Molecular and Cellular Proteomics | May 12, 2021

Napierala JS, Rajapakshe K, Clark A, Chen YY, Huang S, Mesaros C, Xu P, Blair IA, Hauser LA, Farmer J, Lynch DR, Edwards DP, Coarfa C and Napierala M

Mol Cell Proteomics. 2021 May 12;100094

DOI: 10.1016/j.mcpro.2021.100094

Abstract

Identifying biomarkers is important for assessment of disease progression, prediction of symptom development, and determination of treatment effectiveness. While unbiased analyses of differential gene expression using next generation sequencing methods are now routinely conducted, proteomics studies are more challenging due to traditional methods predominantly being low-throughput and offering a limited dynamic range for simultaneous detection of hundreds of proteins that drastically differ in their intracellular abundance. We utilized a sensitive and high-throughput proteomic technique, reverse phase protein array (RPPA), to attain protein expression profiles of primary fibroblasts obtained from Friedreich’s ataxia (FRDA) patients and unaffected controls. The RPPA was designed to detect 217 proteins or phosphorylated proteins by individual antibody, and the specificity of each antibody was validated prior to the experiment. Among sixty-two fibroblast samples (44 FRDA and 18 controls) analyzed, 30 proteins/phosphoproteins were significantly changed in FRDA fibroblasts compared to control cells (p<0.05), mostly representing signaling molecules and metabolic enzymes. As expected, frataxin (FXN) was significantly downregulated in FRDA samples, thus serving as an internal control for assay integrity. Extensive bioinformatic analyses were conducted to correlate differentially expressed proteins with critical disease parameters (e.g. selected symptoms, age of onset, GAA sizes, FXN levels, FARS scores). Members of the integrin family of proteins specifically associated with hearing loss in FRDA. Also, RPPA data, combined with results of transcriptome profiling, uncovered defects in the retinoic acid (RA) metabolism pathway in FRDA samples. Moreover, expression of ALDH1A3 differed significantly between cardiomyopathy positive and negative FRDA cohorts, demonstrating that metabolites such as retinol, retinal or RA could become potential predictive biomarkers of cardiac presentation in FRDA.