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Using the Traditional Ex Vivo Whole Blood Model to Discriminate Bacteria by Their Inducible Host Responses

Heather Chick, Megan Rees, Matthew Lewis, Lisa Williams, Owen Bodger Orcid Logo, Llinos Harris Orcid Logo, Steven Rushton, Thomas Wilkinson Orcid Logo

Biomedicines, Volume: 12, Issue: 4, Start page: 724

Swansea University Authors: Heather Chick, Megan Rees, Matthew Lewis, Lisa Williams, Owen Bodger Orcid Logo, Llinos Harris Orcid Logo, Thomas Wilkinson Orcid Logo

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Abstract

Whole blood models are rapid and versatile for determining immune responses to inflammatory and infectious stimuli, but they have not been used for bacterial discrimination. Staphylococcus aureus, S. epidermidis and Escherichia coli are the most common causes of invasive disease, and rapid testing s...

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Published in: Biomedicines
ISSN: 2227-9059
Published: MDPI AG 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa65918
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Abstract: Whole blood models are rapid and versatile for determining immune responses to inflammatory and infectious stimuli, but they have not been used for bacterial discrimination. Staphylococcus aureus, S. epidermidis and Escherichia coli are the most common causes of invasive disease, and rapid testing strategies utilising host responses remain elusive. Currently, immune responses can only discriminate between bacterial ‘domains’ (fungi, bacteria and viruses), and very few studies can use immune responses to discriminate bacteria at the species and strain level. Here, whole blood was used to investigate the relationship between host responses and bacterial strains. Results confirmed unique temporal profiles for the 10 parameters studied: IL-6, MIP-1α, MIP-3α, IL-10, resistin, phagocytosis, S100A8, S100A8/A9, C5a and TF3. Pairwise analysis confirmed that IL-6, resistin, phagocytosis, C5a and S100A8/A9 could be used in a discrimination scheme to identify to the strain level. Linear discriminant analysis (LDA) confirmed that (i) IL-6, MIP-3α and TF3 could predict genera with 95% accuracy; (ii) IL-6, phagocytosis, resistin and TF3 could predict species at 90% accuracy and (iii) phagocytosis, S100A8 and IL-10 predicted strain at 40% accuracy. These data are important because they confirm the proof of concept that host biomarker panels could be used to identify bacterial pathogens.
Keywords: ex vivo whole blood models; host immune responses; bacterial discrimination; pair-wise comparison; multivariate analysis; Staphylococcus epidermidis; Staphylococcus aureus; Escherichia coli
College: Faculty of Medicine, Health and Life Sciences
Funders: This work was funded by a Health Care Research Wales (HCRW-HS-18-32) PhD studentship for M.L.L. awarded to T.S.W., funded by a Swansea University scholarship for H.M.C. awarded to T.S.W., partially funded by a BBSRC grant (BB0191421/1) awarded to T.S.W.
Issue: 4
Start Page: 724