NPJ Science of Food最新文献

This study aimed to identify novel saltiness-enhancing peptides derived from Pleurotus eryngii and evaluate their influence on saltiness perception. Utilizing an integrated virtual screening strategy, 6 candidate peptides exhibiting potential saltiness-enhancing properties were identified. Sensory analysis revealed that these peptides displayed distinct taste profiles, with detection thresholds ranging between 0.04 and 0.12 mmol/L. Notably, peptides AGHDDFP, GYDTF, and NGYDMR enhanced the saltiness of a 3 mg/mL NaCl solution, demonstrating synergistic or additive effects, consistent with electronic tongue. Molecular docking analysis revealed that three saltiness-enhancing peptides primarily interacted with TMC4 through hydrogen bonding, identifying key interaction residues including Gln527, Glu531, Asp491, Asn404, Arg437, Lys567, Pro409, and Val498. Subsequent molecular dynamics simulations confirmed the structural stability and tightness of saltiness-enhancing peptides-TMC4 complexes, supporting their potential effectiveness in modulating saltiness perception. These results indicate a promising approach for identifying saltiness-enhancing peptides derived from Pleurotus eryngii, potentially serving as taste modulators in reduced-sodium food formulations.

Due to the significant healthcare burden associated with foodborne illness, developing platforms suitable for the on-site detection of food pathogens is of critical importance to public health. Low-cost, equipment-free approaches are desired to allow for point-of-use contamination monitoring along the food supply chain. Here, we demonstrate the compatibility of an Escherichia coli responsive colorimetric DNAzyme-crosslinked hydrogel sensor with a wide range of food products. Sensor functionality involves an E. coli detecting DNAzyme-substrate complex that cleaves the hydrogel crosslinking in the presence of the target bacteria, resulting in a release of gold nanoparticles that is visible to the naked eye. Naked-eye detection of E. coli at concentrations of 10⁵ CFU mL^-1 has been shown in milk as well as samples extracted from produce, leafy greens, and ready-to-eat foods such as rotisserie chickens. The functionality, simplicity, and versatility of this sensing platform may improve the feasibility of frequent pathogen monitoring in the food production pipeline, with the potential to mitigate future outbreaks of foodborne illness.

T-2 toxin is a typical mycotoxin that seriously threatens human and animal health. Liver is the major target organ of T-2 toxin. To elucidate the precise hepatotoxicity mechanism and discover a natural antagonist of T-2 toxin. T-2 toxin (0, 0.5, 1, 2 mg/kg BW)-induced liver injury model, Ferrostatin-1 (1 mg/kg·BW) interference model, Parkin^-/- mice model, Nrf2-activating model (tBHQ, 20 mg/kg·BW) and lycopene (5 mg/kg·BW) treatment model were constructed. Proteomics revealed that ferroptosis is a critical hepatotoxicity mechanism of T-2 toxin. Blocking ferroptosis alleviated the liver damage and mitophagy under T-2 toxin threat. However, these processes were exacerbated in Parkin^-/- mice. In vivo mouse model confirmed that Nrf2 activation increased PINK-Parkin mediated mitophagy and alleviated T-2 toxin-induced ferroptosis, suggesting that Nrf2/mitophagy axis was involved in T-2 toxin-induced hepatic ferroptosis. Further analysis revealed that lycopene promoted Nrf2 nuclear translocation and PINK-Parkin mediated mitophagy to mitigate T-2 toxin-induced hepatic ferroptosis.

The quality of fermented foods is governed by the composition, function, and interactions of their microbial communities. However, fermentations carried out using traditional approaches are often variable with respect to their composition and are difficult to control, thereby limiting industrial reproducibility. Recent advances in omics technologies-including metagenomics, metatranscriptomics, metaproteomics, metabolomics, and culturomics-have greatly enhanced our ability to analyze and reconstruct the microbial ecosystems in fermented foods. This review first highlights the importance of omics analyses for characterizing microbial composition, metabolic potential, and functional interactions. It then discusses the bipartite structure of defined microbial consortia (DMCs), distinguishing between the core microbiome, comprising taxa consistently associated with fermentation performance, and the supplementary microbiome, consisting of variable species that influence flavor diversity and system stability. Finally, we describe a multi-omics-guided strategy for the design and refinement of DMCs, framed within the Assembly-Assessment-Redesign (A-A-R) workflow, which enables iterative optimization of microbial consortia for reproducible and desirable fermentation outcomes. Integrating omics insights with DMC engineering provides a systematic approach for precision fermentation, paving the way for next-generation fermented food production.

Dental caries is a highly prevalent non-communicable disease driven by dysbiosis of the oral microbiota, in which Streptococcus (S.) mutans plays a keystone role. We discovered that cell-free supernatant (CFS) from food-associated Lacticaseibacillus (L.) paracasei disrupts S. mutans membranes, causing leakage, reduced viability, and decreased surface hydrophobicity. CFS also inhibits biofilms by decreasing biomass, metabolic activity, chain length, and exopolysaccharide (EPS) accumulation. Neutralization experiments revealed organic acids as the primary antibacterial factors: activity weakened at pH > 6 but remained stable after heating and long-term storage. In a hydroxyapatite disc model, CFS markedly suppressed biofilm formation and reduced free calcium release, indicating lower cariogenic potential. Transcriptomic analysis revealed downregulation of virulence and quorum-sensing genes (including stsR, gbpA, gbpB, scrB, ldh, aguB, atpA, atpD, luxS, ciaR, ciaH, and ciaX), while metabolomic studies identified creatine and phosphoenolpyruvate as key metabolites linked to these pathways. Our findings demonstrate that L. paracasei postbiotics can act as stable, food-compatible ingredients to modulate cariogenic biofilms, providing a mechanistic basis for developing next-generation postbiotic-based oral care and functional food products. This work connects the science of food-derived postbiotics with oral health, contributing to a One Health approach to caries prevention.

Food is a more complex system than commonly perceived, comprising tens of thousands of molecules whose compositions and interactions ultimately shape human perception. To conceptualize this multifaceted nature, we frame food complexity across three interconnected layers: the molecular composition that defines its chemical foundation, the component interactions that shape food properties, and the perceptual responses that arise from human sensory systems. This review discusses how machine learning is advancing our ability to decode each of these layers, together with multimodal and data-fusion frameworks. Understanding these three layers may enable more accurate prediction of food properties, guide food product innovation, and deepen our scientific understanding of food.

Adulteration of olive oil significantly compromises the interests of both producers and consumers, making its authentication a crucial challenge in the food industry. This study explored the potential of combining Raman spectroscopy with machine learning for discriminating various blended samples and quantifying olive oil content in mixtures. Raman features, such as peak intensities at specific shifts, were extracted from the spectra and analyzed using hierarchical cluster analysis (HCA) and correlation analysis (CA) to identify significant variations corresponding to altered proportions of olive oil. Qualitative and quantitative analyses were performed to classify 10 oil types and predict compositional ratios in binary and ternary blends, comparing different chemometric techniques and input features. Among these, the random forest (RF) model yielded a high classification accuracy (98.9%) and strong predictive performance, with coefficients of determination (R²) of 0.985 and 0.926 on the binary and ternary samples, respectively. The Shapley additive explanations (SHAP) algorithm was subsequently employed to assess the contribution of key Raman features to the prediction accuracy of superior models. Overall, this novel analytical framework highlights Raman features and offers a promising solution for real-time quality monitoring of olive oil products.

Controlling protein solubility is critical yet challenging for food and pharmaceutical applications. This review dissects the molecular and environmental determinants governing solubility behavior. It integrates traditional modification strategies with emerging artificial intelligence-driven approaches, emphasizing the transition from empirical trial-and-error to data-driven rational design. This work provides a systematic framework to advance protein engineering solutions across diverse industrial sectors.

This study examined the growth-stage-dependent metabolic variations in tatsoi microgreens (TM) and baby greens (TBG) through the application of flavoromics, metabolomics, and network pharmacology. The HS-SPME-GC/MS analysis identified 526 volatile organic compounds, with TM predominantly exhibiting green, cucumber, melon, and nutty aromas, whereas TBG developed more complex fruity, floral, and creamy notes attributed to esters and ketones. The UPLC-QqQ-MS analysis detected 1475 non-volatile metabolites, revealing that TBG had elevated levels of phenolic acids, lignans, coumarins, and specific glucosinolates, while TM contained higher concentrations of flavonoids. Network pharmacology analysis identified 113 metabolites with potential multi-target mechanisms effective against metabolic disorders, such as obesity, type 2 diabetes mellitus, and non-alcoholic fatty liver disease, as well as cardiovascular diseases, including hypertension, atherosclerosis, and myocardial infarction. This comprehensive approach underscores the potential of tatsoi, particularly at various growth stages, as a valuable source of flavor compounds and bioactive ingredients for functional foods.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease with persistent colonic inflammation and inadequate therapeutic options. The medicinal and edible plant Polygonatum cyrtonema Hua from Jiuhua Mountain contains polysaccharides with potent anti-inflammatory activities. In this study, a low-molecular-weight fructan (Mw = 2087 Da), designated PCP2, was isolated and purified from its rhizome. Biologically, PCP2 administration markedly alleviated disease severity in dextran sulfate sodium (DSS)-induced colitis mice, as shown by the improvement in multiple indicators of colon injury and inflammation. Fecal microbiota transplantation and antibiotic depletion experiments revealed that the protective effects of PCP2 are mediated through both modulation of the gut microbiota and additional microbiota-independent pathways. Importantly, through molecular dynamics simulations, microscale thermophoresis, and surface plasmon resonance assays, follistatin (Fst) is identified as a direct binding target of PCP2. Functional validation using siRNA-mediated Fst knockdown in Caco-2 cells, combined with adenovirus-mediated knockdown in the murine colon, confirmed that PCP2 exerts its therapeutic effect by directly interacting with Fst and suppressing the BMP4/Smad1/ID1 signaling axis. In summary, PCP2 ameliorates ulcerative colitis via dual mechanisms involving restoration of gut microbiota homeostasis and direct targeting of Fst. These findings establish a novel therapeutic strategy and support the clinical development of P. cyrtonema Hua from Jiuhua Mountain as a functional food for intestinal health.