Dataset Information

Label-free Quantitative Analysis of Changes in Broiler Liver Proteins under Heat Stress using SWATH-MS Technology.

ABSTRACT: High temperature is one of the key environmental stressors affecting broiler production efficiency and meat yield. Knowledge of broiler self-regulation mechanisms under heat stress is important for the modern scale of poultry breeding. In the present study, the SWATH strategy was employed to investigate the temporal response of the broiler liver to heat stress. A total of 4,271 proteins were identified and used to generate a reference library for SWATH analysis. During this analysis, 2,377 proteins were quantified, with a coefficient of variation ?25% among technical and biological replicates. A total of 257 proteins showed differential expression between the control and heat stressed groups. Consistent results for 26 and 5 differential proteins were validated respectively by MRM and western blotting quantitative analyses. Bioinformatics analysis suggests that the up- and down-regulation of these proteins appear involved in the following three categories of cellular pathways and metabolisms: 1) inhibit the ERK signaling pathway; 2) affect broiler liver lipid and amino acid metabolism; 3) induce liver cell immune responses to adapt to the high temperatures and reduce mortality. The study reported here provides an insight into broiler self-regulation mechanisms and shed light on the improved broiler adaptability to high-temperature environments.

SUBMITTER: Tang X

PROVIDER: S-EPMC4602270 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Label-free Quantitative Analysis of Changes in Broiler Liver Proteins under Heat Stress using SWATH-MS Technology.

Tang Xiangfang X Meng Qingshi Q Gao Jie J Zhang Sheng S Zhang Hongfu H Zhang Minhong M

Scientific reports 20151013

High temperature is one of the key environmental stressors affecting broiler production efficiency and meat yield. Knowledge of broiler self-regulation mechanisms under heat stress is important for the modern scale of poultry breeding. In the present study, the SWATH strategy was employed to investigate the temporal response of the broiler liver to heat stress. A total of 4,271 proteins were identified and used to generate a reference library for SWATH analysis. During this analysis, 2,377 prote ...[more]

PMID: 26459884

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Project description:BackgroundSWATH-MS has emerged as the strategy of choice for biomarker discovery due to the proteome coverage achieved in acquisition and provision to re-interrogate the data. However, in quantitative analysis using SWATH, each sample from the comparison group is run individually in mass spectrometer and the resulting inter-run variation may influence relative quantification and identification of biomarkers. Normalization of data to diminish this variation thereby becomes an essential step in SWATH data processing. In most reported studies, data normalization methods used are those provided in instrument-based data analysis software or those used for microarray data. This study, for the first time provides an experimental evidence for selection of normalization method optimal for biomarker identification.MethodsThe efficiency of 12 normalization methods to normalize SWATH-MS data was evaluated based on statistical criteria in 'Normalyzer'-a tool which provides comparative evaluation of normalization by different methods. Further, the suitability of normalized data for biomarker discovery was assessed by evaluating the clustering efficiency of differentiators, identified from the normalized data based on p-value, fold change and both, by hierarchical clustering in Genesis software v.1.8.1.ResultsConventional statistical criteria identified VSN-G as the optimal method for normalization of SWATH data. However, differentiators identified from VSN-G normalized data failed to segregate test and control groups. We thus assessed data normalized by eleven other methods for their ability to yield differentiators which segregate the study groups. Datasets in our study demonstrated that differentiators identified based on p-value from data normalized with Loess-R stratified the study groups optimally.ConclusionThis is the first report of experimentally tested strategy for SWATH-MS data processing with an emphasis on identification of clinically relevant biomarkers. Normalization of SWATH-MS data by Loess-R method and identification of differentiators based on p-value were found to be optimal for biomarker discovery in this study. The study also demonstrates the need to base the choice of normalization method on the application of the data.

Dataset Information

Label-free Quantitative Analysis of Changes in Broiler Liver Proteins under Heat Stress using SWATH-MS Technology.

Publications

Label-free Quantitative Analysis of Changes in Broiler Liver Proteins under Heat Stress using SWATH-MS Technology.

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