Parameterization of Inoculum Effect Via Mathematical Modeling: Aminoglycosides AgainstStaphylococcus aureusandEscherichia coli

Abstract

Inoculum effect describes the inoculum size dependent changes in minimum inhibitory concentrations (MIC) exhibited by antibiotic-bacterium combinations demonstrating such effect. Traditionally, inoculum effect has been loosely defined based on the extent of increase in the MIC with respect to the increase in inoculum size. In most studies, assessment of MIC data has relied on the arbitrary selection of a point of reference for both baseline MIC and inoculum size. More importantly, this conventional method of assessment does not permit information conveyed in a complete MIC versus inoculum size profile to be fully explored. To undertake these issues, a mathematical model was developed for the description of the entire inoculum effect profile. With the employment of three key parameter estimates, i.e., the baseline MIC, the threshold inoculum size at which the increase in MIC commences, and the rate of increase in MIC with respect to inoculum size, both the shape and location of the profile could be adequately defined. To verify the application of this model, a series of four aminoglycosides were tested against standard strains of E. coli and S. aureus. Results showed a good degree of organism specificity and antibiotic-class dependency of the inoculum effect profiles. Analysis of the parameter estimates obtained provided further support for these observations. In conclusion, the mathematical model developed in the present study adequately described the inoculum effect exhibited by the various aminoglycoside-bacterium combinations tested. The parameter estimates generated by the modeling approach allowed comparison and quantitative analysis of the inoculum effect profiles with minimal difficulties.

Microscopic Analysis of Bacterial Inoculum Effect Using Micropatterned Biochip

“…Amikacin, a subclass of aminoglycoside, combines with the 30S ribosomal subunit, which is an irreversible process. Owing to this characterization, we concluded that E. coli has a moderate inoculum effect against amikacin, which corresponds with the findings of other studies [20,25,41]. Unlike cefotaxime, ampicillin, and piperacillin did not show a significant inoculum effect in IBAST.…”

“…Unlike tetracyclines, aminoglycoside inhibition is irreversible, which means that if binding has been completed, recycling is not possible. Therefore, the bacterial densities were found to depend on the antibiotic concentration [20,25]. Studies have suggested that this may be due to natural selection.…”

Vancomycin and maltodextrin affect structure and activity of Staphylococcus aureus biofilms

“…Although the combination effect only showed a 2‐log reduction in CFU density, this 2‐log change may be significant in the context of a real infection and can be tested through in vivo experiments. In our case, we tested this effect for already developed mature biofilm; it may be more significant in initially developing biofilms, because of the inoculum effect (Corrado et al, ; Li and Ma, ; Rose et al, ). Young biofilms grown for 24 h can have 7–8 logs of CFU (Amorena et al, ; Barraud et al, ; Culler et al, ; Freitas et al, ).…”

Synthesis, Critical Micelle Concentrations, and Antimycobacterial Properties of Homologous, Dendritic Amphiphiles. Probing Intrinsic Activity and the “Cutoff” Effect

“…This phenomenon is referred to as the “inoculum effect”. − The “inoculum effect” presumably reflects the increased demand for a given drug as the number of cells and targets increases . A mathematical model (eq 1) of the “inoculum effect” describes the independence of log MIC at low inoculum by defining log MIC 0 as the intrinsic activity, log I as the inoculum, and log I tr as the inoculum at the threshold immediately before the rise in MIC, and k is a constant that describes the rate of increase in MIC. Equation 1 is flat at low inoculum and rises exponentially after I tr , which varies by drug (Figure ).…”