Centre for Complex Systems, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia.
Sydney Infectious Diseases Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
Phys Biol. 2023 Jun 2;20(4). doi: 10.1088/1478-3975/acd899.
Modelling evolution of foodborne pathogens is crucial for mitigation and prevention of outbreaks. We apply network-theoretic and information-theoretic methods to trace evolutionary pathways ofTyphimurium in New South Wales, Australia, by studying whole genome sequencing surveillance data over a five-year period which included several outbreaks. The study derives both undirected and directed genotype networks based on genetic proximity, and relates the network's structural property (centrality) to its functional property (prevalence). The centrality-prevalence space derived for the undirected network reveals a salient exploration-exploitation distinction across the pathogens, further quantified by the normalised Shannon entropy and the Fisher information of the corresponding shell genome. This distinction is also analysed by tracing the probability density along evolutionary paths in the centrality-prevalence space. We quantify the evolutionary pathways, and show that pathogens exploring the evolutionary search-space during the considered period begin to exploit their environment (their prevalence increases resulting in outbreaks), but eventually encounter a bottleneck formed by epidemic containment measures.
对食源性致病菌的进化进行建模对于暴发的减轻和预防至关重要。我们通过研究澳大利亚新南威尔士州长达五年的全基因组测序监测数据（其中包括几次暴发），应用网络理论和信息理论方法来追踪鼠伤寒沙门氏菌的进化途径。该研究基于遗传相似度得出了无向和有向基因型网络，并将网络的结构特性（中心性）与其功能特性（流行率）联系起来。为无向网络推导的中心性-流行率空间揭示了病原体之间明显的探索-开发区分，通过相应壳基因组的归一化香农熵和费希尔信息进一步量化。通过在中心性-流行率空间中的进化路径上追踪概率密度来分析这种区分。我们量化了进化途径，并表明在考虑的时间段内探索进化搜索空间的病原体开始利用其环境（它们的流行率增加导致暴发），但最终遇到了由流行病控制措施形成的瓶颈。
