Aspergillus aureoterreus, A. pseudonomiae, A. siamensis, andA. flocculosus-ochraceopetaliformis as Four New Pathogensof Eye Infection in DNA Barcoding Markers

Background: The use of a morphological method to determine Aspergillus species in routine laboratory investigation has always been challenged with low sensitivity and low specificity. Time-consuming specimen preparation and insufficient expertise are the crucial reasons. DNA barcoding markers have been introduced for identification as another gold standard method. Objective: To investigate DNA barcoding markers in identifying Aspergillus strains isolated from patients with eye infection. Methods: This study extracted 12 DNA samples of 12 Aspergillus strains. DNA barcoding genes, i.e., ITS, betatubulin (BT2), calmodulin (CAL), and actin (ACT) genes, were amplified and sequenced by polymerase chain reaction and Sanger's sequencing methods. All gene sequences were compared to those of the type or reference species collected from public databases. The species were identified with phylogenetic analyses in free applications from public websites. Results: ITS, BT2 and CAL, and ACT identified 5, 6, and 3 species and 3, 2, and 1 species complex of Aspergillus, respectively. DNA barcoding with multi-locus sequence typing revealed four new pathogens of human eye infection, including A. aureoterreus, A. pseudonomiae, A. siamensis, and A. flocculosus-ochraceopetaliformis. Conclusion: The DNA barcoding markers identified Aspergillus species with better specificity than the conventional method. The markers and techniques need to be used as tools for routine Aspergillus identification.

Authors

Institutions

Publication Details

Journal
Journal of Mycology and Infection
Published
2024-09-30
DOI
https://doi.org/10.17966/jmi.2024.29.3.137
Primary Topic
Infectious Diseases and Mycology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Aspergillus aureoterreus, A. pseudonomiae, A. siamensis, andA. flocculosus-ochraceopetaliformis as Four New Pathogensof Eye Infection in DNA Barcoding Markers

Lumyai Wonglakorn, Kittipan Samerpitak, T. Khoi, Waewta Kuwatjanakul
Journal of Mycology and Infection
Infectious Diseases and Mycology
article

Aspergillus aureoterreus, A. pseudonomiae, A. siamensis, andA. flocculosus-ochraceopetaliformis as Four New Pathogensof Eye Infection in DNA Barcoding Markers

Lumyai Wonglakorn, Kittipan Samerpitak, T. Khoi, Waewta Kuwatjanakul
article en

Abstract

Background: The use of a morphological method to determine Aspergillus species in routine laboratory investigation has always been challenged with low sensitivity and low specificity. Time-consuming specimen preparation and insufficient expertise are the crucial reasons. DNA barcoding markers have been introduced for identification as another gold standard method. Objective: To investigate DNA barcoding markers in identifying Aspergillus strains isolated from patients with eye infection. Methods: This study extracted 12 DNA samples of 12 Aspergillus strains. DNA barcoding genes, i.e., ITS, betatubulin (BT2), calmodulin (CAL), and actin (ACT) genes, were amplified and sequenced by polymerase chain reaction and Sanger's sequencing methods. All gene sequences were compared to those of the type or reference species collected from public databases. The species were identified with phylogenetic analyses in free applications from public websites. Results: ITS, BT2 and CAL, and ACT identified 5, 6, and 3 species and 3, 2, and 1 species complex of Aspergillus, respectively. DNA barcoding with multi-locus sequence typing revealed four new pathogens of human eye infection, including A. aureoterreus, A. pseudonomiae, A. siamensis, and A. flocculosus-ochraceopetaliformis. Conclusion: The DNA barcoding markers identified Aspergillus species with better specificity than the conventional method. The markers and techniques need to be used as tools for routine Aspergillus identification.

Journal of Mycology and Infection
Khon Kaen University (TH)
Openalex Percentile: Top 79%
Infectious Diseases and Mycology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.