Growth rate assays reveal fitness consequences of β-lactamases

Antibiotic resistance is a powerful model for studying evolutionary biology and population genetics. For the purpose of these evolutionary studies, fitness data have been approximated through susceptibility testing methods designed for clinical use in providing appropriate antibiotic therapies. An alternative approach for measuring fitness of microbes has experienced growing popularity: growth rates are a highly sensitive approach for measuring the fitness effects of antibiotics and resistance genes, but they differ from susceptibility testing in that a single concentration of antibiotic is used for the assay. Here we show that despite this key difference, the results of growth rates correlate well with clinical determination of resistance by minimum inhibitory concentration (MIC), while providing the sensitivity required for direct input as fitness values into mathematical models. This means that growth rates at a single sublethal inhibitory concentration can help us understand the fitness effects that result in clinical antibiotic resistance. By measuring the growth rates of sequenced clinical isolates obtained from Dignity Health Mercy Medical Center, we detected the fitness effects of individual resistance genes on bacteria exposed to different antibiotics. In our study, the CTX-M-15 gene conferred the highest fitness in assays with cephalosporins. These results show the strong fitness benefit conferred by CTX-M-15. NON-TECHNICAL SUMMARY: Antibiotic resistance is a global human health problem. We partnered with Dignity Health Mercy Medical Center to study antibiotic resistance in clinical isolates. We tested whether growth rates, a sensitive assay used to measure the fitness of bacterial samples, correlate with a clinical test to measure antibiotic resistance. We found a strong correlation between these two methods suggesting that growth rates could be reliably applied to evolutionary studies of clinically relevant problems. Moreover, the sensitivity of the growth rates assay enabled us to identify fitness effects of specific antibiotic resistance genes.