Inflect: Optimizing Computational Workflows for Thermal Proteome Profiling Data Analysis

Abstract

The use of CETSA and Thermal Proteome Profiling (TPP) analytical methods are invaluable for the study of protein-ligand interactions and protein stability in a cellular context. These tools have increasingly been leveraged in work ranging from understanding signaling paradigms to drug discovery. Consequently, there is an important need to optimize the data analysis pipeline that is used to calculate protein melt temperatures (Tm) and relative melt shifts from proteomics abundance data. Here we report a user-friendly analysis of the melt shift calculation workflow where we describe the impact of each individual calculation step on the final output list of stabilized and destabilized proteins. This report also includes a description of how key steps in the analysis workflow quantitatively impacts the list of stabilized/destabilized proteins from an experiment. We applied our findings to develop a more optimized analysis workflow that illustrates the dramatic sensitivity of chosen calculation steps on the final list of reported proteins of interest in a study and will make the R based program Inflect available for research community use. Overall, this work provides an essential resource for scientists as they analyze data from TPP and CETSA experiments and implement their own analysis pipelines geared towards specific applications.

CHalf: Folding Stability Made Simple

“…C Half utilizes a more traditional curve fitting eq (eq 1), whereas Inflect utilizes its own logistic fitting method optimized for TPP as described in its release paper. 10 Both methods have been shown to produce useful PFS curves but do not produce the same quality control metrics to allow for complete direct comparison. Comparing the results yielded from both programs with comparable quality control metrics (curves with C 1/2 values within the range of 34 and 64 degrees and having an R 2 value of greater than 0.6), C Half produced 8237 curves compared to Inflect, producing 6968 curves.…”

Obtaining Increased Functional Proteomics Insights from Thermal Proteome Profiling through Optimized Melt Shift Calculation and Statistical Analysis

“…Algorithms that have been reported by the scientific community are TPP-TR, MSstatsTMT, and Inflect. [13][14][15] Advances in TPP data analysis to date, however, have yet to fully address computational challenges in finding reproducible and significant melt shift changes from TPP datasets. One aspect of TPP that has lagged behind is the development of computational tools to determine which melt shifts are "statistically significant".…”

“…Here we will introduce an updated version of our previously reported program Inflect and have also assessed its utility. 13, 17 In order to improve the sensitivity and selectivity of the computational workflow for biologically-relevant proteins, we have incorporated a z-score and p-value based assessment into the next version of Inflect, InflectSSP. We have also investigated the relative use of quality control variables in the computational analysis pipeline which include number of peptide spectrum matches or unique peptides in the MS experiment along with the melt curve R 2 .…”