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BackgroundShewanella strains are important dissimilatory metal-reducing bacteria which are widely distributed in diverse habitats. Despite efforts to genomically characterize Shewanella, knowledge of the molecular components, functional information and evolutionary patterns remain lacking, especially for their compatibility in the metal-reducing pathway. The increasing number of genome sequences of Shewanella strains offers a basis for pan-genome studies.ResultsA comparative pan-genome analysis was conducted to study genomic diversity and evolutionary relationships among 24 Shewanella strains. Results revealed an open pan-genome of 13,406 non-redundant genes and a core-genome of 1878 non-redundant genes. Selective pressure acted on the invariant members of core genome, in which purifying selection drove evolution in the housekeeping mechanisms. Shewanella strains exhibited extensive genome variability, with high levels of gene gain and loss during the evolution, which affected variable gene sets and facilitated the rapid evolution. Additionally, genes related to metal reduction were diversely distributed in Shewanella strains and evolved under purifying selection, which highlighted the basic conserved functionality and specificity of respiratory systems.ConclusionsThe diversity of genes present in the accessory and specific genomes of Shewanella strains indicates that each strain uses different strategies to adapt to diverse environments. Horizontal gene transfer is an important evolutionary force in shaping Shewanella genomes. Purifying selection plays an important role in the stability of the core-genome and also drives evolution in mtr–omc cluster of different Shewanella strains.Electronic supplementary materialThe online version of this article (10.1186/s13068-018-1201-1) contains supplementary material, which is available to authorized users.

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Objectives: Previous studies have reported that the gut microbiome has an important link with the development of hypertension. Though previous researches have focused on the links of gut bacteria with hypertension, little has been known about the linkage of gut viruses to hypertension and the development of hypertension, largely due to the lack of data mining tools for such investigation. In this work, we have analyzed 196 fecal metagenomic data related to hypertension aiming to profile the gut virome and link the gut virome to pre-hypertension and hypertension.Design: Here, we have applied a statistically sound method for mining of gut virome data and linking gut virome to hypertension. We characterized the viral composition and bacterial composition of 196 samples, identified the viral-type of each sample and linked gut virome to hypertension.Results: We stratified these 196 fecal samples into two viral-types and selected 32 viruses as the biomarkers for these groups. We found that viruses could have a superior resolution and discrimination power than bacteria for differentiation of healthy samples and pre-hypertension samples, as well as hypertension samples. Moreover, as to the co-occurrence networks linking viruses and bacteria, we found increasingly pervasive virus-bacteria linkages from healthy people to pre-hypertension people to hypertension patients.Conclusion: Overall, our results have shown ample indications of the link between human gut virome and hypertension, and could help provide microbial solutions toward early diagnoses of hypertension.

IntroductionThe ocean microbiome represents one of the largest microbiomes and produces nearly half of the primary energy on the planet through photosynthesis or chemosynthesis. Using recent advances in marine genomics, we explore new applications of oceanic metagenomes for protein structure and function prediction.ResultsBy processing 1.3 TB of high-quality reads from the Tara Oceans data, we obtain 97 million non-redundant genes. Of the 5721 Pfam families that lack experimental structures, 2801 have at least one member associated with the oceanic metagenomics dataset. We apply C-QUARK, a deep-learning contact-guided ab initio structure prediction pipeline, to model 27 families, where 20 are predicted to have a reliable fold with estimated template modeling score (TM-score) at least 0.5. Detailed analyses reveal that the abundance of microbial genera in the ocean is highly correlated to the frequency of occurrence in the modeled Pfam families, suggesting the significant role of the Tara Oceans genomes in the contact-map prediction and subsequent ab initio folding simulations. Of interesting note, PF15461, which has a majority of members coming from ocean-related bacteria, is identified as an important photosynthetic protein by structure-based function annotations. The pipeline is extended to a set of 417 Pfam families, built on the combination of Tara with other metagenomics datasets, which results in 235 families with an estimated TM-score over 0.5.ConclusionsThese results demonstrate a new avenue to improve the capacity of protein structure and function modeling through marine metagenomics, especially for difficult proteins with few homologous sequences.