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Pistiki, Aikaterini ; Ramoji, Anuradha ; Ryabchykov, Oleg ; Thomas-Rüddel, Daniel ; Press, Adrian T. ; Makarewicz, Oliwia ; Giamarellos-Bourboulis, Evangelos J. ; Bauer, Michael ; Bocklitz, Thomas ; Popp, Jürgen ; Neugebauer, Ute:
Biochemical Analysis of Leukocytes after In Vitro and In Vivo Activation with Bacterial and Fungal Pathogens Using Raman Spectroscopy.
In: International Journal of Molecular Sciences.
Bd. 22
(2021)
Heft 19
.
- 10481.
ISSN 1422-0067
DOI: https://doi.org/10.3390/ijms221910481
Abstract
Biochemical information from activated leukocytes provide valuable diagnostic information. In this study, Raman spectroscopy was applied as a label-free analytical technique to characterize the activation pattern of leukocyte subpopulations in an in vitro infection model. Neutrophils, monocytes, and lymphocytes were isolated from healthy volunteers and stimulated with heat-inactivated clinical isolates of Candida albicans, Staphylococcus aureus, and Klebsiella pneumoniae. Binary classification models could identify the presence of infection for monocytes and lymphocytes, classify the type of infection as bacterial or fungal for neutrophils, monocytes, and lymphocytes and distinguish the cause of infection as Gram-negative or Gram-positive bacteria in the monocyte subpopulation. Changes in single-cell Raman spectra, upon leukocyte stimulation, can be explained with biochemical changes due to the leukocyte’s specific reaction to each type of pathogen. Raman spectra of leukocytes from the in vitro infection model were compared with spectra from leukocytes of patients with infection (DRKS-ID: DRKS00006265) with the same pathogen groups, and a good agreement was revealed. Our study elucidates the potential of Raman spectroscopy-based single-cell analysis for the differentiation of circulating leukocyte subtypes and identification of the infection by probing the molecular phenotype of those cells.
Weitere Angaben
| Publikationsform: | Artikel in einer Zeitschrift |
|---|---|
| Begutachteter Beitrag: | Ja |
| Keywords: | Raman microspectroscopy; leukocytes; infection model; Staphylococcus aureus; Klebsiella pneumoniae; Candida albicans; neutrophil; PBMC; monocyte; lymphocyte |
| Institutionen der Universität: | Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz |
| Titel an der UBT entstanden: | Nein |
| Themengebiete aus DDC: | 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik 500 Naturwissenschaften und Mathematik > 530 Physik |
| Eingestellt am: | 11 Mai 2023 08:59 |
| Letzte Änderung: | 11 Mai 2023 08:59 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/76408 |