4.7 Article

Can Normal Protein Expression Ranges Be Estimated with High-Throughput Proteomics?

期刊

JOURNAL OF PROTEOME RESEARCH
卷 14, 期 6, 页码 2398-2407

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.5b00176

关键词

proteomics; protein expression; gene expression; variability; normal tissue; normal range; spectral counts

资金

  1. National Science Foundation under the Division of Biological Infrastructure [0969929]
  2. Seattle Children's Research Institute
  3. The Robert B. McMillen Foundation
  4. Div Of Biological Infrastructure
  5. Direct For Biological Sciences [0969929] Funding Source: National Science Foundation

向作者/读者索取更多资源

Although biological Science discovery often involves comparing conditions to a normal state, in proteomics little is actually known about normal. Two Human Proteome studies featured in Nature offer new insights into protein expression and an opportunity to assess how high-throughput proteomics measures normal protein, ranges. We use data from these studies to estimate technical and biological variability in protein expression and compare them to other expression data sets from normal tissue. Results show that measured protein expression across same-tissue replicates vary by +/- 4- to 10-fold for most proteins. Coefficients of variation (CV) for protein expression measurements range from 62% to 117% across different tissue experiments; however, adjusting for technical variation reduced this variability by as much as 50%. In addition, the CV could also be reduced by limiting comparisons to proteins with at least 3 or more unique peptide identifications as the CV was on average 33% lower than for proteins with 2 or fewer peptide identifications. We also selected 13 housekeeping proteins and genes that were expressed across all tissues with low variability to determine their utility as a reference set for normalization and comparative purposes. These results present the first step toward estimating normal protein ranges by determining the variability in expression measurements through combining publicly available data. They support an approach that combines standard protocols with replicates of normal tissues to estimate normal protein ranges for large numbers of proteins and tissues. This would be a tremendous resource for normal cellular physiology and comparisons of proteomics studies.

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