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Review
. 2023 Dec 12;9(12):1188.
doi: 10.3390/jof9121188.

In Vitro Susceptibility Tests in the Context of Antifungal Resistance: Beyond Minimum Inhibitory Concentration in Candida spp

Iacopo Franconi  1   2 , Antonella Lupetti  1   2
Affiliations
Review

In Vitro Susceptibility Tests in the Context of Antifungal Resistance: Beyond Minimum Inhibitory Concentration in Candida spp

Iacopo Franconi et al. J Fungi (Basel). .

Abstract

Antimicrobial resistance is a matter of rising concern, especially in fungal diseases. Multiple reports all over the world are highlighting a worrisome increase in azole- and echinocandin-resistance among fungal pathogens, especially in Candida species, as reported in the recently published fungal pathogens priority list made by WHO. Despite continuous efforts and advances in infection control, development of new antifungal molecules, and research on molecular mechanisms of antifungal resistance made by the scientific community, trends in invasive fungal diseases and associated antifungal resistance are on the rise, hindering therapeutic options and clinical cures. In this context, in vitro susceptibility testing aimed at evaluating minimum inhibitory concentrations, is still a milestone in the management of fungal diseases. However, such testing is not the only type at a microbiologist's disposal. There are other adjunctive in vitro tests aimed at evaluating fungicidal activity of antifungal molecules and also exploring tolerance to antifungals. This plethora of in vitro tests are still left behind and performed only for research purposes, but their role in the context of invasive fungal diseases associated with antifungal resistance might add resourceful information to the clinical management of patients. The aim of this review was therefore to revise and explore all other in vitro tests that could be potentially implemented in current clinical practice in resistant and difficult-to-treat cases.

Keywords: Candida spp. fungicidal tests; antifungal resistance; antifungal susceptibility testing; antifungal tolerance; minimum fungicidal concentration; serum fungicidal concentration; time-kill curve analysis.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Minimum fungicidal concentration assessment method. MIC = minimum inhibitory concentration; MFC = minimum fungicidal concentration. After determination of the MIC value, yeast and antifungal drug suspensions contained in each clear well were displaced on solid agar medium. To avoid antifungal carryover, streaking is performed once the suspension is soaked and the plate is dried. Plates are incubated at 35 °C for 24–48 h in order to count yeast colonies. The first concentration at which 3-Log unit reduction or 99.9% of killing of the final inoculum is observed corresponds to the MFC. Procedure according to Cantón et al. [43]. Image created with BioRender.com.
Figure 2
Figure 2
Time-kill curve assessment method. Time-kill curve analysis according to Klepser et al. [63]. Fungicidal concentration is calculated as the lowest antifungal drug concentration exerting a killing effect (3-Log unit reduction in CFU count or 99.9% of killing of the initial inoculum) at the end of the experiment (24–48 h) as highlighted in the line graph on the left.
Figure 3
Figure 3
Serum fungicidal concentration assessment method. Schematic representation of the serum fungicidal concentration method. On the right serial dilutions of patient’s serum added with fungal suspension with a final inoculum of 5 × 105 CFU/mL. This method refers to the SBC determination methods proposed by Fisher and described by Wolfson and colleagues [84]. GC = growth control. Red line represents the serum concentration kinetic of the selected antifungal.
Figure 4
Figure 4
Evaluation of antifungal tolerance during the disk diffusion test using the diskImageR software (https://cran.r-project.org/). Cell density is highlighted by different shades of color; a more intense color defines a higher cell density and is associate with a higher pixel intensity. RAD = radius of inhibition. RAD20, RAD50, and RAD80 represent the respective distances from the border of the disk where reductions of growth of 20, 50, and 80% are observed, respectively. The area under the curve estimates the fraction of growth (FoG).
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