No abstract

f Combination therapy is rarely used to counter the evolution of resistance in bacterial infections. Expansion of the use of combination therapy requires knowledge of how drugs interact at inhibitory concentrations. More than 50 years ago, it was noted that, if bactericidal drugs are most potent with actively dividing cells, then the inhibition of growth induced by a bacteriostatic drug should result in an overall reduction of efficacy when the drug is used in combination with a bactericidal drug. Our goal here was to investigate this hypothesis systematically. We first constructed time-kill curves using five different antibiotics at clinically relevant concentrations, and we observed antagonism between bactericidal and bacteriostatic drugs. We extended our investigation by performing a screen of pairwise combinations of 21 different antibiotics at subinhibitory concentrations, and we found that strong antagonistic interactions were enriched significantly among combinations of bacteriostatic and bactericidal drugs. Finally, since our hypothesis relies on phenotypic effects produced by different drug classes, we recreated these experiments in a microfluidic device and performed time-lapse microscopy to directly observe and quantify the growth and division of individual cells with controlled antibiotic concentrations. While our single-cell observations supported the antagonism between bacteriostatic and bactericidal drugs, they revealed an unexpected variety of cellular responses to antagonistic drug combinations, suggesting that multiple mechanisms underlie the interactions.

Many bacteria mediate important life-style decisions by varying levels of the second messenger c-di-GMP. Behavioral transitions result from the coordination of complex cellular processes such as motility, surface adherence or the production of virulence factors and toxins. While the regulatory mechanisms responsible for these processes have been elucidated in some cases, the global pleiotropic effects of c-di-GMP are poorly understood, primarily because c-di-GMP networks are inherently complex in most bacteria. Moreover, the quantitative relationships between cellular c-di-GMP levels and c-di-GMP dependent phenotypes are largely unknown. Here, we dissect the c-di-GMP network of Caulobacter crescentus to establish a global and quantitative view of c-di-GMP dependent processes in this organism. A genetic approach that gradually reduced the number of diguanylate cyclases identified novel c-di-GMP dependent cellular processes and unraveled c-di-GMP as an essential component of C. crescentus cell polarity and its bimodal life cycle. By varying cellular c-di-GMP concentrations, we determined dose response curves for individual c-di-GMP-dependent processes. Relating these values to c-di-GMP levels modeled for single cells progressing through the cell cycle sets a quantitative frame for the successive activation of c-di-GMP dependent processes during the C. crescentus life cycle. By reconstructing a simplified c-di-GMP network in a strain devoid of c-di-GMP we defined the minimal requirements for the oscillation of c-di-GMP levels during the C. crescentus cell cycle. Finally, we show that although all c-di-GMP dependent cellular processes were qualitatively restored by artificially adjusting c-di-GMP levels with a heterologous diguanylate cyclase, much higher levels of the second messenger are required under these conditions as compared to the contribution of homologous c-di-GMP metabolizing enzymes. These experiments suggest that a common c-di-GMP pool cannot fully explain spatiotemporal regulation by c-di-GMP in C. crescentus and that individual enzymes preferentially regulate specific phenotypes during the cell cycle.