Computational tools for modeling xenometabolism of the human gut microbiota

Klünemann, Martina; M, Schmid; Patil, Kiran Raosaheb

doi:10.1016/j.tibtech.2014.01.005

Cited by 23 publications

(15 citation statements)

References 86 publications

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“…Novel, large-scale approaches, including in-silico and complex computational tools[79], are now needed to provide in-depth elucidation of the possible pathways through which the gut microbiota may modify xenobiotics and vice versa as well as their combined metabolic effects via ABCB1/MDR1 p-gp (and other transporters) on host immunity and functions in IBD pathogenesis.…”

Section: Conclusion and Future Perspectivementioning

confidence: 99%

P-glycoprotein multidrug transporter in inflammatory bowel diseases: More questions than answers

Cario

2017

WJG

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The gastrointestinal barrier is constantly exposed to numerous environmental substrates that are foreign and potentially harmful. These xenobiotics can cause shifts in the intestinal microbiota composition, affect mucosal immune responses, disturb tissue integrity and impair regeneration. The multidrug transporter ABCB1/MDR1 p-glycoprotein (p-gp) plays a key role at the front line of host defence by efficiently protecting the gastrointestinal barrier from xenobiotic accumulation. This Editorial discusses how altered expression and function of ABCB1/MDR1 p-gp may contribute to the development and persistence of chronic intestinal inflammation in inflammatory bowel diseases (IBD). Recent evidence implies multiple interactions between intestinal microbiota, innate immunity and xenobiotic metabolism via p-gp. While decreased efflux activity may promote disease susceptibility and drug toxicity, increased efflux activity may confer resistance to therapeutic drugs in IBD. Mice deficient in MDR1A develop spontaneously chronic colitis, providing a highly valuable murine IBD model for the study of intestinal epithelial barrier function, immunoregulation, infectious co-triggers and novel therapeutic approaches. Possible associations of human ABCB1 gene polymorphisms with IBD susceptibility have been evaluated, but results are inconsistent. Future studies must focus on further elucidation of the pathophysiological relevance and immunological functions of p-gp and how its ambiguous effects could be therapeutically targeted in IBD.

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Section: Conclusion and Future Perspectivementioning

confidence: 99%

P-glycoprotein multidrug transporter in inflammatory bowel diseases: More questions than answers

Cario

2017

WJG

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“…This resource enables modeling of gut microbial communities and their interactions with the human host [63] . However, these microbial metabolic models do not yet capture xenobiotic metabolism [64] , which will require the use using context-based comparative genomics techniques [65] , to identify microbial enzymes known to modify drugs. The AGORA models can be combined into a microbiota community model [63] and parameterized using metagenomics data.…”

Section: Introductionmentioning

confidence: 99%

Quantitative systems pharmacology and the personalized drug–microbiota–diet axis

Thiele

Clancy

Heinken

et al. 2017

Current Opinion in Systems Biology

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Precision medicine is an emerging paradigm that aims at maximizing the benefits and minimizing the adverse effects of drugs. Realistic mechanistic models are needed to understand and limit heterogeneity in drug responses. While pharmacokinetic models describe in detail a drug's absorption and metabolism, they generally do not account for individual variations in response to environmental influences, in addition to genetic variation. For instance, the human gut microbiota metabolizes drugs and is modulated by diet, and it exhibits significant variation among individuals. However, the influence of the gut microbiota on drug failure or drug side effects is under-researched. Here, we review recent advances in computational modeling approaches that could contribute to a better, mechanism-based understanding of drug–microbiota–diet interactions and their contribution to individual drug responses. By integrating systems biology and quantitative systems pharmacology with microbiology and nutrition, the conceptually and technologically demand for novel approaches could be met to enable the study of individual variability, thereby providing breakthrough support for progress in precision medicine.

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“…[26][27][28] Since intestinal motility, nutrient intake, 29,30 and drugs affect bacterial growth, 31 physiology and microbiome composition, 32,33 incorporation of genome-scale metabolic models of the microbiota into the pharmacokinetic modeling framework might further enhance the ability of these integrative models to predict in vivo metabolism of specific drugs. Improved in silico estimation of drug absorption, 34,35 and putative host [36][37][38][39] and bacterial [40][41][42] xenobiotic biotransformation in combination with systematic experimental studies of microbial drug metabolism, 6 will facilitate accurate prediction of in vivo drug metabolism with integrative pharmacokinetic models in the near future. 43,44 Understanding the role of microbiota in drug metabolism may be instrumental for predicting and controlling adverse effects, because microbiota and host metabolism can be modulated with different interventions.…”

Section: Discussionmentioning

confidence: 99%

Insights from pharmacokinetic models of host-microbiome drug metabolism

2019

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Increasing evidence suggests a role of the gut microbiota in patients' response to medicinal drugs. In our recent study, we combined genomics of human gut commensals and gnotobiotic animal experiments to quantify microbiota and host contributions to drug metabolism. Informed by experimental data, we built a physiology-based pharmacokinetic model of drug metabolism that includes intestinal compartments with microbiome drug-metabolizing activity. This model successfully predicted serum levels of metabolites of three different drugs, quantified microbial contribution to systemic drug metabolite exposure, and simulated the effect of different parameters on host and microbiota drug metabolism. In this addendum, we expand these simulations to assess the effect of microbiota on the systemic drug and metabolite levels under conditions of altered host physiology, microbiota drug-metabolizing activity or physico-chemical properties of drugs. This work illustrates how and under which circumstances the gut microbiome may influence drug pharmacokinetics, and discusses broader implications of expanded pharmacokinetic models.

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Computational tools for modeling xenometabolism of the human gut microbiota

Cited by 23 publications

References 86 publications

P-glycoprotein multidrug transporter in inflammatory bowel diseases: More questions than answers

P-glycoprotein multidrug transporter in inflammatory bowel diseases: More questions than answers

Quantitative systems pharmacology and the personalized drug–microbiota–diet axis

Insights from pharmacokinetic models of host-microbiome drug metabolism

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