Analysis of Aspergillus spp. burden by culture based-methods and molecular methods in different occupational environments: what needs to be done?

AQ Gomes1,2, T Faria1, L Aranha1,3, R Sabino1,4, C Viegas1,5

Author address: 

1Environment and Health Research Group , Escola Superior de Tecnologia da Saude de Lisboa, ESTeSL, Instituto Politenico de Lisboa, Lisbon, Portugal 2T cell Differentiation and Tumor Targeting lab, Instituto de Medicina Molecular, Faculdade de Medicina de Lisboa, Lisbon, Portugal 3Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, University of Lisbon, Lisbon, Portugal 4Mycology Laboratory, National Health Institute Doutor Ricardo Jorge, Lisbon, Portugal 5Centro de Investigacao em Saude Publica, Escola Nacional de Saude Publica, Universidade Nova de Lisboa, Lisbon, Portugal

Abstract: 

Purpose: Fungal burden has traditionally been detected by conventional culture analysis. This method allows the identification and quantification of organisms posing high health/occupational risk and is widely used by the scientific community. However, this method is limited by several factors, including, for example, incubation conditions such as the incubation time, which can be very long for some species, thus preventing a quick assessment of fungal burden. These limitations can be overcome by the use of quantitative real-time PCR (qPCR). This method, based on the amplification of genomic regions specific to certain fungal species, increases sensitivity, allowing the specific detection of a given species and removing interference by other species present in the sample. qPCR also allows the detection of dormant forms of fungi, such as spores.

We present several studies where both methods were used to detect the presence of toxigenic fungi, namely Aspergillus, particularly from the Fumigati, Flavi and Circumdati sections.

Methods: Several matricies, such as air and surface were either subject to culture analysis or molecular biology detection. For culture analysis, extracted material was streaked onto MEA and DG18. After incubation at 27 ºC for 5 to 7 days, Aspergillus spp. densities (colony-forming units, CFU/m2 of filter) were calculated, and Aspergillus sections were identified microscopically and morphological identification was achieved through macro and microscopic characteristics. The molecular detection of the Aspergillus sections Circumdati, Fumigati and Flavi (only the toxigenic strains) was performed by Real Time PCR (RT-PCR).

Results: Air samples were isolated from different settings, including two wastewater plants, 1 wastewater elevation plant, 4 waste treatment plants, 3 cork industries, 5 slaughter houses, 4 feed industries, 1 poultry pavilion and 2 swine pavilions. 125 air samples were subject to conventional analysis, while 100 air samples were analysed by real-time PCR detection of Aspergillus sections Circumdati, Flavi and Fumigati.

All settings presented sampling sites where detection of specific species/strains was possible but in some cases could not be identified by conventional methods. qPCR analysis successfully amplified DNA from the Aspergillus section Fumigati in 18 sampling sites where culture base-methods could not identify this species.

Conclusion: Upon comparing conventional and molecular analysis of Aspergillus spp detection, we came to the conclusion that the ideal scenario is to use these two methods in parallel, as they complement each other to provide useful information for the assessment of exposure to Apsergillus spp. An added value of molecular analysis is to quantify rather than just detect the presence of specific Aspergillus species. This can be achieved by performing calibration curves, which are currently under development. Furthermore, the establishment of these standard curves will ultimately allow the correlation between copy number (obtained by qPCR) and CFU/m3, the reference measure used by international legislation

2018

abstract No: 

162

Full conference title: 

The 8th Advances Against Aspergillus, Lisbon Conference Center, Lisbon, Portugal
    • AAA 8th (2018)