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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 h...

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Autores principales: Shatsky, Maxim, Dong, Ming, Liu, Haichuan, Yang, Lee Lisheng, Choi, Megan, Singer, Mary E., Geller, Jil T., Fisher, Susan J., Hall, Steven C., Hazen, Terry C., Brenner, Steven E., Butland, Gareth, Jin, Jian, Witkowska, H. Ewa, Chandonia, John-Marc, Biggin, Mark D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Biochemistry and Molecular Biology 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5083090/
https://www.ncbi.nlm.nih.gov/pubmed/27099342
http://dx.doi.org/10.1074/mcp.M115.057117
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author Shatsky, Maxim
Dong, Ming
Liu, Haichuan
Yang, Lee Lisheng
Choi, Megan
Singer, Mary E.
Geller, Jil T.
Fisher, Susan J.
Hall, Steven C.
Hazen, Terry C.
Brenner, Steven E.
Butland, Gareth
Jin, Jian
Witkowska, H. Ewa
Chandonia, John-Marc
Biggin, Mark D.
author_facet Shatsky, Maxim
Dong, Ming
Liu, Haichuan
Yang, Lee Lisheng
Choi, Megan
Singer, Mary E.
Geller, Jil T.
Fisher, Susan J.
Hall, Steven C.
Hazen, Terry C.
Brenner, Steven E.
Butland, Gareth
Jin, Jian
Witkowska, H. Ewa
Chandonia, John-Marc
Biggin, Mark D.
author_sort Shatsky, Maxim
collection PubMed
description 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.
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spelling pubmed-50830902016-11-01 Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions Shatsky, Maxim Dong, Ming Liu, Haichuan Yang, Lee Lisheng Choi, Megan Singer, Mary E. Geller, Jil T. Fisher, Susan J. Hall, Steven C. Hazen, Terry C. Brenner, Steven E. Butland, Gareth Jin, Jian Witkowska, H. Ewa Chandonia, John-Marc Biggin, Mark D. Mol Cell Proteomics Technological Innovation and Resources 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. The American Society for Biochemistry and Molecular Biology 2016-06 2016-04-20 /pmc/articles/PMC5083090/ /pubmed/27099342 http://dx.doi.org/10.1074/mcp.M115.057117 Text en © 2016 by The American Society for Biochemistry and Molecular Biology, Inc. Author's Choice—Final version free via Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0) .
spellingShingle Technological Innovation and Resources
Shatsky, Maxim
Dong, Ming
Liu, Haichuan
Yang, Lee Lisheng
Choi, Megan
Singer, Mary E.
Geller, Jil T.
Fisher, Susan J.
Hall, Steven C.
Hazen, Terry C.
Brenner, Steven E.
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
title Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions
title_full Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions
title_fullStr Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions
title_full_unstemmed Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions
title_short Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions
title_sort quantitative tagless copurification: a method to validate and identify protein-protein interactions
topic Technological Innovation and Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5083090/
https://www.ncbi.nlm.nih.gov/pubmed/27099342
http://dx.doi.org/10.1074/mcp.M115.057117
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