Bacteria often infect their hosts from environmental sources, but little is known about how environmental and host-infecting populations are related. Here, phylogenetic clustering and diversity were investigated in a natural community of rhizobial bacteria from the genus Bradyrhizobium. These bacteria live in the soil and also form beneficial root nodule symbioses with legumes, including those in the genus Lotus. Two hundred eighty pure cultures of Bradyrhizobium bacteria were isolated and genotyped from wild hosts, including Lotus angustissimus, Lotus heermannii, Lotus micranthus, and Lotus strigosus. Bacteria were cultured directly from symbiotic nodules and from two microenvironments on the soil-root interface: root tips and mature (old) root surfaces. Bayesian phylogenies of Bradyrhizobium isolates were reconstructed using the internal transcribed spacer (ITS), and the structure of phylogenetic relatedness among bacteria was examined by host species and microenvironment. Inoculation assays were performed to confirm the nodulation status of a subset of isolates. Most recovered rhizobial genotypes were unique and found only in root surface communities, where little bacterial population genetic structure was detected among hosts. Conversely, most nodule isolates could be classified into several related, hyper-abundant genotypes that were phylogenetically clustered within host species. This pattern suggests that host infection provides ample rewards to symbiotic bacteria but that host specificity can strongly structure only a small subset of the rhizobial community.

BackgroundIn many fields of biomedical research, it is important to estimate phylogenetic distances between taxa based on low-coverage sequencing reads. Major applications are, for example, phylogeny reconstruction, species identification from small sequencing samples, or bacterial strain typing in medical diagnostics.ResultsWe adapted our previously developed software program Filtered Spaced-Word Matches (FSWM) for alignment-free phylogeny reconstruction to take unassembled reads as input; we call this implementation Read-SpaM.ConclusionsTest runs on simulated reads from semi-artificial and real-world bacterial genomes show that our approach can estimate phylogenetic distances with high accuracy, even for large evolutionary distances and for very low sequencing coverage.