Modeling the Combination of Amphotericin B, Micafungin, and Nikkomycin Z against Aspergillus fumigatus In Vitro Using a Novel Response Surface Paradigm

Abstract

Response surface methods for the study of multiple-agent interaction allow one to model all of the information present in full concentration-effect data sets and to visualize and quantify local regions of synergy, additivity, and antagonism. In randomized wells of 96-well plates, Aspergillus fumigatus was exposed to various combinations of amphotericin B, micafungin, and nikkomycin Z. The experimental design was comprised of 91 different fixed-ratio mixtures, all performed in quintuplicate. After 24 h of drug exposure, drug effect on fungal viability was assessed using the tetrazolium salt 2,3-bis {2-methoxy-4-nitro-5-[(sulfenylamino) carbonyl]-2H-tetrazolium-hydroxide} (XTT) assay. First, we modeled each fixed-ratio combination alone using the four-parameter Hill concentration-effect model. Then, we modeled each parameter, including the 50% inhibitory concentration (IC 50 ) effect, versus the proportion of each agent using constrained polynomials. Finally, we modeled the three-agent response surface overall. The overall four-dimensional response surface was complex, but it can be explained in detail both analytically and graphically. The grand model that fit the best included complex polynomial equations for the slope parameter m and the combination index (equivalent to the IC 50 for a fixed-ratio concentration, but with concentrations normalized by the respective IC 50 s of the drugs alone). There was a large region of synergy, mostly at the nikkomycin Z/micafungin edge of the ternary plots for equal normalized proportions of each drug and extending into the center of the plots. Applying this response surface method to a huge data set for a three-antifungal-agent combination is novel. This new paradigm has the potential to significantly advance the field of combination antifungal pharmacology.Invasive aspergillosis is a major cause of morbidity and mortality in highly immunocompromised persons (15). Risk factors for invasive aspergillosis include prolonged neutropenia, hematopoietic stem cell transplantation, solid organ transplantation, advanced AIDS, and chronic granulomatous disease (22). The expansion of the number of antifungal drugs with different modes of action that are used in the clinic and that are at preclinical stages of development has generated significant interest in combination antifungal therapy for invasive aspergillosis (4,11,13,14,25). The recent sequencing of the Aspergillus fumigatus genome will provide additional tools for the identification of novel targets for drug development (19). These important advances create a greater need to model effectively the combination of antifungal agents in vitro and in vivo.In the past, various approaches to the assessment of synergy, additivity, and antagonism have been developed. They include older graphical isobologram methods and newer statistical response surface methods. The older methods are mostly limited to two-agent interactions; however, several statistical response surface methods can be used for three-agent and higher order combinations. R...

Trehalose 6‐phosphate phosphatase is required for cell wall integrity and fungal virulence but not trehalose biosynthesis in the human fungal pathogen Aspergillus fumigatus

“…5B and C). CFW is an inhibitor of chitin polymer assembly while NK is a chitin synthase inhibitor (Ram and Klis, 2006; Brun et al ., 2007; Kaur et al ., 2007). Taken together, these results suggest that β‐1,3‐glucan and β‐1,6‐glucan synthesis is likely unaffected, or at least not reduced, in the absence of OrlA.…”

“…Several cell wall inhibitors were utilized for cell wall integrity tests: CR (Sigma Aldrich), CFW (Sigma Aldrich) and NK (Sigma Aldrich; Ram and Klis, 2006; Brun et al ., 2007; Kaur et al ., 2007). CR, CFW or NK were added into GMM at final concentrations of 1 mg ml −1 , 25 µg ml −1 and 0.1 mM respectively; 1 × 10 6 conidia (in a 5 µl drop) of each test strain were placed on the centre of each plate.…”

An application of a Hill-based response surface model for a drug combination experiment on lung cancer

“…In particular, for a three‐drug combination with p = 3, we only include θ 1 and θ 2 because θ 3 = 1 − θ 1 − θ 2 is implicitly included in the model. It is possible to include all θ i explicitly with reparameterization; see .…”

“…To take advantage of both the Hill model and the polynomial model while excluding their respective limitations, we here introduce a global dose–response surface model for multiple drug combinations by combining these two classic models . To inherit the basic principle from the Hill model for two‐drug combinations, we assume a combination with a fixed proportion between multiple drugs as a ‘new’ drug whose dose–effect curve follows a distinct Hill model.…”

“…The model, derived from both Hill and polynomial models, combines the strengths of the two originating models while avoiding their shortcomings. Brun et al applied the Hill‐based model in an anti‐fungal study with a ray design of three drugs. Here, we further apply the model to data from a three‐drug combination experiment on lung cancer with a full factorial design.…”