First pass methods based on BLAST match are commonly used as an initial step to separate the different phylogenetic histories of genes in microbial genomes, and target putative horizontal gene transfer (HGT) events. This will continue to be necessary given the rapid growth of genomic data and the technical difficulties in conducting large-scale explicit phylogenetic analyses. However, these methods often produce misleading results due to their inability to resolve indirect phylogenetic links and their vulnerability to stochastic events. A new computational method of rapid, exhaustive and genome-wide detection of HGT was developed, featuring the systematic analysis of BLAST hit distribution patterns in the context of a priori defined hierarchical evolutionary categories. Genes that fall beyond a series of statistically determined thresholds are identified as not adhering to the typical vertical history of the organisms in question, but instead having a putative horizontal origin. Tests on simulated genomic data suggest that this approach effectively targets atypically distributed genes that are highly likely to be HGT-derived, and exhibits robust performance compared to conventional BLAST-based approaches. This method was further tested on real genomic datasets, including Rickettsia genomes, and was compared to previous studies. Results show consistency with currently employed categories of HGT prediction methods. In-depth analysis of both simulated and real genomic data suggests that the method is notably insensitive to stochastic events such as gene loss, rate variation and database error, which are common challenges to the current methodology. An automated pipeline was created to implement this approach and was made publicly available at: https://github.com/DittmarLab/HGTector . The program is versatile, easily deployed, has a low requirement for computational resources. HGTector is an effective tool for initial or standalone large-scale discovery of candidate HGT-derived genes.

We report the presence and diversity of Bartonella spp. in bats of 13 insectivorous and frugivorous species collected from various locations across Kenya. Bartonella isolates were obtained from 23 Eidolon helvum, 22 Rousettus aegyptiacus, 4 Coleura afra, 7 Triaenops persicus, 1 Hipposideros commersoni, and 49 Miniopterus spp. bats. Sequence analysis of the citrate synthase gene from the obtained isolates showed a wide assortment of Bartonella strains. Phylogenetically, isolates clustered in specific host bat species. All isolates from R. aegyptiacus, C. afra, and T. persicus bats clustered in separate monophyletic groups. In contrast, E. helvum and Miniopterus spp. bats harbored strains that clustered in several groups. Further investigation is needed to determine whether these agents are responsible for human illnesses in the region.

SUMMARY: Bat flies are obligate ectoparasites of bats and it has been hypothesized that they may be involved in the transmission ofBartonellaspecies between bats. A survey was conducted to identify whetherCyclopodia greefi greefi(Diptera: Nycteribiidae) collected from Ghana and 2 islands in the Gulf of Guinea harbourBartonella. In total, 137 adult flies removed fromEidolon helvum, the straw-coloured fruit bat, were screened for the presence ofBartonellaby culture and PCR analysis.BartonellaDNA was detected in 91 (66·4%) of the specimens examined and 1 strain of aBartonellasp., initially identified inE. helvumblood from Kenya, was obtained from a bat fly collected in Ghana. This is the first study, to our knowledge, to report the identification and isolation ofBartonellain bat flies from western Africa.

SUMMARY: Growing evidence demonstrates that bacterial species diversity is substantial, and many of these species are pathogenic in some contexts or hosts. At the same time, laboratories and museums have collected valuable animal tissue and ectoparasite samples that may contain substantial novel information on bacterial prevalence and diversity. However, the identification of bacterial species is challenging, partly due to the difficulty in culturing many microbes and the reliance on molecular data. Although the genomics revolution will surely add to our knowledge of bacterial systematics, these approaches are not accessible to all researchers and rely predominantly on cultured isolates. Thus, there is a need for comprehensive molecular analyses capable of accurately genotyping bacteria from animal tissues or ectoparasites using common methods that will facilitate large-scale comparisons of species diversity and prevalence. To illustrate the challenges of genotyping bacteria, we focus on the genusBartonella, vector-borne bacteria common in mammals. We highlight the value and limitations of commonly used techniques for genotyping bartonellae and make recommendations for researchers interested in studying the diversity of these bacteria in various samples. Our recommendations could be applicable to many bacterial taxa (with some modifications) and could lead to a more complete understanding of bacterial species diversity.

We used a whole-genome scanning technique to identify the NADH dehydrogenase gamma subunit ( nuoG ) primer set that is sensitive and specific enough to detect a diverse number of Bartonella species in a wide range of environmental samples yet maintains minimal cross-reactivity to mammalian host and arthropod vector organisms.