Community and diversity

Published: 11 October 2010 -

Analysis of microbial communities in a multitude of substrates and ecosystems is a central component in a wide range of research projects in the department.

Cortinarius armillatus growing in a forest outside Uppsala, Sweden. Photo: Cajsa Lithell.

Our competence encompasses fungal and bacterial communities in forest, arctic and agricultural soils, wood, litter and harvest residues, as well as symbiotic and parasitic microorganisms associated with living plants and insects.

Our research may be broadly categorized into five areas:

  1. Diversity of forest soil fungi in relation to global change, soil fertility and forestry practices
  2. Functional properties of fungal communities in relation to carbon / nutrient circulation and weathering in boreal and alpine ecosystems
  3. Diversity and dynamics of fungal communities in needles and wood
  4. Microbial communities associated with agricultural crops and their roles in plant nutrient acquisition and health
  5. Development of laboratory and bioinformatic high-throughput methods to analyse microbial communities

Methodological history and the Uppsala Mycology Group

Method development in molecular ecology is currently going through a boom, and the Uppsala Mycology group has been a driving force behind the application of molecular tools in fungal ecology. The department entered the field in 1997, using restriction patterns to identify mycorrhizal fungi colonising root tips. Sequencing of amplified marker genes made identification of mycorrhizal root tips easier, and called for high-quality data bases of reference sequences (UNITE).

With new techniques, such as DGGE , T-RFLP and sequencing of clone libraries, it became possible to study entire communities of microorganisms and identify community members. The most recent methodological advancement is the introduction of high throughput sequencing (454-pyrosequencing), which enable more detailed and semi-quantitative analyses of microbial communities in large numbers of samples. The millions of sequences provided by the new techniques require automated structuring before biological interpretation is possible.

We have developed our own bioinformatic pipe-line to group and identify amplicon sequences from complex microbial communities (SCATA), and collaborate to develop a further refined reference database (Nordforsk).

Page editor: