skip to main content

DOE PAGESDOE PAGES

Title: Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification of endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomesmore » and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less
Authors:
 [1] ;  [1] ;  [2] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [2] ;  [3] ;  [1] ;  [1] ;  [1] ;  [2] ;  [1] ;  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of California, San Francisco, CA (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Grant/Contract Number:
AC05-00OR22725; AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Molecular and Cellular Proteomics
Additional Journal Information:
Journal Volume: 15; Journal Issue: 6; Journal ID: ISSN 1535-9476
Publisher:
American Society for Biochemistry and Molecular Biology
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES
OSTI Identifier:
1329772
Alternate Identifier(s):
OSTI ID: 1354679; OSTI ID: 1379369

Shatsky, Maxim, Dong, Ming, Liu, Haichuan, Yang, Lee Lisheng, Choi, Megan, Singer, Mary, Geller, Jil, Fisher, Susan, Hall, Steven, Hazen, Terry C., Brenner, Steven, Butland, Gareth, Jin, Jian, Witkowska, H. Ewa, Chandonia, John-Marc, and Biggin, Mark D.. Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions. United States: N. p., Web. doi:10.1074/mcp.M115.057117.
Shatsky, Maxim, Dong, Ming, Liu, Haichuan, Yang, Lee Lisheng, Choi, Megan, Singer, Mary, Geller, Jil, Fisher, Susan, Hall, Steven, Hazen, Terry C., Brenner, Steven, Butland, Gareth, Jin, Jian, Witkowska, H. Ewa, Chandonia, John-Marc, & Biggin, Mark D.. Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions. United States. doi:10.1074/mcp.M115.057117.
Shatsky, Maxim, Dong, Ming, Liu, Haichuan, Yang, Lee Lisheng, Choi, Megan, Singer, Mary, Geller, Jil, Fisher, Susan, Hall, Steven, Hazen, Terry C., Brenner, Steven, Butland, Gareth, Jin, Jian, Witkowska, H. Ewa, Chandonia, John-Marc, and Biggin, Mark D.. 2016. "Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions". United States. doi:10.1074/mcp.M115.057117. https://www.osti.gov/servlets/purl/1329772.
@article{osti_1329772,
title = {Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions},
author = {Shatsky, Maxim and Dong, Ming and Liu, Haichuan and Yang, Lee Lisheng and Choi, Megan and Singer, Mary and Geller, Jil and Fisher, Susan and Hall, Steven and Hazen, Terry C. and Brenner, Steven and Butland, Gareth and Jin, Jian and Witkowska, H. Ewa and Chandonia, John-Marc and Biggin, Mark D.},
abstractNote = {Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification of endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.},
doi = {10.1074/mcp.M115.057117},
journal = {Molecular and Cellular Proteomics},
number = 6,
volume = 15,
place = {United States},
year = {2016},
month = {4}
}