Open AccessPeptide location fingerprinting reveals modification‐associated biomarker candidates of ageing in human tissue proteomes
Author(s) -
Ozols Matiss,
Eckersley Alexander,
Mellody Kieran T.,
Mallikarjun Venkatesh,
Warwood Stacey,
O'Cualain Ronan,
Knight David,
Watson Rachel E. B.,
Griffiths Christopher E. M.,
Swift Joe,
Sherratt Michael J.
Publication year - 2021
Publication title -
aging cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.103
H-Index - 140
eISSN - 1474-9726
pISSN - 1474-9718
DOI - 10.1111/acel.13355
Subject(s) - biology , proteostasis , proteome , proteomics , peptide mass fingerprinting , biomarker , biomarker discovery , peptide , computational biology , biochemistry , microbiology and biotechnology , gene
Although dysfunctional protein homeostasis (proteostasis) is a key factor in many age‐related diseases, the untargeted identification of structurally modified proteins remains challenging. Peptide location fingerprinting is a proteomic analysis technique capable of identifying structural modification‐associated differences in mass spectrometry (MS) data sets of complex biological samples. A new webtool (Manchester Peptide Location Fingerprinter), applied to photoaged and intrinsically aged skin proteomes, can relatively quantify peptides and map statistically significant differences to regions within protein structures. New photoageing biomarker candidates were identified in multiple pathways including extracellular matrix organisation (collagens and proteoglycans), protein synthesis and folding (ribosomal proteins and TRiC complex subunits), cornification (keratins) and hemidesmosome assembly (plectin and integrin α6β4). Crucially, peptide location fingerprinting uniquely identified 120 protein biomarker candidates in the dermis and 71 in the epidermis which were modified as a consequence of photoageing but did not differ significantly in relative abundance (measured by MS1 ion intensity). By applying peptide location fingerprinting to published MS data sets, (identifying biomarker candidates including collagen V and versican in ageing tendon) we demonstrate the potential of the MPLF webtool for biomarker discovery.