Patterns of Genomic Variation in the Opportunistic Pathogen Candida glabrata Suggest the Existence of Mating and a Secondary Association with Humans
Open accessAbstract
Candida glabrata is an opportunistic fungal pathogen that ranks as the second most common cause of systemic candidiasis. Despite its genus name, this yeast is more closely related to the model yeast Saccharomyces cerevisiae than to other Candida pathogens, and hence its ability to infect humans is thought to have emerged independently. Moreover, C. glabrata has all the necessary genes to undergo a sexual cycle but is considered an asexual organism due to the lack of direct evidence of sexual reproduction. To reconstruct the recent evolution of this pathogen and find footprints of sexual reproduction, we assessed genomic and phenotypic variation across 33 globally distributed C. glabrata isolates. We cataloged extensive copy-number variation, which particularly affects genes encoding cell-wall-associated proteins, including adhesins. The observed level of genetic variation in C. glabrata is significantly higher than that found in Candida albicans. This variation is structured into seven deeply divergent clades, which show recent geographical dispersion and large within-clade genomic and phenotypic differences. We show compelling evidence of recent admixture between differentiated lineages and of purifying selection on mating genes, which provides the first evidence for the existence of an active sexual cycle in this yeast. Altogether, our data point to a recent global spread of previously genetically isolated populations and suggest that humans are only a secondary niche for this yeast.
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Cell wall-encoding genes are highly variable and are probably unrelated to the petite phenotype.
“Cell wall-encoding genes are known to be highly variable and are probably unrelated to the petite phenotype (20, 21).”
From Overlooked <i>Candida glabrata</i> petites are echinocandin tolerant, induce host inflammatory responses, and display poor <i>in vivo</i> fitness (2023) · cites this paper as [20]
The Conclusions (page not available in our copy) state that genetic variation particularly affects cell-wall proteins involved in adhesion. The paper does not assess whether those genes are related to the petite phenotype; its statement that variants are likely unrelated to a phenotype concerns MSH2 and the mutator phenotype, not petite. (LLM, conf=0.89)
Experimental — accuracy not yet measuredGenetically diverse C. glabrata lineages can recombine, leading to genetic admixture.
“Another ability of C. glabrata that has been confirmed recently, using comparison of whole genome sequences, is that genetically diverse lineages can recombine, leading to genetic admixture (Dodgson et al., 2005; Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
C. glabrata isolates can be ascribed to at least seven genetically distinct clades that lack a geographical structure.
“In a recent study, we have shown that C. glabrata isolates can be ascribed to at least seven genetically distinct clades that lack a geographical structure (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
These strains present an abnormal configuration of mating type MATa (triple a), as previously shown for other strains.
“Among all analyzed samples, CANGA2A and CANGA2B presented deletions in the MATalpha cassette (CAGL0B00242g and CAGL0B01243g) and a duplication in MATa (CAGL0E00341g), which suggest these strains present an abnormal configuration of mating type MATa (triple a), as previously shown for other strains (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
Mating type switching, as inferred from changes in coverage in mating genes, was detected as previously described.
“Mating type switching, as inferred from changes in coverage in mating genes was detected as previously described (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
C. glabrata is likely able to undergo mating and introgression from differentiated strains.
“Importantly, this study also revealed that C. glabrata is likely able to undergo mating and introgression from differentiated strains (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
Previously a MATa to MATalpha switching event has been described for the P35_2/P35_3 pair.
“Previously a MATa to MATalpha switching event has been described already for the P35_2/P35_3 pair (Lin et al., 2007; Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
Closely related strains belonging to the same clade can have large phenotypic differences.
“Recent studies have shown that closely related strains belonging to the same clade can have large phenotypic differences (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
The phenotypes of three pairs of serial isolates included here, B1012M/B1012S, EB101M/BO101S, and P35_2/P35_3, had been studied previously without remarkable differences between the pairs.
“The phenotypes of three pairs of serial isolates included here, B1012M/B1012S, EB101M/BO101S, and P35_2/P35_3, had been studied previously without remarkable differences between the pairs (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
MCA analysis provided consistent results with previously published clades, and suggested that all these new strains could be ascribed to several of the previously described clades.
“MCA analysis provided consistent results with previously published clades, and suggested that all these new strains could be ascribed to several of the previously described clades (Carreté et al., 2018): namely, pairs B1012M/B1012S and EB101M/BO101S belong to clade I; SAT strains to clade II; DSY562/DSY565 to clade III; P35_2/P35_3, CMRL1/CMRL2, and CANGA3A/CANGA3B strains belong to clade VI; NRZ-”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
Aberrant mating type switching events resulting in unorthodox configurations of the mating type loci are common among C. glabrata clinical isolates.
“Aberrant mating type switching events resulting in unorthodox configurations of the mating type loci have been shown to be common among C. glabrata clinical isolates (Brockert et al., 2003; Carreté et al., 2018)”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
Most strains within a pair showed a very low density of SNPs (0.037-0.047 SNPs/Kb), confirming their clonal nature.
“Similarly, most strains within a pair showed a very low density of SNPs (0.037–0.047 SNPs/Kb), confirming their clonal nature (Biswas et al., 2017; Vale-Silva et al., 2017; Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
The functional enrichment of non-synonymous mutations affecting cell-wall proteins was also detected among non-synonymous SNPs found in an overall comparison of clinical C. glabrata strains.
“This functional enrichment was also detected among non-synonymous SNPs found in an overall comparison of clinical C. glabrata strains (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
All serially isolated strains from the same patient belonged to the same clade as defined in previous studies.
“All serially isolated strains from the same patient belonged to the same clade as defined in previous studies (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
The genetic structure of C. glabrata populations suggests that humans may not be the natural niche for this yeast.
“Moreover, the genetic structure of C. glabrata populations suggest that human may not be the natural niche for this yeast (Carreté et al., 2018).”
From Genome Comparisons of Candida glabrata Serial Clinical Isolates Reveal Patterns of Genetic Variation in Infecting Clonal Populations (2019) · cites this paper as Carreté et al., 2018
MSH2 variants represent natural, functional variants rather than hypermutator mutations.
“thereby supporting the notion that these represent natural, functional variants rather than hypermutator mutations.20”
From Narrow mutational signatures drive acquisition of multidrug resistance in the fungal pathogen Candida glabrata (2021) · cites this paper as [20]
C. glabrata exhibits a remarkable capacity to acquire resistance to the tested drugs, independently of the phylogenetic background of the strain.
“Our results show that C. glabrata exhibits a remarkable capacity to acquire resistance to the tested drugs, independently of the phylogenetic background of the strain.20”
From Narrow mutational signatures drive acquisition of multidrug resistance in the fungal pathogen Candida glabrata (2021) · cites this paper as [20]
The 12 strains of C. glabrata used in this study include 11 clinical strains previously analyzed and one commensal strain SLL2_glab.
“The 12 strains of C. glabrata used in this study are listed in the key resources table. Eleven clinical strains had been previously analyzed for several phenotypic characteristics, including susceptibility to various drugs.20 In addition, they have been shown to belong to seven genetically distinct clades. The remaining strain (SLL2_glab) was isolated from an oral wash of a healthy individual from”
From Narrow mutational signatures drive acquisition of multidrug resistance in the fungal pathogen Candida glabrata (2021) · cites this paper as [20]
The opportunistic pathogenic lifestyle of C. glabrata is thought to have arisen independently from that of C. albicans.
“The reproduction mode in C. glabrata is predominantly clonal, and the opportunistic pathogenic lifestyle of C. glabrata is also thought to have arisen independently from that of C. albicans [25].”
From Candida glabrata: A Lot More Than Meets the Eye (2019) · cites this paper as [25]
C. glabrata is a haploid budding yeast that predominantly reproduces clonally.
“C. glabrata is a haploid budding yeast that predominantly reproduces clonally.”
From Candida glabrata: A Lot More Than Meets the Eye (2019) · cites this paper as [25]
Molecular phylogenetic and genome analysis have revealed that the three human pathogenic species of the glabrata group, C. glabrata, C. nivariensis and C. bracarenses, are polyphyletic in origin.
“Intriguingly, molecular phylogenetic and genome analysis have revealed three human pathogenic species, C. glabrata, C. nivariensis and C. bracarenses of the glabrata group, to be polyphyletic in origin [18,25].”
From Candida glabrata: A Lot More Than Meets the Eye (2019) · cites this paper as [25]
Genomic recombination between different clades and evidence for an active sexual cycle have recently been reported in C. glabrata.
“Of note, genomic recombination between different clades and evidence for an active sexual cycle have recently been reported in C. glabrata [25].”
From Candida glabrata: A Lot More Than Meets the Eye (2019) · cites this paper as [25]
High genomic plasticity is one characteristic of Candida yeasts that enables their fast adaptation to varying environments.
“High genomic plasticity is one of the characteristics of Candida yeasts that enables their fast adaptation to varying environments [62,63,64].”
From Evolutionary Emergence of Drug Resistance in Candida Opportunistic Pathogens (2018) · cites this paper as [63]
In contrast to other species, azole resistance in C. glabrata is generally not associated with alteration in ERG11, but rather with mutations in the PDR1 transcription factor that cause differential expression of downstream targets.
“In contrast to other species, azole resistance in C. glabrata is generally not associated with alteration in ERG11 [33,63,96,97], but rather with mutations in the PDR1 transcription factor, which cause the differential expression of downstream targets [97].”
From Evolutionary Emergence of Drug Resistance in Candida Opportunistic Pathogens (2018) · cites this paper as [63]
In a recent whole genome sequencing analysis, aneuploidies containing genes involved in drug resistance were not associated with increased resistance profiles.
“Similarly, in a recent whole genome sequencing analysis, aneuploidies containing genes involved in drug resistance were not associated with increased resistance profiles [63], again excluding a direct effect of chromosomal changes on antifungal drug resistance.”
From Evolutionary Emergence of Drug Resistance in Candida Opportunistic Pathogens (2018) · cites this paper as [63]
Some MSH2 mutations were found to be ancient polymorphisms within different C. glabrata clades, and to be equally widespread among non-resistant isolates.
“For instance, some of these mutations were found to be ancient polymorphisms within different C. glabrata clades, and to be equally widespread among non-resistant isolates [63].”
From Evolutionary Emergence of Drug Resistance in Candida Opportunistic Pathogens (2018) · cites this paper as [63]
For C. glabrata, other studies have cast doubts on the hypothesis that variations in MSH2 generally precede the appearance of other resistance-conferring mutations.
“However, at least for C. glabrata, other studies have cast doubts on the hypothesis that variations in MSH2 generally precede the appearance of other resistance-conferring mutations.”
From Evolutionary Emergence of Drug Resistance in Candida Opportunistic Pathogens (2018) · cites this paper as [63]
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Cites
Trimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548 · see citing works
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041 · see citing works
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895 · see citing works
BLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074 · see citing works
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447 · see citing works
Fast and accurate long-read alignment with Burrows-Wheeler transform.
Li, H., & Durbin, R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp698 · Cited by 12,063 · see citing works
trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses
Capella-Gutiérrez, S., Silla-Martinez, J., & Gabaldón, T. (2009) · Bioinform. · doi:10.1093/bioinformatics/btp348 · Cited by 12,052 · see citing works
Self-citationA framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,216 · see citing works
Application of Phylogenetic Networks in Evolutionary Studies
Huson, D. H., & Bryant, D. (2005) · Molecular Biology and Evolution · doi:10.1093/molbev/msj030 · Cited by 8,751 · see citing works
dbSNP: the NCBI database of genetic variation
Sherry, S. T. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.308 · Cited by 7,502 · see citing works
Van der Auwera, G. A., Carneiro, M. O., Hartl, C., Poplin, R., del Angel, G., Levy‐Moonshine, A., Jordan, T., Shakir, K., Roazen, D., Thibault, J., et al. (2013) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1110s43 · Cited by 6,687 · see citing works
Li, H. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr509 · Cited by 6,283 · see citing works
SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler
Luo, R., Liu, B., Xie, Y., Li, Z., Huang, W., Yuan, J., He, G., Chen, Y., Pan, Q., Liu, Y., et al. (2012) · GigaScience · doi:10.1186/2047-217x-1-18 · Cited by 5,274 · see citing works
Mauve: Multiple alignment of conserved genomic sequence with rearrangements
Darling, A. C. E., Mau, B., Blattner, F. R., & Perna, N. T. (2004) · Genome Research · doi:10.1101/gr.2289704 · Cited by 4,949 · see citing works
Hidden Killers: Human Fungal Infections
Brown, G. D., Denning, D. W., Gow, N. A. R., Levitz, S. M., Netea, M. G., & White, T. C. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3004404 · Cited by 4,284 · see citing works
Inferring weak population structure with the assistance of sample group information
HUBISZ, M. J., FALUSH, D., STEPHENS, M., & PRITCHARD, J. K. (2009) · Molecular Ecology Resources · doi:10.1111/j.1755-0998.2009.02591.x · Cited by 3,475 · see citing works
RDP4: Detection and analysis of recombination patterns in virus genomes
Martin, D. P., Murrell, B., Golden, M., Khoosal, A., & Muhire, B. M. (2015) · Virus Evolution · doi:10.1093/ve/vev003 · Cited by 3,272 · see citing works
AUGUSTUS: ab initio prediction of alternative transcripts
Stanke, M., Keller, O., Gunduz, I., Hayes, A., Waack, S., & Morgenstern, B. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl200 · Cited by 2,829 · see citing works
Dujon, B., Sherman, D., Fischer, G., Durrens, P., Casaregola, S., Lafontaine, I., de Montigny, J., Marck, C., Neuvéglise, C., Talla, E., et al. (2004) · Nature · doi:10.1038/nature02579 · Cited by 1,623 · see citing works
Self-citationRDP: detection of recombination amongst aligned sequences
Martin, D. P., & Rybicki, E. P. (2000) · Bioinformatics · doi:10.1093/bioinformatics/16.6.562 · Cited by 1,535 · see citing works
RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees
Stamatakis, A., Ludwig, T. G., & Meier, H. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bti191 · Cited by 1,429 · see citing works
Population genomics of domestic and wild yeasts
Liti, G., Carter, D. M., Moses, A. M., Warringer, J., Parts, L., James, S. A., Davey, R., Roberts, I. N., Burt, A., Koufopanou, V., et al. (2008) · Nature · doi:10.1038/nature07743 · Cited by 1,391 · see citing works
Assembling Single-Cell Genomes and Mini-Metagenomes From Chimeric MDA Products
Nurk, S., Bankevich, A., Antipov, D., Gurevich, A. A., Korobeynikov, A., Lapidus, A. L., Prjibelski, A. D., Pyshkin, A., Sirotkin, A., Sirotkin, Y., et al. (2013) · Journal of Computational Biology · doi:10.1089/cmb.2013.0084 · Cited by 1,332 · see citing works
The Fine-Scale Structure of Recombination Rate Variation in the Human Genome
McVean, G., Myers, S. R., Hunt, S. E., Deloukas, P., Bentley, D., & Donnelly, P. (2004) · Science · doi:10.1126/science.1092500 · Cited by 968 · see citing works
PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses in R
Pfeifer, B., Wittelsbürger, U., Ramos-Onsins, S. E., & Lercher, M. J. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu136 · Cited by 945 · see citing works
Growthcurver: an R package for obtaining interpretable metrics from microbial growth curves
Sprouffske, K., & Wagner, A. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1016-7 · Cited by 878 · see citing works
Arendrup, M. C., Cuenca-Estrella, M., Lass-Flörl, C., & Hope, W. (2012) · Clinical Microbiology and Infection · doi:10.1111/j.1469-0691.2012.03880.x · Cited by 451 · see citing works
Fischer, S., Brunk, B. P., Chen, F., Gao, X., Harb, O. S., Iodice, J., Shanmugam, D., Roos, D. S., & Stoeckert, C. J. (2011) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi0612s35 · Cited by 444 · see citing works
Mugsy: Fast multiple alignment of closely related whole genomes
Angiuoli, S. V., & Salzberg, S. L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btq665 · Cited by 444 · see citing works
Tenenhaus, M., & Young, F. W. (1985) · Psychometrika · doi:10.1007/bf02294151 · Cited by 419 · see citing works
Genetic and phenotypic intra-species variation in <i>Candida albicans</i>
Hirakawa, M. P., Martinez, D. A., Sakthikumar, S., Anderson, M. Z., Berlin, A., Gujja, S., Zeng, Q., Zisson, E., Wang, J. M., Greenberg, J. M., et al. (2015) · Genome Research · doi:10.1101/gr.174623.114 · Cited by 320 · see citing works
Adhesins in human fungal pathogens: glue with plenty of stick.
de Groot, P. W. J., Bader, O., de Boer, A. D., Weig, M., & Chauhan, N. (2013) · Eukaryotic Cell · doi:10.1128/ec.00364-12 · Cited by 319 · see citing works
The changing epidemiology of healthcare-associated candidemia over three decades
Diekema, D., Arbefeville, S., Boyken, L., Kroeger, J., & Pfaller, M. (2012) · Diagnostic Microbiology and Infectious Disease · doi:10.1016/j.diagmicrobio.2012.02.001 · Cited by 309 · see citing works
Healey, K. R., Zhao, Y., Perez, W. B., Lockhart, S. R., Sobel, J. D., Farmakiotis, D., Kontoyiannis, D. P., Sanglard, D., Taj-Aldeen, S. J., Alexander, B. D., et al. (2016) · Nature Communications · doi:10.1038/ncomms11128 · Cited by 276 · see citing works
Recombination rate estimation in the presence of hotspotsPreprint
Auton, A., & McVean, G. (2007) · Genome Research · doi:10.1101/gr.6386707 · Cited by 273 · see citing works
Boeva, V., Zinovyev, A. Y., Kevin Bleakley, A., Vert, J., Janoueix‐Lerosey, I., Delattre, O., & Barillot, E. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq635 · Cited by 267 · see citing works
Tsai, H.-F., Krol, A. A., Sarti, K. E., & Bennett, J. E. (2006) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.50.4.1384-1392.2006 · Cited by 237 · see citing works
Comparative genomics of emerging pathogens in the Candida glabrata clade.
Gabaldón, T., Martin, T., Marcet-Houben, M., Durrens, P., Bolotin-Fukuhara, M., Lespinet, O., Arnaise, S., Boisnard, S., Aguileta, G., Atanasova, R., et al. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-623 · Cited by 198 · see citing works
Self-citationMultilocus Sequence Typing of Candidaglabrata Reveals Geographically EnrichedClades
Dodgson, A. R., Pujol, C., Denning, D. W., Soll, D. R., & Fox, A. J. (2003) · Journal of Clinical Microbiology · doi:10.1128/jcm.41.12.5709-5717.2003 · Cited by 191 · see citing works
Cormack, B. P., & Falkow, S. (1999) · Genetics · doi:10.1093/genetics/151.3.979 · Cited by 180 · see citing works
Tavanti, A., Davidson, A. D., Fordyce, M. J., Gow, N. A. R., Maiden, M. C. J., & Odds, F. C. (2005) · Journal of Clinical Microbiology · doi:10.1128/jcm.43.11.5601-5613.2005 · Cited by 176 · see citing works
Efficient Inference of Recent and Ancestral Recombination within Bacterial Populations
Mostowy, R. J., Croucher, N. J., Andam, C. P., Corander, J., Hanage, W. P., & Marttinen, P. (2017) · Molecular Biology and Evolution · doi:10.1093/molbev/msx066 · Cited by 160 · see citing works
Esc1, a Nuclear Periphery Protein Required for Sir4-Based Plasmid Anchoring and Partitioning
Andrulis, E. D., Zappulla, D. C., Ansari, A., Perrod, S., Laiosa, C. V., Gartenberg, M. R., & Sternglanz, R. (2002) · Molecular and Cellular Biology · doi:10.1128/mcb.22.23.8292-8301.2002 · Cited by 147 · see citing works
Comparative Genomics in Hemiascomycete Yeasts: Evolution of Sex, Silencing, and Subtelomeres
Fabre, E., Muller, H., Therizols, P., Lafontaine, I., Dujon, B., & Fairhead, C. (2004) · Molecular Biology and Evolution · doi:10.1093/molbev/msi070 · Cited by 141 · see citing works
Self-citationGenomic Sequence Diversity and Population Structure of Saccharomyces cerevisiae Assessed by RAD-seq
Cromie, G. A., Hyma, K. E., Ludlow, C. L., Garmendia‐Torres, C., Gilbert, T., May, P., Huang, A. A., Dudley, A. M., & Fay, J. C. (2013) · G3 Genes Genomes Genetics · doi:10.1534/g3.113.007492 · Cited by 134 · see citing works
Evolutionary genomics of yeast pathogens in the Saccharomycotina
Gabaldón, T., Naranjo-Ortíz, M. A., & Marcet-Houben, M. (2016) · FEMS Yeast Research · doi:10.1093/femsyr/fow064 · Cited by 105 · see citing works
Self-citationGabaldón, T., & Carreté, L. (2016) · FEMS Yeast Research · doi:10.1093/femsyr/fov110 · Cited by 99 · see citing works
Self-citationRichard, G., Kerrest, A., Lafontaine, I., & Dujon, B. (2005) · Molecular Biology and Evolution · doi:10.1093/molbev/msi083 · Cited by 91 · see citing works
Searching and Navigating UniProt Databases
Pundir, S., Magrane, M., Martin, M. J., et al. (2015) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi0127s50 · Cited by 87 · see citing works
The Asexual Yeast Candida glabrata Maintains Distinct a and α Haploid Mating Types
Muller, H., Hennequin, C., Gallaud, J., Dujon, B., & Fairhead, C. (2008) · Eukaryotic Cell · doi:10.1128/ec.00456-07 · Cited by 84 · see citing works
Self-citationMuller, H., Thierry, A., Coppée, J.-Y., Gouyette, C., Hennequin, C., Sismeiro, O., Talla, E., Dujon, B., & Fairhead, C. (2009) · Fungal Genetics and Biology · doi:10.1016/j.fgb.2008.11.006 · Cited by 78 · see citing works
Self-citationEvidence for recombination in Candida glabrata.
Dodgson, A. R., Pujol, C., Pfaller, M. A., Denning, D. W., & Soll, D. R. (2005) · Fungal Genetics and Biology · doi:10.1016/j.fgb.2004.11.010 · Cited by 69 · see citing works
Liu, L., Li, Y., Li, H.-Z., & Chen, J. (2004) · Letters in Applied Microbiology · doi:10.1111/j.1472-765x.2004.01563.x · Cited by 64 · see citing works
Lin, C.-Y., Chen, Y.-C., Lo, H.-J., Chen, K.-W., & Li, S.-Y. (2007) · Journal of Clinical Microbiology · doi:10.1128/jcm.00699-07 · Cited by 62 · see citing works
Brisse, S., Pannier, C., Angoulvant, A., Meeûs, T. D., Diancourt, L., Faure, O., Muller, H., Pemán, J., Viviani, M. A., Grillot, R., et al. (2009) · Eukaryotic Cell · doi:10.1128/ec.00215-08 · Cited by 61 · see citing works
Self-citationFundyga, R. E., Lott, T. J., & Arnold, J. (2002) · Infection Genetics and Evolution · doi:10.1016/s1567-1348(02)00088-6 · Cited by 39 · see citing works
Bader, O., Schwarz, A., Kraneveld, E. A., Tangwattanchuleeporn, M., Schmidt, P., Jacobsen, M. D., Gross, U., De Groot, P. W. J., & Weig, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0052218 · Cited by 39 · see citing works
Self-citationGómez-Molero, E., de Boer, A. D., Dekker, H. L., Moreno-Martínez, A., Kraneveld, E. A., Ichsan, Chauhan, N., Weig, M., de Soet, J. J., de Koster, C. G., et al. (2015) · FEMS Yeast Research · doi:10.1093/femsyr/fov098 · Cited by 39 · see citing works
Angoulvant, A., Bourget, M., Brisse, S., Stockman-Pannier, C., Diancourt, L., François, N., Rimek, D., Fairhead, C., Poulain, D., & Hennequin, C. (2010) · Journal of Clinical Microbiology · doi:10.1128/jcm.02140-09 · Cited by 38 · see citing works
Self-citationBiswas, C., Chen, S. C.-A., Halliday, C., Kennedy, K., Playford, E. G., Marriott, D. J., Slavin, M. A., Sorrell, T. C., & Sintchenko, V. (2017) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2017.03.014 · Cited by 36 · see citing works
Efficient mating-type switching in Candida glabrata induces cell death
Boisnard, S., Zhou Li, Y., Arnaise, S., Sequeira, G., Raffoux, X., Enache-Angoulvant, A., Bolotin-Fukuhara, M., & Fairhead, C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140990 · Cited by 29 · see citing works
Self-citationXu, N., Ye, C., Chen, X., Liu, J., Liu, L., & Chen, J. (2016) · Scientific Reports · doi:10.1038/srep34893 · Cited by 15 · see citing works
Draft Genome Sequences of Candida glabrata Isolates 1A, 1B, 2A, 2B, 3A, and 3B
Håvelsrud, O. E., & Gaustad, P. (2017) · Genome Announcements · doi:10.1128/genomea.00328-16 · Cited by 9 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Evolutionary Emergence of Drug Resistance in Candida Opportunistic Pathogens
Ksiezopolska, E., & Gabaldón, T. (2018) · Genes · doi:10.3390/genes9090461 · Cited by 230 · see citing works
Self-citationGene flow contributes to diversification of the major fungal pathogen Candida albicans
Ropars, J., Maufrais, C., Diogo, D., Marcet-Houben, M., Perin, A., Sertour, N., Mosca, K., Permal, E., Laval, G., Bouchier, C., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04787-4 · Cited by 197 · see citing works
The Quiet and Underappreciated Rise of Drug-Resistant Invasive Fungal Pathogens
Arastehfar, A., Lass-Flörl, C., Garcia-Rubio, R., Daneshnia, F., Ilkit, M., Boekhout, T., Gabaldon, T., & Perlin, D. S. (2020) · Journal of Fungi · doi:10.3390/jof6030138 · Cited by 145 · see citing works
Candida glabrata: A Lot More Than Meets the Eye
Kumar, K., Askari, F., Sahu, M. S., & Kaur, R. (2019) · Microorganisms · doi:10.3390/microorganisms7020039 · Cited by 128 · see citing works
Clade-specific chromosomal rearrangements and loss of subtelomeric adhesins in <i>Candida auris</i>
Muñoz, J. F., Welsh, R. M., Shea, T., Batra, D., Gade, L., Howard, D., Rowe, L. A., Meis, J. F., Litvintseva, A. P., & Cuomo, C. A. (2021) · Genetics · doi:10.1093/genetics/iyab029 · Cited by 125 · see citing works
Ksiezopolska, E., Schikora-Tamarit, M. À., Beyer, R., Nunez-Rodriguez, J. C., Schüller, C., & Gabaldón, T. (2021) · Current Biology · doi:10.1016/j.cub.2021.09.084 · Cited by 107 · see citing works
Self-citationThe Dynamic Fungal Genome: Polyploidy, Aneuploidy and Copy Number Variation in Response to Stress
Vande Zande, P., Zhou, X., & Selmecki, A. (2023) · Annual Review of Microbiology · doi:10.1146/annurev-micro-041320-112443 · Cited by 70 · see citing works
Comparative Genomics for the Elucidation of Multidrug Resistance in Candida lusitaniae
Kannan, A., Asner, S. A., Trachsel, E., Kelly, S., Parker, J., & Sanglard, D. (2019) · mBio · doi:10.1128/mbio.02512-19 · Cited by 63 · see citing works
Carreté, L., Ksiezopolska, E., Gómez-Molero, E., Angoulvant, A., Bader, O., Fairhead, C., & Gabaldón, T. (2019) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.00112 · Cited by 58 · see citing works
Self-citationGale, A. N., Sakhawala, R. M., Levitan, A., Sharan, R., Berman, J., Timp, W., & Cunningham, K. W. (2020) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.120.401595 · Cited by 56 · see citing works
Badrane, H., Cheng, S., Dupont, C., Hao, B., Driscoll, E., Morder, K., Liu, G., Newbrough, A., Fleres, G., Kaul, D., et al. (2023) · doi:10.21203/rs.3.rs-2706400/v1 · Cited by 48 · see citing works
Siscar-Lewin, S., Gabaldón, T., Aldejohann, A. M., Kurzai, O., Hube, B., & Brunke, S. (2021) · mBio · doi:10.1128/mbio.01128-21 · Cited by 36 · see citing works
Self-citationCandida glabrata’s Genome Plasticity Confers a Unique Pattern of Expressed Cell Wall Proteins
López-Fuentes, E., Gutiérrez-Escobedo, G., Timmermans, B., Van Dijck, P., De Las Peñas, A., & Castaño, I. (2018) · Journal of Fungi · doi:10.3390/jof4020067 · Cited by 35 · see citing works
Barber, A. E., Weber, M., Kaerger, K., Linde, J., Gölz, H., Duerschmied, D., Markert, A., Guthke, R., Walther, G., & Kurzai, O. (2019) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.01628-18 · Cited by 32 · see citing works
Garcia-Rubio, R., Jimenez-Ortigosa, C., DeGregorio, L., Quinteros, C., Shor, E., & Perlin, D. S. (2021) · mBio · doi:10.1128/mbio.01959-21 · Cited by 29 · see citing works
Arastehfar, A., Daneshnia, F., Hovhannisyan, H., Fuentes, D., Cabrera, N., Quinteros, C., Ilkit, M., Ünal, N., Hilmioğlu-Polat, S., Jabeen, K., et al. (2023) · mBio · doi:10.1128/mbio.01180-23 · Cited by 27 · see citing works
“To exclude polymorphisms due to phylogenetic distance across clades, we determined the MLST type from the DPL248 genomic sequence as ST7 and identified two previously sequenced strains, CST35 and EB0911Sto, as its closest sequenced relatives (20).”
BackgroundMethodSelf-citationShor, E., Schuyler, J., & Perlin, D. S. (2019) · mBio · doi:10.1128/mbio.00120-19 · Cited by 19 · see citing works
Ksiezopolska, E., Schikora-Tamarit, M. À., Carlos Nunez-Rodriguez, J., & Gabaldón, T. (2024) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2024.1416509 · Cited by 15 · see citing works
Self-citationLi, Y., Hou, X., Li, R., Liao, K., Ma, L., Wang, X., Ji, P., Kong, H., Xia, Y., Ding, H., et al. (2023) · BMC Microbiology · doi:10.1186/s12866-023-03105-3 · Cited by 7 · see citing works
- Authors
- Carreté, L., Ksiezopolska, E., Pegueroles, C., Gómez-Molero, E., Saus, E., Iraola-Guzmán, S., Loska, D., Bader, O., Fairhead, C., & Gabaldón, T.
- Affiliations
- Universitat Pompeu Fabra (ES)
- Universitätsmedizin Göttingen (DE)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Corresponding author
- Gabaldón, Toni
- Venue
- Current Biology
- Publisher
- Elsevier BV
- Published
- 2018-01
- Volume
- 28
- Issue
- 1
- Pages
- 15-27.e7
- ISSN
- 0960-9822 (ISSN-L)
- PMC
- PMC5772174
- OpenAlex
- W2586557085
- Cited by
- 118
- References
- 64
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 11 · 2023: 10 · 2022: 15 · 2021: 21 · 2020: 13 · 2019: 16 · 2018: 14
- FWCI
- 4.81
- Type
- journal article
- Language
- en
- Update notices
- erratum (2022-07-25)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Current Biology (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- RECERCAT (Consorci de Serveis Universitaris de Catalunya) (publishedVersion, other-oa)
- Repositori digital de la UPF (Universitat Pompeu Fabra) (publishedVersion, cc-by-nc-nd)
- HAL (submittedVersion, cc-by-nc-nd)
- Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by-nc-nd)
- GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by-nc-nd)
- Funders
- Spanish Ministry of Economy and Competitiveness (SEV-2012-0208, BFU2015-67107)
- European Regional Development Fund
- European Union (FP7-PEOPLE-2013-ITN-606786)
- ERC Seventh Framework Programme (ERC-2012-StG-310325)
- Catalan Research Agency (SGR857)
- CERCA Programme/Generalitat de Catalunya
- European Union’s Horizon 2020 (H2020-MSCA-ITN-2014-642095)
- GDRI “iGenolevures”
- CNRS
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Yeasts and Rust Fungi Studies
- Health Sciences › Medicine › Infectious Diseases › Antifungal resistance and susceptibility
- Keywords
- Candida glabrata, sexual reproduction, copy number variation, clonal architecture, admixture, purifying selection, opportunistic fungal pathogens, Candida albicans comparison, geographic dispersal, systemic candidiasis
- MeSH terms
- Candidiasis, Humans, Phenotype, Reproduction, Genetic Variation, Genome, Fungal, Evolution, Molecular, Candida glabrata
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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