Inventing the engine for understanding biological networks
University of Toronto
My major motivation in life and science is exploration. Canoeing, snowboarding and fly fishing where no one has before, going somewhere new, that is what drives me.
I think our lab has done two things that are really interesting. Firstly we figured out what thymine proteins do and secondly, we elucidated the breadth and scope of genetic networks through the development of a synthetic genetic array (SGA).
I used to hang out with a lot of the people who were making the deletion mutant collection, and that was clearly a very, very powerful genome-wide tool. Making the double mutants was an obvious next step, and the only problem with that was the scope of the project. You probably couldn’t do it through systematic transformations, so we had to start thinking about mating and stuff like that
Thanks to the ensuing genetic interaction studies using SGA, the majority of pathways in the cell are now within our grasp of understanding, and if we can manipulate them, then we have a good chance of correcting innumerable health issues which stem from those pathways. Eventually, it will allow you to interpret your own genome providing you with the information needed for personalized medicine. Tailoring medical decisions, treatment plans and prescriptions should lead to a drastic increase in the quality of patient care. This is something worth working towards!
We have to figure out how to do SGA 10 times cheaper and 10 times more efficiently. If we can do that then we could redo everything we’ve done, three or four times and remove all the false positives and the false negatives. We could have a perfect picture of the global chain of networks under standard laboratory conditions which admittedly are pretty bizarre because we have to use all these drug selection steps. But, then, we would do the same thing under a bunch of different conditions, and ideally different genetic backgrounds. So, we would live in a much fuller data-rich world of genetic interactions than we do already and we’d have a much broader view of how they differ across conditions and genetic background.
There are two things you need to know about fly fishing. First, you have to do it to “get it” and it’s not easy. In its purest form you are throwing a lasso, a huge line, and you have to handle the rod in a counterintuitive way because you’ve got to use the power of the rod, the flex of the rod, to throw the line. Then you work the line with the other hand so every cast is a fun thing to do. You have to drift the fly in a way that the fish is fooled which is challenging because they have a lot of knowledge about what real flies look like and so they don’t go after things that are not real!
After the take, when they hook up, you have to battle the fish to get in. Most of the time you let them go because we often fish where you can’t actually keep your catch. You’re always in a very beautiful place; walking down the stream by yourself it’s great there’s nothing better than fishing. And fly fishing is sort of the ultimate form of fishing.
There are downtimes when you’re fishing when there is nothing happening and you are hanging out with your buddies. I have learned a lot from my scientific buddies while fly fishing. I guess it’s just human interactions outside the lab.
The “big picture” project a bunch of us have been talking about is what we would like to refer to as Google yeast where every lab designs a read out for their pathway of interest and then we survey all genes for a potential role in the activity of that pathway. We do it quantitatively and in such a way that the information can all be integrated. Therefore we would be extracting information from all around the world in a highly quantitative manner at the level of a single cell and we would integrate that into a global picture of how these pathways are integrated and networked in some kind of cohesive way.
The barriers are huge! You need to build the platform, fund it and then prove that there is value in participating there, so that if you run your pathway through this system that you are going to get a lot of information. Then when you integrate it with the growing database, the big picture will also make sense to you as well. The “big picture” in this context has never been seen before. Exciting stuff!
Yeast is the most well-understood cell on the planet. We can manipulate it like no other organism because of its incredible genetics! Bearing this in mind, yeasts should be our test bed for all things genome-wide and complicated, because that’s where we can assess them quickly. Aside from genome-wide applications yeasts have also served as an incredible tool for understanding signalling pathways, cell cycle regulation, DNA damage response and secretion to name a few. All these fundamental pathways and programs got figured out in yeast!
There is no question that this is the time of biology and the more we understand about biology the healthier every one of us will be. It would be crazy not to invest in this, not to explore this because we are all alive right now and this is the time to figure it out, we are all going to need it!