MALDI-TOF typing highlights geographical and fluconazole resistance clusters in Candida glabrata

Nosocomial transmission of Aspergillus flavus in a neonatal intensive care unit: Long-term persistence in environment and interest of MALDI-ToF mass-spectrometry coupled with convolutional neural network for rapid clone recognition

Aspergillosis of the newborn remains a rare but severe disease. We report four cases of primary cutaneous Aspergillus flavus infections in premature newborns linked to incubators contamination by putative clonal strains. Our objective was to evaluate the ability of matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) coupled to convolutional neural network (CNN) for clone recognition in a context where only a very small number of strains are available for machine learning. Clinical and environmental A. flavus isolates (n = 64) were studied, 15 were epidemiologically related to the four cases. All strains were typed using microsatellite length polymorphism. We found a common genotype for 9/15 related strains. The isolates of this common genotype were selected to obtain a training dataset (6 clonal isolates/25 non-clonal) and a test dataset (3 clonal isolates/31 non-clonal), and spectra were analysed with a simple CNN model. On the test dataset using CNN model, all 31 non-clonal isolates were correctly classified, 2/3 clonal isolates were unambiguously correctly classified, whereas the third strain was undetermined (i.e., the CNN model was unable to discriminate between GT8 and non-GT8). Clonal strains of A. flavus have persisted in the neonatal intensive care unit for several years. Indeed, two strains of A. flavus isolated from incubators in September 2007 are identical to the strain responsible for the second case that occurred 3 years later. MALDI-TOF is a promising tool for detecting clonal isolates of A. flavus using CNN even with a limited training set for limited cost and handling time.

Identification of Mycobacterium abscessus Subspecies by MALDI-TOF Mass Spectrometry and Machine Learning

Mycobacterium abscessus is one of the most common and pathogenic nontuberculous mycobacteria (NTM) isolated in clinical laboratories. It consists of three subspecies: M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense. Due to their different antibiotic susceptibility pattern, a rapid and accurate identification method is necessary for their differentiation. Although matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has proven useful for NTM identification, the differentiation of M. abscessus subspecies is challenging. In this study, a collection of 325 clinical isolates of M. abscessus was used for MALDI-TOF MS analysis and for the development of machine learning predictive models based on MALDI-TOF MS protein spectra. Overall, using a random forest model with several confidence criteria (samples by triplicate and similarity values >60%), a total of 96.5% of isolates were correctly identified at the subspecies level. Moreover, an improved model with Spanish isolates was able to identify 88.9% of strains collected in other countries. In addition, differences in culture media, colony morphology, and geographic origin of the strains were evaluated, showing that the latter had an impact on the protein spectra. Finally, after studying all protein peaks previously reported for this species, two novel peaks with potential for subspecies differentiation were found. Therefore, machine learning methodology has proven to be a promising approach for rapid and accurate identification of subspecies of M. abscessus using MALDI-TOF MS.

MALDI-TOF MS-Based Clustering and Antifungal Susceptibility Tests of Talaromyces marneffei Isolates from Fujian and Guangxi (China)

Introduction

Talaromyces marneffei is a life-threatening pathogen that causes systemic talaromycosis in immunocompromised and acquired immunodeficiency syndrome (AIDS) patients. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) as a tool to cluster T. marneffei isolates is rarely reported and the data on antifungal susceptibility of T. marneffei isolated in the southern region of China, especially in Fujian, is hardly found.

Methods

MALDI-TOF MS was used to cluster 135 T. marneffei isolates, and the minimum inhibitory concentration (MIC) values of amphotericin B, itraconazole, posaconazole, voriconazole, fluconazole, anidulafungin, micafungin, caspofungin and 5-fluorocytosine with Sensititre YeastOne™ YO10 assay were measured during January 2017 to October 2020 in Fujian and Guangxi.

Results

MALDI-TOF MS correctly identified 100% of the T. marneffei isolates. Hierarchical clustering of MALDI-TOF peak profiles identified four different clusters. MICs for itraconazole, posaconazole, voriconazole and amphotericin B were as follows: ≤0.015–0.03 μg/mL, ≤0.008–0.03 μg/mL, ≤0.008–0.06 μg/mL, ≤0.12–1 μg/mL, respectively. MICs for echinocandins and fluconazole were comparatively high.

Conclusion

Since only simple sample preparation is required and since results are available in a short period of time, MALDI-TOF MS can be considered as a method for identification and clustering of T. marneffei. Itraconazole, posaconazole, voriconazole and amphotericin B can be used to treat T. marneffei infected patients due to the low MICs.

Mass spectrometry in research laboratories and clinical diagnostic: a new era in medical mycology

Diagnosis by clinical mycology laboratory plays a critical role in patient care by providing definitive knowledge of the cause of infection and antimicrobial susceptibility data to physicians. Rapid diagnostic methods are likely to improve patient. Aggressive resuscitation bundles, adequate source control, and appropriate antibiotic therapy are cornerstones for success in the treatment of patients. Routine methods for identifying clinical specimen fungal pathogen are based on the cultivation on different media with the subsequent examination of its phenotypic characteristics comprising a combination of microscopic and colony morphologies. As some fungi cannot be readily identified using these methods, molecular diagnostic methods may be required. These methods are fast, but it can cost a lot. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is suitable for high-throughput and rapid diagnostics at low costs. It can be considered an alternative for conventional biochemical and molecular identification systems in a microbiological laboratory. The reliability and accuracy of this method have been scrutinized in many surveys and have been compared with several methods including sequencing and molecular methods. According to these findings, the reliability and accuracy of this method are very high and can be trusted. With all the benefits of this technique, the libraries of MALDI-TOF MS need to be strengthened to enhance its performance. This review provides an overview of the most recent research literature that has investigated the applications and usage of MT-MS to the identification of microorganisms, mycotoxins, antifungal susceptibility examination, and mycobiome research.

Multilocus Sequence Typing and Antifungal Susceptibility of Vaginal and Non-vaginal Candida glabrata Isolates From China

Candida glabrata is a common cause of Candida infections. In our present study, we investigated the antifungal susceptibility and molecular epidemiology of vaginal and non-vaginal C. glabrata isolates. Seventy-six vaginal C. glabrata strains isolated from patients with vulvovaginal candidiasis and 57 non-vaginal C. glabrata isolates were collected at two hospitals in Shanghai, China. Antifungal susceptibility was examined using a broth microdilution method. Multilocus sequence typing was used for genotyping. Overall, 28 (21.1%), 28 (21.1%), and 29 (21.8%) C. glabrata isolates were resistant to fluconazole, itraconazole, and voriconazole, respectively. Briefly, 18 (23.7%), 18 (23.7%), and 19 (25%) vaginal strains were resistant to fluconazole, itraconazole, and voriconazole. While the resistance to these antifungals were all 17.5% (10/57) in non-vaginal strains. All isolates retained susceptibility to amphotericin B, and only four non-vaginal isolates were caspofungin resistant. Genotyping identified 17 ST patterns. In non-vaginal samples, the same genotypes appear as in the vaginal samples, except for one genotype (ST-182), while in the vaginal samples more genotypes appear (ST8, ST19, ST45, ST55, ST66, ST80, ST138, and ST17). The most common genotype was ST7 (81 strains), followed by ST10 (14 strains) and ST15 (11 strains). The majority of resistant phenotype strains (25/30, 83.3%) correlated to the predominant genotype (ST7), and the rest belonged to ST3 (2/30, 6.7%), ST10 (1/30, 3.3%), ST19 (1/30, 3.3%), and ST45 (1/30, 3.3%). Our survey revealed cross-resistance in vaginal and non-vaginal C. glabrata isolates. Moreover, there is no genotype associated with the resistance phenotype.

Can We Improve Antifungal Susceptibility Testing?

Systemic antifungal agents are increasingly used for prevention or treatment of invasive fungal infections, whose prognosis remains poor. At the same time, emergence of resistant or even multi-resistant strains is of concern as the antifungal arsenal is limited. Antifungal susceptibility testing (AFST) is therefore of key importance for patient management and antifungal stewardship. Current AFST methods, including reference and commercial types, are based on growth inhibition in the presence of an antifungal, in liquid or solid media. They usually enable Minimal Inhibitory Concentrations (MIC) to be determined with direct clinical application. However, they are limited by a high turnaround time (TAT). Several innovative methods are currently under development to improve AFST. Techniques based on MALDI-TOF are promising with short TAT, but still need extensive clinical validation. Flow cytometry and computed imaging techniques detecting cellular responses to antifungal stress other than growth inhibition are also of interest. Finally, molecular detection of mutations associated with antifungal resistance is an intriguing alternative to standard AFST, already used in routine microbiology labs for detection of azole resistance in Aspergillus and even directly from samples. It is still restricted to known mutations. The development of Next Generation Sequencing (NGS) and whole-genome approaches may overcome this limitation in the near future. While promising approaches are under development, they are not perfect and the ideal AFST technique (user-friendly, reproducible, low-cost, fast and accurate) still needs to be set up routinely in clinical laboratories.

MALDI-TOF MS in a Medical Mycology Laboratory: On Stage and Backstage

The implementation of MALDI-TOF MS in medical microbiology laboratories has revolutionized practices and significantly reduced turnaround times of identification processes. However, although bacteriology quickly benefited from the contributions of this technique, adjustments were necessary to accommodate the specific characteristics of fungi. MALDI-TOF MS is now an indispensable tool in clinical mycology laboratories, both for the identification of yeasts and filamentous fungi, and other innovative uses are gradually emerging. Based on the practical experience of our medical mycology laboratory, this review will present the current uses of MALDI-TOF MS and the adaptations we implemented, to allow their practical execution in a daily routine. We will also introduce some less mainstream applications, like those for fungemia, or even still under development, as is the case for the determination of sensitivity to antifungal agents or typing methods.

Evaluation of Microsatellite Typing, ITS Sequencing, AFLP Fingerprinting, MALDI-TOF MS, and Fourier-Transform Infrared Spectroscopy Analysis of Candida auris

Candida auris is an emerging opportunistic yeast species causing nosocomial outbreaks at a global scale. A few studies have focused on the C. auris genotypic structure. Here, we compared five epidemiological typing tools using a set of 96 C. auris isolates from 14 geographical areas. Isolates were analyzed by microsatellite typing, ITS sequencing, amplified fragment length polymorphism (AFLP) fingerprint analysis, matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), and Fourier-transform infrared (FTIR) spectroscopy methods. Microsatellite typing grouped the isolates into four main clusters, corresponding to the four known clades in concordance with whole genome sequencing studies. The other investigated typing tools showed poor performance compared with microsatellite typing. A comparison between the five methods showed the highest agreement between microsatellite typing and ITS sequencing with 45% similarity, followed by microsatellite typing and the FTIR method with 33% similarity. The lowest agreement was observed between FTIR spectroscopy, MALDI-TOF MS, and ITS sequencing. This study indicates that microsatellite typing is the tool of choice for C. auris outbreak investigations. Additionally, FTIR spectroscopy requires further optimization and evaluation before it can be used as an epidemiological typing method, comparable with microsatellite typing, as a rapid method for tracing nosocomial fungal outbreaks.

Antifungal drug susceptibility, molecular basis of resistance to echinocandins and molecular epidemiology of fluconazole resistance among clinical Candida glabrata isolates in Kuwait

Candida glabrata readily develops resistance to echinocandins. Identification, antifungal susceptibility testing (AST) and resistance mechanism to echinocandins among C. glabrata was determined in Kuwait. C. glabrata isolates (n = 75) were tested by Vitek2, multiplex PCR and/or PCR-sequencing of rDNA. AST to fluconazole, caspofungin, micafungin and amphotericin B was determined by Etest and to micafungin by broth microdilution (BMD). Mutations in hotspot-1/hotspot-2 of FKS1/FKS2 and ERG11 were detected by PCR-sequencing. All isolates were identified as C. glabrata sensu stricto. Seventy isolates were susceptible and five were resistant to micafungin by Etest and BMD (essential agreement, 93%; categorical agreement, 100%). Three micafungin-resistant isolates were resistant and two were susceptible dose-dependent to caspofungin. Four and one micafungin-resistant isolate contained S663P and ∆659 F mutation, respectively, in hotspot-1 of FKS2. Micafungin-resistant isolates were genotypically distinct strains. Only one of 36 fluconazole-resistant isolate contained nonsynonymous ERG11 mutations. Thirty-four of 36 fluconazole-resistant isolates were genotypically distinct strains. Our data show that micafungin susceptibility reliably identifies echinocandin-resistant isolates and may serve as a surrogate marker for predicting susceptibility/resistance of C. glabrata to caspofungin. All micafungin-resistant isolates also harbored a nonsynonymous/deletion mutation in hotspot-1 of FKS2. Fingerprinting data showed that echinocandin/fluconazole resistance development in C. glabrata is not clonal.

Outbreak of Saprochaete clavata Sepsis in Hematology Patients: Combined Use of MALDI-TOF and Sequencing Strategy to Identify and Correlate the Episodes

Introduction

New fungal species are increasingly reported in immunocompromised patients. Saprochaete clavata (S. clavata), an ascomycetous fungus formerly called Geotrichum clavatum, is intrinsically resistant to echinocandins and is often misidentified.

Objective

We describe a cluster of seven S. clavata infections in hospitalized hematology patients who developed this rare fungemia within a span of 11 months. Three of the seven patients died. Identification of the isolates was determined only with the Saramis database of VitekMS system and sequencing of the internal transcribed spacer (ITS) region. Clonal relatedness of the isolates was determined by matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF) analysis; clonal correlation between the strains was investigated by means of phylogenetic analysis, based on single-nucleotide variants (SNPs). Clinical presentation, 1–3 β-D-glucan (BG) and galactomannan (GM) antigen results and analysis of possible sources of contamination are also described with a prospective case–control study of the outbreak.

Results

MALDI-TOF MS-Vitek (bioMerieux, Marcy l’Etoile, France) failed to identify the six isolates, while SARAMIS (bioMerieux, Marcy l’Etoile, France) identified the isolates as S. clavata. Initially, Vitek 2 identified the strains as Geotrichum capitatum in two of the seven cases. Molecular identification gave 99% homology with S. clavata. BG was positive in three out of six patients (range 159 to >523 pg/ml), GM results were always negative. All the isolates were resistant to echinocandins (anidulafungin, micafungin, and caspofungin) and Fluconazole, but susceptible to Flucytosine and Voriconazole. One isolate showed acquired resistance to Flucytosine and Amphotericin B during treatment. Both the correlation-based dendrograms obtained by MALDI-TOF MS (Bruker Daltonics) and MS-Vitek not only clustered six of the seven bloodstream infection (BSI) isolates in the same group, but also showed their strong relatedness. Phylogenetic analysis using SNPrelate showed that the seven samples recorded during the investigation period clustered together. We observed a split between one case and the remainder with a node supported by a z-score of 2.3 (p-value = 0.021) and 16 mutations unique to each branch.

Conclusion

The use of proteomics for identification and evaluation of strain clonality in outbreaks of rare pathogens is a promising alternative to laborious and time-consuming molecular methods, even if molecular whole-genome sequencing (WGS) typing will still remain the reference method for rare emergent pathogens.

Machine Learning Approach for Candida albicans Fluconazole Resistance Detection Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Candida albicans causes life-threatening systemic infections in immunosuppressed patients. These infections are commonly treated with fluconazole, an antifungal agent targeting the ergosterol biosynthesis pathway. Current Antifungal Susceptibility Testing (AFST) methods are time-consuming and are often subjective. Moreover, they cannot reliably detect the tolerance phenomenon, a breeding ground for the resistance. An alternative to the classical AFST methods could use Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) Mass spectrometry (MS). This tool, already used in clinical microbiology for microbial species identification, has already offered promising results to detect antifungal resistance on non-azole tolerant yeasts. Here, we propose a machine-learning approach, adapted to MALDI-TOF MS data, to qualitatively detect fluconazole resistance in the azole tolerant species C. albicans. MALDI-TOF MS spectra were acquired from 33 C. albicans clinical strains isolated from 15 patients. Those strains were exposed for 3 h to 3 fluconazole concentrations (256, 16, 0 μg/mL) and with (5 μg/mL) or without cyclosporin A, an azole tolerance inhibitor, leading to six different experimental conditions. We then optimized a protein extraction protocol allowing the acquisition of high-quality spectra, which were further filtered through two quality controls. The first one consisted of discarding not identified spectra and the second one selected only the most similar spectra among replicates. Quality-controlled spectra were divided into six sets, following the sample preparation's protocols. Each set was then processed through an R based script using pre-defined housekeeping peaks allowing peak spectra positioning. Finally, 32 machine-learning algorithms applied on the six sets of spectra were compared, leading to 192 different pipelines of analysis. We selected the most robust pipeline with the best accuracy. This LDA model applied to the samples prepared in presence of tolerance inhibitor but in absence of fluconazole reached a specificity of 88.89% and a sensitivity of 83.33%, leading to an overall accuracy of 85.71%. Overall, this work demonstrated that combining MALDI-TOF MS and machine-learning could represent an innovative mycology diagnostic tool.

Molecular Typing of Candida glabrata

The yeast Candida glabrata has emerged, second only to Candida albicans, to be one of the most frequently isolated fungi in clinical specimen from human. Its frequent resistance towards azole antifungal drugs and the high capacity to form biofilms on indwelling catheters of individual isolates render it an often difficult to treat pathogen. Hence, there is a notably increasing scientific and clinical interest in this species. This has led to the development of a variety of molecular tools for genetic modification, strain collections, and last but not least different approaches to analyse the population structure among isolates of different geographical and clinical contexts. Often, these are used to study correlations (or the absence thereof) with different pathogenicity, virulence, or drug resistance traits. Three molecular methods have been used to type within the C. glabrata population on a genetic level by multiple studies: multi-locus sequence typing, microsatellite length polymorphisms, and clustering of whole-genome sequencing data, and these are subject of this review.

BIOF-HILO Assay: A New MALDI-TOF Mass Spectrometry Based Method for Discriminating Between High- and Low-Biofilm-Producing Candida parapsilosis Isolates

Candida parapsilosis is the most frequent cause of catheter-related candidemia among non-Candida albicans species. This may be related to intrinsic capabilities as adhering and forming a biofilm on abiotic surfaces such as on medical devices. As previously demonstrated, patients infected with high biofilm-producing C. parapsilosis isolates had a greater mortality risk compared to patients infected with low biofilm-producing C. parapsilosis isolates. We developed the BIOF–HILO assay, a MALDI–TOF mass spectrometry (MS)-based assay, which compares mass spectra obtained from attached and suspended isolate cells during the early (i.e., 3-h) adhesion phase of in vitro biofilm formation. The composite correlation index (CCI) analysis was used to discriminate between mass spectra differences of the two cell types, classifying all 50 C. parapsilosis clinical isolates, included in the study, after only 3-h of testing, in high or low biofilm producers. All high (n = 25) or low (n = 25) biofilm producers had, according to CCI mass spectra comparison values, higher or lower than one CCI ratios, which were obtained by dividing the CCI_{suspended cells} by the CCI_{attached cells}. In conclusion, the BIOF–HILO assay allows a rapid categorization of C. parapsilosis clinical isolates in high or low biofilm producers. This information, if timely provided to physicians, may improve treatment outcomes in patients with C. parapsilosis candidemia.

Microsatellite Typing and Antifungal Susceptibility of Candida glabrata Strains Isolated From Patients With Candida Vaginitis

Vulvovaginal candidiasis (VVC) is a yeast infection with a global reach and millions of dollars are spent annually for its diagnosis and treatment. Recently, Candida glabrata with different degrees of antifungal resistance has been considered as the second most common cause of vaginal infections. The aim of the present study is to determine the antifungal susceptibility and molecular epidemiology profiles of C. glabrata isolates from patients with VVC. Sixty-one C. glabrata isolates were examined for antifungal susceptibility using the EUCAST broth microdilution method. Moreover, microsatellite length polymorphism (MLP) was used for typing the C. glabrata isolates using six microsatellite markers. Overall, 13, 3.3, and 0% of the isolates were non-wild types to itraconazole, posaconazole, and voriconazole, respectively. Sixty (98.4%) isolates were an intermediate phenotype to fluconazole and only one isolate was fluconazole resistant. Microsatellite length polymorphism with a discriminatory power of 0.964 identified 35 distinct types and 24 singleton genotypes. The assessment of the population genetic structure revealed that the non-wild-type population had a moderate genetic differentiation compared to the wild type population (F_ST = 0.1457). It was also found that the most common genotypes were G27 (eight strains), G12 (six strains), and G4 (five strains). We found that eight strains were resistant/a non-wild phenotype to itraconazole. Five out of eight (62.5%) resistant/non-wild phenotype strains correlated to a predominant genotype (GT27) and the rest belonged to GT11 (12.5%), GT29 (12.5%), and GT28 (12.5%). The current study is the first molecular epidemiology study in the southwest of Iran and demonstrates the antifungal susceptibility profiles of C. glabrata in it. This study shows a wide range of the genetic diversity of C. glabrata (35 different genotypes) from VVC in the southwest of Iran. The majority of the non-wild isolates had a dominant genotype or genotypes related to this dominant genotype (clonal cluster one).

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

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.

Candida tropicalis geographic population structure maintenance and dispersion in the coastal environment may be influenced by the climatic season and anthropogenic action

Candida tropicalis is a pathogenic yeast with worldwide recognition as the second or third more frequently isolated species in Latin America, for both superficial and systemic infections. Because of its high prevalence, and growing clinical interest, it is essential to understand genetic variability patterns of this important Candida species in the tropics. Besides belonging to the human normal microbiota, C. tropicalis may be found in other warm blood animals and in the environment, including water and sand of beaches. The aims of the present study were to evaluate genotypic and phenotypic variability of 62 isolates of C. tropicalis obtained from the coastal environment in Northeast Brazil using microsatellite and MALDI-TOF/MS comparisons. There was a relatively low correspondence between these typing techniques employed. Therefore, further studies are needed to consolidate the use of MALDI-TOF/MS as a yeast typing tool. Nevertheless, the two methods employed demonstrated the heterogeneity of C. tropicalis in a coastal environment. We also found relative maintenance of the population structure within the same season, which may reinforce the idea that this species presents the potential to remain in the environment for a long period of time. In addition, highly related strains were found within different geographic points of collection, demonstrating that this strain may be dispersed at long distances, probably influenced by anthropogenic actions and driven by the sea tides and wind.

Genotyping of clinical isolates of Candida glabrata from Iran by multilocus sequence typing and determination of population structure and drug resistance profile

Candida glabrata is often the second most common causative agent for candidiasis following Candida albicans. Despite the importance of C. glabrata infections, few epidemiological studies have been conducted on this issue. The goal of this study was genotyping of clinical isolates of C. glabrata by multilocus sequence typing (MLST) technique for determination of the endemic prevalent genotypes and any association between isolation source and drug resistance. A total of 50 C. glabrata clinical isolates from Iran were analyzed by MLST and tested for in-vitro susceptibilities to amphotericin-B, caspofungin, fluconazole, and voriconazole according to the Clinical Laboratory Standards Institute (CLSI) M27-A4 document guidelines. Among these isolates, 16 distinct STs were identified, indicating a discriminatory power index of 0.9029. The three major sequence types (STs) were ST-59, ST-74, and ST-7 with 10, 8, and 7 isolates, respectively. Furthermore, a total of 11 new sequences were found, to which no allele numbers were assigned in the MLST database. All the isolates were susceptible to amphotericin B and caspofungin. Fluconazole resistance was shown in four isolates. Also, a sole isolate was voriconazole resistant. This study shows that the population structure of C. glabrata in Iran consists of groups closely related to the global database as well as to some new clonal clusters and STs. Regarding the high prevalence of 11 new sequences found in this study, it can be concluded that, these new alleles are among the endemic genotypes of Iran. The genotypes or STs were independent of drug susceptibility and anatomic sources.

Molecular Epidemiology and Antifungal Susceptibility of Candida glabrata in China (August 2009 to July 2014): A Multi-Center Study

Candida glabrata is an increasingly important cause of invasive candidiasis. In China, relatively little is known of the molecular epidemiology of C. glabrata and of its antifungal susceptibility patterns. Here we studied 411 non-duplicate C. glabrata isolates from 411 patients at 11 hospitals participating in the National China Hospital Invasive Fungal Surveillance Net program (CHIF-NET; 2010-2014). Genotyping was performed using multilocus sequence typing (MLST) employing six genetic loci and by microsatellite analysis. Antifungal susceptibility testing was performed using Sensititre YeastOne™ YO10 methodology. Of 411 isolates, 35 sequence types (ST) were identified by MLST and 79 different genotypes by microsatellite typing; the latter had higher discriminatory power than MLST in the molecular typing of C. glabrata. Using MLST, ST7 and ST3 were the most common STs (66.4 and 9.5% of all isolates, respectively) with 24 novel STs identified; the most common microsatellite types were T25 (30.4% of all isolates) and T31 (12.4%). Resistance to fluconazole (MIC > 32 μg/mL) was seen in 16.5% (68/411) of isolates whilst MICs of >0.5 μg/mL for voriconazole, >2 μg/mL for itraconazole and >2 μg/mL for posaconazole were seen for 28.7, 6.8, and 7.3% of isolates, respectively; 14.8% of all isolates cross-resistant/non-wide-type to fluconazole and voriconazole. Fluconazole resistant rates increased 3-fold over the 5-year period whilst that of isolates with non-WT MICs to voriconazole, 7-fold. All echinocandins exhibited >99% susceptibility rates against all isolates but notably one isolate exhibited multi-drug resistance to the azoles and echinocandins. The study has provided a global picture of the molecular epidemiology and drug resistance rates of C. glabrata in China during the period of the study.

Opportunistic fungal pathogen Candida glabrata circulates between humans and yellow-legged gulls

The opportunistic pathogenic yeast Candida glabrata is a component of the mycobiota of both humans and yellow-legged gulls that is prone to develop fluconazole resistance. Whether gulls are a reservoir of the yeast and facilitate the dissemination of human C. glabrata strains remains an open question. In this study, MLVA genotyping highlighted the lack of genetic structure of 190 C. glabrata strains isolated from either patients in three hospitals or fecal samples collected from gull breeding colonies located in five distinct areas along the French Mediterranean littoral. Fluconazole-resistant isolates were evenly distributed between both gull and human populations. These findings demonstrate that gulls are a reservoir of this species and facilitate the diffusion of C. glabrata and indirect transmission to human or animal hosts via environmental contamination. This eco-epidemiological view, which can be applied to other vertebrate host species, broadens our perspective regarding the reservoirs and dissemination patterns of antifungal-resistant human pathogenic yeast.

Evidence of genotypic diversity among Candida auris isolates by multilocus sequence typing, matrix-assisted laser desorption ionization time-of-flight mass spectrometry and amplified fragment length polymorphism

Candida auris is a multidrug-resistant nosocomial bloodstream pathogen that has been reported from Asian countries and South Africa. Herein, we studied the population structure and genetic relatedness among 104 global C. auris isolates from India, South Africa and Brazil using multilocus sequence typing (MLST), amplified fragment length polymorphism (AFLP) fingerprinting and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). RPB1, RPB2 and internal transcribed spacer (ITS) and D1/D2 regions of the ribosomal DNA were sequenced for MLST. Further, genetic variation and proteomic assessment was carried out using AFLP and MALDI-TOF MS, respectively. Both MLST and AFLP typing clearly demarcated two major clusters comprising Indian and Brazilian isolates. However, the South African isolates were randomly distributed, suggesting different genotypes. MALDI-TOF MS spectral profiling also revealed evidence of geographical clustering but did not correlate fully with the genotyping methods. Notably, overall the population structure of C. auris showed evidence of geographical clustering by all the three techniques analysed. Antifungal susceptibility testing by the CLSI microbroth dilution method revealed that fluconazole had limited activity against 87% of isolates (MIC90, 64 mg/L). Also, MIC90 of AMB was 4 mg/L. Candida auris is emerging as an important yeast pathogen globally and requires reproducible laboratory methods for identification and typing. Evaluation of MALDI-TOF MS as a typing method for this yeast is warranted.

Pushing the Limits of MALDI-TOF Mass Spectrometry: Beyond Fungal Species Identification

Matrix assisted laser desorption ionization time of flight (MALDI-TOF) is a powerful analytical tool that has revolutionized microbial identification. Routinely used for bacterial identification, MALDI-TOF has recently been applied to both yeast and filamentous fungi, confirming its pivotal role in the rapid and reliable diagnosis of infections. Subspecies-level identification holds an important role in epidemiological investigations aimed at tracing virulent or drug resistant clones. This review focuses on present and future applications of this versatile tool in the clinical mycology laboratory.