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

2006 ◽  
Author(s):  
Ken Wilson
Keyword(s):  
Gut Microbiome ◽  
Metagenomic Analysis

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

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

scholarly journals Erratum: Corrigendum: Unique Features of Ethnic Mongolian Gut Microbiome revealed by metagenomic analysis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Wenjun Liu ◽  
Jiachao Zhang ◽  
Chunyan Wu ◽  
Shunfeng Cai ◽  
Weiqiang Huang ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Metagenomic Analysis

Metagenomic Analysis of The Gut Microbiome of Term Infants In The United States Reveals Widespread Dysbiosis

2021 ◽  
Author(s):  
Giorgio Casaburi ◽  
Rebbeca Duar ◽  
Heather K. Brown ◽  
Ryan Mitchell ◽  
Sufyan Kazi ◽  
...  
Keyword(s):  
United States ◽  
Gut Microbiome ◽  
The United States ◽  
Metagenomic Analysis ◽  
Term Infants

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

Acta Naturae ◽  
2013 ◽  
Vol 5 (3) ◽  
pp. 116-125 ◽  
Author(s):  
A. V. Mardanov ◽  
M. M. Babykin ◽  
A. V. Beletsky ◽  
A. I. Grigoriev ◽  
V. V. Zinchenko ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Taxonomic Composition ◽  
Functional Gene ◽  
Stress Factors ◽  
Gene Content ◽  
Metagenomic Analysis ◽  
Stable Gene ◽  
Individual Response ◽  
Negative Consequences ◽  
Dynamic Changes

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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