Xanthomonas axonopodis pv. manihotis (Xam) is the causal agent of bacterial blight of cassava, which is among the main components of human diet in Africa and South America. Current information about the molecular pathogenicity factors involved in the infection process of this organism is limited. Previous studies in other bacteria in this genus suggest that advanced draft genome sequences are valuable resources for molecular studies on their interaction with plants and could provide valuable tools for diagnostics and detection. Here we have generated the first manually annotated high-quality draft genome sequence of Xam strain CIO151. Its genomic structure is similar to that of other xanthomonads, especially Xanthomonas euvesicatoria and Xanthomonas citri pv. citri species. Several putative pathogenicity factors were identified, including type III effectors, cell wall-degrading enzymes and clusters encoding protein secretion systems. Specific characteristics in this genome include changes in the xanthomonadin cluster that could explain the lack of typical yellow color in all strains of this pathovar and the presence of 50 regions in the genome with atypical nucleotide composition. The genome sequence was used to predict and evaluate 22 variable number of tandem repeat (VNTR) loci that were subsequently demonstrated as polymorphic in representative Xam strains. Our results demonstrate that Xanthomonas axonopodis pv. manihotis strain CIO151 possesses ten clusters of pathogenicity factors conserved within the genus Xanthomonas. We report 126 genes that are potentially unique to Xam, as well as potential horizontal transfer events in the history of the genome. The relation of these regions with virulence and pathogenicity could explain several aspects of the biology of this pathogen, including its ability to colonize both vascular and non-vascular tissues of cassava plants. A set of 16 robust, polymorphic VNTR loci will be useful to develop a multi-locus VNTR analysis scheme for epidemiological surveillance of this disease.

Summary Microbial communities ultimately control the fate of petroleum hydrocarbons (PHCs) that enter the natural environment, but the interactions of microbes with PHCs and the environment are highly complex and poorly understood. Genome‐resolved metagenomics can help unravel these complex interactions. However, the lack of a comprehensive database that integrates existing genomic/metagenomic data from oil environments with physicochemical parameters known to regulate the fate of PHCs currently limits data analysis and interpretations. Here, we curated a comprehensive, searchable database that documents microbial populations in natural oil ecosystems and oil spills, along with available underlying physicochemical data, geocoded via geographic information system to reveal their geographic distribution patterns. Analysis of the ~2000 metagenome‐assembled genomes (MAGs) available in the database revealed strong ecological niche specialization within habitats. Over 95% of the recovered MAGs represented novel taxa underscoring the limited representation of cultured organisms from oil‐contaminated and oil reservoir ecosystems. The majority of MAGs linked to oil‐contaminated ecosystems were detectable in non‐oiled samples from the Gulf of Mexico but not in comparable samples from elsewhere, indicating that the Gulf is primed for oil biodegradation. The repository should facilitate future work toward a predictive understanding of the microbial taxa and their activities that control the fate of oil spills.

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Background Phytophthora infestans (Mont.) de Bary causes late blight of potato and tomato, and has a broad host range within the Solanaceae family. Most studies of the Phytophthora – Solanum pathosystem have focused on gene expression in the host and have not analyzed pathogen gene expression in planta.Methodology/Principal FindingsWe describe in detail an in silico approach to mine ESTs from inoculated host plants deposited in a database in order to identify particular pathogen sequences associated with disease. We identified candidate effector genes through mining of 22,795 ESTs corresponding to P. infestans cDNA libraries in compatible and incompatible interactions with hosts from the Solanaceae family.Conclusions/SignificanceWe annotated genes of P. infestans expressed in planta associated with late blight using different approaches and assigned putative functions to 373 out of the 501 sequences found in the P. infestans genome draft, including putative secreted proteins, domains associated with pathogenicity and poorly characterized proteins ideal for further experimental studies. Our study provides a methodology for analyzing cDNA libraries and provides an understanding of the plant – oomycete pathosystems that is independent of the host, condition, or type of sample by identifying genes of the pathogen expressed in planta.

What a strain is and how many strains make up a natural bacterial population remain elusive concepts despite their apparent importance for assessing the role of intra-population diversity in disease emergence or response to environmental perturbations. To advance these concepts, we sequenced 138 randomly selectedSalinibacter ruberisolates from two solar salterns and assessed these genomes against companion short-read metagenomes from the same samples. The distribution of genome-aggregate average nucleotide identity (ANI) values among these isolates revealed a bimodal distribution, with significantly lower occurrence of values between 99.2% and 99.8% relative to ANI >99.8% or <99.2%, revealing a natural "gap" in the sequence space within species. Accordingly, we used this ANI gap to define genomovars and a higher ANI value of >99.99% and shared gene-content >99.0% to define strains. Using these thresholds and extrapolating from how many metagenomic reads each genomovar uniquely recruited, we estimated that -although our 138 isolates represented about 80% of theSal. ruberpopulation- the total population in one pond is composed of 5,500 to 11,000 genomovars, the great majority of which appear to be rare in situ. These data also revealed that the most frequently recovered isolate in lab media was often not the most abundant genomovar in situ, suggesting that cultivation biases are significant, even in cases that cultivation procedures are thought to be robust. Preliminary analyses of available genomes revealed that the thresholds used for defining strains and distinct intra-species units (genomovars) may be broadly applicable to additional bacterial species.

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