Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal.
Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland.
Clin Microbiol Infect. 2018 Apr;24(4):342-349. doi: 10.1016/j.cmi.2017.12.015. Epub 2018 Jan 5.
Presently, the bottleneck in the deployment of high-throughput sequencing technology is the ability to analyse the increasing amount of data produced in a fit-for-purpose manner. The field of microbial bioinformatics is thriving and quickly adapting to technological changes, which creates difficulties for nonbioinformaticians in following the complexity and increasingly obscure jargon of this field.
This review is directed towards nonbioinformaticians who wish to gain understanding of the overall microbial bioinformatic processes, from raw data obtained from sequencers to final outputs.
The software and analytical strategies reviewed are based on the personal experience of the authors.
The bioinformatic processes of transforming raw reads to actionable information in a clinical and epidemiologic context is explained. We review the advantages and limitations of two major strategies currently applied: read mapping, which is the comparison with a predefined reference genome, and de novo assembly, which is the unguided assembly of the raw data. Finally, we discuss the main analytical methodologies and the most frequently used freely available software and its application in the context of bacterial infectious disease management.
High-throughput sequencing technologies are overhauling outbreak investigation and epidemiologic surveillance while creating new challenges due to the amount and complexity of data generated. The continuously evolving field of microbial bioinformatics is required for stakeholders to fully harness the power of these new technologies.
目前，高通量测序技术的部署瓶颈在于能够以合适的方式分析不断增加的数据量。微生物生物信息学领域正在蓬勃发展，并迅速适应技术变革，这使得非生物信息学家难以跟上该领域的复杂性和日益模糊的行话。
本综述面向希望了解从测序仪获得的原始数据到最终输出的整个微生物生物信息学过程的非生物信息学家。
所审查的软件和分析策略基于作者的个人经验。
解释了将原始读数转化为临床和流行病学背景下可操作信息的生物信息学过程。我们回顾了目前应用的两种主要策略的优缺点：读映射，即将其与预定义的参考基因组进行比较，以及从头组装，即对原始数据进行无指导组装。最后，我们讨论了主要的分析方法以及最常用的免费可用软件及其在细菌感染性疾病管理中的应用。
高通量测序技术正在彻底改变暴发调查和流行病学监测，同时由于生成的数据量和复杂性也带来了新的挑战。利益相关者需要不断发展的微生物生物信息学领域来充分利用这些新技术的力量。
