Several species of bacteria are able to modify their swimming behavior in response to chemical attractants or repellents. Methods for the quantitative analysis of bacterial chemotaxis such as quantitative capillary assays are tedious and time-consuming. Computer-based video analysis of swimming bacteria represents a valuable method to directly assess their chemotactic response. Even though multiple studies have used this approach to elucidate various aspects of bacterial chemotaxis, to date, no computer software for such analyses is freely available. Here, we introduce TaxisPy, a Python-based software for the quantitative analysis of bacterial chemotaxis. The software comes with an intuitive graphical user interface and can be accessed easily through Docker on any operating system. Using a video of freely swimming cells as input, TaxisPy estimates the culture's average tumbling frequency over time. We demonstrate the utility of the software by assessing the effect of different concentrations of the attractant shikimate on the swimming behavior of Pseudomonas putida F1 and by capturing the adaptation process that Escherichia coli undergoes after being exposed to l-aspartate.

几种细菌能够响应化学引诱剂或驱避剂而改变其游泳行为。细菌趋化性的定量分析方法，例如定量毛细管测定法，既繁琐又费时。基于计算机的游泳细菌视频分析代表了一种直接评估其趋化反应的有价值的方法。尽管已有多项研究使用这种方法阐明了细菌趋化性的各个方面，但迄今为止，尚无可免费获得的用于此类分析的计算机软件。在这里，我们介绍TaxisPy，这是一种基于Python的软件，用于细菌趋化性的定量分析。该软件带有直观的图形用户界面，可以在任何操作系统上通过Docker轻松访问。使用自由游泳的视频作为输入，TaxisPy估计该文化随时间推移的平均翻滚频率。我们通过评估不同浓度的兴奋剂sh草酸酯对游泳行为的影响来证明该软件的实用性。恶臭假单胞菌F1并通过捕获大肠杆菌暴露于1-天冬氨酸后经历的适应过程。