Milk fat miRNome changes in response to LPS challenge in Holstein cows.

Mastitis is an inflammatory disease in dairy cows, causing economic losses and reducing animal welfare. In order to contribute for the discovery of early and noninvasive indicators, our objective was to determine the effects of a lipopolysaccharide (LPS) challenge on the microRNA profile (miRNome) of milk fat, using microarray analyses in cows. Cows were fed a lactation diet at ad libitum intake (n = 6). At 27 ± 3 days in milk, cows were injected with 50 µg of LPS Escherichia coli in one healthy rear mammary quarter. Milk samples were collected just before LPS challenge (LPS-) and 6.5 h after LPS challenge (LPS +) from the same cows. Microarray analysis was performed using customized 8 × 60 K ruminant miRNA microarrays to compare LPS- to LPS + miRNome. In silico functional analyses were performed using OmicsNet and Mienturnet software. MiRNome comparison between LPS- and LPS + identified 37 differentially abundant miRNAs (q-value ≤ 0.05). The predicted target genes of the 37 differentially abundant miRNAs are mostly involved in cell life including apoptosis, cell cycle, proliferation and differentiation and in gene expression processes. MiRNome analyses suggest that miRNAs profile is related to the inflammation response of the mammary gland. In conclusion, we demonstrated that milk fat might be an easy and rapid source of miRNAs that are potential indicators of early mastitis in cows.

Nutrigenomic analyses reveal miRNAs and mRNAs affected by feed restriction in the mammary gland of midlactation dairy cows.

The objective of this study was to investigate the effects of feed restriction on mammary miRNAs and coding gene expression in midlactation cows. Five Holstein cows and 6 Montbéliarde cows underwent 6 days of feed restriction, during which feed allowance was reduced to meet 50% of their net energy for lactation requirements. Mammary biopsies were performed before and at the end of the restriction period. Mammary miRNA and mRNA analyses were performed using high-throughput sequencing and microarray analyses, respectively. Feed restriction induced a negative energy balance and decreased milk production and fat and protein yields in both breeds. Feed restriction modified the expression of 27 miRNAs and 374 mRNAs in mammary glands from Holstein cows, whereas no significant miRNA change was observed in Montbéliarde cows. Among the 27 differentially expressed miRNAs, 8 miRNAs were associated with dairy QTL. Analysis of target genes indicate that the 8 most abundantly expressed miRNAs control transcripts related to lipid metabolism, mammary remodeling and stress response. A comparison between the mRNAs targeted by the 8 most strongly expressed miRNAs and 374 differentially expressed mRNAs identified 59 mRNAs in common. The bioinformatic analyses of these 59 mRNAs revealed their implication in lipid metabolism and endothelial cell proliferation. These effects of feed restriction on mammary miRNAs and mRNAs observed in Holstein cows suggest a potential role of miRNAs in mammary structure and lipid biosynthesis that could explain changes in milk production and composition.

Estimation of dairy goat body composition: A direct calibration and comparison of eight methods.

The objective was to compare eight methods for estimation of dairy goat body composition, by calibrating against chemical composition (water, lipid, protein, mineral and energy) measured post-mortem. The methods tested on 20 Alpine goats were body condition score (BCS), 3-dimension imaging (3D) automatic assessment of BCS or whole body scan, ultrasound, computer tomography (CT), adipose cell diameter, deuterium oxide dilution space (D2OS) and bioelectrical impedance spectroscopy (BIS). Regressions were tested between predictive variates derived from the methods and empty body (EB) composition. The best equations for estimation of EB lipid mass included BW combined with i) perirenal adipose tissue mass and cell diameter (R2 = 0.95, residual standard deviation, rSD = 0.57 kg), ii) volume of fatty tissues measured by CT (R2 = 0.92, rSD = 0.76 kg), iii) D2OS (R2 = 0.91, rSD = 0.85 kg), and iv) resistance at infinite frequency from BIS (R2 = 0.87, rSD = 1.09 kg). The D2OS combined with BW provided the best equation for EB protein mass (R2 = 0.97, rSD = 0.17 kg), whereas BW alone provided a fair estimate (R2 = 0.92, rSD = 0.25 kg). Sternal BCS combined with BW provided good estimation of EB lipid and protein mass (R2 = 0.80 and 0.95, rSD = 1.27 and 0.22 kg, respectively). Compared to manual BCS, BCS by 3D slightly decreased the precision of the predictive equation for EB lipid (R2 = 0.74, rSD = 1.46 kg), and did not improve the estimation of EB protein compared with BW alone. Ultrasound measurements and whole body 3D imaging methods were not satisfactory estimators of body composition (R2 ≤ 0.40). Further developments in body composition techniques may contribute for high-throughput phenotyping of robustness.

Dataset reporting 4654 cow milk proteins listed according to lactation stages and milk fractions.

Milk contains numerous proteins including bioactive molecules that may be important in human nutrition. Thanks to improvements in proteomic methods, hundreds of proteins identified in milk are available through open data from different publications. We gathered these public data to produce an atlas reporting the cow milk proteins. We aggregated data from 20 publications reporting milk proteome and produced an atlas of 4654 unique proteins detected in milk from healthy cows. In this atlas, proteins are categorized according to four milk fractions: skimmed milk, whey, milk fat globule membranes (MFGM) and exosomes; and five lactation stages: colostrum period, early lactation, peak of lactation, mid-lactation and drying-off. These 9 protein lists were compared and annotated by Gene Ontology (GO) terms to identify the pathways they contribute to, the molecular signatures of different milk fractions and lactation stages. This data article compiles the 4654 cow milk proteins. This atlas may be used by researchers on human nutrition interested in milk protein allergy and/or digestibility in humans, and for milk processing industry. The atlas may be useful to i) find molecular signatures of physiological adaptations of dairy cows, ii) facilitate the isolation of proteins of interest, thanks to the knowledge on their presence in milk fractions and their period of secretion during lactation.

Mammary Gland Transcriptome and Proteome Modifications by Nutrient Restriction in Early Lactation Holstein Cows Challenged with Intra-Mammary Lipopolysaccharide.

: The objective is to study the effects of nutrient restrictions, which induce a metabolic imbalance on the inflammatory response of the mammary gland in early lactation cows. The aim is to decipher the molecular mechanisms involved, by comparing a control, with a restriction group, a transcriptome and proteome, after an intra-mammary lipopolysaccharide challenge. Multi-parous cows were either allowed ad libitum intake of a lactation diet (n = 8), or a ration containing low nutrient density (n = 8; 48% barley straw and dry matter basis) for four days starting at 24 ± 3 days in milk. Three days after the initiation of their treatments, one healthy rear mammary quarter of 12 lactating cows was challenged with 50 µg of lipopolysaccharide (LPS). Transcriptomic and proteomic analyses were performed on mammary biopsies obtained 24 h after the LPS challenge, using bovine 44K microarrays, and nano-LC-MS/MS, respectively. Restriction-induced deficits in energy, led to a marked negative energy balance (41 versus 97 ± 15% of Net Energy for Lactation (NEL) requirements) and metabolic imbalance. A microarray analyses identified 25 differentially expressed genes in response to restriction, suggesting that restriction had modified mammary metabolism, specifically ß-oxidation process. Proteomic analyses identified 53 differentially expressed proteins, which suggests that the modification of protein synthesis from mRNA splicing to folding. Under-nutrition influenced mammary gland expression of the genes involved in metabolism, thereby increasing ß-oxidation and altering protein synthesis, which may affect the response to inflammation.