Database size positively correlates with the loss of species-level taxonomic resolution for the 16S rRNA and other prokaryotic marker genes

被引:0
|
作者
Commichaux, Seth [1 ]
Luan, Tu [2 ,3 ]
Muralidharan, Harihara Subrahmaniam [2 ,3 ]
Pop, Mihai [2 ,3 ]
机构
[1] Food & Drug Adm, Ctr Food Safety & Nutr, Laurel, MD 20708 USA
[2] Univ Maryland, Dept Comp Sci, College Pk, MD USA
[3] Univ Maryland, Ctr Bioinformat & Computat Biol, College Pk, MD USA
基金
美国国家卫生研究院;
关键词
CATALOG;
D O I
10.1371/journal.pcbi.1012343
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
For decades, the 16S rRNA gene has been used to taxonomically classify prokaryotic species and to taxonomically profile microbial communities. However, the 16S rRNA gene has been criticized for being too conserved to differentiate between distinct species. We argue that the inability to differentiate between species is not a unique feature of the 16S rRNA gene. Rather, we observe the gradual loss of species-level resolution for other nearly-universal prokaryotic marker genes as the number of gene sequences increases in reference databases. This trend was strongly correlated with how represented a taxonomic group was in the database and indicates that, at the gene-level, the boundaries between many species might be fuzzy. Through our study, we argue that any approach that relies on a single marker to distinguish bacterial taxa is fraught even if some markers appear to be discriminative in current databases.
引用
收藏
页数:12
相关论文
共 44 条
  • [1] A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy
    Xiang Gao
    Huaiying Lin
    Kashi Revanna
    Qunfeng Dong
    BMC Bioinformatics, 18
  • [2] A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy
    Gao, Xiang
    Lin, Huaiying
    Revanna, Kashi
    Dong, Qunfeng
    BMC BIOINFORMATICS, 2017, 18
  • [3] Species-Level Resolution of Female Bladder Microbiota from 16S rRNA Amplicon Sequencing
    Hoffman, Carter
    Siddiqui, Nazema Y.
    Fields, Ian
    Gregory, W. Thomas
    Simon, Holly M.
    Mooney, Michael A.
    Wolfe, Alan J.
    Karstensa, Lisa
    MSYSTEMS, 2021, 6 (05)
  • [4] NanoCLUST: a species-level analysis of 16S rRNA nanopore sequencing data
    Rodriguez-Perez, Hector
    Ciuffreda, Laura
    Flores, Carlos
    BIOINFORMATICS, 2021, 37 (11) : 1600 - 1601
  • [5] MIMt: a curated 16S rRNA reference database with less redundancy and higher accuracy at species-level identification
    Cabezas, M. Pilar
    Fonseca, Nuno A.
    Munoz-Merida, Antonio
    ENVIRONMENTAL MICROBIOME, 2024, 19 (01)
  • [6] Data-Driven Modeling for Species-Level Taxonomic Assignment From 16S rRNA: Application to Human Microbiomes
    Gwak, Ho-Jin
    Rho, Mina
    FRONTIERS IN MICROBIOLOGY, 2020, 11
  • [7] Species-level resolution of 16S rRNA gene amplicons sequenced through the MinION™ portable nanopore sequencer
    Benitez-Paez, Alfonso
    Portune, Kevin J.
    Sanz, Yolanda
    GIGASCIENCE, 2016, 5
  • [8] Long-read MinION™ sequencing of 16S and 16S-ITS-23S rRNA genes provides species-level resolution of Lactobacillaceae in mixed communities
    Olivier, Sandra A.
    Bull, Michelle K.
    Strube, Mikael Lenz
    Murphy, Robert
    Ross, Tom
    Bowman, John P.
    Chapman, Belinda
    FRONTIERS IN MICROBIOLOGY, 2023, 14
  • [9] rRNA operon improves species-level classification of bacteria and microbial community analysis compared to 16S rRNA
    Won, Sohyoung
    Cho, Seoae
    Kim, Heebal
    MICROBIOLOGY SPECTRUM, 2024,
  • [10] Improving Species Level-taxonomic Assignment from 16S rRNA Sequencing Technologies
    Bars-Cortina, David
    Moratalla-Navarro, Ferran
    Garcia-Serrano, Ainhoa
    Mach, Nuria
    Riobo-Mayo, Lois
    Vea-Barbany, Jordi
    Rius-Sansalvador, Blanca
    Murcia, Silvia
    Obon-Santacana, Mireia
    Moreno, Victor
    CURRENT PROTOCOLS, 2023, 3 (11):