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Monitoring matrix metalloproteinase activity at the epidermal–dermal interface by SILAC‐iTRAQ‐TAILS
Author(s) -
Schlage Pascal,
Kockmann Tobias,
Kizhakkedathu Jayachandran N.,
auf dem Keller Ulrich
Publication year - 2015
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201400627
Subject(s) - stable isotope labeling by amino acids in cell culture , proteases , protease , proteome , extracellular matrix , quantitative proteomics , microbiology and biotechnology , chemistry , proteomics , biochemistry , metalloproteinase , biology , matrix metalloproteinase , enzyme , gene
Secreted proteases act on interstitial tissue secretomes released from multiple cell types. Thus, substrate proteins might be part of higher molecular complexes constituted by many proteins with diverse and potentially unknown cellular origin. In cell culture, these may be reconstituted by mixing native secretomes from different cell types prior to incubation with a test protease. Although current degradomics techniques could identify novel substrate proteins in these complexes, all information on the cellular origin is lost. To address this limitation, we combined iTRAQ-based terminal amine isotopic labeling of substrates (iTRAQ-TAILS) with SILAC to assign proteins to a specific cell type by MS1- and their cleavage by MS2-based quantification in the same experiment. We demonstrate the power of our newly established workflow by monitoring matrix metalloproteinase (MMP) 10 dependent cleavages in mixtures from light-labeled keratinocyte and heavy-labeled fibroblast secretomes. This analysis correctly assigned extracellular matrix components, such as laminins and collagens, to their respective cellular origins and revealed their processing in an MMP10-dependent manner. Hence, our newly devised degradomics workflow facilitates deeper insight into protease activity in complex intercellular compartments such as the epidermal-dermal interface by integrating multiple modes of quantification with positional proteomics. All MS data have been deposited in the ProteomeXchange with identifier PXD001643 (http://proteomecentral.proteomexchange.org/dataset/PXD001643).