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从Streptomyces基因组中去除DNA序列的污染,以实现最佳的基因组挖掘

Raul Vitor Ferreira de Oliveira¹, Leandro Maza Garrido¹, Gabriel Padilla²

¹Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, SP, 05508-900, Brazil.

Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]

|January 15, 2025

概括

基因组DNA污染在全基因组测序中很常见. 这项研究表明,使用生物信息学工具进行有效的化除污染,使微生物基因组和二次代谢的准确分析成为可能.

科学领域:

微生物学微生物学
生物信息学是一种生物信息学.
基因组学就是基因组学.

背景情况:

基因组DNA样本的污染是全基因组测序 (WGS) 中经常出现的问题.
污染可能会损害下游分析,导致有价值数据的潜在损失.
生物信息学的进步为减轻污染影响提供了解决方案.

研究的目的:

开发和评估一个in silico去污管道,以从WGS数据中去除污染的细菌DNA.
评估消毒对基因组组装质量和随后的基因组分析的影响.
能够从受污染的样本中恢复有价值的基因组信息,而无需重新测序.

主要方法:

整个基因组测序可以从Streptomyces sp.中读取. 分析了被Bacillus licheniformis污染的BRB040. 结果显示,这些细菌中含有
使用银河平台工具,MeDuSa,Blast和metaSPAdes.com的组合识别和隔离了污染的读数.
使用Bowtie 2和BBduk进行清除,用于读取过.
基因组组装使用Unicycler进行,并使用BUSCO评估基因组完整性.
生物合成基因集群 (BGCs) 通过使用antiSMASH 7.0.0进行了鉴定.

主要成果:

污染的生物体Bacillus licheniformis被确定并其基因组组装.
使用BBduk进行消毒,然后进行Unicycler组装,生成了99.5%完整的基因组,与参考基因组 (99.8%) 非常接近.
这种方法成功实现了24个生物合成基因集群 (BGC) 的基因组挖掘,与未受污染的对照相比.
基于BBduk的管道在组装完整性和质量方面表现优于SPAdes.

结论:

在 silico 除污染是一种强大而有效的策略,用于从WGS数据集中去除污染的DNA.
生物信息学工具可以成功地隔离目标基因组,并保存基本的基因组信息,包括二次代谢物基因集群.
这种方法为重新测序提供了经济有效的替代方案,特别是当样本有限或不可用时.

关键词:

生物信息学是一种生物信息学.基因组学就是基因组学.国家储备系统 (NGS)自然产品是天然产品.

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