Journal of Dairy Science最新文献

The objective of this study was to investigate the mechanistic effects of different milk-derived substrates, cow milk, goat milk, and whey protein concentrate (WPC), on the structural development, microbial succession, and metabolite production of kefir grains during 28 d of continuous subculturing. Kefir grain morphology, microbial community dynamics, and substrate-driven metabolic shifts were analyzed using scanning electron microscopy, culture- and sequencing-based microbial profiling, and untargeted metabolomics. Despite initial differences among substrates, Lactobacillus kefiranofaciens became the dominant bacterium across all treatments, contributing to the structural and metabolic foundation of the grains. Its abundance was greatest in goat milk, intermediate in cow milk, and lowest in WPC, corresponding to differences in substrate-derived CN, peptides, and free AA. Fermentation resulted in a decrease in primary nutrients, such as lactose and palmitic acid, and an increase in secondary metabolites, including short-chain fatty acids, glycine, hydroxykynurenine, and 2',4'-dihydroxyacetophenone. These metabolites acted as cross-feeding substrates and ecological modulators, facilitating competitive and cooperative interactions among yeasts (Kazachstania turicensis, Kluyveromyces marxianus) and lactic acid bacteria (Lactobacillus kefiri, Leuconostoc mesenteroides). Substrate-specific microbial-metabolite networks influenced final kefir grain morphology: goat milk promoted filamentous, extracellular polysaccharide-rich grains; cow milk supported compact and stable grains; and WPC produced fragmented structures with altered metabolite profiles. These findings provide insights into microbial-metabolite interdependencies in kefir grain development and suggest strategies for substrate optimization and targeted starter culture design in functional dairy fermentation.

Type 2 diabetes (T2D) is a global metabolic disorder influenced by diet. While cheese consumption has been suggested to protect against T2D, the mediating metabolic pathways remain unclear. Using Mendelian randomization (MR), we analyzed genetic variants associated with cheese intake (UK Biobank) and their effects on T2D risk (FinnGen) via 249 metabolites. Instrumental variables were selected under stringent criteria. Causal estimates were derived via inverse-variance weighted method, with sensitivity analyses (MR-Egger method) and mediation testing. Cheese intake was inversely associated with T2D risk (odds ratio [OR] = 0.616). Of 249 metabolites, 26 mediated this relationship, including triglycerides (e.g., total triglycerides levels, 3.55% mediation), free cholesterol (e.g., free cholesterol levels in high-density lipoprotein, 5.84%), glucose (3.43%), and albumin (2.69%). Among the 66 metabolites identified as T2D-associated, notable examples included: AA (Phe OR = 1.14, Leu OR = 1.22, Val OR = 1.13), ketone bodies (acetoacetate OR = 1.62, 3-hydroxybutyrate OR = 1.36), and protective factors (albumin OR = 0.871, apolipoprotein A1 OR = 0.871). Cheese consumption may lower T2D risk primarily by modulating lipid metabolites (triglycerides, cholesterol esters) and albumin. These findings highlight novel metabolic pathways for dietary prevention of T2D and underscore the need for research on cheese-specific components (e.g., fermentation byproducts).

Heat stress-induced liver injury is a common and potentially life-threatening complication of heat exposure in both humans and animals. With the ongoing rise in global temperatures, effective preventive strategies are urgently needed. Lactic acid bacteria have been extensively studied and shown to effectively alleviate various types of liver injury; however, their specific role in heat stress-induced liver damage remains unknown. In our previous work, we isolated Lactobacillus plantarum L19 (LP-19), a strain with strong heat resistance and antioxidant capacity, from Holstein cow milk, suggesting its potential to benefit animals and humans under heat stress. This study aimed to investigate the effects of LP-19 against heat stress-induced liver injury using a mouse model. The results showed that oral administration of LP-19 reduced serum alanine aminotransferase and aspartate aminotransferase levels and inhibited liver oxidative stress in mice with heat-stressed liver injury. Immunohistochemistry and quantitative real-time PCR results showed that LP-19 also reduced levels of heat shock proteins and inflammatory factors. Moreover, LP-19 improved intestinal morphology and modulated gut microbiota by increasing beneficial genera such as Lactobacillus and Dorea while decreasing harmful taxa, including Haemophilus and Desulfovibrionaceae. These changes in the microbiota were closely correlated with therapeutic indices. Functional prediction with PICRUSt2 indicated that the LP-19-regulated microbiota may exert its effects primarily through modulating membrane transport, carbohydrate metabolism, and amino acid metabolism. These findings suggest that LP-19 may help prevent heat stress-induced liver injury by modulating the gut microbiota. Consequently, the study highlights the potential of LP-19 as a novel food additive for preventing heat stress-induced liver injury, offering new prospects for the utilization and the development of cow milk-derived lactic acid bacteria.

The aim of this study was to characterize organic dairy systems in Brazil. It was hypothesized that the production level of the herd influences the productivity and marketing aspects of organic milk production systems. A descriptive analysis was carried out in which the variables were geographical location, herd size, animal production, feed used, health and reproduction management, organic inputs used, feed production management, and transportation of products. The characteristics of the systems were evaluated according to the level of production, with farmers divided into 3 groups, with the upper extract comprising farms with an average production of over 16 L/cow per day (HIG), the medium extract with a production between 10.5 and 16 L/cow per day (MED), and the lower extract with an average production of less than 10.5 L/cow per day (LO). The variables were subjected to binomial logistic regression and comparisons were made by odds ratio. The average area of the properties was 107 ha (minimum 3 ha and maximum 1,450 ha); the area for organic milk production was 44 ha (minimum 1 ha and maximum 550 ha). The average daily milk production was 645 L/d (minimum of 12 L/d and maximum of 5,000 L/d), with an average production of 13 L/cow per day (minimum of 4 L/cow per day and maximum of 25 L/cow per day). The herds had an average of 58 cows (minimum 2 cows and maximum 310 cows) and 40 lactating cows (minimum 2 and maximum 255 cows). The average annual production was 7,517 L/ha per year (minimum 21 L/ha per year and maximum 29,877 L/ha per year). The average number of family workers was 2 (minimum 2 and maximum 7); the average number of external workers was 3 (minimum 2 and maximum 16). The HIG and MED farms were found to be 90% less likely to produce cheese. In addition, HIG and MED farms were 10.7 and 6.6 times more likely to have Holstein × Jersey crosses in their herd, respectively. The MED farms were 80% less likely to have Urochloa spp. pastures, whereas HIG farms were 93.2% less likely to have Urochloa spp. pastures and 92% less likely to use chopped grass to supplement the herd. However, the odds of having Megathyrsus maximus pastures was 4.66 times greater for HIG. In addition, HIG farms were 4.5 times more likely to use any type of management software. The analysis of certified organic dairy farms revealed a concentration in the Southeast region of Brazil, where production is mainly focused on milk, whereas other regions have more diversified organic production. The HIG farms are more likely to use specialized cattle breeds, herd supplementation, pastures formed by higher-yielding forage species with greater nutritional value, and management software. These results emphasize the need for public policies that promote the adoption of technological and sustainable practices to increase the efficiency and productivity of the organic dairy sector.

Ensuring high-quality colostrum for newborn calves is essential for their health and future productivity. We applied Bayesian finite mixture models to estimate optimal cutoff values and evaluate the diagnostic accuracy of 3 methods-radial immunodiffusion (RID) assay, transmission infrared (TIR) spectroscopy, and digital Brix (dBrix) refractometry-measured on a continuous scale for assessing bovine colostrum quality, using 591 colostrum samples from 42 Holstein dairy herds in Atlantic Canada. The mean and standard deviation of IgG concentrations for high-quality colostrum were 61.07 ± 39.8 g/L, 51.28 ± 27.38 g/L, and 24.32 ± 4.13% Brix for RID assay, TIR spectroscopy, and dBrix refractometry, respectively, compared with 19.93 ± 15.54 g/L, 7.78 ± 37.4 g/L, and 15.87 ± 3.45% Brix for low-quality samples. The prevalence of high-quality colostrum was estimated at 83% (95% credible interval [CrI]: 0.79-0.88). The dBrix refractometer demonstrated the highest discriminatory power, with an area under the curve (AUC) of 0.94 (95% CrI: 0.91-0.97), followed by RID assay (AUC: 0.92; 95% CrI: 0.88-0.96) and TIR spectroscopy (AUC: 0.82; 95% CrI: 0.76-0.88). Optimal cutoff values were determined using Youden's index: 34.15 g/L for RID assay (sensitivity [Se] = 0.86, specificity [Sp] = 0.83), 22.74 g/L for TIR spectroscopy (Se = 0.88, Sp = 0.66), and 19.62% Brix for dBrix refractometry (Se = 0.90, Sp = 0.85). Correlation between RID assay and TIR spectroscopy was stronger for high-quality colostrum samples (0.80; 95% CrI: 0.77-0.84) than for low-quality samples (0.36; 95% CrI: 0.16-0.55), indicating that these methods are not perfectly correlated and justifying the need for multiple diagnostic approaches. Among individual methods, dBrix refractometry showed the highest positive predictive value (PPV = 1.00), and all methods demonstrated moderate negative predictive values (NPV = 0.46-0.57). Combining methods in series interpretation increased PPV up to 1.00 when all 3 methods were used together, though with reduced NPV. Conversely, parallel interpretation substantially improved NPV, reaching 0.98 when all 3 methods were combined. By modeling continuous measurements instead of dichotomized test results, our analysis produced refined cutoff values for assessing colostrum quality. The findings indicate that existing thresholds remain largely adequate, offering only minor performance improvements, and emphasize the need to balance diagnostic refinements with their potential effects on calf management and passive immunity. Furthermore, our findings suggest that, although individual assessment methods offer valuable diagnostic information, combining multiple methods can optimize either Se or Sp, depending on the interpretation approach, thereby further enhancing the accuracy of colostrum quality evaluation.