Estimating the Intra-taxa Diversity, Population Genetic Structure, and Evolutionary Pathways of Cryptococcus neoformans and Cryptococcus gattii.

Abstract:

:Members of the Cryptococcus complex, includes Cryptococcus neoformans (most common fungal infection of the brain) and Cryptococcus gattii (high-impact emerging pathogen worldwide). Currently, the fungal multilocus sequence typing database (Fungal MLST Database) constitutes a valuable data repository of the genes used for molecular typing of these pathogens. We analyzed the data available in the Fungal MLST Database for seven housekeeping genes, with the aim to evaluate its contribution in the description of intra-taxa diversity, population genetic structure, and evolutionary patterns. Although the Fungal MLST Database has a greater number of reports for C. neoformans (n = 487) than for C. gattii (n = 344), similar results were obtained for both species in terms of allelic diversity. Phylogenetic reconstructions revealed grouping by molecular type in both species and allowed us to propose differences in evolutionary patterns (gradualism in the case of C. neoformans and punctuated evolution in the case of C. gattii). In addition, C. neoformans showed a population genetic structure consisting of 37 clonal complexes (CCs; CC1 being predominant), high crosslinking [without sequence type (ST) grouping by molecular type], marked divergence events in phylogenetic analysis, and few introgression events (mainly between VNI and VNIV). By contrast, C. gattii showed 50 CCs (with greater homogeneity in ST number by CC) and clustering by molecular type with marked crosslinking events in phylogenetic networks being less evident. Understanding relationships at the molecular level for species of the Cryptococcus complex, based on the sequences of the housekeeping genes, provides information for describing the evolutionary history of these emerging pathogens.

journal_name

Front Genet

journal_title

Frontiers in genetics

authors

Muñoz M,Camargo M,Ramírez JD

doi

10.3389/fgene.2018.00148

subject

Has Abstract

pub_date

2018-04-24 00:00:00

pages

148

issn

1664-8021

journal_volume

9

pub_type

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