Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics

乳腺组学,乳房链球菌乳腺炎实验模型中牛奶的综合组学:2. 无标记相对定量蛋白质组学

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作者:Manikhandan Mudaliar, Riccardo Tassi, Funmilola C Thomas, Tom N McNeilly, Stefan K Weidt, Mark McLaughlin, David Wilson, Richard Burchmore, Pawel Herzyk, P David Eckersall, Ruth N Zadoks

Abstract

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously.

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