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Kyaw TS, Zhang C, Sandy M, Trepka K, Zhang S, Ramirez Hernandez LA, Ramirez L, Goh JJ, Yu K, Dimassa V, Bess EN, Brockert JG, Dumlao DS, Bisanz JE, Turnbaugh PJ. Human gut Actinobacteria boost drug absorption by secreting P-glycoprotein ATPase inhibitors. iScience 2024; 27:110122. [PMID: 38947502 PMCID: PMC11214321 DOI: 10.1016/j.isci.2024.110122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 04/17/2024] [Accepted: 05/24/2024] [Indexed: 07/02/2024] Open
Abstract
Drug efflux transporters are a major determinant of drug efficacy and toxicity. A canonical example is P-glycoprotein (P-gp), an efflux transporter that controls the intestinal absorption of diverse compounds. Despite a rich literature on the dietary and pharmaceutical compounds that impact P-gp activity, its sensitivity to gut microbial metabolites remains an open question. Surprisingly, we found that the cardiac drug-metabolizing gut Actinobacterium Eggerthella lenta increases drug absorption in mice. Experiments in cell culture revealed that E. lenta produces a soluble factor that post-translationally inhibits P-gp ATPase efflux activity. P-gp inhibition is conserved in the Eggerthellaceae family but absent in other Actinobacteria. Comparative genomics identified genes associated with P-gp inhibition. Finally, activity-guided biochemical fractionation coupled to metabolomics implicated a group of small polar metabolites with P-gp inhibitory activity. These results highlight the importance of considering the broader relevance of the gut microbiome for drug disposition beyond first-pass metabolism.
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Affiliation(s)
- Than S. Kyaw
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Chen Zhang
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Moriah Sandy
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
- Quantitative Metabolite Analysis Center, Benioff Center for Microbiome Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Kai Trepka
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Shenwei Zhang
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Luis A. Ramirez Hernandez
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Lorenzo Ramirez
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Janice J.N. Goh
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Kristie Yu
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Vincent Dimassa
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Elizabeth N. Bess
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jacob G. Brockert
- Quantitative Metabolite Analysis Center, Benioff Center for Microbiome Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Darren S. Dumlao
- Quantitative Metabolite Analysis Center, Benioff Center for Microbiome Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jordan E. Bisanz
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Peter J. Turnbaugh
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
- Chan-Zuckerberg Biohub-San Francisco, San Francisco, CA 94158, USA
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Kyaw TS, Patel HV, Jones C, Ha CWY, Khan AR, Hampson LA, Breyer BN, Shaw NM. Urinary and Oral Microbiota Among Men Undergoing Buccal Urethroplasty. Urology 2024:S0090-4295(24)00455-2. [PMID: 38878829 DOI: 10.1016/j.urology.2024.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 05/27/2024] [Accepted: 06/04/2024] [Indexed: 07/02/2024]
Abstract
OBJECTIVE To assess changes in the urinary microbiota after buccal urethroplasty. METHODS At the University of California San Francisco, we enrolled 9 adult males with urethral strictures undergoing buccal urethroplasty where we collected urine and oral swabs intraoperatively and 3 months postoperatively. 16S rRNA sequencing was used to profile the microbiota. RESULTS At baseline, the mouth contains twice the number of unique bacteria (alpha diversity) and the microbial community is significantly distinct compared to the urinary tract. Despite having a buccal mucosa in the urinary tract after urethroplasty, the number of unique bacteria in the urine remained stable. However, the bacterial community composition and structure significantly changed in the urinary tract with the enrichment of Corynebacterium genus at 3 months post-urethroplasty procedure. CONCLUSION In this pilot study, we showed that the alpha diversity in the urinary microbiota did not significantly change despite having a buccal tissue with the capacity to support high bacterial diversity in the urinary tract. To our surprise, the post-urethroplasty urinary microbiota was not a hybrid of baseline oral and urine microbiotas; the changes detected, such as an enrichment of the Corynebacterium genus, were more nuanced yet could profoundly impact surgical outcomes like graft changes and stricture recurrence. Our study not only established the feasibility but also outlined a blueprint for conducting a large-scale study to assess alterations in the urinary microbiome in relation to surgical outcomes.
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Affiliation(s)
- Than S Kyaw
- Medical Scientist Training Program, University of California San Francisco, CA
| | - Hiren V Patel
- Department of Urology, University of California, San Francisco, CA
| | - Charles Jones
- Department of Urology, University of California, San Francisco, CA; Department of Urology, Washington University, Saint Louis, MO
| | - Connie W Y Ha
- Benioff Center for Microbiome Medicine, Division of Gastroenterology, Department of Medicine, University of California, San Francisco, CA
| | - Abdur Rahim Khan
- Benioff Center for Microbiome Medicine, Division of Gastroenterology, Department of Medicine, University of California, San Francisco, CA
| | - Lindsay A Hampson
- Department of Urology, University of California, San Francisco, CA; San Francisco Veterans Affairs Medical Center, San Francisco, CA
| | - Benjamin N Breyer
- Department of Urology, University of California, San Francisco, CA; Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Nathan M Shaw
- Department of Urology, University of California, San Francisco, CA; Department of Urology, MedStar Georgetown University Hospital, Washington DC; Department of Plastic and Reconstructive Surgery, MedStar Georgetown University Hospital, Washington DC.
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Tannock GW. Understanding the gut microbiota by considering human evolution: a story of fire, cereals, cooking, molecular ingenuity, and functional cooperation. Microbiol Mol Biol Rev 2024; 88:e0012722. [PMID: 38126754 PMCID: PMC10966955 DOI: 10.1128/mmbr.00127-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023] Open
Abstract
SUMMARYThe microbial community inhabiting the human colon, referred to as the gut microbiota, is mostly composed of bacterial species that, through extensive metabolic networking, degrade and ferment components of food and human secretions. The taxonomic composition of the microbiota has been extensively investigated in metagenomic studies that have also revealed details of molecular processes by which common components of the human diet are metabolized by specific members of the microbiota. Most studies of the gut microbiota aim to detect deviations in microbiota composition in patients relative to controls in the hope of showing that some diseases and conditions are due to or exacerbated by alterations to the gut microbiota. The aim of this review is to consider the gut microbiota in relation to the evolution of Homo sapiens which was heavily influenced by the consumption of a nutrient-dense non-arboreal diet, limited gut storage capacity, and acquisition of skills relating to mastering fire, cooking, and cultivation of cereal crops. The review delves into the past to gain an appreciation of what is important in the present. A holistic view of "healthy" microbiota function is proposed based on the evolutionary pathway shared by humans and gut microbes.
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Affiliation(s)
- Gerald W. Tannock
- Department of Microbiology and Immunology, University of Otago, Dunedin, New Zealand
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Verdegaal AA, Goodman AL. Integrating the gut microbiome and pharmacology. Sci Transl Med 2024; 16:eadg8357. [PMID: 38295186 DOI: 10.1126/scitranslmed.adg8357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 01/11/2024] [Indexed: 02/02/2024]
Abstract
The gut microbiome harbors trillions of organisms that contribute to human health and disease. These bacteria can also affect the properties of medical drugs used to treat these diseases, and drugs, in turn, can reshape the microbiome. Research addressing interdependent microbiome-host-drug interactions thus has broad impact. In this Review, we discuss these interactions from the perspective of drug bioavailability, absorption, metabolism, excretion, toxicity, and drug-mediated microbiome modulation. We survey approaches that aim to uncover the mechanisms underlying these effects and opportunities to translate this knowledge into new strategies to improve the development, administration, and monitoring of medical drugs.
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Affiliation(s)
- Andrew A Verdegaal
- Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, CT 06536, USA
| | - Andrew L Goodman
- Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, CT 06536, USA
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Yin J, Chen Z, You N, Li F, Zhang H, Xue J, Ma H, Zhao Q, Yu L, Zeng S, Zhu F. VARIDT 3.0: the phenotypic and regulatory variability of drug transporter. Nucleic Acids Res 2024; 52:D1490-D1502. [PMID: 37819041 PMCID: PMC10767864 DOI: 10.1093/nar/gkad818] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/01/2023] [Accepted: 09/27/2023] [Indexed: 10/13/2023] Open
Abstract
The phenotypic and regulatory variability of drug transporter (DT) are vital for the understanding of drug responses, drug-drug interactions, multidrug resistances, and so on. The ADME property of a drug is collectively determined by multiple types of variability, such as: microbiota influence (MBI), transcriptional regulation (TSR), epigenetics regulation (EGR), exogenous modulation (EGM) and post-translational modification (PTM). However, no database has yet been available to comprehensively describe these valuable variabilities of DTs. In this study, a major update of VARIDT was therefore conducted, which gave 2072 MBIs, 10 610 TSRs, 46 748 EGRs, 12 209 EGMs and 10 255 PTMs. These variability data were closely related to the transportation of 585 approved and 301 clinical trial drugs for treating 572 diseases. Moreover, the majority of the DTs in this database were found with multiple variabilities, which allowed a collective consideration in determining the ADME properties of a drug. All in all, VARIDT 3.0 is expected to be a popular data repository that could become an essential complement to existing pharmaceutical databases, and is freely accessible without any login requirement at: https://idrblab.org/varidt/.
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Affiliation(s)
- Jiayi Yin
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Zhen Chen
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
| | - Nanxin You
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
| | - Fengcheng Li
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
- The Children's Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310052, China
| | - Hanyu Zhang
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
| | - Jia Xue
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
| | - Hui Ma
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
| | - Qingwei Zhao
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
| | - Lushan Yu
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
| | - Su Zeng
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
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Role of the Intestinal Microbiota in the Genesis of Major Depression and the Response to Antidepressant Drug Therapy: A Narrative Review. Biomedicines 2023; 11:biomedicines11020550. [PMID: 36831086 PMCID: PMC9953611 DOI: 10.3390/biomedicines11020550] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/16/2023] Open
Abstract
A major depressive disorder is a serious mental illness characterized by a pervasive low mood that negatively concerns personal life, work life, or education, affecting millions of people worldwide. To date, due to the complexity of the disease, the most common and effective treatments consist of a multi-therapy approach, including psychological, social, and pharmacological support with antidepressant drugs. In general, antidepressants are effective in correcting chemical imbalances of neurotransmitters in the brain, but recent evidence has underlined the pivotal role of gut microbiota (GM) also in the regulation of their pharmacokinetics/pharmacodynamics, through indirect or direct mechanisms. The study of these complex interactions between GM and drugs is currently under the spotlight, and it has been recently named "pharmacomicrobiomics". Hence, the purpose of this review is to summarize the contribution of GM and its metabolites in depression, as well as their role in the metabolism and activity of antidepressant drugs, in order to pave the way for the personalized administration of antidepressant therapies.
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