Contract number
Z7-2668
Department:
Department of Biology
Type of project
ARIS projects
Type of project
Postdoctoral projects
Role
Lead
Financing
Duration
01.09.2020 - 31.08.2022
Total
1 FTE
Project manager at BF
Novak Babič MonikaABSTRACT
The United Nations (UN) and the Human Rights Council in the Resolution 64/292 identified drinking water as one of the fundamental human rights. Water originates from geologically determined surface or underground sources. Its quality is influenced by natural and anthropogenic factors, such as sunlight, temperature and water flow, content of inorganic ions, organic material and pollutants. The European Union (EU) in the Drinking Water Directive 98/83/CE states: water is suitable for drinking when it does not contain dangerous chemical substances and microorganisms. Due to the increasing urbanization and pollution natural waters need to be cleaned and disinfected before drinking. The most commonly used disinfectants are chlorines, providing also a residual effect. Before the distribution a regular microbiological monitoring of drinking water is carried out covering the total number of aerobic microorganisms at 22 and 37°C, the presence of faecal coliforms, Escherichia coli, parasites and the number of Clostridium perfringens if the primary water source was a surface water. One of the microbiological parameters affecting the quality of water and human health, but not included in the regular monitoring of drinking water, are fungi. Spores, and thick cell walls enable fungi to survive physico-chemical disinfection, later entering the distribution system and forming biofilms. Their presence in different waters has been confirmed in 19 European countries, with more than 400 species reported. Most common were fungi of the genera Absidia, Alternaria, Aspergillus, Aureobasidium, Candida, Cladosporium, Cystobasidium, Exophiala, Fusarium, Mortierella, Mucor, Naganishia, Penicillium, Phoma, Rhinocladiella, Rhizopus, Rhodotorula, Sarocladium, Scopulariopsis, Sporothrix, Stachybotrys and Trichoderma. They contribute to acidification, corrosion of cementous and metal materials, and leaching of elements in distribution systems. Fungi are also often involved in the limescale deposition on the surface of materials. Consequently, the quality of the materials, as well as the colour, smell and taste of water change. Also, fungal particles and spores are present in drinking water and transmitted to users.
|
In Slovenia, the most commonly isolated fungi from groundwater and drinking water belonged to the genera Aspergillus, Aureobasidium, Candida and Exophiala, of which species of Aspergillus and Candida are also the most common causes of fungal diseases in Slovenians. Although the resistance to azoles in fungi isolated from water in Slovenia has not been proven, this possibility exists particularly in lowland areas, due to the increased agricultural activities. In the project, we propose research on the so far overlooked presence of fungi in natural and disinfected water, detection of the presence of fungi in biofilms on materials in contact with drinking water, and the determination of azole resistance for species of the genera Aspergillus and Candida. We will use conventional cultivation methods and molecular-genetic approach such as PCR and Next Generation Sequencing. Finally, the obtained data will be evaluated with machine learning based model prediction.
THE PHASES OF THE PROJECT AND THEIR REALIZATION
Year 1: Sampling of water and biofilms on the surfaces of materials in contact with drinking water, physico-chemical analyses of water, isolation of pure fungal cultures from the obtained samples of water and biofilms, DNA isolation from pure cultures, characterization and identification of fungi, storage in the microbiological collection Ex, preparation of samples for the Next Generation Sequencing and metagenomic studies, project management.
Year 2: Deposition of single strains’ sequences into an international GenBank database (NCBI), analysing NGS results, testing resistance to azoles, analysing results using the Machine Learning Method, publishing and dissemination of results.
|