Effects of neutrophils peptide-1 transgenic Chlorella ellipsoidea on the gut microbiota of male Sprague–Dawley rats, as revealed by high-throughput 16S rRNA sequencing

A high-throughput 16S rRNA sequencing technology was applied to study changes of the intestinal microbiota in mice after the administration of cow and goat milk. We show a correlation between the gut microbiota and the nutrients in milk.

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Antibiotic-Induced Dysbiosis of Microbiota Promotes Chicken Lipogenesis by Altering Metabolomics in the Cecum

Metabolites ◽

10.3390/metabo11080487 ◽

2021 ◽

Vol 11 (8) ◽

pp. 487

Author(s):

Tao Zhang ◽

Hao Ding ◽

Lan Chen ◽

Yueyue Lin ◽

Yongshuang Gong ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

High Performance ◽

Fat Deposition ◽

16S Rrna Sequencing ◽

Oral Antibiotics ◽

Ms Analysis ◽

Rrna Sequencing ◽

Cecal Microbiota ◽

Metabolite Network

Elucidation of the mechanism of lipogenesis and fat deposition is essential for controlling excessive fat deposition in chicken. Studies have shown that gut microbiota plays an important role in regulating host lipogenesis and lipid metabolism. However, the function of gut microbiota in the lipogenesis of chicken and their relevant mechanisms are poorly understood. In the present study, the gut microbiota of chicken was depleted by oral antibiotics. Changes in cecal microbiota and metabolomics were detected by 16S rRNA sequencing and ultra-high performance liquid chromatography coupled with MS/MS (UHPLC–MS/MS) analysis. The correlation between antibiotic-induced dysbiosis of gut microbiota and metabolites and lipogenesis were analysed. We found that oral antibiotics significantly promoted the lipogenesis of chicken. 16S rRNA sequencing indicated that oral antibiotics significantly reduced the diversity and richness and caused dysbiosis of gut microbiota. Specifically, the abundance of Proteobacteria was increased considerably while the abundances of Bacteroidetes and Firmicutes were significantly decreased. At the genus level, the abundances of genera Escherichia-Shigella and Klebsiella were significantly increased while the abundances of 12 genera were significantly decreased, including Bacteroides. UHPLC-MS/MS analysis showed that antibiotic-induced dysbiosis of gut microbiota significantly altered cecal metabolomics and caused declines in abundance of 799 metabolites and increases in abundance of 945 metabolites. Microbiota-metabolite network revealed significant correlations between 4 differential phyla and 244 differential metabolites as well as 15 differential genera and 304 differential metabolites. Three metabolites of l-glutamic acid, pantothenate acid and N-acetyl-l-aspartic acid were identified as potential metabolites that link gut microbiota and lipogenesis in chicken. In conclusion, our results showed that antibiotic-induced dysbiosis of gut microbiota promotes lipogenesis of chicken by altering relevant metabolomics. The efforts in this study laid a basis for further study of the mechanisms that gut microbiota regulates lipogenesis and fat deposition of chicken.

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Probiotic supplements alleviate gestational diabetes mellitus by restoring the diversity of gut microbiota: a study based on 16S rRNA sequencing

The Journal of Microbiology ◽

10.1007/s12275-021-1094-8 ◽

2021 ◽

Author(s):

Qing-Xiang Zheng ◽

Xiu-Min Jiang ◽

Hai-Wei Wang ◽

Li Ge ◽

Yu-Ting Lai ◽

...

Keyword(s):

Diabetes Mellitus ◽

16S Rrna ◽

Gestational Diabetes ◽

Gut Microbiota ◽

Gestational Diabetes Mellitus ◽

16S Rrna Sequencing ◽

Rrna Sequencing

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Berberine Improves the Symptoms of DHEA-Induced PCOS Rats by Regulating Gut Microbiotas and Metabolites

Gynecologic and Obstetric Investigation ◽

10.1159/000518040 ◽

2021 ◽

pp. 1-10

Author(s):

Hao-Ran Shen ◽

Xiao Xu ◽

Dan Ye ◽

Xue-Lian Li

Keyword(s):

Insulin Resistance ◽

16S Rrna ◽

Polycystic Ovary ◽

Pathological Condition ◽

Enrichment Analysis ◽

16S Rrna Sequencing ◽

Model Assessment ◽

Metabolomic Analysis ◽

Sprague Dawley ◽

Rrna Sequencing

Objectives: The aim of this study was to investigate the effects of berberine on polycystic ovary syndrome (PCOS) with insulin resistance (IR). Design: This study performed 16S rRNA sequencing and metabolomic analysis on dehydroepiandrosterone (DHEA)-induced PCOS rats treated with berberine, focusing on the improvement of PCOS-IR by modifying gut microbiota and metabolism. Methods: Forty-two female Sprague Dawley rats were randomly divided into 4 experimental groups of 8 rats each (PCOS + HFD, PCOS + HFD + BBR, NCD + PCOS, and NCD + PCOS + BBR groups). Homeostasis model assessment of insulin resistance (HOMA-IR) index-related indicators and hormone level in serum were analyzed. 16S rRNA sequencing and metabolomic analysis were performed on DHEA-induced PCOS rats treated with berberine. In addition, the differential microbiotas and metabolites were screened. Also, enrichment analysis was carried out on the differential metabolites. Finally, we constructed a correlation network to analyze the correlation between differential microbiotas and metabolites. Results: Firmicutes and Bacteroidetes were changed at the phylum level, and Romboutsia, Bacteroides, and Clostridium_sensu_stricto_1 were changed at the genus level after berberine treatment. In addition, a total of 26 differential operational taxonomic units and 3 metabolites (glutamine, unsaturated acids [CH = CH], and glucose) between 2 groups were obtained. Moreover, these metabolites were mainly involved in type 2 diabetes mellitus, 2-component system, and ABC transporter Kyoto Encyclopedia of Genes and Genomes pathways. And, 3 microbiotas (Lachnospiraceae_NC2004_group, Flavonifractor, and Parasutterella) were regulated by glucose and glutamine. Limitations: The sample size involved in this study is relatively small. In addition, relevant experiments need to be performed to verify the obtained results from this study, and in-depth functional studies are needed. Conclusions: Berberine is effective in improving the pathological condition in PCOS by regulating the gut microbiotas and metabolites. This study will provide evidence for therapeutic efforts to treat PCOS-IR using berberine.

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313 An oral decaherb formula suppressed Th2 inflammation and improved gut microbiota profile with 16S rRNA sequencing in mice model with atopic dermatitis

Journal of Investigative Dermatology ◽

10.1016/j.jid.2020.03.320 ◽

2020 ◽

Vol 140 (7) ◽

pp. S39

Author(s):

S.K. Loo ◽

H. Li ◽

Y. Xian ◽

J.C. Tsui ◽

S.K. Tusi ◽

...

Keyword(s):

Atopic Dermatitis ◽

16S Rrna ◽

Gut Microbiota ◽

16S Rrna Sequencing ◽

Mice Model ◽

Th2 Inflammation ◽

Rrna Sequencing

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Application of high-throughput 16S rRNA sequencing to identify fecal contamination sources and to complement the detection of fecal indicator bacteria in rural groundwater

Journal of Water and Health ◽

10.2166/wh.2019.295 ◽

2019 ◽

Vol 17 (3) ◽

pp. 393-403 ◽

Cited By ~ 5

Author(s):

Paul Naphtali ◽

Mahi M. Mohiuddin ◽

Athanasios Paschos ◽

Herb E. Schellhorn

Keyword(s):

16S Rrna ◽

High Throughput ◽

Fecal Indicator Bacteria ◽

Fecal Contamination ◽

Indicator Bacteria ◽

16S Rrna Sequencing ◽

Septic Tank ◽

Fecal Indicator ◽

Contamination Sources ◽

Rrna Sequencing

Abstract Residents in rural communities across Canada collect potable water from aquifers. Fecal contaminants from sewage and agricultural runoffs can penetrate aquifers, posing a public health risk. Standard methods for detecting fecal contamination test for fecal indicator bacteria (FIB), but the presence of these do not identify sources of contamination. In contrast, DNA-based diagnostic tools can achieve this important objective. We employed quantitative polymerase chain reaction (qPCR) and high-throughput DNA sequencing to trace fecal contamination sources in Wainfleet, a rural Ontario township that has been under the longest active boil water advisory in Canada due to FIB contamination in groundwater wells. Using traditional methods, we identified FIBs indicating persistent fecal pollution in well waters. We used 16S rRNA sequencing to profile groundwater microbial communities and identified Campylobacteraceae as a fecal contamination DNA marker in septic tank effluents (STEs). We also identified Turicibacter and Gallicola as a potential cow and chicken fecal contamination marker, respectively. Using human specific Bacteroidales markers, we identified leaking septic tanks as the likely primary fecal contamination source in some of Wainfleet's groundwater. Overall, the results support the use of sequencing-based methods to augment traditional water quality testing methods and help end-users assess fecal contamination levels and identify point and non-point pollution sources. This article has been made Open Access thanks to the generous support of a global network of libraries as part of the Knowledge Unlatched Select initiative.

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