New & Noteworthy
August 30, 2015
SGD staff will be attending the 27th International Conference on Yeast Genetics and Molecular Biology (ICYGMB), September 6-12, in Levico Terme, Italy. We will be hosting a Workshop, Posters, and an Exhibit Table. We’ll be available during the entire conference to hear your comments or suggestions about SGD and answer your questions.
Follow @yeastgenome and #Yeast2015 on Twitter for the latest research being presented at ICYGMB.
Find these SGD staff members at the conference:
Sunday, September 6, 4:00 – 6:00 PM
We’ll be discussing our curation efforts in capturing yeast-human functional complementation data, the new sequence Variant Viewer, new data in YeastMine, and more. Bring your questions and comments – we love feedback!
In addition to the Workshop, SGD staff will present three posters – please stop by and chat with us.
|PS7-9||Homology curation at SGD: budding yeast as a model for eukaryotic biology||Stacia Engel||Sala Belvedere||2:30-4 PM, Tuesday and Thursday, 9/8 and 9/10|
|PS15-24||Inferring Genome Variation Patterns in Saccharomyces cerevisiae using the Eukaryote Pan-Genome Toolset||Giltae Song||Sala Impero||2:30-4 PM, Monday and Thursday, 9/7 and 9/10|
|PS15-29||Integrating genome-wide datasets into the Saccharomyces Genome Database||Edith Wong||Sala Impero||2:30-4 PM, Tuesday and Thursday, 9/8 and 9/10|
SGD will also have an exhibit table at the conference. Come by to take a spin on our site, learn about various features of the database, and provide us with feedback as to what we can do to improve SGD. You might even receive a prize for a good question or suggestion!
August 28, 2015
SGD periodically sends out its newsletter to colleagues designated as contacts in SGD. This Summer 2015 newsletter is also available on the community wiki. If you would like to receive the SGD newsletter in the future please use the Colleague Submission/Update form to let us know.
August 26, 2015
If you’ve ever put together something from IKEA you know it can be a bear. So many parts need to connect up together perfectly to build that new bookcase—if you tried to do it all at once you’d go crazy.
Luckily the good folks at IKEA try to make it a bit easier (and more tolerable) by splitting the task into smaller, more manageable pieces. You can concentrate on one part without having to worry about the rest. Once that part is done you can work on the next part and so on. In the end you assemble all the pieces together into your new bookcase.
This is the approach Galanie and coworkers took in their recent Science paper where they engineered our favorite yeast S. cerevisiae to make a couple of different opioids. And it is a good thing they broke this problem up, because it was a way bigger undertaking than anything IKEA might have thrown at them. Engineering this yeast strain was a genetic tour de force.
The authors coordinated 21 different genes from mammals, plants, bacteria and yeast to get the opiate precursor thebaine made. And the semisynthetic opiate hydrocodone took an extra two genes for a grand total of 23! Trying to do all of these at once might have been very frustrating. Thank goodness they split this Herculean task into six (or seven for hydrocodone) smaller modules.
The first step was to get yeast to make (S)-reticuline, a key intermediate on the way to useful opiates. This took 4 modules made up of 17 different genes: six from rat, six from plants, four from yeast and one from bacteria.
And of course just putting these into yeast all at once would almost certainly have made a whole lot of nothing. Each gene needed to be selected from the right beast and then optimized to work in the yeast strain. Sometimes this meant picking the right variant from the right plant, and sometimes it meant mutating a gene to make it behave better. This all would have been overwhelming if the task weren’t split into four easier sections.
Even with all of their optimization, this iteration only made about 20 μg/liter of (S)-reticuline. They needed yeast to crank out more of this intermediate, so they designed a fifth module.
As its name implies, this “bottleneck” module was designed to overcome bottlenecks in the first four modules. After it was added to the strain, the yeast managed to make 82 μg/liter. This was something they could work with!
Except now they were stuck. They needed (R)-reticuline instead of the S form, but no one knew how poppies managed this feat. The gene that did this job hadn’t yet been discovered.
So Galanie and coworkers rolled up their sleeves and dug through plant transcriptome databases to find the gene they were looking for. They found a likely candidate, synthesized the gene in order to produce the enzyme, tested whether it could transform the S form of reticuline into the R form in vitro, and found that it could.
They could now make the right intermediate, which meant they could make their final module. As its name implies, this “thebaine” module would finally allow them to make the opiate precursor thebaine in yeast. This module consisted of their recently discovered gene and three other plant genes.
They had finally made thebaine from simple sugars in yeast! Except it didn’t work very well at all. There seemed to be a bottleneck right after the (R)-reticuline stage. Back to the drawing board!
Given where the bottleneck was, the researchers guessed correctly that the culprit was the SalSyn enzyme which converted (R)-reticuline to salutaradine. A Western blot showed three distinct forms of this enzyme in yeast and only one form, the lowest molecular weight one, when it was expressed in tobacco. Clearly something was happening to inactivate this protein in yeast.
A close look at the protein suggested yeast was glycosylating positions that it shouldn’t, and site directed mutagenesis of these sites confirmed this. The glycosylation was causing the protein to be sorted incorrectly so that it couldn’t do its job.
Unfortunately just mutagenizing away the glycosylation sites wasn’t good enough, because this severely affected the enzyme’s ability to do its job. So the researchers created a chimeric protein with parts of another P450 enzyme they knew did great work in yeast. After optimizing its codons for yeast, this chimera performed beautifully.
Now, finally, they had a yeast strain that could make thebaine. Not a lot of it, only around 6.4 μg/liter—but amazing nonetheless.
A final module was added that consisted of two plant enzymes that converted thebaine to the drug hydrocodone. This monster strain could crank out around 0.3 μg/liter of hydrocodone. Yes, that is as puny as it sounds; one dose of painkiller for an adult would contain 5 mg of hydrocodone.
To be competitive with poppies, they need a 100,000-fold improvement to around 5 mg/liter. In talking with Dr. Smolke, it sounds like this could happen within a couple of years. After scaling up for production, voila! An entirely new source of opiates for pain relief.
Of course the elephant in the room is a Breaking Bad-esque scene where a yeast biologist grabs ahold of an opiate-producing strain and supplies various cartels with illegal drugs. Our Walter White wannabe wouldn’t be able to use the current strain, as he would need thousands of liters of yeast to produce a single dose of Vicodin.
But this scenario will be a real concern in the next few years. Which is why the Smolke lab has crossed every t and dotted every i in setting up and creating this strain. They have made it as difficult as possible for the wrong people to get their hands on it.
This strain represents a stunning achievement in synthetic biology. Move over poppies, there’s a new opiate producer in town.
by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
August 24, 2015
SGD includes data on many thousands of genetic and physical interactions between the genes and proteins of Saccharomyces cerevisiae, as curated by our friends at the BioGRID database. We provide two different graphical displays that help you get a very quick and intuitive overview of known interactions for a particular gene or protein.
All interactions for a gene and its product are listed on its interactions page (see an example). At the top of the page, the Interactions Overview shows at a glance how many interactions have been curated and whether they are physical or genetic. This video explains the details of the Interactions Overview diagram:
Farther down on the Interactions page, the Interaction Network is a visual representation of genetic interactions for a particular gene and the protein-protein interactions for its gene product. The network is interactive, allowing you to choose to view either genetic or physical interactions or both. Using the slider, you can set a minimum number of experiments supporting the interactions displayed. Learn how to use the interactive features of the Interaction Network by watching this brief video: