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Abstract Background Infectious diseases have caused huge economic loss and food security issues in fish aquaculture. Current management and breeding strategies heavily rely on the knowledge of regulative mechanisms underlying disease resistance. Though the intestinal microbial community was linked with disease infection, there is little knowledge about the roles of intestinal microbes in fish disease resistance. Cynoglossus semilaevis is an economically important and widely cultivated flatfish species in China. However, it suffers from outbreaks of vibriosis, which results in huge mortalities and economic loss. Results Here, we used C. semilaevis as a research model to investigate the host-microbiome interactions in regulating vibriosis resistance. The resistance to vibriosis was reflected in intestinal microbiome on both taxonomic and functional levels. Such differences also influenced the host gene expressions in the resistant family. Moreover, the intestinal microbiome might control the host immunological homeostasis and inflammation to enhance vibriosis resistance through the microbe-intestine-immunity axis. For example, Phaeobacter regulated its hdhA gene and host cyp27a1 gene up-expressed in bile acid biosynthesis pathways, but regulated its trxA gene and host akt gene down-expressed in proinflammatory cytokines biosynthesis pathways, to reduce inflammation and resist disease infection in the resistant family. Furthermore, the combination of intestinal microbes and host genes as biomarkers could accurately differentiate resistant family from susceptible family. Conclusion Our study uncovered the regulatory patterns of the microbe-intestine-immunity axis that may contribute to vibriosis resistance in C. semilaevis. These findings could facilitate the disease control and selective breeding of superior germplasm with high disease resistance in fish aquaculture. Video Abstract

Abstract Introduction The 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. Results By 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. Conclusions These 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.

Abstract Background The explosive growth of microbiome data provides ample opportunities to gain a better understanding of the microbes and their interactions in microbial communities. Given these massive data, optimized data mining methods become important and necessary to perform deep and comprehensive analysis. Among the various priorities for microbiome data mining, the examination of species-species co-occurrence patterns becomes one of the key themes in urgent need. Results Hence, in this work, we propose the Meta-Network framework to lucubrate the microbial communities. Rooted in loose definitions of network (two species co-exist in a certain samples rather than all samples) as well as association rule mining (mining more complex forms of correlations like indirect correlation and mutual information), this framework outperforms other methods in restoring the microbial communities, based on two cohorts of microbial communities: (a) the loose definition strategy is capable to generate more reasonable relationships among species in the species-species co-occurrence network; (b) important species-species co-occurrence patterns could not be identified by other existing approaches, but could successfully generated by association rule mining. Conclusions Results have shown that the species-species co-occurrence network we generated are much more informative than those based on traditional methods. Meta-Network has consistently constructed more meaningful networks with biologically important clusters, hubs, and provides a general approach towards deciphering the species-species co-occurrence networks.

Abstract Background Shewanella 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. Results A 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. Conclusions The 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.