Investigating Antifungal Susceptibility in Candida Species With MALDI-TOF MS-Based Assays

Abstract

Half of invasive fungal infections lead to death. Amongst pathogenic fungi, the most widespread species belong to the Candida genus and vary in their susceptibility to antifungal drugs. The emergence of antifungal resistance has become a major clinical problem. Therefore, the definition of susceptibility patterns is crucial for the survival of patients and the monitoring of resistance epidemiology. Although, most routinely used methods of AntiFungal Susceptibility Testing (AFST) have reached their limits, the rediscovery of Matrix Associated Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) in the field of mycology provides a promising alternative for the study of antifungal resistance. MALDI-TOF MS is already used in mycology for fungal identification, which permits to highlight inherent antifungal resistance. However, the main concern of clinicians is the rise of acquired antifungal resistance and the time needed for their detection. For this purpose, MALDI-TOF MS has been shown to be an accurate tool for AFST, presenting numerous advantages in comparison to commonly used techniques. Finally, MALDI-TOF MS could be used directly to detect resistance mechanisms through typing. Consequently, MALDI-TOF MS offers new perspectives in the context of healthcare associated outbreaks of emerging multi-drug resistant fungi, such as C. auris. As a proof of concept, we will illustrate the current and future benefits in using and adapting MALDI-TOF MS-based assays to define the susceptibility pattern of C. auris, by species identification, AFST, and typing.

Keywords: Candida spp.; MALDI-TOF MS; antifungal resistance; antifungal susceptibility testing; identification; typing.

Figure 1

Evolution of the MALDI-TOF MS-based AFST assay. (A) MPCC determination. A 13 × 13 CCI matrix (personal data) is generated by comparing the spectra obtained after exposure to increasing concentrations of fluconazole (0 = MIN to 256 μg/mL = MAX), as explained in De Carolis et al. (2012). Red gradient corresponds to strong correlations and blue gradient corresponds to weak ones. The first and the last column of the CCI matrix, namely the comparison of the spectra at all concentrations with the spectra at MAX (blue box) and at MIN (green box), respectively, are isolated. The MPCC (yellow box) corresponds to the fluconazole concentration at which the value of the MAX column is higher (>) than the value of the MIN column, at the same concentration. (B) MPCC breakpoint determination. MPCC values of several susceptible (S1 to S5) and resistant (R1 to R5) strains from the same Candida spp. are compared. “>” indicates that the spectra at the given concentration is more similar to the spectra at MAX, whereas “ < ” indicates that the spectra at the given concentration is more similar to the spectra at MIN. The MPCC breakpoint concentration (S) correspond to the fluconazole concentration which allow the best discrimination between the resistant and the susceptible strains (red box), as explained in De Carolis et al. (2012). (C) MALDI-TOF MS-based assay. A 3 × 3 CCI matrix is generated by comparing the spectra at MAX, S, and MIN, as presented in Vella et al. (2013). The results of the correlation between S and MAX (blue box) and S and MIN (green box) are compared. The strain is assessed as susceptible if the result of the correlation between S an MAX is higher than the result of the correlation between S and MIN (left matrix, personal data), whereas the strain is assessed as resistant if the result of the correlation between S an MAX is lower than the result of the correlation between S and MIN (right matrix, personal data).^*Lohberger et al. (2014), FLC = fluconazole.

Figure 2

Proposition of C. auris outbreak management with MALDI-TOF MS. (A) Spectrum acquisition. A C. auris colony (here grown on Columbia medium) is analyzed by MALDI-TOF MS to obtain a spectrum. (B) Identification. The spectrum obtained is compared to the reference spectra of the databases and an identification Log(Score) is calculated. For fungal species, a proposed identification is accepted if the Log(Score) is equal or higher than 1.7. C. auris identification with MALDI-TOF MS is already implemented but needs improvements. (C) AFST. Spectra obtained at different antifungal concentrations need to be compared to determine the MPCC. From there, once the EUCAST and/or CLSI breakpoints have been defined, the MPCC breakpoint for C. auris and an antifungal drug can be determined, allowing the AFST implementation. AFST with MALDI-TOF MS need to be adapted from existing protocols (Marinach et al., ; De Carolis et al., ; Vella et al., 2013, 2017) to be used on C. auris. (D) Typing. Spectra of different C. auris strains originated from different clades and with different resistance mechanisms could be compared to identify signature peaks specific to different resistance mechanisms or different clades. C. auris typing with MALDI-TOF MS needs to be developed.