Quantifying variation in bacterial reproductive fitness with and without antimicrobial resistance: a high-throughput method

Abstract

ABSTRACTBackgroundTo evaluate changes in reproductive fitness of bacteria, e.g., after acquisition of antimicrobial resistance, a low-cost high-throughput method to analyse bacterial growth on agar is desirable for broad usability, including in low-resource settings.MethodIn our bacterial quantitative fitness analysis (baQFA), cultures are spotted in a predefined array on agar plates and photographed sequentially while growing. These time-lapse images are analysed using a purpose-built open source software to derive normalised image intensity values for each culture spot. Subsequently, a Gompertz growth model is fitted to these optical intensity values of each culture spot and fitness is calculated from parameters of the model. For image segmentation validation, we investigated the association between normalised intensity values and colony-forming unit (CFU) counts. To represent a range of clinically important pathogenic bacteria, we used different strains of Enterococcus faecium, Escherichia coli and Staphylococcus aureus, with and without antimicrobial resistance. Relative competitive fitness (RCF) was defined as the mean fitness ratio of two strains growing competitively on one plate.ResultsbaQFA permitted the accurate construction of growth curves from bacteria grown on semisolid agar plates and fitting of Gompertz models: Normalised image intensity values showed a strong association with the total CFU/ml count per spotted culture (p<0.001) for all strains of the three species. Bacterial QFA showed relevant reproductive fitness differences between individual strains, suggesting substantial higher fitness of methicillin-resistant S. aureus JE2 than Cowan (RCF 1.60, p<0.001). Similarly, the vancomycin-resistant E. faecium ST172b showed higher competitive fitness than susceptible E. faecium ST172 (RCF 1.72, p<0.001).ConclusionOur baQFA adaptation allows detection of fitness differences between our bacterial strains, and is likely to be applicable to other bacteria. In the future, baQFA may help to estimate epidemiological antimicrobial persistence or contribute to the prediction of clinical outcomes in severe infections at a low cost.