Trends in Biotechnology
ReviewComputational tools for modeling xenometabolism of the human gut microbiota
Section snippets
Gut microbiota as a site of xenometabolism
The gut microbiota has been shown to modify or metabolize several kinds of xenobiotics, from novel cancer drugs through millennia old analgesics to dietary components 1, 2, 3, 4, 5, 6, 7. Recent studies have also highlighted the feasibility of exploiting and manipulating this microbe-mediated xenometabolism to improve the host health or to prohibit medicinal side effects. For example, Wallace et al. [6] recently showed that a deleterious biotransformation of the cancer drug irinotecan can be
Role of modeling in tackling complexity of xenometabolic processes
Xenometabolic processes in the gut can be highly complex due to three main reasons: the widespread promiscuity of metabolic enzymes; the compositional complexity of the gut microbiota; and the interactions between the host and the microbe-mediated xenometabolism. The promiscuity of metabolic enzymes 24, 25, 26 means that the number of possible routes through which a xenobiotic compound can be metabolized or modified increases combinatorially with the enzymatic repertoire of the microbiota. The
Hierarchy of xenometabolic processes in the gut
The general metabolic processes that a xenobiotic compound can undergo in the gut microbiota can be conceptually organized into three levels: community, species, and enzymes (Figure 1). Complex xenometabolic pathways often emerge through the functional interplay within and across these hierarchical levels. At the topmost level, the spatial and compositional structure of the microbial community influences the survival, activity, and procreation of species in the gut environment, and hence the
Enzyme level: promiscuous enzymes drive and enlarge xenometabolism
Enzymes can often catalyze more reactions than those listed in pathway databases like KEGG [34] and may exhibit functions and biochemical features beyond the current description 24, 25. For example, xenobiotic metabolism in the liver is driven by highly promiscuous enzymes like cytochrome P450 oxidases and glutathione S-transferases [35]. Indeed, given the prominent role of the liver in xenobiotic detoxification (Box 1), numerous enzyme–xenobiotic relationships have been described in the
Species level: enzyme availability and interaction between xeno- and native bacterial metabolism
One of the well-known examples of xenometabolism that is specific to a particular gut bacterium is the metabolism of digoxin by Eggerthella lenta [10]. Association between bacterial species and specific metabolites have also been observed in several other studies 5, 6, 54, 55. Although species-level specificity of xenometabolism is known only for a small number of compounds, the known associations can be used to narrow down the list of candidate biotransforming species for structurally similar
Community level: community structure determines the xenometabolic pathways
A typical gut microbiota consists of hundreds of diverse microbial species 13, 69, 70. This compositional complexity, together with the spatial heterogeneity of the microbiota 71, 72, 73, poses arguably the biggest challenge for modeling xenometabolism in the gut. A microbial consortium can transform a certain xenobiotic compound in qualitatively different ways than any single species (Figure 1). A community is especially more likely to perform multiple consecutive transformation steps due to
Limitations of the current tools for modeling xenometabolism
Although the above-discussed computational tools can, in principle, be used to model the individual steps of xenometabolism, there are several critical limitations that must be overcome before their application. Most of these tools originate from diverse disciplines like bioremediation and industrial biotechnology and are currently restricted to applications in their respective fields, and sometimes restricted to even narrower contexts (Table 1). Their power for predicting gut microbe-mediated
Concluding remarks and future perspectives
Despite the proven relevance of the microbiota-mediated xenometabolism to human health, there are only a few published approaches that specifically tackle the task of modeling the underlying complex biochemical processes. Although several challenges remain (Box 2), integration of the available tools into a single platform can be a powerful approach towards holistic modeling of xenometabolism. We envision such an integrative approach as illustrated in Figure 3. For physiologically relevant
Acknowledgments
We thank A. Zelezniak and S. Andrejev for comments on the manuscript. M.S. was supported by the EMBL interdisciplinary postdoctoral program.
Glossary
- BRENDA
- Braunschweig Enzyme Database – one of the main collections of enzyme function and activity data. The database contains several xenobiotic–enzyme interactions (for examples, see Figure 2).
- Constraint-based modeling
- a metabolic modeling technique that uses mass balance, reaction directionality and metabolite uptake/secretion constraints to estimate intracellular fluxes (reaction rates) for a given metabolic network.
- Enterohepatic cycle
- circulation of native or xenobiotic compounds between liver
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