Dataset Information

Milk bottom-up proteomics: method optimisation.

ABSTRACT: Milk is a complex fluid whose proteome displays a diverse set of proteins of high abundance such as caseins and medium to low abundance whey proteins such as ß-lactoglobulin, lactoferrin, immunoglobulins, glycoproteins, peptide hormones and enzymes. A sample preparation method that enables high reproducibility and throughput is key in reliably identifying proteins present or proteins responding to conditions such as a diet, health or genetics. Using skim milk samples from Jersey and Holstein cows, we compared three extraction procedures which have not previously been applied to samples of cows’ milk. Method A (urea) involved a simple dilution of the milk in a urea-based buffer, method B (TCA/acetone) involved a TCA/acetone precipitation and method C (methanol/chloroform) involved a tri-phasic partition method in chloroform/methanol solution. Protein assays, SDS-PAGE profiling, and trypsin digestion followed by nanoHPLC-electrospray ionisation-tandem mass spectrometry (nLC-ESI-MS/MS) analyses were performed to assess their efficiency. Replicates were used at each analytical step (extraction, digestion, injection) to assess reproducibility. Overall 186 unique accessions, major and minor proteins, were identified with a combination of methods. Method C (methanol/chloroform) yielded the best resolved SDS-patterns and highest protein recovery rates, method A (urea) yielded the greatest number of accessions, and, of the three procedures, method B (TCA/acetone) was the least compatible of all with a wide range of downstream analytical procedures. Our results also highlighted breed differences between the proteins in milk of Jersey and Holstein cows.

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Bos Taurus (bovine)

TISSUE(S): Milk

SUBMITTER: Delphine Vincent

LAB HEAD: Delphine Vincent

PROVIDER: PXD002529 | Pride | 2016-01-26

REPOSITORIES: Pride

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Publications

Milk Bottom-Up Proteomics: Method Optimization.

Vincent Delphine D Ezernieks Vilnis V Elkins Aaron A Nguyen Nga N Moate Peter J PJ Cocks Benjamin G BG Rochfort Simone S

Frontiers in genetics 20160111

Milk is a complex fluid whose proteome displays a diverse set of proteins of high abundance such as caseins and medium to low abundance whey proteins such as ß-lactoglobulin, lactoferrin, immunoglobulins, glycoproteins, peptide hormones, and enzymes. A sample preparation method that enables high reproducibility and throughput is key in reliably identifying proteins present or proteins responding to conditions such as a diet, health or genetics. Using skim milk samples from Jersey and Holstein-Fr ...[more]

PMID: 26793233

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Project description:The objective of this study was to determine the effect of the DGAT1 K232A polymorphism on the global mRNA expression pattern of genes in the mammary gland tissue of grazing dairy cows in order to get more insight into the effects of this polymorphism on the physiology of the mammary glandgland of grazing dairy cows. Microarray analysis was used to identify genes whose expression was affected by the DGAT1 polymorphism in the mammary gland biopsies of 9 A232A cows, 13 K232A cows, and 4 K232K cows. The Microarray Analysis of Variance (MAANOVA) and Factor Analysis for Multiple Testing method (FAMT) were used to associate the expression of the genes present on Affymettrix Bovine Genome Arrays with the DGAT1 polymorphism. The data was also analysed at the level of functional modules by gene set enrichment analysis. In this experimental setting, DGAT1 polymorphism did not modify milk yield and composition significantly, although changes occurred in the yields of C14:0, C16:1cis-9, and some long chain fatty acids in milk. The DGAT1 polymorphism resulted in 30 differentially expressed genes related to cell growth, proliferation and development, signalling, remodelling and immune system. At the functional level, the pathways most affected by DGAT1 polymorphism were related to lipid biosynthesis, which likely reflected counter mechanisms of mammary tissue to respond to changes in milk FA composition, signalling, as well as immune system responses. A total of 28 Holstein-Friesian dairy cows in mid-lactation (DIM; 153 M-BM-1 32.8 days), milk yield (25.7 M-BM-1 3.08 kg/d) and fat content (4.3 M-BM-1 0.12%) were used in the study. Two consecutive milk samples (a.m. and p.m. milking) were obtained and pooled. One aliquot was stored at 4M-BM-0C until analysis of fat, protein and lactose percentage, and another aliquot was frozen at -20M-BM-0C until analysis for FA composition by gas chromatography. Specific details regarding the analysis of FA in milk are presented in Mach et al. (2011). Approximately 750 to 1,000 mg of mammary tissue from each cow was obtained by surgical biopsy. One part of the tissue was used for isolation of DNA and the other for extraction of the RNA. Genotyping of the DGAT1 polymorphism was performed using a TaqMan allelic discrimination method in an Applied Biosystems 7500 Real-Time PCR System (Applied Biosystems) as described by Schennink et al. (2007). The genotype at the DGAT1 locus was designated KK, KA, or AA for homozygous Lysine, heterozygous Lysine/Alanine, or homozygous Alanine, respectively. Microarray analysis was used to identify genes whose expression was affected by the DGAT1 polymorphism in the mammary gland biopsies of 11 A232A cows, 13 K232A cows, and 4 K232K cows. Total RNA from mammary gland tissue (50-100 mg) was isolated using TRIzol reagent (Invitrogen, Breda, The Netherlands), following the manufacturerM-bM-^@M-^Ys instructions. The RNA purity and concentrations were determined using a NanoDrop ND-1000 spectrophotometer (Isogen, Maarssen, the Netherlands), and the RNA quality was assessed using the BioAnalyzer 2100 (Agilent Technologies, Amsterdam, the Netherlands). The RNA of each biopsy was amplified, biotin-labeled, and hybridized to single-dye Affymetrix GeneChipM-BM-. Bovine Genome Array (#900493) by ServiceXS (Leiden, the Netherlands)

Dataset Information

Milk bottom-up proteomics: method optimisation.

Publications

Milk Bottom-Up Proteomics: Method Optimization.

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