Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data.

ABSTRACT: Identifying and interrupting transmission chains is important for controlling infectious diseases. One way to identify transmission pairs - two hosts in which infection was transmitted from one to the other - is using the variation of the pathogen within each single host (within-host variation). However, the role of such variation in transmission is understudied due to a lack of experimental and clinical datasets that capture pathogen diversity in both donor and recipient hosts. In this work, we assess the utility of deep-sequenced genomic surveillance (where genomic regions are sequenced hundreds to thousands of times) using a mouse transmission model involving controlled spread of the pathogenic bacterium Citrobacter rodentium from infected to naïve female animals. We observe that within

SUBMITTER: Senghore M 

PROVIDER: S-EPMC10618251 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature