Comparative analyses of clinical and environmental populations of Cryptococcus neoformans in Botswana.
Date
2015-07
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Citation Stats
Attention Stats
Abstract
Cryptococcus neoformans var. grubii (Cng) is the most common cause of fungal meningitis, and its prevalence is highest in sub-Saharan Africa. Patients become infected by inhaling airborne spores or desiccated yeast cells from the environment, where the fungus thrives in avian droppings, trees and soil. To investigate the prevalence and population structure of Cng in southern Africa, we analysed isolates from 77 environmental samples and 64 patients. We detected significant genetic diversity among isolates and strong evidence of geographic structure at the local level. High proportions of isolates with the rare MATa allele were observed in both clinical and environmental isolates; however, the mating-type alleles were unevenly distributed among different subpopulations. Nearly equal proportions of the MATa and MATĪ± mating types were observed among all clinical isolates and in one environmental subpopulation from the eastern part of Botswana. As previously reported, there was evidence of both clonality and recombination in different geographic areas. These results provide a foundation for subsequent genomewide association studies to identify genes and genotypes linked to pathogenicity in humans.
Type
Department
Description
Provenance
Subjects
Citation
Permalink
Published Version (Please cite this version)
Publication Info
Chen, Yuan, Anastasia P Litvintseva, Aubrey E Frazzitta, Miriam R Haverkamp, Liuyang Wang, Charles Fang, Charles Muthoga, Thomas G Mitchell, et al. (2015). Comparative analyses of clinical and environmental populations of Cryptococcus neoformans in Botswana. Mol Ecol, 24(14). pp. 3559ā3571. 10.1111/mec.13260 Retrieved from https://hdl.handle.net/10161/11053.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Collections
Scholars@Duke
Liuyang Wang
Leveraging bioinformatics and big data to understand the intricacies of human diseases.
My overall research goals are centered on unraveling the molecular mechanism underpinning human disease susceptibility and harnessing these findings to innovative diagnostic and therapeutic strategies. I have adopted a multidisciplinary approach that integrates genomics, transcriptomics, and computational biology. Leveraging high-throughput cellular screening and genome-wide association study (GWAS), we have successfully identified hundreds of genomic loci associated with 8 different pathogens (Wang et al. 2018). Utilizing single-cell RNA-seq, we developed scHi-HOST to rapidly identify host genes associated with the influenza virus (Schott and Wang, et al. 2022). I also have developed several novel statistical tools, CPAG and iCPAGdb, that estimate genetic associations among human diseases and traits (Wang et al. 2015, 2021). Combining experimental and computational approaches, I expect to gain a deeper understanding of the genetic architecture of human susceptibility to infection and inflammatory disorders.
Thomas Greenfield Mitchell
Among patients with AIDS, leukemia or other cancers, organ or bone marrow transplants, and similar immunocompromising risk factors, the incidence of opportunistic mycoses and the number of different fungal pathogens are increasing dramatically. For many of these fungi, the definition of a species and the recognition of pathogen are highly problematic. Conventional methods of identification are based on morphological and physiological characteristics and are often time-consuming, difficult to interpret, and inconsistent. This laboratory is using DNA-based methods to (i) identify fungal pathogens, (ii) resolve taxonomic issues, (iii) facilitate epidemiological studies, (iv) recognize strains with clinically relevant phenotypes, such as resistance to antifungal drugs, (v) elucidate the origin(s) of diversity and the population genetics of the major pathogens, and (vi) explore functional genomics to identify virulence factors. We have developed reliable methods to genotype strains and are analyzing gene sequences to clarify the phylogeny of controversial taxa.
To conduct rigorous population studies of Candida albicans, we developed single-locus markers based on polymorphisms of PCR products. Genotypic frequencies and segregation patterns at these loci have confirmed that C. albicans is diploid and suggest that some form of recombination occurs in this "asexual" yeast. To investigate whether separate populations of C. albicans exist in disparate geographical locations, we compared strains collected from healthy and HIV-infected persons in U.S. and Brazil. Although a number of different genotypes were recognized at each location, the same multilocus genotype was prevalent among the clinical isolates, indicating a remarkable homogeneity among these populations.
We are using DNA-based methods to compare global isolates of Cryptococcus neoformans from patients with AIDS and other sources, to analyze the distribution and relatedness of strains, to identify genotypes of clinical importance, and to create linkage map of this pathogen. To determine the source of C. neoformans in patients, we developed a genetic markers to investigate the structure of clinical and environmental populations. With analysis of quantitative trait loci, specific genotypes will be identified that represent clones that have significantly diverged with respect to clinically relevant phenotypes, including susceptibility to antifungal drugs and the expression of virulence factors. We are investigating genomic evolution and phenotypic variation in natural populations of C. neoformans. These approaches will correlate genotypes with pathobiological phenotypes, leading to beneficial and predictive information about the epidemiology, diagnosis and prognosis of cryptococcosis in patients with AIDS.
John Robert Perfect
Research in my laboratory focuses around several aspects of medical mycology. We are investigating antifungal agents (new and old) in animal models of candida and cryptococcal infections. We have examined clinical correlation of in vitro antifungal susceptibility testing and with in vivo outcome. Our basic science project examines the molecular pathogenesis of cryptococcal infections. We have developed a molecular foundation for C. neoformans, including transformation systems, gene disruptions, differential gene expression screens, and cloning pathogenesis genes. The goal of this work is to use C. neoformans as a model yeast system to identify molecular targets for antifungal drug development. There are a series of clinical trials in fungal infections which are being coordinated through this laboratory and my work also includes a series of antibiotic trials in various aspects of infections. Finally, we have now been awarded a NIH sponsored Mycology Unit for 5 years with 6 senior investigators which is focused on C. neoformans as a pathogenic model system, but will include multiple areas of medical mycology from diagnosis to treatment.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the authorās grant of a non-exclusive license to make their work openly accessible.