Original articleComparison of methods for assessing synergic antibiotic interactions
Introduction
Definitions of synergy and antagonism are a contentious issue. In theory, synergy occurs at a fractional inhibitory concentration (FIC) index or fractional bactericidial concentration (FBC) index of <1, but as the chequerboard method has a ±1 dilution error, convention states that synergy is ≤0.5. However, ‘minor’ synergy, (i.e. up to 1), may be clinically important as argued by Berenbaum [1]. Criteria ranging from >1 to >4 have been used to define antagonism. The >4 rule, is widely accepted as it reduces in the presence of experimental error. Also, lower antagonism criteria may have no clinical significance [2].
The advantage of using a chequerboard technique for studying antibiotic interactions is that it is a commonly used method so data produced can be easily compared with already published studies. The technique is also easy to understand and simple, although time consuming to perform. If time kill studies can be combined with chequerboards, then much more detailed kinetic information can be generated for relatively little extra work.
Several studies have assessed the clinical relevance of in vitro synergy testing. For instance, comparison of in vitro antibiotic combination with clinical outcome in serious infection with Pseudomonas aeruginosa suggested that chequerboards were of little value in predicting clinical outcome [3] but in a study of 30 isolates of P. aeruginosa causing endocarditis, lack of synergy in vitro indicated refractoriness to treatment [4].
In this present study, we describe the in vitro assessment of antibiotic interactions in a series of multi-resistant clinical isolates, from patients with relapsing infection, using the same chequerboard methodology to calculate FIC and FBC indices and time kill curves. In previous studies, we have found this method is both reproducible and gives good correlation between FIC and FBC indices and time kill curves [5], [6].
Section snippets
Bacteria studied
Ten strains were studied: Two Staphylococcus aureus (S, D) isolated from infected hip joints, one Klebsiella pneumoniae isolated from cerebro-spinal fluid of a patient with meningitis and seven Burkholderia cepacia, four isolated from cystic fibrosis patients, (CF26, CF28, CF29 pigmented (CF29p) and CF29 non-pigmented (CF29np)), and the other three from a patient with a chronic cerebellar abscess, (Ps132, Ps 141 sensitive (Ps141s) and Ps141 resistant (Ps141r)). All were recent isolates from
Results
Table 1 details the antibiotic combinations tested against each organism, the MIC of each antibiotic/organism combination, the maximum antibiotic concentrations tested in each chequerboard, the FIC and FBC indices and the concentration of antibiotics demonstrating the most synergic activity. Only 21 of the 25 chequerboards could be used to compare the FIC indices and FBC indices as the rest only produced one set of indices or none. No differences between the means of the FIC and FBC indices
Discussion
There is a widely reported lack of correlation between the chequerboard technique and time-kill studies. Norden et al. [3] postulated that correlation can be increased by performing all the synergy tests on the same day, so reducing the observed variability in results. Combination of all measurements within the chequerboard therefore may reduce this variability as we have found previously [5], [6].
The observed differences between the bacteriostatic and bactericidal results are most likely due
Acknowledgements
We are grateful to Dr M. Allan of Wyeth for support.
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2022, Biomedicine and PharmacotherapyCitation Excerpt :Afterward, FBECi for the two combined antibacterial agents was calculated as follows: FBECi = (MBEC drug A in combination/ MBEC drug A alone) + (MBEC drug B in combination/ MBEC drug B alone). FBEC indices are pointed to the kind of drug interaction if the following data are established: Synergy, values n ≤ 0.5; Partial synergy, values 0.5 < n < 1; Additive effect, for a value n = 1; Indifferent effect, for values 1 < n < 4; Antagonistic effect, for a value 4 ≤ n [23,24,51]. Biofilm forming S. epidermidis isolates include strong biofilm-forming MRSE 1, strong biofilm-forming MRSE 4, moderate biofilm-forming MRSE 5, moderate biofilm-forming MSSE 1, as well as strong biofilm-forming S. epidermidis ATCC 35984 were used for evaluation of biofilm-associated expression genes (icaA, aap, and psmβ) by real-time PCR.