Sample Automation Goes Viral in Honeybee Disease Research

How University of Minnesota virologist Declan Schroeder is exploring the landscape of colony losses at scale using new automated sequencing tech

 

This story is part of our celebration of innovation in 2025.

 

by Dana D’Amico, Connect to Science

Sometimes, science is about arriving at the wrong place at the right time – starting at sea and stumbling upon an unexpected landmark that changes your course.

In the early 2000s, virologist Declan Schroeder was in his first post-doc sequencing the complex genomes of so-called “giant viruses” infecting marine phytoplankton populations. Vast plankton blooms, some of which are large enough to be seen from space, play a key role in global climate balance by acting as carbon sinks. Giant viruses are the hidden lever in this careful equilibrium between ocean and atmosphere.

In exploring the genomes of these marine algal viruses, however, Schroeder would inadvertently open a Pandora’s box “too exciting to close” – one that would take his career in a totally new direction.

Because at the molecular level, something looked strange.

“I found a lot of the areas in marine virus metagenomes collected from ocean sampling efforts were matching to areas in honeybee viruses,” said Schroeder “I thought, what’s going on here?’”

Scientist as explorer

Schroeder didn’t know anything about honeybees, except that beekeepers had begun to report a mysterious phenomenon decimating hives across the world. They called it “colony collapse disorder,” and no one knew what was causing it.

The unexpected virome homologues presented the kind of interdisciplinary question that fascinates a scientist like Schroeder. Many virologists will stick to one category like animal viruses, or to a specific virus, or even to a single viral gene or mutation for the entire lengths of their careers.

For others, that approach feels like being boxed in.

“I don’t like pigeonholing myself. I am a more exploratory type of scientist. I like viruses for viruses and understanding where they sit in the big scheme of things,” said Schroeder. “When you focus on the virus rather than the host, you start to see interesting new connections.”

Today, almost 20 years later, his lab at the University of Minnesota College of Veterinary Medicine is once again charting new paths in the field. The team is co-opting the automation technology of biotech and pharma for genomic exploration of bee viruses at scale.

Their work is helping both honeybee managers and native bee researchers understand the disease landscape threatening these beloved pollinators that hold our food systems together.

The honeybee vs. DWV

Honey production aside, commercial honeybees contribute approximately $15 billion annually to the US agricultural industry through pollination services. Migrating colonies pollinate a third of the American food supply, including crops like apples, berries, squashes, oranges, alfalfa, and many more. In the largest single pollination event on earth – a one-month annual spectacle that yields 80 percent of the world’s almond supply – a fleet of semi-trucks tote 130 billion honeybees across the country to California orchards.

In short, a lot relies on the honeybee.

In the winter of 2006, when entire colonies of worker bees started disappearing without a trace, it ignited a public panic. Colony collapse disorder (CCD) kickstarted an urgent global response and a new field of research and management to get it under control.

While the USDA has reported falling CCD rates in recent years, the issue is far from resolved. A 2023-24 US survey of more than 1,600 beekeepers revealed the highest reported colony loss rate in a decade at 55 percent. In Minnesota, where Schroeder’s lab is based, the average was closer to 75 percent. Colony managers consider an “acceptable” loss rate to be just 20 percent.

The exact cause of CCD as described in 2006 is still unknown, but researchers now believe current colony losses to be linked to multiple issues including pesticide exposure, habitat changes, and, critically, the invasive Varroa mite and its vectored pathogen deformed wing virus (DWV).

 

Assembling the viral tapestry

DWV causes physical and cognitive deformities like shriveled or stubby wings, bloated bodies, paralyzed legs, and memory loss. Altogether, the virus typically shortens a bee’s lifespan from 2-20 weeks, depending on season, to under 48 hours.

It is the also virus that first caught Schroeder’s eye for its genomic similarities to marine RNA viromes. Years of inquiry into that “Pandora’s box” has now culminated in a recently published, first-of-its-kind national survey of DWV variants in honeybees and varroa mites.

The survey unearthed genetic evidence of widespread and shapeshifting DWV in US commercial honeybees – its genome recombining into a diverse tapestry as the virus has passed between mites and bees and back again over years and states. To date, researchers have kept tabs on two main DWV variants, dubbed A and B. In fact, Schroeder’s evidence argues that the true DWV variant landscape is a lot more diverse.

“You can think about influenza. When influenza moves from a bird to a human, it usually swaps out one of its genomes – or its subgenomes – and that’s called reassortment. They recombine and actually exchange genetic material to create a new virus,” he said.

Why does it matter?

Keeping up with the “big picture” genetic landscape of a virus is vital for several reasons. Genomic surveillance ensures that diagnostic PCR tests, which rely on specific gene targets, remain accurate as viruses mutate and recombine.

As with human pathogens like SARS-CoV-2, surveillance of the entire DWV landscape also allows scientists to proactively test for significant emerging variants, population changes, spillover risk, and more.

And not all outbreaks of DWV are visible. Some variants initially result in covert infection, which presents with subtle or no symptoms.

“In disease investigations, we don’t always have a patient visiting a doctor or a field crop dying. We don’t always have a known pathology to test for. That’s why I say that I’m an explorer [of the genome],” said Schroeder.

 

Breaking away from the daily grind

An explorer needs the right tools to excavate. Assembling the right toolkit for a nationwide survey of the bee population was a long journey in itself.

The funding and infrastructure systems for ecological and agricultural research are often less centralized than in other fields like human medicine. These systems can be difficult to navigate.

“We’re just individual scientists grinding the old-fashioned way through all these different samples,” said Schroeder. “It’s really time-consuming.”

The grind is literal. Screening a honeybee colony is typically a manual process of pulverizing bee samples and running column-based extractions to isolate DNA or RNA, where each sample may take a week to process. To get the data you need to understand a whole population could take months.

“You need that scale of data to be confident that what we’re seeing is not a strange excepting, but the rule. You need that volume,” said Schroeder.

Likewise, manual sample preparation favors more pointed analyses aimed at known targets or viruses over exploratory genomic expeditions. “Does this colony have DWV?” versus, “what diseases, known and unknown, might be active in this colony?”

Schroeder saw manual processing as a bottleneck to discovery.

“When I was first developing my own lab, I always knew that we needed to go to the automation side. We couldn’t just stick to an individual person grinding up individual samples,” he said. “If you really want an understanding of what is unfolding in real time, you can’t take six months to process samples and get the story line. You need to get your samples processed within 24 hours. That was my target.”

 

Discovery at scale

On a visit from his lab in the United Kingdom to the University of Minnesota’s Bee Lab in Saint Paul, Minnesota, Schroeder received a tour of the campus and facilities.

“I was introduced to the diagnostic lab at the College of Veterinary Medicine and thought ‘wow, look at all that automation,’” he said. “We could do this for honeybees.”

At that time, the diagnostic lab’s automated sample preparation equipment was mainly serving swine industry clients in screening for known viruses. They were hitting a 24-hour turnaround time.

In another moment of career serendipity, Schroeder soon learned that a position was opening at the UMN College of Veterinary Medicine. He landed the job.

Getting in on the automation workflow for large-scale honeybee disease surveillance became his early priority.

“I really made an effort to study the swine industry and how they had automated. I set out to understand the standard operating procedures for creating a diagnostic test on a large, automated scale,” said Schroeder. “I was struck by the fact that no diagnostic lab would touch a species unless you had a strong platform or pilot study showing that the process was possible. So I used my start-up money to create that pilot.”

In true collaborative style, he even made some new connections along the way.

“I ended up becoming a swine virologist in the process and finding another area of overlap with giant viruses, leading to work on African swine fever virus,” he said.

What he learned from the swine industry’s use of automation platforms was invaluable.

Using magnetic bead technology and an automated processer – here, a Thermo Scientific KingFisher™ Sample Purification System – removed the stepwise manual element of spin column extraction and often brought the entire viral RNA extraction process down to one day. His team saw extraction results that were as good or better than in manual processing.

The automated processor also contains a 96-well plate, which means that Schroeder can prepare 96 samples at once. Achieving close to 100 extractions in a single run has allowed the lab to dramatically expand their field of exploration, from focused research on a single disease to population-level surveillance of many.

Of course, automated sample preparation is not new. Scientists used the KingFisher Flex in a similar vein at the height of the COVID-19 pandemic, when labs needed fast RNA sample preparation at scale to process millions of SARS-CoV-2 antibody PCR tests and analyze infection levels and variant spread.

But Schroeder’s goal to use it for generating large, exploratory data sets rather than diagnostic testing was unique for the field of bee research.

“I saw that the tools were there, the equipment was there, and the knowledge was there. I just needed to bring it to honeybee research for a problem like colony collapse disorder,” he said. “When CCD first happened, it took us too long to respond. Having a discovery pipeline like the one we’ve developed will allow us to respond very, very quickly in the future.”

What’s next for bee virologists

With a reliable, large-scale method for sampling now in place, the possibilities for application seem endless. Schroeder is not short on ideas.

Already, his team has used automated sequencing techniques to examine the interactions between non-native, commercial honeybees and native bee species.* Entomologists have long been wary of spillover of the pathogens like DWV potentially causing CCD from honeybees to native species.

“There have been a lot of studies on honeybees as the poster child, because they’re central to our pollination industry. We know that honeybees have a lot of viruses in them, and we have a decent understanding of that landscape,” said Schroeder.

“But we have all these other native species, like bumble bees. In Minnesota alone, more than 500 new species of bees have been discovered recently. These bees are visiting the same flowers and sharing habitat. And viruses are always moving.”

 

Surprisingly, Schroeder’s team found limited concerning genome matches between honeybee and common bumblebee viruses – meaning that spillover that leads to range expansion, i.e. bumblebee-to-bumblebee transmission, is not happening beyond dead-end transmission.

Instead, Schroeder says, the bigger threat for native bees is likely to be endogenous viruses that we haven’t yet discovered. There’s still a lot of ground to explore.

But the beauty of high-scale methods is that with them, researchers can cover more ground. Scientists don’t need to know what virus they’re looking for before they find it.

“Can we move beyond individual virus targets? Can we sequence everything?” said Schroeder. “We’ve done that now.”

Now, the true exploratory work can begin as experts like Schroeder dig into large datasets and find new questions.

In the national survey of DWV in honeybees, for example: “We saw that DWV has been recombining in the population to create really strange mutants. We don’t understand the full significance yet, but we would have missed this discovery had we just done PCR. It was an eye-opener for us that not only does automation technology allow us to go through things faster – it actually allows us to apply whole genome sequencing technologies to gain a fuller picture.”

There’s no going back.

“We’re opening up exciting new doors again. And it’s another Pandora’s box,” said Schroeder. “We can’t close it now that we know what we’d be missing.”

 

More resources

• Read the papers featured in this story:
  • Dominance of recombinant DWV genomes with changing viral landscapes as revealed in national US honey bee and varroa mite survey (Nature Communications Biology)
  • A semi-automated and high-throughput approach for the detection of honey bee viruses in bee samples (PLOS One)
  • Virome compositions indicate that viral spillover is a dead-end between the western honey bee and the common eastern bumblebee (Preprint, Under Review at Nature Portfolio)
• Follow Schroeder’s research at PubMed and Google Scholar
• Learn more about the College of Veterinary Medicine
• Learn more about the University of Minnesota’s Bee Lab
• Learn more about Kingfisher Sample Purification Systems

 

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* This work is funded by the Environment and Natural Resources Trust Fund as recommended by the Legislative-Citizen Commission on Minnesota Resources.

 

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