scholarly journals Comparison between 16S rRNA and shotgun sequencing data for the taxonomic characterization of the gut microbiota

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Francesco Durazzi ◽  
Claudia Sala ◽  
Gastone Castellani ◽  
Gerardo Manfreda ◽  
Daniel Remondini ◽  
...  

AbstractIn this paper we compared taxonomic results obtained by metataxonomics (16S rRNA gene sequencing) and metagenomics (whole shotgun metagenomic sequencing) to investigate their reliability for bacteria profiling, studying the chicken gut as a model system. The experimental conditions included two compartments of gastrointestinal tracts and two sampling times. We compared the relative abundance distributions obtained with the two sequencing strategies and then tested their capability to distinguish the experimental conditions. The results showed that 16S rRNA gene sequencing detects only part of the gut microbiota community revealed by shotgun sequencing. Specifically, when a sufficient number of reads is available, Shotgun sequencing has more power to identify less abundant taxa than 16S sequencing. Finally, we showed that the less abundant genera detected only by shotgun sequencing are biologically meaningful, being able to discriminate between the experimental conditions as much as the more abundant genera detected by both sequencing strategies.

2021 ◽  
Author(s):  
Pei-Qin Cao ◽  
Xiu-Ping Li ◽  
Jian Ou-Yang ◽  
Rong-Gang Jiang ◽  
Fang-Fang Huang ◽  
...  

We evaluated the effects of yellow tea extract on relieving constipation induced by loperamide and evaluated the changes of gut microbiota based on 16S rRNA gene sequencing.


Urolithiasis ◽  
2018 ◽  
Vol 46 (6) ◽  
pp. 503-514 ◽  
Author(s):  
Ruiqiang Tang ◽  
Yonghua Jiang ◽  
Aihua Tan ◽  
Juan Ye ◽  
Xiaoying Xian ◽  
...  

2021 ◽  
Author(s):  
Lalhaba Oinam ◽  
Fumi Minoshima ◽  
Hiroaki Tateno

Background: There has been immense interest in studying the relationship between the gut microbiota and human health. Bacterial glycans modulate the cross talk between the gut microbiota and its host. However, little is known about these glycans because of the lack of appropriate technology to study them. Methods: We previously developed a sequencing-based glycan profiling method called Glycan-seq, which is based on the use of 39 DNA-barcoded lectins. In this study, we applied this technology to analyze the glycome of the intact gut microbiota of mice. Fecal microbiota was incubated with 39 DNA-barcoded lectins exposed to UV, and the number of released DNA barcodes were counted by next-generation sequencing to obtain a signal for each lectin bound to the microbiota. In parallel, the bacterial composition of the gut microbiota was analyzed by 16S rRNA gene sequencing. Finally, we performed a lectin pull-down experiment followed by 16S rRNA gene sequencing to identify lectin-reactive bacteria. Results: The evaluation of cultured gram-positive (Deinococcus radiodurans) and gram-negative (Escherichia coli) bacteria showed significantly distinct glycan profiles between these bacteria, which were selected and further analyzed by flow cytometry. The results of flow cytometry agreed well with those obtained by Glycan-seq, indicating that Glycan-seq can be used for bacterial glycomic analysis. We thus applied Glycan-seq to comparatively analyze the glycomes of young and old mice gut microbiotas. The glycomes of the young and old microbiotas had significantly distinct glycan profiles, which reflect the different bacterial compositions of young and old gut microbiotas based on 16S rRNA gene sequencing. Therefore, the difference in the glycomic profiles between young and old microbiotas may be due to their differing bacterial compositions. α2-6Sia-binders bound specifically to the young microbiota. Lectin pull-down followed by 16S rRNA gene sequencing of the young microbiota identified Lactobacillaceae as the most abundant bacterial family with glycans reacting with α2-6Sia-binders. Conclusion: The Glycan-seq system can, without any prior culturing and fluorescence labeling, reveal the glycomic profile of the intact bacterial gut microbiota. A combination of lectin pull-down and 16S rRNA gene sequencing can identify lectin-reactive bacteria.


BMC Genomics ◽  
2013 ◽  
Vol 14 (Suppl 5) ◽  
pp. S16 ◽  
Author(s):  
Suparna Mitra ◽  
Karin Förster-Fromme ◽  
Antje Damms-Machado ◽  
Tim Scheurenbrand ◽  
Saskia Biskup ◽  
...  

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