16S rRNA Gene Sequencing Reveals Altered Composition of Gut Microbiota in Postoperative Individuals With Renal Stones

2021 ◽  
Author(s):  
Qiong Deng ◽  
Zhu Wang ◽  
Jieyan Wang ◽  
Jianwen Zhang ◽  
Ying Zhang ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Eating Habits ◽  
Stone Formation ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Renal Stones ◽  
Renal Calculi ◽  
Rrna Gene ◽  
Recurrence Rates ◽  
Rrna Gene Sequencing

Abstract BackgroundRenal stones are a common urological disease with high prevalence and recurrence rates. Characterizing gut microbiome profiles of first-onset renal calculi patients, both before and after surgery, may provide valuable insights and identify potential biomarkers for the disease. MethodsWe explored the associations between the gut microbiome and renal stone formation using 16S ribosomal RNA (rRNA) gene sequencing. In brief, 20 patients were recruited, and information on health and eating habits within the previous 1-3 months was collected upon admission.ResultsA total of 493 OTUs were detected in 40 specimens, with an average of 67,888 ± 827 reads per sample. The results of OUT-based PLS-DA analysis showed significant differences between RS1 and RS2 groups, with a significantly higher level of OTU7 in the RS2 group. Taxonomy‑based comparisons of the gut microbiome showed differences in the flora composition, with the prevalence of Enterobacteriales, Enterobacteriaceae, Gammaproteobacteria, and Escherichia being higher in the RS2 group and the prevalence of Pseudomonadaceae, Pseudomonadales, and Pseudomonas being higher in the RS1 group.ConclusionsThese data strongly suggest that the gut microbiome affects kidney stone formation, and these findings may provide new insights for the prevention, diagnosis, and treatment of renal stones.

scholarly journals Correction: 16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0212474 ◽  
Author(s):  
Daniel E. Almonacid ◽  
Laurens Kraal ◽  
Francisco J. Ossandon ◽  
Yelena V. Budovskaya ◽  
Juan Pablo Cardenas ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gut Microbiome ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Reference Ranges ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Rrna Gene Sequencing

scholarly journals The Effect of Xuebijing on the Gut Microbiota and Metabolic of Heat 1 Stroke Rat 2

2021 ◽  
Author(s):  
Qiang wen ◽  
Xuan He ◽  
Yu Shao ◽  
Lun Peng ◽  
Li Zhao ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gut Microbiome ◽  
Heat Stroke ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Control Group ◽  
Rrna Gene ◽  
Metabolism Pathway ◽  
Rrna Gene Sequencing

Abstract The goal of the present study was to evaluate the fecal microbiome and serum metabolites in 16 Xuebijing (XBJ)-injected rats after heat stroke using 16S rRNA gene sequencing and gas chromatography-mass spectrometry (GC-MS) metabolomics. Eighteen rats were divided into the control group (CON), heat stroke group (HS), and XBJ group. The 16S rRNA gene sequencing results revealed that the abundance of Bacteroidetes was overrepresented in the XBJ group compared to the HS group, while Actinobacteria was underrepresented. Metabolomic profiling showed that the pyrimidine metabolism pathway, pentose phosphate pathway, and glycerophospholipid metabolism pathway were upregulated in the XBJ group compared to the HS group. Taken together, these results demonstrated that heat stroke not only altered the gut microbiome community structure of rats but also greatly affected metabolic functions, leading to gut microbiome toxicity.

scholarly journals Mouse Vendor Influence on the Bacterial and Viral Gut Composition Exceeds the Effect of Diet

Viruses ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 435 ◽  
Author(s):  
Torben Sølbeck Rasmussen ◽  
Liv de Vries ◽  
Witold Kot ◽  
Lars Hestbjerg Hansen ◽  
Josué L. Castro-Mejía ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
High Fat Diet ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Mouse Strains ◽  
Rrna Gene ◽  
High Fat ◽  
Low Fat Diet ◽  
Viral Community ◽  
Rrna Gene Sequencing

Often physiological studies using mice from one vendor show different outcome when being reproduced using mice from another vendor. These divergent phenotypes between similar mouse strains from different vendors have been assigned to differences in the gut microbiome. During recent years, evidence has mounted that the gut viral community plays a key role in shaping the gut microbiome and may thus also influence mouse phenotype. However, to date inter-vendor variation in the murine gut virome has not been studied. Using a metavirome approach, combined with 16S rRNA gene sequencing, we here compare the composition of the viral and bacterial gut community of C57BL/6N mice from three different vendors exposed to either a chow-based low-fat diet or high-fat diet. Interestingly, both the bacterial and the viral component of the gut community differed significantly between vendors. The different diets also strongly influenced both the viral and bacterial gut community, but surprisingly the effect of vendor exceeded the effect of diet. In conclusion, the vendor effect is substantial not only on the gut bacterial community but also strongly influences viral community composition. Given the effect of GM on mice phenotype, this is essential to consider for increasing reproducibility of mouse studies.

scholarly journals 16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome

PLoS ONE ◽  
2017 ◽  
Vol 12 (5) ◽  
pp. e0176555 ◽  
Author(s):  
Daniel E. Almonacid ◽  
Laurens Kraal ◽  
Francisco J. Ossandon ◽  
Yelena V. Budovskaya ◽  
Juan Pablo Cardenas ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gut Microbiome ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Reference Ranges ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Rrna Gene Sequencing

scholarly journals Mouse vendor influence on the bacterial and viral gut composition exceeds the effect of diet

2019 ◽  
Author(s):  
Torben Sølbeck Rasmussen ◽  
Liv de Vries ◽  
Witold Kot ◽  
Lars Hestbjerg Hansen ◽  
Josué L. Castro-Mejía ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
High Fat Diet ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Mouse Strains ◽  
Rrna Gene ◽  
High Fat ◽  
Low Fat Diet ◽  
Viral Community ◽  
Rrna Gene Sequencing

AbstractOften physiological studiess using mice from one vendor show different outcome when being reproduced using mice from another vendor. These divergent phenotypes between similar mouse strains from different vendors have been assigned to differences in the gut microbiome. During recent years, evidence has mounted that the gut viral community plays a key role in shaping the gut microbiome and may thus also influence mouse phenotype. However, to date inter-vendor variation in the murine gut virome has not been studied. Using a metavirome approach, combined with 16S rRNA gene sequencing, we here compare the composition of the viral and bacterial gut community of C57BL/6N mice from three different vendors exposed to either a chow-based low-fat diet or high-fat diet. Interestingly, both the bacterial and the viral component of the gut community differed significantly between vendors. The different diets also strongly influenced both the viral and bacterial gut community, but surprisingly the effect of vendor exceeded the effect of diet. In conclusion, the vendor effect is substantial on not only the gut bacterial community, but also strongly influences viral community composition. Given the effect of GM on mice phenotype this is essential to consider, for increasing reproducibility of mouse studies.

scholarly journals Influence of fecal collection conditions and 16S rRNA gene sequencing protocols at two centers on human gut microbiota analysis

2017 ◽  
Author(s):  
Jocelyn Sietsma Penington ◽  
Megan A S Penno ◽  
Katrina M Ngui ◽  
Nadim J Ajami ◽  
Alexandra J Roth-Schulze ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gut Microbiome ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Multicenter Studies ◽  
16S Rrna Analysis ◽  
The Usa ◽  
Rrna Gene Sequencing

AbstractBackgroundTo optimise fecal sampling and analysis yielding reproducible microbiome data, and gain further insight into sources of its variation, we compared different collection conditions and 16S rRNA gene sequencing protocols in two centers. Fecal samples were collected on three sequential days from six healthy adults and placed in commercial collection tubes (OMNIgeneGut OMR-200) at room temperature or in sterile 5 ml screw-top tubes in a home fridge or home freezer for 6-24 h, before transfer at 4°C to the laboratory and storage at - 80°C within 24 hours. Replicate samples were shipped on dry ice to centers in Australia and the USA for DNA extraction and sequencing of the V4 region of the 16S rRNA gene, using different PCR protocols. Sequences were analysed with the QIIME pipeline and Greengenes database at the Australian center and with an in-house pipeline and SILVA database at the USA center.ResultsVariation in gut microbiome composition and diversity was dominated by differences between individuals. Minor differences in the abundance of taxa were found between collection-processing methods and day of collection. Larger differences were evident between the two centers, including in the relative abundances of genus Akkermansia, in phylum Verrucomicrobiales, and Bifidobacteria in Actinobacteria.ConclusionsCollection with storage and transport at 4°C within 24 h is adequate for 16S rRNA analysis of the gut microbiome. However, variation between sequencing centers suggests that cohort samples should be sequenced by the same method in one center. Differences in handling, shipping and methods of PCR gene amplification and sequence analysis in different centers introduce variation in ways that are not fully understood. These findings are particularly relevant as microbiome studies shift towards larger population-based and multicenter studies.

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