Milk urea nitrogen (MUN) is widely used as an indicator of dietary energy–protein balance and nitrogen utilization efficiency in dairy cows, but the ruminal microbial and metabolic basis of MUN variation remains insufficiently understood. Here, we integrated milk trait measurements with rumen metagenomics and untargeted metabolomics to compare eight high-milk urea nitrogen (HMUN, 16.6 ± 0.48 mg/dL) and seven low-milk urea nitrogen (LMUN, 11.7 ± 0.34 mg/dL) cows. Compared with LMUN cows, HMUN cows exhibited higher MUN yield (P < 0.01) and urinary nitrogen excretion (P < 0.05), with a tendency toward higher ruminal NH₃-N concentration (P = 0.059). In contrast, LMUN cows exhibited higher MCP yield (P < 0.05), a greater MPY/MUNY ratio (P < 0.001), and a tendency toward higher milk protein yield (P = 0.058). Dry matter intake, milk yield, and major ruminal volatile fatty acid concentrations did not differ substantially between groups, suggesting that divergence in MUN phenotype was primarily associated with differences in ruminal nitrogen capture and partitioning rather than overall production performance. Multi-omics analyses revealed distinct and coordinated ruminal microbial, functional, and metabolic profiles between the two phenotypes. HMUN cows were characterized by enrichment of Prevotella, Bacteroides, Hallella, and Treponema and by greater representation of amino acid catabolic pathways, particularly branched-chain amino acid degradation. In contrast, LMUN cows showed enrichment of Butyrivibrio, Pseudobutyrivibrio, Eubacterium, and Clostridium, together with pathways related to pyruvate metabolism, the pentose phosphate pathway, sulfur metabolism, and amino acid biosynthesis. Metabolomic and correlation analyses further supported coordinated microbe–metabolite interactions associated with MUN variation. Variance partitioning analysis showed that rumen microbial composition, microbial functional pathways, and metabolite profiles explained similar proportions of MUN variation (13.59%, 13.42%, and 13.38%, respectively). Collectively, these findings indicate that low-MUN cows possess ruminal microbial and metabolic features consistent with more efficient ammonia incorporation into microbial biomass output, whereas high-MUN cows exhibit features associated with enhanced amino acid degradation and less efficient nitrogen capture. These results provide preliminary evidence that these coordinated differences may underlie the development of distinct MUN phenotypes.

Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease and chronic kidney disease. Oxidative stress, a key driver of renal fibrosis and a hallmark of DKD pathological changes, has been extensively studied for its role in DKD progression. However, its specific mechanisms remain unclear. Here, we show that homocysteine (Hcy) accumulation in proximal tubular epithelial cells (PTECs) is a significant contributor to mitochondrial oxidative stress in DKD. Through single-cell RNA sequencing (scRNA-seq) screening, we identify lncPTEC, a DKD-associated long non-coding RNA (lncRNA) from the PTEC cluster. Notably, we find that upregulated lncPTEC correlates with elevated albuminuria in DKD patients and exacerbates mitochondrial oxidative stress, epithelial-mesenchymal transition (EMT) and renal tubular fibrosis both in vitro and in vivo. Mechanistically, lncPTEC is transcriptionally upregulated by the transcription factor specificity protein 1 (SP1) under hyperglycemic conditions. Furthermore, lncPTEC directly interacts with the established key factor of Hcy metabolism, methylenetetrahydrofolate dehydrogenase 1 (MTHFD1), promoting its ubiquitination and degradation via the ubiquitination-related protein UBQLN1. This process leads to Hcy accumulation, mitochondrial oxidative stress, and subsequent DKD progression. Hence, our findings elucidate the role of the lncPTEC/MTHFD1 axis in Hcy-mediated mitochondrial oxidative stress, offering potential diagnostic biomarkers and therapeutic targets for DKD.

Understanding the mechanisms of dietary energy on compensatory growth in beef cattle is crucial for improving feed efficiency and mitigating the environmental footprint of beef production. The objectives of the study were to investigate the effects of dietary energy restriction and subsequent re-alimentation on growth performance, nutrient digestibility, ruminal microbiome, plasma metabolites, and nitrogen metabolism in growing beef bulls. Twelve 6–8-month-old Simmental crossbred bulls (initial body weight: 226 ± 24 kg) were randomly allocated to two groups (n = 6 per group): the dietary energy restriction group (REC) was fed a diet containing 9.25 MJ/kg metabolizable energy (ME) for 4 weeks (energy restriction period), followed by a 2-week re-alimentation period with a 10.29 MJ/kg ME diet, while the control group (CON) was fed the 10.29 MJ/kg ME diet consistently throughout the experimental period. Dietary energy restriction significantly decreased body weight and average daily gain (ADG) compared to CON (P < 0.05). However, no significant differences were observed by the end of the re-alimentation period (P > 0.05), demonstrating successful compensatory growth through dietary energy modulation. Ruminal propionate, total volatile fatty acids, ammonium nitrogen, and microbial crude protein (MCP) concentrations significantly decreased in the energy restriction treatment compared to CON (P < 0.05), but MCP exceeded the levels in CON after dietary energy re-alimentation (P < 0.05). Energy restriction also significantly increased urinary nitrogen excretion (P = 0.002), driven by imbalanced amino acid metabolism and significantly increased urinary urea (P = 0.038), which significantly reduced protein synthesis and nitrogen retention (P = 0.017). Metagenomics analysis revealed that energy restriction significantly increased the relative abundances of Limosilactobacillus, Enterococcus, and Aliarcobacter (P < 0.05), while decreasing those of Gemmatirosa and Mesorhizobium (P < 0.05). Dietary energy re-alimentation significantly increased the relative abundance of Gramella, Acetobacter, Phaeobacter, and Flammeovirga (P < 0.05). These bacteria are associated with pathways related to amination, transamination, and microbial protein synthesis. Integrated multi-omics revealed shifts in the ruminal microbiome and host metabolome, particularly in pathways related to ruminal urea hydrolysis, biosynthesis of glutamate, glutamine, and alanine, and post-absorptive amino acid metabolism, which collectively enhanced protein synthesis and compensatory growth. These findings establish a practical feeding strategy to optimize feed efficiency and enhance compensatory growth in beef bulls via short-term dietary energy manipulation.

Yak and cattle-yak milk are important dairy resources in high-altitude regions, but their lipidomic differences remain poorly characterized. The objective of this study was to compare the milk lipid profiles of 5 Tibetan yak groups and 2 cattle-yak groups produced under plateau conditions. Milk lipids were analyzed by liquid chromatography–tandem mass spectrometry, followed by multivariate analysis, differential lipid screening, and pathway enrichment analysis. A total of 901 lipid species were identified, with glycerophospholipids representing the largest proportion of detected lipids. Multivariate analysis showed distinct lipidomic profiles between yak and cattle-yak milk. Among the 5 yak groups, 28 differential lipids were identified, mainly involving glycerophospholipids, sphingolipids, glycerolipids, and fatty acyl-related molecules. No false discovery rate-confirmed differential lipids were detected between Holstein × yak and Jersey × yak milk, although exploratory analysis suggested group-associated lipid variation. Comparison between yak and cattle-yak milk identified 18 differential lipids after accounting for breed nested within animal type. These lipids were mainly related to membrane-associated polar lipids and glycerolipids. Pathway analysis indicated that glycerophospholipid metabolism was the main pathway distinguishing yak and cattle-yak milk, with additional evidence for fatty acid- and glycerolipid-related differences. A panel of false discovery rate-adjusted lipids showed potential for discriminating among the 7 milk groups, supporting their use as candidate lipid signatures for milk-group characterization. Overall, these findings provide a lipidomic basis for evaluating plateau dairy resources, but broader validation under more controlled production conditions is needed before these lipid signatures can be applied to milk quality assessment or product development.

The study fingerprints the heat-induced metabolic changes in milk across 15 temperature-time treatments (63-136 °C) using an untargeted metabolomics approach. A total of 2277 metabolites were detected, including organic acids, benzene, heterocyclic compounds, aldehydes, ketones, esters, amino acids, carbohydrates, alcohols, amines, fatty acids, lipids, and their derivatives, from thermally processed milk samples across 15 treatment groups. The multivariate analyses (PCA, HCA) and the KEGG pathway enrichment revealed heat-induced metabolic disruptions, particularly in the Maillard reaction products and lipid oxidation pathways. Five thousand three hundred twenty-nine differentially regulated metabolites were observed, with the most pronounced changes observed in the 135 °C vs. raw milk group. Key pathways, including those associated with amino acid and carbohydrate metabolism, were significantly enriched. Amino acid and lipid pathways were most affected by heat processing. Lactulose was consistently downregulated, while L-Proline, Adenosine, and Carnitine were upregulated, suggesting they are candidate thermal biomarkers. The findings fingerprint the thermal-induced biochemical changes in milk, and Lactulose as a potential thermal biomarker for milk quality and authenticity. Further research is required to assess the practical feasibility of the biomarker and the practices needed to optimize dairy processing techniques.

Short-chain fatty acids (SCFAs) are key microbial metabolites that support intestinal and skeletal development, yet their coordinated effects during early life remain poorly defined. In this study, neonatal mice were administered SCFAs for 28 days to evaluate their impacts on growth, intestinal barrier integrity, immune modulation, bone development, and gut microbiota composition. Valerate supplementation significantly increased body weight and intestinal length. It enhanced the villus structure, crypt depth, and goblet cell number, alongside upregulation of tight junction and mucin genes, indicating improved barrier function. Valerate and propionate also promoted the expression of interleukin-4 (IL-4) and interleukin-10 (IL-10) and reduced pro-inflammatory cytokines, suggesting an immunomodulatory shift. In the skeletal system, valerate improved the microarchitecture, increased bone mineral density (BMD), and upregulated osteogenic genes runt-related transcription factor 2 (Runx2), fibroblast growth factor receptor 1 (FGFR1), and growth hormone receptor (GHR). Microbiota profiling showed enrichment of several genera (e.g., Fructobacillus, Pantoea, and Ralstonia) that correlated with intestinal and bone parameters. Collectively, these data indicate that valerate supplementation is associated with concurrent improvements in neonatal intestinal and skeletal outcomes, accompanied by shifts in microbiota and changes related to the barrier and immune systems; however, causal links among these intermediate steps remain to be established.

The rapid and accurate detection of chlorpyrifos (CPF), a widely used pesticide in agricultural products, is crucial for food safety assurance. While traditional methods like HPLC and GC-MS are accurate, they remain costly, slow, and lack portability. Herein, an ultrasensitive magnetic biosensing platform was developed for the ratiometric detection of CPF in tea by integrating surface-enhanced Raman spectroscopy (SERS) with an aptamer-based recognition strategy. The platform employed a competitive displacement mechanism, where specific binding between aptamer and CPF triggered the release of signal probes upon magnetic separation. This process altered the Raman intensity ratio of two reporter molecules (4-MPY and 4-MBN). The ratiometric sensing approach, combined with magnetic separation, improved operational convenience and reduced matrix interference from complex samples. Furthermore, the platform exhibited a wide linear detection range (10-9 M to 10-4 M) with a limit of detection (LOD) of 1.4 × 10-6 mg/kg. It demonstrated high sensitivity, stability, reproducibility and specificity across six tea varieties, offering an effective solution for detecting pesticide residues in complex food matrices.

Geographical origin may be a key factor contributing to variations in dairy product quality. This study focuses on the fatty acid composition and lipidome of camel milk and bovine milk from different regions, aiming to highlight lipid biomarkers that remain unaffected by regional variations in both camel and bovine milk, as well as region-specific lipid biomarkers present in camel milk. The results showed that camel milk consistently exhibited higher levels of long-chain fatty acids and monounsaturated fatty acids, whereas bovine milk showed a higher proportion of medium-chain and short-chain saturated fatty acids, regardless of the region. Lipidomic analysis revealed that phospholipids were more abundant in camel milk, while triglycerides and diglycerides were characteristic lipids in bovine milk. Certain lipid biomarkers were more abundant in specific types of milk, such as PC (21:4/21:6CHO), FA (29:3), and Hex3Cer (d18:0/24:2) in camel milk, and CerPE (d41:6) in bovine milk, and could be used to distinguish camel milk from bovine milk across all 3 regions. Additionally, fatty acids and lipid molecules distinguishing camel milk from different regions were identified, including C18:3n3 and PE (18:2/22:2CHO) in XJNC, C18:2n6c in XJSC, and C14:0 and PS (16:0/18:1) in IMC. These findings provide new insights into developing species-specific nutritional strategies and regional traceability of dairy products.

ABSTRACT Sustainable dairy development is crucial for global food security, as it converts feed resources into nutrient‐dense human food while supporting soil fertility through manure recycling. Milk provides high‐quality protein and essential micronutrients, yet rising production demands have intensified challenges related to animal welfare and environmental impacts. Addressing these issues requires integrated strategies, including precision monitoring technologies, enteric methane inhibitors, and improved manure management. A balanced approach aligning productivity with animal health and ecological integrity is essential for future dairy systems.

Milk urea nitrogen, the primary form of nonprotein nitrogen (N) in milk, is an indirect indicator of N metabolism in dairy cows. The MUN concentrations are modulated by various factors, including dietary composition, physiological status, and environmental conditions. However, the potential roles of host gut microbiota and metabolome in the development of distinct MUN phenotypes remain insufficiently elucidated. Here, we compared fecal microbiota and fecal/serum metabolomes of high-MUN (HMUN) and low-MUN (LMUN) cows (n = 7 per group) under uniform feeding management using 16S rRNA gene sequencing and liquid chromatography-MS-based metabolomics. Compared with that of LMUN cows, the feces of HMUN cows exhibited relatively higher abundances of UCG-009, UCG-002, and Christensenellaceae_R-7_group and lower abundances of Succinivibrio, Lachnospiraceae_NK3A20_group, Acetitomaculum, Prevotellaceae_UCG-001, and norank_f__Bifidobacteriaceae. Metabolomic analysis revealed that HMUN cows had relatively lower levels of hydroxypropionic acid, N-myristoyl arginine, and N-eicosapentaenoyl tryptophan in feces, and reduced amounts of l-serine, linoleic acid, and butyrate in serum. Kyoto Encyclopedia of Genes and Genomes pathway mapping revealed that the metabolites relatively elevated in LMUN cows were primarily involved in the β-alanine metabolism pathway. The UCG-009 and Christensenellaceae_R-7_group were positively correlated with MUN, whereas Succinivibrio, Lachnospiraceae_NK3A20_group, Anaeroplasma, and Acetitomaculum were negatively correlated. These microbial taxa were also significantly associated with several fatty and AA metabolites, including adipic acid, undecenoic acid, dodecanedioic acid, dl-tryptophan, and l-leucine. Collectively, this study revealed certain differences in the gut microbiota and metabolome between cows with high and low MUN levels. These findings suggest that alterations in gut microbial composition and metabolic profiles may contribute to variations in MUN phenotypes and provide new insights into host factors influencing MUN metabolism in dairy cows.

Milk and dairy products are essential food globally, due to their rich nutritional content. The nutritional quality of milk provides an excellent medium for microbial growth. While beneficial microbes can enhance nutritional quality, spoilage and pathogenic bacteria pose significant risks. Extended shelf life (ESL), pasteurization, and ultra-high temperature (UHT) processing reduce microbial load but variably impact nutritional quality and the milk microbiome. This review critically compares the microbiome dynamics across these processing types with a specific emphasis on ESL milk, an area where comprehensive metagenomics data is notably lacking. A deeper understanding of raw milk contamination routes and the potential for outgrowth or survival of biofilm forming or spore forming bacteria during processing is critical. This review summarizes processing driven microbiome shifts, safety implications, and nutritional consequences in milk. A key focus is the limitations of current detection strategies, particularly the challenge of distinguishing viable from non-viable cells in processed milk. By synthesizing existing research and highlighting critical knowledge gaps, this review establishes a framework to guide future dairy microbiome research, focusing on the development of safer, more nutritious milk products and practical industry applications.

The nutritional value of milk fat depends on lipid and fatty acid composition. This study characterized the lipidomics and fatty acid positional distribution of milk from nine mammalian species: cow, buffalo, yak, goat, sheep, camel, mare, donkey, and human. Lipid molecular species were profiled by liquid chromatography-tandem mass spectrometry. Fatty acid positional distribution was determined using NH₂ and Si solid-phase extraction, selective sn-1/3 hydrolysis by Candida antarctica lipase B, and sn-2 monoacylglycerol quantification by gas chromatography-mass spectrometry. Ruminant milks showed high compositional similarity and differed from camel and monogastric milks. Compared to human milk, animal milks had higher triacylglycerols, phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins, but lower free fatty acids and diacylglycerols. Short-chain fatty acids consistently occupied sn-1/3 positions, whereas medium-chain, long-chain, odd-chain, and branched-chain fatty acids favored sn-2 position. Monogastric milks exhibited sn-2 preference for palmitic acid and other saturated fatty acids and sn-1/3 preference for unsaturated fatty acids; ruminant and camel milks showed the reverse. Bray-Curtis analysis identified donkey milk as the closest lipidomic analog to human milk, followed by mare milk. These findings provide a systematic reference for evaluating mammalian milks and data for humanized infant formula lipid design.

Red clover extract (RCE) is rich in isoflavones, which have been reported to improve nitrogen utilization in dairy diets. Therefore, the objective of this study was to evaluate the effects of partially replacing soybean meal (SBM) with RCE plus feed-grade urea on lactation performance and nitrogen metabolism in lactating Holstein cows, relative to a slow-release urea (SRU) nitrogen source formulated to provide a similar amount of dietary nitrogen. In a randomized complete block design, 600 cows received one of 3 diets for 35 d (n = 200 per diet): SBM (10.81% SBM), SRU (0.65% SRU replacing 37.74% of SBM), or RCE (0.20% RCE + 0.57% urea replacing 37.74% of SBM). Diets were formulated to be isoenergetic and isonitrogenous. Data were analyzed using a mixed model with diet as a fixed effect and block and pen nested within diet as random effects; the pen was considered the experimental unit. Milk yield and milk composition did not differ between RCE and SBM. The DMI and feed efficiency were similar between these treatments, whereas SRU was associated with greater DMI and lower feed efficiency relative to SBM. Compared with SBM, RCE increased urinary purine derivatives and estimated microbial N, whereas concentrations of urea N in milk, plasma, and urine did not differ. Apparent NDF and ADF digestibility were similar between RCE and SBM but were lower with SRU. Differences among diets were also observed in selected blood biochemical and endocrine variables. These findings indicate that, during the 35-d experimental period, partial replacement of SBM with RCE plus urea maintained lactation performance relative to SBM and was associated with higher estimated microbial N compared with SBM, whereas responses to SRU differed in several nitrogen-related measures.

N-glycosylation is a crucial post-translational modification regulating protein function in plants. However, its accurate quantification by matrix-assisted laser desorption/ionization-mass spectrometry with time-of-flight is challenged by low glycoprotein abundance, poor glycan ionization, uneven matrix crystallization, and insufficient internal standards. Here, we introduce a novel 5-Da stable isotope labeling method, combining enzymatic 18O-labeling (+2-Da) and reduction with NaBD4 (+3-Da) on a portion of the sample itself to universally generate internal standards that eliminate isobaric interference. Furthermore, a binary matrix of 2-aminoisophthalic acid (2-AIA) plus α-cyano-4-hydroxycinnamic acid (CHCA) was developed, providing high sensitivity and homogeneous co-crystals. The integration of isotope labeling with 2-AIA/CHCA allows linear quantification (R2 > 0.99) over a two orders of magnitude. Applied to tomato and peach during cold storage, the method revealed that H3N2F1X1, the most abundant N-glycan in both fruits, was significantly downregulated, suggesting its role as a candidate biomarker for cold stress response and fruit quality control.

This study optimized ultrasound-assisted extraction (UAE) parameters for polysaccharides from Baizhu Shaoyao powder (BSP), characterized the structure of purified BSP polysaccharides (BSPP) and investigated their immunomodulatory effects on RAW264.7 macrophages. The optimal conditions yielded BSPP at 16.695 ± 0.23%. BSPP was characterized as fructose-enriched polysaccharides with a molecular weight (Mw) of 2.786 kDa, and exhibited amorphous morphology along with characteristic polysaccharide functional groups. BSPP enhanced macrophage pinocytosis and phagocytosis, upregulated antigen-presenting molecules/costimulatory markers, and stimulated inflammatory mediator production. RNA-seq revealed 1,832 DEGs, 66 GO terms, and 97 KEGG pathways with integrated network analysis identifying TNF and IL-1β as hub genes. Western blot analysis confirmed p38 MAPK/NF-κB pathway activation, and inhibitor experiments established TLR2/TLR4-mediated recognition and MyD88-dependent p38 MAPK/NF-κB signaling as essential for BSPP-induced macrophage activation. These findings provide a theoretical basis for enriching the pharmacodynamic material basis of BSP and expanding its clinical applications.

Equol, a bioactive metabolite of isoflavones, is associated with diverse health benefits, yet its enrichment in bovine milk has not been fully clarified. In this study, we established a liquid chromatography-mass spectrometry method for detecting equol in milk, featured by an acid hydrolysis pretreatment. Equol was found predominantly in the milk fat fraction. A random forest regression model was developed to predict milk equol levels based on its significant correlations with various lactation parameters. Dietary supplementation with red clover isoflavones markedly increased equol concentration in milk by up to 15.6 fold. The milk thermol processing and microbial fermentation showed negligible effects on equol level, indicating its strong stability. Collectively, these findings elucidate the distribution patterns and key determinants of equol in milk. Importantly, a strategy of red clover isoflavones supplementation was developed to produce higher equol-enriched milk as a novel functional food for human health.

The cellulolytic bacteria are crucial for applications in animal feeds, food processing, and bioenergy production. However, isolation of these bacteria from the microbial community has been challenging due to limitations in current methodologies. This study introduces a novel cellulose-functionalized magnetic nanoparticle-mediated isolation technique designed to enhance the recovery of cellulolytic bacteria. We hypothesized that bacteria could adhere to magnetic nanoparticles coated with cellulose, allowing selective isolation of cellulolytic strains through their cellulase activity-induced magnetic loss. The magnetic nanocomposite was synthesized and functionalized with cellulose (magnetic nanoparticle-cellulose composite [MNPC]). The anaerobic Streptococcus bovis was used to evaluate the bacteria capture efficiency of MNPCs. A mixture of Cellulomonas flavigena (a cellulolytic bacterium) and S. bovis (a non-cellulolytic bacterium) was used to evaluate the cellulolytic bacteria isolation specificity of the method. This method was also applied to isolate the novel ruminal cellulolytic bacteria. The results showed that the magnetic nanoparticle had an average size of 20.00 nm and superparamagnetism. MNPC achieved a bacterial capture efficiency of 99% and a high specificity. The method successfully captured the known cellulolytic bacteria from the rumen of cattle, including Fibrobacter, Ruminococcus flavefaciens, and Butyrivibrio, indicating its reliability. Furthermore, a novel cellulolytic species from the family Lachnospiraceae was isolated from the rumen, with genome analysis revealing cellulolytic pathway genes encoding endoglucanase, β-glucosidase, and cellobiose phosphorylase. In conclusion, the cellulose-functionalized magnetic nanoparticle-mediated isolation method presents a promising approach for the efficient enrichment and isolation of active cellulolytic bacteria. This technique and the isolated strains have potential applications in enhancing animal productivity, bioenergy production, and the food industry.IMPORTANCELignocellulosic biomass, as the primary component of cell walls in gramineous plants, is widely recognized as an ideal biofuel feedstock due to its sustainability and renewability. It can be digested and degraded by cellulolytic microorganisms, converting it into absorbable proteins and volatile fatty acids that provide energy for the organism. However, isolation of these bacteria from the microbial community has been challenging due to the limitations in current methodologies. In this work, we developed a new method, the cellulose-functionalized magnetic nanoparticle-mediated isolation technology, which can contribute to capture highly active cellulolytic bacteria. We isolated a novel unclassified cellulolytic strain of the Lachnospiraceae from the rumen of cattle. This methodology presents a promising approach for the efficient enrichment and isolation of active cellulolytic bacteria from the community.