High‐Throughput Computational Analysis of Biofilm Formation from Time‐Lapse Microscopy. Issue 7 (9th July 2021) - Salama, Ola E.; Gerstein, Aleeza C.
Abstract: Candida albicans biofilm formation in the presence of drugs can be examined through time‐lapse microscopy. In many cases, the images are used qualitatively, which limits their utility for hypothesis testing. We employed a machine‐learning algorithm implemented in the Orbit Image Analysis program to detect the percent area covered by cells from each image. This is combined with custom R scripts to determine the growth rate, growth asymptote, and time to reach the asymptote as quantitative proxies for biofilm formation. We describe step‐by‐step protocols that go from sample preparation for time‐lapse microscopy through image analysis parameterization and visualization of the model fit. © 2021 Wiley Periodicals LLC. Basic Protocol 1 : Sample preparation Basic Protocol 2 : Time‐lapse microscopy: Evos protocol Basic Protocol 3 : Batch file renaming Basic Protocol 4 : Machine learning analysis of Evos images with Orbit Basic Protocol 5 : Parametrization of Orbit output in R Basic Protocol 6 : Visualization of logistic fits in R