Impact of Different Exercise Modalities on the 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.

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

10.1101/2021.06.29.450302 ◽

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.

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Taxonomic signatures of cause-specific mortality risk in human gut microbiome

Nature Communications ◽

10.1038/s41467-021-22962-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Aaro Salosensaari ◽

Ville Laitinen ◽

Aki S. Havulinna ◽

Guillaume Meric ◽

Susan Cheng ◽

...

Keyword(s):

Mortality Risk ◽

Gut Microbiome ◽

Human Gut ◽

Cross Sectional ◽

Microbiome Composition ◽

Human Gut Microbiome ◽

Non Invasive ◽

Sequencing Technologies

AbstractThe collection of fecal material and developments in sequencing technologies have enabled standardised and non-invasive gut microbiome profiling. Microbiome composition from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterised due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a well-phenotyped and representative population cohort from Finland (n = 7211). We report robust taxonomic and functional microbiome signatures related to the Enterobacteriaceae family that are associated with mortality risk during a 15-year follow-up. Our results extend previous cross-sectional studies, and help to establish the basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status.

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

PLoS ONE ◽

10.1371/journal.pone.0212474 ◽

2019 ◽

Vol 14 (2) ◽

pp. e0212474 ◽

Cited By ~ 1

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

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Alterations in human gut microbiome composition and metabolism after exposure to glyphosate and Roundup and/or a spore-based formulation using the SHIME® technology

10.1101/2021.12.16.472928 ◽

2021 ◽

Author(s):

Robin Mesnage ◽

Marta Calatayud ◽

Cindy Duysburgh ◽

Massimo Marzorati ◽

Michael Antoniou

Keyword(s):

Gut Microbiota ◽

Gut Microbiome ◽

Large Scale ◽

Epidemiological Studies ◽

Human Gut ◽

Microbiome Composition ◽

Human Gut Microbiome ◽

Ammonium Production ◽

Profiling Techniques ◽

Microbial Environment

Despite extensive research into the toxicology of the herbicide glyphosate, there are still major unknowns regarding its effects on the human gut microbiome. As a step in addressing this knowledge gap, we describe for the first time the effects of glyphosate and a Roundup glyphosate-based herbicide on infant gut microbiota using SHIME technology, which mimics the entire gastrointestinal tract. SHIME microbiota culture was undertaken in the presence of a concentration of 100 mg/L (corresponding to a dose of 1.6 mg/kg/day) glyphosate and the same glyphosate equivalent concentration of Roundup, which is in the range of the US chronic reference dose, and subjected to molecular profiling techniques to assess outcomes. Roundup and to a lesser extent glyphosate caused an increase in fermentation activity, resulting in acidification of the microbial environment. This was also reflected by an increase in lactate and acetate production concomitant to a decrease in the levels of propionate, valerate, caproate and butyrate. Ammonium production reflecting proteolytic activities was increased by Roundup exposure. Global metabolomics revealed large scale disturbances in metabolite profiles, including an increased abundance of long chain polyunsaturated fatty acids (n3 and n6). Although changes in bacterial composition measured by qPCR and 16S rRNA sequencing were less clear, our results suggested that lactobacilli had their growth stimulated as a result of microenvironment acidification. Co-treatment with the spore-based probiotic formulation MegaSporeBiotic reverted some of the changes in short-chain fatty acid levels. Altogether, our results suggest that glyphosate can exert effects on human gut microbiota at permitted regulatory levels of exposure, highlighting the need for epidemiological studies aimed at evaluating the effects of glyphosate herbicides on human gut microbiome function.

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Captivity humanizes the primate microbiome

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1521835113 ◽

2016 ◽

Vol 113 (37) ◽

pp. 10376-10381 ◽

Cited By ~ 168

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.

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

Genes ◽

10.3390/genes12030331 ◽

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.

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

Frontiers in Microbiology ◽

10.3389/fmicb.2021.667718 ◽

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.

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

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008487 ◽

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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