{"paper_id":"a1e4b8ee-7b62-4fa5-a1aa-c5f2b8baf72a","body_text":"1 \n \nAntifungal exposure can enhance Candida glabrata pathogenesis 1 \n 2 \nGabriela Fior Ribeiro1,a, Weronika Danecka2, Logan Tomlinson1, Edward W.J. Wallace2, Delma 3 \nS. Childers*1 4 \n 5 \n1 University of Aberdeen, Institute of Medical Sciences, Aberdeen Fungal Group, Aberdeen, 6 \nAB25 2ZD, UK 7 \n2 University of Edinburgh, School of Biological Sciences and Centre for Engineering Biology, 8 \nEdinburgh, EH9 3BF UK 9 \n 10 \naCurrent address: University of Guelph, Department of Molecular and Cellular Biology, Ontario, 11 \nN1H 5N4, Canada 12 \n 13 \n*Corresponding author: 14 \nDr Delma S. Childers 15 \n(email) delma.childers@abdn.ac.uk 16 \n(telephone) +44 1224 437495 17 \n 18 \n 19 \n  20 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n2 \n \nAbstract 21 \n 22 \nAzole antifungal drugs directly inhibit lanosterol 14-ɑ-demethylase and indirectly affect the 23 \nexpression of metabolic, transmembrane transporter, and cell wall organization genes in fungal 24 \npathogens. It is not known how these indirect azole effects depend on dose, timing, and specific 25 \nazole used, or how they influence host interactions. Candida glabrata (recently renamed 26 \nNakaseomyces glabratus) is the second leading cause of candidiasis, and clinical strains have 27 \nhigh rates of intrinsic resistance to azoles. We investigated the early responses of reference 28 \nstrains BG2 and CBS138 to sub-inhibitory doses of fluconazole and voriconazole, and 29 \nparticularly, how these responses affect host-pathogen interactions. Cell wall profiling and 30 \ntranscriptomic data revealed highly similar responses for each strain to both azoles, including 31 \nthe upregulation of several virulence factors, such as yapsins. We also observed significant 32 \nincreases in CBS138 survival in macrophages and increased virulence in Galleria mellonella 33 \nafter voriconazole exposure. Using a combination of pharmacological inhibition of calcium ion 34 \nchannels and deletion strains, we determined that voriconazole-enhanced virulence requires a 35 \nyapsin protease, YPS1, and is regulated via the calcineurin pathway and the cell wall integrity 36 \npathway, both of which regulate YPS1 expression. We also observed that voriconazole 37 \ntreatment significantly reduced the virulence of the bck1Δ strain in G. mellonella, suggesting 38 \nthat inhibitors of the cell wall integrity pathway might potentiate azole activity by improving 39 \nsusceptibility to host killing. Our study provides new insight into short-term azole adaptation in 40 \nC. glabrata, and importantly demonstrates that sub-inhibitory azole exposure can induce 41 \nvirulence factors and alter fungal pathogenesis. 42 \n 43 \nArticle summary 44 \nAntifungal drugs indirectly affect essential fungal cell processes, but we lack an understanding 45 \nof how drug-induced changes affect fungal pathogenesis. We investigated how Candida 46 \nglabrata adapts when exposed to azole drugs in terms of cell wall and transcriptional changes. 47 \nReference strains had similar transcriptional changes in response to azoles, but azole-treated 48 \nCBS138 survived better in immune cells and caused more host death than untreated cells, 49 \nsuggesting that short-term azole treatment can significantly affect pathogenesis. Voriconazole-50 \nenhanced disease requires the calcineurin and cell wall integrity pathways and the virulence 51 \nfactor, YPS1, but could be blocked by a calcium ion channel inhibitor.  52 \n  53 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n3 \n \n 54 \nIntroduction 55 \n 56 \nThere is growing awareness and understanding of the importance of antifungal drug resistance 57 \nand related phenomena in fungal pathogens, including tolerance, persistence and 58 \nheteroresistance(Amich et al., 2025; Yang & Berman, 2024). These phenotypes have 59 \nconcerning implications for clinical disease management and treatment failure, which has driven 60 \ninvestigations to understand the molecular mechanisms that permit pathogenic fungi to adapt to 61 \nantifungals. Resistance is classically linked to stable genetic mutations that allow survival in 62 \nhigh drug concentrations (Marie & White, 2009). However, other adaptive mechanisms, like 63 \ntolerance and heteroresistance, have proven more difficult to characterize due to their 64 \ntransience within the population and lack of a clear, causal link to genetic modifications (Berman 65 \n& Krysan, 2020; Rosenberg et al., 2018; Yang & Berman, 2024). Further, while antifungal 66 \nresistance mutations are known to affect Candida species cell fitness and virulence (Bohner et 67 \nal., 2022), we have a poor understanding of how other antifungal adaptive processes influence 68 \nfitness and host-pathogen interactions. 69 \n 70 \nCandida glabrata (recently renamed Nakaseomyces glabratus) is a major human fungal 71 \npathogen and the second leading cause of systemic candidiasis. C. glabrata is categorised as a 72 \nhigh priority pathogen by the World Health Organisation (WHO, 2022) due to its serious clinical 73 \nburden and high rates of antifungal resistance. Consistent with this classification, a recent 74 \nPublic Health England (PHE) surveillance study reported 17% and 21% of C. glabrata 75 \nbloodstream clinical isolates as resistant to fluconazole and voriconazole, respectively (Budd et 76 \nal., 2023). In comparison, only 1% of clinical isolates of the leading cause of candidiasis, 77 \nCandida albicans, were resistant to fluconazole or voriconazole in the same study (Budd et al., 78 \n2023). Despite these high levels of azole resistance, fluconazole or voriconazole are sometimes 79 \nstill prescribed to patients with suspected fungaemias (Helmstetter et al., 2022). 80 \n 81 \nAzoles directly inhibit lanosterol 14-ɑ-demethylase (encoded by ERG11 in Candida species) 82 \nleading to reduced ergosterol production, toxic sterol intermediate accumulation, and altered 83 \nmembrane fluidity. These processes also indirectly affect the expression of carbohydrate 84 \nmetabolism, transmembrane and ion transporters, and cell wall organization genes (Ribeiro et 85 \nal., 2022). Little is known about the early cellular adaptations that pave the way for C. glabrata 86 \nsurvival and drug resistance development in the host. We expect, based on existing 87 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n4 \n \ntranscriptomics and proteomics datasets, that the indirect effects of azole exposure on cell wall 88 \norganisation and other biological processes alters host interactions. However, the effects of 89 \nazole treatment on C. glabrata host-pathogen interactions are unclear. 90 \n 91 \nIn this study, we investigated the early adaptative responses of two C. glabrata reference 92 \nstrains, BG2 and CBS138, to sub-inhibitory doses of fluconazole and voriconazole, and 93 \nparticularly, how these responses affect host-pathogen interactions. We expected, based on our 94 \nprevious review of -omics datasets and the similarities in both drug class and reported 95 \nresistance rates by PHE, that voriconazole and fluconazole might exert similar effects on cell 96 \nwall remodeling and host-pathogen interactions (Budd et al., 2023; Ribeiro et al., 2022). While 97 \ntranscriptional and cell wall profiling data highlighted similar responses for each strain to both 98 \nazoles, we unexpectedly observed that CBS138 survival in macrophages and virulence in 99 \nGalleria mellonella infection studies was significantly improved after voriconazole exposure. 100 \nFluconazole pre-exposure also mildly enhanced both BG2 and CBS138 virulence in 101 \nG. mellonella. We further demonstrated that voriconazole-enhanced virulence in CBS138 is at 102 \nleast partially dependent on the virulence factor and yapsin, YPS1, and the pathways required 103 \nfor YPS1 expression, including calcium ion channel signaling, the calcineurin pathway, and the 104 \nSlt2-MAPK (PKC) cell wall integrity pathway. Importantly, our study demonstrates how short-105 \nterm adaptation to antifungals can induce survival strategies that enhance fungal pathogenesis. 106 \n 107 \nMaterials and Methods 108 \n 109 \nStrains and Growth Conditions 110 \nC. glabrata reference strains BG2 and CBS138 (ATCC2001) (Cormack & Falkow, 1999; Dujon 111 \net al., 2004; Koszul et al., 2003; Schwarzmuller et al., 2014) were maintained by sub cultivation 112 \non YPD plates (2% glucose, 2% bactopeptone, 1% yeast extract) at 37°C from a frozen stock (-113 \n80°C). 114 \n 115 \nBefore each experiment, yeast cells were conditioned overnight in 5 or 25 mL MOPS-buffered 116 \nliquid RPMI-1640 medium (final concentration: 2% glucose, MOPS 0.165 mol/L, pH 7) (Sigma 117 \nR6504) at 37°C, 200 rpm. Yeast cells were back-diluted from overnight cultures (1x106 cells/mL) 118 \nfor a further 4 hours growth in 10, 50 or 100 mL RPMI-1640 with antifungals (MIC50 119 \nconcentrations, Table 1), 50 µg/mL verapamil (Sigma), or DMSO (Sigma) only according to 120 \nexperimental requirements. 121 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n5 \n \n 122 \nMinimum Inhibitory Concentration (MIC) Determination 123 \nMIC testing was performed according to EUCAST guidelines ((The European Committee on 124 \nAntimicrobial Susceptibility Testing, 2020). Briefly, C. glabrata yeast cells were grown overnight 125 \nin MOPS-buffered RPMI-1640 at 37°C. Cells were then centrifuged for 5 minutes, 7000 rpm, 126 \nand the pellet was resuspended in RPMI-1640. 1x105 yeast cells were added to each well in a 127 \n96 well plate in 90 μL RPMI-1640 and 10 μL of the respective drug dilution. Drug test ranges 128 \nwere 0.125-64 mg/L for fluconazole and 0.0156-8 mg/L for voriconazole. Plates were incubated 129 \nfor 24 hours at 37°C in the dark. The plates were then read on a spectrophotometer (VersaMax, 130 \nSoftMax® Pro 7 Software), OD530, and the MIC50 and MIC80 for each strain and drug 131 \ncombinations were determined as the lowest concentration of drug needed to inhibit 50% or 132 \n80%, respectively, of cell growth. 133 \n 134 \nFlow Cytometry 135 \nTo analyse cell wall carbohydrate exposure, cells grown with and without antifungals were 136 \ninactivated overnight in 50 mM thimerosal (Sigma). Cells were then washed three times with 137 \nPBS and counted by haemocytometer.  2.5x106 cells were stained with 0.5 µg/mL Fc-Dectin-1 138 \n(kindly provided by Gordon Brown, MRC-CMM) and 1:200 diluted goat anti-human IgG antibody 139 \nconjugated to Alexa Fluor 488 (Invitrogen), 50 µg/mL Wheat Germ Agglutinin (WGA) conjugated 140 \nto Alexa Fluor 680 (Invitrogen), and 25 µg/mL Concanavalin A (ConA) conjugated to Texas Red 141 \n(Invitrogen). Data were acquired for a minimum of 20,000 events on the Attune NxT (Thermo 142 \nFisher) and analysed using FlowJo v10 software (TreeStar Inc.) and gated as previously 143 \ndescribed (Ribeiro et al., 2025). 144 \n 145 \nTransmission Electron Microscopy (TEM) 146 \nYeast cells were grown overnight in 5 mL RPMI-1640 (37°C, 200 rpm), counted, and 1x108 cells 147 \nwere back-diluted and grown for a further 4 hours in 100 mL RPMI-1640 at 37°C, 200 rpm, 148 \ncontaining voriconazole (MIC50) or DMSO (solvent control). Cells were then centrifuged at 4,000 149 \nrpm for 5 minutes. The concentrated pellet was placed between the sides of a small copper 150 \nholder, enough to fill up the required space. Cells were then frozen in a high-pressure freezer 151 \nand rapid transport system (Leica EMPACT2). Freeze substitution was carried out following the 152 \nprogram detailed in Supplemental Table 2. Samples were then removed and placed in 10% 153 \nSpurr’s (TAAB):Acetone for 72 hours – 30% Spurr’s overnight; 50% Spurr’s for 8 hours; 70% 154 \nSpurr’s overnight; 90% Spurr’s for 8 hours. Subsequently, samples were embedded in Spurr’s 155 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n6 \n \nresin at 60°C for at least 24 hours. Then 90nm sections were prepared using a diamond knife 156 \n(Diatome Ltd, Switzerland) onto copper grids (EMResolutions) using a Leica UC6; and with 157 \nUranyless (TAAB) and Lead Citrate in a Leica AC20. Samples were viewed on the 158 \nTransmission Electron Microscope JEM 1400 plus (JEOL) and captured using an AMT 159 \nUltraVUE camera (AMT). Image J (Fiji) was used to measure the thickness of the inner (chitin 160 \nand glucan) and outer (mannan) cell wall of 19-30 cells/group and 10-13 measurements/cell.  161 \n 162 \nBMDM Challenge 163 \nBone Marrow-Derived Macrophages (BMDMs) were isolated from the femurs and tibias of male 164 \n12-weeks old C57BL/6 mice as previously described (Davies & Gordon, 2005; Gonçalves & 165 \nMosser, 2015). Mice were a kind gift from Gordon Brown and were randomly selected from in-166 \nhouse breeding colonies housed under specific-pathogen-free conditions at University of 167 \nAberdeen. Mice were not subjected to any regulated procedures prior to cervical dislocation and 168 \nfemur removal in accordance with ethical regulations approved by the University of Aberdeen 169 \nAnimal Welfare and Ethical Review body and the ARRIVE guidelines. BMDMs were maintained 170 \nand differentiated in Dulbecco’s modified Eagle’s medium (DMEM; Sigma) supplemented with 171 \n10% heat inactivated Fetal Calf Serum (Gicbo), 15% L929 cell conditioned medium, 1% L-172 \nglutamine (Sigma), and 1% Penicillin/Streptomycin (Sigma). For macrophage interaction 173 \nstudies, 3x104 BMDMs were plated on flat bottom 96-well plates and incubated overnight at 174 \n37°C, 5% CO2. BG2 and CBS138 wild-type cells were grown overnight in RPMI-1640, counted 175 \nand 1x107 cells were grown for a further 4 hours with MIC50 fluconazole, voriconazole, or <1% 176 \nDMSO in 10 mL RPMI-1640 (2% Glucose, pH 7) at 37°C. Yeast cells were then washed with 177 \nPBS and added to the 96-well plates in duplicate wells at a multiplicity of infection (MOI) of 3:1 178 \n(yeast cells to macrophages). Two hours post challenge the supernatant was removed, each 179 \nwell was washed with DMEM, and new media was added to remove unengulfed yeast cells. For 180 \nthe 2-hour timepoint 100 μL of 0.02% chilled SDS (Sodium Dodecyl Sulphate, Melford) was 181 \nadded to each well, its contents were scraped, serially diluted, spotted on YPD agar plates and 182 \nincubated at 37°C. The same BMDM lysis and yeast recovery procedure was performed after 183 \n24 hours co-culture to determine CFU/mL and fold change in yeast cell recovery. 184 \n 185 \nGalleria mellonella Infection, Survival and Melanization 186 \nG. mellonella larvae were purchased from Livefood UK Ltd. (Axbridge, UK) and stored in wood 187 \nshavings in the dark at room temperature prior to infection. C. glabrata yeast cells were grown 188 \novernight in 6 mL RPMI-1640 at 37°C, 200 rpm, and back-diluted to 1x108 yeast cells in 100 mL 189 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n7 \n \nRPMI-1640 with the indicated antifungals at MIC50 concentration or equivalent volume solvent, 190 \nfor a further 4 hours growth at 37°C, 200 rpm. Cells were washed and resuspended in sterile 191 \nPBS. Larvae (~250 mg weight) were randomly allocated into groups (specific sample sizes 192 \nindicated on figure legends) and infected in the last left proleg with 5x106 cells in a 50 μL/larvae 193 \nsuspension using a U-100 30G Micro-fine syringe (BD). Control groups were injected with 50 μL 194 \nsterile saline only. Larvae were incubated at 37°C in the dark and survival and melanisation 195 \nwere assessed daily for a period of 6 days (144 hours). Larvae were scored for melanization as 196 \ndescribed previously (Usher et al., 2023). Briefly, larvae were considered partially melanised 197 \nwhen their natural colour had been visibly altered, however they still did not present a fully 198 \ndarkened body. Larvae were considered fully melanised when their colour had been completely 199 \naltered to a dark grey/brown pigmentation. 200 \n 201 \nStatistical Analyses 202 \nStatistical analyses were performed using GraphPad Prism v5.0 software (GraphPad Software) 203 \nand IBM SPSS Statistics v27.0 (IBM Corp.). Specific experimental analyses described on figure 204 \nlegends. Macrophage-yeast survival and flow cytometry were analysed by Two-way ANOVA 205 \nwith Dunnett’s multiple comparisons test. TEM measurements were analysed by Two-Way 206 \nANOVA with Sidak’s multiple comparisons test. G. mellonella survival was analysed by Kaplan-207 \nMeier, Log-Rank pairwise over strata. A p value of <0.05 was considered to be significant, and 208 \nthe results are shown as mean ± standard error of the mean (SEM). 209 \n 210 \nRNA sequencing 211 \nStrains were streaked to single colonies on YPD agar plates for 2 days, then a single colony 212 \ninoculated for each biological replicate into 5 mL RPMI-1640 with 2% glucose (Sigma R6504) 213 \nand grown overnight. The next day, 108 cells were pelleted and inoculated into 50 mL of RPMI-214 \n1640 media with 2% glucose pre-warmed to 37°C with drug or DMSO (mock) treatment. For 215 \ndrug addition, stock solutions of VCZ or fluconazole were prepared in DMSO, and the solution 216 \nmixed with RPMI media immediately before inoculation.  Antifungals were added at MIC50 217 \nconcentration: VCZ at 0.25 ug/mL or 0.125 ug/mL for BG2 and CBS138, respectively; FCZ at 16 218 \nug/mL or 8 ug/mL for BG2 and CBS138, respectively. Mock-treatment was performed using 219 \n0.004% DMSO, and DMSO was added to all VCZ and FCZ treatments to the final concentration 220 \nof 0.004%.  221 \n 222 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n8 \n \nAfter inoculation, cells were grown for 4 hours at 37°C with 200 rpm shaking, and harvested by 223 \npelleting cells for 3 min at 4000 rpm, the supernatant was decanted, and the cells were pelleted 224 \nfor 2 min at 3000 g to remove all supernatant, and the pellet frozen in liquid nitrogen, and stored 225 \nat -80°C. Three biological replicates were prepared on successive days. 226 \n 227 \nRNA was extracted using a modified silica column protocol following bead-beating with zirconia 228 \nbeads. The yeast pellets were thawed briefly on ice, then transferred to a screw cap tube and 229 \n200 μL of zirconia beads were added. 400 μL of RNA binding buffer (R1013, Zymo Research) 230 \nwas added, and the mixture was kept on ice for 1 minute. The tubes were transferred to 231 \nPreCellys homogenizer (Bertin Technologies) and lysed using the following protocol: 10 232 \nseconds vortexing, followed by 10 seconds of waiting, repeated 3 times. The cells were then 233 \ntransferred to ice for 1 minute. Vortexing and incubation on ice were repeated a total of 6 times. 234 \nThe tubes were then centrifuged at 12,000 × g for 2 minutes. The supernatant was transferred 235 \nto a Zymo Spin IIICG column (C1006, Zymo Research) and centrifuged at 12,000 g for 1 236 \nminute. 400 μL of ethanol was added to the flow through, mixed, transferred to a Zymo Spin IIC 237 \ncolumn (C1011, Zymo Research) and centrifuged for 1 minute. The column was washed with 238 \nDNA/RNA Prep buffer (D7010-2, Zymo Research) and centrifuged for 1 minute, and then 239 \nwashed with DNA/RNA Wash buffer (D7010-3, Zymo Research) and centrifuged for 1 minute 240 \ntwice. The column was then transferred to a clean 1.5 mL tube, and RNA was eluted by adding 241 \n30 μL of water and centrifuging at 10,000 × g for 1 minute. The concentration of the samples 242 \nwas measured using Denovix. The quality and integrity of RNA was assessed on Fragment 243 \nAnalyzer (Agilent) using High Sensitivity RNA Kit (DNF-472-1000, Agilent). RQN and 28S/18S 244 \nratio were used to determine the quality of the sample. 245 \n 246 \nRNA sequencing libraries were prepared from 500 ng total RNA using QuantSeq 3′ mRNA-Seq 247 \nV2 Library Prep Kit REV (Lexogen, Vienna, Austria), a method that sequences a single 248 \nfragment per mRNA, at the 3′ end proximal to the poly(A)-tail. Libraries were sequenced on 249 \nNextSeq 2000 (Illumina, San Diego, USA) 250 \n 251 \nRNA-Seq FASTQ files were processed using a Nextflow pipeline for QuantSeq data which is 252 \navailable online in GitHub (https://github.com/DimmestP/nextflow_paired_reads_pipeline). 253 \nSoftware versions used were (Nextflow 3.1, FastQC 0.12.1, Cutadapt 4.3, HISAT2 2.2.1, 254 \nSAMtools 1.17, MultiQC 1.14, BEDTools 2.30.0, Subread /FeatureCounts 3.11.3, DESeq2 255 \n1.40.2, Python 3.11.3, R 4.3.2, NCBI Datasets CLI 16.0.0) (Danecek et al., 2021; Di Tommaso 256 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n9 \n \net al., 2017; Ewels et al., 2016; Kim et al., 2019; Liao et al., 2014; Love et al., 2014; Martin, 257 \n2011; O'Leary et al., 2024; Quinlan & Hall, 2010; Wingett & Andrews, 2018). The reads were 258 \naligned to the genome sequence, for strain BG2: GCA_014217725.1; For CBS138, 259 \nGCF_000002545.3. For assigning 3′ fragments to mRNAs, we used stranded alignment with an 260 \nannotation file including 300nt added to the 3′ end of the annotated CDS.  Differential gene 261 \nexpression was performed using DESeq2 (Love et al., 2014), R (R Core Team, 2021) and 262 \npackages from the tidyverse (Wickham et al., 2019), and code is shared in GitHub 263 \n(https://github.com/ewallace/cglab_rnaseq/). Genes were called as differentially expressed if 264 \nthey showed at least 2-fold difference at an adjusted p-value of 0.05 (5% false discovery rate), 265 \nunless otherwise stated. 266 \n 267 \n 268 \nResults 269 \n 270 \nCell wall polysaccharide exposure is affected by sub-inhibitory azole treatment 271 \nWe first investigated inhibitory concentrations of fluconazole (FCZ) and voriconazole (VCZ) for 272 \nC. glabrata with the aim of identifying concentrations that impose significant stress while 273 \nmimicking treatment failure (i.e. failure to completely inhibit or kill cells). We performed minimum 274 \ninhibitory concentration (MIC) testing in accordance with EUCAST guidelines (The European 275 \nCommittee on Antimicrobial Susceptibility Testing, 2020). The concentration required to inhibit 276 \n50% of growth (MIC50) for CBS138 in FCZ and VCZ was 8 mg/L and 0.125 mg/L, respectively 277 \n(Table 1). In comparison, the MIC50 for BG2 was 16 mg/L FCZ and 0.25 mg/L VCZ (Table 1), 278 \nsuggesting CBS138 is mildly more susceptible than BG2 to azole inhibition. This susceptibility 279 \nwas more pronounced for the MIC80 (concentration of drug required to inhibit at least 80% of 280 \ngrowth compared to the control), where BG2 was four times more resistant to FCZ (64 mg/L 281 \nversus 16 mg/L) and twice as resistant to VCZ (4 mg/L versus 2 mg/L) compared to CBS138 282 \n(Table 1). 283 \n 284 \nPrevious studies demonstrated that antifungal treatment leads to differential cell wall gene 285 \nexpression and significant changes in the cell wall that can have paradoxical effects on survival 286 \nin C. albicans mammalian infections (Hopke et al., 2018; Lee et al., 2012; Walker et al., 2008). 287 \nTherefore, we next tested whether short-term (4-hour) MIC50 antifungal exposure affected yeast 288 \ncell wall polysaccharide detection among the C. glabrata reference strains, BG2 and CBS138. 289 \nCell wall features in BG2 were not majorly affected by FCZ or VCZ pre-treatment (Fig. 1a-c). In 290 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n10 \n \nCBS138, there was a minor increase in β- glucan (~1.21 and 1.27 fold-change for FCZ and 291 \nVCZ, respectively) and chitin (~1.23 and ~1.16 fold-change for FCZ and VCZ, respectively) 292 \nexposure levels in response to both azoles (Fig. 1a and 1c) compared to untreated cells. 293 \nMannan exposure was also significantly higher for CBS138 compared to BG2 (~1.45 and ~1.48 294 \nfold-change for FCZ and VCZ, respectively) (Fig. 1b).  295 \n 296 \nCell wall layer measurements by TEM further show that BG2 yeast cells pre-exposed to VCZ 297 \nhad slight differences in inner and outer wall thickness. BG2 cells had a slight, but significant, 298 \nincrease in inner (~1.12 fold-change) layer thickness, but similar outer layer size (~1.05 fold-299 \nchange) compared to its control (Fig. 1d and 1e). However, and in contrast to BG2, CBS138 300 \ncells pre-treated with VCZ showed significantly reduced inner (~0.6 fold change; p<0.05) but 301 \nsimilar outer (~1.03 fold-change) layer thickness compared to controls (Fig. 1d and 1f). 302 \n 303 \nTaken together, our flow cytometry data showed minimal changes in β- glucan and chitin 304 \nexposure after azole treatment which was unexpected given the changes in inner layer 305 \nthickness by TEM. However, both azoles increased mannan exposure in CBS138 compared to 306 \nBG2 (~1.9-fold; Fig. 1b), and our TEM measurement data indicates that CBS138 cells generally 307 \nhad a thicker outer cell wall layer compared to BG2 (Fig. 1d-f).  308 \n 309 \nVoriconazole exposure enhances CBS138 pathogenesis 310 \n 311 \nWe observed above that short-term FCZ and VCZ exposure differentially impacted some 312 \ncarbohydrate exposure and the gross cell wall architecture of the two C. glabrata reference 313 \nstrains, CBS138 and BG2. Cell wall composition plays an important role in modulating host 314 \nresponses, including fungal clearance by immune cells (Gow et al., 2017). Therefore, we next 315 \ntested how azole pre-exposure affected yeast survival in macrophages by measuring yeast 316 \ncolony forming unit (CFU) recovery following macrophage challenge (Ribeiro et al., 2025). 317 \n 318 \nAs before, yeast cells were treated with or without MIC50 FCZ or VCZ prior to co-incubation with 319 \nbone marrow-derived macrophages. After 2 hours of yeast-macrophage challenge, we observed 320 \nno statistically significant differences in yeast recovery from macrophages between azole-321 \ntreated and untreated groups for either strain, though there was a trend toward a greater 322 \npercentage recovery of the CBS138 inoculum from groups pre-exposed to azoles, especially 323 \nVCZ (Fig. 2a and 2b). After 24 hours of co-incubation, we still observed no significant 324 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n11 \n \ndifferences in yeast recovery between treatment groups for BG2 (Fig. 2c). However, at 24 hours 325 \nwe recovered significantly higher CFUs of VCZ-treated CBS138 cells compared to FCZ-treated 326 \ncells or the control, suggesting that VCZ-treated CBS138 cells were able to replicate better 327 \nwithin macrophages than FCZ-treated and untreated yeast cells (Fig. 2c). As expected, based 328 \non the CFUs recovered at each time point, the fold change in yeast recovery between 2 and 24 329 \nhours showed no variance for BG2 between groups and a trend of increased survival for VCZ-330 \ntreated CBS138 yeast cells compared to FCZ-treated and untreated cells (Figure 2d).  331 \n 332 \nWe next tested whether azole pre-treatment affected C. glabrata virulence in the G. mellonella 333 \nsystemic infection model. Consistent with our macrophage interaction data, we observed no 334 \nsignificant differences in G. mellonella survival during infection with azole-treated and untreated 335 \nBG2 yeast cells (Fig. 2e). For CBS138, infection with FCZ-treated yeast induced slightly faster 336 \nlarval death than the control, but VCZ-treated yeast killed larvae significantly faster than 337 \nuntreated cells (Fig. 2f; p<0.05) with a final survival difference >40% between control and VCZ-338 \nexposed infection groups. 339 \n 340 \nAltogether, our findings suggest that azole pre-treatment has minimal effects on BG2 host 341 \ninteractions, but azoles, and especially VCZ, trigger enhanced survival and virulence in 342 \nCBS138. 343 \n 344 \nTranscriptomic responses to azole drugs are broadly similar across strains 345 \nWe designed an RNA-seq experiment to identify transcriptomic changes that might explain 346 \ndifferences in azole-enhanced virulence between BG2 and CBS138. As above, we treated yeast 347 \nfor 4 hours with either FCZ or VCZ at MIC50 concentration or a mock-treated DMSO-only 348 \ncontrol. We prepared 3 biological replicates and made libraries using a 3′ mRNA-Seq approach. 349 \nExtracted RNA was high-quality and the aligned reads passed all relevant quality checks, 350 \nincluding high correlations between replicate samples (Figs S1, S2). 351 \n 352 \nTranscriptome profiles clustered both by strain and by drug treatment, as revealed by principal 353 \ncomponent analysis of the regularized log-counts (Fig 3a). Comparing principal components 1 354 \nand 2 shows that differences between strain and drug are almost orthogonal (Fig 3a) and 355 \ncontain almost 70% of the variance (Fig 3b). Transcriptome profiles from treatment by VCZ and 356 \nFCZ were very similar within each strain, both in the principal component plot (Fig 3a) and by 357 \ncorrelation analysis (Figs S1, S2). Differential gene expression analysis confirmed these 358 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n12 \n \nfindings: hundreds of genes were significantly differentially expressed between strains in each 359 \ngrowth condition, and differentially expressed between drug-treated cells and mock-treated cells 360 \nfor each strain (Fig S3). However, within-strain no significantly differentially expressed genes 361 \nwere found between FCZ and VCZ (Fig S3). We conclude that as each strain received the same 362 \n“subjective dose” of VCZ and FCZ, at the strain-specific MIC50 concentration, the transcriptomic 363 \nresponses to these two azoles were practically indistinguishable. 364 \n 365 \nThus, we break down the analysis into three main components: baseline differences between 366 \nstrains (Fig. 3c), common drug-regulated transcripts in both strains (Fig. 3d), and transcripts that 367 \nwere differentially induced in one strain compared to the other, i.e. drug-strain interactions (Fig. 368 \n3e). 369 \n  370 \nThe baseline differences between BG2 and CBS138 are extensive (Fig 3c). In the control 371 \nsamples, 194 genes had significantly higher expression in CBS138 compared to 265 in BG2 372 \n(Fig. 3c). Genes with higher expression in CBS138 are enriched in GO categories including 373 \nthose associated with cell wall assembly, cell-cell adhesion, and cell aggregation (i.e. GAS3, 374 \nSWM1, FKS3, EPA6, EPA3, ZAP1, KSS1, and several uncharacterized genes), and some 375 \ninvolved in amino acid biosynthetic processes including lysine and other amino acid 376 \nbiosynthesis (i.e. LYS9, ARG1, IDP1, MET13, LYS12, LEU2, LYS21, STR3, and several 377 \nuncharacterized genes). Genes with higher expression in BG2 are enriched in a variety of 378 \ncategories related to metabolism including trehalose metabolism (TPS2, ATH1, UGP1, 379 \nCAGL0H02387g, CAGL0K03421g), stress responses (including GCN4, MSN4, YHB1, TUP11, 380 \nNUC1, KRE29, TDH3, HSP12, SSA3, HSP78), and translation (including FRS2, TIF1, EFT2). 381 \nWe did not find a clear picture here about how baseline transcriptomic differences between 382 \nstrains could explain their different phenotypes, so focused on azole responses subsequently. 383 \n 384 \nCommon azole-regulated targets are extensive (Fig 3d) and consistent with previous datasets 385 \n(Ribeiro et al., 2022). The 258 significantly azole-induced upregulated genes are enriched in GO 386 \nterms such as lipid metabolism, organelle organization, response to chemical, and vesicle-387 \nmediated transport. Consistent with azoles targeting ergosterol production, ergosterol 388 \nbiosynthesis pathway genes were induced in both strains including ERG1, ERG2, ERG3, 389 \nERG5, ERG7, ERG11, ERG24, and ERG25 (Fig 4). Azole upregulates the multidrug resistance 390 \ntranscription factor PDR1, along with target transporters involved in drug resistance, CDR1 and 391 \nPDH1, but not the homolog SNQ2 (Fig 4a). Several yapsins, proteases which are important 392 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n13 \n \nvirulence factors that suppress host immune responses (Rasheed et al., 2018), were 393 \nupregulated in both strain backgrounds (Fig 4). The 355 significantly azole-downregulated 394 \ngenes include genes involved in ribosomal biogenesis and translation, consistent with drug 395 \ntreatment having a negative impact on growth. Full GO results are included in the online 396 \nsupplementary data. 397 \n 398 \nWe expected that transcripts that are differentially induced by azoles in CBS138 compared to 399 \nBG2 might explain the increase in virulence in azole-treated CBS138. Surprisingly, very few 400 \ngenes fall into this category: only 9 are more induced in CBS138 than BG2, and 22 vice versa, 401 \nat a false discovery rate of 5% and minimal 2-fold expression change (Fig 3e). The genes 402 \ninduced more in CBS138 include the YAP6 transcription factor, that has roles in stress 403 \nresponses (Merhej et al., 2016), and eight uncharacterized genes. The 22 genes induced more 404 \nin BG2 are largely associated with transport and metabolic processes (full list available in online 405 \nsupplemental). 406 \n 407 \nThe calcineurin pathway and its transcription factor, CRZ1, are important regulators of azole 408 \nresistance in C. glabrata (Vu et al., 2023) and provide a critical stress response to combat 409 \nazole-mediated membrane disruption in C. albicans (Onyewu et al., 2004). In our datasets, we 410 \nobserved differential expression of CRZ1-dependent genes, including induction of the 411 \ncalcineurin negative feedback regulator, RCN2, in response to azole treatment. Given the 412 \ndiverse roles calcineurin plays in cell wall maintenance, stress responses and host interaction, 413 \nwe hypothesized that the enhanced virulence of azole-treated CBS138 requires calcineurin 414 \nactivity and induction of CRZ1-dependent targets, like yapsins.  415 \n 416 \nCalcium ion channel inhibition suppresses voriconazole-enhanced virulence 417 \n 418 \nThe calcineurin pathway is typically known for its role in calcium signaling, and blocking calcium 419 \nchannels alongside azole treatment synergistically inhibits the growth of drug-resistant 420 \nC. albicans strains (Liu et al., 2016). We therefore tested the importance of calcium for azole-421 \nenhanced virulence using the drug verapamil to inhibit calcium-importing ion channels (Fig. 5a) 422 \n(Teng et al., 2008; Yu, Q. et al., 2013).  423 \n 424 \nCBS138 and BG2 cells were untreated or treated for 4 hours with 50 µg/mL verapamil, MIC50 425 \nVCZ, or a combination of both verapamil and VCZ prior to infecting G. mellonella (Fig. 5). 426 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n14 \n \nSimilar to our earlier observations (Fig. 2e), there were no significant differences in virulence for 427 \nlarvae infected with either VCZ-treated or untreated BG2 cells (Fig. 5b). Verapamil treatment 428 \nalone also did not significantly alter BG2 virulence compared to untreated yeast. BG2 cells pre-429 \ntreated with the combination of verapamil and VCZ resulted in slightly better overall larval 430 \nsurvival (~40% survival versus 25% for the control), but this was not significant compared to 431 \ninfection with untreated cells.  432 \n 433 \nWe again observed significantly enhanced virulence for CBS138 cells pre-treated with VCZ 434 \ncompared to untreated controls (p<0.01, Fig. 5c) Treatment with verapamil alone did not 435 \nsignificantly alter CBS138 virulence (Fig. 5c). However, the combination of verapamil and VCZ 436 \nrescued larval survival back to control levels (Fig. 5c), suggesting that calcium ion channels are 437 \nrequired for voriconazole-enhanced virulence. Indirectly, azoles may be inadvertently triggering 438 \ncalcium signaling and other pathways in a way which promotes CBS138 virulence. 439 \n 440 \nCell wall integrity, calcineurin and YPS1 are necessary for voriconazole-enhanced 441 \nvirulence in CBS138 442 \nOur verapamil study suggested that target genes downstream of the calcineurin pathway may 443 \nbe important for voriconazole-enhanced virulence in CBS138. One target of this pathway that 444 \nwas upregulated in our RNA-Seq dataset is the yapsin, YPS1, which requires both calcineurin 445 \nand cell wall integrity pathway (Slt2-MAPK) signaling for its expression (Fig. 6a) (Miyazaki et al., 446 \n2011). We used available mutants in a published gene deletion collection (Schwarzmuller et al., 447 \n2014) to test our hypothesis that calcineurin, the cell wall integrity pathway, and virulence factor 448 \nYPS1 contribute to voriconazole-enhanced virulence.  449 \n 450 \ncna1Δ, cnb1Δ, crz1Δ, bck1Δ and slt2Δ were grown for 4 hours with or without VCZ at MIC50 451 \nconcentration prior to infecting G. mellonella (Fig. 6b-f). Larvae infected with either treatment 452 \ngroup for cna1Δ, cnb1Δ, crz1Δ and slt2Δ showed no significant differences in survival at 168 453 \nhours post-infection. The only slight, but still statistically insignificant difference was for crz1Δ 454 \nduring early infection (18 hours), where we observed reduced survival for larvae infected with 455 \nuntreated cells compared to VCZ-treated cells (~40% survival versus ~70% survival, 456 \nrespectively; Fig. 6d). Surprisingly, VCZ-treated bck1Δ cells were attenuated for virulence 457 \ncompared to untreated cells. Untreated bck1Δ cells killed all larvae within 144 hours while 458 \ninfection with VCZ-treated cells resulted in ~40% survival (Fig. 6f). Overall, these data support 459 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n15 \n \nour hypothesis that Slt2-MAPK and the calcineurin pathway are necessary for the CBS138 460 \nvoriconazole-enhanced virulence phenotype. 461 \n 462 \nWe next tested yps1Δ, which we grew with and without VCZ for 4 hours prior to infecting 463 \nG. mellonella (Fig. 6g). Larvae infected with VCZ-treated or untreated yps1Δ cells died at similar 464 \nrates up to 48 hours post-infection. After 48 hours, larvae infected with VCZ-treated yps1Δ cells 465 \ndied at a slower rate than larvae infected with untreated cells in a trend similar to the bck1Δ 466 \nstrain.  467 \n 468 \nAltogether, our data suggest that the voriconazole-enhanced virulence we observed for CBS138 469 \nrequires both the cell wall integrity and calcineurin signaling pathways and their downstream co-470 \nregulated virulence factor, YPS1. 471 \n 472 \nDiscussion 473 \n 474 \nAzole treatment stalls fungal growth by directly inhibiting ergosterol biosynthesis, but also 475 \nindirectly affects cellular processes such as cell wall biogenesis (Ribeiro et al., 2022). We have 476 \na poor understanding of how the direct and indirect effects of azole treatment contribute to 477 \nfungal fitness and persistence in the host. Most studies investigate antifungal responses using a 478 \nsingle reference strain or drug. This approach is perfectly reasonable given potential issues with 479 \nstudy feasibility and cost, but makes systematic comparisons between drugs, strains and 480 \nspecies difficult. In our study, we address some of these issues by exploring the early 481 \nadaptation of two C. glabrata reference strains to two azole drugs. 482 \n 483 \nPublished transcriptomics and proteomics datasets indicated that cell wall biogenesis processes 484 \nare differentially regulated by multiple antifungal drug classes, including azoles (Ribeiro et al., 485 \n2022). The cell wall is the first point of contact between fungi and host cells, and cell wall 486 \ncarbohydrates are an important mediator of host innate immune responses. However, we 487 \nobserved few changes in cell wall carbohydrate exposure after 4 hours of FCZ or VCZ treatment 488 \n(Fig 1a-c), though we did observe differences in inner cell wall thickness in VCZ-treated cells 489 \ncompared to controls and in CBS138 mannan exposure in response to both drugs (Fig 1d-f). 490 \nOur flow cytometry probes include lectins specific for the inner cell wall carbohydrates chitin and 491 \nβ-1,3-glucan (Allen et al., 1973; Palma et al., 2006), therefore it is possible that changes in the 492 \ninner cell wall architecture are related to β-1,6-glucan abundance, which we are currently unable 493 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n16 \n \nto detect. The differences in cell wall thickness and CBS138 mannan exposure also suggest 494 \npotential changes in cell wall protein abundance, though there are limited data available 495 \ncharacterizing the fungal proteome in response to antifungal treatment (Pais et al., 2016; 496 \nRibeiro et al., 2022). Pais et al. found that clotrimazole treatment altered the abundance of 37 497 \nC. glabrata membrane proteins; however, 25 of these proteins had decreased abundance. In 498 \nC. albicans, ketoconazole treatment increased the abundance of 32 proteins, but the protein 499 \nisolation procedure was not specific to the cell wall (Hoehamer et al., 2010). Our RNA-Seq 500 \nanalysis shows evidence for differential regulation of cell wall-associated genes (Fig. 4a), but no 501 \nclear bias towards mechanisms that would be consistent with our flow cytometry profiling, such 502 \nas general upregulation of genes encoding mannoproteins.  503 \n 504 \nAzole exposure and associated minor cell wall changes did not appear to affect host 505 \ninteractions for strain BG2. Azole-treated BG2 cells had no major differences in inoculum uptake 506 \nby macrophages, intracellular survival, or virulence in G. mellonella versus untreated controls. 507 \nHowever, we observed that sub-inhibitory azole treatment altered CBS138-host interactions. 508 \nFCZ-treated cells had a mild trend towards decreased intracellular replication over 24 h and 509 \nslightly increased virulence in G. mellonella compared to control cells. VCZ-treated cells had 510 \nhigher intracellular inoculum recovery at 2 h post-macrophage co-incubation, were recovered at 511 \nsignificantly higher CFU after 24 h co-incubation with macrophages and were significantly more 512 \nvirulent in G. mellonella than control cells. While we do not yet know the reason behind these 513 \ndrug-specific effects in CBS138, others have shown that azoles can localize to multiple 514 \nsubcellular compartments, including the mitochondria (Benhamou et al., 2017; Elias et al., 2019; 515 \nKoren et al., 2024), and may have off-target effects on heme production or other processes 516 \nwhich could explain the differences in virulence phenotypes between drugs. 517 \n 518 \nWe performed RNA-Seq to determine what transcriptional changes might drive the strain- and 519 \ndrug-dependent differences we observed in C. glabrata virulence. We were surprised to 520 \ndiscover that both azoles induced nearly indistinguishable transcriptional differences for BG2 521 \nand CBS138, with only 31 genes showing altered differential expression between strains in 522 \nresponse to azoles. Most of these 31 genes are uncharacterized, and several genes 523 \nupregulated in BG2 during azole exposure are associated with metabolic processes such as 524 \nsterol uptake (TIR3), the tricarboxylic acid cycle (CAGL0L02079g, ACO2, CAGL0K11616g), and 525 \namino acid biosynthesis for methionine (MET15), lysine (CAGL0J06402g, CAGL0K07788g, 526 \nLYS9, LYS12, LYS21) and arginine (ARG8, CAGL0I08987g). Notably, the azole-induced lysine 527 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n17 \n \nbiosynthetic genes are homologous to S. cerevisiae enzymes that play a vital role in cellular 528 \ntolerance against oxidative stress (O'Doherty et al., 2014; Olin-Sandoval et al., 2019). Their 529 \nupregulation in BG2 suggests that cells mount an oxidative stress defense early during azole 530 \ntreatment, which is consistent with studies demonstrating that FCZ and other azoles induce 531 \nreactive oxygen species (ROS) in multiple Candida species (Gonzalez-Jimenez et al., 2023; 532 \nMahl et al., 2015). While azole-induction of the lysine biosynthetic pathway appeared to be 533 \nBG2-specific, it is important to note that 4 out of 5 of these genes already had significantly 534 \nelevated baseline expression in CBS138 under control conditions compared to BG2 (online 535 \nsupplemental). 536 \n 537 \nOur RNA-Seq data also indicated that azoles induced the expression of several virulence 538 \nfactors, particularly the yapsins, in both reference strains. Yapsins are 539 \nglycosylphosphatidylinositol (GPI)-linked aspartyl proteases that participate in cell wall 540 \nremodeling, immune evasion, and virulence. YPS1 and YPS5 expression is regulated by CRZ1 541 \nvia the calcineurin pathway (Chen et al., 2012), and YPS1 expression requires additional input 542 \nfrom the cell wall integrity (Slt2-MAPK) signaling pathway (Miyazaki et al., 2011). The 543 \ncalcineurin and cell wall integrity pathways play important roles in drug and stress tolerance 544 \nacross fungal pathogens. In particular, the calcineurin pathway is required for azole and 545 \ncaspofungin tolerance (Yu, S. et al., 2015), thermotolerance (Chen et al., 2012), and maximizes 546 \nC. glabrata survival in response to micafungin and manogepix treatment (Pavesic et al., 2024). 547 \nWe observed that several C. glabrata CRZ1-regulated targets were induced by both FCZ and 548 \nVCZ, including the calcineurin negative feedback regulator, RCN2 (Chen et al., 2012). The loss 549 \nof VCZ-enhanced virulence for genetic mutants in the calcineurin pathway as well as after 550 \npharmacological inhibition of calcium ion channels using verapamil (Scorzoni et al., 2020; Teng 551 \net al., 2008) strongly suggest that the calcineurin pathway is an essential component of the 552 \nCBS138 VCZ-enhanced virulence phenotype. Further, genes in the cell wall integrity pathway 553 \nand YPS1 were also necessary for CBS138 VCZ-enhanced virulence in G. mellonella. 554 \nUnexpectedly, VCZ-treated bck1Δ was significantly less virulent than control cells, and VCZ-555 \ntreated yps1Δ also had reduced virulence compared to the control, though this was not 556 \nstatistically significant. This virulence attenuation is not likely due to differences in drug cidality 557 \nbecause we obtained similar CFU compared to the controls when inocula were plated to verify 558 \ncell counts (data not shown). However, this virulence defect was not observed with slt2Δ. The 559 \nVCZ-induced virulence defect for bck1Δ and yps1Δ suggests that BCK1 and YPS1 contribute to 560 \ncompensatory processes that are necessary for C. glabrata azole adaptation independently of 561 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n18 \n \nSLT2. Further, previous work has shown that YPS1 expression was not fully repressed in the 562 \nslt2Δ background in response to thermal stress (Miyazaki et al., 2011), suggesting that low 563 \nlevels of YPS1 expression are sufficient to maintain virulence post-VCZ treatment in the slt2Δ 564 \nbackground.  565 \n 566 \nIn conclusion, our study provides fundamental insights into the baseline and azole-induced 567 \ndifferences of two key C. glabrata reference strains. We demonstrated how azole-exposure 568 \nalters CBS138 host interactions, which can be blocked by calcium ion channel inhibition (i.e. 569 \nverapamil) or deletion of key components in the calcineurin and cell wall integrity pathways. Our 570 \nstudy establishes that these pathways, in addition to contributing to cell survival and drug 571 \nresistance development, also contribute to maintaining virulence in the host after azole 572 \ntreatment and offer the prospect that interfering with cell wall integrity signaling could potentiate 573 \nazole-induced fitness defects in the host.  574 \n 575 \n 576 \n 577 \nAuthor contributions: G.F.R - experimental design, data acquisition and analysis, writing & 578 \nediting; W.D. - experimental design, data acquisition and analysis, funding acquisition, writing & 579 \nediting; L.T. - data acquisition and analysis, editing; E.W.J.W. - experimental design, data 580 \nanalysis, funding acquisition, writing & editing; D.S.C. - experimental design, data acquisition 581 \nand analysis, funding acquisition, writing & editing 582 \n 583 \nData availability 584 \nRNA-seq data are available on Gene Expression Omnibus (GEO), accession number 585 \nGSE273379. Supplemental code and GO tables are available at: 586 \nhttps://github.com/ewallace/cglab_rnaseq/. 587 \n 588 \nAcknowledgments 589 \nWe are grateful to our colleagues at the University of Aberdeen Institute of Medical Sciences 590 \ncore facilities and wish to acknowledge Andrea Holme and the Iain Fraser Cytometry Centre 591 \nand Debbie Wilkinson, Gillian Milne and Lucy Wight in the Microscopy and Histology Facility for 592 \ntraining and assistance with cytometry and microscopy. We thank our Aberdeen Fungal Group 593 \ncolleagues, especially Donna MacCallum, for helpful discussions. We thank Wallace lab 594 \nmembers for helpful discussions. We thank Richard Clarke, Angie Fawkes, and Lee Murphy for 595 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n19 \n \nperforming RNA-seq at the Genetics Core of the Edinburgh Wellcome Trust Clinical Research 596 \nFacility. We also thank Jane Usher at University of Exeter for helpful comments and discussion. 597 \n 598 \nStudy funding 599 \nThe authors are supported by the following funding sources. L.T. and G.F.R. received a PhD 600 \nstudentship from the University of Aberdeen and G.F.R. received the Elphinstone scholarship. 601 \nD.S.C. received funding from the Academy of Medical Sciences (SBF006\\1128). W.D. was 602 \nfunded by the Medical Research Council (grant number MR/N013166/1). E.W.J.W. received 603 \nfunding from the Wellcome Trust (208779/Z/17/Z). 604 \n 605 \nConflict of interest 606 \nThe authors declare no known conflicts of interest. 607 \n 608 \nReferences 609 \nAllen, A. K., Neuberger, A., & Sharon, N. (1973). 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Calcineurin signaling: lessons from Candida species. 805 \nFEMS Yeast Research, 15(4), fov016. 10.1093/femsyr/fov016 806 \n 807 \n  808 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n29 \n \nFigure Legends 809 \nFigure 1. Pre-exposure to fluconazole and voriconazole impacts yeast cell wall 810 \narchitecture for C. glabrata reference strains BG2 and CBS138. We analyzed Median 811 \nFluorescence Intensities (MFI), based on Median Absolute Deviation of flow cytometry data, for 812 \nC. glabrata reference strains BG2 and CBS138, pre-exposed or not to MIC50 fluconazole (FCZ) 813 \nor voriconazole (VCZ), for β-glucan (Fc-Dectin-1) (a), mannan (Concanavalin A, ConA) (b) and 814 \nchitin (Wheat Germ Agglutinin, WGA) exposure (c). Data represents two independent 815 \nexperiments, n = 4-6 biological replicates/group plotted as mean ± standard error of the mean 816 \n(SEM) and normalized to their respective controls (DMSO only). * p ≤ 0.05 between indicated 817 \ngroups and their respective controls. Statistical analyses were done by Two-Way ANOVA with 818 \nDunnett’s multiple comparisons test. (d) Transmission Electron Microscopy (TEM) comparison 819 \nof the cell wall of BG2 and CBS138. (e, f) TEM measurements of inner and outer cell wall 820 \nthickness for BG2 (e) and CBS138 (f), pre-exposed or not to FCZ or VCZ. Scale bars represent 821 \n100 nm. Arrow indicates separation of inner and outer layers for CBS138 pre-treated with VCZ. 822 \nn = 19-28 cells/group, 10-13 measurements/cell (maximum of 256 values plotted). Data plotted 823 \nas mean ± SEM. * p ≤ 0.05 between indicated groups. Statistical analyses were done by Two-824 \nWay ANOVA with Sidak’s multiple comparisons test. CT, control (DMSO only).  825 \n 826 \nFigure 2. VCZ pre-exposure improves CBS138 yeast cell recovery after 24-hour 827 \nchallenge with BMDMs and enhances virulence in G. mellonella. (a-d) BMDMs were 828 \nchallenged in technical duplicate at an MOI of 3:1 C. glabrata cells to macrophages. Internalized 829 \nyeast cells at 2 hours post-challenge are presented as percent of initial inoculum (a) and 830 \nCFU/mL (b). (c) Internalized yeast cells were also determined at 24 hours post-challenge. (d) 831 \nThe fold change of yeast survival was determined by the ratio of recovered cells at 24 hours vs 832 \n2 hours post-challenge. The mean and SEM are indicated by the line and whiskers on each plot. 833 \nData represents six independent experiments, n = 4-8 biological replicates per group for 834 \nmacrophage yeast survival, mean of technical replicates. Statistical analyses were done by 835 \nTwo-Way ANOVA with Dunnett’s multiple comparisons test. * p ≤ 0.05 between indicated 836 \ngroups. (e and f) G. mellonella larvae were injected with 5x106 BG2 (e) or 837 \nCBS138 (f) yeast cells that had been exposed to no treatment, FCZ or VCZ for 4 hours. Survival 838 \nwas monitored for up to 144 hours post-infection. Data represents five independent experiments 839 \nn = 10-15 larvae per group per experiment. * p ≤ 0.05 between the indicated group versus 840 \ncontrol. Statistical analyses were done by Kaplan-Meier. CT, DMSO only control.  841 \n 842 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n30 \n \nFigure 3. Azole drugs induce a consistent transcriptomic response, overlaid on strain-843 \ndependent baseline gene expression. (a) Principal Component Analysis shows that RNA-seq 844 \nsamples cluster by strain and by azole drug treatment. Principal components 1 and 2 of the 845 \nregularized logarithm of counts per gene are shown for all samples; see methods for details. (b) 846 \nBetween-sample variance is concentrated in principal components 1 and 2, that panel a shows 847 \ncluster by strain and azole treatment. (c) There are extensive baseline gene expression 848 \ndifferences between strains BG2 and CBS138. (d) A consistent azole-dependent transcriptomic 849 \nresponse is identified by pooling azole-dependent differential expression across both FCZ and 850 \nVCZ drugs across both strains BG2 and CBS138. (e) There are minimal strain-dependent 851 \ndifferences in drug-induced gene expression, detected using the interaction term in a DESeq2 852 \nanalysis with both factors (`design = ~ Strain * Drug`). See methods for details of differential 853 \ngene expression analysis across 3 biological replicates using DESeq2, and supplementary 854 \nfigure S3 for additional pairwise differential expression plots. 855 \n 856 \n 857 \nFigure 4. Azole drugs induce differential expression of specific genetic pathways. (a) 858 \nAzoles induce expression of select multidrug transporters (PDR1 transcription factor, CDR1 859 \ntransporter, PDH1 transporter, but not the SNQ2 transporter), along with multiple ergosterol 860 \nbiosynthesis genes. Azoles also induce expression of the yapsin family of aspartyl proteases. 861 \nAzoles further induce differential expression of different cell wall genes. (b) Azoles induce 862 \nexpression of multiple genes in the CRZ1 calcineurin-responsive transcription factor pathway, 863 \nand other key stress response genes. 864 \n 865 \n 866 \nFigure 5. Verapamil inhibits voriconazole-enhanced virulence. (a) Diagram of the 867 \ncalcineurin pathway. (B-C) G. mellonella larvae were injected with 5x106 BG2 (b) or CBS138 868 \nHTL (c) yeast cells that had been pre-exposed to no treatment, MIC50 VCZ, 50 µg/mL verapamil, 869 \nor both VCZ and verapamil for 4 hours. Survival was monitored for up to 120 hours post-870 \ninfection. Data represents three independent experiments n = 10 larvae per group per 871 \nexperiment. ** p ≤ 0.01 between the VCZ group versus control and VCZ+Verapamil. Statistical 872 \nanalyses were done by Kaplan-Meier. CT, DMSO only control.  873 \n 874 \n 875 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n31 \n \nFigure 6. YPS1, calcineurin pathway, and PKC pathway components are required for 876 \nvoriconazole-enhanced virulence. (a) Diagram of calcineurin and MAPK pathways 877 \ncoordinating YPS1 expression in C. glabrata. (b-g) G. mellonella larvae were injected with 5x106 878 \ncells of the indicated strain that were untreated or pre-treated with MIC50 VCZ for 4 hours. 879 \nSurvival was monitored for up to 168 hours post-infection. Data represents two independent 880 \nexperiments n = 10 larvae per group per experiment. * p ≤ 0.05 between the VCZ group versus 881 \ncontrol. Statistical analyses were done by Kaplan-Meier. CT, DMSO only control.  882 \n 883 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n32 \n \nGraphical Abstract \n \n \n  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n33 \n \nFigure 1 \n \n  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n34 \n \nFigure 2 \n  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n35 \n \nFigure 3 \n \n  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n36 \n \nFigure 4 \n \n  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n37 \n \nFigure 5 \n \n  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n38 \n \nFigure 6 \n \n \n  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint \n\n39 \n \nTable 1. Minimum inhibitory concentrations for indicated antifungals and strains \ndetermined by broth microdilution method.  \n Fluconazole Voriconazole \nStrain MIC50  MIC80 MIC50 MIC80 \nBG2 16mg/L >64mg/L 0.25mg/L 4mg/L \nCBS138 8mg/L >16mg/L 0.125mg/L >2mg/L \n \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted July 31, 2025. ; https://doi.org/10.1101/2025.07.31.667834doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}