PeerJ talks to Professor Mya Breitbart from the University of South Florida about her latest research article “Evaluation of DNA metabarcoding for identifying fish eggs: a case study on the West Florida Shelf“, published in PeerJ Life & Environment as part of the IABO Hub. The IABO Hub is the publishing home of the International Association for Biological Oceanography, and features the latest biological oceanography research published by the members of IABO.
Can you tell us a bit about yourself and your general research interests?
My research primarily focuses on microbial ecology – our lab uses molecular biology techniques to explore the diversity, distribution, and ecological impacts of viruses and bacteria in a variety of different environments. About 10 years ago, we began collaborating with fisheries ecologists and learned that fish eggs are almost impossible to identify based on visual features alone – this represents a significant limitation to identifying spawning sites for different fish species. This presented a great opportunity to apply molecular biological methods (namely, DNA barcoding) to identify fish eggs and this technique has identified novel spawning sites for ecologically and economically important fish species.
Can you give us a brief overview of your article “Evaluation of DNA metabarcoding for identifying fish eggs: a case study on the West Florida Shelf”?
Over the past decade, we have used DNA barcoding to identify thousands of individual fish eggs from hundreds of locations in the Gulf of Mexico and Florida Straits, with the goal of identifying spawning sites for ecologically and economically important species. However, DNA barcoding of individual fish eggs is expensive and time-consuming, limiting the number of samples that can be processed. This research explored the potential of DNA metabarcoding, in which DNA is extracted and amplified from a composited sample containing all the fish eggs collected at a given site, to increase throughput and support a lower cost long-term fish egg monitoring program at high spatial resolution. We successfully identified 37 taxa from almost 5,000 surveyed fish eggs and found that the egg distributions on the West Florida Shelf corresponded with known habitat types occupied by these taxa. However, we noted some downsides to the metabarcoding technique. Compared to barcoding individual fish eggs, metabarcoding is not quantitative (i.e., it cannot tell us what proportion of eggs belonged to a given species). In addition, some samples yielded sequences from more taxa than the number of eggs present, demonstrating the presence of contaminating DNA and requiring the application of a minimum threshold for counting a taxon as present.
Why is it important to establish long-term fish egg monitoring?
A critical factor in fisheries management is protecting spawning sites and habitats used by fishes during their early life stages. Research often predicts spawning sites based on the locations where larvae from a given species have been identified, but this method is imprecise because larvae can be days, weeks, or even months old at the time of capture. In contrast, predicting spawning sites based on the presence of eggs is much more reliable since most fish only remain in this developmental stage for a maximum of 2 days and eggs behave as relatively passive particles. Therefore, identifying fish egg composition over long time scales and at high spatial resolution is extremely valuable for observing changes in spawning dynamics of different fishes and deciphering how human activities (ranging from acute events like oil spills to long-term impacts like climate change) affect fish spawning.
Can you explain the process of metabarcoding and why it is a useful technique?
DNA barcoding involves amplification and sequencing of a conserved gene that is present in all animals. This unique “barcode” serves as a fingerprint, allowing identification of the organism (or in our case, fish egg) upon comparison to a database. This technique has been widely applied to identify individual fish eggs. Fish eggs are collected by towing a plankton net which collects free-floating eggs, since the majority of fish release their eggs into the water column. We then look through all the plankton under a microscope and gently pick out each individual fish egg with tweezers. Each egg is smashed with a toothpick to release the DNA and the barcoding gene is amplified and sequenced. This process is extremely time consuming and quite expensive (~$5 per egg and $500 to sequence 96 eggs/site). In metabarcoding, all the fish eggs are picked from an individual sample and then they are processed together as a composite. This method is significantly cheaper (~$0.78 per egg and $65 to sequence 96 eggs/site) and would allow us to process many more samples to build a long-term time series with high spatial resolution.
What was your most interesting finding from this research?
It is always interesting to see where we detect eggs from different fish species. In this paper, we recovered eggs from three fish species we hadn’t previously documented spawning for in this area: Atlantic blue marlin, crested scabbardfish, and burrfish. However, I think the most interesting (and frustrating) finding from this research was that sometimes we recovered more species from a given sample than the number of eggs in that sample, which indicates contaminating DNA. The source of this DNA is most likely “environmental DNA” which is shed by all living species and can get stuck to the outside of the fish eggs. We had to apply a threshold (i.e., a cut-off for the proportion of sequences belonging to a particular species) to consider that species as present – and this likely introduces biases by excluding rare species.
How could you see your research being implemented?
We concluded that DNA metabarcoding was not advantageous for our long-term study’s goals, in which we need to be quantitative, confident that the DNA is originating from a fish egg, and obtain data with high spatial resolution. However, we can see many potential applications of DNA metabacoding for fish egg identification – for example, if the location of each egg wasn’t critical, researchers could combine all the eggs collected in a geographic region (e.g., the West Florida Shelf) in a given season and use metabarcoding to generate an overview of fish spawning at that time, which can then be compared to other seasons.
What are your next steps for this research?
We plan to continue monitoring fish egg community composition on the West Florida Shelf over time to determine if changes in spawning locations are occurring. In addition, we plan to collect fish eggs in different seasons to determine peak spawning timing for different species and monitor any changes. We also plan to compare spawning communities between different bottom habitat types and look for correlations between spawning patterns and various environmental parameters.
Your article is the first to be submitted and published by the IABO Hub, what are your thoughts on the Hub concept?
As a member of the PeerJ editorial board, I am excited to see how the Hubs develop and progress over time. One of the strengths of PeerJ is the broad range of topics covered; however, it can sometimes be overwhelming to find relevant work. I’m eager to explore the research published by the IABO Hub.
Were you already an IABO member before learning about the Hub?
No, I wasn’t actually aware of IABO prior to learning about the Hub, but I’m excited to be a member now!
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