Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers

Research output: Contribution to journalJournal articlepeer-review

Standard

Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers. / Fritz, Blaine; Bier-Kirkegaard, Julius; Nielsen, Claus Henrik; Kirketerp-Møller, Klaus; Malone, Matthew; Bjarnsholt, Thomas.

In: A P M I S. Acta Pathologica, Microbiologica et Immunologica Scandinavica, Vol. 130, No. 8, 2022, p. 524-534.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Fritz, B, Bier-Kirkegaard, J, Nielsen, CH, Kirketerp-Møller, K, Malone, M & Bjarnsholt, T 2022, 'Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers', A P M I S. Acta Pathologica, Microbiologica et Immunologica Scandinavica, vol. 130, no. 8, pp. 524-534. https://doi.org/10.1111/apm.13234

APA

Fritz, B., Bier-Kirkegaard, J., Nielsen, C. H., Kirketerp-Møller, K., Malone, M., & Bjarnsholt, T. (2022). Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers. A P M I S. Acta Pathologica, Microbiologica et Immunologica Scandinavica, 130(8), 524-534. https://doi.org/10.1111/apm.13234

Vancouver

Fritz B, Bier-Kirkegaard J, Nielsen CH, Kirketerp-Møller K, Malone M, Bjarnsholt T. Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers. A P M I S. Acta Pathologica, Microbiologica et Immunologica Scandinavica. 2022;130(8):524-534. https://doi.org/10.1111/apm.13234

Author

Fritz, Blaine ; Bier-Kirkegaard, Julius ; Nielsen, Claus Henrik ; Kirketerp-Møller, Klaus ; Malone, Matthew ; Bjarnsholt, Thomas. / Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers. In: A P M I S. Acta Pathologica, Microbiologica et Immunologica Scandinavica. 2022 ; Vol. 130, No. 8. pp. 524-534.

Bibtex

@article{c28dc64494e9432cadbb80b0d3121ddb,
title = "Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers",
abstract = "Clinicians and researchers utilize subjective classification systems based on clinical parameters to stratify lower extremity ulcer infections for treatment and research. This study compared clinical infection classifications (mild to severe) of lower extremity ulcers (n = 44) with transcriptomic profiles and direct measurement of bacterial RNA signatures by RNA-sequencing. Samples demonstrating similar transcriptomes were clustered and characterized by transcriptomic fingerprint. Clinical infection severity did not explain the major sources of variability among the samples and samples with the same clinical classification demonstrated high inter-sample variability. High proportions of bacterial RNA, however, resulted in a strong effect on transcription and increased expression of genes associated with immune response and inflammation. K-means clustering identified two clusters of samples, one of which contained all of the samples with high levels of bacterial RNA. A support vector classifier identified a fingerprint of 20 genes, including immune-associated genes such as CXCL8, GADD45B, and HILPDA, which accurately identified samples with signs of infection via cross-validation. This suggests that stratification of infection states based on a transcriptomic fingerprint may be a useful tool for studying host-bacterial interactions in these ulcers, as well as an objective classification method to identify the severity of infection.",
author = "Blaine Fritz and Julius Bier-Kirkegaard and Nielsen, {Claus Henrik} and Klaus Kirketerp-M{\o}ller and Matthew Malone and Thomas Bjarnsholt",
year = "2022",
doi = "10.1111/apm.13234",
language = "English",
volume = "130",
pages = "524--534",
journal = "A P M I S. Acta Pathologica, Microbiologica et Immunologica Scandinavica",
issn = "0903-4641",
publisher = "Wiley Online",
number = "8",

}

RIS

TY - JOUR

T1 - Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers

AU - Fritz, Blaine

AU - Bier-Kirkegaard, Julius

AU - Nielsen, Claus Henrik

AU - Kirketerp-Møller, Klaus

AU - Malone, Matthew

AU - Bjarnsholt, Thomas

PY - 2022

Y1 - 2022

N2 - Clinicians and researchers utilize subjective classification systems based on clinical parameters to stratify lower extremity ulcer infections for treatment and research. This study compared clinical infection classifications (mild to severe) of lower extremity ulcers (n = 44) with transcriptomic profiles and direct measurement of bacterial RNA signatures by RNA-sequencing. Samples demonstrating similar transcriptomes were clustered and characterized by transcriptomic fingerprint. Clinical infection severity did not explain the major sources of variability among the samples and samples with the same clinical classification demonstrated high inter-sample variability. High proportions of bacterial RNA, however, resulted in a strong effect on transcription and increased expression of genes associated with immune response and inflammation. K-means clustering identified two clusters of samples, one of which contained all of the samples with high levels of bacterial RNA. A support vector classifier identified a fingerprint of 20 genes, including immune-associated genes such as CXCL8, GADD45B, and HILPDA, which accurately identified samples with signs of infection via cross-validation. This suggests that stratification of infection states based on a transcriptomic fingerprint may be a useful tool for studying host-bacterial interactions in these ulcers, as well as an objective classification method to identify the severity of infection.

AB - Clinicians and researchers utilize subjective classification systems based on clinical parameters to stratify lower extremity ulcer infections for treatment and research. This study compared clinical infection classifications (mild to severe) of lower extremity ulcers (n = 44) with transcriptomic profiles and direct measurement of bacterial RNA signatures by RNA-sequencing. Samples demonstrating similar transcriptomes were clustered and characterized by transcriptomic fingerprint. Clinical infection severity did not explain the major sources of variability among the samples and samples with the same clinical classification demonstrated high inter-sample variability. High proportions of bacterial RNA, however, resulted in a strong effect on transcription and increased expression of genes associated with immune response and inflammation. K-means clustering identified two clusters of samples, one of which contained all of the samples with high levels of bacterial RNA. A support vector classifier identified a fingerprint of 20 genes, including immune-associated genes such as CXCL8, GADD45B, and HILPDA, which accurately identified samples with signs of infection via cross-validation. This suggests that stratification of infection states based on a transcriptomic fingerprint may be a useful tool for studying host-bacterial interactions in these ulcers, as well as an objective classification method to identify the severity of infection.

U2 - 10.1111/apm.13234

DO - 10.1111/apm.13234

M3 - Journal article

C2 - 35567538

VL - 130

SP - 524

EP - 534

JO - A P M I S. Acta Pathologica, Microbiologica et Immunologica Scandinavica

JF - A P M I S. Acta Pathologica, Microbiologica et Immunologica Scandinavica

SN - 0903-4641

IS - 8

ER -

ID: 310155616