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Comparative proteomic assessment of matrisome enrichment methodologies.

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Publication Date
2016-09-02
ICR Author
Howard, Beatrice
Natrajan, Rachael
Huang, Paul
Author
Krasny, L
Paul, A
Wai, P
Howard, BA
Natrajan, RC
Huang, PH
Type
Journal Article
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Abstract
The matrisome is a complex and heterogeneous collection of extracellular matrix (ECM) and ECM-associated proteins that play important roles in tissue development and homeostasis. While several strategies for matrisome enrichment have been developed, it is currently unknown how the performance of these different methodologies compares in the proteomic identification of matrisome components across multiple tissue types. In this study, we perform a comparative proteomic assessment of two widely used decellularisation protocols and two extraction methods to characterise the matrisome in four murine organs (heart, mammary gland, lung and liver). We undertook a systematic evaluation of the performance of the individual methods on protein yield, matrisome enrichment capability and the ability to isolate core matrisome and matrisome-associated components. Our data finds that SDS decellularisation leads to the highest matrisome enrichment efficiency while the extraction protocol that comprises chemical and trypsin digestion of the ECM fraction consistently identifies the highest number of matrisomal proteins across all tissue examined. Matrisome enrichment had a clear benefit over non-enriched tissue for the comprehensive identification of matrisomal components in murine liver and heart. Strikingly, we find that all four matrisome enrichment methods led to significant losses in the soluble matrisome-associated proteins across all organs. Our findings highlight the multiple factors (including tissue type, matrisome class of interest and desired enrichment purity) that influence the choice of enrichment methodology and we anticipate that this data will serve as a useful guide for the design of future proteomic studies of the matrisome.
URL
https://repository.icr.ac.uk/handle/internal/100
Collections
  • Breast Cancer Research
  • Cancer Biology
  • Molecular Pathology
Research team
Molecular Cell Biology
Protein Networks
Functional Genomics
Language
eng
Date accepted
2016-09-02
License start date
2016-09-02
Citation
The Biochemical journal, 2016

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