Bin Wang

Molting is a critical physiological process for the growth and development of Eriocheir sinensis. Any disruption in this process can significantly affect both survival rates and crab quality. The regulatory mechanisms of molting vary across different stages of the molting cycle and remain poorly understood. In this study, ATAC-seq and RNA-seq were combined to identify the integrated differentially expressed genes (IDEGs) in muscle across adjacent stages of the molting cycle. A total of 17, 491, 84, and 491 IDEGs were identified in the comparisons of inter-molt_vs_pre-molt, pre-molt_vs_molt, molt_vs_post-molt, and post-molt_vs_inter-molt stages, respectively. GO enrichment analysis of these IDEGs revealed several key signaling pathways involved in each adjacent molting stage. The GPCR signaling, steroid hormone-mediated signaling, and smoothened signaling pathways were all active across three molting transitions (pre-molt_vs_molt, molt_vs_post-molt, and post-molt_vs_inter-molt). Among them, the GPCR pathway played a dominant role throughout the process. Further structural analysis and RT-qPCR validation identified eight GPCRs involved in molting regulation: GRM7 and moody were specific to the post-molt_vs_inter-molt stage; Kpna6, ADRB2, and SSTR2 were unique to the pre-molt_vs_molt stage; FMRFaR and gpr161 functioned in both post-molt_vs_inter-molt and pre-molt_vs_molt stages; and mth2 was active in both post-molt_vs_inter-molt and molt_vs_post-molt stages. These findings improve the understanding of molting regulation and provide potential targets for further genetic improvement in E. sinensis.

Vibrio parahaemolyticus is a pathogenic bacterium widely distributed in marine environments, posing significant threats to aquatic organisms and human health. The overuse and misuse of antibiotics has led to the development of multidrug- and pan-resistant V. parahaemolyticus strains. There is an urgent need for novel antibacterial therapies with innovative mechanisms of action. In this work, a genome-scale metabolic network model (GMSN) of V. parahaemolyticus, named VPA2061, was reconstructed to predict the metabolites that can be explored as potential drug targets for eliminating V. parahaemolyticus infections. The model comprises 2061 reactions and 1812 metabolites. Through essential metabolite analysis and pathogen–host association screening with VPA2061, 10 essential metabolites critical for the survival of V. parahaemolyticus were identified, which may serve as key candidates for developing new antimicrobial strategies. Additionally, 39 structural analogs were found for these essential metabolites. The molecular docking analysis of the essential metabolites and structural analogs further investigated the potential value of these metabolites for drug design. The GSMN reconstructed in this work provides a new tool for understanding the pathogenic mechanisms of V. parahaemolyticus. Furthermore, the analysis results regarding the essential metabolites hold profound implications for the development of novel antibacterial therapies for V. parahaemolyticus-related disease.

Embryonic diapause is a common evolutionary adaptation observed across a wide range of organisms. Artemia is one of the classic animal models for diapause research. The current studies of Artemia diapause mainly focus on the induction and maintenance of the embryonic diapause, with little research on the molecular regulatory mechanism of Artemia embryonic reactivation. The first 5 h after embryonic diapause breaking has been proved to be most important for embryonic reactivation in Artemia. In this work, two high-throughput sequencing methods, ATAC-seq and RNA-seq, were integrated to study the signal regulation process in embryonic reactivation of Artemia at 5 h after diapause breaking. Through the GO and KEGG enrichment analysis of the high-throughput datasets, it was showed that after 5 h of diapause breaking, the metabolism and regulation of Artemia cyst were quite active. Several signal transduction pathways were identified in the embryonic reactivation process, such as G-protein-coupled receptor (GPCR) signaling pathway, cell surface receptor signaling pathway, hormone-mediated signaling pathway, Wnt, Notch, mTOR signaling pathways, etc. It indicates that embryonic reactivation is a complex process regulated by multiple signaling pathways. With the further protein structure analysis and RT-qPCR verification, 11 GPCR genes were identified, in which 5 genes function in the embryonic reactivation stage and the other 6 genes contribute to the diapause stage. The results of this work reveal the signal transduction pathways and GPCRs involved in the embryonic reactivation process of Artemia cysts. These findings offer significant clues for in-depth research on the signal regulatory mechanisms of the embryonic reactivation process and valuable insights into the mechanism of animal embryonic diapause.

Eriocheir sinensis is an economically important aquatic animal. Its regulatory mechanisms underlying many biological processes are still vague due to the lack of systematic analysis tools. The protein–protein interaction network (PIN) is an important tool for the systematic analysis of regulatory mechanisms. In this work, a novel machine learning method, DGO-SVM, was applied to predict the protein–protein interaction (PPI) in E. sinensis, and its PIN was reconstructed. With the domain, biological process, molecular functions and subcellular locations of proteins as the features, DGO-SVM showed excellent performance in Bombyx mori, humans and five aquatic crustaceans, with 92–96% accuracy. With DGO-SVM, the PIN of E. sinensis was reconstructed, containing 14,703 proteins and 7,243,597 interactions, in which 35,604 interactions were associated with 566 novel proteins mainly involved in the response to exogenous stimuli, cellular macromolecular metabolism and regulation. The DGO-SVM demonstrated that the biological process, molecular functions and subcellular locations of proteins are significant factors for the precise prediction of PPIs. We reconstructed the largest PIN for E. sinensis, which provides a systematic tool for the regulatory mechanism analysis. Furthermore, the novel-protein-related PPIs in the PIN may provide important clues for the mechanism analysis of the underlying specific physiological processes in E. sinensis.