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Discrimination of three genetically close Aspergillus species by using high resolution melting analysis applied to
Xavier Libert1,2, Ann Packeu2, Fabrice Bureau3
1Platform Biotechnology and Molecular Biology, Scientific Institute of Public Health (WIV-ISP), J. Wytsmanstraat 14, 1050, Brussels, Belgium.
Background:
Indoor air pollution caused by fungal contamination is suspected to have a public health impact. Monitoring of the composition of the indoor airborne fungal contaminants is therefore important. To avoid problems linked to culture-dependent protocols, molecular methods are increasingly being proposed as an alternative. Among these molecular methods, the polymerase chain reaction (PCR) and the real-time PCR are the most frequently used tools for indoor fungal detection. However, even if these tools have demonstrated their appropriate performance, some of them are not able to discriminate between species which are genetically close. A solution to this could be the use of a post-qPCR high resolution melting (HRM) analysis, which would allow the discrimination of these species based on the highly accurate determination of the difference in melting temperature of the obtained amplicon. In this study, we provide a proof-of-concept for this approach, using a dye adapted version of our previously developed qPCR SYBR®Green method to detect Aspergillus versicolor in indoor air, an important airborne fungus in terms of occurrence and cause of health problems. Despite the good performance observed for that qPCR method, no discrimination could previously be made between A. versicolor, Aspergillus creber and Aspergillus sydowii.
Methods:
In this study, we developed and evaluated an HRM assay for the discrimination between A. versicolor, Aspergillus creber and Aspergillus sydowii.
Results:
Using HRM analysis, the discrimination of the 3 Aspergillus species could be made. No false positive, nor false negatives were observed during the performance assessment including 20 strains of Aspergillus. The limit of detection was determined for each species i.e., 0.5 pg of gDNA for A. creber and A. sydowii, and 0.1 pg of gDNA for A. versicolor. The HRM analysis was also successfully tested on environmental samples.
Conclusion:
We reported the development of HRM tools for the discrimination of A. versicolor, A. creber and A. sydowii. However, this study could be considered as a study case demonstrating that HRM based on existing qPCR assays, allows a more accurate identification of indoor air contaminants. This contributes to an improved insight in the diversity of indoor airborne fungi and hence, eventually in the causal link with health problems.
Insights
High-resolution melting (HRM) analysis accurately distinguishes closely related Aspergillus species in indoor air. This molecular method improves the detection of fungal contaminants linked to health issues.
Area of Science:
- Environmental microbiology
- Molecular diagnostics
- Public health
Background:
- Indoor air pollution from fungal contamination poses public health risks.
- Molecular methods like polymerase chain reaction (PCR) are used for fungal detection but struggle to differentiate closely related species.
- Accurate identification of airborne fungi is crucial for understanding their health impacts.
Purpose of the Study:
- To develop and evaluate a high-resolution melting (HRM) assay for discriminating between Aspergillus versicolor, Aspergillus creber, and Aspergillus sydowii.
- To demonstrate the utility of HRM analysis as a post-real-time PCR method for enhanced fungal identification.
Main Methods:
- A dye-adapted, previously developed real-time PCR SYBR®Green method was utilized.
- High-resolution melting (HRM) analysis was applied post-real-time PCR to differentiate amplicons.
- The assay was tested on 20 Aspergillus strains and environmental samples.
Main Results:
- The HRM assay successfully discriminated between A. versicolor, A. creber, and A. sydowii.
- No false positives or negatives were observed, with limits of detection as low as 0.1 pg gDNA for A. versicolor.
- The HRM analysis demonstrated effectiveness on environmental samples.
Conclusions:
- HRM analysis, when integrated with existing qPCR assays, provides a more accurate identification of indoor airborne fungal contaminants.
- This improved identification enhances understanding of fungal diversity indoors and its potential links to health problems.
- The developed HRM tools offer a valuable advancement for monitoring indoor air quality and associated health risks.