scholarly journals HumGut: A comprehensive Human Gut prokaryotic genomes collection filtered by metagenome data

2020 ◽  
Author(s):  
Pranvera Hiseni ◽  
Knut Rudi ◽  
Robert C. Wilson ◽  
Finn Terje Hegge ◽  
Lars Snipen

AbstractA major challenge with human gut microbiome studies is the lack of a publicly accessible human gut genome collection that is verifiably complete. We aimed to create Humgut, a comprehensive collection of healthy human gut prokaryotic genomes, to be used as a reference for worldwide human gut microbiome studies. We screened >2,300 healthy human gut metagenomes for the containment of >486,000 publicly available prokaryotic genomes. The contained genomes were then scored, ranked, and clustered based on their sequence identity, only to keep representative genomes per cluster, resulting thus in the creation of HumGut. Superior performance in the taxonomic assignment of metagenomic reads, classifying 97% of reads on average, is a benchmark advantage of HumGut. Re-analyses of healthy gut samples using HumGut revealed that >90% contained a core set of 129 bacterial species and that, on average, the guts of healthy people contain around 1,000 bacterial species. The HumGut collection will continuously be updated as the list of publicly available genomes and metagenomes expand. Our approach can also be extended to disease-associated genomes and metagenomes, in addition to other species. The comprehensive, yet slim HumGut database streamlines analyses while significantly improving taxonomic assignments in a field in dire need of method standardization and effectivity.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mark Loftus ◽  
Sayf Al-Deen Hassouneh ◽  
Shibu Yooseph

AbstractIn a microbial community, associations between constituent members play an important role in determining the overall structure and function of the community. The human gut microbiome is believed to play an integral role in host health and disease. To understand the nature of bacterial associations at the species level in healthy human gut microbiomes, we analyzed previously published collections of whole-genome shotgun sequence data, totaling over 1.6 Tbp, generated from 606 fecal samples obtained from four different healthy human populations. Using a Random Forest Classifier, we identified 202 signature bacterial species that were prevalent in these populations and whose relative abundances could be used to accurately distinguish between the populations. Bacterial association networks were constructed with these signature species using an approach based on the graphical lasso. Network analysis revealed conserved bacterial associations across populations and a dominance of positive associations over negative associations, with this dominance being driven by associations between species that are closely related either taxonomically or functionally. Bacterial species that form network modules, and species that constitute hubs and bottlenecks, were also identified. Functional analysis using protein families suggests that much of the taxonomic variation across human populations does not foment substantial functional or structural differences.


2018 ◽  
Vol 14 (9) ◽  
pp. 560-573 ◽  
Author(s):  
Fauzul Mobeen ◽  
◽  
Vikas Sharma ◽  
Tulika Prakash ◽  
◽  
...  

2012 ◽  
Vol 12 (5) ◽  
pp. 611-622 ◽  
Author(s):  
Fredrik Bäckhed ◽  
Claire M. Fraser ◽  
Yehuda Ringel ◽  
Mary Ellen Sanders ◽  
R. Balfour Sartor ◽  
...  

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Bianca De Saedeleer ◽  
Antoine Malabirade ◽  
Javier Ramiro-Garcia ◽  
Janine Habier ◽  
Jean-Pierre Trezzi ◽  
...  

AbstractThe human gut microbiome produces a complex mixture of biomolecules that interact with human physiology and play essential roles in health and disease. Crosstalk between micro-organisms and host cells is enabled by different direct contacts, but also by the export of molecules through secretion systems and extracellular vesicles. The resulting molecular network, comprised of various biomolecular moieties, has so far eluded systematic study. Here we present a methodological framework, optimized for the extraction of the microbiome-derived, extracellular biomolecular complement, including nucleic acids, (poly)peptides, and metabolites, from flash-frozen stool samples of healthy human individuals. Our method allows simultaneous isolation of individual biomolecular fractions from the same original stool sample, followed by specialized omic analyses. The resulting multi-omics data enable coherent data integration for the systematic characterization of this molecular complex. Our results demonstrate the distinctiveness of the different extracellular biomolecular fractions, both in terms of their taxonomic and functional composition. This highlights the challenge of inferring the extracellular biomolecular complement of the gut microbiome based on single-omic data. The developed methodological framework provides the foundation for systematically investigating mechanistic links between microbiome-secreted molecules, including those that are typically vesicle-associated, and their impact on host physiology in health and disease.


2019 ◽  
Author(s):  
Pranatchareeya Chankhamjon ◽  
Bahar Javdan ◽  
Jaime Lopez ◽  
Raphaella Hull ◽  
Seema Chatterjee ◽  
...  

ABSTRACTThe human gut microbiome harbors hundreds of bacterial species with diverse biochemical capabilities, making it one of nature’s highest density, highest diversity bioreactors. Several drugs have been previously shown to be directly metabolized by the gut microbiome, but the extent of this phenomenon has not been systematically explored. Here, we develop a systematic screen for mapping the ability of the complex human gut microbiome to biochemically transform small molecules (MDM-Screen), and apply it to a library of 575 clinically used oral drugs. We show that 13% of the analyzed drugs, spanning 28 pharmacological classes, are metabolized by a single microbiome sample. In a proof-of-principle example, we show that microbiome-derived metabolism occursin vivo, identify the genes responsible for it, and provide a possible link between its consequences and clinically observed features of drug bioavailability and toxicity. Our findings reveal a previously underappreciated role for the gut microbiome in drug metabolism, and provide a comprehensive framework for characterizing this important class of drug-microbiome interactions.


2021 ◽  
Author(s):  
Moses Stamboulian ◽  
Jamie Canderan ◽  
Yuzhen Ye

AbstractHost-microbiome interactions and the microbial community have broad impact in human health and diseases. Most microbiome based studies are performed at the genome level based on next-generation sequencing techniques, but metaproteomics is emerging as a powerful technique to study microbiome functional activity by characterizing the complex and dynamic composition of microbial proteins. We conducted a large-scale survey of human gut microbiome metaproteomic data to identify generalist species that are ubiquitously expressed across all samples and specialists that are highly expressed in a small subset of samples associated with a certain phenotype. We were able to utilize the metaproteomic mass spectrometry data to reveal the protein landscapes of these species, which enables the characterization of the expression levels of proteins of different functions and underlying regulatory mechanisms, such as operons. Finally, we were able to recover a large number of open reading frames (ORFs) with spectral support, which were missed by de novo protein-coding gene predictors. We showed that a majority of the rescued ORFs overlapped with de novo predicted proteincoding genes, but on opposite strands or on different frames. Together, these demonstrate applications of metaproteomics for the characterization of important gut bacterial species. Results are available for public access at https://omics.informatics.indiana.edu/GutBac.Author summaryMany reference genomes for studying human gut microbiome are available, but knowledge about how microbial organisms work is limited. Identification of proteins at individual species or community level provides direct insight into the functionality of microbial organisms. By analyzing more than a thousand metaproteomics datasets, we examined protein landscapes of more than two thousands of microbial species that may be important to human health and diseases. This work demonstrated new applications of metaproteomic datasets for studying individual genomes. We made the analysis results available through the GutBac website, which we believe will become a resource for studying microbial species important for human health and diseases.


2017 ◽  
Vol 5 (2) ◽  
Author(s):  
Bruce A. Rosa ◽  
Kymberlie Hallsworth-Pepin ◽  
John Martin ◽  
Aye Wollam ◽  
Makedonka Mitreva

ABSTRACT Obesity influences and is influenced by the human gut microbiome. Here, we present the genome of Christensenella minuta, a highly heritable bacterial species which has been found to be strongly associated with obesity through an unknown biological mechanism. This novel genome provides a valuable resource for future obesity therapeutic studies.


2021 ◽  
pp. 100039
Author(s):  
Zhuye Jie ◽  
Suisha Liang ◽  
Qiuxia Ding ◽  
Fei Li ◽  
Shanmei Tang ◽  
...  

2021 ◽  
Author(s):  
Richard Wolff ◽  
William R. Shoemaker ◽  
Nandita R. Garud

The human gut microbiome is a complex community that harbors substantial ecological diversity at the species level, as well as at the strain level within species. In healthy hosts, species abundance fluctuations in the microbiome community are thought to be stable, and these fluctuations can be described by macroecological laws. However, it is less clear how strain abundances change over time. An open question is whether individual strains behave like species themselves, exhibiting stability and following the macroecological relationships known to hold at the species level, or whether strains have different dynamics, perhaps due to the relatively close phylogenetic relatedness of co-colonizing lineages. In this study, we sought to characterize the typical strain-level dynamics of the healthy human gut microbiome on timescales ranging from days to years. We show that genetic diversity within almost all species is stationary, tending towards a long-term typical value within hosts over time scales of several years, despite fluctuations on shorter timescales. Moreover, the abundance fluctuations of strains can be sufficiently described by a stochastic logistic model (SLM), a model previously used to describe abundance fluctuations among species around a fixed carrying capacity, in the vast majority of cases, suggesting that strains are dynamically stable. Lastly, we find that strain abundances follow the same macroecological laws known to hold at the species level. Together, our results suggest that macroecological properties of the human gut microbiome, including its stability, emerge at the level of strains.


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