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Cited by 105Fungal and yeast genetics researchYeasts and Rust Fungi StudiesAntifungal resistance and susceptibility

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Evolutionary genomics of yeast pathogens in the Saccharomycotina

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Gabaldón, Toni, Naranjo-Ortíz, Miguel A., Marcet-Houben, Marina·2016·FEMS Yeast Research
DOI 10.1093/femsyr/fow064PMC PMC5815160
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Abstract

Saccharomycotina comprises a diverse group of yeasts that includes numerous species of industrial or clinical relevance. Opportunistic pathogens within this clade are often assigned to the genus Candida but belong to phylogenetically distant lineages that also comprise non-pathogenic species. This indicates that the ability to infect humans has evolved independently several times among Saccharomycotina. Although the mechanisms of infection of the main groups of Candida pathogens are starting to be unveiled, we still lack sufficient understanding of the evolutionary paths that led to a virulent phenotype in each of the pathogenic lineages. Deciphering what genomic changes underlie the evolutionary emergence of a virulence trait will not only aid the discovery of novel virulence mechanisms but it will also provide valuable information to understand how new pathogens emerge, and what clades may pose a future danger. Here we review recent comparative genomics efforts that have revealed possible evolutionary paths to pathogenesis in different lineages, focusing on the main three agents of candidiasis worldwide: Candida albicans, C. parapsilosis and C. glabrata We will discuss what genomic traits may facilitate the emergence of virulence, and focus on two different genome evolution mechanisms able to generate drastic phenotypic changes and which have been associated to the emergence of virulence: gene family expansion and interspecies hybridization.

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Crossref · 10.1093/femsyr/fow064

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Figure 1. Schematic overview of comparative genomics methods to find virulence factors. In the center of the image a phylogenetic tree represents the evolutionary relationships between an idealized group of pathogenic and non-pathogenic species, where the ones drawn in red are pathogenic. Red stars indicate two points in the tree where virulence emerged. For species E, a list of strains is indicated on the right showing the presence of sequenced strains with different degrees of virulence. The boxes surrounding the tree indicate different kinds of analyses that can be performed to detect virulence traits. (A) Search for genomic re-arrangements. (B) Presence and absence of genes, shown as a table where the white squares represent missing genes and the gray and red square represent present genes. In addition, red squares indicate putative virulence factors. (C) Detection of differences between strains. Each arrow represents a gene. Red horizontal lines represent SNPs. (D) Detection of positive selection. Red horizontal lines represent non-synonymous SNPs and black horizontal lines represent synonymous SNPs. (E) Events that can be detected with the use of phylogenetic trees. Arrows represent genes. Gene duplication and loss is represented along with changes in gene order. (F) Gene expansions. Phylogenetic tree representing two independent expansion events in the pathogenic species. Expansion points are marked with a star.
Figure 1. Schematic overview of comparative genomics methods to find virulence factors. In the center of the image a phylogenetic tree represents the evolutionary relationships between an idealized group of pathogenic and non-pathogenic species, where the ones drawn in red are pathogenic. Red stars indicate two points in the tree where virulence emerged. For species E, a list of strains is indicated on the right showing the presence of sequenced strains with different degrees of virulence. The boxes surrounding the tree indicate different kinds of analyses that can be performed to detect virulence traits. (A) Search for genomic re-arrangements. (B) Presence and absence of genes, shown as a table where the white squares represent missing genes and the gray and red square represent present genes. In addition, red squares indicate putative virulence factors. (C) Detection of differences between strains. Each arrow represents a gene. Red horizontal lines represent SNPs. (D) Detection of positive selection. Red horizontal lines represent non-synonymous SNPs and black horizontal lines represent synonymous SNPs. (E) Events that can be detected with the use of phylogenetic trees. Arrows represent genes. Gene duplication and loss is represented along with changes in gene order. (F) Gene expansions. Phylogenetic tree representing two independent expansion events in the pathogenic species. Expansion points are marked with a star.CC BY-NC · PubMed Central
Figure 2. Phylogenetic relationships among Candida. A total of 516 genes detected as single copy genes in Saccharomyces species (Marcet-Houben and Gabaldón 2015) were used to perform a homology search against a proteome database formed by the 71 Saccharomycotina species included in the tree. A phylogenetic tree was reconstructed for each group of homologs using the phylome reconstruction pipeline (Huerta-Cepas et al.2014). Phylogenetic trees were examined with ETE (Huerta-Cepas, Dopazo and Gabaldón 2010), species-specific duplications were deleted and one sequence belonging to the duplicated clade was randomly chosen to represent the clade. Trees that, after filtering, contained one-to-one orthologs in at least three-fourth of the species were retained and their alignments were concatenated. The final alignment contained 190 110 amino acid positions. The phylogenetic tree was reconstructed using RAxML with the PROTGAMMALG model (Stamatakis, Ludwig and Meier 2005). Bootstraps were reconstructed using RAxML rapid bootstrap approach, supports below 100 are marked on the tree. For Candida species, red-colored leaves indicate pathogenic species while green-colored leaves indicate non-pathogenic species.
Figure 2. Phylogenetic relationships among Candida. A total of 516 genes detected as single copy genes in Saccharomyces species (Marcet-Houben and Gabaldón 2015) were used to perform a homology search against a proteome database formed by the 71 Saccharomycotina species included in the tree. A phylogenetic tree was reconstructed for each group of homologs using the phylome reconstruction pipeline (Huerta-Cepas et al.2014). Phylogenetic trees were examined with ETE (Huerta-Cepas, Dopazo and Gabaldón 2010), species-specific duplications were deleted and one sequence belonging to the duplicated clade was randomly chosen to represent the clade. Trees that, after filtering, contained one-to-one orthologs in at least three-fourth of the species were retained and their alignments were concatenated. The final alignment contained 190 110 amino acid positions. The phylogenetic tree was reconstructed using RAxML with the PROTGAMMALG model (Stamatakis, Ludwig and Meier 2005). Bootstraps were reconstructed using RAxML rapid bootstrap approach, supports below 100 are marked on the tree. For Candida species, red-colored leaves indicate pathogenic species while green-colored leaves indicate non-pathogenic species.CC BY-NC · PubMed Central

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Metadata

Authors
Gabaldón, T., Naranjo-Ortíz, M. A., & Marcet-Houben, M.
Affiliations
  • Institució Catalana de Recerca i Estudis Avançats (ES)
  • Universitat Pompeu Fabra (ES)
Corresponding author
Gabaldón, Toni
ORCID
Venue
FEMS Yeast Research
Publisher
Oxford University Press (OUP)
Published
2016-08-03
Volume
16
Issue
6
Pages
fow064
ISSN
  • 1567-1356 (ISSN-L)
  • 1567-1364
DOI
10.1093/femsyr/fow064
PMC
PMC5815160
OpenAlex
W2488745281
Cited by
105
References
64
Citations by year
2026: 6 · 2025: 10 · 2024: 11 · 2023: 16 · 2022: 4 · 2021: 17 · 2020: 10 · 2019: 13 · 2018: 11 · 2017: 7
FWCI
0.93
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • FEMS Yeast Research (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • RECERCAT (Consorci de Serveis Universitaris de Catalunya) (publishedVersion, other-oa)
  • Repositori digital de la UPF (Universitat Pompeu Fabra) (publishedVersion, cc-by-nc)
  • HighWire Press Open Archive (submittedVersion)
Funders
  • European Commission (H2020-MSCA-ITN, H2020-MSCA-ITN-2014, 2007–2013, FP7 2007-2013, 642095, FP7-PEOPLE-2013, FP7/2007, FP7‐PEOPLE‐ 2013‐ITN, 606786, H2020-MSCA)
  • Ministerio de Economía y Competitividad (642095, SEV‐2012‐0208, BIO2012-37161)
  • Horizon 2020 Framework Programme (MSCA-ITN-2014, FP7/2007-2013, H2020MSCA‐ITN‐2014, H2020-MSCA, H2020-MSCA-ITN-2014-642095, 642095, H2020-MSCA-ITN)
  • Agència de Gestió d'Ajuts Universitaris i de Recerca (SGR857)
  • European Regional Development Fund (H2020-MSCA-ITN-2014, FP7/2007‐2013, 2007 – 2013)
  • FP7 People: Marie-Curie Actions (FP7-PEOPLE-2013-ITN-606786, 2007-2013, 2013‐ITN‐606786, FP7-PEOPLE-2013-ITN, FP7/2007‐2013/, FP7-PEOPLE-2013)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
  • Life Sciences › Immunology and Microbiology › Microbiology › Yeasts and Rust Fungi Studies
  • Health Sciences › Medicine › Infectious Diseases › Antifungal resistance and susceptibility
Keywords
Saccharomycotina, pathogenic yeasts, Candida, candidiasis, virulence evolution, Candida albicans, Candida parapsilosis, Candida glabrata, comparative genomics, gene family expansion, interspecific hybridization, genome evolution, opportunistic pathogens
MeSH terms
Ascomycota, Evolution, Molecular, Genomics, Virulence Factors

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