Bacterial colony size growth estimation by deep learning.

Autor: Nagy SÁ; Centre for Bioinformatics, University of Veterinary Medicine, 1078, Budapest, Hungary., Makrai L; Autovakcina Ltd, 1171, Budapest, Hungary., Csabai I; Department of Physics of Complex Systems, Eötvös Loránd University, 1117, Budapest, Hungary., Tőzsér D; Centre for Bioinformatics, University of Veterinary Medicine, 1078, Budapest, Hungary., Szita G; Centre for Bioinformatics, University of Veterinary Medicine, 1078, Budapest, Hungary., Solymosi N; Centre for Bioinformatics, University of Veterinary Medicine, 1078, Budapest, Hungary. solymosi.norbert@gmail.com.; Department of Physics of Complex Systems, Eötvös Loránd University, 1117, Budapest, Hungary. solymosi.norbert@gmail.com.
Jazyk: angličtina
Zdroj: BMC microbiology [BMC Microbiol] 2023 Oct 26; Vol. 23 (1), pp. 307. Date of Electronic Publication: 2023 Oct 26.
DOI: 10.1186/s12866-023-03053-y
Abstrakt: The bacterial growth rate is important for pathogenicity and food safety. Therefore, the study of bacterial growth rate over time can provide important data from a medical and veterinary point of view. We trained convolutional neural networks (CNNs) on manually annotated solid medium cultures to detect bacterial colonies as accurately as possible. Predictions of bacterial colony size and growth rate were estimated from image sequences of independent Staphylococcus aureus cultures using trained CNNs. A simple linear model for control cultures with less than 150 colonies estimated that the mean growth rate was 60.3 [Formula: see text] for the first 24 h. Analyzing with a mixed effect model that also takes into account the effect of culture, smaller values of change in colony size were obtained (control: 51.0 [Formula: see text], rifampicin pretreated: 36.5[Formula: see text]). An increase in the number of neighboring colonies clearly reduces the colony growth rate in the control group but less typically in the rifampicin-pretreated group. Based on our results, CNN-based bacterial colony detection and the subsequent analysis of bacterial colony growth dynamics might become an accurate and efficient tool for bacteriological work and research.
(© 2023. BioMed Central Ltd., part of Springer Nature.)
Databáze: MEDLINE
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