Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia; National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australia; Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia.
Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia; Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia; Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia.
Trends Microbiol. 2021 Sep;29(9):788-797. doi: 10.1016/j.tim.2021.02.008. Epub 2021 Mar 15.
Phylodynamic methods have been essential to understand the interplay between the evolution and epidemiology of infectious diseases. To date, the field has centered on viruses. Bacterial pathogens are seldom analyzed under such phylodynamic frameworks, due to their complex genome evolution and, until recently, a paucity of whole-genome sequence data sets with rich associated metadata. We posit that the increasing availability of bacterial genomes and epidemiological data means that the field is now ripe to lay the foundations for applying phylodynamics to bacterial pathogens. The development of new methods that integrate more complex genomic and ecological data will help to inform public heath surveillance and control strategies for bacterial pathogens that represent serious threats to human health.
系统发育动力学方法对于理解传染病的进化和流行病学之间的相互作用至关重要。迄今为止,该领域的研究重点主要集中在病毒上。由于细菌病原体的基因组进化复杂,并且直到最近,具有丰富相关元数据的全基因组序列数据集也很少,因此很少在这种系统发育动力学框架下对细菌病原体进行分析。我们认为,随着细菌基因组和流行病学数据的日益普及,现在为将系统发育动力学应用于细菌病原体奠定基础的时机已经成熟。开发新的方法,整合更复杂的基因组和生态数据,将有助于为代表人类健康严重威胁的细菌病原体提供公共卫生监测和控制策略的信息。