Assessing the reliability of eBURST using simulated populations with known ancestry
File(s)
Author(s)
Turner, KME
Hanage, WP
Fraser, C
Connor, TR
Spratt, BG
Type
Journal Article
Abstract
Background:
The program eBURST uses multilocus sequence typing data to divide bacterial
populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evolutionary descent of all other strains in the group from the founder. The reliability of eBURST was evaluated using populations simulated with different levels of recombination in which the ancestry of all strains was known.
Results:
For strictly clonal simulations, where all allelic change is due to point mutation, the groups of related strains identified by eBURST were very similar to those expected from the true ancestry and most of the true ancestor-descendant rela
tionships (90–98%) were identified by eBURST. Populations simulated with low or moderate levels of recombination showed similarly high performance but the reliability of eBURST declined with increasing recombination to mutation
ratio. Populations simulated under a high recombination to mutation ratio were dominated by a single large straggly eBURST group, which resulted from the incorrect linking of unrelated groups of strains into the same eBURST group. The reliability of the ancestor-descendant links in eBURST diagrams was related to the proportion of strains in the largest eBURST group, which provides a
useful guide to when eBURST is likely to be unreliable.
Conclusion:
Examination of eBURST groups within populations of a range of bacterial species
showed that most were within the range in which eBURST is reliable, and only a small number (e.g. Burkholderia pseudomallei and Enterococcus faecium) appeared to have such high rates of recombination that eBURST is likely to be unrel iable. The study also demonstrates how three simple tests in eBURST v3 can be used to detect unreliable eBURST performance and recognise
populations in which there appears to be a high rate of recombination
relative to mutation.
The program eBURST uses multilocus sequence typing data to divide bacterial
populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evolutionary descent of all other strains in the group from the founder. The reliability of eBURST was evaluated using populations simulated with different levels of recombination in which the ancestry of all strains was known.
Results:
For strictly clonal simulations, where all allelic change is due to point mutation, the groups of related strains identified by eBURST were very similar to those expected from the true ancestry and most of the true ancestor-descendant rela
tionships (90–98%) were identified by eBURST. Populations simulated with low or moderate levels of recombination showed similarly high performance but the reliability of eBURST declined with increasing recombination to mutation
ratio. Populations simulated under a high recombination to mutation ratio were dominated by a single large straggly eBURST group, which resulted from the incorrect linking of unrelated groups of strains into the same eBURST group. The reliability of the ancestor-descendant links in eBURST diagrams was related to the proportion of strains in the largest eBURST group, which provides a
useful guide to when eBURST is likely to be unreliable.
Conclusion:
Examination of eBURST groups within populations of a range of bacterial species
showed that most were within the range in which eBURST is reliable, and only a small number (e.g. Burkholderia pseudomallei and Enterococcus faecium) appeared to have such high rates of recombination that eBURST is likely to be unrel iable. The study also demonstrates how three simple tests in eBURST v3 can be used to detect unreliable eBURST performance and recognise
populations in which there appears to be a high rate of recombination
relative to mutation.
Date Issued
2007-04-12
Date Acceptance
2007-04-12
Citation
BMC Microbiology, 2007, 7
ISSN
1471-2180
Publisher
BioMed Central
Journal / Book Title
BMC Microbiology
Volume
7
Copyright Statement
© 2007 Turner et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution
License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the orig
inal work is properly cited.
This is an Open Access article distributed under the terms of the Creative Commons Attribution
License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the orig
inal work is properly cited.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000246364100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Life Sciences & Biomedicine
Microbiology
Bacteria
Computer Simulation
Genotype
Models, Genetic
Mutation
Phylogeny
Reproducibility of Results
Sensitivity and Specificity
Software
Biological Sciences
Medical And Health Sciences
Agricultural And Veterinary Sciences
Publication Status
Published
Article Number
ARTN 30