LogMPIE, pan-India profiling of the human gut microbiome using 16S rRNA sequencing

The consortium of trillions of microorganisms that live inside the human gut are integral to health. Little has been done to collate and characterize the microbiome of children. A systematic review was undertaken to address this gap (PROSPERO ID: CRD42018109599). MEDLINE and EMBASE were searched using the keywords: “healthy preadolescent children” and “gut microbiome” to 31 August 2018. Of the 815 journal articles, 42 met the inclusion criteria. The primary outcome was the relative abundance of bacteria at the phylum, family, and genus taxonomic ranks. α-diversity, short chain fatty acid concentrations, diet, 16S rRNA sequencing region, and geographical location were documented. The preadolescent gut microbiome is dominated at the phylum level by Firmicutes (weighted overall average relative abundance = 51.1%) and Bacteroidetes (36.0%); genus level by Bacteroides (16.0%), Prevotella (8.69%), Faecalibacterium (7.51%), and Bifidobacterium (5.47%). Geographic location and 16S rRNA sequencing region were independently associated with microbial proportions. There was limited consensus between studies that reported α-diversity and short chain fatty acids. Broadly speaking, participants from non-Western locations, who were less likely to follow a Westernized dietary pattern, had higher α-diversity and SCFA concentrations. Confirmatory studies will increase the understanding of the composition and functional capacity of the preadolescent gut microbiome.

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Faculty Opinions recommendation of The pervasive effects of an antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1148044.605153 ◽

2009 ◽

Author(s):

Anna-Louise Reysenbach

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

16S Rrna Sequencing ◽

Human Gut ◽

Human Gut Microbiota ◽

Rrna Sequencing

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Accurate Five-category Classification for Colorectal Cancer Using Gut Microbiome 16S rRNA Sequencing

10.21203/rs.3.rs-763700/v1 ◽

2021 ◽

Author(s):

Liying Zhang ◽

Jiaqi Zhu ◽

Qiutao Ding ◽

Yanqi Huang ◽

Hongbo Zhang ◽

...

Keyword(s):

Colorectal Cancer ◽

16S Rrna ◽

Gut Microbiome ◽

Large Scale ◽

Operational Taxonomic Unit ◽

16S Rrna Sequencing ◽

Screening Tests ◽

Advanced Adenoma ◽

Sequencing Data ◽

Rrna Sequencing

Abstract The association between the gut microbiome and the five stages of colorectal cancer (CRC) (healthy, polyposis, nonadvanced adenoma, advanced adenoma, and cancer) remains unclear. We performed 16S rRNA sequencing of the V3-V4 amplicon from 999 samples from subjects at various stages of CRC development and constructed an accurate predictive random forest model for CRC development. In the testing set, our five-category CRC prediction classifier had accuracies of 0.84 and 0.74 using the relative operational taxonomic unit (OTU) abundances and relative genus abundances, respectively. Specifically, the OTU-based classifier had a sensitivity of 0.97 and specificity of 0.97 for CRC samples, and the genus-based classifier had a sensitivity of 0.97 and specificity of 0.95 for CRC samples. Meanwhile, the gut microbiota was found to differ at all stages of CRC development. The differential abundances of closely related bacteria were used to accurately classify the five stages of CRC development. Additionally, both unannotated and annotated OTUs played important roles in classifier modelling. Our work not only provides valuable 16S rRNA sequencing data from patients and healthy individuals on a large scale but also identifies reproducible gut microbiome biomarkers for CRC staging and highlights their potential applications as noninvasive microbiome biomarkers for diagnosis and as predictive CRC screening tests.

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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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The Pervasive Effects of an Antibiotic on the Human Gut Microbiota, as Revealed by Deep 16S rRNA Sequencing

PLoS Biology ◽

10.1371/journal.pbio.0060280 ◽

2008 ◽

Vol 6 (11) ◽

pp. e280 ◽

Cited By ~ 1421

Author(s):

Les Dethlefsen ◽

Sue Huse ◽

Mitchell L Sogin ◽

David A Relman

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

16S Rrna Sequencing ◽

Human Gut ◽

Human Gut Microbiota ◽

Rrna Sequencing

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Stimulation of Codonopsis pilosula Polysaccharide on Bifidobacterium of Human Gut Bacteria In Vitro

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/9524913 ◽

2021 ◽

Vol 2021 ◽

pp. 1-4

Author(s):

Jiankuan Li ◽

Lina Dong ◽

Yue Liu ◽

Jianping Gao

Keyword(s):

16S Rrna ◽

Human Health ◽

Gut Bacteria ◽

16S Rrna Sequencing ◽

Human Gut ◽

In Vitro Methods ◽

Codonopsis Pilosula ◽

Rrna Sequencing ◽

Stimulation Of

Objective. To evaluate the prebiotic effects of Codonopsis pilosula polysaccharide (CPP) on human gut bacteria in vitro. Methods. Codonopsis Radix was extracted with water at 100°C, and the extract was precipitated by 80% ethanol to obtain CPP. Human fresh fecal samples were collected from three healthy adults and used to ferment CPP. The fermented samples were collected to be analyzed by 16S rRNA sequencing. Results. The results showed that CPP exhibited significantly the stimulation on the growth of genus Bifidobacterium of human gut bacteria (Padj < 0.05). Although CPP also exhibited regulative trends on the genera including Acidaminococcus, Bilophila, Dorea, and Eggerthella, no significant differences were observed (Padj > 0.05), which was likely associated with the limited samples (n = 3). Conclusion. CPP has the potential to stimulate the growth of Bifidobacterium of the human gut bacteria and to be benefit to human health.

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Noise exposure-induced intestinal flora dysbiosis disrupts homeostasis of oxi-inflamm-barrier in the gut–brain axis of APP/PS1 mice: implications for early onset Alzheimer's disease

10.21203/rs.3.rs-19045/v1 ◽

2020 ◽

Author(s):

Bo Cui ◽

Huimin Chi ◽

Wa Cao ◽

Donghong Su ◽

Honglian Yang ◽

...

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

16S Rrna ◽

Gut Microbiome ◽

Early Onset ◽

Noise Exposure ◽

Intestinal Flora ◽

Environmental Noise ◽

16S Rrna Sequencing ◽

Rrna Sequencing

Abstract Background: Environmental noise exposure and genetic risk factors are thought to be associated with gut microbiome that exacerbates Alzheimer’s disease (AD) pathology. However, the role and mechanism of environmental risk factors in early-onset AD (EOAD) pathogenesis remain unclear. Methods: We established APP/PS1 Tg and C57BL/6 (wild type [WT]) mouse models to evaluate the molecular pathways underlying EOAD pathophysiology following environmental noise exposure. 16S rRNA sequencing analyses were used for intestinal flora measurements and Tax4Fun were used to predict the metagenome content from 16S rRNA sequencing results; and assessment of the flora dysbiosis-triggered dyshomeostasis of oxi-inflamm-barrier and the effects of the CNS end of the gut–brain axis were conducted to explore the underlying pathological mechanisms. Results: Both WT and APP/PS1 mice showed statistically significant relationship between environmental noise and the taxonomic composition of the corresponding gut microbiome. Bacterial-encoded functional categories in noise-exposed WT and APP/PS1 mice included phospholipid and galactose metabolism, oxidative stress, and cell senescence. These alterations corresponded with imbalanced intestinal oxidation and anti-oxidation systems and low-grade systemic inflammation after noise exposure. Mechanistically, axis-series experiments demonstrated that after noise exposure, intestinal and hippocampal tight junction proteins levels reduced, whereas serum levels of inflammatory mediator were elevated. With regard to APP/PS1 overexpression, noise-induced abnormalities in the gut–brain axis may contribute to aggravation of neuropathology in the presymptomatic stage of EOAD mice model. Conclusions: Our results demonstrate that noise exposure has deleterious effects on the homeostasis of oxi-inflamm-barrier in the microbiome–gut–brain axis. Therefore, at least in a genetic context, chronic noise may aggravate the progression of EOAD.

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Gut microbiota modification suppresses the development of pulmonary arterial hypertension in an SU5416/hypoxia rat model

Pulmonary Circulation ◽

10.1177/2045894020929147 ◽

2020 ◽

Vol 10 (3) ◽

pp. 204589402092914

Author(s):

Takayuki J. Sanada ◽

Koji Hosomi ◽

Hiroki Shoji ◽

Jonguk Park ◽

Akira Naito ◽

...

Keyword(s):

Pulmonary Arterial Hypertension ◽

16S Rrna ◽

Gut Microbiota ◽

Arterial Hypertension ◽

Right Ventricular ◽

Rat Model ◽

Gut Microbiome ◽

16S Rrna Sequencing ◽

Rrna Sequencing ◽

Pulmonary Arterial

The pathogenesis of pulmonary arterial hypertension is closely associated with dysregulated inflammation. Recently, abnormal alterations in gut microbiome composition and function were reported in a pulmonary arterial hypertension experimental animal model. However, it remains unclear whether these alterations are a result or the cause of pulmonary arterial hypertension. The purpose of this study was to investigate whether alterations in the gut microbiome affected the hemodynamics in SU5416/hypoxia rats. We used the SU5416/hypoxia rat model in our study. SU5416/hypoxia rats were treated with a single SU5416 injection (30 mg/kg) and a three-week hypoxia exposure (10% O2). Three SU5416/hypoxia rats were treated with a combination of four antibiotics (SU5416/hypoxia + ABx group) for four weeks. Another group was exposed to hypoxia (10% O2) without the SU5416 treatment, and control rats received no treatment. Fecal samples were collected from each animal, and the gut microbiota composition was analyzed by 16S rRNA sequencing. The antibiotic treatment significantly suppressed the vascular remodeling, right ventricular hypertrophy, and increase in the right ventricular systolic pressure in SU5416/hypoxia rats. 16S rRNA sequencing analysis revealed gut microbiota modification in SU5416/hypoxia + ABx group. The Firmicutes-to-Bacteroidetes ratio in SU5416/hypoxia rats was significantly higher than that in control and hypoxia rats. Compared with the control microbiota, 14 bacterial genera, including Bacteroides and Akkermansia, increased, whereas seven bacteria, including Rothia and Prevotellaceae, decreased in abundance in SU5416/hypoxia rats. Antibiotic-induced modification of the gut microbiota suppresses the development of pulmonary arterial hypertension. Dysbiosis may play a causal role in the development and progression of pulmonary arterial hypertension.

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