Abstract
The outcome of an antibiotic treatment on the growth capacity of bacteria is largely dependent on the initial population size (Inoculum Effect). We characterized and built a model of this effect in E. coli cultures using a large variety of antimicrobials, including conventional antibiotics, and for the first time, cationic antimicrobial peptides (CAMPs). Our results show that all classes of antimicrobial drugs induce an inoculum effect, which, as we explain, implies that the dynamic is bistable: For a range of anti-microbial densities, a very small inoculum decays whereas a larger inoculum grows, and the threshold inoculum depends on the drug concentration. We characterized three distinct classes of drug-induced bistable growth dynamics and demonstrate that in rich medium, CAMPs correspond to the simplest class, bacteriostatic antibiotics to the second class, and all other traditional antibiotics to the third, more complex class. These findings provide a unifying universal framework for describing the dynamics of the inoculum effect induced by antimicrobials with inherently different killing mechanisms.
Highlights
Antibiotic resistance is rising to dangerously high levels in all parts of the world.Over-prescription and misusage cause natural selection that favors strains with new resistance mechanisms, threatening our ability to treat common infectious diseases effectively
In rich medium, the rate of change of the bacterial concentration depends only on its current concentration (B(t)) and not on the initial load B(0) or the time of growth. Such a behavior corresponds to classical deterministic 1D dynamics, so, this verifies that the bacterial dynamics in rich medium is well approximated by the one-dimensional model (1) for at least 16 h
In all agents we tested, including all cationic antimicrobial peptides and all conven‐ tional antibiotics, independently of their biochemical mechanism of action (Table 1), we found the inoculum effect
Summary
Antibiotic resistance is rising to dangerously high levels in all parts of the world. A much greater proportion of the signaling factors is available per cell, and bacteria can better cope with the relevant stressor [30] Another density-dependent mechanism, which does not involve cellular signaling, is reduction in the antibiotic concentration. The above density dependent mechanisms are inherently nonlinear since they do not increase gradually, proportionally to the bacterial load and antimicrobial concentration, but rather have either a threshold or limiting effects. In the bacteria-antimicrobial context, a monostable system corresponds to the case where any initial number of bacteria (B) reaches the same maximal population size if treated with antibiotic concentration (A) that does not kill all cells (“sub-lethal treatment”). Polymixin B was purchased from Fluka BioChemika (Seelze, Germany). and tetracycline hydrochloride was purchased from Sigma-Aldrich (Rehovot, Israel)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
