Spectroscopic characterization of bacterial colonies through UV hyperspectral imaging techniques
J. Ezenarro, Josune (Universitat Autònoma de Barcelona. Departament de Genètica i de Microbiologia)
Al Ktash, Mohammad (Reutlingen University)
Vigués, Núria (Universitat Autònoma de Barcelona. Departament de Genètica i de Microbiologia)
Mas Gordi, Jordi (Universitat Autònoma de Barcelona. Departament de Genètica i de Microbiologia)
Muñoz-Berbel, Xavi (Institut de Microelectrònica de Barcelona)
Brecht, Marc (Reutlingen University)

Fecha:	2025
Resumen:	Introduction: Plate culturing and visual inspection are the gold standard methods for bacterial identification. Despite the growing attention on molecular biology techniques, colony identification using agar plates remains manual, interpretative, and heavily reliant on human experience, making it prone to errors. Advanced imaging techniques, like hyperspectral imaging, offer potential alternatives. However, the use of hyperspectral imaging in the VIS-NIR region has been hindered by sensitivity to various components and culture medium changes, leading to inaccurate results. The application of hyperspectral imaging in the ultraviolet (UV) region has not been explored, despite the presence of specific absorption and emission peaks in bacterial components. Methods: To address this gap, we developed a predictive model for bacterial colony detection and identification using UV hyperspectral imaging. The model utilizes hyperspectral images acquired in the UV wavelength range of 225-400 nm, processed with principal component analysis (PCA) and discriminant analysis (DA). The measurement setup includes a hyperspectral imager, a PC for automated data analysis, and a conveyor belt system to transport agar plates for automated analysis. Four bacterial species (Escherichia coli, Staphylococcus, Pseudomonas, and Shewanella) were cultured on two different media, Luria Bertani and Tryptic Soy, to train and validate the model. Results: The PCA-DA-based model demonstrated high accuracy (90%) in differentiating bacterial species based on the first three principal components, highlighting the potential of UV hyperspectral imaging for bacterial identification. Discussion: This study shows that UV hyperspectral imaging, coupled with advanced data analysis techniques, offers a robust and automated alternative to traditional methods for bacterial identification. The model's high accuracy emphasizes the untapped potential of UV hyperspectral imaging in microbiological analysis, reducing human error and improving reliability in bacterial species differentiation.
Ayudas:	Agencia Estatal de Investigación RTC2019-007060-2 Agencia Estatal de Investigación RTC2016-5766-2 Agencia Estatal de Investigación PID2021-125469NB-C32
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Hyperspectral imaging ; UV spectroscopy ; Principal component analysis ; Discriminant analysis ; Colony identification
Publicado en:	Frontiers in chemistry, Vol. 13 (February 2025) , art. 1530955, ISSN 2296-2646

DOI: 10.3389/fchem.2025.1530955
PMID: 40041392

10 p, 1.6 MB

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