Association between Growth Rate and Pathogenicity of Spotted Fever Group Rickettsia

Bourchookarn, Apichai; Paddock, Christopher D.; Macaluso, Kevin R.; Bourchookarn, Walairat

doi:10.22207/jpam.16.1.31

Cited by 2 publications

(2 citation statements)

References 55 publications

(56 reference statements)

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“…Bacteria reproduce by simple division, the rate of which is fundamentally influenced by the environment and the characteristics of the bacterium. The rate of bacterial multiplication is important for pathogenicity [1][2][3] and food safety 4 . Therefore, the study of bacterial growth (multiplication rate) per unit of time can provide important data from a medical and veterinary point of view.…”

Section: Introductionmentioning

confidence: 99%

Bacterial colony size growth estimation by deep learning

Nagy

Makrai

Csabai

et al. 2023

Preprint

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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 μm/h 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 μm/h, rifampicin pretreated: 36.5 μm/h). 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.

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Section: Introductionmentioning

confidence: 99%

Bacterial colony size growth estimation by deep learning

Nagy

Makrai

Csabai

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Bacteria reproduce by simple division, the rate of which is fundamentally influenced by the environment and the characteristics of the bacterium. The rate of bacterial multiplication is important for pathogenicity [ 1 , 2 ] and food safety [ 3 ]. Therefore, the study of bacterial growth (multiplication rate) per unit of time can provide important data from a medical and veterinary point of view.…”

Section: Introductionmentioning

confidence: 99%

Bacterial colony size growth estimation by deep learning

Nagy,

Makrai,

Csabai

et al. 2023

BMC Microbiol

View full text Add to dashboard Cite

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 $$\mu m/h$$ μ m / h 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 $$\mu m/h$$ μ m / h , rifampicin pretreated: 36.5$$\mu m/h$$ μ m / h ). 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.

show abstract

Association between Growth Rate and Pathogenicity of Spotted Fever Group Rickettsia

Cited by 2 publications

References 55 publications

Bacterial colony size growth estimation by deep learning

Bacterial colony size growth estimation by deep learning

Bacterial colony size growth estimation by deep learning

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