Skip to main content
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems
  • Log in
  • My alerts
  • My Cart

Main menu

  • Home
  • Articles
    • Latest Articles
    • COVID-19 Special Collection
    • Archive
    • Minireviews
  • Topics
    • Applied and Environmental Science
    • Clinical Science and Epidemiology
    • Ecological and Evolutionary Science
    • Host-Microbe Biology
    • Molecular Biology and Physiology
    • Therapeutics and Prevention
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About mBio
    • Editor in Chief
    • Board of Editors
    • AAM Fellows
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems

User menu

  • Log in
  • My alerts
  • My Cart

Search

  • Advanced search
mBio
publisher-logosite-logo

Advanced Search

  • Home
  • Articles
    • Latest Articles
    • COVID-19 Special Collection
    • Archive
    • Minireviews
  • Topics
    • Applied and Environmental Science
    • Clinical Science and Epidemiology
    • Ecological and Evolutionary Science
    • Host-Microbe Biology
    • Molecular Biology and Physiology
    • Therapeutics and Prevention
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About mBio
    • Editor in Chief
    • Board of Editors
    • AAM Fellows
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
Research Article

Highly Recombinant VGII Cryptococcus gattii Population Develops Clonal Outbreak Clusters through both Sexual Macroevolution and Asexual Microevolution

R. Blake Billmyre, Daniel Croll, Wenjun Li, Piotr Mieczkowski, Dee A. Carter, Christina A. Cuomo, James W. Kronstad, Joseph Heitman
Jacques Ravel, Editor
R. Blake Billmyre
aDepartment of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Daniel Croll
bThe Michael Smith Laboratories, Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Wenjun Li
aDepartment of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Piotr Mieczkowski
cDepartment of Genetics, School of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dee A. Carter
dSchool of Molecular Bioscience, University of Sydney, Sydney, New South Wales, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christina A. Cuomo
eBroad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James W. Kronstad
bThe Michael Smith Laboratories, Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Joseph Heitman
aDepartment of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jacques Ravel
University of Maryland School of Medicine
Roles: Editor
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1128/mBio.01494-14
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Supplemental Material
  • Additional Files
  • FIG 1 
    • Open in new tab
    • Download powerpoint
    FIG 1 

    Phylogenetic reconstruction shows evidence for clonal expansion in outbreak groups. Maximum likelihood phylogenies were constructed using a matrix of all available SNPs. Bootstrap values are based on 500 replicates. The scale bar indicates the number of substitutions per nucleotide position. (A) Phylogeny based on SNPs unique to VGIIa. ICB107 was also included as it differed at only one MLST marker in previous studies. (B) Phylogeny based on SNPs unique to VGIIb. 99/473-1 was also included as it was similar to VGIIb in previous studies. (C) Phylogeny based on SNPs unique to VGIIc.

  • FIG 2 
    • Open in new tab
    • Download powerpoint
    FIG 2 

    VGIIa outbreak isolates are more closely related to each other than to historical isolates or South American VGII isolates. (A) Prediction of VGIIa population structure based on haplotype network inference. Only SNPs were used to eliminate alignment artifacts. All Pacific Northwest isolates are predicted to share a relatively recent last common ancestor. The South American isolate ICB107, while the closest among isolates included in this analysis, is more distantly related. (B) SNPs distinguishing ICB107 from the VGIIa isolate R265 plotted across the genome. SNPs are distributed across the genome, suggesting ICB107 was not separated from VGIIa by a recent meiotic event.

  • FIG 3 
    • Open in new tab
    • Download powerpoint
    FIG 3 

    VGIIb outbreak isolates cluster more closely with Australian isolates than Caribbean and Florida isolates. Shown is a prediction of VGIIb population structure based on haplotype network inference. Pacific Northwest VGIIb isolates and Australian isolates cluster together, with the exception of the Pacific Northwest isolate B8554 sequenced by the CDC.

  • FIG 4 
    • Open in new tab
    • Download powerpoint
    FIG 4 

    VGIIa-like low-virulence clade has a hypermutator mutation. (A) Read depth across an exon of CNBG_1161 from three VGIIa-like genomes, two VGIIa genomes, one VGIIb genome, and one VGIIc genome. All three VGIIa-like isolates have a single base deletion (denoted with a box) resulting in a frameshift mutation in the MSH2 gene. (B) Results from a conserved domain search for CNBG_1161 performed using the NCBI’s CD search program. CNBG_1161 has strong homology to the MutS or Msh2 domains involved in DNA damage repair.

  • FIG 5 
    • Open in new tab
    • Download powerpoint
    FIG 5 

    VGII phylogenies are incongruent based on different loci. Shown is a pair of maximum likelihood phylogenies generated from the first 100 kb of supercontigs 6 and 7. Clonal clusters are shaded to facilitate comparison. Bootstrap values are based on 500 bootstraps. The scale bar indicates substitutions per nucleotide position. Crossing lines indicate lack of congruence.

  • FIG 6 
    • Open in new tab
    • Download powerpoint
    FIG 6 

    Regions of reduced SNP density provide evidence for ancestral sexual reproduction. (A) SNP density is plotted relative to the R265 reference genome. Clonal groups are collapsed to the SNPs shared by all members of the group. Regions of unexpectedly low levels of polymorphism are boxed for emphasis. (B) Maximum likelihood phylogenies generated from regions of depressed SNP density demarcated in panel A. Bootstrap values are based on 500 bootstraps. The scale bar indicates the number of substitutions per nucleotide position. Outbreak groups are highlighted in larger font, as well as individual global isolates that contribute to the identity island.

  • FIG 7 
    • Open in new tab
    • Download powerpoint
    FIG 7 

    Whole-genome allele compatibility test shows evidence for prolific recombination at the population level. (A) An example of a paired allele compatibility test from the VGII population. Alternative SNPs are depicted in red and the reference in white. Evidence for recombination is provided by any pairwise comparison of two loci in which strains are present where red-red, white-white, red-white, and white-red combinations are all found (AB, Ab, aB, and ab) satisfying the allele compatibility test, providing evidence for recombination. (B) One hundred random SNPs were selected from the VGII data set and collapsed into 46 unique allele patterns. The reference nucleotide is indicated by white and the variant by red. A pairwise comparison of all 46 unique loci is shown, with green shading indicating a positive result and evidence for recombination.

  • FIG 8 
    • Open in new tab
    • Download powerpoint
    FIG 8 

    Genomic islands of high polymorphism on supercontig 13 are caused by two distinct VGII clades. (A) Linkage disequilibria (R2) among SNP loci on supercontig 13. Two regions located between positions 393 and 417 kb were in high linkage disequilibria. (B) Polymorphism among VGII isolates on supercontig 13. An island of high polymorphism colocalized with high linkage disequilibria between positions 393 and 417 kb. (C) The islands of high polymorphism were caused by the presence of two distinct groups of VGII isolates. Exclusion of isolates 2001/935-1 and IP96/1120-1 reduced the polymorphism within VGII to low levels (red area) between positions 393 and 408 kb compared to polymorphism among all VGII isolates (gray area). Exclusion of isolates NT3, NT7, NT8, RDH2, RDH7, and MMRL2647 reduced the polymorphism within VGII to low levels (blue area) between positions 414 and 417 kb compared to polymorphism among all VGII isolates (gray area). (D) Maximum likelihood phylogeny of VGII isolates based on all SNP on supercontig 13. Values indicate bootstrap support among 100 replicates. Isolates 2001/935-1 and IP96/1120-1 and isolates NT3, NT7, NT8, RDH2, RDH7, and MMRL2647 each grouped into a distinct clade of VGII.

  • FIG 9 
    • Open in new tab
    • Download powerpoint
    FIG 9 

    Island of polymorphism on supercontig 13 shows evidence of introgression into VGII. (A) The region of high polymorphism between 393 and 408 kb on supercontig 13 contains three genes (CNBG_4871 to -4873). Variation in GC content in the region is shown in red. (B) Maximum likelihood phylogeny of C. gattii VGI, VGII, VGIII, and VGIV isolates. The tree was constructed based on 297 informative SNPs in the region of 393 to 408 kb on supercontig 13. VGII isolates 2001/935-1 and IP96/1120-1 most closely grouped with VGI. Values indicate bootstrap support among 100 replicates.

  • FIG 10 
    • Open in new tab
    • Download powerpoint
    FIG 10 

    Aligned read depth on supercontigs of IP96/1120-1. Read depth was approximately 2-fold higher than the genome-wide mean coverage on supercontigs 6, 13, and 14. Variation in read depth on supercontigs 6 and 13 suggests partial duplications across the region of the chromosome mapping to these supercontigs. Read depth on supercontig 14 suggests duplication of the entire region represented by this supercontig.

Tables

  • Figures
  • Supplemental Material
  • Additional Files
  • TABLE 1 

    C. gattii genomes sequenceda

    Population and strainOriginMating typeSequenced by
    VGIIa
        R265Vancouver Island, clinicalMATαBroad Institute
        RB1Vancouver Island, environmentalMATαHeitman lab
        RB59Vancouver Island, environmentalMATαHeitman lab
        EJB17Oregon, veterinaryMATαHeitman lab/CDC
        EJB21 (or B7467)Oregon, clinicalMATαHeitman lab
        B7395Washington, clinicalMATαHeitman lab/CDC
        B7436California, veterinaryMATαHeitman lab
        R498Vancouver Island, veterinaryMATαHeitman lab
        R265 reseqVancouver Island, clinicalMATαHeitman lab
        B7422Oregon, veterinaryMATαCDC
        B8849Oregon, environmentalMATαCDC
        B8577British Columbia, environmentalMATαCDC
    VGIIa-like
        ICB107Brazil, clinicalMATαHeitman lab
        CBS7750San Francisco, environmentalMATαHeitman lab
        NIH444Seattle, clinical, 1975MATαHeitman lab
    VGIIb
        R272Vancouver Island, clinicalMATαHeitman lab
        NT13Australia, Northern TerritoryMATαHeitman lab
        B7394Washington, veterinaryMATαCDC
        B7735Oregon, clinicalMATαCDC
        B8554Oregon, veterinaryMATαCDC
        B8828Washington, veterinaryMATαCDC
        RDH6Australia, Northern Territory, clinicalMATαHeitman lab
        V9Australia, veterinaryMATαHeitman lab
        V6Australia, veterinaryMATαHeitman lab
        V26Australia, veterinaryMATαHeitman lab
    VGIIb-like
        99/473-1Caribbean Islands, clinicalMATαHeitman lab
        B9588Florida, clinicalMATαHeitman lab
    VGIIc
        B8571Washington, clinicalMATαCDC
        B8843Oregon, clinicalMATαCDC
        B8838Washington, clinicalMATαCDC
        B7466 (or EJB52)Oregon, veterinaryMATαCDC
        B7737Oregon, clinicalMATαCDC
        B6863Oregon, clinicalMATαCDC
        B7390Idaho, clinicalMATαCDC
        B7432Oregon, clinicalMATαCDC
        EJB87Oregon, veterinaryMATαHeitman lab
        EJB18Oregon, clinicalMATαHeitman lab
    VGIIMATa
        LA499Colombia, clinicalMATaHeitman lab
        CBS1930Aruba, veterinaryMATaHeitman lab
        VBGc11Puerto Rico, environmentalMATaHeitman lab
    VGIInt
        NT3Australia, Northern Territory, clinicalMATαHeitman lab
        NT7Australia, Northern Territory, clinicalMATαHeitman lab
        NT8Australia, Northern Territory, clinicalMATαHeitman lab
        RDH2Australia, clinicalMATαHeitman lab
        RDH7Australia, Northern Territory, clinicalMATαHeitman lab
    VGII
        78-5-46Utah, clinicalMATαHeitman lab
        ICB182Brazil, clinicalMATαHeitman lab
        ICB183Brazil, environmentalMATαHeitman lab
        ICB184Brazil, environmentalMATαHeitman lab
        WA861Western Australia, veterinaryMATαHeitman lab
        WM178Sydney, Australia, clinicalMATαHeitman lab
        IP96/1120-1French, clinicalMATαHeitman lab
        2003.125French, clinicalMATαHeitman lab
        93.980French, clinicalMATαHeitman lab
        98.1132Caribbean, clinicalMATαHeitman lab
    • ↵a The strains utilized in this study are listed. The source of the sequence is indicated, with “Heitman lab” designating isolates newly sequenced in this study.

Supplemental Material

  • Figures
  • Tables
  • Additional Files
  • Table S1

    Predicted impact of VGIIa-like SNPs and indels. SNPeff predictions of SNP and indel effects on genes that divide the VGIIa and VGIIa-like lineages. Table S1, PDF file, 0.1 MB.

    Copyright © 2014 Billmyre et al.

    This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • Figure S1

    MAT locus shows evidence of gene conversion. (A) Maximum likelihood phylogeny was derived from alignment of the MAT locus. This region corresponds to R265 supercontig 18, from nucleotides 26430 to 121589. Five hundred bootstraps were used to calculate support. The scale bar indicates substitutions per nucleotide site. (B) Allele compatibility test of region that is suggestive of recombination/gene conversion within the MAT locus. Reference alleles are indicated in green and alternate alleles in red. Each locus depicted is biallelic. In the paired allele compatibility diagram below, evidence for recombination is indicated by the presence of all four alleles and an hourglass shape, which is colored red for emphasis. Stars indicate loci containing allele combinations found only once within MAT, which break apart otherwise conserved haplotypes. Download Figure S1, PDF file, 0.1 MB.

    Copyright © 2014 Billmyre et al.

    This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • Figure S2

    Amino acid polymorphisms in proteins encoded by genes CNBG_4871 to -4873 located in the introgressed region of the VGII isolates 2001/935-1 and IP96/1120-1. Variable amino acid positions are shown for distinct protein haplotypes grouped by the VG type of C. gattii. The protein haplotype found in introgressed isolates 2001/935-1 and IP96/1120-1 is highlighted in yellow. Download Figure S2, PDF file, 0.1 MB.

    Copyright © 2014 Billmyre et al.

    This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • Figure S3

    Supercontig copy number variation among VGII isolates. The aligned read depth of resequenced isolates was normalized to the genome-wide mean coverage. Orange represents supercontigs with a read depth identical to the genome-wide average (normalized to 1). Red shows supercontigs with a 2-fold-increased read depth compared to the genome-wide average. Shades of color between orange and red indicate supercontigs with putative partial duplications. Download Figure S3, PDF file, 0.1 MB.

    Copyright © 2014 Billmyre et al.

    This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • Figure S4

    French clinical isolate 93.980 has highly aneuploid supercontig 6. Depth of coverage across supercontig 6 of 93.980 was determined using the IGVtools count program and visualized using IGV (45). The genome average depth of coverage is indicated by a solid black horizontal line. Regions of the supercontig 6 range include 1N, 2N, 3N, 4N, 5N, and 6N. Download Figure S4, PDF file, 0.1 MB.

    Copyright © 2014 Billmyre et al.

    This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • Table S2

    Outgroup isolates for introgression analyses. Additional VGI, VGII, VGIII, and VGIV isolates were used as outgroups in the phylogenetic introgression analyses. Table S2, PDF file, 0.1 MB.

    Copyright © 2014 Billmyre et al.

    This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • Text S1

    Scripts. Download Text S1, TXT file, 0.1 MB.

    Copyright © 2014 Billmyre et al.

    This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

Additional Files

  • Figures
  • Tables
  • Supplemental Material
  • Supplementary Data

    Supplementary Data

    Files in this Data Supplement:

    • Figure sf01, PDF - Figure sf01, PDF
    • Figure sf02, PDF - Figure sf02, PDF
    • Figure sf03, PDF - Figure sf03, PDF
    • Figure sf04, PDF - Figure sf04, PDF
    • Table st1, PDF - Table st1, PDF
    • Table st2, PDF - Table st2, PDF
    • Text s1, TXT - Text s1, TXT
PreviousNext
Back to top
Download PDF
Citation Tools
Highly Recombinant VGII Cryptococcus gattii Population Develops Clonal Outbreak Clusters through both Sexual Macroevolution and Asexual Microevolution
R. Blake Billmyre, Daniel Croll, Wenjun Li, Piotr Mieczkowski, Dee A. Carter, Christina A. Cuomo, James W. Kronstad, Joseph Heitman
mBio Jul 2014, 5 (4) e01494-14; DOI: 10.1128/mBio.01494-14

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Print

Alerts
Sign In to Email Alerts with your Email Address
Email

Thank you for sharing this mBio article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Highly Recombinant VGII Cryptococcus gattii Population Develops Clonal Outbreak Clusters through both Sexual Macroevolution and Asexual Microevolution
(Your Name) has forwarded a page to you from mBio
(Your Name) thought you would be interested in this article in mBio.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Highly Recombinant VGII Cryptococcus gattii Population Develops Clonal Outbreak Clusters through both Sexual Macroevolution and Asexual Microevolution
R. Blake Billmyre, Daniel Croll, Wenjun Li, Piotr Mieczkowski, Dee A. Carter, Christina A. Cuomo, James W. Kronstad, Joseph Heitman
mBio Jul 2014, 5 (4) e01494-14; DOI: 10.1128/mBio.01494-14
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Top
  • Article
    • ABSTRACT
    • INTRODUCTION
    • RESULTS
    • DISCUSSION
    • MATERIALS AND METHODS
    • SUPPLEMENTAL MATERIAL
    • ACKNOWLEDGMENTS
    • FOOTNOTES
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

Cited By...

About

  • About mBio
  • Editor in Chief
  • Board of Editors
  • AAM Fellows
  • Policies
  • For Reviewers
  • For the Media
  • For Librarians
  • For Advertisers
  • Alerts
  • RSS
  • FAQ
  • Permissions
  • Journal Announcements

Authors

  • ASM Author Center
  • Submit a Manuscript
  • Author Warranty
  • Article Types
  • Ethics
  • Contact Us

Follow #mBio

@ASMicrobiology

       

ASM Journals

ASM journals are the most prominent publications in the field, delivering up-to-date and authoritative coverage of both basic and clinical microbiology.

About ASM | Contact Us | Press Room

 

ASM is a member of

Scientific Society Publisher Alliance

 

American Society for Microbiology
1752 N St. NW
Washington, DC 20036
Phone: (202) 737-3600

Copyright © 2021 American Society for Microbiology | Privacy Policy | Website feedback

Online ISSN: 2150-7511