Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application.

Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application.
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使用自动化图像分析应用程序ColTapp进行高效的微生物菌落生长动力学定量。

DOI:
10.1038/s41598-020-72979-4
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发表时间:
2020-09-30
期刊:
影响因子:
4.6
通讯作者:
Vulin C
Vulin C
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Bär J;Boumasmoud M;Kouyos RD;Zinkernagel AS;Vulin C

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Populations of genetically identical bacteria are phenotypically heterogeneous, giving rise to population functionalities that would not be possible in homogeneous populations. For instance, a proportion of non-dividing bacteria could persist through antibiotic challenges and secure population survival. This heterogeneity can be studied in complex environmental or clinical samples by spreading the bacteria on agar plates and monitoring time to growth resumption in order to infer their metabolic state distribution. We present ColTapp, the Colony Time-lapse application for bacterial colony growth quantification. Its intuitive graphical user interface allows users to analyze time-lapse images of agar plates to monitor size, color and morphology of colonies. Additionally, images at isolated timepoints can be used to estimate lag time. Using ColTapp, we analyze a dataset of Staphylococcus aureus time-lapse images including populations with heterogeneous lag time. Colonies on dense plates reach saturation early, leading to overestimation of lag time from isolated images. We show that this bias can be corrected by taking into account the area available to each colony on the plate. We envision that in clinical settings, improved analysis of colony growth dynamics may help treatment decisions oriented towards personalized antibiotic therapies.
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