Dataset Information

Milk proteome from in silico data aggregation allows the identification of putative biomarkers of negative energy balance in dairy cows.

ABSTRACT: A better knowledge of the bovine milk proteome and its main drivers is a prerequisite for the modulation of bioactive proteins in milk for human nutrition, as well as for the discovery of biomarkers that are useful in husbandry and veterinary medicine. Milk composition is affected by lactation stage and reflects, in part, the energy balance of dairy cows. We aggregated the cow milk proteins reported in 20 recent proteomics publications to produce an atlas of 4654 unique proteins. A multistep assessment was applied to the milk proteome datasets according to lactation stages and milk fractions, including annotations, pathway analysis and literature mining. Fifty-nine proteins were exclusively detected in milk from early lactation. Among them, we propose six milk proteins as putative biomarkers of negative energy balance based on their implication in metabolic adaptative pathways. These proteins are PCK2, which is a gluconeogenic enzyme; ACAT1 and IVD, which are involved in ketone metabolism; SDHA and UQCRC1, which are related to mitochondrial oxidative metabolism; and LRRC59, which is linked to mammary gland cell proliferation. The cellular origin of these proteins warrants more in-depth research but may constitute part of a molecular signature for metabolic adaptations typical of early lactation.

SUBMITTER: Delosiere M

PROVIDER: S-EPMC6609625 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Milk proteome from in silico data aggregation allows the identification of putative biomarkers of negative energy balance in dairy cows.

Delosière Mylène M Pires José J Bernard Laurence L Cassar-Malek Isabelle I Bonnet Muriel M

Scientific reports 20190704 1

A better knowledge of the bovine milk proteome and its main drivers is a prerequisite for the modulation of bioactive proteins in milk for human nutrition, as well as for the discovery of biomarkers that are useful in husbandry and veterinary medicine. Milk composition is affected by lactation stage and reflects, in part, the energy balance of dairy cows. We aggregated the cow milk proteins reported in 20 recent proteomics publications to produce an atlas of 4654 unique proteins. A multistep ass ...[more]

PMID: 31273261

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Project description:Milk is a highly nutritious natural product that provides not only a rich source of amino acids to the consumer but also hundreds of bioactive peptides and proteins known to elicit health-benefitting activities. We investigated the milk protein profile produced by Holstein and Jersey dairy cows maintained under the same diet, management and environmental conditions using proteomic approaches that optimize protein extraction and characterization of the low abundance proteins within the skim milk fraction of bovine milk. In total, 935 low abundance proteins were identified. Gene ontology classified all proteins identified into various cellular localization and function categories. A total of 43 low abundance proteins were differentially expressed between the two dairy breeds. Bioactive proteins involved in host-defense, including lactotransferrin (P=0.0026) and complement C2 protein (P=0.0001), were differentially expressed by the two breeds, whereas others such as osteopontin (P=0.1788) and lactoperoxidase (P=0.2973) were not. This work is the first to outline the protein profile produced by two important breeds of dairy cattle maintained under the same diet, environment and management conditions in order to observe likely true breed differences. This research now allows us to better understand and contrast further research examining the bovine proteome that includes these different breeds.Biological significanceWithin the last decade, the amount of research characterizing the bovine milk proteome has increased due to growing interest in the bioactive proteins that are present in milk. Proteomic analysis of low abundance whey proteins has mainly focused on human breast milk; however, previous research has highlighted the presence of bioactive proteins in bovine milk. Recent publications outlining the cross-reactivity of bovine bioactive proteins on human biological function highlight the need for further investigation into the bovine milk proteome. The rationale behind this study is to characterize and compare the low abundance protein profile in the skim milk fraction produced from Holstein and Jersey breeds of dairy cattle, which are two major dairy cattle breeds in the USA. A combination of fractionation strategies was used to efficiently enrich the low abundance proteins from bovine skim milk for proteomic profiling. A total of 935 low abundance proteins were identified and compared between the two bovine breeds. The results from this study provide insight into breed differences and similarities in the milk proteome profile produced by two breeds of dairy cattle.

Project description:Background: The liver is central to most economically important metabolic processes in cattle. However, the changes in expression of genes that drive these processes remain incompletely characterised. RNA-seq is the new gold standard for whole transcriptome analysis but so far there are no reports of its application to analysis of differential gene expression in cattle liver. We used RNA-seq to study differences in expression profiles of hepatic genes and their associated pathways in individual cattle in either mild negative energy balance (MNEB) or severe negative energy balance (SNEB). NEB is an imbalance between energy intake and energy requirements for lactation and body maintenance. This aberrant metabolic state affects high-yielding dairy cows after calving and is of considerable economic importance because of its negative impact on fertility and health in dairy herds. Analysis of changes in hepatic gene expression in SNEB animals will increase our understanding of NEB and contribute to the development of strategies to circumvent it. Results: RNA-seq analysis was carried out on total RNA from liver from early post partum Holstein Friesian cows in MNEB (n=5) and SNEB (n=6). 12,833 genes were deemed to be expressed (>4 reads per gene per animal), 413 of which were shown to be statistically significantly differentially expressed (SDE) at a false discovery rate (FDR) of 0.1% and 200 of which were SDE (FDR of 0.1%) with a ≥2-fold change between MNEB and SNEB animals. GOseq/KEGG pathway analysis showed that SDE genes with ≥2- fold change were associated (P <0.05) with 9 KEGG pathways. Seven of these pathways were related to fatty acid metabolism and unexpectedly included ‘Steroid hormone biosynthesis’, a process which mainly occurs in the reproductive organs rather than the liver. Conclusions: RNA-seq analysis showed that the major changes at the level of transcription in the liver of SNEB cows were related to fat metabolism. 'Steroid hormone biosynthesis', a process that normally occurs in reproductive tissue, was significantly associated with changes in gene expression in the liver of SNEB cows. Changes in gene expression were found in this pathway that have not been previously been identified in SNEB cows. 11 liver RNA samples were analysed in total, 6 samples were from SNEB animals and 5 samples from MNEB animals

Dataset Information

Milk proteome from in silico data aggregation allows the identification of putative biomarkers of negative energy balance in dairy cows.

Publications

Milk proteome from in silico data aggregation allows the identification of putative biomarkers of negative energy balance in dairy cows.

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