• Subscribe

At Science Node, we need your help. Science Node is serving more people than ever before. Because of the economics of support for scientific research organizations, our sponsorship dollars are running behind our expenditure rate. We'd like to raise $20k from readers to balance the books for the first 6 months of the year. Donate now to Science Node through the IU Foundation.

What's in a honey bee's diet?

Speed read
  • Supercomputers plus DNA sequencing reveal contents of bee diets.
  • Metabarcoding technique quickly isolates individual pollen grains.
  • Supercomputers at the Ohio Supercomputing Center called on to process millions of DNA sequences. 

One of the best parts of our work here at Science Node is that there’s never a shortage of cool tech stories to write about. But with so much science to follow, some of the best ideas get lost in the shuffle. To fix that, we’re bringing you some of our favorite stories, in case you missed them the first time.

<strong>What's for dinner?</strong> Since pollination requires a healthy bee population, it's important to know what bees are eating and if they are consuming contaminants. Researchers at The Ohio State University took samples of pollen and millions of DNA sequences to the Ohio Supercomputing Center, and what they've learned can enhance the ecosystem to help sustain this important partner of civilization.To uncover what plants honey bees rely on, researchers from The Ohio State University are using the latest DNA sequencing technology and a supercomputer. They spent months collecting pollen from beehives and have developed a multi-locus metabarcoding approach to identify which plants, and what proportions of each, are present in pollen samples.

A single colony can collect pollen from dozens of different plant species, and this pollen is useful evidence of the colony’s foraging behavior and nutrition preferences.

“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,” says 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, metabarcoding is key to this research. It is a DNA analysis method that enables researchers to identify biological specimens.

Metabarcoding 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.

Richardson and his colleagues devised the new metabarcoding method using three specific locations in the genome, or loci, as markers. They found that using multiple loci simultaneously produced the best metabarcoding results for pollen. The entire procedure, including DNA extraction, sequencing, and marker analysis, is described in the November issue of Applications in Plant Sciences

Courtesy Chris Fort; Flickr.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,” Richardson says. “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 metabarcoding experiments, the researchers worked solely with a marker found in the nuclear genome called ITS2, which, while successfully identifying plant species present in pollen samples, 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. 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.

“As a researcher, you feel like a kid in a candy store,” Richardson says. “You can analyze huge datasets in an instant."

The new multi-locus metabarcoding 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.” Richardson says, “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.”


Reprinted from Applications in Plant Sciences (APPS) a monthly, peer-reviewed, open access journal published by the Botanical Society of America. APPS is available as part of BioOne’s Open Access collectionFor further information, please contact the APPS staff at apps@botany.org.

Join the conversation

Do you have story ideas or something to contribute? Let us know!

Copyright © 2018 Science Node ™  |  Privacy Notice  |  Sitemap

Disclaimer: While Science Node ™ does its best to provide complete and up-to-date information, it does not warrant that the information is error-free and disclaims all liability with respect to results from the use of the information.

Republish

We encourage you to republish this article online and in print, it’s free under our creative commons attribution license, but please follow some simple guidelines:
  1. You have to credit our authors.
  2. You have to credit ScienceNode.org — where possible include our logo with a link back to the original article.
  3. You can simply run the first few lines of the article and then add: “Read the full article on ScienceNode.org” containing a link back to the original article.
  4. The easiest way to get the article on your site is to embed the code below.