Proteomics and Visual Health Research: Proteome of the Human Sclera Using High-Resolution Mass Spectrometry

Autor: Krishna R Murthy, Yashwanth Subbannayya, Kunal Kumar Singh, Sunita Dalal, Cynthia Arunachalam, Sneha M. Pinto, Varshasnata Mohanty, Mohammed Altaf Najar, Shyamjith Manikkoth, Hilda Karuppiah, Thottethodi Subrahmanya Keshava Prasad, Bhuvaragavan Sreeramulu, Sandeep Kasaragod
Rok vydání: 2019
Předmět:
Zdroj: OMICS: A Journal of Integrative Biology. 23:98-110
ISSN: 1557-8100
DOI: 10.1089/omi.2018.0185
Popis: Eye disorders and resulting visual loss are major public health problems affecting millions of people worldwide. In this context, the sclera is an opaque, thick outer coat covering more than 80% of the eye, and essential in maintaining the shape of the eye and protecting the intraocular contents against infection and the external environment. Despite efforts undertaken to decipher the scleral proteome, the functional and structural picture of the sclera still remain elusive. Recently, proteomics has arisen as a powerful tool that enables identification of proteins playing a critical role in health and disease. Therefore, we carried out an in-depth proteomic analysis of the human scleral tissue using a high-resolution Orbitrap Fusion Tribrid mass spectrometer. We identified 4493 proteins using SequestHT and Mascot as search algorithms in Proteome Discoverer 2.1. Importantly, the proteins, including radixin, synaptopodin, paladin, netrin 1, and kelch-like family member 41, were identified for the first time in human sclera. Gene ontology analysis unveiled that the majority of proteins were localized to the cytoplasm and involved in cell communication and metabolism. In sum, this study offers the largest catalog of proteins identified in sclera with the aim of facilitating their contribution to diagnostics and therapeutics innovation in visual health and autoimmune disorders. This study also provides a valuable baseline for future investigations so as to map the dynamic changes that occur in sclera in various pathological conditions.
Databáze: OpenAIRE