Vertebrate gut microbiome often underpins the metabolic capability and provides many beneficial effects on their hosts. However, little was known about how host trophic level influences fish gut microbiota and metabolic activity. In this study, more than 985,000 quality-filtered sequences from 24 16S rRNA libraries were obtained and the results revealed distinct compositions and diversities of gut microbiota in four trophic categories. PCoA test showed that gut bacterial communities of carnivorous and herbivorous fishes formed distinctly different clusters in PCoA space. Although fish in different trophic levels shared a large size of OTUs comprising a core microbiota community, at the genus level a strong distinction existed. Cellulose-degrading bacteria Clostridium, Citrobacter and Leptotrichia were dominant in the herbivorous, while Cetobacterium and protease-producing bacteria Halomonas were dominant in the carnivorous. PICRUSt predictions of metagenome function revealed that fishes in different trophic levels affected the metabolic capacity of their gut microbiota. Moreover, cellulase and amylase activities in herbivorous fishes were significantly higher than in the carnivorous, while trypsin activity in the carnivorous was much higher than in the herbivorous. These results indicated that host trophic level influenced the structure and composition of gut microbiota, metabolic capacity and gut content enzyme activity.

Blunt snout bream (Megalobrama amblycephala) is an herbivorous freshwater fish species native to China and has been recognized as a main aquaculture species in the Chinese freshwater polyculture system with high economic value. Right now, only limited EST resources were available for M. amblycephala. Recent advances in large-scale RNA sequencing provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Using 454 pyrosequencing, a total of 1,409,706 high quality reads (total length 577 Mbp) were generated from the normalized cDNA of pooled M. amblycephala individuals. These sequences were assembled into 26,802 contigs and 73,675 singletons. After BLAST searches against the NCBI non-redundant (NR) and UniProt databases with an arbitrary expectation value of E⁻¹⁰, over 40,000 unigenes were functionally annotated and classified using the FunCat functional annotation scheme. A comparative genomics approach revealed a substantial proportion of genes expressed in M. amblycephala tanscriptome to be shared across the genomes of zebrafish, medaka, tetraodon, fugu, stickleback, human, mouse, and chicken, and identified a substantial number of potentially novel M. amblycephala genes. A total number of 4,952 SSRs were found and 116 polymorphic loci have been characterized. A significant number of SNPs (25,697) and indels (23,287) were identified based on specific filter criteria in the M. amblycephala. This study is the first comprehensive transcriptome analysis for a fish species belonging to the genus Megalobrama. These large EST resources are expected to be valuable for the development of molecular markers, construction of gene-based linkage map, and large-scale expression analysis of M. amblycephala, as well as comparative genome analysis for the genus Megalobrama fish species. The identified SSR and SNP markers will greatly benefit its breeding program and whole genome association studies.

Background: Blunt snout bream (Megalobrama amblycephala) is an economically important fish species in the Chinese freshwater polyculture system for its delicacy and high economic value. MicroRNAs (miRNAs) play important roles in regulation of almost all biological processes in eukaryotes. Although previous studies have identified thousands of miRNAs from many species, little information is known for miRNAs of M. amblycephala. To investigate functions of miRNAs associated with growth of M. amblycephala, we adopted the Solexa sequencing technology to sequence two small RNA libraries prepared from four growth related tissues (brain, pituitary, liver and muscle) of M. amblycephala using individuals with relatively high and low growth rates. Results: In this study, we have identified 347 conserved miRNAs (belonging to 123 families) and 22 novel miRNAs in M. amblycephala. Moreover, we observed sequence variants and seed edits of the miRNAs. Of the 5,166 single nucleotide substitutions observed in two libraries, the most abundant were G-to-U (15.9%), followed by U-to-C (12.1%), G-to-A (11.2%), and A to G (11.2%). Subsequently, we compared the expression patterns of miRNAs in the two libraries (big-size group with high growth rate versus small-size group with low growth rate). Results indicated that 27 miRNAs displayed significant differential expressions between the two libraries (p < 0.05). Of these, 16 were significantly up-regulated and 11 were significantly down-regulated in the big-size group compared to the small-size group. Furthermore, stem-loop RT-PCR was applied to validate and profile the expression of the differentially expressed miRNAs in ten tissues, and the result revealed that the conserved miRNAs expressed at higher levels than the novel miRNAs, especially in brain, liver and muscle. Also, targets prediction of differentially expressed miRNAs and KEGG pathway analysis suggested that differentially expressed miRNAs are involved in growth and metabolism, signal transduction, cell cycle, neural development and functions. Conclusions: The present study provides the first large-scale characterization of miRNAs in M. amblycephala and miRNA profile related to different growth performances. The discovery of miRNA resource from this study is expected to contribute to a better understanding of the miRNAs roles playing in regulating the growth biological processes and the study of miRNA function and phenotype-associated miRNA identification in fish.

Global aquatic or ‘blue’ foods, essential to over 3.2 billion people, face challenges of maintaining supply in a changing environment while adhering to safety and sustainability standards. Despite the growing concerns over their environmental impacts, limited attention has been paid to how blue food production is influenced by anthropogenic environmental changes. Here we assess the vulnerability of global blue food systems to predominant environmental disturbances and predict the spatial impacts. Over 90% of global blue food production faces substantial risks from environmental change, with the major producers in Asia and the United States facing the greatest threats. Capture fisheries generally demonstrate higher vulnerability than aquaculture in marine environments, while the opposite is true in freshwater environments. While threats to production quantity are widespread across marine and inland systems, food safety risks are concentrated within a few countries. Identifying and supporting mitigation and adaptation measures in response to environmental stressors is particularly important in developing countries in Asia, Latin America and Africa where risks are high and national response capacities are low. These findings lay groundwork for future work to map environmental threats and opportunities, aiding strategic planning and policy development for resilient and sustainable blue food production under changing conditions.