Integrative proteome and metabolome analyses reveal molecular basis underlying growth and nutrient composition in the Pacific oyster, Crassostrea gigas

Novel model organisms and proteomics for a better biological understanding

The concept of « model organisms » is being revisited in the light of the latest advances in multi-omics technologies that can now capture the full range of molecular events that occur over time, regardless of the organism studied. Classic, well-studied models, such as Escherichia coli, Saccharomyces cerevisiae, to name a few, have long been valuable for hypothesis testing, reproducibility, and sharing common platforms among researchers. However, they are not suitable for all types of research. The complexity of unanswered questions in biology demands more elaborated systems, particularly to study plant and animal biodiversity, microbial ecosystems and their interactions with their hosts if any. More integrated systems, known as « holobionts », are emerging to describe and unify host organisms and associated microorganisms, providing an overview of all their possible interactions and trajectories. Comparative evolutionary proteomics offers interesting prospects for extrapolating knowledge from a few selected model organisms to others. This approach enables a deeper characterization of the diversity of proteins and proteoforms across the three branches of the tree of life, i.e. Bacteria, Archaea, and Eukarya. It also provides a powerful means to address remaining biological questions, such as identifying the key molecular players in organisms when they are confronted to environmental challenges, like anthropogenic toxicants, pathogens, dietary shifts or climate stressors, and proposing long-term sustainable solutions. SIGNIFICANCE: In this commentary, we reevaluated the concept of "model organisms" in light of advancements in multi-omics technologies. Traditional models have proven invaluable for hypothesis testing, reproducibility, and fostering shared research frameworks. However, we discussed that they are not universally applicable. To address complexities such as biodiversity and understand microbial ecosystems and their host interactions, integrated systems like "holobionts," which encompass host organisms and their associated microbes, are gaining prominence. Comparative evolutionary proteomics further enhances our understanding by enabling detailed exploration of protein diversity across organisms. This approach also facilitates the identification of critical molecular players in organisms facing environmental challenges, such as pollutants, pathogens, dietary changes, or climate stress, and contributes to developing sustainable long-term solutions.

Wnt signaling pathway and retinoic acid signaling pathway involved in delamination and migration of chicken trunk NCCs and contributing to HVP phenotype

Hyperpigmentation of the visceral peritoneum (HVP) is a hereditary trait that significantly affects the carcass quality in bearded chickens, yet its molecular mechanisms remain unclear. This study utilized data-independent acquisition proteomics to analyze the protein expression profiles of black peritoneum (B), faded peritoneum (F), and normal peritoneum (N) in bearded chickens at 40 and 120 d of age. Combined with histopathological and functional enrichment analyses, we revealed the regulatory network underlying HVP formation. Results indicated that the melanin content was significantly elevated in HVP samples, without accompanying inflammatory responses or tumor characteristics, suggesting that its formation is driven by developmental abnormalities. A total of 9,375 high-confidence proteins were identified through proteomics, with differentially abundant proteins at 40 d of age (219 proteins) primarily enriched in ribosomal function, tyrosine metabolism, and melanin synthesis pathways. In comparison, at 120 d of age (246 proteins), they were enriched in transcription regulation and chromatin remodeling pathways. The abnormal expression of key co-expressed proteins DHRS3 and DACT1 suggests that the dysregulation of retinoic acid (RA) and the Wnt signaling pathway may promote the directed differentiation of melanocytes by regulating neural crest cells (NCCs). The reduced abundance of the chondroitin sulfate proteoglycan, VCAN, weakened the peritoneal barrier function, whereas estradiol accelerated melanin synthesis via hormonal microenvironmental regulation. Furthermore, the formation of HVP led to a reprogramming of energy metabolism, reduced fat deposition, and a downregulation of immune-related molecules, implying that pigment deposition may weaken the chicken immune response. This study systematically elucidates the molecular mechanisms of HVP and provides potential targets for molecular breeding of HVP.

Integrative Utilization of Transcriptomics and Metabolomics Sheds Light on Disparate Growth Performance of Whiteleg Shrimp, Litopenaeus vannamei

Litopenaeus vannamei is a key economic species in aquaculture, yet the molecular mechanisms underlying its growth variability remain unclear. This study conducted transcriptomic and metabolomic analyses of fast-growing (NL) and slow-growing (NS) shrimp under identical conditions. A total of 1280 differentially expressed genes (DEGs) related to protein processing, ribosomes, and oxidative phosphorylation, along with 5297 differentially abundant metabolites (DMs) involved in arginine biosynthesis, amino acid metabolism, and pantothenate and CoA biosynthesis, were identified and analyzed. An integrative analysis revealed that the NL shrimp exhibited an enhanced retinol, glutathione, riboflavin, and purine metabolism, which implies a higher tolerance to environmental stress. In contrast, the NS shrimp showed increased fatty acid degradation and an accelerated TCA cycle. This suggests that NS shrimp might require a substantial amount of energy to cope with environmental changes, consequently resulting in increased energy expenditures. This study provides significant insights into the molecular mechanisms underlying the growth disparity in L. vannamei, offering valuable data for future research aimed at optimizing shrimp growth performance and enhancing aquaculture productivity.

Intelligent Evaluation and Dynamic Prediction of Oysters Freshness with Electronic Nose Non-Destructive Monitoring and Machine Learning

Physiological and environmental fluctuations in the oyster cold chain can lead to quality deterioration, highlighting the importance of monitoring and evaluating oyster freshness. In this study, an electronic nose was developed using ten partially selective metal oxide-based gas sensors for rapid freshness assessment. Simultaneous analyses, including GC-MS, TVBN, microorganism, texture, and sensory evaluations, were conducted to assess the quality status of oysters. Real-time electronic nose measurements were taken at various storage temperatures (4 °C, 12 °C, 20 °C, 28 °C) to thoroughly investigate quality changes under different storage conditions. Principal component analysis was utilized to reduce the 10-dimensional vectors to 3-dimensional vectors, enabling the clustering of samples into fresh, sub-fresh, and decayed categories. A GA-BP neural network model based on these three classes achieved a test data accuracy rate exceeding 93%. Expert input was solicited for performance analysis and optimization suggestions enhanced the efficiency and applicability of the established prediction system. The results demonstrate that combining an electronic nose with quality indices is an effective approach for diagnosing oyster spoilage and mitigating quality and safety risks in the oyster industry.

Flexible Sensing Enabled Nondestructive Detection on Viability/Quality of Live Edible Oyster

Environmental and physiological fluctuations in the live oyster cold chain can result in reduced survival and quality. In this study, a flexible wireless sensor network (F-WSN) monitoring system combined with knowledge engineering was designed and developed to monitor environmental information and physiological fluctuations in the live oyster cold chain. Based on the Hazard Analysis and Critical Control Point (HACCP) plan to identify the critical control points (CCPs) in the live oyster cold chain, the F-WSN was utilized to conduct tracking and collection experiments in real scenarios from Yantai, Shandong Province, to Beijing. The knowledge model for shelf-life and quality prediction based on environmental information and physiological fluctuations was established, and the prediction accuracies of TVB-N, TVC, and pH were 96%, 85%, and 97%, respectively, and the prediction accuracy of viability was 96%. Relevant managers, workers, and experts were invited to participate in the efficiency and applicability assessment of the established system. The results indicated that combining F-WSN monitoring with knowledge-based HACCP modeling is an effective approach to improving the transparency of cold chain management, reducing quality and safety risks in the oyster industry, and promoting the sharing and reuse of HACCP knowledge in the oyster cold chain.