Genetic diversity and antifungal resistance in Candida albicans from VVC cases in Indian women

Abstract

Background

Vulvovaginal candidiasis (VVC) is a common fungal infection primarily caused by Candida albicans. It is associated with significant morbidity, especially in recurrent cases. Antifungal resistance, particularly to azole drugs, poses a growing challenge in treatment.

Aim

This study investigates the genetic diversity and antifungal resistance patterns of C. albicans isolated from VVC patients.

Method

A total of 170 vaginal swab samples were collected from Indian women attending the obstetrics and gynecology departments at IMS SUM Hospital and Kalinga Hospital, Odisha, India. C. albicans isolates were identified through microscopic analysis, growth on HiCrome™ Candida Differential Agar, germ tube formation tests, and the Vitek2 Compact system. Antifungal susceptibility was determined using the Kirby-Bauer disk diffusion method. Genetic diversity was assessed through Inter-Simple Sequence Repeat (ISSR) and Random Amplified Polymorphic DNA (RAPD) marker techniques. The data were analyzed using dendrograms, genetic similarity matrices, and Principal Component Analysis (PCA).

Results

Out of 170 vaginal swabs, 122 Candida isolates were identified, with 35 confirmed as C. albicans. Eighteen representative C. albicans isolates were analyzed for genetic diversity. Antifungal susceptibility tests revealed that Nystatin showed the highest sensitivity (60%), followed by miconazole (54.29%) and fluconazole (42.86%). In contrast, ketoconazole and voriconazole exhibited the highest resistance rates (60%). Itraconazole and clotrimazole also showed considerable resistance at 51.43% and 48.57%, respectively. Amphotericin B demonstrated moderate efficacy, with 20% sensitivity and a high intermediate response (45.71%). Genetic diversity analysis using ISSR and RAPD markers showed considerable polymorphism, indicating a heterogeneous C. albicans population. Strain S95 exhibited significant genetic divergence compared to other isolates, suggesting unique genetic characteristics. Both dendrograms and PCA identified distinct genetic clusters within the isolates.

Conclusion

The study demonstrates significant genetic variability among C. albicans isolates and widespread antifungal resistance, particularly to azole-based treatments. The results underscore the importance of regular monitoring of genetic diversity and resistance patterns in C. albicans to guide effective treatment strategies for VVC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-025-04256-1.

Introduction

Vulvovaginal candidiasis (VVC) is a widespread fungal infection predominantly caused by Candida (C.) albicans, yeast that normally colonizes mucosal surfaces in healthy women [1–3]. However, it can act as an opportunistic pathogen when the natural balance of the vaginal microbiota is disturbed, leading to infection [4, 5]. While most cases of VVC are easily treated, recurrent infections and antifungal resistance are increasing concerns, particularly in immunocompromised individuals [6, 7]. Understanding the genetic diversity and resistance patterns of C. albicans strains is crucial for developing more effective diagnostic and therapeutic approaches [8].

VVC affects approximately 75% of women at least once in their lifetime, with a significant proportion experiencing recurrent infections [6]. The symptoms, such as itching, burning, and abnormal discharge, can severely affect the quality of life. While most infections are caused by C. albicans, other non-albicans Candida species are also emerging as important etiological agents [9, 10]. Recurrent VVC (RVVC), defined as four or more episodes in a year, presents a greater clinical challenge due to persistent infections and diminished response to standard antifungal treatments [11]. The emergence of antifungal-resistant strains of C. albicans in RVVC cases underscores the need for deeper insights into the genetic characteristics of these pathogens [12].

Antifungal resistance, especially to azoles, is a growing problem in treating VVC [13]. Azoles, including fluconazole and itraconazole, are commonly prescribed, but resistance mechanisms such as efflux pump overexpression, target enzyme mutations, and biofilm formation have been identified in C. albicans [14]. As resistance increases, treatment options become limited, resulting in treatment failure and recurrent infections [15, 16]. The correlation between genetic diversity and antifungal resistance is of particular interest, as it can reveal how C. albicans adapts to environmental pressures, including antifungal drugs [14]. Monitoring genetic variation in clinical isolates helps to track the emergence of resistant strains and guide treatment strategies.

Inter-Simple Sequence Repeat (ISSR) markers are valuable tools for assessing genetic diversity, offering a high level of reproducibility and resolution [17]. These markers amplify regions between inter simple sequence repeats scattered across the genome, allowing researchers to detect polymorphisms in different isolates of C. albicans [18]. Since ISSR does not require prior knowledge of the genome, it provides an efficient and cost-effective way to assess genetic variability in microbial populations [19].

Random Amplified Polymorphic DNA (RAPD) is another molecular technique that enables the study of genetic diversity by amplifying random segments of DNA using short primers [20]. This method detects genetic polymorphisms across the genome and provides insight into the genetic structure of C. albicans populations [21]. RAPD is particularly useful in identifying genetic differences among strains that may contribute to variations in virulence, pathogenicity, and antifungal resistance [22]. Like ISSR, RAPD is highly advantageous because it does not require prior genomic information, making it an accessible tool for screening genetic diversity across multiple isolates.

Genetic diversity within C. albicans populations plays a pivotal role in the pathogen’s adaptability to antifungal drugs and environmental changes [23]. High genetic variability may allow certain strains to acquire or develop resistance mechanisms, leading to treatment failure [24]. The use of ISSR and RAPD markers enables the exploration of genetic distinctions between susceptible and resistant isolates, offering a foundation for predicting the emergence of antifungal-resistant strains [25–28].

Moreover, these genetic studies can help in understanding how environmental factors, such as antibiotic use or immune status, influence the evolution of C. albicans strains. Tracking these changes can also aid in epidemiological surveillance and the development of novel therapeutic interventions those target resistant populations more effectively.

The study aimed to identify and characterize the various Candida species present in clinical samples, with a particular focus on C. albicans, using both conventional and Vitek2 methods. Furthermore, the antifungal susceptibility of these isolates was assessed to determine their resistance profiles against commonly used antifungal agents. To gain insights into the genetic variability among the C. albicans isolates, ISSR and RAPD markers were employed.

Patients and methods

Ethical considerations

The study protocol was approval from the Institutional Ethics Committee, ICMR-RMRC, Bhubaneswar and maintained data confidentiality.

Sample collection

For this study, a total of 170 vaginal swabs were collected from the obstetrics and gynaecology departments of IMS SUM Hospital and Kalinga Hospital in Bhubaneswar, Odisha. These sterile, transportable cotton swabs, were then transfered under aseptic conditions to the RMRC-ICMR laboratory for further analyses.

Identification of C. albicans

The swabs were cultured on Sabouraud Dextrose Agar (SDA) (HiMedia Laboratories, Mumbai, India) to selectively isolate fungal organisms and were incubated at 37 °C for 48 h [29]. The identification of the genus Candida based on a series of tests which include the following:

Microscopic test

The morphology of the yeast cells was analyzed microscopically after being stained using the Gram stain technique to assess their staining reaction, cellular arrangement, and the presence of yeast budding [30].

Growth on HiCrome™ Candida Differential Agar (CDA)

The HiCrome™ CDA (HiMedia Laboratories, Mumbai, India) plates were inoculated with cultured yeast colonies using a sterile loop in a streaking pattern then incubated at 37 °C for 48 h. After incubation, the growth and colour of the colonies were observed [29].

Germ tube formation test

In this test, small sterile test tubes containing 0.5 ml of human serum were inoculated with the yeast colonies and incubated at 37 °C for 3–4 h. Following incubation, a drop of the mixture was put on a sterile glass slide, covered with a cover slip, and examined under a 40X magnification microscope to look for the development of germ tubes [30, 31].

Vitek2 test

The Yeast isolates were confirmed using the Vitek 2 Compact system (bioMérieux, France) [29].

Antifungal susceptibility testing

All C. albicans isolates undergo for antifungal susceptibility testing using the Kirby-Bauer disk diffusion method on SDA plate and incubated at 37 °C for 24–48 h, following the Clinical and Laboratory Standards Institute (CLSI) M44-A2 guidelines. The antifungal agents examined in this study included azoles (fluconazole, itraconazole, voriconazole, ketoconazole, miconazole, and clotrimazole), polyenes (nystatin and amphotericin B), and an echinocandin (caspofungin) (HiMedia Laboratories, Mumbai, India). Depending on the inhibitory zones, the findings were classified as sensitive, intermediate, or resistant (Table S1) [32, 33].

DNA extraction

The DNA extraction protocol involved centrifuging 2 mL of Candida liquid culture at 8,000 rpm for 15 min to obtain a cell pellet. The pellet was mixed with glass beads, cell lysis buffer, Triton X-100, proteinase K, and RNase A, followed by incubation at 65 °C for 1 h. After adding phenol, chloroform, and isoamyal alcohol, the mixture was vortexed and centrifuged. DNA was kept overnight at −20 °C after the top aqueous layer was moved to a fresh tube and cold ethanol was added. After being washed with 70% ethanol, the DNA pellet was dried and reconstituted in TE buffer. A Nanodrop spectrophotometer and a 0.8% agarose gel electrophoresis were used to determine the concentration and purity of the extracted DNA.

ISSR and RAPD amplification

The primer sequences were collected from relevant literature [18, 25, 26, 34–37], and these primers were subsequently purchased from a commercial supplier (For details see Supplementary Table S2 and S3). A total of 33 primers (19 ISSR and 14 RAPD) were used in PCR amplification and it was carried out in a 10 µl reaction volume containing 5 µl of the master mix (DSS Takara Bio India Pvt. Ltd., New Delhi, India), 3 µl of nuclease free water, 1 µl of template DNA and 1 µl of each primer. The optimal annealing temperature for both RAPD and ISSR primers (Tables S2 and S3) was found to vary according to the base composition of the primers. Therefore, ISSR and RAPD-PCR was performed at an initial denaturation at 95 ℃ for 5 min, 35 cycles of 95 ℃ for 30 s, annealing temperature (depending on primer sequence) for 45 s, 72 ℃ for 1 min, and final extension at 72 ℃ for 7 min. PCR amplified products were electrophoresed on 1.5% agarose in 1x TBE buffer, and the gels were stained with ethidium bromide and the DNA bands were recorded using a Gel Doc Imaging System (Protein Simple AlphaImager EC, USA). Primers that produce repeatable DNA bands were the only ones taken into consideration for the data analysis.

Data analysis

The gel images from RAPD and ISSR analysis were scored for the presence or absence of bands, and the data were compiled into a binary matrix (1 for presence and 0 for absence). Polymorphic bands are those that vary between samples, appearing in some but not others. Unique bands are found only in one specific sample, while monomorphic bands are present in every sample. The pairwise genetic similarity coefficient was calculated using Jaccard’s coefficient [38] and dendrogram was constructed based on the matrix of distance using unweighted pair group method with arithmetic averages (UPGMA) [39] and Principal Component Analysis (PCA) were performed using the statistical package NTSY-pc software Version 2.10e [40]. Resolving power of the ISSR and RAPD primers and primer index (RPI) was calculated as per Zarini et al. [41].

Results

Out of the 170 of vaginal swab samples collected from patients with suspected VVC, 122 isolates were confirmed as Candida species based on colour pigmentation on HiCrome™ CDA plates, and other 48 samples were negative. Out of which 35 isolates were confirmed as C. albicans based on germ tube test and HiCrome™ CDA results. The light green pigmentation on HiCrome™ CDA plates (Fig. S1), combined with the Vitek2 Compact system analysis, verified the presence of C. albicans. Eighteen C. albicans samples were randomly taken for this study out of 35 samples.

Antibiotic resistance patterns

The antifungal susceptibility test results for 35 C. albicans isolates across various antifungal agents demonstrate diverse sensitivity patterns. The highest sensitivity was observed for Nystatin, where 60% of the isolates were sensitive. Miconazole also showed a considerable sensitivity rate (54.29%), but with 37.14% resistant strains. In contrast, Ketoconazole and Voriconazole exhibited high resistance, with 60% of isolates resistant to each. Intermediate resistance was common for Amphotericin B (45.71%) and Itraconazole (42.86%). Fluconazole and Caspofungin displayed relatively balanced sensitivity and resistance patterns, with Fluconazole having 54.29% resistant isolates. Overall, resistance was widespread for several antifungals, particularly Ketoconazole, Voriconazole, and Itraconazole, indicating potential challenges in treatment options (Table 1).

Table 1.

Antifungal susceptibility test of all identified C. albicans species

Antifungal	Concentration (µg)	Sensitive (n, %)	Intermediate (n, %)	Resistant (n, %)	Total
MIC	30	19 (54.29%)	3 (8.57%)	13 (37.14%)	35
NS	100	21 (60.00%)	8 (22.86%)	6 (17.14%)	35
CC	10	9 (25.71%)	9 (25.71%)	17 (48.57%)	35
KT	10	8 (22.86%)	6 (17.14%)	21 (60.00%)	35
AP	20	7 (20.00%)	16 (45.71%)	12 (34.29%)	35
FLC	10	15 (42.86%)	1 (2.86%)	19 (54.29%)	35
CAS	10	12 (34.29%)	6 (17.14%)	17 (48.57%)	35
IT	10	2 (5.71%)	15 (42.86%)	18 (51.43%)	35
VRC	1	14 (40.00%)	0 (0.00%)	21 (60.00%)	35

MIC 30 Miconazole (30 µg), NS 100 Nystatin (100 units), CC 10 Clotrimazole (10 µg), KT 10 Ketoconazole (10 µg), AP 20 Amphotericin B (20 µg), FLC 10 Fluconazole (10 µg), CAS 10 Caspofungin (10 µg), IT 10 Itraconazole (10 µg), VRC 1 Voriconazole (1 µg)

ISSR-PCR analysis

The amplification patterns of 18 C. albicans using ISSR primers (ISSR 1 to ISSR 19) are presented in Table 2 and illustrated in Fig. S2.1, S2.2, S2.3 and S2.4. Each primer generates a distinct number of amplified bands across the samples, representing different DNA segments. For example, ISSR 6 produced the highest number of bands (81 total), indicating its ability to amplify multiple loci in the genome, contributing significantly to genetic diversity analysis. Conversely, primers like ISSR 10 and ISSR 15 amplified very few bands (2 each), suggesting limited polymorphism with those primers. The variation in band numbers across the samples and primers reflects genetic diversity among the C. albicans isolates, with some primers (ISSR 6 and ISSR 11) being more informative due to the higher number of amplified regions, while others are less polymorphic. This diversity helps differentiate the genetic makeup of the isolates, useful in epidemiological studies and understanding strain variability. Most primers generate polymorphic bands, indicating genetic variation across the samples. ISSR 6 exhibits the highest resolving power (1.29), highlighting its ability to differentiate between genetic variants, though it did not produce any unique bands. Primers like ISSR 5 and ISSR 19 produced both monomorphic and unique bands, showing some genetic conservation alongside variability. ISSR 10 and ISSR 15, with lower resolving power and few unique bands, indicate limited effectiveness in distinguishing isolates. Overall, primers with higher resolving power (ISSR 6, ISSR 11, and ISSR 19) and more polymorphic bands are better at revealing genetic diversity, while those with lower values are less informative.

Table 2.

Details of ISSR banding pattern in C. albicans sample

Primer name	Band present	Monomorphic band	Polymorphic band	Unique bands	Resolving power	Primer index
ISSR 1	9	0	5	4	0.2	0.18
ISSR 2	41	0	5	0	0.91	0.5
ISSR 3	20	0	5	1	0.44	0.35
ISSR 4	50	0	8	1	0.69	0.45
ISSR 5	35	1	5	4	0.65	0.44
ISSR 6	81	0	7	0	1.29	0.46
ISSR 7	44	0	5	0	0.98	0.5
ISSR 9	52	0	6	0	0.96	0.5
ISSR 10	2	0	0	2	0.11	0.1
ISSR 11	55	0	6	0	1.02	0.5
ISSR 12	4	0	1	1	0.22	0.2
ISSR 13	33	0	4	2	0.52	0.39
ISSR 14	41	0	5	0	0.91	0.5
ISSR 15	2	0	0	2	0.11	0.1
ISSR 18	36	0	4	0	1	0.5
ISSR 19	52	1	3	1	1.16	0.49

The (Fig. 1) illustrates the genetic similarity matrix among 18 C. albicans samples based on ISSR marker analysis. The values range from 0.4337 to 1.000, indicating varying degrees of genetic relatedness between the samples. A value of 1.000 (between samples S95 and itself) represents identical genetic profiles, while lower values indicate greater genetic differences. Samples such as S110 and S117 (0.8554) or S123 and S124 (0.8313) show high similarity, suggesting that they are closely related. In contrast, pairs like S95 and S230 (0.4337) exhibit significant genetic divergence. This matrix helps reveal the genetic structure and diversity within the C. albicans population, which could be important for understanding its adaptability and resistance mechanisms in clinical settings.

Fig. 1.

Genetic similarity between 18 samples of C. albicans using ISSR marker

The dendrogram (Fig. 2) illustrates the hierarchical clustering of different Candida albicans strains based on genetic distance. The strains are grouped into clusters according to their genetic similarity, with closer branches indicating higher similarity. Strains like S252, S260, and S268 form a distinct cluster, indicating they are closely related genetically. In contrast, strains such as S95 and S230 are more genetically distant from the others, as reflected in their connection to the rest of the tree at a larger distance. This clustering pattern reveals the genetic relationships and diversity among the C. albicans strains, with some forming tightly-knit groups and others being more genetically distinct.

Fig. 2.

Genetic diversity of 18 samples of C. albicans with phylogenetic tree analysis using ISSR marker

The Principal Component Analysis (PCA) (Fig. 3) plot displays the genetic variation among C. albicans strains, with the first two principal components, PC1 and PC2, explaining 22.95% and 14.98% of the variance, respectively. The plot shows that most strains cluster closely together near the origin, indicating minimal genetic divergence among them. However, strain S95 is significantly separated along the PC1 axis, suggesting it is genetically distinct from the other strains. Similarly, strains S230, S268, S260, and S251 are also more dispersed along the PC1 and PC2 axes, indicating varying degrees of genetic divergence. This analysis highlights the presence of both closely related and genetically distinct strains within the population, with strain S95 being particularly unique.

Fig. 3.

PCA showing relationship among 18 samples of C. albicans using ISSR marker

RAPD-PCR analysis

The amplification pattern (Table 3) of same 18 C. albicans samples using RAPD markers reveals significant variation in band generation across different primers and isolates. The majority of the primers produced few or no bands in several samples, indicating minimal amplification in most cases. Primer OPA 03 stood out; generating a total of 35 bands across all 18 C. albicans samples (Fig. S3), suggesting it is highly effective in amplifying multiple loci. Primer OPE 04 also showed moderate amplification with 18 bands, distributed among most of the isolates. However, primers such as OPA 01, OPA 07, OPA 09, and OPA 18 produced very few bands, typically one or two, in isolated cases. This pattern suggests that certain primers like OPA 03 are more robust for detecting genetic variation in C. albicans, while others are less effective. Among the primers tested, OPA 03 exhibited the highest level of polymorphism, with three polymorphic bands and one unique band, showcasing its effectiveness in distinguishing genetic diversity within the samples. OPE 04 also contributed to the genetic profile with two polymorphic bands. In contrast, primers OPA 01, OPA 02, OPA 07, OPA 09, and OPA 18 demonstrated limited utility, producing only one or two unique bands without any monomorphic bands.

Table 3.

Details of RAPD banding pattern in C. albicans sample

Primer name	Band present	Monomorphic band	Polymorphic band	Unique bands	Resolving power	Primer index
OPA 01	2	0	1	0	0.22	0.2
OPA 02	2	0	0	2	0.11	0.1
OPA 03	35	0	3	1	1.3	0.46
OPE 04	18	0	2	0	1	0.5
OPA 07	1	0	0	1	0.11	0.1
OPA 09	1	0	0	1	0.11	0.1
OPA 18	1	0	0	1	0.11	0.1

The resolving power of the primers varied, with OPA 03 achieving the highest value (1.3), indicating its capability to differentiate between various strains effectively, while the other primers had lower resolving power, suggesting less efficiency in revealing genetic variation among the samples. Overall, these results highlight the varying effectiveness of RAPD primers in amplifying specific genetic markers in C. albicans.

The (Fig. 4) illustrates the genetic similarity among 18 samples of C. albicans based on RAPD markers. Notably, sample S 109 shows a similarity of 1.000 with samples S 110, S 117, S 139, S 141, S 148 and S 215, indicating that these samples are genetically identical in the regions amplified by the RAPD markers used. In contrast, some samples exhibit lower similarity values, such as S 109 and S 95, which share a similarity of only 0.5556, suggesting they are genetically distinct from one another. The matrix provides insights into the genetic diversity and relationships among the different C. albicans strains, indicating potential genetic clusters and variations that could be relevant for understanding pathogenicity, resistance, and epidemiology of the species.

Fig. 4.

Genetic similarity between 18 samples of C. albicans using RAPD marker

The dendrogram (Fig. 5) demonstrates the genetic diversity among various C. albicans strains, with different clusters representing strains that are genetically similar. Strains like S230 and S260 are closely related, forming a tight cluster with minimal genetic distance, while others, such as S95, show greater divergence, joining the tree at a larger distance. The hierarchical clustering reveals distinct subgroups within the strains, suggesting significant genetic variability.

Fig. 5.

Genetic diversity of 18 samples of C. albicans with phylogenetic tree analysis using RAPD marker

The Principal Component Analysis (PCA) plot (Fig. 6) reveals the distribution of C. albicans strains based on their genetic variability, represented along the first two principal components (PC1 and PC2), which explain 52.63% and 19.15% of the variance, respectively. Most of the strains cluster closely together near the origin, indicating genetic similarity. However, strain S95 is distinct and separated along the PC1 axis, suggesting significant genetic divergence from the other strains. Additionally, strain S124 is somewhat isolated along the negative axis of PC2, indicating another level of genetic difference. These findings highlight the presence of both closely related and genetically distinct strains within the analyzed population.

Fig. 6.

PCA showing relationship among 18 samples of C. albicans using RAPD marker

Discussion

Candida infections affect patients general health and recuperation and are linked to high rates of mortality and morbidity. Additionally, they impact both individuals and organizations by increasing the financial strain on healthcare systems and contributing to longer hospital admissions. These difficulties demonstrate the ongoing and complex effects of Candida infections on world health. Although notable progress has been made in the development and application of antifungal therapies, available treatment options for infections caused by Candida species remain constrained and frequently insufficient [15, 42].

The results from the antifungal susceptibility testing of C. albicans isolates highlight a concerning level of resistance to commonly used antifungal agents. The observed resistance patterns, particularly to azoles, are consistent with the mechanism described by Whaley et al. [43], who reported that mutations in the ERG11 gene contribute significantly to the rising trend of fluconazole resistance in clinical Candida isolates. This widespread resistance poses significant challenges for treatment, echoing the findings of Perlin et al. [44], who emphasized the need for continuous surveillance of antifungal susceptibility. Interestingly, the highest sensitivity was observed with Nystatin, which was effective against 60% of the isolates. This finding is consistent with previous studies that suggest Nystatin may remain a viable treatment option, particularly for superficial infections [45, 46].

Azole misuse has resulted in selective pressure and cross-resistance among C. albicans isolates, as seen by the high resistance to azoles that was found, with 60% resistance to ketoconazole and voriconazole. Fluconazole resistance was 59.54% in C. albicans isolates from Burkina Faso, and azole resistance was associated with changes in the ERG11 gene [47]. Additionally, intermediate resistance to Itraconazole (42.86%) and Amphotericin B (45.71%) was noted in this investigation. Nystatin (60%) and Miconazole (54.29%) showed higher sensitivity, which is consistent with research published from Saudi Arabia that found that boric acid and Nystatin were two of the most successful treatments for Candida vaginal isolates [48]. Its limited application in VVC may be reflected in its balanced sensitivity and resistance profile. In order to correctly identify isolates as susceptible, dose-dependent, or resistant, the broth microdilution approach yields more accurate and repeatable minimum inhibitory concentration (MIC) results than disk diffusion. Given the growing number of reports of azole resistance in VVC, this is especially crucial. Disk diffusion may underestimate resistance, particularly in physiological settings that impact azole efficacy, such as vaginal pH 4.5, as the study by Sobel and Akins [49] highlights. By allowing for precise pH modification, broth microdilution can more accurately replicate the vaginal environment and uncover clinically significant resistance that disk diffusion would overlook. Other researchers also emphasize how disc diffusion’s zone diameters and interpretive breakpoints can vary from one lab to another, potentially producing contradictory findings [50, 51]. On the other hand, broth microdilution conforms to CLSI reference standards (such as M27-A4), guaranteeing standardized, quantitative data that aids in resistance surveillance and well-informed treatment decisions. Integration of broth microdilution methods over disk diffusion is recommended for more accurate MIC determination, especially in low pH environments typical of vaginal mucosa. Although recent advancements in molecular approaches have demonstrated efficacy in strain differentiation, data collection and interpretation across heterogeneous populations continue to present obstacles. The need for standardized procedures and cooperative efforts to incorporate genetic insights into clinical practices is highlighted by the heterogeneity seen across C. albicans isolates [52].

The genetic diversity analysis through ISSR-PCR and RAPD-PCR revealed significant polymorphism among the C. albicans isolates, indicating a heterogeneous population. The high number of bands produced by primers such as ISSR 6 (81 bands) suggests that certain ISSR markers are more effective in amplifying genetic diversity, corroborating findings by Souframanien et al. [53] regarding the utility of molecular markers in assessing fungal populations. The effective differentiation of strains, especially those that are closely related, supports the epidemiological relevance of these molecular techniques. In decision, relevant research emphasizes how important genetic diversity analysis is for understanding fungal epidemiology and developing treatments [54].

Moreover, the genetic similarity matrix demonstrated a range of genetic relationships among isolates, with some strains, such as S109 and S117, showing high genetic similarity. This is consistent with previous research that highlights the importance of genetic analysis in understanding the population structure and potential transmission dynamics of C. albicans. The dendrogram further illustrated these relationships, indicating that certain strains form distinct clusters, which may reflect clonal expansion in specific settings [55].

In terms of resistance mechanisms, the varying effectiveness of the RAPD primers used highlights the complexity of genetic variation within C. albicans. Primer OPA 03, which exhibited the highest polymorphism, supports the notion that certain RAPD markers are particularly useful in detecting genetic diversity [56]. The identification of unique bands associated with resistant strains suggests that genetic factors may play a crucial role in antifungal resistance, as noted by Hamzehee et al. [57].

Ultimately, this study underscores the critical need for regular monitoring of antifungal resistance patterns in C. albicans populations to inform treatment strategies. As highlighted by Fan et al. [46], understanding the genetic diversity and resistance profiles of these isolates is essential for managing vulvovaginal candidiasis effectively. The substantial genetic similarity among some strains has been repeatedly demonstrated by studies, which is essential for comprehending the pathogen’s population structure and its transmission dynamics. Regarding resistance mechanisms, the use of RAPD primers has been successful in revealing the intricacy of C. albicans genetic diversity [57].

In clinical mycology, C. albicans genotyping has emerged as a vital technology that allows for precise isolate identification and epidemiological monitoring across a range of patient groups and healthcare environments. Significant genetic heterogeneity among ICU-derived isolates was emphasized by studies like El Kazzaz & Attia [34] which used RAPD primers (OPA3, OPA7, OPA9) to uncover 12 to 20 different genotypes by UPGMA dendrogram analysis. RAPD is one of the most popular genotyping techniques because of its ease of use, affordability and capacity to identify genetic variations without the need for previous genomic sequence data. In the meanwhile, ISSR markers are prized for their great sensitivity and reliability in detecting variations in microsatellite regions among clinical isolates. Both the RAPD and ISSR approaches have demonstrated efficacy in finding localized genotype dominance, such as recurrent patterns in blood or vaginal specimens and in differentiating isolates that are epidemiologically unrelated. Molecular genotyping is an essential fingerprinting technique for controlling hospital outbreaks and helps identify drug-resistant C. albicans strains early [58–60]. In this study, genetic variation among C. albicans isolates correlates with fluconazole resistance patterns. The results of both AFST and genotyping revealed that resistant and susceptible isolates exhibited distinguishable genetic differences, indicating that genotypic variation is associated with antifungal resistance. Furthermore, there is growing evidence linking molecular profile to virulence and antifungal susceptibility characteristics, which supports better clinical judgment and individualized treatment plans. To obtain a comprehensive picture of the dynamics of Candida infections and resistance mechanisms, future studies should attempt to combine genotypic data with clinical information about patients.

Conclusion

The study explores the genetic diversity and antifungal resistance patterns of C. albicans in clinical samples of vulvovaginal candidiasis patients. It reveals significant genetic variability, which is crucial for understanding its adaptability and pathogenic potential. Resistance trends were found to be concerning, particularly to azole-based treatments. The study highlights the importance of regular genetic monitoring to understand drug resistance evolution and inform therapeutic approaches. Future research should explore the correlation between genetic markers and resistance mechanisms.

Abbreviations

CDA

Candida Differential Agar

CLSI

Clinical and Laboratory Standards Institute

DNA

Deoxyribonucleic Acid

ERG11

Ergosterol Biosynthesis Gene 11

ICU

Intensive Care Unit

ISSR

Inter Simple Sequence Repeat

MIC

Minimum Inhibitory Concentration

PCA

Principal Component Analysis

PCR

Polymerase Chain Reaction

RAPD

Random Amplified Polymorphic DNA

RPI

Resolving Power Index

RVVC

Recurrent Vulvovaginal Candidiasis

SDA

Sabouraud Dextrose Agar

TBE

Tris-Borate-EDTA

UPGMA

Unweighted Pair Group Method with Arithmetic Averages

VVC

Vulvovaginal Candidiasis

Authors’ contributions

BKS, UM were actively involved in performing the experiments and research work. RH is involved in the collection of samples. JT & MCS helped shape the overall research plan. SKP carefully reviewed the manuscript and provided valuable feedback and corrections.

Funding

Open access funding provided by Siksha 'O' Anusandhan (Deemed To Be University). Open access funding provided by SOA and research activity are carried out using ICMR-RMRC, Bhubaneswar intramural fund.

Data availability

Data is provided within the manuscript or supplementary information files.

Declarations

Ethics approval and consent to participate

The study protocol was reviewed and approved by the Institutional Ethics Committee of ICMR-Regional Medical Research Centre (ICMR-RMRC), Bhubaneswar (Approval No. ICMR_RMRC/ AEC-2025/M4/001). This study involves no direct interaction with patients. All analyses are conducted using anonymised clinical samples provided by the gynaecology departments of IMS SUM Hospital, and Kalinga Hospital, Bhubaneswar, Odisha. Patient identifiers have been removed prior to sample transfer, ensuring confidentiality and compliance with ethical standards.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.