"Knowing the degree to which certain plants are being foraged upon allows us to infer things like the potential for pesticide exposure in a given landscape, the preference of certain plant species over others, and the degree to which certain plant species contribute to the honey bee diet", stated graduate student Rodney Richardson. "One of the major interests of our lab is researching honey bee foraging preferences so we can enhance landscapes to sustain robust honey bee populations."
For Richardson and his colleagues, meta-barcoding is key to this research. It is a DNA analysis method that enables researchers to identify biological specimens.
Meta-barcoding works by comparing short genetic sequence "markers" from unidentified biological specimens to libraries of known reference sequences. It can be used to detect biological contaminants in food and water, characterize animal diets from dung samples, and even test air samples for bacteria and fungal spores. In the case of pollen, it could save researchers countless hours of identifying and counting individual pollen grains under a microscope.
Rodney Richardson and his colleagues devised the new meta-barcoding method using three specific locations in the genome, or loci, as markers. They found that using multiple loci simultaneously produced the best meta-barcoding results for pollen. The entire procedure, including DNA extraction, sequencing, and marker analysis, is described in the November issue ofApplications in Plant Sciences.
To develop the new method, the researchers needed a machine powerful enough to process millions of DNA sequences. For this work, the team turned to the Ohio Supercomputer Center.
"As a researcher, you feel like a kid in a candy store", Rodney Richardson stated. "You can analyze huge datasets in an instant and experiment with the fast-evolving world of open source bioinformatics software as well as the vast amount of publicly available data from previous studies."
In previous meta-barcoding experiments, the researchers worked solely with a marker found in the nuclear genome called ITS2. ITS2 successfully identified plant species present in pollen samples, but it could not produce quantitative measurements of the proportions of each.
While searching for something better, they decided to test two markers from the plastid genome. Pollen was previously thought to rarely contain plastids, but recent studies showed promise for plastid-based barcoding of pollen. Rodney Richardson and his colleagues found that the combined data from the two plastid markers, rbcL and matK, successfully correlated with microscopic measurements of pollen abundance.
The new multi-locus meta-barcoding method involves all three markers and could serve as a valuable tool for research on the native bee species that comprise local bee communities.
"With a tool like this, we could more easily assess what plants various bee species are relying on, helping to boost their populations as well as the economic and ecological services they provide to our agricultural and natural landscapes". Rodney Richardson stated. "While the honey bee is seen as our most economically important pollinator, it's only one of several hundred bee species in Ohio, the vast majority of which are greatly understudied in terms of their foraging ecology."
Rodney T. Richardson, Chia-Hua Lin, Juan O. Quijia, Natalia S. Riusech, Karen Goodell, and Reed M. Johnson are the authors of "Rank-based characterization of pollen assemblages collected by honey bees using a multi-locus metabarcoding approach". The paper appears inApplications in Plant Sciences3(11): 1500043 - doi:10.3732/apps.1500043.