"We're trying to figure out which flowers bees are utilizing for the collection of pollen", Rodney Richardson stated. "Honey bee forage is something we don't think about often. We don't always think about what's happening when they're out in the field providing pollination services, but they're not just doing it for free. They're collecting food for themselves, and luckily for us, that's often translated into increased agricultural productivity. We need good data, and lots of it, to decide how we can enhance forage for pollinators. It's going to be a complex issue, but I think this research can help us figure it out."
The research started with Reed Johnson, assistant professor for the Department of Entomology and Principal Investigator for the project, whose group was interested in finding out what types of insecticides bees were exposed to during the Midwest's corn planting season in the spring.
Reed Johnson's project was centered on bee exposure to a particular insecticide. That resulted in an interest in what bees were foraging on in late April and early May. To do that, pollen is collected from beehives, which helps identify foraging behaviours and preferences.
The difficulty comes when it's time to identify the pollen. Traditionally, pollen researchers use a microscopic approach, but that is a major challenge. This is where Chia-Hua Lin, postdoctoral researcher in Reed Johnson's lab and coauthor of the research, comes in. Chia-Hua Lin specializes in the microscopic identification of pollen and she analyzed pollen samples for the research to allow for comparison between the microscopic approach and the new method.
In 2013, Rodney Richardson, a new graduate student who had used OSC resources in a graduate bioinformatics class, worked with Reed Johnson to see what a supercomputer could do in conjunction with DNA sequencing. Using a metabarcoding technique, the research team was able to identify the plants present in samples collected from Ohio State University honey bee colonies.
"It takes incredible experience to confidently identify pollen under a microscope", Reed Johnson stated. "An effective sequencing approach would be a major advance, allowing researchers to compare their data to reference sequences of known taxonomic origin with the help of bioinformatics and a supercomputer. It's much more approachable for your average researcher that hasn't been doing microscopic identification for years."
The key for this new method is the powerful high-performance computing environment offered by the OSC. Considering the huge amounts of sequence data produced by the metabarcoding method, computationally expensive analytical approaches are required.
"Having the OSC is an incredible resource", Rodney Richardson stated. "It enables us to get things done more quickly and efficiently. Things run so much faster, it gives you a lot more flexibility to experiment with the analytical approach than if you were just trying to do this on a personal computer. For perspective, an analysis might take you a few days on your own personal computer and if you want to analyze it in 10 different ways, you're going to be waiting a while."
The metabarcoding has helped the research team work toward quantitatively figuring out what plants the bees are foraging on. In the past, the method wasn't quantitatively reliable and the researchers couldn't tell the proportions of the different types of pollen the bees were collecting. Now they're getting closer to reliably measuring how much of the pollen comes from, say, a dandelion or a maple tree or Hawthorns.
This will be especially helpful as Johnsons group begins to look at pollination throughout the year.
"We're getting closer to saying which plants are more important than others during specific times of the year", Reed Johnson stated. "This research is the foundation for a tool that people can use to figure out which plants are truly beneficial to honey bees and other pollinators. This will allow people in many different places with many different bees and pollinators to figure out what plants are most valuable for these highly beneficial insects."