NPJ Science of Food最新文献

Non-alcoholic fatty liver disease (NAFLD) is a prevalent metabolic disorder with limited treatment options. This study investigated the therapeutic potential of water extract of Ajania fruticulosa (WEAF) against NAFLD in cellular and animal models. WEAF significantly attenuated obesity, lipid accumulation, liver injury, and inflammation in NAFLD mice. Next, UPLC-MS/MS-based network pharmacology and molecular biology revealed that WEAF alleviated NAFLD by TLR2-mediated MYD88/NF-κB and SREBP1/PPAR-γ pathways, with 3,4-dihydroxyphenylpropionic acid, glycitein, and isorhapontigenin identified as the primary bioactive compounds. Finally, molecular docking, molecular dynamics, drug affinity responsive target stability, and cellular thermal shift assay confirmed that glycitein and isorhapontigenin directly bind to TLR2 to modulate the NF-κB/PPAR-γ signaling, and their anti-NAFLD effects were abolished by TLR2 agonist Pam3CSK4. In conclusion, WEAF and its key active compounds, glycitein and isorhapontigenin, effectively ameliorate obesity-induced NAFLD via the NF-κB/PPAR-γ signaling pathway by targeting TLR2, supporting their potential as therapeutic target and agents for NAFLD.

We previously reported inverse associations of coarse grain (CG) intake with blood pressure, mediated by metabolites and gut microbiota. In this 12-week randomized controlled trial among 172 prehypertension participants, both the CG (100 g/day) group and the control group (refined grain) showed significant reductions in systolic blood pressure (SBP) and diastolic blood pressure (DBP) over 12 weeks, with no significant time by group interaction. In the exploratory analyses of secondary outcomes, significant time by group interactions were detected for 26 taxa (such as g__Lactococcus and g__Faecalibacterium), associated with 23 differential fecal metabolites, which in turn were correlated with blood pressure changes over the CG intervention. Microbial ATP-binding cassette transporter was highlighted in the pathway annotation for the CG-derived differential microbial taxa. Baseline gut microbiota exhibited predictive potential for blood pressure reduction, while host ABO variance rs514659 modulated the intervention effect on SBP and DBP (P interaction < 0.05), providing preliminary evidence for the tailored nutrition strategies optimizing blood pressure and gut microbiota profiles.

Modern nutrition science still lacks a comprehensive, machine-readable map linking diet to molecular composition and biological effects. Here we present FoodAtlas, a large-scale knowledge graph that links 1430 foods to 3610 chemicals, 2181 diseases, and 958 flavor descriptors through 96,981 provenance-tracked edges. A transformer-based text-mining pipeline extracted 48,474 quantitative food-chemical associations from 125,723 literature sentences (F₁ = 0.67) and integrated them with 23,211 chemical-disease assertions from the Comparative Toxicogenomics Database, 15,222 chemical-bioactivity records from ChEMBL, 3645 flavor annotations from FlavorDB and PubChem, and 6429 taxonomic relationships. Graph embeddings revealed six dietary modules whose signature metabolites delineate distinct, multisystem disease-risk trajectories. Models built on FoodAtlas demonstrate practical utility: a bioactivity predictor achieved strong correlation with antioxidant assays (R² = 0.52; ρ = 0.72), and a substitution engine reduced simulated total disease risk by 11.9%.

Real-world data help clarify the contribution of food to nutrition, the environment, and food expenditure. We studied the implications of a hypothetical transition in protein sources for these sustainability dimensions using loyalty-card holders' (n = 22,901) food purchases. Six consumer clusters were identified via sequence analysis, representing realistic transitions in protein sources alongside other food consumption changes. Cross-sectional comparisons revealed that higher expenditure of Plant-based and Fish clusters per 2500 kcal was largely driven by other food groups than the protein sources, while the protein source expenditure was relatively consistent across clusters. Environmental impact differences were largely attributable to the protein sources, with meat and fish contributing the most. Aside from protein sources, discretionary foods accounted for 22% of spending and contributed up to 17-32% of environmental impacts. Therefore, alongside protein source changes, reducing discretionary food consumption could yield notable environmental benefits and allow reallocation of expenditure towards more nutritious foods.

The popularity of low-temperature dairy products is challenged by Bacillus species, whose heat-resistant spores and biofilms often survive pasteurization. Moreover, heat treatment can paradoxically enhance biofilm formation in some Bacillus spp., a phenomenon whose metabolic basis is not fully understood. Combining untargeted metabolomics with random forest analysis, we decoded the metabolic adaptations behind this heat-induced biofilm enhancement in raw milk Bacillus isolates. Our results demonstrate strain-specific mechanisms: in BC01, heat stress activated glutaminase, depleting L-glutamine and free histidine to relieve metabolic inhibition and activate biofilm genes, while reduced xanthosine promoted the biofilm-state transition. In BS01, metabolic network restructuring led to decreased synthesis of arginine, D-amino acid, dopamine, and arachidonic acid, thereby mitigating their known inhibitory effects on biofilm formation. This study clarifies the metabolic drivers of biofilm adaptation under heat stress, highlighting novel targets for metabolic intervention in dairy safety.

Aflatoxin contamination is a major food safety concern and has a particularly negative impact on peanuts. Climate conditions are known to influence the natural occurrence of mycotoxins; however, the specific impacts of climate change on the prevalence of aflatoxin remain poorly understood. In this study, we analysed a national-scale dataset comprising 17263 records of peanut aflatoxin B₁ (AFB₁) contamination in China from 2009 to 2022. Our results revealed that the occurrence of AFB₁ contamination in 2017 and 2021 significantly increased compared with that in 2009. The key climatic drivers included nighttime temperature, wind speed, and precipitation. Notably, temperature variations explain 49.46% of the observed increase. In a high-emissions scenario, future projections estimated that AFB₁ contamination would reach 15.06 μg·kg⁻¹ by the end of the century, representing a 8.50% increase relative to the current level. In 2022, the AFB₁ level in approximately 478,400 metric tons of peanuts exceeded the regulatory limit, and the amount was projected to rise to 1.16 million metric tons by 2100. These results underscore the urgent need to enhance aflatoxin surveillance and develop proactive strategies to mitigate aflatoxin contamination under accelerating climate change.

Pesticide residue analysis in food is frequently carried out worldwide, often requiring a large volume of organic solvents. To improve sustainability, new generation solvents such as natural deep eutectic solvents (NADES) have recently emerged as a promising alternative to conventional solvents. This study demonstrates the applicability of NADES as green extraction solvents for pesticides in food samples prior to analysis by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). The present research goes beyond previous studies by covering an extended set of pesticide residues. For that, five hydrophilic and hydrophobic NADES were evaluated as extraction solvents in a solid-liquid extraction (SLE). Initially, eleven representative pesticides covering a broad range of chemical classes and physicochemical properties were selected, while food matrices were chosen to cover different commodity groups according to SANTE/11312/2021v2, including orange, wheat, and spinach. NADES were tailored in order to cover a wide range of physicochemical properties such as polarity, pH, and viscosity. Thymol: menthol (molar ratio, 1:1) was found to be the most effective, and key extraction parameters were optimized. The greenness and transferability of the NADES-based SLE were evaluated using the AGREEprep and BAGI metrics. Finally, the method was successfully validated for the extraction of a wide range of pesticides commonly analyzed in food safety assessments.

Fusarium wilt diseases pose a huge threat to faba bean (Vicia faba L.) production globally, with significant outbreaks in Chongqing, China. Symptomatic plants showed wilting leaves and rotten roots, ultimately perishing in the advanced stage. Morphological features, multilocus phylogenetic analyses, and pathogenicity tests demonstrated that the primary causal agent was Fusarium oxysporum. Untargeted metabolomics of faba beans revealed substantial metabolic differences in the infected faba bean roots. Plants responded to fungal biotic stress by reprogramming key metabolic pathways, including alanine, aspartate, and glutamate metabolism, the citrate cycle, arginine biosynthesis, and jasmonic acid metabolism, which collectively underscore activated defense responses. Metagenome sequencing showed that Fusarium wilt significantly reshaped the structure of the rhizosphere microbiota and affected the abundance of genes encoding element cycling in soil. This work elucidates the pathogenic mechanisms of F. oxysporum by integrating pathogen identification, host metabolism, and microbiome ecology. Our findings offer biomarkers for disease diagnosis and targets for biocontrol, advancing sustainable management of Fusarium wilt diseases in legumes.

Metal accumulation in rice grains influenced both nutritional composition and consumer-perceived eating quality. Concentrations of 26 metal elements were quantified in 36 rice samples by ICP-MS, and hierarchical cluster analysis grouped the samples into three categories. ANOVA revealed significant differences in essential elements (Ca, Mg, Zn, Cu) and non-essential or potentially toxic elements (Al, Ba, B), highlighting their contribution to classification. Sensory evaluation of representative samples demonstrated pronounced variation in odor, taste, palatability, and overall eating quality. Pearson correlation and PLSR-VIP analyses identified Ag, Al, B, Ba, Co, and V as strongly and negatively associated with sensory traits, whereas Ca and Fe exerted attribute-specific effects. Electronic tongue analysis with PCA achieved clear group separation, and a SVM model reached 93% overall accuracy. These results established a close linkage between elemental profiles and sensory performance, providing a framework for rapid, objective, and non-destructive rice quality assessment.