Label-Free Quantitative Thermal Proteome Profiling Reveals Target Transcription Factors with Activities Modulated by MC3R Signaling.

Thermal proteome profiling with label-free quantitation using ion-mobility-enhanced LC-MS offers versatile data sets, providing information on protein differential expression, thermal stability, and the activities of transcription factors. We developed a multidimensional data analysis workflow for label-free quantitative thermal proteome profiling (TPP) experiments that incorporates the aspects of gene set enrichment analysis, differential protein expression analysis, and inference of transcription factor activities from LC-MS data. We applied it to study the signaling processes downstream of melanocortin 3 receptor (MC3R) activation by endogenous agonists derived from the proopiomelanocortin prohormone: ACTH, α-MSH, and γ-MSH. The obtained information was used to map signaling pathways downstream of MC3R and to deduce transcription factors responsible for cellular response to ligand treatment. Using our workflow, we identified differentially expressed proteins and investigated their thermal stability. We found in total 298 proteins with altered thermal stability, resulting from MC3R activation. Out of these, several proteins were transcription factors, indicating them as being downstream target regulators that take part in the MC3R signaling cascade. We found transcription factors CCAR2, DDX21, HMGB2, SRSF7, and TET2 to have altered thermal stability. These apparent target transcription factors within the MC3R signaling cascade play important roles in immune responses. Additionally, we inferred the activities of the transcription factors identified in our data set. This was done with Bayesian statistics using the differential expression data we obtained with label-free quantitative LC-MS. The inferred transcription factor activities were validated in our bioinformatic pipeline by the phosphorylated peptide abundances that we observed, highlighting the importance of post-translational modifications in transcription factor regulation. Our multidimensional data analysis workflow allows for a comprehensive characterization of the signaling processes downstream of MC3R activation. It provides insights into protein differential expression, thermal stability, and activities of key transcription factors. All proteomic data generated in this study are publicly available at DOI: 10.6019/PXD039945.

Well-Plate µFASP for Proteomic Analysis of Single Pancreatic Islets.

Filter-aided sample preparation (FASP) is widely used in bottom-up proteomics for tryptic digestion. However, the sample recovery yield of this method is limited by the amount of the starting material. While ∼100 ng of digested protein is sufficient for thorough protein identification, proteomic information gets lost with a protein content <10 µg due to incomplete peptide recovery from the filter. We developed and optimized a flexible well-plate µFASP device and protocol that is suitable for an ∼1 µg protein sample. In 1 µg of HeLa digest, we identified 1295 ± 10 proteins with µFASP followed by analysis with liquid chromatography-mass spectrometry. In contrast, only 524 ± 5 proteins were identified with the standard FASP protocol, while 1395 ± 4 proteins were identified in 20 µg after standard FASP as a benchmark. Furthermore, we conducted a combined peptidomic and proteomic study of single pancreatic islets with well-plate µFASP. Here, we separated neuropeptides and digested the remaining on-filter proteins for bottom-up proteomic analysis. Our results indicate inter-islet heterogeneity for the expression of proteins involved in glucose catabolism, pancreatic hormone processing, and secreted peptide hormones. We consider our method to provide a useful tool for proteomic characterization of samples where the biological material is scarce. All proteomic data are available under DOI: 10.6019/PXD029039.