Paul Bobby
Department of Bioinformatics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
F1000Res. 2023 Sep 1;11:1530. doi: 10.12688/f1000research.128320.3. eCollection 2022.
Microscopic, biochemical, molecular, and computer-based approaches are extensively used to identify and classify bacterial populations. Advances in DNA sequencing and bioinformatics workflows have facilitated sophisticated genome-based methods for microbial taxonomy although sequencing of the 16S rRNA gene is widely employed to identify and classify bacterial communities as a cost-effective and single-gene approach. However, the 16S rRNA sequence-based species identification accuracy is limited because of the occurrence of multiple copies of the 16S rRNA gene and higher sequence identity between closely related species. The availability of the genomes of several bacterial species provided an opportunity to develop comprehensive species-specific 16S rRNA reference libraries. Sequences of the 16S rRNA genes were retrieved from the whole genomes available in the Genome databases. With defined criteria, four 16S rRNA gene copy variants were concatenated to develop a species-specific reference library. The sequence similarity search was performed with a web-based BLAST program, and MEGA software was used to construct the phylogenetic tree. Using this approach, species-specific 16S rRNA gene libraries were developed for four closely related species ( , , , and ). Sequence similarity and phylogenetic analysis using concatenated 16S rRNA copies yielded better resolution than single gene copy approaches. The approach is very effective in classifying genetically closely related bacterial species and may reduce misclassification of bacterial species and genome assemblies.
微观、生化、分子以及基于计算机的方法被广泛用于识别和分类细菌群体。尽管16S rRNA基因测序作为一种经济高效的单基因方法被广泛用于识别和分类细菌群落,但DNA测序和生物信息学工作流程的进展推动了基于基因组的复杂微生物分类方法的发展。然而,由于16S rRNA基因存在多个拷贝以及亲缘关系密切的物种之间序列同一性较高,基于16S rRNA序列的物种识别准确性受到限制。几种细菌物种基因组的可得性为开发全面的物种特异性16S rRNA参考文库提供了机会。从基因组数据库中可用的全基因组中检索16S rRNA基因的序列。根据既定标准,将四个16S rRNA基因拷贝变体串联起来,以开发一个物种特异性参考文库。使用基于网络的BLAST程序进行序列相似性搜索,并使用MEGA软件构建系统发育树。利用这种方法,为四个亲缘关系密切的物种( 、 、 和 )开发了物种特异性16S rRNA基因文库。使用串联的16S rRNA拷贝进行序列相似性和系统发育分析比单基因拷贝方法具有更高的分辨率。该方法在对遗传关系密切的细菌物种进行分类方面非常有效,并且可能减少细菌物种和基因组组装的错误分类。