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Wurm LM, Fischer B, Neuschmelting V, Reinecke D, Fischer I, Croner RS, Goldbrunner R, Hacker MC, Dybaś J, Kahlert UD. Rapid, label-free classification of glioblastoma differentiation status combining confocal Raman spectroscopy and machine learning. Analyst 2023; 148:6109-6119. [PMID: 37927114 DOI: 10.1039/d3an01303k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
Label-free identification of tumor cells using spectroscopic assays has emerged as a technological innovation with a proven ability for rapid implementation in clinical care. Machine learning facilitates the optimization of processing and interpretation of extensive data, such as various spectroscopy data obtained from surgical samples. The here-described preclinical work investigates the potential of machine learning algorithms combining confocal Raman spectroscopy to distinguish non-differentiated glioblastoma cells and their respective isogenic differentiated phenotype by means of confocal ultra-rapid measurements. For this purpose, we measured and correlated modalities of 1146 intracellular single-point measurements and sustainingly clustered cell components to predict tumor stem cell existence. By further narrowing a few selected peaks, we found indicative evidence that using our computational imaging technology is a powerful approach to detect tumor stem cells in vitro with an accuracy of 91.7% in distinct cell compartments, mainly because of greater lipid content and putative different protein structures. We also demonstrate that the presented technology can overcome intra- and intertumoral cellular heterogeneity of our disease models, verifying the elevated physiological relevance of our applied disease modeling technology despite intracellular noise limitations for future translational evaluation.
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Affiliation(s)
- Lennard M Wurm
- Department of Neurosurgery, University Hospital Düsseldorf and Medical Faculty Heinrich-Heine University, Düsseldorf, Germany
- Department of Neurosurgery, University Hospital Cologne, Cologne, Germany
| | - Björn Fischer
- Institute of Pharmaceutics and Biopharmaceutics, University of Düsseldorf, Düsseldorf, Germany
- FISCHER GmbH, Raman Spectroscopic Services, 40667 Meerbusch, Germany
| | | | - David Reinecke
- Department of Neurosurgery, University Hospital Cologne, Cologne, Germany
| | - Igor Fischer
- Department of Neurosurgery, University Hospital Düsseldorf and Medical Faculty Heinrich-Heine University, Düsseldorf, Germany
| | - Roland S Croner
- Clinic of General- Visceral-, Vascular and Transplantation Surgery, Department of Molecular and Experimental Surgery, University Hospital Magdeburg and Medical Faculty Otto-von-Guericke University, Magdeburg, Germany.
| | - Roland Goldbrunner
- Department of Neurosurgery, University Hospital Cologne, Cologne, Germany
| | - Michael C Hacker
- Institute of Pharmaceutics and Biopharmaceutics, University of Düsseldorf, Düsseldorf, Germany
| | - Jakub Dybaś
- Jagiellonian Center for Experimental Therapeutics, Jagiellonian University, Krakow, Poland
| | - Ulf D Kahlert
- Clinic of General- Visceral-, Vascular and Transplantation Surgery, Department of Molecular and Experimental Surgery, University Hospital Magdeburg and Medical Faculty Otto-von-Guericke University, Magdeburg, Germany.
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Kochan K, Nethercott C, Taghavimoghaddam J, Richardson Z, Lai E, Crawford SA, Peleg AY, Wood BR, Heraud P. Rapid Approach for Detection of Antibiotic Resistance in Bacteria Using Vibrational Spectroscopy. Anal Chem 2020; 92:8235-8243. [PMID: 32407103 DOI: 10.1021/acs.analchem.0c00474] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Here, we applied vibrational spectroscopy to investigate the drug response following incubation of S. aureus with oxacillin. The main focus of this work was to identify the chemical changes caused by oxacillin over time and to determine the feasibility of the spectroscopic approach to detect antimicrobial resistance. The oxacillin-induced changes in the chemical composition of susceptible bacteria, preceding (and leading to) the inhibition of growth, included an increase in the relative content of nucleic acids, alteration in the α-helical/β-sheet protein ratio, structural changes in carbohydrates (observed via changes in the band at 1035 cm-1), and significant thickening of the cell wall. These observations enabled a dose-dependent discrimination between susceptible bacteria incubated with and without oxacillin after 120 min. In methicillin resistant strains, no spectral differences were observed between cells, regardless of drug exposure. These results pave the way for a new, rapid spectroscopic approach to detect drug resistance in pathogens, based on their early positive/negative drug response.
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Affiliation(s)
- Kamila Kochan
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Cara Nethercott
- Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | | | - Zack Richardson
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Elizabeth Lai
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Simon A Crawford
- The Ramaciotti Centre for Cryo Electron Microscopy, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Anton Y Peleg
- Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia.,Department of Infectious Diseases, The Alfred Hospital and Central Clinical School, Monash University, Melbourne 3004, Victoria, Australia
| | - Bayden R Wood
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia.,School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
| | - Philip Heraud
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia.,Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton Campus, Clayton 3800, Victoria, Australia
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Pogocki D, Kisała J, Cebulski J. Depression as is Seen by Molecular Spectroscopy. Phospholipid- Protein Balance in Affective Disorders and Dementia. Curr Mol Med 2019; 20:484-487. [PMID: 31854279 DOI: 10.2174/1566524020666191219102746] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 11/26/2019] [Accepted: 12/06/2019] [Indexed: 01/30/2023]
Abstract
There is an expanding field of research investigating the instrumental methods to measure the development of affective disorders. The goal of the commentary is to turn the attention of medical practitioners at the molecular spectroscopy techniques (FTIR, Raman and UV-Vis) that can be applied for monitoring and quantification of the phospholipid-protein balance in human blood serum of depressed patients. Even facial overview of cited original research strongly suggests that disturbed phospholipid-protein balance could be one of the biomarkers of affective disorders. The blood serum monitoring of depressed patients would serve as a tool for more effective holistic therapy.
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Affiliation(s)
- Dariusz Pogocki
- College of Natural Sciences, University of Rzeszow, Rzeszow, Poland.,Institute of Nuclear Chemistry and Technology, Warsaw, Poland
| | - Joanna Kisała
- College of Natural Sciences, University of Rzeszow, Rzeszow, Poland
| | - Józef Cebulski
- College of Natural Sciences, University of Rzeszow, Rzeszow, Poland
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