Metagenomic Analysis of the Dynamic Changes in the Gut Microbiome of the Participants of the MARS-500 Experiment, Simulating Long Term Space Flight

A metagenomic analysis of the dynamic changes of the composition of the intestinal microbiome of five participants of the MARS-500 experiment was performed. DNA samples were isolated from the feces of the participants taken just before the experiment, upon 14, 30, 210, 363 and 510 days of isolation in the experimental module, and two weeks upon completion of the experiment. The taxonomic composition of the microbiome was analyzed by pyrosequencing of 16S rRNA gene fragments. Both the taxonomic and functional gene content of the microbiome of one participant were analyzed by whole metagenome sequencing using the SOLiD technique. Each participant had a specific microbiome that could be assigned to one of three recognized enterotypes. Two participants had enterotype I microbiomes characterized by the prevalence of Bacteroides, while the microbiomes of two others, assigned to type II, were dominated by Prevotella. One participant had a microbiome of mixed type. It was found that (1) changes in the taxonimic composition of the microbiomes occurred in the course of the experiment, but the enterotypes remained the same; (2) significant changes in the compositions of the microbiomes occurred just 14-30 days after the beginning of the experiment, presumably indicating the influence of stress factors in the first stage of the experiment; (3) a tendency toward a reversion of the microbiomes to their initial composition was observed two weeks after the end of the experiment, but complete recovery was not achieved. The metagenomic analysis of the microbiome of one of the participants showed that in spite of variations in the taxonomic compositions of microbiomes, the functional genetic composition was much more stable for most of the functional gene categories. Probably in the course of the experiment the taxonomic composition of the gut microbiome was adaptively changed to reflect the individual response to the experimental conditions. A new, balanced taxonomic composition of the microbiome was formed to ensure a stable gene content of the community as a whole without negative consequences for the health of the participants.

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Mo1673 Metagenomic Analysis of the Dynamic Changes in the Gut Microbiome of African American With Colorectal Cancer

Gastroenterology ◽

10.1016/s0016-5085(14)62290-3 ◽

2014 ◽

Vol 146 (5) ◽

pp. S-633

Author(s):

Hassan Brim ◽

Edward L. Lee ◽

Adeyinka O. Laiyemo ◽

Scot E. Dowd ◽

Hassan Ashktorab

Keyword(s):

Colorectal Cancer ◽

African American ◽

Gut Microbiome ◽

Metagenomic Analysis ◽

Dynamic Changes

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Characterization of gut microbiome associated with improvement of ulcerative colitis after antibiotic combination therapy using fecal metagenomic analysis

10.26226/morressier.59a6b343d462b80290b54311 ◽

2017 ◽

Author(s):

Kimitoshi Kato

Keyword(s):

Ulcerative Colitis ◽

Combination Therapy ◽

Gut Microbiome ◽

Metagenomic Analysis ◽

Antibiotic Combination

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Faculty Opinions recommendation of Metagenomic analysis of the human distal gut microbiome.

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

10.3410/f.1001228.374620 ◽

2006 ◽

Author(s):

Ken Wilson

Keyword(s):

Gut Microbiome ◽

Metagenomic Analysis

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Fecal Metaproteomics Reveals Reduced Gut Inflammation and Changed Microbial Metabolism Following Lifestyle-Induced Weight Loss

Biomolecules ◽

10.3390/biom11050726 ◽

2021 ◽

Vol 11 (5) ◽

pp. 726

Author(s):

Ronald Biemann ◽

Enrico Buß ◽

Dirk Benndorf ◽

Theresa Lehmann ◽

Kay Schallert ◽

...

Keyword(s):

Metabolic Syndrome ◽

Weight Loss ◽

Gut Microbiome ◽

Taxonomic Composition ◽

Low Grade ◽

Gut Inflammation ◽

Functional Changes ◽

Microbiome Composition ◽

Before And After ◽

Human Proteins

Gut microbiota-mediated inflammation promotes obesity-associated low-grade inflammation, which represents a hallmark of metabolic syndrome. To investigate if lifestyle-induced weight loss (WL) may modulate the gut microbiome composition and its interaction with the host on a functional level, we analyzed the fecal metaproteome of 33 individuals with metabolic syndrome in a longitudinal study before and after lifestyle-induced WL in a well-defined cohort. The 6-month WL intervention resulted in reduced BMI (−13.7%), improved insulin sensitivity (HOMA-IR, −46.1%), and reduced levels of circulating hsCRP (−39.9%), indicating metabolic syndrome reversal. The metaprotein spectra revealed a decrease of human proteins associated with gut inflammation. Taxonomic analysis revealed only minor changes in the bacterial composition with an increase of the families Desulfovibrionaceae, Leptospiraceae, Syntrophomonadaceae, Thermotogaceae and Verrucomicrobiaceae. Yet we detected an increased abundance of microbial metaprotein spectra that suggest an enhanced hydrolysis of complex carbohydrates. Hence, lifestyle-induced WL was associated with reduced gut inflammation and functional changes of human and microbial enzymes for carbohydrate hydrolysis while the taxonomic composition of the gut microbiome remained almost stable. The metaproteomics workflow has proven to be a suitable method for monitoring inflammatory changes in the fecal metaproteome.

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The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

10.1101/593301 ◽

2019 ◽

Author(s):

H. Soon Gweon ◽

Liam P. Shaw ◽

Jeremy Swann ◽

Nicola De Maio ◽

Manal AbuOun ◽

...

Keyword(s):

Data Processing ◽

Open Source ◽

Open Source Software ◽

River Sediment ◽

Taxonomic Composition ◽

Sequencing Depth ◽

Gene Content ◽

Metagenomic Data ◽

Software Pipeline ◽

Shotgun Metagenomics

ABSTRACTBackgroundShotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (∼200 million reads per sample). Alongside this, we cultured single-colony isolates ofEnterobacteriaceaefrom the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, ‘ResPipe’.ResultsTaxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve <1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike ofThermus thermophilusDNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment.ConclusionsSequencing depth and profiling method can critically affect the profiling of polymicrobial animal and environmental samples with shotgun metagenomics. Both sequencing of cultured isolates and shotgun metagenomics can recover substantial diversity that is not identified using the other methods. Particular consideration is required when inferring AMR gene content or presence by mapping metagenomic reads to a database. ResPipe, the open-source software pipeline we have developed, is freely available (https://gitlab.com/hsgweon/ResPipe).

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414 A randomized phase II study of systemic therapy plus WeiLeShu (WLS) versus systemic therapy alone in patients with metastatic colorectal cancer (mCRC)

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-sitc2021.414 ◽

2021 ◽

Vol 9 (Suppl 3) ◽

pp. A445-A445

Author(s):

Ruyi Zhang ◽

Xiaoxuan Tu ◽

Zhou Tong ◽

Hangyu Zhang ◽

Xudong Zhu ◽

...

Keyword(s):

Random Forest ◽

Systemic Therapy ◽

Gut Microbiome ◽

Clinical Benefit ◽

Metabolic Pathways ◽

Random Forest Model ◽

Metagenomic Analysis ◽

Dependent Manner ◽

Inflammatory Microenvironment ◽

Forest Model

BackgroundIn recent years, the role of inflammatory microenvironment induced by gut microbiome in the occurrence and development of CRC has received increased attention across a number of disciplines. WLS is a probiotics product consisted of with 6 billion live probiotics, mainly Lactobacillus helveticus and Bifidobacterium longum. To further explore the influence of gut microbiome in the anti-tumor efficacy of patients with mCRC, we conducted a randomized controlled trial (NCT04021589).MethodsPatients receiving corresponding systemic therapy were randomly included into the WLS-intervention and the control arms. Fecal samples were collected at baseline and about two months after treatment initiation. Gut microbiota composition was assessed using shotgun metagenomic sequencing. Best clinical response was dichotomized as partial remission (clinical benefit, CB) versus stable disease or disease progression (non-clinical benefit, NCB). Metagenomic analysis across patients with CB and NCB was conducted and random forest model training was employed to predict the efficacy of treatment.Abstract 414 Figure 1Metabolic pathways for differential enrichment. Metabolic pathways for differential enrichment of the gut microbiome genome in microbiota preparation group through KEGG analysisResultsA total of 40 patients with mCRC in two tertiary hospitals were enrolled. Dynamic metagenomic analysis indicated that during systemic treatment, the a diversity of the gut microbiome were all decreased in both arms. It has been reported that higher a diversity is associated with a better prognosis, while the degree of decline in WLS-intervention group was a relatively minor change. GO enrichment analysis of differential genes indicated a strong enrichment for genes related to lipid metabolism after WLS intervention (figure 1; p<0.01). Lipopolysaccharide (LPS) could regulate the accumulation of monocyte-like macrophages and promote the inflammatory microenvironment in a chemokine-dependent manner, while WLS intervention down-regulated genes related to its synthesis pathway, which may slow the development of CRC. Random forest model showed abundance of Desulfovibrio_vulgaris and Parvimonas_sp._oral_taxon_393 predominantly discriminated between CB and NCB. They were then used to construct a classifier, which achieved an AUC of 0.95 for efficacy prediction.ConclusionsThis prospective randomized pilot study provided insights for influence of the gut microbiome with probiotics in mCRC. WLS could maintain intestinal microecological balance of patients with mCRC by decreasing the degree of abundance of gut microbiome fall after chemotherapy and down-regulating lipopolysaccharide metabolism-related pathway. We established a novel classifier that accurately distinguished between patients with CB and NCB on systemic therapy.Trial RegistrationNCT04021589Ethics ApprovalThis study has been approved by Clinical Research Ethics Committee of the First Affiliated Hospital, College of Medicine, Zhejiang University. Acceptance number: IIT20200348A-R1

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Taxonomic composition and biodiversity of the gut microbiome from patients with irritable bowel syndrome, ulcerative colitis, and asthma

Vavilov Journal of Genetics and Breeding ◽

10.18699/vj21.100 ◽

2022 ◽

Vol 25 (8) ◽

pp. 864-873

Author(s):

A. Y. Tikunov ◽

A. N. Shvalov ◽

V. V. Morozov ◽

I. V. Babkin ◽

G. V. Seledtsova ◽

...

Keyword(s):

Ulcerative Colitis ◽

Irritable Bowel Syndrome ◽

Gut Microbiota ◽

Gut Microbiome ◽

Taxonomic Composition ◽

16S Rrna Genes ◽

Rrna Genes ◽

Taxonomic Structure ◽

Opportunistic Bacteria ◽

Irritable Bowel

To date, the association of an imbalance of the intestinal microbiota with various human diseases, including both diseases of the gastrointestinal tract and disorders of the immune system, has been shown. However, despite the huge amount of accumulated data, many key questions still remain unanswered. Given limited data on the composition of the gut microbiota in patients with ulcerative colitis (UC) and irritable bowel syndrome (IBS) from different parts of Siberia, as well as the lack of data on the gut microbiota of patients with bronchial asthma (BA), the aim of the study was to assess the biodiversity of the gut microbiota of patients with IBS, UC and BA in comparison with those of healthy volunteers (HV). In this study, a comparative assessment of the biodiversity and taxonomic structure of gut microbiome was conducted based on the sequencing of 16S rRNA genes obtained from fecal samples of patients with IBS, UC, BA and volunteers. Sequences of the Firmicutes and Bacteroidetes types dominated in all samples studied. The third most common in all samples were sequences of the Proteobacteria type, which contains pathogenic and opportunistic bacteria. Sequences of the Actinobacteria type were, on average, the fourth most common. The results showed the presence of dysbiosis in the samples from patients compared to the sample from HVs. The ratio of Firmicutes/Bacteroidetes was lower in the IBS and UC samples than in HV and higher the BA samples. In the samples from patients with intestinal diseases (IBS and UC), an increase in the proportion of sequences of the Bacteroidetes type and a decrease in the proportion of sequences of the Clostridia class, as well as the Ruminococcaceae, but not Erysipelotrichaceae family, were found. The IBS, UC, and BA samples had signif icantly more Proteobacteria sequences, including Methylobacterium, Sphingomonas, Parasutterella, Halomonas, Vibrio, as well as Escherichia spp. and Shigella spp. In the gut microbiota of adults with BA, a decrease in the proportion of Roseburia, Lachnospira, Veillonella sequences was detected, but the share of Faecalibacterium and Lactobacillus sequences was the same as in healthy individuals. A signif icant increase in the proportion of Halomonas and Vibrio sequences in the gut microbiota in patients with BA has been described for the f irst time.

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StrainPro – a highly accurate Metagenomic strain-level profiling tool

10.1101/807149 ◽

2019 ◽

Author(s):

Hsin-Nan Lin ◽

Yaw-Ling Lin ◽

Wen-Lian Hsu

Keyword(s):

Microbial Community ◽

Relative Abundance ◽

Taxonomic Diversity ◽

Evaluation Study ◽

Taxonomic Composition ◽

Strain Level ◽

Metagenomic Analysis ◽

Reference Database ◽

Analysis Tool ◽

Analysis Tools

ABSTRACTCharacterizing the taxonomic diversity of a microbial community is very important to understand the roles of microorganisms. Next generation sequencing (NGS) provides great potential for investigation of a microbial community and leads to Metagenomic studies. NGS generates DNA fragment sequences directly from microorganism samples, and it requires analysis tools to identify microbial species (or taxonomic composition) and estimate their relative abundance in the studied community. However, only a few tools could achieve strain-level identification and most tools estimate the microbial abundances simply according to the read counts. An evaluation study on metagenomic analysis tools concludes that the predicted abundance differed significantly from the true abundance. In this study, we present StrainPro, a novel metagenomic analysis tool which is highly accurate both at characterizing microorganisms at strain-level and estimating their relative abundances. A unique feature of StrainPro is it identifies representative sequence segments from reference genomes. We generate three simulated datasets using known strain sequences and another three simulated datasets using unknown strain sequences. We compare the performance of StrainPro with seven existing tools. The results show that StrainPro not only identifies metagenomes with high precision and recall, but it is also highly robust even when the metagenomes are not included in the reference database. Moreover, StrainPro estimates the relative abundance with high accuracy. We demonstrate that there is a strong positive linear relationship between observed and predicted abundances.

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