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.

遗传相同细菌的种群在表型上是异质的，从而产生在同质种群中不可能实现的种群功能。例如，一部分非分裂细菌可以通过抗生素挑战持续存在并确保种群生存。这种异质性可以通过将细菌散布在琼脂平板上并监测恢复生长的时间以推断其代谢状态分布，在复杂的环境或临床样本中进行研究。我们展示了 ColTapp，这是用于细菌菌落生长量化的菌落延时应用。其直观的图形用户界面允许用户分析琼脂平板的延时图像，以监测菌落的大小、颜色和形态。此外，隔离时间点的图像可用于估计滞后时间。使用 ColTapp，金黄色葡萄球菌延时图像，包括具有异质滞后时间的种群。密集板上的菌落很早就达到饱和，导致高估孤立图像的滞后时间。我们表明可以通过考虑板上每个菌落可用的区域来纠正这种偏差。我们设想在临床环境中，对菌落生长动态的改进分析可能有助于针对个性化抗生素治疗的治疗决策。