Using population genomics to recognise and prevent the emergence and establishment of Klebsiella pneumoniae high-risk lineages

本项目将重点研究三个纵向库群的比较群体基因组学。肺炎跨越12-20年从三个不同的设置;英国，阿根廷和马拉维。目前的数据K。肺炎几乎完全基于特定病房/医院的短期研究，通常在高度不同的环境中。这使得无法分析长期信号，因为这将需要比较高度混淆的数据，例如来自不同国家的分离株代表的不同年份，从而无法区分分离时间与分离国家的影响。三种高度不同的设置的比较减少了这种混淆因素，因为患者集水区组随着时间的推移保持相似。为了自信地识别普遍有效的全球适用信号，该项目将比较在三种不同环境中触发谱系扩张的因素。然后，可以将在相关设置中观察到的人口的时间变化相互比较，以确定K的共同规则。当所有人共享相似的AMR决定因素时，肺炎谱系的成功率高于其他谱系。了解是什么导致了新的高风险谱系的出现，对于形成高风险克隆出现的预警系统至关重要，并将感染控制的努力集中在这些方面，特别是在资源有限的情况下。

This project will focus on comparative population genomics of three longitudinal collections of K. pneumoniae spanning 12-20 years from three diverse settings; the UK, Argentina and Malawi. Current data on K. pneumoniae is almost exclusively based on short-term studies of specific wards/hospitals, often in highly different settings. This makes the analysis of long-term signals impossible, as this would require the comparison of highly confounded data, e.g. different years represented by isolates from different countries, making it impossible to distinguish between the influence of time of isolation from the country of isolation. The comparison of three highly different settings reduces this confounder, as the patient catchment group remains similar over time. To confidently recognise globally applicable signals that are universally valid, this project will compare what triggers lineage expansion in the three different settings with each other. The observed temporal changes in the population in the relevant settings can then be compared with each other, to identify shared rules for what makes a K. pneumoniae lineage successful over others when all share similar AMR determinants. Understanding what leads to the emergence of new high-risk lineages is essential to form an early-warning system for the emergence of high-risk clones, and focus efforts of infection control on these, especially when resources are limited.