Using eDNA to identify invisible underground fungi

Identifying mycorrhizal fungi in soil

Most mycorrhizal fungi live their entire lives underground – many of them don’t even make mushrooms, the fruiting bodies of fungi that pop up above the soil level. The hidden nature of these organisms can make studying them particularly challenging. For organisms like plants and animals, scientists can gather observational data, counting and recording or tagging study subjects. When it comes to belowground fungi and microbes, these surveys become more complicated.

Identifying invisible mycorrhizal fungi from soils is challenging because molecular techniques are needed to distinguish one species from another. The only way to know definitively what species are present is to sequence their DNA.

Using eDNA to identify fungi

To determine which fungi live where, we use environmental DNA (eDNA) collected from the soil. eDNA has a slightly different meaning than just DNA alone – DNA is the term for the molecule itself, and eDNA refers to the DNA molecules gathered from the environment, such as those found in air, soil, or water. eDNA is an incredible tool because it yields information about all the organisms which are present, or have been present in that environment in the recent past. 

Environmental DNA extraction

Once we have identified a key location  for soil collection (see how we chose locations here), we take a grid of nine soil cores and then combine them to make sure we get a representative sample. It’s important that we record the exact GPS location and make notes about what plants are present, the way the land is being used, and any other relevant environmental meta-data. Once these samples are collected we take them into the lab for DNA extraction.

DNA barcode: PCR identification of mycorrhizal species

The DNA extraction process purifies all DNA in the soil sample, resulting in DNA from many soil organisms such as worms, bacteria, and various types of fungi. Since we want to only study the mycorrhizal fungi in the sample, we use molecular biology and a process called the Polymerase Chain Reaction (PCR), to create huge numbers of only the mycorrhizal DNA molecules. The amplified mycorrhizal DNA is a short region called a “DNA barcode”, and each barcode is matched to a database of mycorrhizal DNA from known species, allowing us to identify which mycorrhizal species are present in our samples. 

eDNA sequencing in the field

We are testing new techniques that allow for eDNA sequencing in the field or in locations without comprehensive laboratory facilities, but they still require more R&D. These new devices comfortably fit in the palm of your hand, and can help us analyze eDNA in the field, rather than sending it out to a lab. These tools can make eDNA data collection much more accessible for field biologists.

Mycorrhizal Mapping and Metagenomics Workshop

To begin testing these techniques, we recently teamed up with two African-led organizations, JR Biotek and CSIR - Crops Research Institute to develop the Africa Mycorrhizal Mapping and Metagenomics Workshop, an event that we held in Ghana. We worked with a representative of Oxford Nanopore Technologies to train a group of 12 researchers from 9 African countries on the molecular biology, portable sequencing, and analysis of eDNA from soil.

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Many of Ghana’s traditional crops form relationships with arbuscular mycorrhizal fungi, so it’s really important that scientists there have an easy and efficient way to identify which species are present in different agricultural systems and associated with specific crops. At present, most biological samples, such as eDNA from soils, are sent to facilities in the Global North for DNA sequencing. This technology allows the data to stay in its country of origin from start to finish.

A central part of SPUN’s mission is to generate more data on mycorrhizal biodiversity from around the world, and map which species are in which places. Our goal is to create a global network of data gatherers. Building capacity for eDNA analysis in the field is one way to ensure that we continue to build out our global maps of mycorrhizal fungal data.