Obtaining Functional Proteomics Insights From Thermal Proteome Profiling Through Optimized Melt Shift Calculation and Statistical Analysis With InflectSSP
Thermal proteome profiling (TPP) is an invaluable tool for functional proteomics studies that has been shown to discover changes associated with protein–ligand, protein–protein, and protein–RNA interaction dynamics along with changes in protein stability resulting from cellular signaling. The increa...
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description | Thermal proteome profiling (TPP) is an invaluable tool for functional proteomics studies that has been shown to discover changes associated with protein–ligand, protein–protein, and protein–RNA interaction dynamics along with changes in protein stability resulting from cellular signaling. The increasing number of reports employing this assay has not been met concomitantly with new approaches leading to advancements in the quality and sensitivity of the corresponding data analysis. The gap between data acquisition and data analysis tools is important to fill as TPP findings have reported subtle melt shift changes related to signaling events such as protein posttranslational modifications. In this study, we have improved the Inflect data analysis pipeline (now referred to as InflectSSP, available at https://CRAN.R-project.org/package=InflectSSP) to increase the sensitivity of detection for both large and subtle changes in the proteome as measured by TPP. Specifically, InflectSSP now has integrated statistical and bioinformatic functions to improve objective functional proteomics findings from the quantitative results obtained from TPP studies through increasing both the sensitivity and specificity of the data analysis pipeline. InflectSSP incorporates calculation of a “melt coefficient” into the pipeline with production of average melt curves for biological replicate studies to aid in identification of proteins with significant melts. To benchmark InflectSSP, we have reanalyzed two previously reported datasets to demonstrate the performance of our publicly available R-based program for TPP data analysis. We report new findings following temporal treatment of human cells with the small molecule thapsigargin that induces the unfolded protein response as a consequence of inhibition of sarcoplasmic/endoplasmic reticulum calcium ATPase 2A. InflectSSP analysis of our unfolded protein response study revealed highly reproducible and statistically significant target engagement over a time course of treatment while simultaneously providing new insights into the possible mechanisms of action of the small molecule thapsigargin.
[Display omitted]
•InflectSSP for computational and statistical analysis of thermal proteome profiling.•Novel integrative replicate analyses for calculation of p-values for melt shifts.•Melt shift coefficient provides new metric for TPP hit prioritization.•InflectSSP provides highly reproducible detection of temporal target engagement.•Identifica |
doi_str_mv | 10.1016/j.mcpro.2023.100630 |
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[Display omitted]
•InflectSSP for computational and statistical analysis of thermal proteome profiling.•Novel integrative replicate analyses for calculation of p-values for melt shifts.•Melt shift coefficient provides new metric for TPP hit prioritization.•InflectSSP provides highly reproducible detection of temporal target engagement.•Identification of candidate downstream effectors of the inhibitor thapsigargin.
In this work, we describe our computational workflow for statistical analysis of thermal proteome profiling data known as InflectSSP. InflectSSP has been optimized for sensitive and reproducible detection and prioritization of protein melt shift changes in biological thermal proteome profiling datasets. Analysis of induction of the unfolded protein response with the small molecule inhibitor thapsigargin using InflectSSP revealed significant melt shift changes that shed new light on the potential mechanisms of action of inhibition of the ER calcium channel SERCA2.</description><identifier>ISSN: 1535-9476</identifier><identifier>ISSN: 1535-9484</identifier><identifier>EISSN: 1535-9484</identifier><identifier>DOI: 10.1016/j.mcpro.2023.100630</identifier><identifier>PMID: 37562535</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>functional proteomics ; Humans ; InflectSSP ; Proteome - metabolism ; Proteomics - methods ; Thapsigargin ; Thapsigargin - pharmacology ; thermal proteome profiling ; unfolded protein response</subject><ispartof>Molecular & cellular proteomics, 2023-09, Vol.22 (9), p.100630, Article 100630</ispartof><rights>2023 The Authors</rights><rights>Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.</rights><rights>2023 The Authors 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c460t-58f0e7aacce4d78e9796498e8b836d726934a3ce905d99d552b603619680cca03</citedby><cites>FETCH-LOGICAL-c460t-58f0e7aacce4d78e9796498e8b836d726934a3ce905d99d552b603619680cca03</cites><orcidid>0000-0003-4897-929X ; 0000-0002-8209-5626 ; 0000-0001-5822-2894 ; 0000-0001-6798-6407 ; 0000-0003-0356-7478</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494267/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494267/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37562535$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>McCracken, Neil A.</creatorcontrib><creatorcontrib>Liu, Hao</creatorcontrib><creatorcontrib>Runnebohm, Avery M.</creatorcontrib><creatorcontrib>Wijeratne, H.R. Sagara</creatorcontrib><creatorcontrib>Wijeratne, Aruna B.</creatorcontrib><creatorcontrib>Staschke, Kirk A.</creatorcontrib><creatorcontrib>Mosley, Amber L.</creatorcontrib><title>Obtaining Functional Proteomics Insights From Thermal Proteome Profiling Through Optimized Melt Shift Calculation and Statistical Analysis With InflectSSP</title><title>Molecular & cellular proteomics</title><addtitle>Mol Cell Proteomics</addtitle><description>Thermal proteome profiling (TPP) is an invaluable tool for functional proteomics studies that has been shown to discover changes associated with protein–ligand, protein–protein, and protein–RNA interaction dynamics along with changes in protein stability resulting from cellular signaling. The increasing number of reports employing this assay has not been met concomitantly with new approaches leading to advancements in the quality and sensitivity of the corresponding data analysis. The gap between data acquisition and data analysis tools is important to fill as TPP findings have reported subtle melt shift changes related to signaling events such as protein posttranslational modifications. In this study, we have improved the Inflect data analysis pipeline (now referred to as InflectSSP, available at https://CRAN.R-project.org/package=InflectSSP) to increase the sensitivity of detection for both large and subtle changes in the proteome as measured by TPP. Specifically, InflectSSP now has integrated statistical and bioinformatic functions to improve objective functional proteomics findings from the quantitative results obtained from TPP studies through increasing both the sensitivity and specificity of the data analysis pipeline. InflectSSP incorporates calculation of a “melt coefficient” into the pipeline with production of average melt curves for biological replicate studies to aid in identification of proteins with significant melts. To benchmark InflectSSP, we have reanalyzed two previously reported datasets to demonstrate the performance of our publicly available R-based program for TPP data analysis. We report new findings following temporal treatment of human cells with the small molecule thapsigargin that induces the unfolded protein response as a consequence of inhibition of sarcoplasmic/endoplasmic reticulum calcium ATPase 2A. InflectSSP analysis of our unfolded protein response study revealed highly reproducible and statistically significant target engagement over a time course of treatment while simultaneously providing new insights into the possible mechanisms of action of the small molecule thapsigargin.
[Display omitted]
•InflectSSP for computational and statistical analysis of thermal proteome profiling.•Novel integrative replicate analyses for calculation of p-values for melt shifts.•Melt shift coefficient provides new metric for TPP hit prioritization.•InflectSSP provides highly reproducible detection of temporal target engagement.•Identification of candidate downstream effectors of the inhibitor thapsigargin.
In this work, we describe our computational workflow for statistical analysis of thermal proteome profiling data known as InflectSSP. InflectSSP has been optimized for sensitive and reproducible detection and prioritization of protein melt shift changes in biological thermal proteome profiling datasets. Analysis of induction of the unfolded protein response with the small molecule inhibitor thapsigargin using InflectSSP revealed significant melt shift changes that shed new light on the potential mechanisms of action of inhibition of the ER calcium channel SERCA2.</description><subject>functional proteomics</subject><subject>Humans</subject><subject>InflectSSP</subject><subject>Proteome - metabolism</subject><subject>Proteomics - methods</subject><subject>Thapsigargin</subject><subject>Thapsigargin - pharmacology</subject><subject>thermal proteome profiling</subject><subject>unfolded protein response</subject><issn>1535-9476</issn><issn>1535-9484</issn><issn>1535-9484</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9UcuO0zAUjRCIecAXICEv2bTYcezEC4RG1ZQZaVBHahFLy3VuGleOXWxnpOFT-FocOhTYsPKR73lc3VMUbwieE0z4-_180Ifg5yUuaf7BnOJnxTlhlM1E1VTPT7jmZ8VFjHuMS0xq9rI4ozXjZR6eFz9W26SMM26HlqPTyXinLLoPPoEfjI7o1kWz61NEy-AHtOkhDH8IMIHO2Em-6YMfdz1aHZIZzHdo0WewCa170yW0UFaPVk32SLkWrVPGMRmdva5y4mM0EX01qc95nQWd1uv7V8WLTtkIr5_ey-LL8nqzuJndrT7dLq7uZrriOM1Y02GoldIaqrZuQNSCV6KBZttQ3tYlF7RSVIPArBWiZazcckw5EbzBWitML4uPR9_DuB2g1eBSUFYeghlUeJReGfnvxJle7vyDJLgSVcnr7PDuySH4byPEJAcTNVirHPgxyrJhmBLKapKp9EjVwccYoDvlECynWuVe_qpVTrXKY61Z9fbvFU-a3z1mwocjAfKhHgwEGbUBp6E1IV9Ttt78N-AnpOe4oA</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>McCracken, Neil A.</creator><creator>Liu, Hao</creator><creator>Runnebohm, Avery M.</creator><creator>Wijeratne, H.R. Sagara</creator><creator>Wijeratne, Aruna B.</creator><creator>Staschke, Kirk A.</creator><creator>Mosley, Amber L.</creator><general>Elsevier Inc</general><general>American Society for Biochemistry and Molecular Biology</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4897-929X</orcidid><orcidid>https://orcid.org/0000-0002-8209-5626</orcidid><orcidid>https://orcid.org/0000-0001-5822-2894</orcidid><orcidid>https://orcid.org/0000-0001-6798-6407</orcidid><orcidid>https://orcid.org/0000-0003-0356-7478</orcidid></search><sort><creationdate>20230901</creationdate><title>Obtaining Functional Proteomics Insights From Thermal Proteome Profiling Through Optimized Melt Shift Calculation and Statistical Analysis With InflectSSP</title><author>McCracken, Neil A. ; Liu, Hao ; Runnebohm, Avery M. ; Wijeratne, H.R. Sagara ; Wijeratne, Aruna B. ; Staschke, Kirk A. ; Mosley, Amber L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c460t-58f0e7aacce4d78e9796498e8b836d726934a3ce905d99d552b603619680cca03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>functional proteomics</topic><topic>Humans</topic><topic>InflectSSP</topic><topic>Proteome - metabolism</topic><topic>Proteomics - methods</topic><topic>Thapsigargin</topic><topic>Thapsigargin - pharmacology</topic><topic>thermal proteome profiling</topic><topic>unfolded protein response</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>McCracken, Neil A.</creatorcontrib><creatorcontrib>Liu, Hao</creatorcontrib><creatorcontrib>Runnebohm, Avery M.</creatorcontrib><creatorcontrib>Wijeratne, H.R. Sagara</creatorcontrib><creatorcontrib>Wijeratne, Aruna B.</creatorcontrib><creatorcontrib>Staschke, Kirk A.</creatorcontrib><creatorcontrib>Mosley, Amber L.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Molecular & cellular proteomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>McCracken, Neil A.</au><au>Liu, Hao</au><au>Runnebohm, Avery M.</au><au>Wijeratne, H.R. Sagara</au><au>Wijeratne, Aruna B.</au><au>Staschke, Kirk A.</au><au>Mosley, Amber L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Obtaining Functional Proteomics Insights From Thermal Proteome Profiling Through Optimized Melt Shift Calculation and Statistical Analysis With InflectSSP</atitle><jtitle>Molecular & cellular proteomics</jtitle><addtitle>Mol Cell Proteomics</addtitle><date>2023-09-01</date><risdate>2023</risdate><volume>22</volume><issue>9</issue><spage>100630</spage><pages>100630-</pages><artnum>100630</artnum><issn>1535-9476</issn><issn>1535-9484</issn><eissn>1535-9484</eissn><abstract>Thermal proteome profiling (TPP) is an invaluable tool for functional proteomics studies that has been shown to discover changes associated with protein–ligand, protein–protein, and protein–RNA interaction dynamics along with changes in protein stability resulting from cellular signaling. The increasing number of reports employing this assay has not been met concomitantly with new approaches leading to advancements in the quality and sensitivity of the corresponding data analysis. The gap between data acquisition and data analysis tools is important to fill as TPP findings have reported subtle melt shift changes related to signaling events such as protein posttranslational modifications. In this study, we have improved the Inflect data analysis pipeline (now referred to as InflectSSP, available at https://CRAN.R-project.org/package=InflectSSP) to increase the sensitivity of detection for both large and subtle changes in the proteome as measured by TPP. Specifically, InflectSSP now has integrated statistical and bioinformatic functions to improve objective functional proteomics findings from the quantitative results obtained from TPP studies through increasing both the sensitivity and specificity of the data analysis pipeline. InflectSSP incorporates calculation of a “melt coefficient” into the pipeline with production of average melt curves for biological replicate studies to aid in identification of proteins with significant melts. To benchmark InflectSSP, we have reanalyzed two previously reported datasets to demonstrate the performance of our publicly available R-based program for TPP data analysis. We report new findings following temporal treatment of human cells with the small molecule thapsigargin that induces the unfolded protein response as a consequence of inhibition of sarcoplasmic/endoplasmic reticulum calcium ATPase 2A. InflectSSP analysis of our unfolded protein response study revealed highly reproducible and statistically significant target engagement over a time course of treatment while simultaneously providing new insights into the possible mechanisms of action of the small molecule thapsigargin.
[Display omitted]
•InflectSSP for computational and statistical analysis of thermal proteome profiling.•Novel integrative replicate analyses for calculation of p-values for melt shifts.•Melt shift coefficient provides new metric for TPP hit prioritization.•InflectSSP provides highly reproducible detection of temporal target engagement.•Identification of candidate downstream effectors of the inhibitor thapsigargin.
In this work, we describe our computational workflow for statistical analysis of thermal proteome profiling data known as InflectSSP. InflectSSP has been optimized for sensitive and reproducible detection and prioritization of protein melt shift changes in biological thermal proteome profiling datasets. Analysis of induction of the unfolded protein response with the small molecule inhibitor thapsigargin using InflectSSP revealed significant melt shift changes that shed new light on the potential mechanisms of action of inhibition of the ER calcium channel SERCA2.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>37562535</pmid><doi>10.1016/j.mcpro.2023.100630</doi><orcidid>https://orcid.org/0000-0003-4897-929X</orcidid><orcidid>https://orcid.org/0000-0002-8209-5626</orcidid><orcidid>https://orcid.org/0000-0001-5822-2894</orcidid><orcidid>https://orcid.org/0000-0001-6798-6407</orcidid><orcidid>https://orcid.org/0000-0003-0356-7478</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | functional proteomics Humans InflectSSP Proteome - metabolism Proteomics - methods Thapsigargin Thapsigargin - pharmacology thermal proteome profiling unfolded protein response |
title | Obtaining Functional Proteomics Insights From Thermal Proteome Profiling Through Optimized Melt Shift Calculation and Statistical Analysis With InflectSSP |
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