scholarly journals Captivity humanizes the primate microbiome

2016 ◽  
Vol 113 (37) ◽  
pp. 10376-10381 ◽  
Author(s):  
Jonathan B. Clayton ◽  
Pajau Vangay ◽  
Hu Huang ◽  
Tonya Ward ◽  
Benjamin M. Hillmann ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Meta Analysis ◽  
Human Microbiome ◽  
16S Rrna Gene Sequencing ◽  
Modern Human ◽  
Primate Species ◽  
Rrna Gene ◽  
Human Gut ◽  
Dietary Analysis ◽  
Human Gut Microbiome

The primate gastrointestinal tract is home to trillions of bacteria, whose composition is associated with numerous metabolic, autoimmune, and infectious human diseases. Although there is increasing evidence that modern and Westernized societies are associated with dramatic loss of natural human gut microbiome diversity, the causes and consequences of such loss are challenging to study. Here we use nonhuman primates (NHPs) as a model system for studying the effects of emigration and lifestyle disruption on the human gut microbiome. Using 16S rRNA gene sequencing in two model NHP species, we show that although different primate species have distinctive signature microbiota in the wild, in captivity they lose their native microbes and become colonized with Prevotella and Bacteroides, the dominant genera in the modern human gut microbiome. We confirm that captive individuals from eight other NHP species in a different zoo show the same pattern of convergence, and that semicaptive primates housed in a sanctuary represent an intermediate microbiome state between wild and captive. Using deep shotgun sequencing, chemical dietary analysis, and chloroplast relative abundance, we show that decreasing dietary fiber and plant content are associated with the captive primate microbiome. Finally, in a meta-analysis including published human data, we show that captivity has a parallel effect on the NHP gut microbiome to that of Westernization in humans. These results demonstrate that captivity and lifestyle disruption cause primates to lose native microbiota and converge along an axis toward the modern human microbiome.

scholarly journals Correction: 16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0212474 ◽  
Author(s):  
Daniel E. Almonacid ◽  
Laurens Kraal ◽  
Francisco J. Ossandon ◽  
Yelena V. Budovskaya ◽  
Juan Pablo Cardenas ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gut Microbiome ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Reference Ranges ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Rrna Gene Sequencing

scholarly journals Whole-Genome Metagenomic Analysis of the Gut Microbiome in HIV-1-Infected Individuals on Antiretroviral Therapy

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiangning Bai ◽  
Aswathy Narayanan ◽  
Piotr Nowak ◽  
Shilpa Ray ◽  
Ujjwal Neogi ◽  
...  
Keyword(s):  
Antiretroviral Therapy ◽  
Gut Microbiome ◽  
Alpha Diversity ◽  
16S Rrna Gene Sequencing ◽  
Taxonomic Resolution ◽  
Rrna Gene ◽  
Human Gut ◽  
Shotgun Metagenomics ◽  
Human Gut Microbiome ◽  
Hiv 1

Gut microbiome plays a significant role in HIV-1 immunopathogenesis and HIV-1-associated complications. Previous studies have mostly been based on 16S rRNA gene sequencing, which is limited in taxonomic resolution at the genus level and inferred functionality. Herein, we performed a deep shotgun metagenomics study with the aim to obtain a more precise landscape of gut microbiome dysbiosis in HIV-1 infection. A reduced tendency of alpha diversity and significantly higher beta diversity were found in HIV-1-infected individuals on antiretroviral therapy (ART) compared to HIV-1-negative controls. Several species, such as Streptococcus anginosus, Actinomyces odontolyticus, and Rothia mucilaginosa, were significantly enriched in the HIV-1-ART group. Correlations were observed between the degree of immunodeficiency and gut microbiome in terms of microbiota composition and metabolic pathways. Furthermore, microbial shift in HIV-1-infected individuals was found to be associated with changes in microbial virulome and resistome. From the perspective of methodological evaluations, our study showed that different DNA extraction protocols significantly affect the genomic DNA quantity and quality. Moreover, whole metagenome sequencing depth affects critically the recovery of microbial genes, including virulome and resistome, while less than 5 million reads per sample is sufficient for taxonomy profiling in human fecal metagenomic samples. These findings advance our understanding of human gut microbiome and their potential associations with HIV-1 infection. The methodological assessment assists in future study design to accurately assess human gut microbiome.

scholarly journals 16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome

PLoS ONE ◽  
2017 ◽  
Vol 12 (5) ◽  
pp. e0176555 ◽  
Author(s):  
Daniel E. Almonacid ◽  
Laurens Kraal ◽  
Francisco J. Ossandon ◽  
Yelena V. Budovskaya ◽  
Juan Pablo Cardenas ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gut Microbiome ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Reference Ranges ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Rrna Gene Sequencing

scholarly journals Revealing Protein-Level Functional Redundancy in the Human Gut Microbiome using Ultra-deep Metaproteomics

2021 ◽  
Author(s):  
Leyuan Li ◽  
Zhibin Ning ◽  
Xu Zhang ◽  
James Butcher ◽  
Caitlin Simopoulos ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Protein Level ◽  
Functional Organization ◽  
Human Microbiome ◽  
Functional Redundancy ◽  
Human Gut ◽  
Functional Roles ◽  
Human Gut Microbiome ◽  
Metagenomics Data ◽  
Network Approaches

Functional redundancy is a key property of ecosystems and represents the fact that phylogenetically unrelated taxa can play similar functional roles within an ecosystem. The redundancy of potential functions of human microbiome has been recently quantified using metagenomics data. Yet, the redundancy of functions which are actually expressed within the human microbiome remains largely unexplored. Here, we quantify the protein-level functional redundancy in the human gut microbiome using metaproteomics and network approaches. In particular, our ultra-deep metaproteomics approach revealed high protein-level functional redundancy and high nestedness in proteomic content networks - bipartite graphs that connect taxa with their expressed functions. We further examined multiple metaproteomics datasets and showed that various environmental factors, including individuality, biogeography, xenobiotics, and disease, significantly altered the protein-level functional redundancy. Finally, by projecting the bipartite proteomic content networks into unipartite weighted genus networks, functional hub genera across individual microbiomes were discovered, suggesting that there may be a universal principle of functional organization in microbiome assembly.

scholarly journals Quantitatively Different, yet Qualitatively Alike: A Meta-Analysis of the Mouse Core Gut Microbiome with a View towards the Human Gut Microbiome

PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e62578 ◽  
Author(s):  
Lukasz Krych ◽  
Camilla H. F. Hansen ◽  
Axel K. Hansen ◽  
Frans W. J. van den Berg ◽  
Dennis S. Nielsen
Keyword(s):  
Gut Microbiome ◽  
Meta Analysis ◽  
Human Gut ◽  
Human Gut Microbiome

scholarly journals Natural and after colon washing fecal samples: the two sides of the coin for investigating the human gut microbiome

2021 ◽  
Author(s):  
Elisabetta Piancone ◽  
Bruno Fosso ◽  
Mariangela De Robertis ◽  
Elisabetta Notario ◽  
Annarita Oranger ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Gut Microbiome ◽  
Digital Pcr ◽  
Shannon Index ◽  
Individual Variability ◽  
Rrna Gene ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Taxonomic Analysis ◽  
Paired Samples

To date there are several studies focusing on the importance of gut microbiome for human health, however the selection of a universal sampling matrix representative of the microbial biodiversity associated to the gastrointestinal (GI) tract, still represents a challenge. Here we present a study in which, through a deep metabarcoding analysis of the 16S rRNA gene, we compared two sampling matrices, feces (F) and colonic lavage liquid (LL), in order to evaluate their accuracy to represent the complexity of the human gut microbiome. A training set of 37 volunteers was attained and paired F and LL samples were collected from each subject. A preliminary absolute quantification of total 16S rDNA, performed by droplet digital PCR (ddPCR), confirmed that sequencing and taxonomic analysis were performed on same total bacterial abundance obtained from the two sampling methods. The taxonomic analysis of paired samples revealed that, although specific taxa were predominantly or exclusively observed in LL samples, as well as other taxa were detectable only or were predominant in stool, the microbiomes of the paired samples F and LL in the same subject hold overlapping taxonomic composition. Moreover, LL samples revealed a higher biodiversity than stool at all taxonomic ranks, as demonstrated by the Shannon Index and the Inverse Simpson's Index. We also found greater inter-individual variability than intra-individual variability in both sample matrices. Finally, functional differences were unveiled in the gut microbiome detected in the F and LL samples. A significant overrepresentation of 22 and 13 metabolic pathways, mainly occurring in Firmicutes and Proteobacteria, was observed in gut microbiota detected in feces and LL samples, respectively. This suggests that LL samples may allow for the detection of microbes adhering to the intestinal mucosal surface as members of the resident flora that are not easily detectable in stool, most likely representative of a diet-influenced transient microbiota. This first comparative study on feces and LL samples for the study of the human gut microbiome demonstrates that the use of both types of sample matrices may represent a possible choice to obtain a more complete view of the human gut microbiota in response to different biological and clinical questions.

scholarly journals Impact of Different Exercise Modalities on the Human Gut Microbiome

Sports ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 14
Author(s):  
Dierdra Bycura ◽  
Anthony C. Santos ◽  
Arron Shiffer ◽  
Shari Kyman ◽  
Kyle Winfree ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Gut Microbiome ◽  
Sequence Data ◽  
Exercise Program ◽  
Rrna Gene ◽  
Human Gut ◽  
Post Intervention ◽  
Cross Sectional ◽  
Intervention Phase ◽  
Human Gut Microbiome

In this study we examined changes to the human gut microbiome resulting from an eight-week intervention of either cardiorespiratory exercise (CRE) or resistance training exercise (RTE). Twenty-eight subjects (21 F; aged 18–26) were recruited for our CRE study and 28 subjects (17 F; aged 18–33) were recruited for our RTE study. Fecal samples for gut microbiome profiling were collected twice weekly during the pre-intervention phase (three weeks), intervention phase (eight weeks), and post-intervention phase (three weeks). Pre/post VO2max, three repetition maximum (3RM), and body composition measurements were conducted. Heart rate ranges for CRE were determined by subjects’ initial VO2max test. RTE weight ranges were established by subjects’ initial 3RM testing for squat, bench press, and bent-over row. Gut microbiota were profiled using 16S rRNA gene sequencing. Microbiome sequence data were analyzed with QIIME 2. CRE resulted in initial changes to the gut microbiome which were not sustained through or after the intervention period, while RTE resulted in no detectable changes to the gut microbiota. For both CRE and RTE, we observe some evidence that the baseline microbiome composition may be predictive of exercise gains. This work suggests that the human gut microbiome can change in response to a new exercise program, but the type of exercise likely impacts whether a change occurs. The changes observed in our CRE intervention resemble a disturbance to the microbiome, where an initial shift is observed followed by a return to the baseline state. More work is needed to understand how sustained changes to the microbiome occur, resulting in differences that have been reported in cross sectional studies of athletes and non-athletes.

scholarly journals Analysis of Human Gut Microbiome: Taxonomy and Metabolic Functions in Thai Adults

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 331
Author(s):  
Nachon Raethong ◽  
Massalin Nakphaichit ◽  
Narissara Suratannon ◽  
Witida Sathitkowitchai ◽  
Wanlapa Weerapakorn ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Asian Country ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Human Gut ◽  
Thai Population ◽  
Shotgun Metagenomics ◽  
Human Gut Microbiome ◽  
Metabolic Functions

The gut microbiome plays a major role in the maintenance of human health. Characterizing the taxonomy and metabolic functions of the human gut microbiome is necessary for enhancing health. Here, we analyzed the metagenomic sequencing, assembly and construction of a meta-gene catalogue of the human gut microbiome with the overall aim of investigating the taxonomy and metabolic functions of the gut microbiome in Thai adults. As a result, the integrative analysis of 16S rRNA gene and whole metagenome shotgun (WMGS) sequencing data revealed that the dominant gut bacterial families were Lachnospiraceae and Ruminococcaceae of the Firmicutes phylum. Consistently, across 3.8 million (M) genes annotated from 163.5 gigabases (Gb) of WMGS sequencing data, a significant number of genes associated with carbohydrate metabolism of the dominant bacterial families were identified. Further identification of bacterial community-wide metabolic functions promisingly highlighted the importance of Roseburia and Faecalibacterium involvement in central carbon metabolism, sugar utilization and metabolism towards butyrate biosynthesis. This work presents an initial study of shotgun metagenomics in a Thai population-based cohort in a developing Southeast Asian country.

scholarly journals Microbial ACBP/DBI-like genes are rare in the human gut microbiome and show no links with obesity

2021 ◽  
Author(s):  
Andrew Maltez Thomas ◽  
Francesco Asnicar ◽  
Guido Kroemer ◽  
Nicola Segata
Keyword(s):  
Gut Microbiome ◽  
Pathogenic Bacteria ◽  
Coenzyme A ◽  
Binding Protein ◽  
Human Microbiome ◽  
Human Metabolism ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Domains Of Life ◽  
Acyl Coenzyme A

Acyl coenzyme A (CoA) binding protein (ACBP), also called diazepam-binding inhibitor (DBI) is a phylogenetically conserved protein that is expressed by all eukaryotic species as well as by some bacteria. Since elevated ACBP/DBI levels play a major role in the inhibition of autophagy, increase in appetite and lipoanabolism that accompany obesity, we wondered whether ACBP/DBI produced by the human microbiome might affect host weight. We found that the genomes of bacterial commensals rarely contain ACBP/DBI homologues, which are rather encoded by genomes of some pathogenic or environmental taxa that were not prevalent in human feces. Exhaustive bioinformatic analyses of 1,899 gut samples from healthy individuals refuted the hypothesis that bacterial ACBP/DBI might affect the BMI in a physiological context. Thus, the physiological regulation of BMI is unlikely to be affected by microbial ACBP/DBI-like proteins. However, at the speculative level, it remains possible that ACBP/DBI produced by potential pathogenic bacteria might enhance their virulence by inhibiting autophagy and hence subverting innate immune responses. Importance Acyl coenzyme A (CoA) binding protein (ACBP) can be encoded by several organisms across the domains of life, including microbes, and has shown to play major roles in human metabolic processes. However, little is known about its presence in the human gut microbiome and whether its microbial counterpart could also play a role in human metabolism. In the present study, we found that microbial ACBP/DBI sequences were rarely present in the gut microbiome across multiple metagenomic datasets. Microbes that carried ACBP/DBI in the human gut microbiome included Saccharomyces cerevisiae, Lautropia mirabilis and Comamonas kerstersii, but these microorganisms were not associated with body-mass index, further indicating an unconvincing role for microbial ACBP/DBI in human metabolism.

scholarly journals MetGEMs Toolbox: Metagenome-scale models as integrative toolbox for uncovering metabolic functions and routes of human gut microbiome

2021 ◽  
Vol 17 (1) ◽  
pp. e1008487
Author(s):  
Preecha Patumcharoenpol ◽  
Massalin Nakphaichit ◽  
Gianni Panagiotou ◽  
Anchalee Senavonge ◽  
Narissara Suratannon ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gut Microbiome ◽  
Rrna Gene ◽  
16S Rrna Gene Sequences ◽  
Functional Capability ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Metabolic Functions ◽  
Scale Models

Investigating metabolic functional capability of a human gut microbiome enables the quantification of microbiome changes, which can cause a phenotypic change of host physiology and disease. One possible way to estimate the functional capability of a microbial community is through inferring metagenomic content from 16S rRNA gene sequences. Genome-scale models (GEMs) can be used as scaffold for functional estimation analysis at a systematic level, however up to date, there is no integrative toolbox based on GEMs for uncovering metabolic functions. Here, we developed the MetGEMs (metagenome-scale models) toolbox, an open-source application for inferring metabolic functions from 16S rRNA gene sequences to facilitate the study of the human gut microbiome by the wider scientific community. The developed toolbox was validated using shotgun metagenomic data and shown to be superior in predicting functional composition in human clinical samples compared to existing state-of-the-art tools. Therefore, the MetGEMs toolbox was subsequently applied for annotating putative enzyme functions and metabolic routes related in human disease using atopic dermatitis as a case study.

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