiotics by the human body and is linked to microbiota-human host co-metabolism [9]. The method is based on pretreatment of the sample with a purified and highly promiscuous arylsulfatase. A very high degree of enzymatic purity is critical, in order to avoid undesired metabolic background conversions. Comparison of the pretreated sample with an untreated sample after analysis using ultra high-performance liquid chromatography-mass spectrometric techniques led to the identification of 206 sulfated metabolites, exceeding the number of sulfated metabolites previously catalogued by a factor of three to four. Seven previously reported metabolites derived from human-microbiota co-metabolism were among these sulfated compounds, demonstrating the efficacy of the technique. This concept has also been successfully applied to the analysis of glucuronidated metabolites, the most common phase II modification leading to the identification of several polyphenolic metabolites that are derived from microbiota metabolism of dietary macromolecules in the human body [10].

Conclusion

Detailed investigation of microbiota-derived metabolites has a high potential to identify unknown bioactive compounds. These molecules can have diverse functions of interest for different application fields, e.g. biomarker discovery, antimicrobial drugs, quorum sensing, and dietary markers. A more comprehensive microbiota-derived metabolite analysis will require new chemical, bioinformatic and analytical methods to identify, elucidate and validate metabolite structures. These new techniques will play key roles in improving our understanding of the metabolic interaction of microbiota with their human host, allowing us to utilize and manipulate microbiota metabolism to improve healthcare.

​Authors
Louis Conway1, Mario Correia1, Daniel Globisch1

Affiliation
1Department of Medicinal Chemistry, Science for Life Laboratory, Uppsala University, Uppsala, Sweden

Contact
Assoc. Prof. Dr. Daniel Globisch

Uppsala University, Department of
Medicinal Chemistry, Uppsala, Sweden
Daniel.globisch@scilifelab.uu.se

 

References

[1]        Nicholson JK, Holmes E, Kinross J, Burcelin R, Gibson G, Jia W, et al. Host-gut microbiota metabolic interactions. Science. 2012;336(6086):1262-7.

[2]        Donia MS, Fischbach MA. Small Molecules from the Human Microbiota. Science. 2015;349(6246):1254766.

[3]        Huan T, Forsberg EM, Rinehart D, Johnson CH, Ivanisevic J, Benton HP, et al. Systems biology guided by XCMS Online metabolomics. Nat Meth. 2017;14(5):461-2.

[4]        Wikoff WR, Anfora AT, Liu J, Schultz PG, Lesley SA, Peters EC, et al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc Natl Acad Sci U S A. 2009;106(10):3698-703.

[5]        Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vázquez-Fresno R, et al. HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018;46(D1):D608-D17.

[6]        Pluskal T, Castillo S, Villar-Briones A, Oresic M. MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics. 2010;11:395.

[7]        Wang M, Carver JJ, Phelan VV, Sanchez LM, Garg N, Peng Y, et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat Biotechnol. 2016;34(8):828-37.

[8]        Garg N, Conway LP, Ballet C, Correia MSP, Olsson FKS, Vujasinovic M, et al. Chemoselective Probe Containing a Unique Bioorthogonal Cleavage Site for Investigation of Gut Microbiota Metabolism. Angew Chem Int Ed Engl. 2018;57(42):13805-9.

[9]        Ballet C, Correia MSP, Conway LP, Locher TL, Lehmann LC, Garg N, et al. New enzymatic and mass spectrometric methodology for the selective investigation of gut microbiota-derived metabolites. Chem Sci. 2018;9(29):6233-9.

[10]      Correia MSP, Rao M, Ballet C, Globisch D. Enzymatic and mass spectrometric analysis for selective identification of glucuronidated metabolites in human samples. Chembiochem. 2019.

 

Contact

Uppsala University, Department of Medicinal Chemistry


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