Bioinformatic Analysis of the Wound Peptidome Reveals Potential Biomarkers and Antimicrobial Peptides
(2021) In Frontiers in Immunology 11.- Abstract
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... (More)
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.
(Less)
- author
- Hartman, Erik
LU
; Wallblom, Karl
LU
; van der Plas, Mariena J.A. LU ; Petrlova, Jitka LU ; Cai, Jun ; Saleh, Karim LU ; Kjellström, Sven LU and Schmidtchen, Artur LU
- organization
- publishing date
- 2021-02-03
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- antimicrobial peptide, bioinformatics, biomarkers, hemoglobin, mass spectrometry, peptidomics, wound healing, wound infection
- in
- Frontiers in Immunology
- volume
- 11
- article number
- 620707
- publisher
- Frontiers Media S. A.
- external identifiers
-
- pmid:33613550
- scopus:85101179463
- ISSN
- 1664-3224
- DOI
- 10.3389/fimmu.2020.620707
- project
- Translational wound healing studies with focus on microbes, inflammation, and methods for non-invasive wound evaluation
- language
- English
- LU publication?
- yes
- id
- ea5ea26c-8883-4262-a2cb-7c29c0f4348f
- date added to LUP
- 2022-03-21 16:55:28
- date last changed
- 2025-01-16 07:22:54
@article{ea5ea26c-8883-4262-a2cb-7c29c0f4348f, abstract = {{<p>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.</p>}}, author = {{Hartman, Erik and Wallblom, Karl and van der Plas, Mariena J.A. and Petrlova, Jitka and Cai, Jun and Saleh, Karim and Kjellström, Sven and Schmidtchen, Artur}}, issn = {{1664-3224}}, keywords = {{antimicrobial peptide; bioinformatics; biomarkers; hemoglobin; mass spectrometry; peptidomics; wound healing; wound infection}}, language = {{eng}}, month = {{02}}, publisher = {{Frontiers Media S. A.}}, series = {{Frontiers in Immunology}}, title = {{Bioinformatic Analysis of the Wound Peptidome Reveals Potential Biomarkers and Antimicrobial Peptides}}, url = {{http://dx.doi.org/10.3389/fimmu.2020.620707}}, doi = {{10.3389/fimmu.2020.620707}}, volume = {{11}}, year = {{2021}}, }