Quantifying Variation in Bacterial Reproductive Fitness: a High-Throughput Method

• Published in: mSystems 2021-02, Vol.6 (1)
• Main Authors: Frey, Pascal M, Baer, Julian, Bergada-Pijuan, Judith, Lawless, Conor, Bühler, Philipp K, Kouyos, Roger D, Lemon, Katherine P, Zinkernagel, Annelies S, Brugger, Silvio D
• Format: Article
• Language: English
• Subjects: antimicrobial resistance; bacterial fitness; image analysis; Methods and Protocols; Novel Systems Biology Techniques; quantitative fitness analysis
• ISSN: 2379-5077; 2379-5077
• DOI: 10.1128/MSYSTEMS.01323-20

To evaluate changes in reproductive fitness of bacteria, e.g., after acquisition of antimicrobial resistance, a low-cost high-throughput method to analyze bacterial growth on agar is desirable for broad usability. In our bacterial quantitative fitness analysis (BaQFA), arrayed cultures are spotted on agar and photographed sequentially while growing. These time-lapse images are analyzed using a purpose-built open-source software to derive normalized image intensity (NI) values for each culture spot. Subsequently, a Gompertz growth model is fitted to NI values, and fitness is calculated from model parameters. To represent a range of clinically important pathogenic bacteria, we used different strains of , , and , with and without antimicrobial resistance. Relative competitive fitness (RCF) was defined as the mean fitness ratio of two strains growing competitively on one plate.BaQFA permitted the accurate construction of growth curves from bacteria grown on semisolid agar plates and fitting of Gompertz models. Normalized image intensity values showed a strong association with the total CFU/ml count per spotted culture (