Investigation of multi-drug resistant Candida

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Introduction

Out of almost 300 species in the genus Candida, several are known to be associated with humans, causing infections primarily in immuno-compromised persons [1]. These infections contribute significantly to morbidity and mortality, particularly in immunocompromised and long-term hospitalized patients. Candida exhibits virulence that enables it to infect individuals across all age groups, with infection ranging from moderate to severe. The overuse of broad-spectrum antibiotics has further exacerbated resistance among non-albicans species. Despite advancements in medical diagnostics and treatment, fungal infections remain challenging to diagnose and cure [2].

Candida albicans typically colonizes various anatomical sites without causing harm. However, environmental changes can lead to mucosal to invasive systemic infections, resulting in damage mediated by the host and the pathogen [3]. While C. albicans is the most frequent cause of yeast infections, other species such as C. glabrata, C. tropicalis, C. krusei, and C. dubliniensis are increasingly prevalent. Recently Candida auris has emerged as a significant fungal pathogen, characterized by multidrug resistance and ability to cause nosocomial infections globally [4–5].

It is estimated that over 1/3 of patients with invasive C. auris infections, such as those affecting the bloodstream, heart, or brain, succumb to the disease. During the COVID-19 pandemic, the Pan American Health Organization (PAHO) World Health Organization (WHO) issued an epidemiological alert on February 6, 2021, highlighting outbreaks of C. auris, particularly among ICU patients, who are at the highest risk [6]. By late 2020, seven countries, including Italy, the United States and in Latin America, reported cases of C. auris in patients affected by COVID-19 [7].

Candida auris was first identified in 2009 in Japan through ribosomal DNA (rDNA) sequencing from a patient’s ear. Retrospective analyses revealed its presence as early as 1996 in bloodstream infections in South Korea [8]. In 2014, an outbreak at Aga Khan University Hospital in Karachi, Pakistan, initially misidentified as Saccharomyces cerevisiae, was later confirmed as C. auris due to its unique antifungal resistance pattern. Subsequent reports from Venezuela, South Africa, India and United States have drawn significant attention [9–10].

The Quetta city lies in the under developed region (Balochistan) of Pakistan where the situation is compounded due both to inadequate diagnostic facilities and management of Candida infection, especially emerging novel C. auris. Despite the critical need for regional data, no prior studies have systematically assessed the occurrence of C. auris in this region, particularly among hospitalized immunocompromised patients. This research study aims to provide a comprehensive and accurate framework for identifying C. auris and other Candida spp. addressing diagnostic challenges employing a combination of traditional and advanced diagnostics techniques. The focus is on delivering a reliable approach for the identification of these species in immunocompromised patients at a tertiary care hospital in Quetta, Pakistan.

The pathogen C. auris demonstrates resistance to multiple antifungal drugs, with over 90% resistance to fluconazole and 73% resistance to Voriconazole. Although some strains show resistance to amphotericin B, echinocandins remain the most effective treatment. The pathogen is also challenging to identify using traditional methods, often leading to underreporting. Phylogenetic analyses suggest that C. auris originated independently in four regions: South Asia, East Asia, Africa, and South America [10].

Yeast identification commonly relies on morphological, biochemical and molecular characteristics [11]. Morphological methods include observation of budding cells, hyphal development, germ tube formation and colony features [12–13]. Chromogenic media, such as Brilliance CHROMagar, enable species differentiation through characteristics colony coloration [14]. Molecular diagnostics, particularly DNA-based techniques, provide precise and rapid identification, notably for species like C. auris [14–16]. PCR amplification of ITS regions using universal primers (e.g., ITS1–4) are effective for almost all fungal genera including Candida spp. Techniques such as PCR-RFLP and species specific primers targeting genes such as topoisomerase II, phospholipase (PLB), and Candida Drug Resistant (CDR) genes further enhance identification accuracy have been effective for the detection of Candida species [14,17–29]. Clinical laboratories may misidentify C. auris as other species such as C. kefyr, C. famata or C. haemulonii, using manual and automated commercial technologies based on phenotypic and biochemical features including Vitek 2, Phoenix, API 20C, and MicroScan, resulting in inadequate management of yeast infections [25–27].

On the other hand, specific primers which can amplify DNA fragments from genomic and hybrid DNA ensuring rapid and targeted species-level identification of Candida species [25,28–34]. The PLB gene known for its diversity, is particularly recommended for primer design due to its role in pathogenicity [35–38]. DNA topoisomerases are enzymes that facilitate topological alterations in DNA by transiently cleaving and reconnecting double-stranded DNA. The DNA topoisomerase II cleave and ligate both strands of DNA to alleviate supercoiling. The genes of such enzymes are strong enough targets for phylogenetic research and the identification of fungal species [39–40]. Similarly, CDR (Candida Drug Resistance) genes like CDR1–5 that facilitate efflux via ATP-binding cassette (ABC) transporters, a key mechanism in antifungal resistance, against azoles, and other potential drugs such as polyenes and echinocandins as compared to other genes, makes it a very potential gene for the targeted identification of C. auris and other Candida species [40–46].

Recent therapeutic advancements emphasize echinocandins and broad-spectrum azoles for managing candidemia, invasive candidiasis, and mucosal infections. Fluconazole, initiated with an 800mg loading dose followed by 400mg daily for at least 14 days after a negative blood culture, remains the standard treatment for most Candida infections [47–48]. Other antifungals, such as boric acid, nystatin, and flucytosine are used for specific cases including intravaginal applications. Amphotericin B is reserved for severe cases, such as oral thrush in HIV patients [49–50].

Materials and methods

Ethical approval of research study

This study was conducted with approval from the Institutional Review Board (IRB) approval under the protocol titled “Prevalence, analysis and molecular diagnosis of newly emerging multidrug resistant human pathogenic Candida auris in the population of Quetta”. Written informed consent was obtained from patients or their guardians using standardized consent forms, permitting sample collection for research purposes. Socio-demographic data were collected through a structured questionnaire which included personal information (bed number, ward, duration of admission etc.), clinical symptoms, comorbidities, ongoing treatments, and medication.

Study design

The study design involved the collection of clinical samples, followed by culture testing. An overview of the study design is illustrated in Fig 1. All cultures with growth were sequentially analyzed to differentiate yeast species using two chromogenic media. Identification was further confirmed through PCR amplification of ITS regions using universal primers (ITS1&4, ITS 1&2, and ITS3&4) followed by DNA sequencing. Additional techniques included PCR-restriction length polymorphism (PCR-RFLP) assays using the Msp1 restriction enzyme, MALDI-TOF analysis, Vitek 2 system, and species-specific primers targeting genes such as Phospholipase B (PLB), Candida Drug Resistance (CDR), Topoisomerase II, and 18S genes. The cultures of Candida auris were also tested for growth on salt Sabouroud agar (SDA), corn meal agar (CMA) and using salt Dulcitol Test. Identified yeast species underwent phylogenetic and statistical analysis. Antifungal susceptibility was assessed against fluconazole, amphotericin B and voriconazole.

[Figure omitted. See PDF.]

Sample collection

This study focused on immunocompromised patients admitted to the Special Care Units (SCU) and Intensive Care Units (ICU) of Fatima Jinnah Chest Hospital in Quetta, Pakistan. Patients were selected based on their clinical indicative presentation of symptoms (fever, chest infection, cough, ear infection etc.), indicative of yeast infections (comorbidities and treatment taken), hospital stay for (≥2 days), and their critical medical condition requiring specialized care. Samples were collected from multiple body sites (ear, axilla groin, oral cavities, etc.), as Candida auris is known to colonize various anatomical locations. From 21/10/2022 till 20/10/2023, swab samples were obtained from 150 immunocompromised patients admitted to ICU and SCU Fatima Jinnah Chest Hospital, Quetta, Pakistan. Each patient provided samples from the ear axilla, groin and saliva/sputum, regardless of age and gender.

For comparison, 100 swab samples from the ear, axilla and saliva were collected from healthy individuals, the comprehensive sampling strategy was implemented to capture colonization patterns and align with the study’s objectives of investigating C. auris prevalence, distribution and colonization across different body sites.

Culture testing and yeast identification

Culture test was conducted on Yeast-Mold (YM) Agar medium, prepared using glucose (10 g), peptone (5 g), malt extract (3 g), yeast extract (3 g), and agar (20 g), these components were purchased separately and combined to prepare the medium. Swab samples were initially inoculated into pre-prepared YM Broth in glass culture tubes, incubated at 37 °C for 24–48 hours and subsequently transferred to YM agar plates using a sterile wire loop. Saliva/sputum samples were directly streaked onto YM agar plates and incubated at 37 °C for 24–48 hours, and subsequently transferred to YM agar plates under the same conditions.

Yeast growth was confirmed microscopically by preparing slides and observing the cells at 100× magnification using compound light microscope (Optika Microscopes, Italy) connected to a PC tablet [1].

Chromogenic media identification

To differentiate yeast species, two chromogenic media were used such as, Brilliance CHROMagar (BCA) (OXOID) and CHROMagar Candida Plus (CCP) (CHROMagar^TM) which is considered as an advanced medium with enhanced accuracy in distinguishing Candida spp. as described by [51]. All yeast species are identified based on colony color and appearance.

Specific testing for Candida auris

Suspected C. auris isolates were grown on cornmeal agar as C. auris does not produce pseudohyphea [52]. To access its high salt and temperature resistance, isolates were tested on Salt Dulcitol test [53] and Salt Sabouroud test [54]. Due to the limitations of conventional methods, time consuming and less reliable, molecular techniques were employed for rapid and accurate identification. These techniques allowed for the precise validation of Candida species, particularly C. auris.

Molecular characterization

The molecular characterization of isolated and purified yeast cultures was performed using PCR amplification. Three sets of universal ITS primers (ITS1&4, ITS1&2, ITS3&4) and species-specific primers targeting Phospholipase, Topoisomerase, CDR and 18S genes were employed. Species identification was validated through DNA sequencing of PCR products and PCR-Restriction Fragment Length Polymorphism (RFLP) assay using Msp1 Restriction enzyme [55]. Species-specific primers were designed using Primer3 software and optimized through in-silico PCR.

DNA extraction and primer preparation

DNA was extracted using cetyl trimethyl ammonium bromide (CTAB) method and the quality was accessed via 1% gel electrophoresis. 20 µl of PCR reaction mix was prepared including 1.5 µl of each reverse and forward primers, 2µl template DNA. PCR reaction consisted of initial denaturation (95 °C for 6 mins), 40 cycles of cyclic temperatures included denaturation at 95°C for 40sec, annealing temperature (with respect to primers) for 40 sec and 72 °C for 1 min (extension) with a final extension at 72 °C for 5 min. The annealing temperatures for primers pairs ITS1&4, ITS1&2 and ITS 3&4 primers were, and respectively. Whereas the annealing temperatures for species-specific primers are summarized in Table 1.

[Figure omitted. See PDF.]

Yeast identification using VITEK and MALDI-TOF

The automated VITEK 2 Compact (bioMérieux, France) and MALDI-TOF mass spectrometry (Bruker Daltonics, Germany) were used to carry out phenotypic and biochemical identification of the yeast isolates that were selected for the investigation. All isolates were first cultured on YM Agar and incubated for 24–48 hours at 37 °C to ensure pure and viable colonies. A single colony from each culture was suspended in sterile saline to reach a turbidity of 0.5 McFarland for Vitek analysis. The Vitek 2 yeast identification cards (YST ID cards), which included pre-defined biochemical substrates, were loaded with the produced solutions. The technology provided species-level identification via database matching by automatically recording and analyzing metabolic profiles.

Each isolate was identified using MALDI-TOF by spotting one colony onto a target plate. One microlitre of matrix solution (α-cyano-4-hydroxycinnamic acid in 50% acetonitrile and 2.5% trifluoroacetic acid) was applied to the samples, and they were then left to air dry. After that, the target plate was put into the MALDI Biotyper apparatus. Protein mass fingerprinting was used to create spectral profiles, which were then matched to reference databases to identify species.

Antifungal susceptibility testing

Antifungal susceptibility testing was performed using the disk diffusion method also known as Kirby-Bauer test, a standardized approach for evaluating antifungal resistance. This method involves placing paper disks impregnated with specific antifungal agents on agar plates inoculated with yeast cultures. As the antifungal agent diffuses during incubation, it creates a concentration gradient, resulting in zone of inhibition where fungal growth is suppressed. These zones of inhibition were measured and compared to standardized guidelines (CLSI) to determine antifungal susceptibility, i.e., susceptible, intermediate, or resistant (Table 2). Eleven Candida species were tested against fluconazole (5–25 µg/ml), amphotericin B (0.5–4 µg/ml), and voriconazole (0.5–4 µg/ml). Samples were first incubated in YM broth for 24 hours in a shaking incubator, diluted tenfold, and then inoculated onto YM agar plates using spread plate method. For each Candida species, 12 plates were prepared three controls and three replicates for each antifungal agent. Five sterilized disks with specific drug concentrations were placed on each plate, which were incubated for 37 °C for 48 hours. The inhibition zones were measured in millimeters (mm) to access the antifungal susceptibility of the isolates.

[Figure omitted. See PDF.]

Statistical analysis

The clinical data obtained from patients and the identification of yeasts species were statistically analyzed to access the significance of the results and to explore relationships between various variables using IBM SPSS 22. The frequency distribution of identified yeast species was calculated through crosstab analysis, Binary and multinomial logistic regression analyses were performed to examine the relationships between the dependent variable (yeast infection) and independent variables, including age gender, ward type, sample type, health disorders and symptoms. In multinomial regression the yeast species identified using ITS technique were selected as dependent variable with C. albicans as the reference category.

Results

Description of samples

The demographic and clinical characteristics of the patients, including gender, age, ward type, sample type, health disorders and symptoms were documented and summarized in Table 3, presented as numbers and percentages.

[Figure omitted. See PDF.]

Morphological grouping of fungal cultures

Out of 600 samples collected from axilla, ear, groin and saliva of 150 patients, 256 samples tested positive for yeast on YM agar medium. The highest occurrence was observed in saliva samples (107/150), followed by ear (72/150), axilla (42/150) and groin (35/150). Morphological characteristics of yeast cultures were accessed both macroscopically and microscopically. Most colonies exhibited a glossy surface with smooth margins, and their colors varied from white to cream and pink after incubation after 48 hours of incubation at 37°C on YM agar.

Some samples indicated mixed yeast infection. Microscopically, most yeast cultures displayed round, spherical, or oval cells, while others produced filamentous structures such as hyphae or pseudohyphea. In contrast, 19 yeast cultures were isolated identified from 100 healthy individuals. Among these, 16 cultures produced white or cream-colored colonies and 3 yielded pink yeast colonies.

Candida species identification on chromogenic media

All yeast cultures producing white or cream-colored colonies on YM agar medium were further tested using two different chromogenic media which revealed distinct colony colors and morphologies. Based on the colony appearances on BCA and CCP, these cultures were classified into seven different Candida species. The sensitivity and specificity of the chromogenic media were particularly high for identifying C. tropicalis and C. albicans as illustrated in Fig 2.

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Molecular characterization of yeast species

The molecular characterization of all isolated yeasts species was conducted using molecular identification and validation techniques. Yeast cultures were identified through PCR amplification of their Internally Transcribed Spacer (ITS) regions, employing three different primers sets: ITS1&4, ITS1&2, and ITS3&4. The results were validated through Restriction Fragment Length Polymorphism (RFLP) assay using MspI restriction enzyme. Further validation included PCR amplification with species-specific primers designed for various Candida species, targeting such as Phospholipase B (PLB), Topoisomerase-II (TOP), Candida Drug Resistance (CDR), and 18S. Additionally DNA sequencing and phylogenetic analysis were performed to confirm species identification.

Identification through PCR amplification of ITS regions.

The standard PCR amplification technique was used to amplify the Internal Transcribed Spacer (ITS) regions of each yeast culture, employing three different sets of primers: ITS1&4, ITS1&2 and ITS3&4. The number of identified species in total number of participants is summarized in Table 4.

[Figure omitted. See PDF.]

The sizes of their PCR amplified products obtained using the ITS1&4, ITS1&2 and ITS3&4 primers are summarized in Table 5. The visualized PCR products of ITS1&4 are illustrated in Figs 3 and 4, while those amplified with ITS1&2 and ITS3&4 primers are illustrated in Figs 5 and 6, respectively.

[Figure omitted. See PDF.]

CAU= Candida auris (267 bp), CA= C. albicans (328 bp), and CT=C. tropicalis (329 bp), CD= C. dubliniensis (343 bp), CP= C. parapsilosis (311 bp), CF= C. famata (381 bp), CKE= C. kefyr (432 bp) CG= C. glabrata (419 bp), CF= C. famata (381 bp), RM= Rhodotorulla mucilaginosa (404 bp) CN= Cryptococcus neoformans (373 bp) CL= C. lusitaniae (255 bp) as compared to 100 bp DNA ladder (9).

Validation through restriction fragment length polymorphism (RFLP).

PCR-based identification of Candida species was further validated using the Restriction enzyme Msp1 to Perform Restriction Fragment Length Polymorphism (RFLP) analysis. Band sizes were determined by downloading the reference sequences from NCBI and performing in silico digestion of nucleotide sequences using NEB cutter software. This allowed the calculation of DNA digestion products generated by the Msp1 enzyme. The sizes of PCR products and their corresponding digested fragments are summarized in Table 6 (Figs 7–9).

[Figure omitted. See PDF.]

1= Candida tropicalis (340,186 bp), 2, 12, 13= C. glabrata (320, 561 bp), 3, 9, 11= C. kefyr (771 bp), 4= C. parapsilosis (530 bp), 5= C. dubliniensis (340,200 bp), 6= C. dubliniensis (340, 200 bp), 7= Meyerozyma guilliermondii (82, 155, 370 bp) 8= C. lusitaniae (250,120 bp), and as compared to 100 bp DNA ladder (7).

[Figure omitted. See PDF.]

Using Msp1 restriction enzyme, CL= Candida lusitaniae (267,116 bp), CF= C. famata (381 bp), CP= C. parapsilosis (520 bp), CN= Cryptococcus neoformans (239,298 bp) 100 bp DNA ladder and N = Negative Control.

[Figure omitted. See PDF.]

Validation through species-specific primers

Phospholipase-B (PLB) gene.

The identification of all yeast species was further validated using species-specific primers. DNA sequences in FASTA format for the Phospholipase B (PLB) gene, Topoisomerase-II and Candida Drug Resistance genes were retrieved from NCBI, and primers were designed using Primer 3 online software. Species-specific primers for the Phospholipase B gene successfully identified Candida albicans, C. dubliniensis, C. tropicalis, C. glabrata, and C. lusitaniae. The amplified PCR bands were observed at 164 bp, 225 bp, 160 bp, 177 bp, 234 bp, and 230 bp corresponding to C. albicans, C. dubliniensis, C. glabrata, C. lusitaniae, C. parapsilosis and C. tropicalis, respectively (Figs 10–12).

[Figure omitted. See PDF.]

Topoisomerase II (Top) gene.

The identification of Candida auris (Fig 12), C. glabrata, C. lusitaniae and C. tropicalis, was further validated using species-specific primers targeting the Topoisomerase-II gene. The amplified PCR bands for these Candida species were observed at 209 bp, 219 bp, 220 bp and 160 bp, respectively (Fig 13).

[Figure omitted. See PDF.]

= C. lusitaniae (219 bp), CP(TOP) = C. parapsilosis (220 bp), CG(TOP) = C. glabrata (160 bp); CDR gene: CD(CDR)= C. dubliniensis (241 bp), CT(CDR)= C. tropicalis (163 bp), CP(CDR)= C. parapsilosis (221 bp), CG(CDR)= C. glabrata (188 bp); and D=100 bp ladder.

Candida Drug Resistance (CDR) gene.

The identification of Candida auris (Fig 12), C. dubliniensis, C. glabrata, C. parapsilosis and C. tropicalis was also validated using species-specific primers targeting CDR gene. The amplified PCR bands were observed at 164 bp, 241 bp, 188 bp, 221 bp and 163 bp, respectively. These bands correspond to C. glabrata, C. lusitaniae, and C. parapsilosis (Fig 13).

18S gene.

Species-specific primers targeting the 18S gene successfully amplified a PCR product of 167 bp, confirming the identification of Candida auris (Fig 12).

DNA sequencing and analysis of human pathogenic yeasts.

The ITS regions of all human pathogenic yeasts, visualized during PCR amplification and gel electrophoresis using universal primers, were sequenced. The obtained sequences of all yeast species were subjected to BLAST analysis against NCBI reference sequences, ITS, and non-redundant nucleotide databases. Based on BLAST search results, twelve (12) yeast species were identified: Candida albicans, C. auris, C. dubliniensis, C. glabrata, C. guilliermondii, C. lusitaniae, C. kefyr, C. krusei, C. parapsilosis, C. tropicalis, and Cryptococcus neoformans. All the Sequences were submitted to NCBI and accession numbers for each species listed in Table 7.

[Figure omitted. See PDF.]

The aligned sequences were downloaded in FASTA format and further processed in MEGA software alongside the query sequences. Phylogenetic trees were constructed using Maximum Likelihood Model, enabling the identification of yeast species based on sequence homology (Fig 14).

[Figure omitted. See PDF.]

Validation of yeasts identification through MALDI-TOF.

The validation process, conducted using VITEK and MALDI-TOF analyses, successfully confirmed the accurate identification tool, generated detailed biochemical profiles that corresponded to specific yeast species. Similarly, MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time-of-Flight) mass spectrometry produced unique protein spectra, enabling precise identification through characteristic protein signatures. The results from both methods demonstrated strong concordance, emphasizing the reliability of these complementary techniques for yeast identification. This validation underscores their importance in microbiological studies, ensuring consistent and reproducible results across diverse yeast samples.

Statistical analysis

Descriptive crosstab analysis, binary logistic and multinomial logistic regression analyses were applied to evaluate the effects of various variables on the occurrence of different types of yeast infections. The values of key findings are summarized in Table 8.

[Figure omitted. See PDF.]

Crosstab analysis showed a significant relationship between types of yeast species vs. different dependent variable, i.e., age (70–79), ward, gender, health disorders (hypertension and chest infection) and symptoms (ear itching). Analysis through binary logistic regression demonstrated that the model was highly suitable (Nagelkarke, R² value 0.903) where the yeast infection was 90.3% explained by independent variables (age, gender, wards, sample type, health disorder and symptoms).

The model fitting information demonstrated that the multinomial logistic regression model was highly appropriate and effectively explaining the association between yeast infection and the independent variables (χ 536.226, df 360, significance p<0.000). The Goodness of Fit test further validated the model’s suitability, with the Pearson Chi-square value being highly significant (0.000, i.e., >0.05). The R² values for Cox & Snell (0.586) and Nagelkarke (0.613) indicated that the independent variables explained 58.6% and 61.3% of the variance in yeast species identification, respectively as summarized in Table 8 (the details are attached as S1 Data).

Antifungal susceptibility testing (AST)

The antifungal susceptibility of 11 different Candida species was accessed using YM agar. Candida auris exhibited resistance to all three tested antifungal drugs. Among the drugs tested, Fluconazole showed the highest resistance rates, while Amphotericin-B was the most effective against the Candida species. C. albicans and C. krusei demonstrated high susceptibility to all three drugs. Meyerozyma (Candida) guilliermondii was particularly susceptible to Voriconazole, while Amphotericin-B was most effective against C. lusitaniae. C. parapsilosis exhibited susceptibility to all three tested antifungal drugs. A summary of drug resistance pattern is provided in Table 9, and corresponding figures (Figs 15–25) are attached as S2 Data.

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Discussions

Most yeast cultures in this study formed glossy colonies with smooth edges, displaying colors ranging from white to cream and pink after 48 hours of incubation at 37°C on YM agar. Saliva samples yielded the highest number of positive cultures, followed by ear samples [56]. Colonies with white and cream hues were predominantly associated with the Candida genus, prompting further analysis using chromogenic media such as Brilliance Candida Agar (BCA) to differentiate between Candida species [57–58].

BCA effectively identified species such as C. albicans, C. dubliniensis, C. krusei, C. tropicalis, and C. parapsilosis. However, identifying C. auris proved challenging due to its variable colony colors, including beige, cream, and pink. While BCA successfully distinguished C. tropicalis and C. dubliniensis, the differentiation of C. albicans and C. glabrata was less definitive [16,59]. Additionally, some cultures were not identifiable using BCA and CCP, highlighting the limitations of these methods [15,59].

These limitations prompted a shift toward molecular methods for yeast identification. The ITS regions of fungal ribosomal DNA (rDNA), located between the 18S, 5.8S, and 28S coding regions, are commonly used for PCR-based fungal species differentiation. These regions are highly conserved yet evolve slowly, making them ideal targets for identification. Reference sequences for these regions are available in the NCBI database [18,20]. In this study, PCR amplification of the yeast ITS regions was performed using primer ITS1–4, ITS1–2, and ITS3–4 producing fragments between 148 and 872 bp which were visualized on an agarose gel [60]. Further species identification was achieved through species-specific PCR targeting genes such as PLB, Topoisomerase II, CDR, and 18S, along with PCR-RFLP analysis using the MspI enzyme [61]. These techniques provide accessible alternatives for routine diagnostics laboratories that often lack resources for DNA sequencing.

In the RFLP assay using the Msp1 restriction enzyme on ITS PCR-amplified products, 12 species, including Candida albicans, C. dubliniensis, C. krusei, C. glabrata, C. lusitaniae, C. tropicalis, and Cryptococcus neoformans, produced two fragments, while C. guilliermondii yielded three fragments, corroborating prior findings [62]. However, C. auris, C. famata, C. kefyr, and C. parapsilosis did not generate digested products, further confirming earlier reports [63–64].

The Phospholipase-B (PLB) gene, essentials for maintaining membrane stability and nutrient uptake, has fewer variable regions than rRNA genes, making it a reliable marker for accurate species identification [21,37,65]. DNA topoisomerases, which regulate DNA topology, are critical targets for pharmacological intervention. Despite limited research on fungal topoisomerase II, this gene was selected due to its species-specific sequence. [20,34,66,67]. Primers targeting topoisomerase II gene variation were designed for C. auris, C. lusitaniae, C. glabrata, and C. parapsilosis, producing PCR bands of 209 bp, 154 bp, 220 bp, and 219 bp, respectively.

Similarly, Candida Drug Resistance (CDR) genes, primarily studied for their role in antifungal resistance, have been underutilized for species identification. In this study, species-specific primers targeting the CDR1 gene were employed to identify C. auris, C. glabrata, C. dubliniensis, C. parapsilosis, and C. tropicalis, yielding the expected PCR bands of 161 bp, 188 bp, 241 bp, 221 bp, and 163 bp, respectively.

DNA sequencing of the ITS region confirmed the accurate identification of all yeast species analyzed in the study. Genetic relatedness among these species was evaluated by constructing a phylogenetic tree using Maximum Likelihood (ML) analysis in MEGA11 software, based on DNA sequence data obtained through BLAST comparisons [68–72]. The analysis revealed substantial homogeneity among the isolates and identifying 11 species of Candida and one species of pink yeast, comprising C. albicans, C. auris, C. dubliniensis, C. famata, C. glabrata, C. guilliermondii, C. kefyr, C. krusei, C. lusitaniae, C. parapsilosis, C. tropicalis, and Cryptococcus neoformans.

The antifungal susceptibly of these yeast species was accessed using three antifungal agents: fluconazole, amphotericin-B, and voriconazole. Candida auris exhibited resistance to all three agents, with fluconazole showing the highest resistance, while amphotericin-B emerged as the most effective antifungal. C. albicans displayed the greatest susceptibility to all three drugs. Additionally, Meyerozyma (Candida) guilliermondii showed significant susceptibility to voriconazole, and amphotericin-B demonstrated the highest efficacy against C. lusitaniae. Meanwhile, C. parapsilosis was found to be susceptible to all three antifungal agents [73].

Conclusion

This study is the first of its kind in Quetta, Balochistan, to document the presence of Candida auris among immunocompromised patients in special care and intensive care units. The detection of various yeast infections in immunocompromised patients can be enhanced through the application of diverse diagnostic techniques. Using of species-specific primers targeting various genes proved to be a rapid method for identifying the human pathogenic yeasts studied.

Statistical analyses, including crosstab, binary and multinomial logistic regression, revealed significant associations between yeast infection and various factors.

The study also highlighted antifungal resistance in certain Candida species, particularly against fluconazole, whereas amphotericin B was identified as the most effective antifungal agent.

Future research will focus on developing species-specific primers and probes for real-time PCR to target additional genes, thereby improving the identification of Candida auris and other Candida species. Researchers will also explore the role of the Candida drug resistance (CDR1) gene in contributing to drug resistance across various Candida species and antifungal drugs. Furthermore, antifungal susceptibility testing will be expanded to include echinocandin-class medications and other available therapies to identify more effective treatment options.

Limitations of study

“The present study provides significant insights into the prevalence, identification, and antifungal resistance of Candida auris in immunocompromised patients in Quetta, Balochistan; however, certain limitations were identified. The broth microdilution assay could not be employed for antifungal susceptibility testing due to a lack of resources, including specialized equipment, and reagents etc. Additionally, echinocandin drugs were not included in antifungal susceptibility testing due to their unavailability in the region. Limited resources and inadequate funding posed significant challenges to conducting research in this underdeveloped area, hindering access to essential equipment, reagents, and infrastructure necessary for advanced scientific studies.”

Supporting information

S1 Data. Detailed results of statistical analysis.

https://doi.org/10.1371/journal.pone.0319485.s001

(DOCX)

S2 Data. Images of antifungal susceptibility testing.

https://doi.org/10.1371/journal.pone.0319485.s002

(DOCX)

S1 Fig. Raw images.

https://doi.org/10.1371/journal.pone.0319485.s003

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Citation: Ejaz H, Mushtaq M, Khan S, Azim N, Hussain A, Kakar K, et al. (2025) Investigation of multi-drug resistant Candida auris using species-specific molecular markers in immunocompromised patients from a tertiary care hospital in Quetta, Pakistan. PLoS ONE 20(4): e0319485. https://doi.org/10.1371/journal.pone.0319485

About the Authors:

Hira Ejaz

Contributed equally to this work with: Hira Ejaz, Muhammad Mushtaq

Roles: Conceptualization, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

E-mail: [email protected] (HE); [email protected] (MM)

Affiliation: Department of Biotechnology, Faculty of Life Sciences & Informatics (FLS&I), Balochistan University of Information Technology, Engineering and Management Sciences (BUITEMS), Balili, Quetta, Balochistan, Pakistan

Muhammad Mushtaq

Contributed equally to this work with: Hira Ejaz, Muhammad Mushtaq

Roles: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

E-mail: [email protected] (HE); [email protected] (MM)

ORICD: https://orcid.org/0000-0001-7585-2644

Shereen Khan

Roles: Conceptualization, Data curation, Methodology