Deep data mining reveals variable abundance and distribution of microbial reproductive manipulators within and among diverse host species.

ABSTRACT: Bacterial symbionts that manipulate the reproduction of their hosts are important factors in invertebrate ecology and evolution, and are being leveraged for host biological control. Infection prevalence restricts which biological control strategies are possible and is thought to be strongly influenced by the density of symbiont infection within hosts, termed titer. Current methods to estimate infection prevalence and symbiont titers are low-throughput, biased towards sampling infected species, and rarely measure titer. Here we develop a data mining approach to estimate symbiont infection frequencies within host species and titers within host tissues. We applied this approach to screen ~32,000 publicly available sequence samples from the most common symbiont host taxa, discovering 2,083 art

SUBMITTER: Medina P 

PROVIDER: S-EPMC10335654 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature