Applied DNA metabarcoding: Towards a streamlined approach for DNA-based profiling of indoor mycobiomes (completed)

The overarching aims of the IndoorMyco project are to improve the knowledge about the indoor mycobiome and its impact on human health by using HTS analyses and investigate the potential for commercial applications.

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About the project

Objectives

The overarching aims of the IndoorMyco project are to improve the knowledge about the indoor mycobiome by implementing state-of-the-art HTS analyses and investigate the potential for commercial applications. We want to reach the following sub-goals which are coupled to five work packages:

  1. Construct a reference DNA sequence database for widespread cultivable indoor fungi, fined-tuned to North-European conditions.

  2. Evaluate and implement the use of internal mock community standards in metabarcoding analyses for better quantitative assessment of the mycobiome.

  3. Analyse the spatiotemporal variation in the indoor mycobiome within single buildings and on broader geographic scales and identify the main determinants of the indoor mycobiome.

  4. Improve and adapt existing bioinformatics and computational tools relevant for DNA metabarcoding analyses of the indoor mycobiome.

  5. Assess how the characterization of the mycobiome can be streamlined, for commercial purposes.

Outcomes

The obtained results from IndoorMyco have a clear potential for commercialization. Customers of Mycoteam AS already asks for DNA-based methods for profiling indoor fungi. In addition to private customers, HTS-based mycobiome analyses might be required by various public institutions (e.g. kindergartens, schools and hospitals).

Background

Most fungi reside in natural habitats, but some species have expanded their habitat into buildings. Wherever excess moisture is available, fungi and other microorganisms start to grow. Many fungi with mainly asexual forms, fast filamentous growth and high spore production, (“molds”) appear. Mold growth in buildings acts as a source of indoor pollutants, such as spores, cells, fragments of hyphae, microbial volatile organic compounds and mycotoxins. Dampness- and mold-related indoor air quality problems are associated with adverse health effects, such as allergies, asthma and other respiratory symptoms (Bornehag et al. 2001). Nevertheless, the causative agents and mechanisms of such health effects are insufficiently understood. Decay fungi, causing damages to wood constructions and building materials, is another concern (Kauserud et al. 2012).

Microbiological indoor assessments are mainly focused on air and dust samples, as well as building materials if contamination is suspected. The fungal content of samples can be analyzed using different approaches, such as microscopy, culturing, chemical and molecular analyses. In recent years a shift toward DNA-based methods has taken place. Real-time quantitative PCR (qPCR) has been widely used to detect and quantify indoor fungi, but this approach only monitors fungi that you a priori suspect are present and does not provide new knowledge about other taxa. High throughput sequencing (HTS) of amplified markers (DNA metabarcoding) has lately become a key tool for surveying fungal communities (Lindahl et al. 2013). Major obstacles during HTS-based analyses are the computational and bioinformatics analyses, where the massive amount of DNA sequences needs to be processed (Mahé et al. 2015). In other parts of the world there are initiatives to understand the indoor fungal diversity using HTS analyses (Barberan et al. 2015). However, so far there have not been any studies in Europe and Scandinavia implementing HTS, despite that indoor fungal communities present in different geographic regions can show significant differences.

Cooperation

Mycoteam AS

Digital Life Norway

 

Tools

High throughput sequencing, DNA metabarcoding

Tags: sopp, fungi, indoor fungi, hussopp, DNA sequencing
Published Feb. 6, 2017 11:10 AM - Last modified Feb. 22, 2023 10:28 AM

Contact

Leader:

Håvard Kauserud

 

Eva Lena F. Estensmo

Participants

  • Håvard Kauserud Universitetet i Oslo
  • Eva Lena Fjeld Estensmo Universitetet i Oslo
  • Pedro Maria Martin-Sanchez Universitetet i Oslo
  • Inger Skrede Universitetet i Oslo
  • Torbjørn Rognes Universitetet i Oslo
  • Ingeborg Bjorvand Engh
  • Maria Nunez
  • Johan Mattsson
  • Kolbjørn Mohn Jenssen
  • Urmas Köljalg
  • Kessy Abarenkov
  • Henrik Nilsson
Detailed list of participants