Ex vivo immune profiling in patient blood enables quantification of innate immune effector functions

Please always quote using this URN: urn:nbn:de:bvb:20-opus-363337
  • The assessment of a patient’s immune function is critical in many clinical situations. In complex clinical immune dysfunction like sepsis, which results from a loss of immune homeostasis due to microbial infection, a plethora of pro- and anti-inflammatory stimuli may occur consecutively or simultaneously. Thus, any immunomodulatory therapy would require in-depth knowledge of an individual patient’s immune status at a given time. Whereas lab-based immune profiling often relies solely on quantification of cell numbers, we used an ex vivoThe assessment of a patient’s immune function is critical in many clinical situations. In complex clinical immune dysfunction like sepsis, which results from a loss of immune homeostasis due to microbial infection, a plethora of pro- and anti-inflammatory stimuli may occur consecutively or simultaneously. Thus, any immunomodulatory therapy would require in-depth knowledge of an individual patient’s immune status at a given time. Whereas lab-based immune profiling often relies solely on quantification of cell numbers, we used an ex vivo whole-blood infection model in combination with biomathematical modeling to quantify functional parameters of innate immune cells in blood from patients undergoing cardiac surgery. These patients experience a well-characterized inflammatory insult, which results in mitigation of the pathogen-specific response patterns towards Staphylococcus aureus and Candida albicans that are characteristic of healthy people and our patients at baseline. This not only interferes with the elimination of these pathogens from blood, but also selectively augments the escape of C. albicans from phagocytosis. In summary, our model could serve as a valuable functional immune assay for recording and evaluating innate responses to infection.show moreshow less

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Metadaten
Author: Teresa Lehnert, Ines Leonhardt, Sandra Timme, Daniel Thomas-Rüddel, Frank Bloos, Christoph Sponholz, Oliver Kurzai, Marc Thilo Figge, Kerstin Hünniger
URN:urn:nbn:de:bvb:20-opus-363337
Document Type:Journal article
Faculties:Medizinische Fakultät / Institut für Hygiene und Mikrobiologie
Language:English
Parent Title (English):Scientific Reports
Year of Completion:2021
Volume:11
Article Number:12039
Source:Scientific Reports (2021) 11:12039. https://doi.org/10.1038/s41598-021-91362-5
DOI:https://doi.org/10.1038/s41598-021-91362-5
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:computational biology and bioinformatics; computational models; immunology; infection; inflammation; innate immunity
Release Date:2024/09/05
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International