In today’s ecological research, the need for accurate and non-invasive methods to monitor biodiversity has never been greater. Environmental DNA (eDNA) metabarcoding has emerged as a ground-breaking tool in this field, allowing scientists to detect a wide range of organisms from tiny fragments of genetic material left behind in the environment. While this technique has been predominantly used in aquatic settings, recent advancements have expanded its application to terrestrial environments, including soil, animal droppings, and now, plant surfaces.
A ground-breaking study by South African researchers sheds light on the untapped potential of grass inflorescences—the flowering parts of grasses—as rich sources of eDNA. By analysing genetic material collected from grass flowers, researchers can gain valuable insights into the diversity of species interacting within grassland ecosystems, particularly focusing on invertebrates and fungi.
Grass Inflorescence: A Novel Source for eDNA Collection
Grasslands are vital ecosystems covering approximately 40% of the Earth’s land surface. They provide essential services such as grazing lands for livestock, carbon storage, and water regulation. Despite their significance, grasslands often receive less conservation attention compared to forests or wetlands. In South Africa, for instance, grasslands are rich in native plant species but face threats from urbanisation, agriculture, and invasive species.
Using grass inflorescences for eDNA collection offers a new avenue for monitoring biodiversity within these ecosystems. By examining organisms that come into contact with grass flowers, scientists can create a snapshot of local biodiversity without disturbing the environment. This method holds promise for enhancing our understanding of grassland ecosystems and informing conservation strategies.
Methodology: From Field Collection to DNA Sequencing
The study was conducted in an urban grassland area on the campus of the University of the Free State in Bloemfontein, South Africa. This region is part of the Dry Highveld Grassland Bioregion, known for its rich diversity of grass species. The researchers selected four common grass species for their investigation: Cymbopogon caesius (Kachi grass), Themeda triandra (Kangaroo grass), Panicum coloratum (Kleingrass), and Sporobolus fimbriatus (Perennial Dropseed).
Inflorescences from these grasses were collected from four different sites within a 13,000 square meter area. To ensure the integrity of the samples, strict sterilisation protocols were followed. Sterile gloves were worn during each collection, and tools like forceps and scissors were sterilised with hypochlorite and ethanol between samples. Small sections of the grass flowers were carefully cut and placed into separate sterile tubes to avoid cross-contamination.
Once collected, the samples were kept cool in the field and then stored at -20°C until DNA extraction. In the laboratory, DNA was extracted and amplified using polymerase chain reaction (PCR) techniques targeting specific genetic markers. High-throughput DNA sequencing was then performed to identify the various organisms present in the samples.
The raw sequencing data underwent rigorous processing using specialised software like QIIME2. This involved steps such as removing low-quality reads, filtering out errors, and assigning taxonomic identities to the DNA sequences using reference databases. The final curated datasets were analysed to determine the diversity and abundance of species detected.
Key Findings: A Window into Biodiversity
The analysis of eDNA collected from grass inflorescences revealed a diverse array of both invertebrate and fungal species, highlighting the effectiveness of this method for biodiversity monitoring in grassland ecosystems.
Invertebrate Diversity
Several DNA sequences were identified as belonging to arthropods—a group that includes insects and mites. Specifically, DNA from the orders Coleoptera (beetles), Diptera (flies), Thysanoptera (thrips), and Trombidiformes (mites) was detected.
One of the most commonly found arthropods was from the family Eriophyidae, which includes tiny mites often associated with plants. These mites were present in all samples, indicating a widespread interaction with the grass species studied. Thrips from the genus Haplothrips were also frequently detected across all grass types. Beetle and fly DNA were found but were less common, appearing in samples from specific grass species.
Fungal Diversity
A significant portion of the DNA sequences corresponded to fungi, mainly from the phyla Ascomycota and Basidiomycota. These groups include a wide variety of fungi, from moulds to mushrooms. Commonly detected fungi included species from the genera Penicillium (known for producing the antibiotic penicillin) and Pleurotus (a type of edible mushroom). The presence of these fungi suggests they are either interacting directly with the grass inflorescences or are prevalent in the surrounding environment.
Challenges and Considerations
While the study demonstrated the potential of using grass inflorescences for eDNA collection, several biases and challenges were identified.
First, due to the tiny size of some invertebrates like mites and thrips, they were difficult to remove entirely during sample preparation. Their accidental inclusion could lead to an overrepresentation of their DNA in the results.
Second, the primers used in PCR to amplify DNA can sometimes favour certain groups of organisms over others. In this study, the primers designed to amplify a wide range of species ended up amplifying fungal DNA more efficiently, leading to a higher proportion of fungal sequences in the data.
Third, without negative controls (samples to detect contamination), it is challenging to determine whether some of the detected DNA came from the immediate environment, such as airborne spores, rather than direct interaction with the grass inflorescences.
Implications for Conservation and Future Research
Despite these challenges, the study opens up exciting possibilities for biodiversity monitoring. Using grass inflorescences for eDNA collection is minimally invasive and does not require capturing or observing organisms directly, reducing stress on wildlife. High-throughput DNA sequencing allows for the simultaneous detection of multiple species from a single sample, saving time and resources. Improved monitoring techniques can inform conservation strategies by providing up-to-date information on species presence and ecosystem health.
To enhance the accuracy and reliability of this method, future studies should consider increasing sample sizes to provide a more comprehensive picture of biodiversity and help account for variability. Refining DNA extraction methods by employing multiple extraction replicates can improve the chances of detecting less abundant species. Developing better primers that reduce bias and amplify a broader range of species will improve detection rates. Building local reference databases by enhancing them with DNA sequences from local species will improve the accuracy of taxonomic assignments, especially in regions where species are underrepresented in global databases.
Conclusion
The utilisation of grass inflorescences as a source for eDNA metabarcoding represents a promising advancement in ecological research. Harnessing the power of eDNA from grass inflorescences not only broadens our toolkit for biodiversity monitoring but also underscores the importance of grasslands in global ecology. This approach could revolutionise how we study and conserve these vital ecosystems, ensuring they continue to thrive amidst growing environmental challenges.
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