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PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗
PubMed2026

Herbicolin A, an antifungal lipopeptide produced by Pantoea agglomerans APC 4211 is a promising biocontrol agent against food spoilage fungi.

Fungal contamination of food with yeast and molds is associated with major economic losses due to spoilage and also poses health risks in the form of mycotoxin production. The strain Pantoea agglomerans APC 4211 isolated from leaves of Ilex aquifolium (holly tree) has broad spectrum antifungal activity against a variety of food spoilage fungi. Genomic analysis of the strain confirmed the presence of biosynthetic gene clusters potentially encoding for the enzymatic machinery required for the production of the antifungal lipopeptide herbicolin A. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis of the cell-free supernatant (CFS) confirmed the presence of molecular masses corresponding to herbicolin A (1300.8 Da), and herbicolin B (1138 Da). Purified herbicolin A has desirable properties for biotechnological applications, including potent antifungal activity against a range of spoilage fungi, thermal stability and resistance to proteases. The lipopeptide has low cytotoxicity against epithelial cell lines and has minimum inhibitory concentrations (MICs) lower than those of some commercial antifungal drugs (0.2-2.5 mg/L). In a model dairy system (10% skim milk), herbicolin A demonstrated excellent solubility and stability, effectively eliminating Aspergillus niger and Penicillium notatum at a concentration of 5 mg/L. Overall, the study determines herbicolin's A spectrum against food spoilage organisms and examines potential applications in food. In conclusion, herbicolin A is a potent, naturally occurring antifungal agent with the potential to be applied as a biopreservative in food systems, providing a safe, clean-label, and efficient compound for synthetic preservatives replacement.

Pantoea↗
PubMed2026

Genomic diversity and thermal niches of Aspergillus molds disrupting rind formation of surface-ripened cheeses.

Filamentous fungi play important roles in the development of surface-ripened cheese microbial communities and contribute to the aesthetics and flavors of these products. Much is known about the diversity and ecology of desirable cheese fungi, but our understanding of the natural history of cheese spoilage molds is limited. The goal of this work was to characterize the genomic diversity of Aspergillus species contaminating artisan cheeses and to identify how the abiotic environment of cheese (the substrate itself and temperature) may constrain the growth of Aspergillus. Comparative genomics identified two main species of Aspergillus, A. westerdijkiae and A. ostianus, as the spoilage molds across three different facilities in the Northeastern United States that experienced contamination events. Multiple genomic types of A. westerdijkiae were found across the different cheese production facilities, indicating that these contamination events are not caused by a single clonal strain. All A. westerdijkiae isolates produced ochratoxin A, but concentrations varied greatly across strains. RNA-sequencing of A. westerdijkiae on nutrient-rich lab media (malt extract agar) versus cheese curd agar identified a suite of pathways enriched in expression on cheese, including degradation of amino and fatty acids. Experiments measuring growth over a range of temperatures identified that spoilage Aspergillus species have a higher optimal growth temperature compared to desirable fungal species in cheese rinds and are outcompeted by Penicillium species at temperatures lower than 15°C. Global fungal metabarcoding databases suggest that A. westerdijkiae is not normally found in natural habitats of the Northeastern United States, and it may be introduced to this region.IMPORTANCEOver the past decade, disruptive contamination events of Aspergillus spoilage molds have occurred at cheese production facilities in Massachusetts, Connecticut, and Vermont in the United States, causing aesthetic, flavor, and potential safety issues. Our work highlights independent introductions of different strains of A. westerdijkiae into multiple cheese facilities and suggests that temperature could be used to control the abundance of Aspergillus spoilage molds. Based on our analysis of the global distribution of A. westerdijkiae, it is not invading cheese facilities from local fungal populations and may be a contaminant in materials used for cheese production.

Aspergillus↗
PubMed2026

Intestinal content accelerates muscle protein degradation in red shrimp (Solenocera crassicornis) during refrigeration: Insights from metagenomics and metabolomics.

This study systematically explored the effects of intestinal components on muscle quality deterioration and protein degradation of red shrimp during refrigerated storage. The results demonstrated that refrigeration induced continuous quality degradation and muscle protein breakdown in red shrimp, whereas eliminating intestinal tissues effectively retarded muscle spoilage and protein degradation, and optimized muscle texture. The intestinal microorganisms could secrete extracellular proteases to promote muscle protein degradation were primarily Vibrio, Bacillus, Pseudomonas, Photobacterium, and Shewanella. These microorganisms promote protein degradation by secreting zinc proteases, serine proteases, and aspartyl proteases. This study elucidates the molecular mechanisms of intestinal microbial metabolism influences the muscle protein degradation of red shrimp during refrigeration. The findings provide a theoretical foundation for precise regulation of intestinal-targeted microorganisms, thereby maintaining optimal quality of shrimps during refrigeration.

Animals↗