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临床非结核分枝杆菌不同种属内整合噬菌体的特性研究。

Characterization of integrated prophages within diverse species of clinical nontuberculous mycobacteria.

机构信息

Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA.

Computational Bioscience Program, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA.

出版信息

Virol J. 2020 Aug 17;17(1):124. doi: 10.1186/s12985-020-01394-y.

DOI:10.1186/s12985-020-01394-y
PMID:32807206
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7433156/
Abstract

BACKGROUND

Nontuberculous mycobacterial (NTM) infections are increasing in prevalence, with current estimates suggesting that over 100,000 people in the United States are affected each year. It is unclear how certain species of mycobacteria transition from environmental bacteria to clinical pathogens, or what genetic elements influence the differences in virulence among strains of the same species. A potential mechanism of genetic evolution and diversity within mycobacteria is the presence of integrated viruses called prophages in the host genome. Prophages may act as carriers of bacterial genes, with the potential of altering bacterial fitness through horizontal gene transfer. In this study, we quantify the frequency and composition of prophages within mycobacteria isolated from clinical samples and compare them against the composition of PhagesDB, an environmental mycobacteriophage database.

METHODS

Prophages were predicted by agreement between two discovery tools, VirSorter and Phaster, and the frequencies of integrated prophages were compared by growth rate. Prophages were assigned to PhagesDB lettered clusters. Bacterial virulence gene frequency was calculated using a combination of the Virulence Factor Database (VFDB) and the Pathosystems Resource Integration Center virulence database (Patric-VF) within the gene annotation software Prokka. CRISPR elements were discovered using CRT. ARAGORN was used to quantify tRNAs.

RESULTS

Rapidly growing mycobacteria (RGM) were more likely to contain prophage than slowly growing mycobacteria (SGM). CRISPR elements were not associated with prophage abundance in mycobacteria. The abundance of tRNAs was enriched in SGM compared to RGM. We compared the abundance of bacterial virulence genes within prophage genomes from clinical isolates to mycobacteriophages from PhagesDB. Our data suggests that prophages from clinical mycobacteria are enriched for bacterial virulence genes relative to environmental mycobacteriophage from PhagesDB.

CONCLUSION

Prophages are present in clinical NTM isolates. Prophages are more likely to be present in RGM compared to SGM genomes. The mechanism and selective advantage of this enrichment by growth rate remain unclear. In addition, the frequency of bacterial virulence genes in prophages from clinical NTM is enriched relative to the PhagesDB environmental proxy. This suggests prophages may act as a reservoir of genetic elements bacteria could use to thrive within a clinical environment.

摘要

背景

非结核分枝杆菌(NTM)感染的发病率正在上升,目前估计美国每年有超过 10 万人受到感染。目前尚不清楚某些分枝杆菌物种如何从环境细菌转变为临床病原体,也不清楚哪些遗传因素影响同一物种菌株之间的毒力差异。分枝杆菌内遗传进化和多样性的一个潜在机制是宿主基因组中存在整合病毒,称为噬菌体。噬菌体可以作为细菌基因的载体,通过水平基因转移有可能改变细菌的适应性。在这项研究中,我们定量分析了从临床样本中分离出的分枝杆菌中噬菌体的频率和组成,并将其与环境分枝杆菌噬菌体数据库 PhagesDB 的组成进行了比较。

方法

通过两种发现工具 VirSorter 和 Phaster 的一致性来预测噬菌体,通过生长速率比较整合噬菌体的频率。噬菌体被分配到 PhagesDB 字母聚类中。使用基因注释软件 Prokka 中的毒力因子数据库(VFDB)和病原系统资源整合中心毒力数据库(Patric-VF)计算细菌毒力基因的频率。使用 CRT 发现 CRISPR 元件。使用 ARAGORN 量化 tRNA。

结果

快速生长分枝杆菌(RGM)比缓慢生长分枝杆菌(SGM)更有可能含有噬菌体。CRISPR 元件与分枝杆菌噬菌体的丰度无关。与 RGM 相比,SGM 中 tRNA 的丰度更高。我们将临床分离株噬菌体基因组中的细菌毒力基因丰度与 PhagesDB 中的分枝杆菌噬菌体进行了比较。我们的数据表明,与 PhagesDB 中的环境分枝杆菌噬菌体相比,临床分枝杆菌噬菌体中的噬菌体富含细菌毒力基因。

结论

临床 NTM 分离株中存在噬菌体。与 SGM 基因组相比,RGM 中更有可能存在噬菌体。这种由生长速率引起的富集的机制和选择优势尚不清楚。此外,临床 NTM 中噬菌体的细菌毒力基因的频率相对于 PhagesDB 环境代理是富集的。这表明噬菌体可能是细菌在临床环境中赖以生存的遗传元件的储存库。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/3320144f28b2/12985_2020_1394_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/958216b428c8/12985_2020_1394_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/cc061e5c24d3/12985_2020_1394_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/249302557be7/12985_2020_1394_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/bcf120a432a7/12985_2020_1394_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/3320144f28b2/12985_2020_1394_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/958216b428c8/12985_2020_1394_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/cc061e5c24d3/12985_2020_1394_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/249302557be7/12985_2020_1394_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/bcf120a432a7/12985_2020_1394_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9012/7433156/3320144f28b2/12985_2020_1394_Fig5_HTML.jpg

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