Discrimination of three genetically close Aspergillus species by using high resolution melting analysis applied to indoor air as case study

Abstract

BackgroundIndoor 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.MethodsIn this study, we developed and evaluated an HRM assay for the discrimination between A. versicolor, Aspergillus creber and Aspergillus sydowii.ResultsUsing 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.ConclusionWe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-017-0996-4) contains supplementary material, which is available to authorized users.

Morphologic identification of clinically encountered moulds using a residual neural network

“…In addition, Aspergillus lentulus was not distinguished from Aspergillus fumigatus but was identified at Aspergillus fumigatus complex by XMVision Fungus AI. Similar to previous studies (Libert et al, 2017), our results show that Aspergillus sydowii and Aspergillus versicolor were difficult to distinguish both morphologically and genetically. Due to the absence of database entries for Syncephalastrum racemosum and Penicillium oxalicum in the VITEK ® MS system, no identification results were obtained by MALDI-TOF MS for these species.…”

Development of high-resolution melting PCR (HRM-PCR) assay to identify native fungal species associated with the wheat endosphere

“…Thus far, several studies have employed the HRM technique to develop a molecular approach for the identification and discrimination of clinically relevant fungal species (Hrncirova et al 2010;Decat et al 2013;Didehdar et al 2016;Lu et al 2017), for monitoring the composition of the indoor airborne fungal contaminants (Libert et al 2017), or for the identification of phytopathogenic fungi (Papavasileiou et al 2016). Currently, a number of studies are focusing on exploring the wheat mycobiome (Comby et al 2016;Gdanetz and Trail 2017) and acquiring fungal endophytes that might be beneficial to the host plant (Gdanetz and Trail 2017).…”

Rapid and accurate identification of black aspergilli from grapes using high‐resolution melting (HRM) analysis

“…A. fumigatus, A. lentulus) and Versicolores (i.e. A. sydowii, A. versicolor, A. creber), as well as A. flavus, A. niger and A. tubingensis, among others, [36][37][38][39] or discriminate among A. fumigatus fungicide-resistant mutants. 40 These reports clearly depict the usefulness and applicability of HRM to identification of Aspergillus spp.…”