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Multilocus DNA sequence comparisons rapidly identify pathogenic molds.

ABSTRACT: The increasing incidence of opportunistic fungal infections necessitates rapid and accurate identification of the associated fungi to facilitate optimal patient treatment. Traditional phenotype-based identification methods utilized in clinical laboratories rely on the production and recognition of reproductive structures, making identification difficult or impossible when these structures are not observed. We hypothesized that DNA sequence analysis of multiple loci is useful for rapidly identifying medically important molds. Our study included the analysis of the D1/D2 hypervariable region of the 28S ribosomal gene and the internal transcribed spacer (ITS) regions 1 and 2 of the rRNA operon. Two hundred one strains, including 143 clinical isolates and 58 reference and type strains, representing 43 recognized species and one possible new species, were examined. We generated a phenotypically validated database of 118 diagnostic alleles. DNA length polymorphisms detected among ITS1 and ITS2 PCR products can differentiate 20 of 33 species of molds tested, and ITS DNA sequence analysis permits identification of all species tested. For 42 of 44 species tested, conspecific strains displayed >99% sequence identity at ITS1 and ITS2; sequevars were detected in two species. For all 44 species, identifications by genotypic and traditional phenotypic methods were 100% concordant. Because dendrograms based on ITS sequence analysis are similar in topology to 28S-based trees, we conclude that ITS sequences provide phylogenetically valid information and can be utilized to identify clinically important molds. Additionally, this phenotypically validated database of ITS sequences will be useful for identifying new species of pathogenic molds.

SUBMITTER: Rakeman JL

PROVIDER: S-EPMC1169180 | biostudies-literature | 2005 Jul

REPOSITORIES: biostudies-literature

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Multilocus DNA sequence comparisons rapidly identify pathogenic molds.

Rakeman Jennifer L JL Bui Uyen U Lafe Karen K Chen Yi-Ching YC Honeycutt Rhonda J RJ Cookson Brad T BT

Journal of clinical microbiology 20050701 7

The increasing incidence of opportunistic fungal infections necessitates rapid and accurate identification of the associated fungi to facilitate optimal patient treatment. Traditional phenotype-based identification methods utilized in clinical laboratories rely on the production and recognition of reproductive structures, making identification difficult or impossible when these structures are not observed. We hypothesized that DNA sequence analysis of multiple loci is useful for rapidly identify ...[more]

PMID: 16000456

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Project description:Brucellosis poses a significant burden to human and animal health worldwide. Robust and harmonized molecular epidemiological approaches and population studies that include routine disease screening are needed to efficiently track the origin and spread of Brucella strains. Core genome multilocus sequence typing (cgMLST) is a powerful genotyping system commonly used to delineate pathogen transmission routes for disease surveillance and control. Except for Brucella melitensis, cgMLST schemes for Brucella species are currently not established. Here, we describe a novel cgMLST scheme that covers multiple Brucella species. We first determined the phylogenetic breadth of the genus using 612 Brucella genomes. We selected 1,764 genes that were particularly well conserved and typeable in at least 98% of these genomes. We tested the new scheme on 600 genomes and found high agreement with the whole-genome-based single nucleotide polymorphism (SNP) analysis. Next, we applied the scheme to reanalyze the genome of Brucella strains from epidemiologically linked outbreaks. We demonstrated the applicability of the new scheme for high-resolution typing required in outbreak investigations as previously reported with whole-genome SNP methods. We also used the novel scheme to define the global population structure of the genus using 1,322 Brucella genomes. Finally, we demonstrated the possibility of tracing distribution of Brucella strains by performing cluster analysis of cgMLST profiles and found nearly identical cgMLST profiles in different countries. Our results show that sequencing depth of more than 40-fold is optimal for allele calling with this scheme. In summary, this study describes a novel Brucella-wide cgMLST scheme that is applicable in Brucella molecular epidemiology and helps in accurately tracking and thus controlling the sources of infection. The scheme is publicly accessible and should represent a valuable resource for laboratories with limited computational resources and bioinformatics expertise.

Dataset Information

Multilocus DNA sequence comparisons rapidly identify pathogenic molds.

Publications

Multilocus DNA sequence comparisons rapidly identify pathogenic molds.

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