Predicting drug-metagenome interactions: Variation in the microbial β-glucuronidase level in the human gut metagenomes

Characterizing the gut microbiota in terms of their capacity to interfere with drug metabolism is necessary to achieve drug efficacy and safety. Although examples of drug-microbiome interactions are well-documented, little has been reported about a computational pipeline for systematically identifying and characterizing bacterial enzymes that process particular classes of drugs. The goal of our study is to develop a computational approach that compiles drugs whose metabolism may be influenced by a particular class of microbial enzymes and that quantifies the variability in the collective level of those enzymes among individuals. The present paper describes this approach, with microbial β-glucuronidases as an example, which break down drug-glucuronide conjugates and reactivate the drugs or their metabolites. We identified 100 medications that may be metabolized by β-glucuronidases from the gut microbiome. These medications included morphine, estrogen, ibuprofen, midazolam, and their structural analogues. The analysis of metagenomic data available through the Sequence Read Archive (SRA) showed that the level of β-glucuronidase in the gut metagenomes was higher in males than in females, which provides a potential explanation for the sex-based differences in efficacy and toxicity for several drugs, reported in previous studies. Our analysis also showed that infant gut metagenomes at birth and 12 months of age have higher levels of β-glucuronidase than the metagenomes of their mothers and the implication of this observed variability was discussed in the context of breastfeeding as well as infant hyperbilirubinemia. Overall, despite important limitations discussed in this paper, our analysis provided useful insights on the role of the human gut metagenome in the variability in drug response among individuals. Importantly, this approach exploits drug and metagenome data available in public databases as well as open-source cheminformatics and bioinformatics tools to predict drug-metagenome interactions.

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Editorial (Thematic Issue: Topic on The Role of Drug Transport and Pharmacokinetics in Drug Efficacy and Safety Part 1)

Current Drug Metabolism ◽

10.2174/138920021609151201121900 ◽

2015 ◽

Vol 16 (9) ◽

pp. 730-731

Author(s):

Changxiao Liu ◽

Xin He

Keyword(s):

Drug Transport ◽

Drug Efficacy ◽

Thematic Issue ◽

Efficacy And Safety

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Editorial (Thematic Issue: Role of Drug Metabolism and its Mediated DDI in Drug Efficacy and Safety Part 2)

Current Drug Metabolism ◽

10.2174/138920021610151210163929 ◽

2015 ◽

Vol 16 (10) ◽

pp. 848-849

Author(s):

Changxiao Liu ◽

Xin He

Keyword(s):

Drug Metabolism ◽

Drug Efficacy ◽

Thematic Issue ◽

Efficacy And Safety

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Human gut microbiome: hopes, threats and promises

Gut ◽

10.1136/gutjnl-2018-316723 ◽

2018 ◽

Vol 67 (9) ◽

pp. 1716-1725 ◽

Cited By ~ 332

Author(s):

Patrice D Cani

Keyword(s):

Gut Microbiota ◽

Dietary Habits ◽

Current Knowledge ◽

Metagenomic Data ◽

Human Gut ◽

Drug Treatments ◽

Key Issues ◽

Number Of Publications ◽

The Impact

The microbiome has received increasing attention over the last 15 years. Although gut microbes have been explored for several decades, investigations of the role of microorganisms that reside in the human gut has attracted much attention beyond classical infectious diseases. For example, numerous studies have reported changes in the gut microbiota during not only obesity, diabetes, and liver diseases but also cancer and even neurodegenerative diseases. The human gut microbiota is viewed as a potential source of novel therapeutics. Between 2013 and 2017, the number of publications focusing on the gut microbiota was, remarkably, 12 900, which represents four-fifths of the total number of publications over the last 40 years that investigated this topic. This review discusses recent evidence of the impact of the gut microbiota on metabolic disorders and focus on selected key mechanisms. This review also aims to provide a critical analysis of the current knowledge in this field, identify putative key issues or problems and discuss misinterpretations. The abundance of metagenomic data generated on comparing diseased and healthy subjects can lead to the erroneous claim that a bacterium is causally linked with the protection or the onset of a disease. In fact, environmental factors such as dietary habits, drug treatments, intestinal motility and stool frequency and consistency are all factors that influence the composition of the microbiota and should be considered. The cases of the bacteria Prevotella copri and Akkermansia muciniphila will be discussed as key examples.

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Identifying Core Operons in Metagenomic Data

10.1101/2019.12.20.885269 ◽

2019 ◽

Author(s):

Xiao Hu ◽

Iddo Friedberg

Keyword(s):

Functional Unit ◽

High Accuracy ◽

Metagenomic Data ◽

Human Gut ◽

Microbial Genetics ◽

Polycistronic Mrna ◽

Functional Complexity ◽

Powerful Mechanism ◽

Gut Metagenome ◽

Metagenome Sample

AbstractAn operon is a functional unit of DNA whose genes are co-transcribed on polycistronic mRNA, in a co-regulated fashion. Operons are a powerful mechanism of introducing functional complexity in bacteria, and are therefore of interest in microbial genetics, physiology, biochemistry, and evolution. Here we present a Pipeline for Operon Exploration in Metagenomes or POEM. At the heart of POEM lies the concept of a core operon, a functional unit enabled by a predicted operon in a metagenome. Using a series of benchmarks, we show the high accuracy of POEM, and demonstrate its use on a human gut metagenome sample. We conclude that POEM is a useful tool for analyzing metagenomes beyond the genomic level, and for identifying multi-gene functionalities and possible neofunctionalization in metagenomes. Availability: https://github.com/Rinoahu/POEM_py3k

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Prediction and analysis of metagenomic operons via MetaRon: a pipeline for prediction of Metagenome and whole-genome opeRons

BMC Genomics ◽

10.1186/s12864-020-07357-5 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Syed Shujaat Ali Zaidi ◽

Masood Ur Rehman Kayani ◽

Xuegong Zhang ◽

Younan Ouyang ◽

Imran Haider Shamsi

Keyword(s):

Type 2 Diabetes ◽

Secondary Metabolites ◽

Metagenomic Data ◽

Whole Genome ◽

Functional Information ◽

Human Gut ◽

E Coli ◽

Operon Prediction ◽

Gut Metagenome

Abstract Background Efficient regulation of bacterial genes in response to the environmental stimulus results in unique gene clusters known as operons. Lack of complete operonic reference and functional information makes the prediction of metagenomic operons a challenging task; thus, opening new perspectives on the interpretation of the host-microbe interactions. Results In this work, we identified whole-genome and metagenomic operons via MetaRon (Metagenome and whole-genome opeRon prediction pipeline). MetaRon identifies operons without any experimental or functional information. MetaRon was implemented on datasets with different levels of complexity and information. Starting from its application on whole-genome to simulated mixture of three whole-genomes (E. coli MG1655, Mycobacterium tuberculosis H37Rv and Bacillus subtilis str. 16), E. coli c20 draft genome extracted from chicken gut and finally on 145 whole-metagenome data samples from human gut. MetaRon consistently achieved high operon prediction sensitivity, specificity and accuracy across E. coli whole-genome (97.8, 94.1 and 92.4%), simulated genome (93.7, 75.5 and 88.1%) and E. coli c20 (87, 91 and 88%,), respectively. Finally, we identified 1,232,407 unique operons from 145 paired-end human gut metagenome samples. We also report strong association of type 2 diabetes with Maltose phosphorylase (K00691), 3-deoxy-D-glycero-D-galacto-nononate 9-phosphate synthase (K21279) and an uncharacterized protein (K07101). Conclusion With MetaRon, we were able to remove two notable limitations of existing whole-genome operon prediction methods: (1) generalizability (ability to predict operons in unrelated bacterial genomes), and (2) whole-genome and metagenomic data management. We also demonstrate the use of operons as a subset to represent the trends of secondary metabolites in whole-metagenome data and the role of secondary metabolites in the occurrence of disease condition. Using operonic data from metagenome to study secondary metabolic trends will significantly reduce the data volume to more precise data. Furthermore, the identification of metabolic pathways associated with the occurrence of type 2 diabetes (T2D) also presents another dimension of analyzing the human gut metagenome. Presumably, this study is the first organized effort to predict metagenomic operons and perform a detailed analysis in association with a disease, in this case type 2 diabetes. The application of MetaRon to metagenomic data at diverse scale will be beneficial to understand the gene regulation and therapeutic metagenomics.

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Gut Mycobiota and Fungal Metabolites in Human Homeostasis

Current Drug Targets ◽

10.2174/1389450119666180724125020 ◽

2018 ◽

Vol 20 (2) ◽

pp. 232-240 ◽

Cited By ~ 3

Author(s):

Izabella Mogilnicka ◽

Marcin Ufnal

Keyword(s):

Wide Spectrum ◽

Biological Effects ◽

Fungal Species ◽

Fungal Metabolites ◽

Human Gut ◽

Fecal Transplantation ◽

Bacterial Microbiota ◽

Bowel Diseases ◽

Inflammatory Bowel

Background:Accumulating evidence suggests that microbiota play an important role in host’s homeostasis. Thus far, researchers have mostly focused on the role of bacterial microbiota. However, human gut is a habitat for several fungal species, which produce numerous metabolites. Furthermore, various types of food and beverages are rich in a wide spectrum of fungi and their metabolites.Methods:We searched PUBMED and Google Scholar databases to identify clinical and pre-clinical studies on fungal metabolites, composition of human mycobiota and fungal dysbiosis.Results:Fungal metabolites may serve as signaling molecules and exert significant biological effects including trophic, anti-inflammatory or antibacterial actions. Finally, research suggests an association between shifts in gut fungi composition and human health. Changes in mycobiota composition have been found in obesity, hepatitis and inflammatory bowel diseases.Conclusion:The influence of mycobiota and dietary fungi on homeostasis in mammals suggests a pharmacotherapeutic potential of modulating the mycobiota which may include treatment with probiotics and fecal transplantation. Furthermore, antibacterial action of fungi-derived molecules may be considered as a substitution for currently used antibacterial agents and preservatives in food industry.

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Influence of pig farming on human Gut Microbiota: role of airborne microbial communities

Gut Microbes ◽

10.1080/19490976.2021.1927634 ◽

2021 ◽

Vol 13 (1) ◽

pp. 1-13

Author(s):

Julia Moor ◽

Tsering Wüthrich ◽

Suzanne Aebi ◽

Nadezda Mostacci ◽

Gudrun Overesch ◽

...

Keyword(s):

Gut Microbiota ◽

Microbial Communities ◽

Human Gut ◽

Human Gut Microbiota ◽

Pig Farming

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Sex differences in the phylum‐level human gut microbiota composition

BMC Microbiology ◽

10.1186/s12866-021-02198-y ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Alexander Koliada ◽

Vladislav Moseiko ◽

Mariana Romanenko ◽

Oleh Lushchak ◽

Nadiia Kryzhanovska ◽

...

Keyword(s):

Sex Differences ◽

Gut Microbiota ◽

Age Groups ◽

Microbiota Composition ◽

Human Gut ◽

Cross Sectional ◽

Total N ◽

Human Gut Microbiota ◽

Gut Microbiota Composition

Abstract Background Evidence was previously provided for sex-related differences in the human gut microbiota composition, and sex-specific discrepancy in hormonal profiles was proposed as a main determinant of these differences. On the basis of these findings, the assumption was made on the role of microbiota in the sexual dimorphism of human diseases. To date, sex differences in fecal microbiota were demonstrated primarily at lower taxonomic levels, whereas phylum-level differences between sexes were reported in few studies only. In the present population-based cross-sectional research, sex differences in the phylum-level human gut microbiota composition were identified in a large (total n = 2301) sample of relatively healthy individuals from Ukraine. Results Relative abundances of Firmicutes and Actinobacteria, as determined by qRT-PCR, were found to be significantly increased, while that of Bacteroidetes was significantly decreased in females compared to males. The Firmicutes to Bacteroidetes (F/B) ratio was significantly increased in females compared to males. Females had 31 % higher odds of having F/B ratio more than 1 than males. This trend was evident in all age groups. The difference between sexes was even more pronounced in the elder individuals (50+): in this age group, female participants had 56 % higher odds of having F/B ratio > 1 than the male ones. Conclusions In conclusion, sex-specific differences in the phylum-level intestinal microbiota composition were observed in the Ukraine population. The F/B ratio was significantly increased in females compared to males. Further investigation is needed to draw strong conclusions regarding the mechanistic basis for sex-specific differences in the gut microbiota composition and regarding the role of these differences in the initiation and progression of human chronic diseases.

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