Bioinformatics approaches and big data analytics opportunities in improving fisheries and aquaculture

Identification of TonB-dependent siderophore receptor inhibitors against Flavobacterium columnare using a structure-based high-throughput virtual screening method

TonB-dependent siderophore receptors play a critical transport role for Flavobacterium columnare virulence formation and growth, and have become valuable targets for the development of novel antimicrobial agents. Traditional Chinese medicine has demonstrated notable efficacy in the treatment of fish diseases and includes potential antibacterial agents. Herein, we performed molecular docking-based virtual screening to discover novel TonB-dependent siderophore receptor inhibitors from traditional Chinese medicine and provide information for developing novel antibacterial agents. Firstly, we efficiently obtained 11 potential inhibitors with desirable drug-like characteristics from thousands of compounds in the TCM library based on virtual screening and property prediction. The antibacterial activity of Enoxolone, along with its interaction characteristics, were determined via an MIC assay and molecular dynamic simulation. Transcriptional profiling, along with validation experiments, subsequently revealed that an insufficient uptake of iron ions by bacteria upon binding to the TonB-dependent siderophore receptors is the antibacterial mechanism of Enoxolone. Finally, Enoxolone's acceptable toxicity was illustrated through immersion experiments. In summary, we have used virtual screening techniques for the first time in the development of antimicrobial agents in aquaculture. Through this process, we have identified Enoxolone as a promising compound targeting the TonB-dependent siderophore receptor of F. columnare. In addition, our findings will provide new ideas for the advancement of innovative antimicrobial medications in aquaculture.

Comparative analysis and characterization of the chloroplast genome of Krascheninnikovia ceratoides (Amarathaceae): a xerophytic semi-shrub exhibiting drought resistance and high-quality traits

BACKGROUND

Krascheninnikovia ceratoides, a perennial halophytic semi-shrub belonging to the genus Krascheninnikovia (Amarathaceae), possesses noteworthy ecological, nutritional, and economic relevance. This species is primarily distributed across arid, semi-arid, and saline-alkaline regions of the Eurasian continent, encompassing Inner Mongolia, Xinjiang, Qinghai, Gansu, Ningxia, and Tibet.

RESULTS

We reported the comprehensive chloroplast (cp) genome of K. ceratoides, characterized by a circular conformation spanning 151,968 bp with a GC content of 36.60%. The cp genome encompassed a large single copy (LSC, 84,029 bp), a small single copy (SSC, 19,043 bp), and a pair of inverted repeats (IRs) regions (24,448 bp each). This genome harbored 128 genes and encompassed 150 simple sequence repeats (SSRs). Through comparative analyses involving cp genomes from other Cyclolobeae (Amarathaceae) taxa, we observed that the K. ceratoides cp genome exhibited high conservation, with minor divergence events in protein-coding genes (PCGs) accD, matK, ndhF, ndhK, ycf1, and ycf2. Phylogenetic reconstructions delineated K. ceratoides as the sister taxon to Atriplex, Chenopodium, Dysphania, and Suaeda, thus constituting a robust clade. Intriguingly, nucleotide substitution ratios (Ka/Ks) between K. ceratoides and Dysphania species for ycf1 and ycf2 genes surpassed 1.0, indicating the presence of positive selection pressure on these loci.

CONCLUSIONS

The findings of this study augment the genomic repository for the Amarathaceae family and furnish crucial molecular instruments for subsequent investigations into the ecological adaptation mechanisms of K. ceratoides within desert ecosystems.

Genetics and Genomics of Infectious Diseases in Key Aquaculture Species

Diseases pose a significant and pressing concern for the sustainable development of the aquaculture sector, particularly as their impact continues to grow due to climatic shifts such as rising water temperatures. While various approaches, ranging from biosecurity measures to vaccines, have been devised to combat infectious diseases, their efficacy is disease and species specific and contingent upon a multitude of factors. The fields of genetics and genomics offer effective tools to control and prevent disease outbreaks in aquatic animal species. In this study, we present the key findings from our recent research, focusing on the genetic resistance to three specific diseases: White Spot Syndrome Virus (WSSV) in white shrimp, Bacterial Necrotic Pancreatitis (BNP) in striped catfish, and skin fluke (a parasitic ailment) in yellowtail kingfish. Our investigations reveal that all three species possess substantial heritable genetic components for disease-resistant traits, indicating their potential responsiveness to artificial selection in genetic improvement programs tailored to combat these diseases. Also, we observed a high genetic association between disease traits and survival rates. Through selective breeding aimed at enhancing resistance to these pathogens, we achieved substantial genetic gains, averaging 10% per generation. These selection programs also contributed positively to the overall production performance and productivity of these species. Although the effects of selection on immunological traits or immune responses were not significant in white shrimp, they yielded favorable results in striped catfish. Furthermore, our genomic analyses, including shallow genome sequencing of pedigreed populations, enriched our understanding of the genomic architecture underlying disease resistance traits. These traits are primarily governed by a polygenic nature, with numerous genes or genetic variants, each with small effects. Leveraging a range of advanced statistical methods, from mixed models to machine and deep learning, we developed prediction models that demonstrated moderate-to-high levels of accuracy in forecasting these disease-related traits. In addition to genomics, our RNA-seq experiments identified several genes that undergo upregulation in response to infection or viral loads within the populations. Preliminary microbiome data, while offering limited predictive accuracy for disease traits in one of our studied species, underscore the potential for combining such data with genome sequence information to enhance predictive power for disease traits in our populations. Lastly, this paper briefly discusses the roles of precision agriculture systems and AI algorithms and outlines the path for future research to expedite the development of disease-resistant genetic lines tailored to our target species. In conclusion, our study underscores the critical role of genetics and genomics in fortifying the aquaculture sector against the threats posed by diseases, paving the way for more sustainable and resilient aquaculture development.