Introduction. Quantification of bacterial load in tissue homogenates in in vivo pharmacodynamic studies is cumbersome and time-consuming.Aim. We therefore developed a new method for quantifying bacterial load in tissue homogenates of animals treated with a β-lactam and β-lactamase inhibitor using growth curves.Methods. The log10 colony-forming units (c.f.u.) ml-1 of 184 thigh and lung homogenates from female CD-1 mice infected intranasally and intramuscularly with 4 Pseudomonas aeruginosa, 4 Klebsiella pneumoniae, 3 Enterobacter cloacae and 2 Escherichia coli strains treated with a β-lactam drug and tazobactam were calculated using the standard approach of serial quantitative cultures and analysis of growth curves. Growth curves were obtained with continuous (every 10 min) monitoring of optical density at 630 nm (OD630) after 20 µl tissue homogenates were inoculated in total volume of 200 µl Mueller-Hinton broth in 96-well microtitration plates and incubated at 37 °C for 18 h.Results. The best correlation between log10 c.f.u. ml-1 determined with the serial quantitative cultures and growth curves was found at the time point corresponding to an OD630 of 0.25 increase above the baseline OD (average of first five timepoints) (R2=0.918-0.999). The median (range) differences between the two methods was -0.19 (-1.79-1.69) with 86-97 % of all isolates and species being within 1 log10 c.f.u. ml-1 with 1 h hands-on-time and <13 h of incubation for 96 samples. Pharmacodynamic analysis showed similar dose-response relationships and 1 log kill dose estimations (paired t-test, P=0.112).Conclusion. The new technique resulted in comparable c.f.u. counts to those for the standard serial dilution/culture technique with minimal hands-on and turnaround times.

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doi.org/10.1099/jmm.0.001183, hdl.handle.net/1765/127571
Journal of Medical Microbiology

Georgiou, P.-C. (Panagiota-Christina), Mouton, J., Pournaras, S., & Meletiadis, J. (2020). Bacterial quantification in tissue homogenates from in vivo pharmacodynamic studies using growth curves. Journal of Medical Microbiology, 69(5), 676–684. doi:10.1099/jmm.0.001183