Mechanisms of azole antifungal resistance in clinical isolates of Candida tropicalis.

This study was designed to understand the molecular mechanisms of azole resistance in Candida tropicalis using genetic and bioinformatics approaches. Thirty-two azole-resistant and 10 azole-susceptible (S) clinical isolates of C. tropicalis were subjected to mutation analysis of the azole target genes including ERG11. Inducible expression analysis of 17 other genes potentially associated with azole resistance was also evaluated. Homology modeling and molecular docking analysis were performed to study the effect of amino acid alterations in mediating azole resistance. Of the 32 resistant isolates, 12 (37.5%) showed A395T and C461T mutations in the ERG11 gene. The mean overexpression of CDR1, CDR3, TAC1, ERG1, ERG2, ERG3, ERG11, UPC2, and MKC1 in resistant isolates without mutation (R-WTM) was significantly higher (p<0.05) than those with mutation (R-WM) and the sensitive isolates (3.2-11 vs. 0.2-2.5 and 0.3-2.2 folds, respectively). Although the R-WTM and R-WM had higher (p<0.05) CDR2 and MRR1 expression compared to S isolates, noticeable variation was not seen among the other genes. Protein homology modelling and molecular docking revealed that the mutations in the ERG11 gene were responsible for structural alteration and low binding efficiency between ERG11p and ligands. Isolates with ERG11 mutations also presented A220C in ERG1 and together T503C, G751A mutations in UPC2. Nonsynonymous mutations in the ERG11 gene and coordinated overexpression of various genes including different transporters, ergosterol biosynthesis pathway, transcription factors, and stress-responsive genes are associated with azole resistance in clinical isolates of C. tropicalis.

Introduction

Candida species, including Candida albicans and non-Candida albicans Candida (NCAC) species are implicated in a myriad of superficial and invasive infections including bloodstream infections [1]. Morbidity and mortality due to invasive candidiasis (IC) are significantly higher in immunocompromised patients [2-4]. Candida tropicalis, among the NCAC species, has emerged as the predominant species responsible for IC in Asian countries including India [3, 5, 6].

Escalating acquired resistance of C. tropicalis to currently available antifungal drugs such as azoles derivatives, echinocandins, and amphotericin B has been reported in several studies [1–3, 5, 6]. Factors linked with the development of resistance include, the rampant misuse of antifungals, improper dosing resulting in suboptimal drug concentrations, long-term therapy, and the unregulated use of antifungals in agriculture and/or animal husbandry [2, 5]. Fluconazole is perhaps the most commonly used azole because of its low cost, effective bioavailability, and fewer side effects [7, 8]. Azoles act by inhibiting lanosterol C14 alpha-demethylase (ERG11p), an essential enzyme for ergosterol biosynthesis, encoded by the ERG11gene.

The predominant mechanism of azole resistance Candida species is mutation/ overexpression of different genes [1, 9]. Mutations and overexpression in the azole target ERG11 are well known mechanisms to be associated with antifungal resistance [10-14], with which the amino acid alterations disrupt the affinity between enzyme and substrate [1, 9, 11, 15–17]. The drug inducible overexpression of transporter genes like the ATP-binding cassette (ABC) and the major facilitator superfamily (MFS) can cause active efflux of cellular azole antifungal drugs thereby contributing to antifungal resistance [1, 9, 17]. Both, the up- and down- regulation of various drug transporters and ergosterol pathway genes have been reported among resistant isolates of C. tropicalis [1, 9, 10, 12–14, 16]. There are also reports of alternative mechanisms associated with azole resistance such as mitochondrial defects and biofilm formation [1, 9]. Despite available literature, comprehensive knowledge about the mechanisms behind the azole resistance in C. tropicalis is still limited.

The present study was designed to explore the underlying mechanisms of azole resistance in clinical C. tropicalis isolates by studying the role of multiple drug transporters, transcription factors, ergosterol biosynthesis pathway, stress-responsive pathways and exploring various known and unknown resistance pathways by using a combination of phenotypic, genetic and bioinformatics approaches.

Materials and methods

Yeast isolates

A total of 613 C. tropicalis isolates causing invasive infections including 32 azole-resistant isolates were screened for a duration of 4 years (January 2015 to December 2018). These 32 resistant isolates and ten susceptible isolates were included in the present study (Table 1). The isolates examined in this study were also used in our previous studies [18-22]. The institutional ethics committee of the Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India approved the study. The isolates were identified by MALDI-TOF MS (Microflex LT mass spectrometer, Bruker Daltonik, Germany) and PCR sequencing of the internal transcribed spacer (ITS) region of ribosomal DNA [23, 24].

Table 1

Details of isolates with clinical background.

Isolate ID	Flu MIC (mg/L)	Vori MIC (mg/L)	Itra MIC (mg/L)	Posa MIC (mg/L)	ERG11 mutations (A395T & C461T)	Amino acid alterations (Y132F & S154F	Patient Age	Sex	Clinical diagnosis	Type of sample
420182	16	0.25	0.06	0.12	No	No	69	M	Perforation peritonitis	Blood
420183	64	0.25	0.25	0.12	No	No	25	M	Meningitis	CSF
420184	32	0.5	0.12	0.06	No	No	60	M	Sepsis	Blood
420185	32	2	0.25	0.06	No	No	14 Days	M	Late-onset of neonatal sepsis	Blood
420186	16	0.12	0.12	0.06	No	No	50	M	Sepsis	Blood
420187	32	1	0.06	0.06	No	No	29	M	Acute Chronic Liver failure	Blood
420188	16	0.5	0.03	0.06	No	No	22	M	Meningioma	Blood
420189	128	4	0.5	0.5	Yes	Yes	67	M	Sepsis	Blood
420190	16	0.25	0.06	0.03	No	No	35	M	Burns	Blood
420201	64	0.5	0.06	0.06	No	No	54	M	Sepsis	Blood
420191	64	0.25	0.06	0.06	No	No	67	M	Shock	Blood
420192	16	0.25	0.03	0.06	No	No	60	M	Pancreatitis	Blood
420193	128	1	0.12	0.25	No	No	29	M	Poisoning	Blood
420194	32	0.25	0.03	0.06	No	No	50	M	Respiratory Distress	Blood
420195	128	4	2	1	No	No	29	M	Pancreatitis	Blood
420227	128	0.5	0.25	0.5	Yes	Yes	45	F	Pancreatitis	Pus
420228	256	4	2	2	No	No	58	M	Septic shock	Blood
420229	128	4	2	2	No	No	35	M	Lung Carcinoma	Blood
420230	256	4	2	2	No	No	10	M	Sepsis	Blood
420231	256	2	0.12	0.12	No	No	73	M	Septic shock	CSF
420232	32	0.5	0.5	0.5	Yes	Yes	60	F	Roadside accident	Blood
420233	32	1	0.25	0.25	Yes	Yes	20	M	Pancreatic injury	Blood
420234	64	1	0.25	0.25	Yes	Yes	50	M	Sepsis	Blood
420235	32	0.5	0.25	0.25	Yes	Yes	20	M	Gastric perforation peritonitis	Blood
420236	32	0.5	0.25	0.25	Yes	Yes	20	M	Gastric perforation peritonitis	Blood
420237	64	1	0.5	0.5	Yes	Yes	50	M	Sepsis	Blood
420238	256	16	16	2	Yes	Yes	20	M	Sepsis	Blood
420239	256	16	16	0.5	Yes	Yes	14 Days	M	Seizure	Blood
420245	128	2	1	0.5	Yes	Yes	14 Days	M	Jejunal atresia	Blood
420246	32	1	0.25	0.5	No	No	1 Month	F	Meningitis	Blood
420247	128	4	2	0.25	Yes	Yes	28	M	Leg fracture	Wound slough
420248	16	0.5	0.25	0.25	No	No	14 Days	F	Tracheoesophageal fistula	Blood
420214	1	0.03	0.06	0.06	No	No	2 months	F	Sepsis	Blood
420215	0.5	0.06	0.12	0.03	No	No	77	M	Post-op gastrectomy	Blood
420203	1	0.12	0.12	0.06	No	No	84	F	Cerebral venous accident	Blood
420200	0.5	0.03	0.03	0.06	No	No	52	F	Sepsis	Blood
420212	0.5	0.25	0.12	0.25	No	No	32	M	Sepsis	Blood
420210	0.5	0.03	0.06	0.06	No	No	62	F	Ovarian carcinoma	Blood
420199	1	0.03	0.12	0.12	No	No	23	M	Road traffic accident	Blood
420205	1	0.25	0.12	0.06	No	No	65	M	Extrahepatic Biliary obstruction	Ascitic Fluid
420204	0.5	0.06	0.12	0.03	No	No	8	M	Anemia decreased evaluation	Blood
420198	0.5	0.12	0.06	0.03	No	No	28	M	Sepsis	Blood

Flu: Fluconazole; Vori: Voriconazole; Itra: Itraconazole; Posa: Posaconazole; CSF: Cerebrospinal fluid; A: Adenine; T: Thymine; C: Cytosine; Y: Tyrosine; F: Phenylalanine; S: Serine

Antifungal susceptibility testing (AFST)

Minimum inhibitory concentrations (MICs) with respect to fluconazole, voriconazole, itraconazole, and posaconazole (Sigma-Aldrich, Germany) were assessed for all the isolates using the CLSI broth micro-dilution (BMD) method (M27-A3) followed by MIC interpretation in accordance with the CLSI M27-S4 guidelines [25, 26].

Sequencing of azole drug target ERG11

PCR sequencing of the ERG11 gene was performed in all the isolates by using two primer pairs as demonstrated in our previous study (S1 Table in S1 File) [20]. SeqMan software (DNASTAR, USA) was used to align the multiple fragments of the ERG11 gene. ClustalX 2.1 software (UCD Conway Institute, Ireland) was used to align the consensus sequence of the isolates with respect to C. tropicalis MYA- 3404 (GenBank accession no. XM_002550939.1) to determine the molecular alterations.

Expression analysis of target genes

Drug-induced expression of 17 genes [ergosterol synthesis genes (ERG1, ERG2, ERG3, ERG11, ERG24, and HMG), drug efflux transporter genes (CDR1, CDR2, CDR3, and MDR1), transcription factors [Multidrug resistance regulator (MRR1), Transcriptional activator of CDR genes (TAC1) and Transcription factor of ERG11 (UPC2)], and different stress pathway genes (HSP90, HOG1, MKC1, and SOD1)] was studied. The primers from our previously published study were used for expression analysis (S2 Table in S1 File) [20]. The RT-qPCR based expression analysis was performed as described previously [20, 21]. In brief, after the incubation of cells for 7 hours with and without drug, total RNA was extracted with TRIzol reagent (Invitrogen, California, USA). The quality and quantity of the RNA was confirmed by NanoDrop (Thermo Scientific, Massachusetts, USA) and the 260/280 for the samples was in between 1.85 and 2.1. The cDNA was synthesized using High-capacity cDNA synthesis kit (Thermo Fisher Scientific, Massachusetts, USA) with 1μg RNA input and Eppendorf 5331 MasterCycler (Eppendorf, Hamburg, Germany) was used for amplification. Expression of the target genes were examined with the Light Cycler 480 (Roche, Switzerland) RT-qPCR system using the PowerUp SYBR Green Master Mix (Termo Fisher Scientific, United States) following the manufacturer’s instructions using 1μL cDNA. The RT-qPCR running protocol was as follows: One cycle initial denaturation at 95°C for 1 minute; 45 repeated cycles of denaturation, annealing and extension at 94°C for 10 seconds, 59°C for 10 seconds, 72°C for 10 seconds respectively. Finally, melting curve was generated using the setup at 95°C for 5 seconds, 59°C for 1 min and 97°C for 15 seconds. The expression of the genes was analyzed with respect to untreated control using the ΔΔCT method [27]. We optimized elongation factor 1α (EF1) as the stable reference gene and used for the drug-induced expression of the target genes [21].

Homology modelling and model quality assessment

The model of both wild and mutant protein was generated by different programs and model quality scores were analyzed (S3 Table in S1 File). To investigate the structural variations upon mutation, structural superimposition of both wild and mutant types was performed. ΔΔG value (Gibbs free energy) was calculated to infer the effect of mutations on the structural stability of the protein. The detailed methodology of homology modelling and model quality assessment is explained in the S1, S2 and S4 Material and Methods in S1 File.

Molecular docking study

Docking analysis was performed to determine the binding affinity of fluconazole and voriconazole against the lanosterol 14-alpha demethylase (ERG11p) of both wild and mutant C. tropicalis. After every successful docking simulation, the model falling in the top-ranked cluster with the strongest binding energy was utilized for further analysis. The methodology of molecular doc king is explained in the S3 and S4 Material and Methods in S1 File.

Sequence analysis of other resistance-related genes

Apart from the ERG11, sequencing of ERG1, ERG3, UPC2, and TAC1 genes was performed as these genes are well documented to be associated with azole resistance in Candida. An attempt was taken to analyze the nonsynonymous mutations among these genes. The gene sequences of C. tropicalis MYA-3404 was used as a reference for mutation analysis of target genes in isolates used in this study.

Statistical analysis

GraphPad software (GraphPad Prism 9, California, USA) was used for statistical analysis. Statistical significance was computed using Kruskal-Wallis test, Student’s t-test and ANOVA. A p-value <0.05 is significant.

Results

Clinical details of the isolates

The 42 isolates used in the present study, were recovered from blood, ascitic fluid, cerebrospinal fluid, pus, and wound slough. Out of 32 azole-resistant C. tropicalis, 28 (87.5%) patients were male and 4 (12.5%) were female. Most of the patients were ≥ 20 years old and presented a huge diversity in the underlying conditions is present. Among the patients, 8 (25%) patients were receiving fluconazole treatment for 7–28 days. Among the 10 susceptible isolates, 3 were exposed to fluconazole for 7–14 days (Table 1).

Antifungal susceptibility profile and nonsynonymous mutations in the ERG11 gene

All the 32 fluconazole-resistant isolates showed the MICs between 16 to 256 mg/L, while in the 10 fluconazole susceptible isolates MICs ranged between 0.5 to 1mg/L. Out of 32 fluconazole-resistant isolates cross-resistance to voriconazole, itraconazole, and posaconazole was presented by 17(1–16 mg/L), 8(1–16 mg/L), and 5(1–2mg/L) respectively (Table 1).

Out of the 32 resistant isolates, ERG11 mutations at 395 and 461 positions were observed in 12 (37.5%) isolates. At 395 position, adenine (A) was replaced by thymine (T) whereas, at 461 position, cytosine (C) was replaced by T. Due to these two alterations, Tyrosine (Y) to Phenylalanine (F) substitution at 132 position and Serine (S) to F alteration at 154 position was seen in the protein sequence of Lanosterol 14-alpha demethylase enzyme (ERG11p). No nonsynonymous mutations were noticed among the susceptible isolates (Table 1).

Inducible expression of resistance related genes

To determine the inducible expression of the genes, freshly frown cells at a concentration of 1×106 cells/mL were inoculated in Yeast extract peptone dextrose (YPD) broth. After 4 hours, cells were treated with sub-inhibitory concentration of fluconazole (Two dilutions lower than the MIC of the isolates) along with another setup with untreated control. Cells were incubated up to 7 hours and the expression of the different genes were analyzed. The mean inducible expression of CDR1, CDR3, and TAC1 was significantly higher (p<0.05) in the 20 resistant isolates without ERG11 mutations (R-WTM) at 4.9, 4.5, and 3.2 folds respectively compared to the 12 resistant isolates with ERG11 mutations (R-WM) at 1.8, 1.6, and 2 folds respectively and the 10 susceptible isolates (S) at 0.3, 1, and 1.4 fold respectively. On the other hand, expression of CDR2 and MRR1 in R-WTM (2.1 and 1.8 fold respectively) and R-WM (2.2 and 1 fold respectively) was significantly higher (p<0.05) than the S isolates (0.02 and 0.1 fold respectively). No significant variation (p>0.05) in the MDR1 expression was noted in the R-WTM, R-WM, and S isolates (Fig 1A–1F).

Fig 1

Scatter dot plots depicting the inducible expression of different transporters (CDR1, CDR2, CDR3 and MDR1), ergosterol biosynthesis pathway genes (ERG1, ERG2, ERG3, ERG11, and ERG24), and transcription factors (TAC1, MRR1 and UPC2) represented as fold change relative to untreated control.

The level of expression was calculated using 2-ΔΔCT method. One-way ANOVA with multiple comparisons was perform to determine the statistical significance. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, and NS = Non Significant.

The average fold overexpression of ERG1, ERG2, ERG3, ERG11, and UPC2 in R-WTM (11, 3.4, 5, 6.1, and 4.6 respectively) was significantly (p<0.05) higher than the R-WM (1.5, 1.4, 1.6, 2.5, and 2 respectively) and S (1.3, 2, 2.2, 2.2, and 0.3 respectively) isolates. Though the mean ERG24 expression was comparatively higher in resistant isolates compared to S isolates, no statistically significant difference was seen in the mean ERG24 and HMG expression among the R-WTM (4 and 0.1), R-WM (2.5 and 0.4), and S (2.7 and 0.5) isolates (p>0.05) (Fig 1G–1K and S1 Fig in S1 File).

No noticeable variation in the expression of HSP90, HOG, and SOD1 was seen among R-WTM, R-WM, and S isolates (p>0.05). However, the MKC1 expression was significantly higher in R-WTM (5.1 fold) compared to both the R-WM (0.2 fold) and S (0.8 fold) isolates (p<0.05) (Fig 1L and S2 Fig in S1 File).

The double gradient heat map confirmed that the ergosterol biosynthesis pathway genes are activated in all three groups. The level of their expression in azole-resistant isolates was higher compared to susceptible isolates. In contrast, a higher level of transporter gene expressions was only noted in resistant isolates. Among the stress-responsive genes, MKC1 expression was only observed in R-WTM. All together the ergosterol biosynthesis pathway genes, transporter genes, and stress-responsive genes are coordinately expressed specifically in resistant isolates (Fig 2). The heat map is confirming a probable interrelation between the genes and their direct effect on azole resistance.

Fig 2

Heat map demonstrating the comparison between the inducible expression of azole resistance genes among the R-WM (Isolate 1–12), R-WTM (13–32), and S (33–42) isolates.

‘Y’ axis is representing the isolates used and ‘X’ axis representing the genes tested. The scale representing the upregulation (in red) and downregulation (in green) of the genes among resistant and susceptible isolates.

ERG11 expression in cross-resistance isolates

The overexpression of azole drug target ERG11 gene was also measured among isolates resistant to only fluconazole (Flu), cross-resistant to Flu and voriconazole (Flu+Vori) and also cross-resistant to Flu, Vori, and itraconazole (Flu+Vori+Itra). No significant variation in average fold expression levels (4.8, 5.4, and 3.9 respectively) was seen among these three groups (p>0.05) (S3 Fig in S1 File).

Homology modelling of lanosterol 14-alpha demethylase (ERG11p)

BLASTp search against the PDB database shows that the protein has 83.11% identity with protein Lanosterol C14 alpha demethylase (PDB ID: 5V5Z) from Candida albicans. The sequence had an overall query coverage of 99% and 91% similar amino acids. Hence, the 5V5Z was selected as template for the tertiary structure predication. Modeller v9.25 was used for homology modelling and the best model was selected based on the minimum DOPE score generated. The model was further subjected to energy minimization using Swiss Pdb viewer and Chimera. After each minimization, the structure was verified using SAVES server. Mutagenesis was achieved using Pymol and the structure was also subjected to refinement procedures same as wild type structure. Gibbs free energy calculation (ΔΔG for Y132F = 5.17, S154F = 9.27 and overall ΔΔG = 8.74) suggested that the reported mutations are destabilizing the protein (Fig 3).

Fig 3

Homology modelling of ERG11p.

Structural superimposition of both wild and mutant type. Wild type is colored in orange and mutant is in cyan. Mutated residues are shown in stick representation and labelled accordingly.

Molecular docking

After each successful docking simulation, the pose that falls in the top-ranked cluster with highest binding energy was used for post docking analysis. Results from the docking study reflected that binding energy of native protein is low compared to mutated protein. Binding energy of fluconazole against the native protein was -6.83 kcal/mol [(Fig 4(A1)]; whereas binding energy of fluconazole against the mutant protein was -6.38 kcal/mol [(Fig 4(A2)]. Similarly binding energy of voriconazole against the native protein was -7.44 kcal/mol [(Fig 4(B1)] and -7.22 kcal/mol [(Fig 4(B2)] against the mutant protein. The potential binding site analysis revealed that Tyrosine 132 is highly crucial in forming hydrogen bonds between heme cofactor and the drug molecules i.e fluconazole and voriconazole in the native form. Substitution of Tyrosine 132 by Phenylalanine 132 negates the hydrogen bond between both cofactor and the ligand molecule (Fig 4).

Fig 4

Docked pose and interacting residues of (A1) wild protein with Tyrosine132 (cyan) H-binding to Heme (purple) and Fluconazole (green) (A2) mutated protein with Phenylalanine 132 (yellow) in presence of Heme (purple) and fluconazole (green) displays no H-bonding (B1) wild protein with H-bonding of Tyrosine 132 with Heme (purple) and Voriconazole (green) (B2) mutated protein with no H-bonding of Phenylalanine in presence of Heme (purple) and Voriconazole (green). For clarity, only selected binding site residues are shown.

Analysis of additional resistance-related genes

Surprisingly, the 12 isolates (R-WM) presented ERG11 mutations also presented nonsynonymous mutations in the coding sequences of ERG1 and UPC2 genes. Asparagine (N) to Histidine (H) substitution at 74 position in the Squalene epoxidase enzyme (ERG1p) was noted due to A220C transversion in the ERG1 gene. The T503C and G751A mutations in UPC2 transcription factor were responsible for Leucine (L) to Proline (P) and Alanine (A) to Threonine (T) substitution at 168 and 251 positions (S4 Table in S1 File). No nonsynonymous mutation was seen in the coding sequences of ERG3 and TAC1 genes. We could not build the model of ERG1p and UPC2p due to the lack of a proper template.

Discussion

A paradigm shift in the epidemiology of IC with an increase in reports of C. tropicalis infections and rising azole resistance has been reported in Asian countries including India [3, 5, 6]. The mechanism of azole resistance was investigated in the present study among 32 clinical isolates of C. tropicalis primarily with respect to their drug efflux transporters, azole antifungal drug target ERG11 and other ergosterol biosynthesis pathway genes, different transcription factors and stress pathways.

Various host, drugs, and microbial factors are associated with resistance [2]. From the age, sex and background conditions of the patients it is inconclusive whether the host factors are actively responsible for the development of azole resistance or not. Further studies with large number of azole resistant C. tropicalis clinical isolates are needed for further conclusion. Of our 32 resistant C. tropicalis isolates, only 8 (25%) were under fluconazole treatment for <1 month, suggesting the possible role of other biotic and abiotic factors in the development of azole resistance or the probable acquisition of infection from some unknown sources. Unfortunately, the complete clinical details from the patients could not be retrieved for analysis in the context of their clinical data. Among all C. tropicalis isolates in the study period, 5.2% (32 of 613) were fluconazole-resistant with the presence of cross-resistance to voriconazole 53.1% (17 of 32), itraconazole 25% (8 of 32) and even posaconazole 15.6% (5 of 32) indicating that other azoles may not be effective in the scenario.

The active role of mutations in the ERG11 gene is reported to be responsible for azole resistance in C. tropicalis [10-14]. In the present study, 12(37.5%) resistant isolates (MICs: 32–256 mg/L) showed two non-synonymous mutations (A395T and C461T) in the coding sequence of the ERG11 gene indicating their possible role in mediating azole resistance in C. tropicalis. The study by Fan et al. reported that the C. tropicalis isolates with non-wild-type ERG11 gene presented higher MICs; however, we didn’t find any noticeable variation among R-WM and R-WTM groups [14].

Overexpression of ERG11 and different drug efflux transporters (CDR and MDR) is a well-documented mechanism of resistance in C. tropicalis [1, 9, 13, 14]. Most reports suggest no difference in their expression between azole-resistant and susceptible isolates of C. tropicalis [10, 28]. However, in our study, while the expression of MDR1 was uniformly low in both resistant and susceptible isolates, expression of ERG11, CDR1, and CDR3 was significantly higher in R-WTM compared to S isolates, indicating their active role in azole resistance. Although, the role of other ergosterol biosynthesis pathway genes in azole resistance have also been demonstrated in previous studies, the significantly higher expression of ERG1, ERG2, and ERG3 in resistant isolates is reported in the present study for the first time [29, 30]. Among the transcription factors, Jiang C et al. has explored the role of only UPC2 on azole resistance in C. tropicalis [31]. Here we explored the role of MRR1 and TAC1 in addition to UPC2 in C. tropicalis azole resistance. Our result showed a significantly higher level of TAC1, UPC2, and MRR1 expression in R-WTM isolates which affects the regulation of their target genes. While previous studies have investigated the role of SOD1 in azole-resistant C. tropicalis, we have additionally examined the expression of other stress pathway genes like HSP90, HOG1, and MKC1 for the first time [32]. Among these genes, only MKC1 presented a higher level of expression among R-WTM, indicting its probable role in mediating azole resistance. We also studied the expression of ERG11 in azole resistant and cross-resistant isolates; however, no difference in expression was seen. Our previous published work on the experimentally induced fluconazole resistance in C. tropicalis supports the findings of this study [20].

Several studies have reported that Y132F and S154F polymorphisms due to alterations at 395 and 461 positions of C. tropicalis ERG11p made the target enzyme resistant to azoles [10, 12–14] and these alterations were seen in the 12 resistant (R-WM) isolates even in the present study. These two mutations appeared together consistently, which is similar to the findings of Jiang et al. [10]. Homology modelling analysis in the past has revealed that tyrosine to phenylalanine conversion at 132 position in ERG11p is responsible for the loss of the normal hydrogen bonding between tyrosine and heme. Since heme is an important cofactor required for binding of azole to ERG11p, this alteration affects drug binding [11, 16]. In the present study, the ΔΔG revealed, these two mutations probably destabilized the protein. Tan et al. speculated, Y132F alteration in ERG11p would reduce the affinity between the target site of enzyme and fluconazole, as it is a hydrophilic drug molecule [11]. It is known that, tyrosine is an aromatic amino acid and is preferentially substituted by amino acids with similar properties and considering the fact that phenylalanine is a precursor of tyrosine and it is a likely substitution in the ERG11p. We confirmed for the first time that substitutions of Y132F and S154F hindered the formation of Pi-Pi and Pi-cation interaction between the cofactor and the ligand molecules thereby dipping the overall binding energy of the mutated docked complex. Moreover, Y132F within the active site greatly altered the hydrophobicity and overall geometry of the active site. Therefore, these two amino acid substitutions reduced the binding energy of both the ligand molecules and in turn conferred resistance towards the ligand molecule.

Previous studies have demonstrated the role of ERG1 and UPC2 mutations in azole resistance [13, 31, 33, 34]. Tsai et al. reported that ERG1 mutation in C. glabrata increased the susceptibility to azoles [33]. However, nonsynonymous ERG1 mutation (A220C) was seen concomitant with ERG11 mutation among resistant isolates in our study. Gain-of-function (GOF) mutations in the transcription factor UPC2 have been reported to transform it into a hyperactive state, responsible for azole resistance [31, 34]. Similar to the previous studies, two nonsynonymous mutations in UPC2 were seen in the present study [13, 35], while the mutation at 503 position is novel. Due to the unavailability of the proper template, the homology modeling of ERG1p and UPC2p could not be performed. Although mutations in ERG3 and TAC1 genes have been reported in azole-resistant isolates, we didn’t notice any alteration in the coding sequences of these genes [12, 36]. Further studies are needed for functional validation of our findings, preferably in a larger number of isolates to determine the exact role of ERG1p and UPC2p in azole-resistant C. tropicalis. Detailed analysis of our findings in the context of clinical information such as duration of hospitalization, prior antifungal treatment and duration, other antimicrobial therapies etc., could also help in providing a better understanding of the factors driving the development of infections due to resistant isolates.

Conclusions

In conclusion, nonsynonymous mutations in the ERG11 gene were one of the predominant mechanisms of azole resistance in clinical isolates of C. tropicalis as demonstrated by molecular docking analysis for the first time. In addition, to studying the overexpression of previously known genes, we demonstrated the involvement of different transporters, ergosterol biosynthesis pathway genes, transcription factors, and stress pathway genes in azole resistance. However, in view of the rising azole resistance in C. tropicalis clinical isolates, systematic and extensive future studies are essential to fully elucidate the mechanisms driving resistance.

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31 Jan 2022

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Although this paper could be potentially of interest, it suffers from including findings, which have been obviously and repeatedly reported elsewhere. Examples are below,

1. It is not clear why authors attempted to undertake the phenotypic assay, while antifungal susceptibility profile clearly showed that fluconazole at low doses was inhibitory for susceptible isolates, but not for resistant ones. Basically, this phenotypic assay is redundant and is suggested to be removed from the study.

2. Clinical profile of such isolates to be presented in an informative table, where authors include the following details, age/sex, unedrlying conditions, central venous catheter, corticosteroid and broadsectrum antibiotic use, mechanical ventilation, duration of hospitalization, antifungal treatment with doasge and duration, and finally outcome. These data are recommended to be used instead of the phenotypic analysis and the overall findings from this is encouraged to be discussed in discussion. Clearly most of the patients infected with azole resistant isolates are azole-naive and this finding should be discussed in the context of clinical data and that such infections were either acquired horizontally or from other unknown sources.

3. Instead of Table 1, authors can present a comprehensive table, where the MIC of each isolate along with amino acid substituted and also the fold expression of the genes studied can be shown. This way the data is more clear. Also please remove Figure 1.

4. The basis for choosing the genes studied by RT-qPCR has not been clarified. Have authors inferred this from RNAseq analysis of a specific fluconazole resistant C. tropicalis isolate? This needs to be clarified and clearly link their association with azole resistance to solidify the philosophy behind their inclusion in the current study.

5. Please explain which fluconazole dosage and duration was used to study the inducible expression of the target genes? This should be explicitly introduced in the results section.

6. Lines 240-247 do not deserve to be a separate heading and it should be a paragraph furthering the previous heading (line 208).

7. Sections dealing with homology modeling and docking analysis are not necessary given that this is a very well-known mutation, which confers azole resistance in various Candida species.

Reviewer #2: General comments

This study investigated the molecular mechanisms of azole resistance in Candida tropicalis, an emerging challenge in Asia, even globally. Like the resistant mechanisms in other Candida species, numbers of papers have illustrated several mechanisms involving ergosterol biosynthesis pathway or upregulation of efflux pumps in C. tropicalis. The findings in the present study not only echoed those in the previous research but also provided insight into the stress response pathways. The manuscript contains interesting data but also has some issues warranted further clarification with respect to methods and presentation.

Specific comments

1. The authors need to describe the methods for quantitative RT-PCR in details, especially the conditions of drug induction and the reference for calculation of relative gene expression in each strain. How many untreated control strains (Line 232) were used?

2. Based on 2-∆∆CT method (Line 232), all relative expression levels are theoretically above zero. But it’s unusual to depict negative values shown in the current figures and supplementary figures. Please check relative expression levels in each gene for all strains tested again. If indicated, please calculate the statistics among three groups (R-WM, R-WTM, and Susceptible) and revise the manuscript accordingly.

3. Among two nonsynonymous mutations (A395T and C461T) identified in the ERG11 gene, C461T dosen’t confer azole resistance per se by the site-direct mutagenesis experiment (reference 14). Please revise Line 360-361 accordingly.

4. In the current study, these two ERG11 mutations were simultaneously evaluated by the bioinformatics approaches. It’s interesting to test the impact of C461T on azole resistance by performing the homology modelling and molecular docking of single mutation.

5. Please provide the reference strain to determine the molecular alternations in ERG1, ERG3, UPC2, and TAC1 genes.

6. Please note that T503C in UPC2 gene has been reported among azole resistant C. tropicalis (https://doi.org/10.3390/jof7080612). Please revise Line 375-377 accordingly.

7. Throughout the manuscript, the gene names need to be italicized (Line 198 as an example), while protein names are not.

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6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

Reviewer #2: No

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24 Apr 2022

Editor comments:

Comment: The experimental parameters need to be stated and more clearly described.

Relative expression levels need to be readdressed as discussed by reviewer #2

Review the discussion and conclusions to confirm they reflect results (see reviewer #2) and also identify content that has already been reported (reviewer #1).

Please consider all the comments of the reviewers and if you think their suggestions would improve what you are trying to emphasize.

Response: Thank you for considering our manuscript in your esteemed journal. We have tried our best to address all the issues raised by the Academic Editor and Reviewers. We addressed the query of the second reviewer on the relative expression level. We modified the discussion and conclusion as per the suggestion of the second reviewer and also address the concerns of the first reviewer.

Comment: Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Response: We are submitting the rebuttal letter containing each point raised by the academic editor and reviewers.

We are also sending one copy of the ‘Revised Manuscript with Track Changes’ and one clean copy of the revised version labeled as ‘Manuscript’.

Comment: If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

Response: Required modifications in the financial disclosure has included in the updated statement of the cover letter.

Comment: Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

Response: We are resubmitting the figure files according to the guidelines of this journal.

Reviewers’ comments:

Reviewer's Responses to Questions:

Comments:

1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

3. Have the authors made all data underlying the findings in their manuscript fully available?The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

Response: Thank you so much for your appreciation and positive responses.

Review Comments to the Author:

Reviewer #1

Although this paper could be potentially of interest, it suffers from including findings, which have been obviously and repeatedly reported elsewhere. Examples are below,

Comment 1: It is not clear why authors attempted to undertake the phenotypic assay, while antifungal susceptibility profile clearly showed that fluconazole at low doses was inhibitory for susceptible isolates, but not for resistant ones. Basically, this phenotypic assay is redundant and is suggested to be removed from the study.

Response: Thank you so much for your valuable suggestion. We removed the phenotypic assay from the revised manuscript.

Comment 2: Clinical profile of such isolates to be presented in an informative table, where authors include the following details, age/sex, unedrlying conditions, central venous catheter, corticosteroid and broad-spectrum antibiotic use, mechanical ventilation, duration of hospitalization, antifungal treatment with doasge and duration, and finally outcome. These data are recommended to be used instead of the phenotypic analysis and the overall findings from this is encouraged to be discussed in discussion. Clearly most of the patients infected with azole resistant isolates are azole-naive and this finding should be discussed in the context of clinical data and that such infections were either acquired horizontally or from other unknown sources.

Response: Thank you so much for your suggestion. All the available clinical details have been added to table 1. However, we were unable to retrieve the complete clinical details of all patients. The clinical aspects not mentioned in the table 1 have discussed in the discussion section of the revised manuscript.

Comment 3: Instead of Table 1, authors can present a comprehensive table, where the MIC of each isolate along with amino acid substituted and also the fold expression of the genes studied can be shown. This way the data is more clear. Also please remove Figure 1.

Response: Thank you so much for your meticulous comments. We are presenting the MIC of the isolates with amino acid substitution in Table 1 in the revised manuscript. We think the fold expression will not be best suited to the table format. Therefore, we are presenting the expression date in graph format in the figures. As per your suggestion, Figure 1 has been removed from the revised manuscript.

Comment 4: The basis for choosing the genes studied by RT-qPCR has not been clarified. Have authors inferred this from RNAseq analysis of a specific fluconazole resistant C. tropicalis isolate? This needs to be clarified and clearly link their association with azole resistance to solidify the philosophy behind their inclusion in the current study.

Response: Thank you so much for your query. Unfortunately, we could not perform the RNAseq analysis due to the unavailability of adequate funds. The genes were selected based on the existing literature on azole resistance in different Candida species. The published articles on these genes are cited in this manuscript and also in our previously published article on the dynamics of in vitro development of azole resistance in Candida tropicalis (doi: 10.1016/j.jgar.2020.04.018).

Comment 5: Please explain which fluconazole dosage and duration was used to study the inducible expression of the target genes? This should be explicitly introduced in the results section.

Response: As per your suggestion, we explained the fluconazole doses and duration of drug exposure to study the expression of target genes in the result section of the revised manuscript.

Comment 6: Lines 240-247 do not deserve to be a separate heading and it should be a paragraph furthering the previous heading (line 208).

Response: We removed the heading for lines 240-247 and it is included as a paragraph with the previous heading. Relevant modifications have been made in the revised manuscript.

Comment 7: Sections dealing with homology modeling and docking analysis are not necessary given that this is a very well-known mutation, which confers azole resistance in various Candida species.

Response: To the best of our knowledge, the exact role of the non-synonymous alteration in azole resistance has not been elucidated yet. It is known that tyrosine (Y) is an aromatic amino acid and is preferentially substituted by amino acids with similar properties and considering the fact that phenylalanine (F) is the precursor of tyrosine, it is a likely substitution in the ERG11. We confirmed for the first time that substitutions of Y132F and S154F hindered the formation of Pi-Pi and Pi-cation interaction between the cofactor and the ligand molecules thereby dipping the overall binding energy of the mutated docked complex. Therefore, for the present study homology modeling and docking analysis are innovative and help in understanding the effect of the mutations in drug binding, particularly in the context of C. tropicalis. With your permission, we wish to retain the homology modeling and docking data in the revised manuscript.

Reviewer #2:

This study investigated the molecular mechanisms of azole resistance in Candida tropicalis, an emerging challenge in Asia, even globally. Like the resistant mechanisms in other Candida species, numbers of papers have illustrated several mechanisms involving ergosterol biosynthesis pathway or upregulation of efflux pumps in C. tropicalis. The findings in the present study not only echoed those in the previous research but also provided insight into the stress response pathways. The manuscript contains interesting data but also has some issues warranted further clarification with respect to methods and presentation.

Comment 1: The authors need to describe the methods for quantitative RT-PCR in details, especially the conditions of drug induction and the reference for calculation of relative gene expression in each strain. How many untreated control strains (Line 232) were used?

Response: Thank you so much for your valuable suggestions. We described the method for RT-qPCR in detail in the method section of the revised manuscript.

The conditions of drug induction are included in the result section of the modified manuscript.

In our previously published study on the selection and evaluation of appropriate reference genes for RT-qPCR-based expression analysis in Candida tropicalis following azole treatment, we confirmed that EF1 is the most stable reference gene. Therefore, we used elongation factor 1α (EF1) as a reference gene for the calculation of relative gene expression in each strain.

The drug-induced expression for each isolate was calculated with respect to the drug untreated control for the same isolate along with the reference gene. Therefore, the number of drug-treated samples is the same as the control.

Comment 2: Based on 2-ΔΔCT method (Line 232), all relative expression levels are theoretically above zero. But it’s unusual to depict negative values shown in the current figures and supplementary figures. Please check relative expression levels in each gene for all strains tested again. If indicated, please calculate the statistics among three groups (R-WM, R-WTM, and Susceptible) and revise the manuscript accordingly.

Response: We calculated the gene expression using 2-ΔΔCT method based on the study entitled “Analyzing real-time PCR data by the comparative CT method” by Thomas D Schmittgen & Kenneth J Livak (doi:10.1038/nprot.2008.73). According to this study, if the CT for the treated sample is higher than the untreated sample, the level of gene expression is -1/calculated fold change. The result will be negative and which confirms that the expression is reduced due to treatment. In our study, the negative values shown in the current figures and supplementary figures confirm that drug treatment decreased the expression of the genes when compared with their untreated control. There according to us, the calculation for the gene expression is perfect and flawless.

Comment 3: Among two nonsynonymous mutations (A395T and C461T) identified in the ERG11 gene, C461T doesn’t confer azole resistance per se by the site-direct mutagenesis experiment (reference 14). Please revise Line 360-361 accordingly.

Response: Thank you so much for your valuable suggestion. Relevant changes have been made in the revised manuscript.

Comment 4: In the current study, these two ERG11 mutations were simultaneously evaluated by the bioinformatics approaches. It’s interesting to test the impact of C461T on azole resistance by performing the homology modelling and molecular docking of single mutation.

Response: As per your suggestion, we performed the homology modelling and molecular docking of the C461T single mutation and have presented the results for your reference below. However, since the results do not seem to add much to the current manuscript we have not added them to the revised draft.

The figures showed that Serine/Phenylalanine at 154 position does not interact with the Heme and any of the 2 drugs. Indicating that the amino acids are not associated with drug interaction unlike Tyrosine 132 position which forms a bond with the drugs. Both Serine and Phenylalanine form polar bonds with their neighboring amino acids and the number of bonds decreases as Serine mutates to Phenylalanine from 7 to 4.

A) The superimposed S154F mutation with native structure in a Fluconazole and protein complex. Tyrosin 132 (green), Heme (red), Fluconazole (Blue), S154 (orange) superimposed by F154 (purple). The S154F does not interact with the fluconazole heme Tyrosine 132 complex.

A.1. The polar bond among the Serine 154 (orange) residues and its neighboring amino acids (purple) indicated by yellow dotted lines, while the ligands heme (red) and Fluconazole (blue) are in polar bond with Tyrosine (cyan) and neighboring amino acids (purple) and A.2. Polar bonds between mutated phenylalanine 154 residue (green) in polar contact with neighbouring amino acids and no change in the polar bonds between Heme, Fluconazol and Tyrosine 132

A.1 A.2

B) Fig shows the superimposed S154F mutation with native structure in a Voriconazole and protein complex Tyrosin 132 (cyan), Heme (red), Voriconazole (Blue) , S154 (orange) superimposed by F154 (green)

B.1. Fig shows the polar bond among the Serine 154 residues (green) and the neighboring amino acids. The heme and voriconazole interact with Tyrosine 132(cyan) independent of Serine and B.2. Polar interaction between phenylalanine (light blue) and the neighboring amino acids (in purple).

B.1 B.2

Comment 5: Please provide the reference strain to determine the molecular alternations in ERG1, ERG3, UPC2, and TAC1 genes.

Response: The details of the reference strain have been included in the modified manuscript.

Comment 6: Please note that T503C in UPC2 gene has been reported among azole resistant C. tropicalis (https://doi.org/10.3390/jof7080612). Please revise Line 375-377 accordingly.

Response: We agree with you and the lines have been modified in the revised manuscript.

Comment 7: Throughout the manuscript, the gene names need to be italicized (Line 198 as an example), while protein names are not.

Response: The gene and protein names are corrected as per the suggestion and relevant changes have been included in the modified and revised manuscript.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

27 May 2022

Mechanisms of azole antifungal resistance in clinical isolates of Candida tropicalis

PONE-D-21-29687R1

Dear Dr. Ghosh,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Joy Sturtevant

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: As shown in example 1 of the reference 27 (10.1038/nprot.2008.73), the value of 2-ΔΔCT<1 implies that there was a reduction in the expression due to treatment. If the authors choose to present the level of gene expression as -1/calculated fold change for which CT for the treated sample is higher than the untreated sample, it would be better to describe briefly regarding this methodology in the method section.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

4 Jul 2022

PONE-D-21-29687R1

Mechanisms of azole antifungal resistance in clinical isolates of Candida tropicalis

Dear Dr. Ghosh:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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If we can help with anything else, please email us at plosone@plos.org.

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on behalf of

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