ABSTRACT
Alzheimer's disease (AD) is a common complex disease and a major public health burden in both developed and developing countries. Postgenomic technologies such as proteomics and intelligent mining of multi-omics Big Data offer new prospects for diagnostics and therapeutics innovation for AD. In this context, it is noteworthy that mass spectrometry (MS) data are often searched against proteomics databases to unravel the identity of protein biomarkers. In contrast, only a fraction of the MS data can be matched to known proteins, while a large portion of such raw data remains underutilized. Furthermore, the spectral data can be mined for multiple high-confidence post-translational modifications (PTMs) without a priori enrichment. Thus, AD research stands to gain by greater attention to the biological mechanisms regulated by PTMs. Protein modifications may serve as diagnostic biomarkers or as novel molecular targets for drug discovery. We report here novel PTMs discovered in relation to the AD from MS/MS-based proteomic datasets. Publicly available label-free proteomics data were searched for select PTMs using SEQUEST-HT. Only high-confidence PTMs were analyzed using bioinformatics analysis. We identified 4961 unique modified peptides corresponding to 1856 proteins from AD datasets. Of these, 52 proteins were known to be involved in Alzheimer's pathway. Importantly, 3164 PTMs reported in this study are novel in the context of AD. Furthermore, protein quantification revealed expression of 13 high-abundant secretary proteins across multiple studies, which can be potentially harnessed in the future to develop biomarkers. In summary, this study identifies novel PTMs which might help develop new insights on the molecular substrates of AD and thus inform future development of novel diagnostics and treatments for this highly prevalent disease.
Subject(s)
Alzheimer Disease/metabolism , Proteome , Proteomics , Alzheimer Disease/etiology , Biomarkers , Computational Biology/methods , Databases, Protein , Gene Ontology , Humans , Neurodegenerative Diseases/etiology , Neurodegenerative Diseases/metabolism , Peptides , Protein Processing, Post-Translational , Proteomics/methods , Signal Transduction , Tandem Mass SpectrometryABSTRACT
Candida tropicalis belongs to the non-albicans group of Candida, and causes epidermal, mucosal, or systemic candidiasis in immunocompromised individuals. Although the prevalence of candidiasis has increased worldwide and non-albicans Candida (NAC) are becoming more significant, there are very few studies that focus on the NAC biology. Proteins and their post-translational modifications (PTMs) are an integral aspect in the pathobiology of such medically important fungi. Previously, we had reported the largest proteomic catalog of C. tropicalis. Notably, PTMs can be identified from proteomics data without a priori enrichment for a particular PTM, thus allowing broad-scale omics analyses. In this study, we developed the "PTM-Pro," a graphical user interface-based tool for identification and summary of high-confidence PTM sites based on statistical threshold of users' choice. We mined available proteomic data of C. tropicalis, and using PTM-Pro identified nearly 600 high-confidence PTM sites. The PTMs identified include phosphorylation of serine, threonine, and tyrosine; acetylation, crotonylation, methylation, and succinylation of lysine. These PTMs reside on biologically significant molecules, including histones, enzymes, and transcription factors. To our knowledge, this is the first report of PTMs in C. tropicalis and lays a foundation for future investigations of C. tropicalis PTMs. In addition, the PTM-Pro offers a graphical user interface tool for research on PTM sites in the field of proteomics.
