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Updated: May 22, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
Population genetic analysis of Enterocytozoon bieneusi in humans
Wei Li1, Vitaliano Cama, Yaoyu Feng
1Division of Foodborne, Waterborne and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.
Abstract:
Genotyping based on sequence analysis of the ribosomal internal transcribed spacer has revealed significant genetic diversity in Enterocytozoonbieneusi. Thus far, the population genetics of E. bieneusi and its significance in the epidemiology of microsporidiosis have not been examined. In this study, a multilocus sequence typing of E. bieneusi in AIDS patients in Lima, Peru was conducted, using 72 specimens previously genotyped as A, D, IV, EbpC, WL11, Peru7, Peru8, Peru10 and Peru11 at the internal transcribed spacer locus. Altogether, 39 multilocus genotypes were identified among the 72 specimens. The observation of strong intragenic linkage disequilibria and limited genetic recombination among markers were indicative of an overall clonal population structure of E. bieneusi. Measures of pair-wise intergenic linkage disequilibria and a standardised index of association (IAS) based on allelic profile data further supported this conclusion. Both sequence-based and allelic profile-based phylogenetic analyses showed the presence of two genetically isolated groups in the study population, one (group 1) containing isolates of the anthroponotic internal transcribed spacer genotype A, and the other (group 2) containing isolates of multiple internal transcribed spacer genotypes (mainly genotypes D and IV) with zoonotic potential. The measurement of linkage disequilibria and recombination indicated group 2 had a clonal population structure, whereas group 1 had an epidemic population structure. The formation of the two sub-populations was confirmed by STRUCTURE and Wright's fixation index (FST) analyses. The data highlight the power of MLST in understanding the epidemiology of E. bieneusi.
