Tracing mother-infant transmission of bacteriophages by means of a novel analytical tool for shotgun metagenomic datasets: METAnnotatorX

利用一种新型的宏基因组鸟枪法测序数据集分析工具METAnnotatorX追踪噬菌体母婴传播。

阅读:1

Abstract

BACKGROUND: Despite the relevance of viral populations, our knowledge of (bacterio) phage populations, i.e., the phageome, suffers from the absence of a "gold standard" protocol for viral DNA extraction with associated in silico sequence processing analyses. To overcome this apparent hiatus, we present here a comprehensive performance evaluation of various protocols and propose an optimized pipeline that covers DNA extraction, sequencing, and bioinformatic analysis of phageome data. RESULTS: Five widely used protocols for viral DNA extraction from fecal samples were tested for their performance in removal of non-viral DNA. Moreover, we developed a novel bioinformatic platform, METAnnotatorX, for metagenomic dataset analysis. This in silico tool facilitates a range of read- and assembly-based analyses, including taxonomic profiling using an iterative multi-database pipeline, classification of contigs at genus and species level, as well as functional characterizations of reads and assembled data. Performances of METAnnotatorX were assessed through investigation of seven mother-newborn pairs, leading to the identification of shared phage genotypes, of which two were genomically decoded and characterized. METAnnotatorX was furthermore employed to evaluate a protocol for the identification of contaminant non-viral DNA in sequenced datasets and was exploited to determine the amount of metagenomic data needed for robust evaluation of human adult-derived (fecal) phageomes. CONCLUSIONS: Results obtained in this study demonstrate that a comprehensive pipeline for analysis of phageomes will be pivotal for future explorations of the ecology of phages in the gut environment as well as for understanding their impact on the physiology and bacterial community kinetics as players of dysbiosis and homeostasis in the gut microbiota.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。