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过去十年微生物基因组学生物信息学工具的进步和挑战:朝着生物信息学工具,数字资源和新兴技术的智能集成,分析复杂的生物数据
Cheikh Tidiane Houmenou1, Cheikh Sokhna2, Florence Fenollar3
1Institut Hospitalo-universitaire Méditerranée Infection, Marseille, France; Aix Marseille University, AP-HM, MEPHI, Marseille, France.
概括
微生物基因组学已经以新的测序和生物信息学工具进步,使全面的基因组分析和生态调查成为可能. 未来的方向包括人工智能和先进的测序,用于预测和可重现的研究.
科学领域:
- 微生物基因组学 微生物基因组学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 测序和生物信息学的进步彻底改变了微生物基因组学.
- 该领域已经从向基因标记转向全基因组组合和元基因组调查.
研究的目的:
- 为微生物基因组学中的生物信息学管道提供全面的概述.
- 突出标准和创新的工具及其应用.
- 讨论该领域的挑战和未来前景.
主要方法:
- 审查当前的生物信息管道从样本准备到数据库提交.
- 突出了诸如FastQC,SPAdes,Prokka,Bakta,CARD,GTDB-Tk,QIIME 2和Kraken2.2这样的关键工具.
- 讨论诸如混合装配器,自动化工作流程 (nf-core,Bactopia) 和本体学驱动的注释等创新.
主要成果:
- 标准化工具和创新方法有助于微生物基因组分析.
- 应用包括抗菌素耐药性监测,植物遗传学分类和生态研究.
- 案例研究证明了肠道微生物群的概况,新物种的描述和病原体的特征.
结论:
- 持续存在的挑战包括数据库的局限性,计算瓶和经济差异.
- 国际倡议促进 FAIR 数据原则和全球合作.
- 人工智能,长期测序和云基础设施的未来整合将增强微生物基因组学.
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