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.

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.

Ruminants have the ability to convert agricultural byproducts into valuable resources. However, the influence of functional roughage with medicinal value on production performance and rumen function in ruminants remains unclear. This study aimed to examine the role of Eucommia ulmoides leaves (EUL) in the growth performance and rumen microbiome of sheep. Twenty-one healthy female sheep were randomly divided into three groups, in which the EUL feeding amounts were 0

Milk contains numerous bioactive components contributing to its health benefits. As raw milk undergoes processing, the impact of heat treatments on bioactive substances is crucial. This review outlines milk components with their bioactive functions, summarizes common milk thermal processing methods, including LTLT, HTST, and UHT pasteurization. It further compares changes in their activity under different heat treatments. Providing a theoretical basis for developing functional dairy products. Additionally, novel milk processing techniques such as microwave heating, ultra-high pressure homogenization, and turbulent-flow ultraviolet treatment are introduced. The findings indicate that heat treatment causes denaturation of proteins and enzymes, while UHT processing damages milk fat, in contrast to pasteurization, which shows no significant effect. Compared to other methods, pasteurization induces less damage to bioactive substances in dairy products.

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.

Milk titratable acidity is a key indicator of raw milk freshness and quality, but its variation across different dairy animal species remains incompletely characterized. Based on 16,984 raw milk samples from eight dairy animal species (Holstein cow, goat, buffalo, camel, sheep, yak, donkey, and horse) collected within a retrospective raw milk quality monitoring framework in China from 2016 to 2024, this study provides a large-scale descriptive comparison of milk titratable acidity across species. Distinct titratable acidity profiles were observed among species, with camel and yak milk showing relatively high values, sheep, Holstein, and buffalo milk exhibiting intermediate values, and donkey and horse milk presenting markedly low values. Calendar-season-associated patterns also differed among species. Correlations between titratable acidity and milk components varied by species, with relatively stronger positive associations with protein and solids-not-fat (SNF) in several ruminant milks, suggesting that milk composition may contribute to differences in titratable acidity. However, because this study was based on an unbalanced observational dataset with limited animal-level, farm-level, feeding, management, physiological, and environmental metadata, these observations should be interpreted as descriptive and exploratory patterns rather than causal biological mechanisms. This dataset provides preliminary reference information for future studies on species-associated variation in raw milk titratable acidity and for discussions on species-specific raw milk quality evaluation.

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.

Bacterial cellulose (BC) is employed as a toughening agent in the preparation of composite hydrogels. However, achieving both high strength and toughness after incorporating BC into hydrogels remains challenging. Insufficient amounts of BC limit the enhancement of strength, whereas excessive BC results in reduced elongation of hydrogels. Herein, a fiber salting-out method was developed to fabricate BC/polyvinyl alcohol (PVA) hydrogels by modifying BC with Hofmeister series ions (-COO-, -PO32-, -SO3-). Through the fiber salting-out effect of BC, PVA was induced to aggregate on the BC surface, forming more crystalline domains and thereby improving the mechanical properties of the hydrogels. Among them, the tensile strength and toughness of the SBCP hydrogel (BC modified with -SO3-) reached the highest values, measuring 2.98 MPa and 27.48 MJ m-3, respectively-representing 9-fold and 36-fold increases over those of pure PVA hydrogels. Furthermore, this hydrogel exhibits high electrical conductivity and favorable biocompatibility. This study presents a new strategy for fabricating tough BC-based hydrogels and provides insight into new applications for BC fibers.

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.

Orotic acid (OA) is known to promote cell proliferation and influence triglyceride (TG) and protein metabolism in several animal species and cell types. However, its biological function in ovine mammary epithelial cells (OMECs) remains unclear. In this study, we evaluated the effects of OA on cell proliferation, oxidative stress, and synthesis of lactose, milk fat, and protein, and the explored potential regulatory mechanism using transcriptomic analysis. Treatment with 30 µg/mL of OA significantly promoted OMEC proliferation. OA also improved oxidative stress related indicators, increasing CAT (14.71 ± 3.27 VS 6.90 ± 1.40 U/106cell, P < 0.05) and SOD (7.08 ± 0.86 VS 4.18 ± 1.32 U/106cell, P < 0.05) activates, and reducing MDA (38.55 ± 12.06 VS 80.19 ± 12.34 U/106cell, P < 0.05). TG concentrations increased significantly both in cells (12.58 ± 1.86 VS 2.69 ± 0.23 µg/106 cells, P < 0.05) and culture supernatant (8.54 ± 0.62 VS 2.82 ± 0.12 ng/mL, P < 0.001). In contrast, OA significantly decreased the CSN2 concentration in the supernatant (24.41 ± 0.98 VS 34.62 ± 0.59 ng/mL, P < 0.001). Transcriptomic analysis identified 365 differentially expressed genes (DEGs), including 94 up-regulated and 271 down-regulated genes in the OA treated group. Up-regulated DEGs were enriched in the JAK-STAT signaling pathway and so on, while down-regulated DEGs were enriched in the protein digestion and absorption and so on. DEGs such as RPS6KA2 and FOXO4 were associated with cell proliferation, and ALDOC, SULT2B1, ADRB1, STAT5A were associated with fat metabolism. These findings suggest that OA enhances cells proliferation, improves oxidative stress indicators, and promotes TG synthesis in OMECs. The study provides a useful reference for understanding the regulation mechanism of lactation traits and for dairy sheep breeding.

Ciboria shiraiana (C. shiraiana), a pathogenic fungus, is a major threat to mulberry trees, causing mulberry sclerotinia diseases. Current control strategies primarily rely on chemical pesticides, whose long-term use leads to adverse effects such as pesticide residues, environmental pollution, and pathogen resistance. This study aimed to develop a green pesticide derived from the essential oil (EOs) of Solidago canadensis L. (S. canadensis L.) and to analyze its antifungal mechanism. SLEOs were extracted from flowers, leaves, and stems of S. canadensis L. via hydro-distillation. Their chemical composition was analyzed by GC-MS. Multivariate statistical analysis was used to assess compositional differences among SLEOs from various plant parts and evaluate the correlation between their chemical components and antifungal efficacy. The antifungal mechanism of SLEOs against C. shiraiana was investigated using an integrated approach combining transcriptomics with physiological and biochemical analyses. The EO yield varied with plant part: flowers yielded the most (1.00% ± 0.07%), followed by leaves (0.76% ± 0.04%) and stems (0.05% ± 0.01%). Flower EOs (FEOs) strongly inhibited C. shiraiana, with an EC50 value of 0.642 μL/mL. α-pinene and myrcene showed the highest correlation with antifungal activity. Transcriptomic and physiological data revealed that SLEOs compromise cell wall and membrane integrity, infiltrate cells, and trigger leakage of intracellular contents. Additionally, SLEOs inhibited activities of antioxidant enzymes (SOD, CAT, and POD), leading to intracellular ROS accumulation, oxidative stress, lipid peroxidation, and DNA damage. SLEOs constitute a promising natural and environmentally sustainable antifungal agent. Their activity is linked to specific components and a multi-target mechanism involving membrane disruption and oxidative stress induction. This study provides a foundation for developing plant-based agents to manage mulberry sclerotinia diseases.

[This corrects the article DOI: 10.3389/fmicb.2021.730656.].

Free monosaccharides are important carbohydrates in milk, providing both basic and bioactive nutritional benefits; however, the content and composition of free monosaccharides in milk from different species are still not well understood. The aim of this study was to develop a highly sensitive and accurate liquid chromatography (LC)-MS method for the precise quantification of free monosaccharides in milk from 8 species, including human, cow, goat, sheep, yak, camel, horse, and donkey. The chromatographic conditions and MS parameters were systematically optimized to ensure high resolution, minimal matrix effects, and low detection limits for all 8 target monosaccharides. The method was validated with excellent linearity (R2 > 0.996), high recovery rates (94.18%-115.02%), and low CV (<10%), demonstrating robustness across various concentrations. The compositional analysis revealed significant interspecies differences in monosaccharide profiles. Human milk was uniquely enriched in glucose (4,262.98 ± 246.49 ng/mL) and fucose (1,024.80 ± 61.82 ng/mL). In contrast, ruminant milk, such as cow and sheep milk, exhibited high levels of galactose (1,803.56 ± 94.63 ng/mL and 1,230.31 ± 52.33 ng/mL, respectively) and mannose (375.24 ± 16.27 ng/mL and 55.81 ± 3.76 ng/mL, respectively). Principal component analysis and a complementary stacked bar chart effectively visualized the clustering and relative distribution of monosaccharides among species, highlighting their metabolic and functional diversity. This study provides novel insights into the biological roles and evolutionary significance of milk monosaccharides. The developed LC-MS method offers a robust tool for advancing our understanding of milk composition and its implications for neonatal nutrition, dairy product innovation, and human health.

This study assessed the effects of industrial-scale direct (130 °C/0.5 s) and indirect (75 °C/15 s, 122 °C/4 s, 137 °C/4 s) heat treatments on raw milk through integrated multi-omics and sensory profiling. Results showed that direct and mild indirect (75 °C/15 s) treatments best preserved sensory qualities close to raw milk, with enhanced umami and richness, reduced sulfurous and nitrogen oxide signal, and minimal changes in proteomic, lipidomic, and metabolomic profiles. Direct heating produced smaller protein particles, although fat-globule size was unaffected. Increasing heat intensity elevated membrane proteins, diminished bioactive proteins, and reduced the abundance and diversity of amino acids, lipids, and organic acids. Multi-omics correlation networks linked milk fat globule membrane components and lipids to particle size and sensory attributes-fat globule size was strongly associated with richness. The study demonstrates that direct heating better retains native milk properties and provides molecular-level insight into thermal processing effects.

To investigate the source of the bitter almond taste in whole corn silage (WPCS), headspace solid-phase microextraction combined with gas chromatography–mass spectrometry (HS-SPME-GC-MS), headspace gas chromatography–ion migration spectrometry (HS-GC-IMS), and electronic nose (E-nose) technology were employed. The study analyzed the differences in volatile compounds between two WPCS samples with distinct odors from the same cellar. GC-IMS and GC-MS identified 32 and 101 volatile organic compounds (VOCs), respectively, including aldehydes, alcohols, esters, ketones, and other compounds. Three characteristic volatile organic compounds associated with the bitter almond taste were detected: benzaldehyde, cyanide, and isocyanate. The electronic nose demonstrated varying sensitivities across its sensors, and principal component analysis (PCA) combined with variable importance projection (VIP) analysis revealed that W5S (nitrogen oxides) could differentiate between the two distinct silage odors. This finding was consistent with the GC-MS results, which identified 34 nitrogen-containing heterocyclic compounds in the abnormal silage sample, accounting for 77% of the total nitrogen-containing compounds. In summary, significant differences in aroma composition were observed between the bitter almond-flavored silage and the other silage in the same cellar. These differences were primarily attributed to changes in volatile organic compounds, which could serve as indicators for identifying bitter almond-flavored silage.

This study aimed to assess the effectiveness of fatty acid (FA) fingerprinting in distinguishing the geographical origin of milk and linking milk FA profiles with those of forage. A total of 66 bulk-tank milk samples and 66 corresponding forage samples were collected over 3 consecutive days from 22 dairy farms across western, eastern, and southern China. The FA compositions of the samples were analyzed using GC-MS, identifying 81 individual FA. Using orthogonal partial least squares discriminant analysis and significance analysis, we identified significant regional differences in the 35 milk FA. Recursive feature elimination was used to identify 10 potential FA biomarkers for the geographical origin of milk, including C18:2 cis-9,trans-12, C18:1 trans-6, PUFA, C18:1 cis-12, C20:3 cis-8,cis-11,cis-14, C14:0, MUFA, C13:0 iso, C16:1 cis-9, and C13:0. A support vector machine model based on these 10 biomarkers classified the milk samples by region with an accuracy >95%. Canonical and Spearman's correlation analyses indicated relationships between milk and forage FA profiles. Specifically, milk FA such as C13:0 iso, C13:0, C14:0, and C16:1 cis-9 showed significant positive correlations with most short-chain FA, odd-chain SFA, and branched-chain SFA in the forage and negative correlations with long-chain FA and FA greater than C16. Conversely, milk FA C18:2 cis-9,trans-12, C18:1 trans-6, and C18:1 cis-12 exhibited the opposite trend. The correlation between UFA in milk and forage was more complex, showing both positive and negative relationships. These findings demonstrate that FA fingerprinting is a reliable method for determining the geographical origin of milk. The observed variations in milk FA are primarily influenced by forage FA, providing valuable insights for improving milk quality through better forage management.

Bacterial proteomics is a pivotal tool for elucidating microbial physiology and pathogenicity. The efficiency and reliability of proteomic analyses are highly dependent on the protein extraction methodology, which directly influences the detectable proteome. In this study, we systematically compared four protein extraction protocols—SDT lysis buffer with boiling (SDT-B), SDT lysis buffer with ultrasonication (SDT-U/S), a combination of boiling and ultrasonication (SDT-B-U/S), and SDT lysis buffer with liquid nitrogen grinding followed by ultrasonication (SDT-LNG-U/S)—to evaluate their effects on peptide and protein identification, distribution, and reproducibility in Escherichia coli and Staphylococcus aureus. Both data-dependent acquisition (DDA) and data-independent acquisition (DIA) strategies were employed for comprehensive proteomic profiling. DDA analysis identified 23,912 unique peptides corresponding to 2,141 proteins in E. coli and 13,150 unique peptides corresponding to 1,511 proteins in S. aureus. DIA analysis yielded slightly fewer peptides (21,027 for E. coli and 7,707 for S. aureus) but demonstrated superior reproducibility. Among the tested protocols, SDT-B-U/S outperformed the others, identifying 16,560 peptides for E. coli and 10,575 peptides for S. aureus in DDA mode. It also exhibited the highest technical replicate correlation in DIA analysis (R2 = 0.92). This method enhanced the extraction of proteins within key molecular weight ranges (20–30 kDa for E. coli; 10–40 kDa for S. aureus) and was particularly effective for recovering membrane proteins (e.g., OmpC). Additionally, ultrasonication-based protocols outperformed the liquid nitrogen grinding approach in extracting the S. aureus proteome. These findings underscore the significant impact of protein extraction methods on bacterial proteomics. The SDT-B-U/S protocol—thermal denaturation followed by ultrasonication—proved most effective, enhancing protein recovery and reproducibility across both Gram-negative and Gram-positive bacteria. This work offers key guidance for optimizing microbial proteomic workflows.

Bioreactors are crucial in industrial production, where enzyme catalysis typically occurs in water and requires continuous heating, consuming significant energy. This study reports a new type of precisely heated reactor constructed from cellulose and MXene with directional channels and porous inner walls. MXene forms directional channels with cellulose via layered stacking, enabling rapid heat conduction and accurate heat transference to the enzyme catalyst. A temperature control box monitors the reactor's temperature and uses automated heating to reduce energy loss. The reactor's porous structures facilitate faster fluid diffusion, improving the "disturbance" effect. Compared to traditional methods, which heat the entire aqueous solution, this reactor accelerates heat and mass transfer processes, enhancing catalytic performance. The reactor can quickly raise the temperature around the enzyme to 60 degrees C within 100 s and achieve a 98.12 % conversion rate for polydatin within 2 h, significantly higher than the traditional method (89.84 %). The layered MXene reactor structure reduces energy consumption by over 76 %, with total electrical energy consumption of 3.33 Wh compared to 14.33 Wh in traditional methods. This reactor is suitable for continuous-flow catalysis with low energy consumption and excellent cyclic storage stability, offering a new approach for constructing precise temperature-controlled bioreactors.

[This corrects the article DOI: 10.3389/fmicb.2025.1586662.].