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Review
. 2018 May;9(5):432-445.
doi: 10.1007/s13238-018-0547-2. Epub 2018 Apr 28.

Pharmacomicrobiomics: a novel route towards personalized medicine?

Affiliations
Review

Pharmacomicrobiomics: a novel route towards personalized medicine?

Marwah Doestzada et al. Protein Cell. 2018 May.

Abstract

Inter-individual heterogeneity in drug response is a serious problem that affects the patient's wellbeing and poses enormous clinical and financial burdens on a societal level. Pharmacogenomics has been at the forefront of research into the impact of individual genetic background on drug response variability or drug toxicity, and recently the gut microbiome, which has also been called the second genome, has been recognized as an important player in this respect. Moreover, the microbiome is a very attractive target for improving drug efficacy and safety due to the opportunities to manipulate its composition. Pharmacomicrobiomics is an emerging field that investigates the interplay of microbiome variation and drugs response and disposition (absorption, distribution, metabolism and excretion). In this review, we provide a historical overview and examine current state-of-the-art knowledge on the complex interactions between gut microbiome, host and drugs. We argue that combining pharmacogenomics and pharmacomicrobiomics will provide an important foundation for making major advances in personalized medicine.

Keywords: drug metabolism; gut microbiome; personalized medicine.

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Figures

Figure 1
Figure 1
Sites and types of reactions for drug metabolism. Bacterial enzymes can participate in drug metabolism mainly through reductive and hydrolytic reactions. Drugs and their metabolites can be absorbed from the intestine and transported via the portal vein to the liver, where a fraction of them will be taken up and another fraction will spill over to the systemic circulation. Hepatic enzymes mainly conduct oxidative and conjugative reactions. Subsequently, drugs and/or their metabolites can be excreted back into the blood to be transported to targeted tissues, removed by the kidney via the urine, or directly excreted by the liver via the biliary system back into the gut lumen
Figure 2
Figure 2
Drug-microbe effects. (A) Impact of drugs on the gut microbiome: drugs can perturb microbial composition and function. (B) Direct effect of gut microbiome on drug efficacy and toxicity: microbial transformation can activate or inactivate drugs, or induce drug toxicity to the host. (C) Indirect effect of gut microbiome on drug response: the gut microbiome can influence drug bioavailability and drug response via its interaction with host immune and metabolic systems. Specific examples illustrate each case
Figure 3
Figure 3
Gut microbiome associated with response of PD-1/PD-L1 based immunotherapy. (A) Checkpoints of immunotherapy. Programmed cell death protein 1 (PD-1) is a cell surface receptor that serves as an immune checkpoint. This receptor plays an important role in suppressing T cell inflammatory activity and down-regulating the immune system. Tumour cells can express PD-1 ligands (PD-L1) that are able to bind to PD-l protein and thus inactivate T cells. Accordingly, several PD-1/PD-L1 blockers have been designed to block the interaction between PD-1 and PD-L1 to enable anti-tumour immunity. (B) Gut microbes associated with individual response of immunotherapy and the proportion of their variation explained by host genetics and environmental factors. Five bacterial taxa are associated to higher response, while bacteroidales is linked to low response. Inter-individual variation is scaled as 1 and the proportion of explained variation by genetic factors and environmental factors are shaded blue and green, respectively. Estimation of explained variation derived from the TwinsUK study: Goodrich et al. (2014) Cell, 159:789–799
Figure 4
Figure 4
Host-microbe-diet interactions in drug metabolism. Complex drug-microbe interactions can result in alterations in microbial composition and function and change the chemical structure of compounds that could directly or indirectly affect drug metabolism in the liver. Moreover, genetics and exogenous factors, including diet, can affect both gut microbiome and drug metabolism in the host
Figure 5
Figure 5
Overview of LifeLines-DEEP cohort. LifeLines-DEEP is a subset of 1,500 individuals from the large, prospective, population-based LifeLines cohort (n = 167,000 individuals). In addition to information about >2,000 exogenous factors (morphological, physiological, clinical), LifeLines-DEEP participants have been deeply profiled for multiple “omics” data layers
Figure 6
Figure 6
Individual-based drug testing. Advance of bacterial “culturomics”, development of organs-on-chip and high-throughput metabolism and pharmacokinetic analyses, will enable individual-based in vitro drug testing in the near future. For this purpose, liver gut microbiome can be collected for culturing. This can be done either on whole community level or on individual species or strain level (blue arrows). Currently, organs-on-chips are emerging as a next-generation drug-testing model system. Non-invasive collection of urine leads to human induced pluripotent stem cells from which we can generate different types of tissue cells (e.g., gut epithelial cells or hepatocytes) (green arrows). These cells will have exactly the same genetic background. Coupling cultured bacteria and organs-on-chip offers a high potential to conduct individual-based drug testing, by taking into consideration both an individual’s own genome and his/her metagenome (red arrows)

References

    1. Alexander JL, Wilson ID, Teare J, Marchesi JR, Nicholson JK, Kinross JM. Gut microbiota modulation of chemotherapy efficacy and toxicity. Nat Rev Gastroenterol Hepatol. 2017;14:356–365. doi: 10.1038/nrgastro.2017.20. - DOI - PubMed
    1. Ananthakrishnan AN, Luo C, Yajnik V, Khalili H, Garber JJ, Stevens BW, Cleland T, Xavier RJ. Gut microbiome function predicts response to anti-integrin biologic therapy in inflammatory bowel diseases. Cell Host Microbe. 2017;21:603.e3–610.e3. doi: 10.1016/j.chom.2017.04.010. - DOI - PMC - PubMed
    1. Atarashi K, Tanoue T, Oshima K, Suda W, Nagano Y, Nishikawa H, Fukuda S, Saito T, Narushima S, Hase K, et al. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature. 2013;500:232–236. doi: 10.1038/nature12331. - DOI - PubMed
    1. Basit AW, Lacey LF. Colonic metabolism of ranitidine: implications for its delivery and absorption. Int J Pharm. 2001;227:157–165. doi: 10.1016/S0378-5173(01)00794-3. - DOI - PubMed
    1. Benson AK, Kelly SA, Legge R, Ma F, Low SJ, Kim J, Zhang M, Oh PL, Nehrenberg D, Hua K, et al. Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc Natl Acad Sci USA. 2010;107:18933–18938. doi: 10.1073/pnas.1007028107. - DOI - PMC - PubMed

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