Yaobitong capsules reshape and rebalance the gut microbiota and metabolites of arthritic rats: An integrated study of microbiome and fecal metabolomics analysis

Abstract Background: The COVID-19 pandemic is spreading globally with high disparity in the susceptibility of the disease severity. Identification of the key underlying factors for this disparity is highly warranted. Results: Here we describe constructing a proteomic risk score (PRS) based on 20 blood proteomic biomarkers which related to the progression to severe COVID-19. Among COVID-19 patients, per 10% increment in the PRS was associated with a 57% higher risk of progressing to clinically severe phase (RR=1.57; 95% CI, 1.35-1.82). We demonstrate that in our own cohort of 990 individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discovered that a core set of gut microbiota could accurately predict the blood proteomic biomarkers of COVID-19 using a machine learning model. The core OTU-predicted PRS had a significant correlation with actual PRS both cross-sectionally (n=132, p<0.001) and prospectively (n=169, p<0.05). Most of the core OTUs were highly correlated with proinflammatory cytokines. Fecal metabolomics analysis suggested potential amino acid-related pathways linking the above core gut microbiota to inflammation.Conclusions: Our study suggests that gut microbiota may underlie the predisposition of healthy individuals to COVID-19-sensitive proteomic biomarkers.

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Advances in Research on Diabetes by Human Nutriomics

International Journal of Molecular Sciences ◽

10.3390/ijms20215375 ◽

2019 ◽

Vol 20 (21) ◽

pp. 5375

Author(s):

Xinmin Ren ◽

Xiangdong Li

Keyword(s):

Diabetes Mellitus ◽

Amino Acids ◽

Gut Microbiota ◽

New Targets ◽

Nutritional Metabolomics ◽

Pathogenic Factors ◽

Nutrient Analyses ◽

Dietary Strategies ◽

Prevalence Of Diabetes Mellitus ◽

Metabolomics Analysis

The incidence and prevalence of diabetes mellitus (DM) have increased rapidly worldwide over the last two decades. Because the pathogenic factors of DM are heterogeneous, determining clinically effective treatments for DM patients is difficult. Applying various nutrient analyses has yielded new insight and potential treatments for DM patients. In this review, we summarized the omics analysis methods, including nutrigenomics, nutritional-metabolomics, and foodomics. The list of the new targets of SNPs, genes, proteins, and gut microbiota associated with DM has been obtained by the analysis of nutrigenomics and microbiomics within last few years, which provides a reference for the diagnosis of DM. The use of nutrient metabolomics analysis can obtain new targets of amino acids, lipids, and metal elements, which provides a reference for the treatment of DM. Foodomics analysis can provide targeted dietary strategies for DM patients. This review summarizes the DM-associated molecular biomarkers in current applied omics analyses and may provide guidance for diagnosing and treating DM.

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Pulmonary fibrosis alters gut microbiota and associated metabolites in mice: An integrated 16S and metabolomics analysis

Life Sciences ◽

10.1016/j.lfs.2020.118616 ◽

2021 ◽

Vol 264 ◽

pp. 118616

Author(s):

Gen-cheng Gong ◽

Sheng-ren Song ◽

Jin Su

Keyword(s):

Pulmonary Fibrosis ◽

Gut Microbiota ◽

Metabolomics Analysis

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Longitudinal effects of antibiotics and fecal transplant on lemur gut microbiota structure, associations, and resistomes

10.1101/2020.11.11.378349 ◽

2020 ◽

Author(s):

Sally L. Bornbusch ◽

Rachel L. Harris ◽

Nicholas M. Grebe ◽

Kimberly Roche ◽

Kristin Dimac-Stohl ◽

...

Keyword(s):

Antibiotic Resistance ◽

Gut Microbiota ◽

Antibiotic Resistance Genes ◽

Microbial Consortia ◽

Negative Consequences ◽

Fecal Transplant ◽

Negative Effects ◽

Beneficial Effects ◽

Integrated Study

AbstractAntibiotics alter the diversity, structure, and dynamics of host-associated microbial consortia, including via development of antibiotic resistance; however, patterns of recovery from dysbiosis and methods to mitigate negative effects, remain poorly understood. We applied an ecological framework via long-term, integrated study of community structure, across scales, to improve understanding of host-microbe symbiosis during dysbiosis and recovery. We experimentally administered a broad-spectrum antibiotic alone or with subsequent fecal transfaunation to healthy, male ring-tailed lemurs (Lemur catta) and longitudinally tracked the diversity, composition, associations, and resistomes of their gut microbiota. Whereas microbial diversity recovered rapidly in lemurs, antibiotics caused long-term instability in community composition – effects that were attenuated by fecal transfaunation. Antibiotic resistance genes, which were universally present, including in treatment-naïve subjects, increased during and persisted after antibiotic treatment. Long-term, integrated study post antibiotic-induced dysbiosis revealed differential, metric-dependent evidence of recovery, beneficial effects of fecal transfaunation, and negative consequences to lemur resistomes.

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