Your browser doesn't support javascript.
loading
Obtaining Functional Proteomics Insights From Thermal Proteome Profiling Through Optimized Melt Shift Calculation and Statistical Analysis With InflectSSP.
McCracken, Neil A; Liu, Hao; Runnebohm, Avery M; Wijeratne, H R Sagara; Wijeratne, Aruna B; Staschke, Kirk A; Mosley, Amber L.
Afiliación
  • McCracken NA; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, United States.
  • Liu H; Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, United States; Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, New Jersey, United States.
  • Runnebohm AM; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, United States.
  • Wijeratne HRS; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, United States.
  • Wijeratne AB; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, United States.
  • Staschke KA; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, United States.
  • Mosley AL; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, United States; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA. Electronic address: almosley@iu.edu.
Mol Cell Proteomics ; 22(9): 100630, 2023 09.
Article en En | MEDLINE | ID: mdl-37562535
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.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteoma / Proteómica Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Mol Cell Proteomics Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteoma / Proteómica Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Mol Cell Proteomics Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
...