scholarly journals Toward a unified diversity–area relationship (DAR) of species and gene diversity illustrated with the human gut metagenome

Ecosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
Author(s):  
Zhanshan (Sam) Ma ◽  
Aaron M. Ellison
Keyword(s):  
Gene Diversity ◽  
Human Gut ◽  
Gut Metagenome

scholarly journals An assessment of Oxford Nanopore sequencing for human gut metagenome profiling: A pilot study of head and neck cancer patients

2019 ◽  
Vol 166 ◽  
pp. 105739 ◽  
Author(s):  
Thidathip Wongsurawat ◽  
Mayumi Nakagawa ◽  
Omar Atiq ◽  
Hannah N. Coleman ◽  
Piroon Jenjaroenpun ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Pilot Study ◽  
Head And Neck ◽  
Cancer Patients ◽  
Neck Cancer ◽  
Nanopore Sequencing ◽  
Human Gut ◽  
Oxford Nanopore ◽  
Gut Metagenome

scholarly journals Flavonoid-modifying capabilities of the gut microbiome – an in silico study

2021 ◽  
Author(s):  
Tobias Goris ◽  
Rafael Cuadrat ◽  
Annett Braune
Keyword(s):  
Large Scale ◽  
Health Impact ◽  
Gut Bacteria ◽  
Human Gut ◽  
Positive Health ◽  
Nutritional Recommendations ◽  
In Silico Study ◽  
Gut Metagenome ◽  
Insight Into ◽  
Large Scale Screening

Abstract Flavonoids are a major group of dietary plant polyphenols and have a positive health impact, but their modification and degradation in the human gut is still widely unknown. Due to the rise of human gut metagenome data and the assembly of hundreds of thousands of bacterial metagenome-assembled genomes (MAGs), large-scale screening for potential flavonoid-modifying enzymes is now feasible. With sequences from characterized flavonoid-transforming enzymes as queries, the Unified Human Gastrointestinal Protein catalog was analyzed and quantification of putative flavonoid-modifying enzymes was carried out. The results revealed that flavonoid-modifying enzymes are often highly abundant in bacteria hitherto not considered as flavonoid-modifying gut bacteria. The enzymes for the physiologically important daidzein to equol conversion, well studied in Slackia isoflavoniconvertens, were encoded only to a low extent in Slackia MAGs, but more abundant in Adlercreutzia equolifaciens and an uncharacterizedEggerthellaceae species. In addition, a high abundance of genes with a similarity of only about 35% in uncultivated Collinsella species suggest a hitherto uncharacterized Daidzein-to-equol potential in these bacteria. Of all potential flavonoid modification steps, O-deglycosylation (including derhamnosylation) was by far the most abundant in this analysis. In contrast, enzymes putatively involved in C-deglycosylation were detected less often in human gut bacteria and mainly found in Agathobacter faecis (formerly Roseburia faecis). Phloretin hydrolase, flavanonol/flavanone-cleaving reductase and flavone reductase (all three most abundant in Flavonifractor plautii) and O-demethylase (Intestinibacter bartlettii) homologs were of intermediate prevalence (several hundreds of MAGs). This first comprehensive insight into the black box of flavonoid modification in the human gut highlights many hitherto overlooked and uncultured bacterial genera and species as key organisms in flavonoid modification by the human gut microbiota. This could lead to a significant contribution to future biochemical-microbiological investigations on gut bacterial flavonoid transformation. In addition, our results are important for individual nutritional recommendations and for biotechnological applications which rely on novel enzymes catalyzing potentially useful flavonoid modification reactions.

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

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244876
Author(s):  
Moamen M. Elmassry ◽  
Sunghwan Kim ◽  
Ben Busby
Keyword(s):  
Drug Response ◽  
Drug Efficacy ◽  
Metagenomic Data ◽  
Efficacy And Safety ◽  
Human Gut ◽  
Microbial Enzymes ◽  
Sequence Read Archive ◽  
Structural Analogues ◽  
Gut Metagenome

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.

scholarly journals Antibiotic Resistance Gene Diversity and Virulence Gene Diversity Are Correlated in Human Gut and Environmental Microbiomes

mSphere ◽  
2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Pedro Escudeiro ◽  
Joël Pothier ◽  
Francisco Dionisio ◽  
Teresa Nogueira
Keyword(s):  
Antibiotic Resistance ◽  
Comparative Study ◽  
Microbial Communities ◽  
Pathogenic Bacteria ◽  
Gene Diversity ◽  
Bacterial Species ◽  
Human Populations ◽  
Virulence Determinants ◽  
Human Gut ◽  
The World

ABSTRACT Human beings have used large amounts of antibiotics, not only in medical contexts but also, for example, as growth factors in agriculture and livestock, resulting in the contamination of the environment. Even when pathogenic bacteria are the targets of antibiotics, hundreds of nonpathogenic bacterial species are affected as well. Therefore, both pathogenic and nonpathogenic bacteria have gradually become resistant to antibiotics. We tested whether there is still cooccurrence of resistance and virulence determinants. We performed a comparative study of environmental and human gut metagenomes from different individuals and from distinct human populations across the world. We found a great diversity of antibiotic resistance determinants (AR diversity [ARd]) and virulence factors (VF diversity [VFd]) in metagenomes. Importantly there is a correlation between ARd and VFd, even after correcting for protein family richness. In the human gut, there are less ARd and VFd than in more diversified environments, and yet correlations between the ARd and VFd are stronger. They can vary from very high in Malawi, where antibiotic consumption is unattended, to nonexistent in the uncontacted Amerindian population. We conclude that there is cooccurrence of resistance and virulence determinants in human gut microbiomes, suggesting a possible coselective mechanism. IMPORTANCE Every year, thousands of tons of antibiotics are used, not only in human and animal health but also as growth promoters in livestock. Consequently, during the last 75 years, antibiotic-resistant bacterial strains have been selected in human and environmental microbial communities. This implies that, even when pathogenic bacteria are the targets of antibiotics, hundreds of nonpathogenic bacterial species are also affected. Here, we performed a comparative study of environmental and human gut microbial communities issuing from different individuals and from distinct human populations across the world. We found that antibiotic resistance and pathogenicity are correlated and speculate that, by selecting for resistant bacteria, we may be selecting for more virulent strains as a side effect of antimicrobial therapy.

scholarly journals Towards a unifying diversity-area relationship (DAR) of species- and gene-diversity

2020 ◽  
Author(s):  
Zhanshan (Sam) Ma ◽  
Aaron M. Ellison
Keyword(s):  
Gene Diversity ◽  
Temporal Distribution ◽  
Operational Taxonomic Unit ◽  
Population Diversity ◽  
Human Gut ◽  
Individual Level ◽  
Successful Case ◽  
Species Area ◽  
Diversity Profile ◽  
Hill Numbers

AbstractAimThe microbiome as a biogeographic entity can be investigated, to the minimum, from two perspectives: one is the spatial/temporal distribution of species (or any level of the operational taxonomic unit or OTU) diversity, and another is the spatial/temporal distribution of metagenomic gene diversity. Both are necessary for comprehensive understanding of the taxonomical, ecological, evolutionary and functional aspects of the microbiome biogeography. Here we propose to investigate the metagenomic diversity-area relationship (m-DAR), which is a transformation of the species-DAR (s-DAR) that extended the classic SAR (species-area relationship) by replacing the species richness with general species diversity measured in Hill numbers.InnovationThe m-DAR and s-DAR, using the same mathematical models, offer a unifying tool for investigating the biogeography of microbiome from ecological, metagenomic and functional perspectives. Specifically, we investigate m-DAR of the human gut metagenome in terms of the MG (metagenomic gene) and MFGC (metagenome functional gene cluster) respectively, by sketching out the DAR-profile, PDO (pair-wise diversity overlap) profile, MAD (maximal accrual diversity) profile, and RIP (ratio of individual- to population-diversity) profile at each scale. These profiles constitute our unifying DAR toolset and can be applied to any microbiomes beyond the human gut microbiome.Main conclusionsWe demonstrate the construction and applications of the m-DAR and its associated four profiles with six large datasets of the human gut metagenomes including three microbiome-associated diseases (obesity, diabetes, IBD) and their healthy controls, supported with randomization tests to determine the differences between healthy and diseased treatments in their m-DAT parameters. Theoretically, our study presents a successful case to demonstrate the feasibility of unifying systematic biogeography vs. evolutionary biogeography, of an inclusive biogeography of plants, animal and microbes. Practically, our approach offers an important tool for investigating the spatial scaling of human metagenome diversity in a population (cohort) and its relationship with individual-level diversity.

scholarly journals DNA microarray analysis reveals that antibiotic resistance-gene diversity in human gut microbiota is age related

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Na Lu ◽  
Yongfei Hu ◽  
Liying Zhu ◽  
Xi Yang ◽  
Yeshi Yin ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Gut Microbiota ◽  
Resistance Gene ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Gene Diversity ◽  
Antibiotic Resistance Gene ◽  
Human Gut ◽  
Dna Microarray Analysis ◽  
Age Related

scholarly journals Comprehensive mouse gut metagenome catalog reveals major difference to the human counterpart

2021 ◽  
Author(s):  
Silas Kieser ◽  
Evgeny M. Zdobnov ◽  
Mirko Trajkovski
Keyword(s):  
Gut Microbiota ◽  
Gut Microbiome ◽  
New Order ◽  
Human Gut ◽  
Rarefaction Analysis ◽  
Human Counterpart ◽  
The Impact ◽  
Human And Mouse ◽  
Gut Metagenome ◽  
Mouse Gut Microbiota

AbstractMouse is the most used model for studying the impact of microbiota on its host, but the repertoire of species from the mouse gut microbiome remains largely unknown. Here, we construct a Comprehensive Mouse Gut Metagenome (CMGM) catalog by assembling all currently available mouse gut metagenomes and combining them with published reference and metagenome-assembled genomes. The 50’011 genomes cluster into 1’699 species, of which 78.1% are uncultured, and we discovered 226 new genera, 7 new families, and 1 new order. Rarefaction analysis indicates comprehensive sampling of the species from the mouse gut. CMGM enables an unprecedented coverage of the mouse gut microbiome exceeding 90%. Comparing CMGM to the human gut microbiota shows an overlap 64% at the genus, but only 16% at the species level, demonstrating that human and mouse gut microbiota are largely distinct.

scholarly journals Variations in the Post-weaning Human Gut Metagenome Profile As Result of Bifidobacterium Acquisition in the Western Microbiome

2016 ◽  
Vol 07 ◽  
Author(s):  
Matteo Soverini ◽  
Simone Rampelli ◽  
Silvia Turroni ◽  
Stephanie L. Schnorr ◽  
Sara Quercia ◽  
...  
Keyword(s):  
Human Gut ◽  
Gut Metagenome

scholarly journals Identifying Core Operons in Metagenomic Data

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

scholarly journals Revealing microbial assemblage structure in the human gut microbiome using latent Dirichlet allocation

2019 ◽  
Author(s):  
Shion Hosoda ◽  
Suguru Nishijima ◽  
Tsukasa Fukunaga ◽  
Masahira Hattori ◽  
Michiaki Hamada
Keyword(s):  
Data Mining ◽  
Cluster Analysis ◽  
Gut Microbiome ◽  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Mining Methods ◽  
Gut Metagenome ◽  
Dirichlet Allocation

AbstractRecent research has revealed that there are various microbial species in the human gut microbiome. To clarify the structure of the human gut microbiome, many data mining methods have been applied to microbial composition data. Cluster analysis, one of the key data mining methods that have been used in human gut microbiome research, can classify the human gut microbiome into three clusters, called enterotypes. The human gut microbiome has been suggested to be composed of the microbial assemblages or groups of co-occurring microbes, and one human gut microbiome can contain several microbial assemblages. However, cluster analysis can cluster samples into groups without capturing minor assemblages. In addition, a reliable method of assemblage detection has not been established, and little is known about the distributions of microbial assemblages at a population-level scale. Accordingly, the purpose of this study was to clarify the microbial assemblages in the human gut microbiome. In this study, we detected gut microbiome assemblages using a latent Dirichlet allocation (LDA) method, which was first proposed for the classification of documents in natural language processing. We applied LDA to a large-scale human gut metagenome dataset and found that a four-assemblage LDA model can represent relationships between enterotypes and assemblages with high interpretability. This model indicates that each individual tends to have several assemblages, and each of three assemblages corresponded to each enterotype. However, the C-assemblage can exist in all enterotypes. Interestingly, the dominant genera of the C-assemblage (Clostridium, Eubacterium, Faecalibacterium, Roseburia, Coprococcus, and Butyrivibrio) included butyrate-producing species such as Faecalibacterium prausnitzii. Finally, we revealed that genera mainly appearing in the same assemblage were correlated to each other. We conducted an assemblage analysis on a large-scale human gut metagenome dataset using LDA, a powerful method for detection of microbial assemblages. This approach has the potential to reveal the structure of the human gut microbiome.

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