Bioinformatic Analysis of the Wound Peptidome Reveals Potential Biomarkers and Antimicrobial Peptides.

Autor:	Hartman E; Division of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden., Wallblom K; Division of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden., van der Plas MJA; Division of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.; LEO Foundation Center for Cutaneous Drug Delivery, Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark., Petrlova J; Division of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden., Cai J; LEO Foundation Center for Cutaneous Drug Delivery, Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark., Saleh K; Division of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.; Dermatology, Skane University Hospital, Lund, Sweden., Kjellström S; Division of Mass Spectrometry, Department of Clinical Sciences, Lund University, Lund, Sweden., Schmidtchen A; Division of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.; Dermatology, Skane University Hospital, Lund, Sweden.; Copenhagen Wound Healing Center, Bispebjerg Hospital, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.
Jazyk:	angličtina
Zdroj:	Frontiers in immunology [Front Immunol] 2021 Feb 03; Vol. 11, pp. 620707. Date of Electronic Publication: 2021 Feb 03 (Print Publication: 2020).
DOI:	10.3389/fimmu.2020.620707
Abstrakt:	Wound infection is a common and serious medical condition with an unmet need for improved diagnostic tools. A peptidomic approach, aided by mass spectrometry and bioinformatics, could provide novel means of identifying new peptide biomarkers for wound healing and infection assessment. Wound fluid is suitable for peptidomic analysis since it is both intimately tied to the wound environment and is readily available. In this study we investigate the peptidomes of wound fluids derived from surgical drainages following mastectomy and from wound dressings following facial skin grafting. By applying sorting algorithms and open source third party software to peptidomic label free tandem mass spectrometry data we provide an unbiased general methodology for analyzing and differentiating between peptidomes. We show that the wound fluid peptidomes of patients are highly individualized. However, differences emerge when grouping the patients depending on wound type. Furthermore, the abundance of peptides originating from documented antimicrobial regions of hemoglobin in infected wounds may contribute to an antimicrobial wound environment, as determined by in silico analysis. We validate our findings by compiling literature on peptide biomarkers and peptides of physiological significance and cross checking the results against our dataset, demonstrating that well-documented peptides of immunological significance are abundant in infected wounds, and originate from certain distinct regions in proteins such as hemoglobin and fibrinogen. Ultimately, we have demonstrated the power using sorting algorithms and open source software to help yield insights and visualize peptidomic data. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2021 Hartman, Wallblom, van der Plas, Petrlova, Cai, Saleh, Kjellström and Schmidtchen.)
Databáze:	MEDLINE
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