Author:
Schei Haugan Maria,Løbner-Olesen Anders,Frimodt-Møller Niels
Abstract
AbstractCommonly used antibiotics exert their effect predominantly on rapidly growing bacterial cells, yet growth dynamics taking place during infection in a complex host environment remain largely unknown. Hence, means to measure in situ bacterial growth rate is essential to predict the outcome of antibacterial treatment. We have recently validated chromosome replication as readout for in situ bacterial growth rate during Escherichia coli infection in the mouse peritonitis model. By the use of two complementary methods (qPCR and fluorescence microscopy) for differential genome origin and terminus copy number quantification, we demonstrated the ability to track bacterial growth rate, both on a population average and on a single-cell level; from one single biological specimen. Here, we asked whether the in situ growth rate could predict antibiotic treatment effect during infection in the same model. Parallel in vitro growth experiments were conducted as proof-of-concept. Our data demonstrate that the activity of commonly used antibiotics Ceftriaxone and Gentamicin correlated with pre-treatment bacterial growth rate; both drugs performing better during rapid growth than during slow growth. Conversely, Ciprofloxacin was less sensitive to bacterial growth rate, both in a homogenous in vitro bacterial population and in a more heterogeneous in vivo bacterial population. The method serves as a platform to test any antibiotic’s dependency upon active in situ bacterial growth. Improved insight into this relationship in vivo could ultimately prove helpful in evaluating future antibacterial strategies.ImportanceMost antibiotics in clinical use exert their effect predominantly on rapidly growing bacterial cells, yet there is a lack of insight into bacterial growth dynamics taking place during infection in vivo. We have applied inexpensive and easily accessible methods for extraction of in situ bacterial growth rate from bacterial chromosome replication during experimental murine infection. This approach not only allows for a better understanding of bacterial growth dynamics taking place during the course of infection, but also serves as a platform to test the activity of different antibiotics as a function of pre-treatment in situ growth rate. The method has the advantage that bacterial growth rate can be probed from a single biological sample, with the potential for extension into clinical use in pre-treatment infected biological specimens. A better understanding of commonly used antibiotics’ level of dependency upon bacterial growth, combined with measurements of in situ bacterial growth rate in infected clinical specimens, could prove helpful in evaluating future antibacterial treatment regimens.
Publisher
Cold Spring Harbor Laboratory