Personalized Mapping of Drug Metabolism by the Human Gut Microbiome.
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ABSTRACT:
SUBMITTER: Javdan B
PROVIDER: S-EPMC8591631 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Individuals vary widely in their responses to medicinal drugs, which can be dangerous and expensive owing to treatment delays and adverse effects. Although increasing evidence implicates the gut microbiome in this variability, the molecular mechanisms involved remain largely unknown. Here we show, by measuring the ability of 76 human gut bacteria from diverse clades to metabolize 271 orally administered drugs, that many drugs are chemically modified by microorganisms. We combined high-throughput genetic analyses with mass spectrometry to systematically identify microbial gene products that metabolize drugs. These microbiome-encoded enzymes can directly and substantially affect intestinal and systemic drug metabolism in mice, and can explain the drug-metabolizing activities of human gut bacteria and communities on the basis of their genomic contents. These causal links between the gene content and metabolic activities of the microbiota connect interpersonal variability in microbiomes to interpersonal differences in drug metabolism, which has implications for medical therapy and drug development across multiple disease indications.
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Project description:Bacteria in the human gut have the ability to activate, inactivate, and reactivate drugs with both intended and unintended effects. For example, the drug digoxin is reduced to the inactive metabolite dihydrodigoxin by the gut Actinobacterium E. lenta, and patients colonized with high levels of drug metabolizing strains may have limited response to the drug. Understanding the complete space of drugs that are metabolized by the human gut microbiome is critical for predicting bacteria-drug relationships and their effects on individual patient response. Discovery and validation of drug metabolism via bacterial enzymes has yielded >50 drugs after nearly a century of experimental research. However, there are limited computational tools for screening drugs for potential metabolism by the gut microbiome. We developed a pipeline for comparing and characterizing chemical transformations using continuous vector representations of molecular structure learned using unsupervised representation learning. We applied this pipeline to chemical reaction data from MetaCyc to characterize the utility of vector representations for chemical reaction transformations. After clustering molecular and reaction vectors, we performed enrichment analyses and queries to characterize the space. We detected enriched enzyme names, Gene Ontology terms, and Enzyme Consortium (EC) classes within reaction clusters. In addition, we queried reactions against drug-metabolite transformations known to be metabolized by the human gut microbiome. The top results for these known drug transformations contained similar substructure modifications to the original drug pair. This work enables high throughput screening of drugs and their resulting metabolites against chemical reactions common to gut bacteria.
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Project description:<p>Individuals vary widely in their drug responses, which can be dangerous and expensive due to treatment delays and adverse effects. Growing evidence implicates the gut microbiome in this variability, however the molecular mechanisms remain largely unknown. We measured the ability of 76 diverse human gut bacteria to metabolize 271 oral drugs and found that many of these drugs are chemically modified by microbes. We combined high-throughput genetics with mass spectrometry to systematically identify drug-metabolizing microbial gene products. These microbiome-encoded enzymes can directly and significantly impact intestinal and systemic drug metabolism in mice, and can explain drug-metabolizing activities of human gut bacteria and communities based on their genomic contents. These causal links between microbiota gene content and metabolic activities connect interpersonal microbiome variability to interpersonal differences in drug metabolism, which has implications for medical therapy and drug development across multiple disease indications.</p><p><br></p><p>Additional data related to this study can also be found by the following links;</p><p>- Raw sequencing data; <a href='https://www.ebi.ac.uk/ena/data/view/PRJEB31790' rel='noopener noreferrer' target='_blank'>ENA (accession no. PRJEB31790)</a></p><p>- Data for Figures; <a href='https://doi.org/10.6084/m9.figshare.8119058' rel='noopener noreferrer' target='_blank'>FigShare</a> </p><p>- Analysis pipeline schemes, scripts and input files for analzing data and generating figures; <a href='https://github.com/mszimmermann/drug-bacteria-gene_mapping' rel='noopener noreferrer' target='_blank'>GitHub</a> and archived <a href='https://doi.org/10.5281/zenodo.2827640' rel='noopener noreferrer' target='_blank'>Zenodo</a></p>
2019-07-10 | MTBLS896 | MetaboLights
Project description:The trillions of microorganisms in the human gastrointestinal tract are an underexplored aspect of pharmacology. Despite numerous examples of microbial effects on drug efficacy and toxicity, there is often an incomplete understanding of the underlying mechanisms. Here, we dissect the inactivation of the commonly prescribed cardiac glycoside, digoxin, by Eggerthella lenta. Whole genome transcriptional profiling, comparative genomics, and culture-based assays revealed a cytochrome-encoding operon up-regulated by digoxin, absent in non-metabolizing E. lenta strains, and predictive of the efficiency of digoxin inactivation by the human gut microbiome. Digoxin inactivation was further enhanced by microbial interactions and inhibited by arginine. Pharmacokinetic studies using gnotobiotic mice revealed that increasing dietary protein reduces the in vivo metabolism of digoxin by E. lenta, with significant changes to drug concentration in the urine and serum. These results emphasize the importance of viewing pharmacology from the perspective of both our human and microbial genomes. RNA-Seq analysis of Eggerthella lenta cultured with or without digoxin.
2013-06-15 | E-GEOD-43919 | biostudies-arrayexpress
Project description:The human gut is inhabited by a complex and metabolically active microbial ecosystem. While many studies focused on the effect of individual microbial taxa on human health, their overall metabolic potential has been under-explored. Using whole-metagenome shotgun sequencing data in 1,004 twins, we first observed that unrelated subjects share, on average, almost double the number of metabolic pathways (82%) than species (43%). Then, using 673 blood and 713 faecal metabolites, we found metabolic pathways to be associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species showed less than 3,000 associations. Finally, we estimated that the microbiome was involved in a dialogue between 71% of faecal, and 15% of blood, metabolites. This study underlines the importance of studying the microbial metabolic potential rather than focusing purely on taxonomy to find therapeutic and diagnostic targets, and provides a unique resource describing the interplay between the microbiome and the systemic and faecal metabolic environments.
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Project description:The trillions of microorganisms in the human gastrointestinal tract are an underexplored aspect of pharmacology. Despite numerous examples of microbial effects on drug efficacy and toxicity, there is often an incomplete understanding of the underlying mechanisms. Here, we dissect the inactivation of the commonly prescribed cardiac glycoside, digoxin, by Eggerthella lenta. Whole genome transcriptional profiling, comparative genomics, and culture-based assays revealed a cytochrome-encoding operon up-regulated by digoxin, absent in non-metabolizing E. lenta strains, and predictive of the efficiency of digoxin inactivation by the human gut microbiome. Digoxin inactivation was further enhanced by microbial interactions and inhibited by arginine. Pharmacokinetic studies using gnotobiotic mice revealed that increasing dietary protein reduces the in vivo metabolism of digoxin by E. lenta, with significant changes to drug concentration in the urine and serum. These results emphasize the importance of viewing pharmacology from the perspective of both our human and microbial genomes.
2013-06-15 | GSE43919 | GEO
Project description:It is well appreciated that microbial metabolism of drugs can influence treatment efficacy. Microbial β-glucuronidases in the gut can reactivate the excreted, inactive metabolite of irinotecan, a first-line chemotherapeutic for metastatic colorectal cancer. Reactivation causes adverse drug responses, including severe diarrhea. However, a direct connection between irinotecan metabolism and the composition of an individual's gut microbiota has not previously been made. Here, we report quantitative evidence of inter-individual variability in microbiome metabolism of the inactive metabolite of irinotecan to its active form. We identify a high turnover microbiota metabotype with potentially elevated risk for irinotecan-dependent adverse drug responses. We link the high turnover metabotype to unreported microbial β-glucuronidases; inhibiting these enzymes may decrease irinotecan-dependent adverse drug responses in targeted subsets of patients. In total, this study reveals metagenomic mining of the microbiome, combined with metabolomics, as a non-invasive approach to develop biomarkers for colorectal cancer treatment outcomes.
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