Categories
BLOG

genetic strain

Genetic Strain Diversity of Multi-Host RNA Viruses that Infect a Wide Range of Pollinators and Associates is Shaped by Geographic Origins

Affiliation

  • 1 School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand.
  • PMID: 32213950
  • PMCID: PMC7150836
  • DOI: 10.3390/v12030358

Free PMC article

Genetic Strain Diversity of Multi-Host RNA Viruses that Infect a Wide Range of Pollinators and Associates is Shaped by Geographic Origins

  • Search in PubMed
  • Search in NLM Catalog
  • Add to Search

Authors

Affiliation

  • 1 School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand.
  • PMID: 32213950
  • PMCID: PMC7150836
  • DOI: 10.3390/v12030358

Abstract

Emerging viruses have caused concerns about pollinator population declines, as multi-host RNA viruses may pose a health threat to pollinators and associated arthropods. In order to understand the ecology and impact these viruses have, we studied their host range and determined to what extent host and spatial variation affect strain diversity. Firstly, we used RT-PCR to screen pollinators and associates, including honey bees (Apis mellifera) and invasive Argentine ants (Linepithema humile), for virus presence and replication. We tested for the black queen cell virus (BQCV), deformed wing virus (DWV), and Kashmir bee virus (KBV) that were initially detected in bees, and the two recently discovered Linepithema humile bunya-like virus 1 (LhuBLV1) and Moku virus (MKV). DWV, KBV, and MKV were detected and replicated in a wide range of hosts and commonly co-infected hymenopterans. Secondly, we placed KBV and DWV in a global phylogeny with sequences from various countries and hosts to determine the association of geographic origin and host with shared ancestry. Both phylogenies showed strong geographic rather than host-specific clustering, suggesting frequent inter-species virus transmission. Transmission routes between hosts are largely unknown. Nonetheless, avoiding the introduction of non-native species and diseased pollinators appears important to limit spill overs and disease emergence.

Keywords: Apis mellifera; DWV; KBV; Linepithema humile; Moku virus; bee associate; honey bee virus; invasive species; pollinator.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Venn diagram of virus coinfection…

Venn diagram of virus coinfection in honey bees ( Apis mellifera ) (…

Maximum clade credibility tree for…

Maximum clade credibility tree for the RNA-dependent RNA polymerase ( RdRp ) fragment…

Maximum clade credibility tree for…

Maximum clade credibility tree for the major capsid protein vp3 fragment (360 bp)…

Emerging viruses have caused concerns about pollinator population declines, as multi-host RNA viruses may pose a health threat to pollinators and associated arthropods. In order to understand the ecology and impact these viruses have, we studied their host range and determined to what extent host an …

A New Crop of Marijuana Geneticists Sets Out to Build Better Weed

To revist this article, visit My Profile, then View saved stories.

To revist this article, visit My Profile, then View saved stories.

The marijuana analytics company Steep Hill doesn’t smell dank, or skunky, or “loud”—unless you happen to arrive when a client is dropping off a sample. No seven-pointed-leaf logos ornament the walls; no Tibetan prayer flags flutter from the doorframe. Inside, a half-dozen young scientists work in a glass-walled lab to the sounds of whirring ventilation and soft jazz. The effect is one of professionalism and scientific objectivity.

Still, this place is all about weed. And Reggie Gaudino, Steep Hill’s burly and dreadlocked 53-year-old vice president of scientific operations, does look the part. Steep Hill is headquartered in famously 420-friendly Berkeley, California, after all. “I’ve been smoking since I was 13 years old,” he says, looking down over a railing at the lab. It’s a world he has long appreciated. Now he’d like to give a little back. “There’s so much good that can be done with cannabis, and so little of it is being done.”

As more and more states (23 so far) are finding legal ways for people to consume cannabis, Steep Hill and labs like it are becoming more important. Steep Hill quantifies the numbers you see on labels in dispensaries: how much tetrahydrocannabinol (THC, the molecule that gets you high) and cannabidiol (CBD, the component of weed thought to alleviate seizures) are in a given strain of pot. But any remotely dedicated smoker will tell you that a strain is more than its potency. Purple Kush and Sour Diesel have different characters, different smells and tastes and feels. Those are the result of the interactions of hundreds of molecules—cannabinoids, yes, but also another class called terpenoids. Myrcene, for example, smells like hops and mango (and some fans claim it increases the potency of THC). Beta-caryophyllene has the scent of pepper. There’s also ocimene, nerolidol, pinene—the interaction of all these chemicals creates whatever distinction exists between ’78 LA OG Affie and, say, Green Crack.

So when someone drops off one of those samples at Steep Hill’s reception, the lab swoops in to quantify 27 of the most prominent of these flavorful, experience-defining molecules. After eight years in business, the company has accumulated and tested thousands of samples—it has stacks and stacks of plant tissue in test tubes in a giant freezer. It has analytical chemistry on those, and thanks to a deal with the marijuana review site Leafly, the company also has thousands of crowdsourced reviews. When it comes to data on weed, Steep Hill is, well, the bomb.

It’s one thing, though, to know what molecules are found in different weed strains. It’s another to know what those chemicals actually do—scientifically speaking. Their aromas certainly affect the experience of consumption, somehow. They might even underpin cannabis’s putative medicinal effects—fighting nausea, stimulating appetite, easing seizures, and perhaps even more.

And it’s yet another thing to understand the genetic basis for those differences. That’s the key. It’s what you need if you plan to breed scientifically, to enhance the qualities the market might pay for. Even more than legalization, that’s how you transform marijuana from an illicit pleasure to a licit business. “Every other commercially important agricultural plant in the world has had a ton of research done on it,” Gaudino says. “But here is this commercially important crop that has so much variation, and nobody knows what that variation’s all about.”

Plant biologists would love to understand cannabis better. But marijuana is a Schedule I drug in the United States, as illegal as heroin. Most academic researchers working with it are limited to (pathetic) weed grown at the University of Mississippi. Much of the research funding comes from the National Institute on Drug Abuse, which prioritizes studying ill effects over any potential good.

But Steep Hill has all those samples and all those chemical profiles. Now it just needs the genetics. And Gaudino, a geneticist and former patent agent, has a plan to get that. The problem is, deciphering the pot genome is, like, way harder than it sounds.

In 1993, the average THC content in weed was about 3 percent by weight. Over the next 15 years, breeders tripled the potency. Today, not even a decade later, levels top out at a whopping 37 percent. Thank the war on drugs: As growers moved indoors and out of sight, they drove up THC levels. Then they could charge more to pay for the costs of climate control and artificial lighting.

Smokers have gotten savvier, too. Increasing THC gets you higher but lessens the plant’s ability to make other, arguably more interesting, cannabinoids and terpenoids. So growers also set out to create new breeds that would be as different from one another as a chardonnay and a pinot noir. And it sort of worked: Just like a vintner will rattle off a bottle’s tasting notes and terroir, a Denver budtender can sell a smoker on a plant’s piney nose and its concentration of crystallized trichomes, hairlike protrusions that contain high levels of psychoactive cannabinoids. These kinds of characteristics, the ones you can see (or smell), are a plant’s phenotype.

If you know your plant’s genotype, though—the genes behind those traits—then you can grow the plants with the traits you want much faster and with extreme precision. Called marker-assisted selection, it’s the key to modern agriculture.

When Gaudino joined Steep Hill in 2014, he looked at the company’s vast trove of data and asked CEO David Lampach what kind of research their competitors were doing. Lampach’s response: “What do you mean, what are people doing? There are only three testing labs worth anything in the entire US.”

Gaudino was shocked. “I asked, ‘Have you guys ever considered genetic analysis?’”

Specifically, Gaudino wanted to build a full assembly of marijuana’s 800 million base pairs and 10 chromosomes to help breeders discover more markers for specific traits. Then, ideally, they’d be able to turn up the expression of any of the hundreds of chemicals in weed—some that smell great, some that get you high, and some that might ease pain or maybe even treat a disease. “My mad-scientist dream is a database where you can type in what you’re looking for,” Gaudino says. “You’ll either get out the strain that exists that does that or if it doesn’t exist, it’ll tell you what strains you could begin breeding.”

Other people had already tried it. In 2011, Kevin McKernan, chief scientific officer of a firm called Medicinal Genomics, made public the sequences for strains called Chemdawg and LA Confidential. And Jonathan Page, a biochemist with Canada’s National Research Council, had results for the Purple Kush genome. But these weren’t the kind of sequences anyone could use.

The problem is, geneticists don’t simply unspool all the DNA in a cell and then run it through a scanner, like the roll on an old-time player piano. They break those miles of code into teeny pieces, read those, and then use the overlaps to put them all back together like a jigsaw puzzle. The go-to standard sequencing machine, built by a company called Illumina, scans pieces of DNA from 100 to 350 base pairs long. (A single gene might comprise more than 2,000 base pairs.)

This method isn’t great for plants. Their genomes are naturally full of repeating sequences, which makes it almost impossible to tell which fragments overlap—they all look the same, so you can’t line them up. Worse, plants tend to maintain multiple copies of their useful, core genes as backups in case something goes awry in their environment. (Unlike animals, which can run away from their problems, plants have had to adapt to their protean surroundings.)

Cannabis breeders have made the problems even worse. They’ve been crossbreeding for so long to pump up pot’s psychoactivity that modern strains can have as many as 11 copies of the gene that synthesizes THC. If the crossbred genome were a jigsaw puzzle, most of the picture would be blue sky.

In the end, those first attempts to sequence the cannabis genome yielded hundreds of thousands of tiny fragments, so many that nobody could stitch them together. But Gaudino thought he could do better. “I’m not a gambling man, but this was one of the times that I gambled,” he says. “And I went long.” In 2014, Steep Hill spent $1.1 million on a PacBio RS II sequencer, one of fewer than 200 in the country. It’s a giant white box sitting next to the freezer full of frozen buds, adorned with 8-inch-tall Cheech and Chong dolls that Gaudino got when he was a kid. Unlike the much cheaper Illumina sequencers, the PacBio reads fragments of DNA as long as 53,000 base pairs.

Then Gaudino went to a Berkeley dispensary, bought a citrusy-smelling Kush strain called Pineapple Bubba, and spent $20,000 on reagents and data-crunching to sequence it. It wasn’t a genome yet: 583 million base pairs shattered into 18,000 puzzle pieces. Still, they were longer than anyone else had, easier to reassemble. Gaudino just needed more data to string them together.

There are thousands of strains of weed. Cracking their genetic codes may be the key to transforming pot from a budding business to a high-flying industry.