Collateral sensitivity counteracts the evolution of antifungal drug resistance in Candida auris.
Journal
Nature microbiology
ISSN: 2058-5276
Titre abrégé: Nat Microbiol
Pays: England
ID NLM: 101674869
Informations de publication
Date de publication:
Nov 2024
Nov 2024
Historique:
received:
18
10
2023
accepted:
15
08
2024
medline:
30
10
2024
pubmed:
30
10
2024
entrez:
30
10
2024
Statut:
ppublish
Résumé
Antifungal drug resistance represents a serious global health threat, necessitating new treatment strategies. Here we investigated collateral sensitivity (CS), in which resistance to one drug increases sensitivity to another, and cross-resistance (XR), in which one drug resistance mechanism reduces susceptibility to multiple drugs, since CS and XR dynamics can guide treatment design to impede resistance development, but have not been systematically explored in pathogenic fungi. We used experimental evolution and mathematical modelling of Candida auris population dynamics during cyclic and combined drug exposures and found that especially CS-based drug cycling can effectively prevent the emergence of drug resistance. In addition, we found that a CS-based treatment switch can actively select against or eradicate resistant sub-populations, highlighting the potential to consider CS in therapeutic decision-making upon resistance detection. Furthermore, we show that some CS trends are robust among different strains and resistance mechanisms. Overall, these findings provide a promising direction for improved antifungal treatment approaches.
Identifiants
pubmed: 39472696
doi: 10.1038/s41564-024-01811-w
pii: 10.1038/s41564-024-01811-w
doi:
Substances chimiques
Antifungal Agents
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2954-2969Subventions
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 945352
Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Nature Limited.
Références
Denning, D. W. Global incidence and mortality of severe fungal disease. Lancet Infect. Dis. 24, E428–E438 (2024).
pubmed: 38224705
doi: 10.1016/S1473-3099(23)00692-8
Almeida, F., Rodrigues, M. L. & Coelho, C. The still underestimated problem of fungal diseases worldwide. Front. Microbiol. 10, 214 (2019).
pubmed: 30809213
pmcid: 6379264
doi: 10.3389/fmicb.2019.00214
Fisher, M. C. & Denning, D. W. The WHO fungal priority pathogens list as a game-changer. Nat. Rev. Microbiol. 21, 211–212 (2023).
pubmed: 36747091
pmcid: 9901396
doi: 10.1038/s41579-023-00861-x
Jermy, A. Stop neglecting fungi. Nat. Microbiol. 2, 17120 (2017).
doi: 10.1038/nmicrobiol.2017.120
Perfect, J. R. The antifungal pipeline: a reality check. Nat. Rev. Drug Discov. 16, 603–616 (2017).
pubmed: 28496146
pmcid: 5760994
doi: 10.1038/nrd.2017.46
Lockhart, S. R., Chowdhary, A. & Gold, J. A. W. The rapid emergence of antifungal-resistant human-pathogenic fungi. Nat. Rev. Microbiol. 21, 818–832 (2023).
pubmed: 37648790
doi: 10.1038/s41579-023-00960-9
Fisher, M. C., Hawkins, N. J., Sanglard, D. & Gurr, S. J. Worldwide emergence of resistance to antifungal drugs challenges human health and food security. Science 360, 739–742 (2018).
pubmed: 29773744
doi: 10.1126/science.aap7999
Satoh, K. et al. Candida auris sp. nov., a novel ascomycetous yeast isolated from the external ear canal of an inpatient in a Japanese hospital. Microbiol. Immunol. 53, 41–44 (2009).
pubmed: 19161556
doi: 10.1111/j.1348-0421.2008.00083.x
Lockhart, S. R. et al. Simultaneous emergence of multidrug-resistant Candida auris on 3 continents confirmed by whole-genome sequencing and epidemiological analyses. Clin. Infect. Dis. 64, 134–140 (2017).
pubmed: 27988485
doi: 10.1093/cid/ciw691
Rhodes, J. & Fisher, M. C. Global epidemiology of emerging Candida auris. Curr. Opin. Microbiol. 52, 84–89 (2019).
pubmed: 31279224
doi: 10.1016/j.mib.2019.05.008
Antibiotic Resistance Threats in the United States (CDC, 2019); https://www.cdc.gov/antimicrobial-resistance/media/pdfs/2019-ar-threats-report-508.pdf
Rybak, J. M., Cuomo, C. A. & David Rogers, P. The molecular and genetic basis of antifungal resistance in the emerging fungal pathogen Candida auris. Curr. Opin. Microbiol. 70, 102208 (2022).
pubmed: 36242897
pmcid: 10364995
doi: 10.1016/j.mib.2022.102208
Imamovic, L. & Sommer, M. O. Use of collateral sensitivity networks to design drug cycling protocols that avoid resistance development. Sci. Transl. Med. 5, 204ra132 (2013).
pubmed: 24068739
doi: 10.1126/scitranslmed.3006609
Munck, C., Gumpert, H. K., Wallin, A. I., Wang, H. H. & Sommer, M. O. Prediction of resistance development against drug combinations by collateral responses to component drugs. Sci. Transl. Med. 6, 262ra156 (2014).
pubmed: 25391482
pmcid: 4503331
doi: 10.1126/scitranslmed.3009940
Pal, C., Papp, B. & Lazar, V. Collateral sensitivity of antibiotic-resistant microbes. Trends Microbiol. 23, 401–407 (2015).
pubmed: 25818802
pmcid: 5958998
doi: 10.1016/j.tim.2015.02.009
Pluchino, K. M., Hall, M. D., Goldsborough, A. S., Callaghan, R. & Gottesman, M. M. Collateral sensitivity as a strategy against cancer multidrug resistance. Drug Resist. Updat. 15, 98–105 (2012).
pubmed: 22483810
pmcid: 3348266
doi: 10.1016/j.drup.2012.03.002
Hall, M. D., Handley, M. D. & Gottesman, M. M. Is resistance useless? Multidrug resistance and collateral sensitivity. Trends Pharmacol. Sci. 30, 546–556 (2009).
pubmed: 19762091
pmcid: 2774243
doi: 10.1016/j.tips.2009.07.003
Szybalski, W. & Bryson, V. Genetic studies on microbial cross resistance to toxic agents. I. Cross resistance of Escherichia coli to fifteen antibiotics. J. Bacteriol. 64, 489–499 (1952).
pubmed: 12999676
pmcid: 169383
doi: 10.1128/jb.64.4.489-499.1952
Kim, S., Lieberman, T. D. & Kishony, R. Alternating antibiotic treatments constrain evolutionary paths to multidrug resistance. Proc. Natl Acad. Sci. USA 111, 14494–14499 (2014).
pubmed: 25246554
pmcid: 4210010
doi: 10.1073/pnas.1409800111
Aulin, L. B. S., Liakopoulos, A., van der Graaf, P. H., Rozen, D. E. & van Hasselt, J. G. C. Design principles of collateral sensitivity-based dosing strategies. Nat. Commun. 12, 5691 (2021).
pubmed: 34584086
pmcid: 8479078
doi: 10.1038/s41467-021-25927-3
Tetteh, J. N. A., Olaru, S., Crauel, H. & Hernandez-Vargas, E. A. Scheduling collateral sensitivity-based cycling therapies toward eradication of drug-resistant infections. Int. J. Robust Nonlinear Control 33, 4824–4842 (2023).
doi: 10.1002/rnc.6528
Maltas, J. & Wood, K. B. Pervasive and diverse collateral sensitivity profiles inform optimal strategies to limit antibiotic resistance. PLoS Biol. 17, e3000515 (2019).
pubmed: 31652256
pmcid: 6834293
doi: 10.1371/journal.pbio.3000515
Yen, P. & Papin, J. A. History of antibiotic adaptation influences microbial evolutionary dynamics during subsequent treatment. PLoS Biol. 15, e2001586 (2017).
pubmed: 28792497
pmcid: 5549691
doi: 10.1371/journal.pbio.2001586
Yoshida, M. et al. Time-programmable drug dosing allows the manipulation, suppression and reversal of antibiotic drug resistance in vitro. Nat. Commun. 8, 15589 (2017).
pubmed: 28593940
pmcid: 5472167
doi: 10.1038/ncomms15589
Barbosa, C., Römhild, R., Rosenstiel, P. & Schulenburg, H. Evolutionary stability of collateral sensitivity to antibiotics in the model pathogen Pseudomonas aeruginosa. eLife 8, e51481 (2019).
pubmed: 31658946
pmcid: 6881144
doi: 10.7554/eLife.51481
Niederman, M. S. Appropriate use of antimicrobial agents: challenges and strategies for improvement. Crit. Care Med. 31, 608–616 (2003).
pubmed: 12576973
doi: 10.1097/01.CCM.0000050464.70382.D6
Brepoels, P. et al. Antibiotic cycling affects resistance evolution independently of collateral sensitivity. Mol. Biol. Evol. 39, msac257 (2022).
pubmed: 36480297
pmcid: 9778841
doi: 10.1093/molbev/msac257
Lukens, A. K. et al. Harnessing evolutionary fitness in Plasmodium falciparum for drug discovery and suppressing resistance. Proc. Natl Acad. Sci. USA 111, 799–804 (2014).
pubmed: 24381157
doi: 10.1073/pnas.1320886110
Rodriguez de Evgrafov, M., Gumpert, H., Munck, C., Thomsen, T. T. & Sommer, M. O. A. Collateral resistance and sensitivity modulate evolution of high-level resistance to drug combination treatment in Staphylococcus aureus. Mol. Biol. Evol. 32, 1175–1185 (2015).
pubmed: 25618457
doi: 10.1093/molbev/msv006
Rosenkilde, C. E. H. et al. Collateral sensitivity constrains resistance evolution of the CTX-M-15 β-lactamase. Nat. Commun. 10, 618 (2019).
pubmed: 30728359
pmcid: 6365502
doi: 10.1038/s41467-019-08529-y
Dromer, F., Bernede-Bauduin, C., Guillemot, D. & Lortholary, O. Major role for amphotericin B–flucytosine combination in severe cryptococcosis. PLoS ONE 3, e2870 (2008).
pubmed: 18682846
pmcid: 2483933
doi: 10.1371/journal.pone.0002870
Maziarz, E. K. & Perfect, J. R. in Diagnosis and Treatment of Fungal Infections (eds Hospenthal, D. R. et al.) 245–265 (Springer, 2023).
Pappas, P. G. et al. Clinical practice guideline for the management of candidiasis: 2016 update by the Infectious Diseases Society of America. Clin. Infect. Dis. 62, e1–e50 (2016).
pubmed: 26679628
doi: 10.1093/cid/civ933
Aghaei Gharehbolagh, S. et al. New weapons to fight a new enemy: a systematic review of drug combinations against the drug-resistant fungus Candida auris. Mycoses 64, 1308–1316 (2021).
pubmed: 33774879
doi: 10.1111/myc.13277
Hill, J. A., O’Meara, T. R. & Cowen, L. E. Fitness trade-offs associated with the evolution of resistance to antifungal drug combinations. Cell Rep. 10, 809–819 (2015).
pubmed: 25660029
doi: 10.1016/j.celrep.2015.01.009
Maertens, J. A. History of the development of azole derivatives. Clin. Microbiol. Infect. 10, 1–10 (2004).
pubmed: 14748798
doi: 10.1111/j.1470-9465.2004.00841.x
Szymański, M., Chmielewska, S., Czyżewska, U., Malinowska, M. & Tylicki, A. Echinocandins—structure, mechanism of action and use in antifungal therapy. J. Enzyme Inhib. Med. Chem. 37, 876–894 (2022).
pubmed: 35296203
pmcid: 8933026
doi: 10.1080/14756366.2022.2050224
Stevens, D. A., Espiritu, M. & Parmar, R. Paradoxical effect of caspofungin: reduced activity against Candida albicans at high drug concentrations. Antimicrob. Agents Chemother. 48, 3407–3411 (2004).
pubmed: 15328104
pmcid: 514730
doi: 10.1128/AAC.48.9.3407-3411.2004
Kordalewska, M. et al. Understanding echinocandin resistance in the emerging pathogen Candida auris. Antimicrob. Agents Chemother. 62, e00238-18 (2018).
pubmed: 29632013
pmcid: 5971591
doi: 10.1128/AAC.00238-18
Billamboz, M., Fatima, Z., Hameed, S. & Jawhara, S. Promising drug candidates and new strategies for fighting against the emerging superbug Candida auris. Microorganisms 9, 634 (2021).
pubmed: 33803604
pmcid: 8003017
doi: 10.3390/microorganisms9030634
Bouz, G. & Doleal, M. Advances in antifungal drug development: an up-to-date mini review. Pharmaceuticals 14, 1312 (2021).
pubmed: 34959712
pmcid: 8706862
doi: 10.3390/ph14121312
Mamouei, Z. et al. Alexidine dihydrochloride has broad-spectrum activities against diverse fungal pathogens. mSphere 3, https://doi.org/10.1128/mSphere.00539-18 (2018).
Berman, J. & Krysan, D. J. Drug resistance and tolerance in fungi. Nat. Rev. Microbiol. 18, 319–331 (2020).
pubmed: 32047294
pmcid: 7231573
doi: 10.1038/s41579-019-0322-2
Petzoldt, T. growthrates: estimate growth rates from experimental data. R package version 0.8.4 https://CRAN.R-project.org/package=growthrates (2022).
Gerami-Nejad, M., Zacchi, L. F., McClellan, M., Matter, K. & Berman, J. Shuttle vectors for facile gap repair cloning and integration into a neutral locus in Candida albicans. Microbiology 159, 565–579 (2013).
pubmed: 23306673
pmcid: 3709822
doi: 10.1099/mic.0.064097-0
Kim, S. H. et al. Genetic analysis of Candida auris implicates Hsp90 in morphogenesis and azole tolerance and Cdr1 in azole resistance. mBio 10, e02529-18 (2019).
pubmed: 30696744
pmcid: 6355988
doi: 10.1128/mBio.02529-18
Ko, H.-C., Hsiao, T.-Y., Chen, C.-T. & Yang, Y.-L. Candida albicans ENO1 null mutants exhibit altered drug susceptibility, hyphal formation, and virulence. J. Microbiol. 51, 345–351 (2013).
pubmed: 23812815
doi: 10.1007/s12275-013-2577-z
Ennis, C. L., Hernday, A. D. & Nobile, C. J. A markerless CRISPR-mediated system for genome editing in Candida auris reveals a conserved role for Cas5 in the caspofungin response. Microbiol. Spectr. 9, e01820–e01821 (2021).
pubmed: 34730409
pmcid: 8567271
doi: 10.1128/Spectrum.01820-21
Santana, D. J. & O’Meara, T. R. Forward and reverse genetic dissection of morphogenesis identifies filament-competent Candida auris strains. Nat. Commun. 12, 7197 (2021).
pubmed: 34893621
pmcid: 8664941
doi: 10.1038/s41467-021-27545-5
Carolus, H. et al. Acquired amphotericin B resistance and fitness trade-off compensation in Candida auris. Res. Sq. https://doi.org/10.21203/rs.3.rs-3621420/v1 (2023).
Vincent, B. M., Lancaster, A. K., Scherz-Shouval, R., Whitesell, L. & Lindquist, S. Fitness trade-offs restrict the evolution of resistance to amphotericin B. PLoS Biol. 11, e1001692 (2013).
pubmed: 24204207
pmcid: 3812114
doi: 10.1371/journal.pbio.1001692
Carolus, H. et al. Genome-wide analysis of experimentally evolved Candida auris reveals multiple novel mechanisms of multidrug resistance. mBio 12, e03333-20 (2021).
pubmed: 33820824
pmcid: 8092288
doi: 10.1128/mBio.03333-20
Carolus, H., Pierson, S., Lagrou, K. & Van Dijck, P. Amphotericin B and other polyenes—discovery, clinical use, mode of action and drug resistance. J. Fungi 6, 321 (2020).
doi: 10.3390/jof6040321
Barbosa, C. et al. Alternative evolutionary paths to bacterial antibiotic resistance cause distinct collateral effects. Mol. Biol. Evol. 34, 2229–2244 (2017).
pubmed: 28541480
pmcid: 5850482
doi: 10.1093/molbev/msx158
Kordalewska, M. et al. Rare modification in the ergosterol biosynthesis pathway leads to amphotericin B resistance in Candida auris clinical isolates. Preprint at bioRxiv https://doi.org/10.1101/2021.10.22.465535 (2021).
Rybak, J. M. et al. In vivo emergence of high-level resistance during treatment reveals the first identified mechanism of amphotericin B resistance in Candida auris. Clin. Microbiol. Infect. 28, 838–843 (2022).
pubmed: 34915074
doi: 10.1016/j.cmi.2021.11.024
Chow, N. A. et al. Tracing the evolutionary history and global expansion of Candida auris using population genomic analyses. mBio 11, e03364-19 (2020).
pubmed: 32345637
pmcid: 7188998
doi: 10.1128/mBio.03364-19
Jeffery-Smith, A. et al. Candida auris: a review of the literature. Clin. Microbiol. Rev. 31, e00029-17 (2017).
pubmed: 29142078
pmcid: 5740969
doi: 10.1128/CMR.00029-17
Després, P. C. et al. Asymmetrical dose responses shape the evolutionary trade-off between antifungal resistance and nutrient use. Nat. Ecol. Evol. 6, 1501–1515 (2022).
pubmed: 36050399
doi: 10.1038/s41559-022-01846-4
Wall, G., Herrera, N. & Lopez-Ribot, J. L. Repositionable compounds with antifungal activity against multidrug resistant Candida auris identified in the Medicines for Malaria Venture’s Pathogen Box. J. Fungi 5, 92 (2019).
doi: 10.3390/jof5040092
Subissi, A., Monti, D., Togni, G. & Mailland, F. Ciclopirox. Drugs 70, 2133–2152 (2010).
pubmed: 20964457
doi: 10.2165/11538110-000000000-00000
Fuchs, F. et al. Antifungal activity of nitroxoline against Candida auris isolates. Clin. Microbiol. Infect. 27, 1697.e7–1697.e10 (2021).
pubmed: 34245904
doi: 10.1016/j.cmi.2021.06.035
Pristov, K. E. & Ghannoum, M. A. Resistance of Candida to azoles and echinocandins worldwide. Clin. Microbiol. Infect. 25, 792–798 (2019).
pubmed: 30965100
doi: 10.1016/j.cmi.2019.03.028
Panackal, A. A. et al. Clinical significance of azole antifungal drug cross-resistance in Candida glabrata. J. Clin. Microbiol. 44, 1740–1743 (2006).
pubmed: 16672401
pmcid: 1479212
doi: 10.1128/JCM.44.5.1740-1743.2006
Forastiero, A. et al. Candida tropicalis antifungal cross-resistance is related to different azole target (Erg11p) modifications. Antimicrob. Agents Chemother. 57, 4769–4781 (2013).
pubmed: 23877676
pmcid: 3811422
doi: 10.1128/AAC.00477-13
Perlin, D. S. Resistance to echinocandin-class antifungal drugs. Drug Resist. Updat. 10, 121–130 (2007).
pubmed: 17569573
pmcid: 2696280
doi: 10.1016/j.drup.2007.04.002
Chassot, F. et al. Exploring the in vitro resistance of Candida parapsilosis to echinocandins. Mycopathologia 181, 663–670 (2016).
pubmed: 27318852
doi: 10.1007/s11046-016-0028-1
Arendrup, M. C. & Perlin, D. S. Echinocandin resistance: an emerging clinical problem? Curr. Opin. Infect. Dis. 27, 484–492 (2014).
pubmed: 25304391
pmcid: 4221099
doi: 10.1097/QCO.0000000000000111
Durand, R. et al. Mutational landscape and molecular bases of echinocandin resistance. Preprint at bioRxiv https://doi.org/10.1101/2024.07.21.604487 (2024).
Kathuria, S. et al. Multidrug-resistant Candida auris misidentified as Candida haemulonii: characterization by matrix-assisted laser desorption ionization–time of flight mass spectrometry and DNA sequencing and its antifungal susceptibility profile variability by Vitek 2, CLSI broth microdilution, and Etest method. J. Clin. Microbiol. 53, 1823–1830 (2015).
pubmed: 25809970
pmcid: 4432077
doi: 10.1128/JCM.00367-15
Arendrup, M. C., Prakash, A., Meletiadis, J., Sharma, C. & Chowdhary, A. Comparison of EUCAST and CLSI reference microdilution MICs of eight antifungal compounds for Candida auris and associated tentative epidemiological cutoff values. Antimicrob. Agents Chemother. 61, e00485-17 (2017).
pubmed: 28416539
pmcid: 5444165
doi: 10.1128/AAC.00485-17
Sanglard, D., Ischer, F., Parkinson, T., Falconer, D. & Bille, J. Candida albicans mutations in the ergosterol biosynthetic pathway and resistance to several antifungal agents. Antimicrob. Agents Chemother. 47, 2404–2412 (2003).
pubmed: 12878497
pmcid: 166068
doi: 10.1128/AAC.47.8.2404-2412.2003
Kelly, S. L. et al. Resistance to fluconazole and cross‐resistance to amphotericin B in Candida albicans from AIDS patients caused by defective sterol Δ5,6‐desaturation. FEBS Lett. 400, 80–82 (1997).
pubmed: 9000517
doi: 10.1016/S0014-5793(96)01360-9
Hull, C. M. et al. Facultative sterol uptake in an ergosterol-deficient clinical isolate of Candida glabrata harboring a missense mutation in ERG11 and exhibiting cross-resistance to azoles and amphotericin B. Antimicrob. Agents Chemother. 56, 4223–4232 (2012).
pubmed: 22615281
pmcid: 3421581
doi: 10.1128/AAC.06253-11
Eddouzi, J. et al. Molecular mechanisms of drug resistance in clinical Candida species isolated from Tunisian hospitals. Antimicrob. Agents Chemother. 57, 3182–3193 (2013).
pubmed: 23629718
pmcid: 3697321
doi: 10.1128/AAC.00555-13
Rosenberg, A. et al. Antifungal tolerance is a subpopulation effect distinct from resistance and is associated with persistent candidemia. Nat. Commun. 9, 2470 (2018).
pubmed: 29941885
pmcid: 6018213
doi: 10.1038/s41467-018-04926-x
Levinson, T. et al. Impact of tolerance to fluconazole on treatment response in Candida albicans bloodstream infection. Mycoses 64, 78–85 (2021).
pubmed: 33000505
doi: 10.1111/myc.13191
Chen, L. et al. Brain glucose induces tolerance of Cryptococcus neoformans to amphotericin B during meningitis. Nat. Microbiol. 9, 346–358 (2024).
pubmed: 38225460
doi: 10.1038/s41564-023-01561-1
Nichol, D. et al. Antibiotic collateral sensitivity is contingent on the repeatability of evolution. Nat. Commun. 10, 334 (2019).
pubmed: 30659188
pmcid: 6338734
doi: 10.1038/s41467-018-08098-6
Yekani, M. et al. Collateral sensitivity: an evolutionary trade-off between antibiotic resistance mechanisms, attractive for dealing with drug-resistance crisis. Health Sci, Rep. 6, e1418 (2023).
pubmed: 37448730
doi: 10.1002/hsr2.1418
Hernando-Amado, S., Laborda, P. & Martínez, J. L. Tackling antibiotic resistance by inducing transient and robust collateral sensitivity. Nat. Commun. 14, 1723 (2023).
pubmed: 36997518
pmcid: 10063638
doi: 10.1038/s41467-023-37357-4
Cowen, L. E. Hsp90 orchestrates stress response signaling governing fungal drug resistance. PLoS Pathog. 5, e1000471 (2009).
pubmed: 19714223
pmcid: 2726949
doi: 10.1371/journal.ppat.1000471
Montañés, F. M., Pascual-Ahuir, A. & Proft, M. Repression of ergosterol biosynthesis is essential for stress resistance and is mediated by the Hog1 MAP kinase and the Mot3 and Rox1 transcription factors. Mol. Microbiol. 79, 1008–1023 (2011).
pubmed: 21299653
doi: 10.1111/j.1365-2958.2010.07502.x
Ko, Y. J. et al. Remodeling of global transcription patterns of Cryptococcus neoformans genes mediated by the stress-activated HOG signaling pathways. Eukaryot. Cell 8, 1197–1217 (2009).
pubmed: 19542307
pmcid: 2725552
doi: 10.1128/EC.00120-09
Day, A. M., McNiff, M. M., da Silva Dantas, A., Gow, N. A. R. & Quinn, J. Hog1 regulates stress tolerance and virulence in the emerging fungal pathogen Candida auris. mSphere 3, e00506-18 (2018).
pubmed: 30355673
pmcid: 6200985
doi: 10.1128/mSphere.00506-18
Ksiezopolska, E. et al. Narrow mutational signatures drive acquisition of multidrug resistance in the fungal pathogen Candida glabrata. Curr. Biol. 31, 5314–5326.e10 (2021).
pubmed: 34699784
pmcid: 8660101
doi: 10.1016/j.cub.2021.09.084
Papp, C. et al. Triazole evolution of Candida parapsilosis results in cross-resistance to other antifungal drugs, influences stress responses, and alters virulence in an antifungal drug-dependent manner. mSphere 5, e00821-20 (2020).
pubmed: 33115837
pmcid: 7593601
doi: 10.1128/mSphere.00821-20
Scott, N. E., Erayil, E. S., Kline, S. E. & Selmecki, A. Rapid evolution of multidrug resistance in a Candida lusitaniae infection during micafungin monotherapy. Antimicrob. Agents Chemother. 67, e0054323 (2023).
pubmed: 37428075
doi: 10.1128/aac.00543-23
Spettel, K. et al. Analysis of antifungal resistance genes in Candida albicans and Candida glabrata using next generation sequencing. PLoS ONE 14, e0210397 (2019).
pubmed: 30629653
pmcid: 6328131
doi: 10.1371/journal.pone.0210397
Roemhild, R. & Andersson, D. I. Mechanisms and therapeutic potential of collateral sensitivity to antibiotics. PLoS Pathog. 17, e1009172 (2021).
pubmed: 33444399
pmcid: 7808580
doi: 10.1371/journal.ppat.1009172
Cowen, L. E. et al. Harnessing Hsp90 function as a powerful, broadly effective therapeutic strategy for fungal infectious disease. Proc. Natl Acad. Sci. USA 106, 2818–2823 (2009).
pubmed: 19196973
pmcid: 2650349
doi: 10.1073/pnas.0813394106
Cowen, L. E. & Lindquist, S. Hsp90 potentiates the rapid evolution of new traits: drug resistance in diverse fungi. Science 309, 2185–2189 (2005).
pubmed: 16195452
doi: 10.1126/science.1118370
Pachl, J. et al. A randomized, blinded, multicenter trial of lipid-associated amphotericin B alone versus in combination with an antibody-based inhibitor of heat shock protein 90 in patients with invasive candidiasis. Clin. Infect. Dis. 42, 1404–1413 (2006).
pubmed: 16619152
doi: 10.1086/503428
Skrzypek, M. et al. The Candida Genome Database (CGD): incorporation of Assembly 22, systematic identifiers and visualization of high throughput sequencing data. Nucleic Acids Res. 45, D592–D596 (2017).
pubmed: 27738138
doi: 10.1093/nar/gkw924
Muñoz, J. F. et al. Genomic insights into multidrug-resistance, mating and virulence in Candida auris and related emerging species. Nat. Commun. 9, 5346 (2018).
pubmed: 30559369
pmcid: 6297351
doi: 10.1038/s41467-018-07779-6
Muñoz, J. F. et al. Clade-specific chromosomal rearrangements and loss of subtelomeric adhesins in Candida auris. Genetics 218, iyab029 (2021).
Rybak, J. M. et al. Mutations in TAC1B: a novel genetic determinant of clinical fluconazole resistance in Candida auris. mBio 11, e00365-20 (2020).
pubmed: 32398311
pmcid: 7218281
doi: 10.1128/mBio.00365-20
Misas, E. et al. Mitochondrial genome sequences of the emerging fungal pathogen Candida auris. Front. Microbiol. 11, 560332 (2020).
pubmed: 33193142
pmcid: 7652928
doi: 10.3389/fmicb.2020.560332
Rybak, J. M. et al. Abrogation of triazole resistance upon deletion of CDR1 in a clinical isolate of Candida auris. Antimicrob. Agents Chemother. 63, e00057-19 (2019).
pubmed: 30718246
pmcid: 6437491
doi: 10.1128/AAC.00057-19
Burrack, L. S., Todd, R. T., Soisangwan, N., Wiederhold, N. P. & Selmecki, A. Genomic diversity across Candida auris clinical isolates shapes rapid development of antifungal resistance in vitro and in vivo. mBio 13, e0084222 (2022).
pubmed: 35862787
doi: 10.1128/mbio.00842-22
Carolus, H. et al. Diagnostic allele-specific PCR for the identification of Candida auris clades. J. Fungi 7, 754 (2021).
doi: 10.3390/jof7090754
Reference Method for Broth Dilution Antifungal Susceptibility Testing of Yeasts; Approved Standard—Third Edition CLSI document M27-A3 Vol. 28 (Clinical and Laboratory Standards Institute, 2008).
Boeke, J. D., LaCroute, F. & Fink, G. R. A positive selection for mutants lacking orotidine-5′-phosphate decarboxylase activity in yeast: 5-fluoro-orotic acid resistance. Mol. Gen. Genet. 197, 345–346 (1984).
pubmed: 6394957
doi: 10.1007/BF00330984
Foster, P. L. Methods for determining spontaneous mutation rates. Methods Enzymol. 409, 195–213 (2006).
pubmed: 16793403
pmcid: 2041832
doi: 10.1016/S0076-6879(05)09012-9
Bellmann, R. & Smuszkiewicz, P. Pharmacokinetics of antifungal drugs: practical implications for optimized treatment of patients. Infection 45, 737–779 (2017).
pubmed: 28702763
pmcid: 5696449
doi: 10.1007/s15010-017-1042-z
Caballero, U. et al. In vitro pharmacokinetic/pharmacodynamic modelling and simulation of amphotericin B against Candida auris. Pharmaceutics 13, 1767 (2021).
pubmed: 34834182
pmcid: 8624019
doi: 10.3390/pharmaceutics13111767
Caballero, U. et al. PK/PD modeling and simulation of the in vitro activity of the combinations of isavuconazole with echinocandins against Candida auris. CPT Pharmacometrics Syst. Pharmacol. 12, 770–782 (2023).
pubmed: 36915233
pmcid: 10272309
doi: 10.1002/psp4.12949
Hünniger, K. et al. A virtual infection model quantifies innate effector mechanisms and Candida albicans immune escape in human blood. PLoS Comput. Biol. 10, e1003479 (2014).
pubmed: 24586131
pmcid: 3930496
doi: 10.1371/journal.pcbi.1003479
Prauße, M. T. et al. Predictive virtual infection modeling of fungal immune evasion in human whole blood. Front. Immunol. 9, 560 (2018).
pubmed: 29619027
pmcid: 5871695
doi: 10.3389/fimmu.2018.00560
Ankomah, P. & Levin, B. R. Exploring the collaboration between antibiotics and the immune response in the treatment of acute, self-limiting infections. Proc. Natl Acad. Sci. USA 111, 8331–8338 (2014).
pubmed: 24843148
pmcid: 4060691
doi: 10.1073/pnas.1400352111
Kochin, B. F., Yates, A. J., de Roode, J. C. & Antia, R. On the control of acute rodent malaria infections by innate immunity. PLoS ONE 5, e10444 (2010).
pubmed: 20463903
pmcid: 2865546
doi: 10.1371/journal.pone.0010444
Reuß, O., Vik, A., Kolter, R. & Morschhauser, J. The SAT1 flipper, an optimized tool for gene disruption in Candida albicans. Gene 341, 119–127 (2004).
pubmed: 15474295
doi: 10.1016/j.gene.2004.06.021
Schikora-Tamarit, M. A. & Gabaldon, T. PerSVade: personalized structural variant detection in any species of interest. Genome Biol. 23, 175 (2022).
pubmed: 35974382
pmcid: 9380391
doi: 10.1186/s13059-022-02737-4
Andrews, S. FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
pubmed: 24695404
pmcid: 4103590
doi: 10.1093/bioinformatics/btu170
Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).
Poplin, R. et al. Scaling accurate genetic variant discovery to tens of thousands of samples. Preprint at bioRxiv https://doi.org/10.1101/201178 (2018).
Garisson, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. Preprint at https://arxiv.org/abs/1207.3907 (2012).
McLaren, W. et al. The Ensembl Variant Effect Predictor. Genome Biol. 17, 122 (2016).
pubmed: 27268795
pmcid: 4893825
doi: 10.1186/s13059-016-0974-4