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

被引:335
作者
Durazzi, Francesco [1 ]
Sala, Claudia [1 ]
Castellani, Gastone [2 ]
Manfreda, Gerardo [3 ]
Remondini, Daniel [1 ]
De Cesare, Alessandra [4 ]
机构
[1] Univ Bologna, Dept Phys & Astron, I-40127 Bologna, Italy
[2] Univ Bologna, Dept Expt Diagnost & Specialty Med, I-40127 Bologna, Italy
[3] Univ Bologna, Dept Agr & Food Sci, I-40064 Ozzano Dellemilia, Italy
[4] Univ Bologna, Dept Vet Med Sci, I-40064 Ozzano Dellemilia, Italy
基金
欧盟地平线“2020”;
关键词
METAGENOMICS; HEALTH;
D O I
10.1038/s41598-021-82726-y
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In 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.
引用
收藏
页数:10
相关论文
共 27 条
[1]  
[Anonymous], 2015, R package
[2]  
[Anonymous], 2013, 16S METAGENOMIC SEQU, P1
[3]   Exact sequence variants should replace operational taxonomic units in marker-gene data analysis [J].
Callahan, Benjamin J. ;
McMurdie, Paul J. ;
Holmes, Susan P. .
ISME JOURNAL, 2017, 11 (12) :2639-2643
[4]  
Chistoserdova L, 2010, BIOTECHNOL GENET ENG, V26, P335
[5]   Clinical metagenomics [J].
Chiu, Charles Y. ;
Miller, Steven A. .
NATURE REVIEWS GENETICS, 2019, 20 (06) :341-355
[6]   Metagenomic Analysis of Chicken Gut Microbiota for Improving Metabolism and Health of Chickens - A Review [J].
Choi, Ki Young ;
Lee, Tae Kwon ;
Sul, Woo Jun .
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES, 2015, 28 (09) :1217-1225
[7]  
Colwell R.K, 2009, PRINCET GUIDE ECOL, P257, DOI DOI 10.1515/9781400833023.257
[8]   Effect of Lactobacillus acidophilus D2/CSL (CECT 4529) supplementation in drinking water on chicken crop and caeca microbiome [J].
De Cesare, Alessandra ;
Sala, Claudia ;
Castellani, Gastone ;
Astolfi, Annalisa ;
Indio, Valentina ;
Giardini, Alberto ;
Manfreda, Gerardo .
PLOS ONE, 2020, 15 (01)
[9]   Impact of a probiotic-based cleaning product on the microbiological profile of broiler litters and chicken caeca microbiota [J].
De Cesare, Alessandra ;
Caselli, Elisabetta ;
Lucchi, Alex ;
Sala, Claudia ;
Parisi, Antonio ;
Manfreda, Gerardo ;
Mazzacane, Sante .
POULTRY SCIENCE, 2019, 98 (09) :3602-3610
[10]   Contamination in Low Microbial Biomass Microbiome Studies: Issues and Recommendations [J].
Eisenhofer, Raphael ;
Minich, Jeremiah J. ;
Marotz, Clarisse ;
Cooper, Alan ;
Knight, Rob ;
Weyrich, Laura S. .
TRENDS IN MICROBIOLOGY, 2019, 27 (02) :105-117