DGRP infection classification accuracy.

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 arthropod and 119 nematode infected samples. From these data, we estimated that Wolbachia infects approximately 44% of all arthropod and 34% of all nematode species, while other reproductive manipulators only infect 1–8% of arthropod and nematode species. Although relative titers within hosts were highly variable within and between arthropod species, a combination of arthropod host species and Wolbachia strain explained approximately 36% of variation in Wolbachia titer across the dataset. To explore potential mechanisms for host control of symbiont titer, we leveraged population genomic data from the model system Drosophila melanogaster. In this host, we found a number of SNPs associated with titer in candidate genes potentially relevant to host interactions with Wolbachia. Our study demonstrates that data mining is a powerful tool to detect bacterial infections and quantify infection intensities, thus opening an array of previously inaccessible data for further analysis in host-symbiont evolution.操控宿主生殖过程的细菌共生体，是无脊椎动物生态学与演化研究中的关键调控因子，同时也被广泛应用于宿主生物防控实践。感染流行率会制约可采用的生物防控策略类型，而宿主体内共生菌的感染密度——即滴度（titer）——被认为对感染流行率具有显著的调控作用。当前用于估算感染流行率与共生菌滴度的方法存在诸多局限：通量低下、采样偏向感染宿主物种，且极少能直接测定共生菌滴度。本研究开发了一种数据挖掘方法，可用于估算宿主物种内的共生菌感染频率，以及宿主组织内的共生菌滴度。我们将该方法应用于筛选最常见共生菌宿主类群的约32000条公开可用序列样本，共鉴定得到2083个节肢动物感染样本与119个线虫感染样本。基于上述数据，我们估算得出：沃尔巴克氏体（Wolbachia）约感染44%的节肢动物物种与34%的线虫物种，而其他生殖操控型共生菌仅感染1%~8%的节肢动物与线虫物种。尽管宿主体内的相对滴度在节肢动物物种内部及物种间均存在高度变异，但在本数据集范围内，节肢动物宿主物种与沃尔巴克氏体菌株的组合可解释约36%的沃尔巴克氏体滴度变异。为探究宿主调控共生菌滴度的潜在分子机制，我们利用了模式生物黑腹果蝇（Drosophila melanogaster）的群体基因组数据。在该模式宿主中，我们在与沃尔巴克氏体宿主互作相关的候选基因内，鉴定到多个与共生菌滴度相关的单核苷酸多态性位点（SNPs）。本研究证实，数据挖掘是一种可用于检测细菌感染并量化感染强度的高效工具，由此为宿主-共生菌协同演化领域的后续研究解锁了大量此前难以获取的数据集。