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ISMB 2022: MEGARes and the Resistome of Honey Bees

I had the great privilege of attending the Intelligent Systems for Molecular Biology conference in Madison, July 10–14. Here, I’m sharing about something interesting I learned there!

While bioinformatics can often seem esoteric or academic (and I certainly enjoy those parts of it!), it also has widespread practical applicability. This research on apiculture, along with the open-source resources that it highlights, shows some of that applicability in a field most people don’t think of often but has far-reaching potential implications.

Photo of a honey bee pollinating a green plant
Photo by Justus Menke on Unsplash

A short glance at Wikipedia provides a list of crop plants that rely on bees for pollination – some such as all melon and squash varieties that are absolutely dependent on bees for the production of fruit. and others such as apples, almonds, and avocados that utilize bees for the majority of their pollination. But bees, like any other species, are subject to pathogenic disease – and those pathogens, just like human pathogens, can develop resistance to the drugs that target them. An antibiotic resistant pathogen spreading among honey bee hives is not quite the specter of horror that an antibiotic resistant pathogen spreading among the human community would be, at least for us humans, but the dependence of so much of our agriculture on bee health means that it could have significant and devastating consequences on produce availability and affordability.

In 2020, Enrique Doster and a number of other scientists published an improved version of an antimicrobial resistance database, MEGARes 2.0, along with a pipeline for interfacing with that database to identify and quantify different antimicrobial resistance genes called AMR++ (AMR is a shorthand for antimicrobial resistance). To increase the quality of the output, this is a hand-curated database that includes genes providing resistance against metals and biocides as well as standard antibiotics, and includes 7,868 genes in total.

Photo of a bee on a honeycomb
Photo by Wolfgang Hasselmann on Unsplash

In the research presented at ISMB 2022, scientists from Agriculture Canada applied these resources to the problem of spreading antimicrobial resistance in honey bee pathogens. Instead of isolating the pathogen from infected bees, culturing it, and sequencing it to determine the exact AMR genes it contained from any given hive, they were able to skip straight to sequencing and analyze the full microbial population of a honey bee at once using short-read shotgun metagenomics. Since microbes can transfer AMR genes to each other (even outside species boundaries), and bees can spread microbes to each other through touch and close contact, it is useful to know the whole spectrum of AMR genes represented in a hive! For infected hives, this can direct treatment; for healthy hives, it can help beekeepers to track the spread of different specific antimicrobial resistance types and be prepared with an effective treatment if serious infection does occur in the future. The relative affordability and increased scope provided by shotgun metagenomic sequencing, along with the speed and accuracy provided by tools like MEGARes and AMR++, makes it more feasible for beekeepers or agricultural agencies to form an accurate picture of the spread of antimicrobial population through the honey bee population.

If you are interested in incorporating AMR data into your research, please let us know via our contact form! We are able to assist with experimental design, sequencing, and bioinformatic analysis using these resources and others.

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