Competitive fitness is a fundamental concept in evolutionary biology that captures the ability of organisms to survive, reproduce, and compete for resources in their environment. Competitive fitness is typically assessed in the lab by growing two or more competitors together and measuring the frequency of each at multiple time points. Traditional microbial competitive fitness assays are labor intensive and involve plating on solid medium and counting colonies. Here, we describe a method to quantitatively measure competitive fitness using fluorescence microscopic imaging and machine-learning-enabled image analysis to directly count the number of cells from each competitor in the mixed population. This high-throughput, primarily automated, and efficient process gives accurate and reproducible results for competitive fitness. Here, we describe the entire process, from sample preparation through microscopy to quantification, and provide instructions and scripts for the image analysis, fitness calculations, and sample data visualizations. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Sample preparation Basic Protocol 2: Photographing fluorescing and non-fluorescing cells using an EVOS microscope Basic Protocol 3: Counting fluorescing and non-fluorescing cells with Orbit Image Analysis Basic Protocol 4: Getting the average cell counts per well and changing the file names Basic Protocol 5: Calculating competitive fitness using R.

• PMID: 39869052
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Journal Article

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Sumanarathne AS, Gerstein AC

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