Author:
E Bradshaw1, P Chandorkar2, E Hopwood3, E Kington3, MD Richardson2,3, R Rautemaa-Richardson2,3, L Novak Frazer2,3*
Author address:
1National Aspergillosis Centre, Manchester University NHS Foundation Trust, Manchester, UK
2Mycology Reference Centre Manchester, ECMM Centre of Excellence, Manchester University NHS Foundation Trust, Manchester, UK
3Faculty of Biological Sciences, University of Manchester, Manchester, UK
Full conference title:
10th Advances Against Aspergillosis and Mucormycosis
Date: 2 February 2022
Abstract:
Purpose:
The Mycology Reference Centre Manchester processes respiratory specimens from patients with invasive, chronic pulmonary, and allergic bronchopulmonary aspergillosis, who attend the National Aspergillosis Centre. Alongside high-volume culture, quantitative PCR (qPCR) is used to detect and quantify Aspergillus species; both tests help guide systemic antifungal drug therapy. The ELITech Aspergillus spp. ELITe MGB® qPCR uses a specific 18S rRNA molecular beacon probe linked to a minor groove binding (MGB) reagent that allows use of a particularly short probe. However, given the known homology of the Aspergillus 18S rRNA region to non-Aspergillus species, we suspected there was significant cross-reactivity that could lead to false positive results. We investigated which of the non-Aspergillus species known to be cultured from our patients could produce a positive qPCR (and how strong), as well as whether non-Aspergillus species could be distinguished using melt curve analysis.
Methods:
We evaluated the performance of the CE-IVD validated qPCR with 5 Aspergillus species, 15 closely related moulds (including Penicillium, Talaromyces, Thermomyces, Hamigera, Paecilomyces, and Rasamsonia) and 3 non-related moulds (Trichophyton, Fusarium and Scedosporium). DNA from 20,000 spores was extracted using the same protocol as used for respiratory specimens: suspensions were processed using the ELITech EXTRABlood prelysis kit and extracted using the ELITe Star automated platform. Melt curve data was generated using the ABI 7500 Fast Dx System and 5 control species: A. fumigatus, A. flavus, A. niger, A. terreus, A. sydowii. The qPCR results and melt curves from 2459 patient specimens were also analysed to determine if melt curve analysis could predict non-Aspergillus DNA.
Results:
All 5 control Aspergillus species gave strong positive qPCR result (5,800-88,700 copies). Melting temperatures were similar among A. fumigatus, A. flavus and A. sydowii (68°C), with a slightly higher temperature (69°C) for A. niger and A. terreus.
Strong positive results were also produced by Penicillium chrysogenum, P. rubens and Paecilomyces variotii, albeit with fewer copies (all <3,000). Their melting temperatures (67-68°C) were very similar to Aspergillus controls. Rasamsonia piperina also gave a strong positive result but with a distinctly lower melt temperature (64°C). The melt temperatures of other species
were significantly lower than that for Aspergillus and the 3 non-related species were qPCR negative.
Melt curve data from 2,459 patient samples compared to standards and positive extraction controls suggested that 56 demonstrated melting temperature differences that could be associated with false positives.
Conclusion:
Two Penicillium species and Paecilomyces variotii were qPCR-positive, with melt curves that could not be distinguished from Aspergillus. Although care must be taken when interpreting the results of this test in a clinical context, the frequency of these events was minimal and supported by positive HVC. Approximately 2.3% of patient positive qPCRs with unusual melt curves may have been false positives caused by cross-reactivity with other species. Moreover, melt curve analysis could not distinguish between A. fumigatus, A. flavus and A. sydowii, but further analysis may resolve A. niger and A. terreus. We are currently investigating the use of an A. fumigatus-specific probe.
Abstract Number: 37
Conference Year: 2022
Link to conference website: https://aaam2022.org/
Tables:
Link Conference abstract:
Conference abstracts, posters & presentations
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Title
Author
Year
Number
Poster
-
v
Vasireddy Teja, Bibhuti Saha Hod, Soumendranath Haldar (IN)
2024
81
n/a
-
v
Rose-Anne Lavergne (FR)
2024
79
n/a
-
v
Rutuja H. Patil1, Tereza Juříková1, Andrea Palyzová1, and Vladimír Havlíček1,2
2024
78
n/a
-
v
Rui Xu1-2,, Chuqin Huang1 , Rong Yan1, Yanyan Lou1-2, Bo Zhang1, Yingyi Pan1, Yingying Liu1, Sini Huang1, Zhiyuan Zhang1, Antonin Tidu2, Thorsten Heinekamp3, Philippe Bulet4, Franck Martin2, , Axel Brakhage3, Li Zi1, Samuel Liegeois1-2, Dominique Ferrandon* 1-2
2024
75
n/a
-
v
Dominika Luptáková1, Tereza Hřivnová Juříková 1, Miloš Petřík2, Andrea Palyzová1, Vladimír Havlíček1
2024
74
n/a
-
v
Amer Ali Abd El-Hafeez1, Gabriele Sass2, David A. Stevens2,3, Vladimír Havlíček4,5, Ioly Kotta-Loizou6,7, Joe Hsu1
2024
73
n/a