Asymmetrical dose responses shape the evolutionary trade-off between antifungal resistance and nutrient use

ABSTRACT Antimicrobial resistance is an emerging threat for public health. The success of resistance mutations depends on the trade-off between the benefits and costs they incur. This

trade-off is largely unknown and uncharacterized for antifungals. Here, we systematically measure the effect of all amino acid substitutions in the yeast cytosine deaminase Fcy1, the target

of the antifungal 5-fluorocytosine (5-FC, flucytosine). We identify over 900 missense mutations granting resistance to 5-FC, a large fraction of which appear to act through destabilization

of the protein. The relationship between 5-FC resistance and growth sustained by cytosine deamination is characterized by a sharp trade-off, such that small gains in resistance universally

lead to large losses in canonical enzyme function. We show that this steep relationship can be explained by differences in the dose–response functions of 5-FC and cytosine. Finally, we

observe the same trade-off shape for the orthologue of _FCY1_ in _Cryptoccocus neoformans_, a human pathogen. Our results provide a powerful resource and platform for interpreting drug

target variants in fungal pathogens as well as unprecedented insights into resistance–function trade-offs. Access through your institution Buy or subscribe This is a preview of subscription

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DRUG TARGET CONFER CROSS-RESISTANCE WITHOUT INTRINSIC FITNESS COST Article 08 October 2024 DRUG-DEPENDENT GROWTH CURVE RESHAPING REVEALS MECHANISMS OF ANTIFUNGAL RESISTANCE IN

_SACCHAROMYCES CEREVISIAE_ Article Open access 31 March 2022 ADAPTIVE LABORATORY EVOLUTION IN _S. CEREVISIAE_ HIGHLIGHTS ROLE OF TRANSCRIPTION FACTORS IN FUNGAL XENOBIOTIC RESISTANCE Article

Open access 11 February 2022 DATA AVAILABILITY Raw sequencing files for the DMS libraries and the competition screen have been deposited on the NCBI SRA (accession number PRJNA782569). All

raw images (source data for Supplementary Fig. 2 and Fig. 6b and Extended Data Fig. 9) are provided as Supplementary Data 13 and 15. Supplementary Data 5–10 provide the source data for the

DMS experiments and NGS analysis, the validation studies, the dose–response assays and the experiments in the _C. neoformans_ orthologue. CODE AVAILABILITY Scripts used for data analysis and

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PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS We thank members of the Landry lab for helpful discussions, in particular D. Evans-Yamamoto, M. Hénault, F. Mattenberger and R.

Durand. This work was supported by the Canadian Institutes of Health Research Foundation grant number 387697 to C.R.L. and a Vanier graduate scholarship to P.C.D, as well as by the National

Science and Engineering Research Council through the EvoFunPath CREATE grant (number 555337-2021) and by FRQNT through team grant (number 2022-PR-298169) and a PBEEE scholarship to A.F.C.

C.R.L. holds the Canada Research Chair in in Cellular Systems and Synthetic Biology. Molecular graphics and analyses were performed with UCSF ChimeraX, developed by the Resource for

Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from National Institutes of Health R01-GM129325 and the Office of Cyber

Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Département de Biochimie, de Microbiologie et

de Bio-informatique, Faculté des Sciences et de Génie, Université Laval, Québec, Canada Philippe C. Després, Angel F. Cisneros, Emilie M. M. Alexander, Ria Sonigara, Cynthia Gagné-Thivierge,

 Alexandre K. Dubé & Christian R. Landry * Institut de Biologie Intégrative et des Systèmes, Université Laval, Québec, Canada Philippe C. Després, Angel F. Cisneros, Emilie M. M.

Alexander, Ria Sonigara, Cynthia Gagné-Thivierge, Alexandre K. Dubé & Christian R. Landry * PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les

applications des protéines, Université Laval, Québec, Canada Philippe C. Després, Angel F. Cisneros, Emilie M. M. Alexander, Cynthia Gagné-Thivierge, Alexandre K. Dubé & Christian R.

Landry * Centre de Recherche sur les Données Massives, Université Laval, Québec, Canada Philippe C. Després, Angel F. Cisneros, Emilie M. M. Alexander, Ria Sonigara, Cynthia Gagné-Thivierge,

 Alexandre K. Dubé & Christian R. Landry * Département de Biologie, Faculté des Sciences et de Génie, Université Laval, Québec, Canada Ria Sonigara, Cynthia Gagné-Thivierge, Alexandre K.

Dubé & Christian R. Landry Authors * Philippe C. Després View author publications You can also search for this author inPubMed Google Scholar * Angel F. Cisneros View author

publications You can also search for this author inPubMed Google Scholar * Emilie M. M. Alexander View author publications You can also search for this author inPubMed Google Scholar * Ria

Sonigara View author publications You can also search for this author inPubMed Google Scholar * Cynthia Gagné-Thivierge View author publications You can also search for this author inPubMed 

Google Scholar * Alexandre K. Dubé View author publications You can also search for this author inPubMed Google Scholar * Christian R. Landry View author publications You can also search for

this author inPubMed Google Scholar CONTRIBUTIONS P.C.D., A.K.D. and C.R.L. designed the research. P.C.D., E.M.M.A., C.G-T. and A.K.D. performed the experiments. P.C.D., A.F.C., R.S. and

C.R.L performed the data analysis. P.C.D. and C.R.L. wrote the paper with input from all authors. CORRESPONDING AUTHORS Correspondence to Philippe C. Després or Christian R. Landry. ETHICS

DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Ecology & Evolution_ thanks Nobuhiko Tokuriki and the other,

anonymous, reviewer(s) for their contribution to the peer review of this work. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in

published maps and institutional affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 REPLICATE AMINO ACID LOG2 FOLD-CHANGES IN THE DMS EXPERIMENTS. Correlation between R1 and R2 was measured

using Spearman’s rank correlation. A) Pool 1, 5-FC (n = 1372). B) Pool 2, 5-FC (n = 1298). C) Pool 3, 5-FC (n = 1374). D) Pool 1, cytosine (n = 1372). E) Pool 2, cytosine (n = 1298). F) Pool

3, cytosine (n = 1374). G) Pool 2, 5-FC + Cytosine (n = 1298). EXTENDED DATA FIG. 2 USING POOL OVERLAPPING FRAGMENTS TO HARMONISE THE LOG2 FOLD-CHANGES OF THE _FCY1_ MUTANT POOLS. For each

panel, the linear least-squares regression parameters are shown, with Spearman’s rank correlation shown below. A) Pool 1 to Pool 2, cytosine (n = 397). B) Pool 3 to Pool 2, cytosine (n = 

375). C) Pool 1 to Pool 2, 5-FC (n = 397). D) Pool 3 to Pool 2, 5-FC (n = 375). EXTENDED DATA FIG. 3 SCALING LOG2 FOLD-CHANGES TO POOL 2 AND SCALING SCORES TO SYNONYMOUS AND NONSENSE

MUTATIONS. For panel A-F, the linear least-squares regression parameters are shown, with Spearman’s rank correlation shown below for the comparison between raw pool scores and pool 2

adjusted scores. A) Raw pool 1 vs adjusted pool 1, cytosine (n = 1372) B) Raw pool 2 vs adjusted pool 2, cytosine (n = 1298). C) Raw pool 3 vs adjusted pool 3, cytosine (n = 1374). D) Raw

pool 1 vs adjusted pool 1, 5-FC (n = 1372) E) Raw pool 2 vs adjusted pool 2, 5-FC (n = 1298). F) Raw pool 3 vs adjusted pool 3, 5-FC (n = 1374). G) Adjusted log2 fold-change for synonymous

(black) and nonsense (red) mutants in cytosine (n = 148 synonymous, n = 156 nonsense mutants) along the protein positions. For positions where Met and Trp are the wild-type amino acids,

there are no synonymous codons. This occurs 8 times in the _FCY1_ coding sequence (not including the start Met). H) Adjusted log2 fold-change for synonymous (black) and nonsense (red)

mutants in 5-FC (n = 148 synonymous, n = 156 nonsense mutants). EXTENDED DATA FIG. 4 DMSSCORE DISTRIBUTIONS BY MUTANT TYPE. Silent mutations are shown in green, nonsense in magenta, and

missense mutants in grey. A) 5-FC (n = 148 silent, 151 nonsense, 2968 missense). B) Cytosine (n = 148 silent, 151 nonsense, 2968 missense) C) 5-FC + cytosine (n = 59 silent, 62 nonsense,

1177 missense). D) DMSscore in 5-FC + cytosine as a function of scores in cytosine only with spearman’s rank correlation shown (n = 1298 mutants). EXTENDED DATA FIG. 5 _FCY1_ EVOLUTIONARY

RATE AND ORTHOLOGOUS RESIDUE DIVERSITY. A) frequency of the _S. cerevisiae_ amino acid at each position in the orthologous sequences. B) Normalized evolutionary rate for all Fcy1 residues

(Rate4site24) from 215 orthologues. The blue line represents the rolling average over a 6 amino acid window. This statistic represents the rate at which amino acids change along a phylogeny:

higher values represent more variable positions, while lower values represent more conserved positions. C) Multiple sequence alignment coverage of _S. cerevisiae_ Fcy1 positions in the set

of orthologues. The maximum value is 215, representing perfectly conserved amino acids positions across all sequences. EXTENDED DATA FIG. 6 DHFR-PCA DATA SUPPORTS PROTEIN STRUCTURE STABILITY

PREDICTIONS FOR VALIDATION MUTANTS. _FCY1_ variants were tagged with a DHFR-PCA25 fragment to measure protein complex formation with a wild-type copy of _FCY1_. In this approach, Fcy1 is

fused to DHFR fragments that complement upon dimerization, allowing growth in media containing methotrexate (MTX). Growth reflects the amount of complex formed, therefore providing a

quantitative measure of the stability of the Fcy1 subunits and complex. The 54 mutants are colored based on their DMS cluster (see Extended Data Fig. 7). All panels show Spearman’s rank

correlation. A) Growth rates in DMSO of the validation mutants for the two replicates. DMSO is the MTX solvent and is the control condition for the DHFR-PCA assay. B) Growth rates in MTX of

the validation mutants for the two replicates. C) Growth rate in MTX as a function of their growth rate in DMSO. As expected, there is no strong correlation between the two. D) Growth rate

in MTX as a function of FoldX58 predicted change in Fcy1 structure stability measured as ΔΔG. Positive ΔΔG represents destabilization. E) Growth rate in MTX as a function of the growth rate

in cytosine media of the haploid strain. F) Growth rate in MTX and in 5-FC media of the haploid strain. EXTENDED DATA FIG. 7 DMS ASSAY VALIDATIONS IN 5-FC AND CYTOSINE MEDIA. A) Location on

the cytosine/5-FC landscape of the Fcy1 variants (shown as grey dots) selected for validations superimposed on the density plot presented in Fig. 2d. The circles used to define the three

clusters are also shown: green for silent-like mutants, magenta for nonsense-like mutants, and blue for front minimum mutants. Mutants falling outside these clusters were classified as

‘other’ and encompass most outliers from the DMS screen. Variants with both high 5-FC and cytosine DMSscore are shown as squares: these outliers potentially escape the resistance-function

trade-off. B) Spearman’s correlation between growth curve replicates in 5-FC media, n = 73 variants. C) Spearman’s correlation between growth curve replicates in cytosine media, n = 72

variants. Data collected from the cytosine media from the outlier (T86M) was excluded from downstream analysis. D) Linear least-squares regression fit and Spearman’s correlation between 5-FC

growth rates measured in the 1st and 2nd rounds of validations for 17 mutants present in both growth curve assays. E) Linear least-squares regression fit and Spearman’s correlation between

cytosine growth rates measured in the 1st and 2nd rounds of validations for 17 mutants present in both assays. F) Growth rate values of the 2nd round of validations scaled to the growth rate

of the 1st round for the 17 mutants present in both assays. G) Spearman’s correlation between validation growth curves in 5-FC media and DMS 5-FC score, n = 79 variants. H) Spearman’s

correlation between validation growth curves in cytosine media and DMS cytosine score, n = 79 variants. I) Spearman’s correlation between validation growth curves in cytosine media and DMS

5-FC + cytosine score, n = 38 variants. EXTENDED DATA FIG. 8 PHENOTYPES OF THE SCFCY1 AND CNFCY1 MUTANTS. A) Growth rate for the 29 (27 of which were successfully constructed) scFCY1

variants selected in the DMS assay validation experiments. B) Representative examples of the phenotypes observed in the spot assays (Synthetic media + 194 μM 5-FC, 10-fold dilutions starting

at 1 OD/ml), where S: sensitive, r: low growth and R: full resistance. C) Phenotypes of scFCY1_opt (_S. cerevisiae_ codon optimized _FCY1_ at the _FCY1_ locus), cnFCY1_opt (_C. neoformans_

codon optimized _FCY1_ at the _S. cerevisiae FCY1_ locus) compared to the parental strain (BY4742) and the deletion mutant (Δfcy1). D) Comparison of growth rate between orthologous variants

in 5-FC media. Spearman’s rank correlation is shown (n = 22 pairs). Variants are colored by the position along the trade-off of the scFCY1 variant. E) Comparison of 5-FC media growth rate

between orthologous variants. Spearman’s rank correlation is shown (n = 22 pairs). F) Changes in growth rate in SC + 12 μM 5-FC and SC-Ura + 84 μM cytosine between scFcy1 and cnFcy1

variants. Spearman’s rank correlation is shown (n = 22 pairs). EXTENDED DATA FIG. 9 SPOT DILUTION ASSAY PHENOTYPES ARE MOST OFTEN CONSERVED BETWEEN ORTHOLOGOUS MUTANTS OF SCFCY1 AND CNFCY1.

The same dilutions of control strains BY4742 (WT FCY1), scFCY1_opt (_S. cerevisiae_ codon optimized _FCY1_ at the _FCY1_ locus), cnFCY1_opt (_C. neoformans_ codon optimized _FCY1_ at the _S.

cerevisiae FCY1_ locus) and _Δfcy1_ were spotted on each plate. For each mutant pair, the scFcy1 strain is in white and the cnFcy1 is highlighted in grey. The phenotype score (as defined

earlier) for each strain is shown on the right. The raw images used to generate the figure are available as Supplementary Data 5. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION

Supplementary Figs. 1–9. REPORTING SUMMARY. SUPPLEMENTARY DATA Supplementary Data 1–15. RIGHTS AND PERMISSIONS Springer Nature or its licensor holds exclusive rights to this article under a

publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing

agreement and applicable law. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Després, P.C., Cisneros, A.F., Alexander, E.M.M. _et al._ Asymmetrical dose responses shape the

evolutionary trade-off between antifungal resistance and nutrient use. _Nat Ecol Evol_ 6, 1501–1515 (2022). https://doi.org/10.1038/s41559-022-01846-4 Download citation * Received: 09

December 2021 * Accepted: 07 July 2022 * Published: 01 September 2022 * Issue Date: October 2022 * DOI: https://doi.org/10.1038/s41559-022-01846-4 SHARE THIS ARTICLE Anyone you share the

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