Thermo Fisher Scientific Baltics, V. A. Graičiūno str. 8, Vilnius 02241, Lithuania.
Institute of Biosciences, Life Sciences Center, Vilnius University, Saulėtekio al. 7, Vilnius 10257, Lithuania.
Microb Genom. 2021 Sep;7(9). doi: 10.1099/mgen.0.000624.
Sequence-based characterization of bacterial communities has long been a hostage of limitations of both 16S rRNA gene and whole metagenome sequencing. Neither approach is universally applicable, and the main efforts to resolve constraints have been devoted to improvement of computational prediction tools. Here, we present semi-targeted 16S rRNA sequencing (st16S-seq), a method designed for sequencing V1-V2 regions of the 16S rRNA gene along with the genomic locus upstream of the gene. By analysis of 13 570 bacterial genome assemblies, we show that genome-linked 16S rRNA sequencing is superior to individual hypervariable regions or full-length gene sequences in terms of classification accuracy and identification of gene copy numbers. Using mock communities and soil samples we experimentally validate st16S-seq and benchmark it against the established microbial classification techniques. We show that st16S-seq delivers accurate estimation of 16S rRNA gene copy numbers, enables taxonomic resolution at the species level and closely approximates community structures obtainable by whole metagenome sequencing.
基于序列的细菌群落特征分析长期以来一直受到 16S rRNA 基因和全宏基因组测序的限制。这两种方法都不是普遍适用的，解决限制的主要努力都集中在改进计算预测工具上。在这里，我们提出了半靶向 16S rRNA 测序（st16S-seq），这是一种设计用于测序 16S rRNA 基因 V1-V2 区以及基因上游基因组位点的方法。通过对 13570 个细菌基因组组装的分析，我们表明，与单个高变区或全长基因序列相比，基因组相关的 16S rRNA 测序在分类准确性和基因拷贝数鉴定方面具有优势。使用模拟群落和土壤样本，我们通过实验验证了 st16S-seq，并将其与既定的微生物分类技术进行了基准测试。我们表明，st16S-seq 可以准确估计 16S rRNA 基因拷贝数，能够在物种水平上进行分类分辨率，并接近通过全宏基因组测序获得的群落结构。
