From One Rotation to the Next

by simoneng

So far, it’s been about a month and half since I started grad school here in Toronto. My first rotation has come to a close, and my next one starts next Tuesday. What have I learned so far?

A department of hypothesis-driven projects

Here, the immunology department is very traditionalist in a scientific sense—from what I can surmise so far, the research in the department is heavily based on a hypothesis-driven approach. After talking with some students and post-docs, it appears that I may have arrived at a very interesting time in the sense that the department has only really awoken to the potential of applications of bioinformatics and computational biology to some of the projects here. The PIs I have talked with to date are without a doubt really excited about my arrival in Toronto.

I’m beginning to feel that I made the right choice in department here in Toronto. I didn’t want to do a bioinformatics degree for the very reason that I wanted to be able to infer the biological implications of the results of whatever bioinformatic analyses I perform on data. As an immunologist-bioinformatician, I suppose that I’ll be expected to generate my own data in the lab and analyze them in weird and wonderful ways. This excites me greatly…to go beyond just statistical analyses. Graphs! Algorithms! Computational models! Which then feed right back into bench work. In a sense, I guess I’ll become intimate with the data. Very intimate.

In a sense, my position in the department seems unusual, almost alien. The sort of projects I will get to tackle are almost guaranteed to involve exploratory analyses. Since I’ll be interacting with scientists and students to whom the scientific method (and consequently hypotheses) is king, the question that I will likely have to answer repeatedly is, “What in the world are your hypotheses?” Hmm. Good question.

What else have I learned so far?

Laboratory stuff

• Experiments are like cooking: you should have everything nicely prepared before you start. Like having all of your reagents readily available, your materials nicely laid out, labelled, and arranged (!), and ensuring that any apparatuses you’re going to use are set to the correct parameters. When you’re making a soup, do you slice up your vegetables after the water has come to a complete boil? Thaw your meat while the oil in the pan is sizzling? No. Same thing with experiments.
• Always label things. Well. Very well. Use tape and marker if necessary. Write painful amounts of details, because four weeks down the road, will you remember what that microfuge tube with the plus sign contains?
• People tend to be late in running experiments. This consideration is important when you book thermocyclers for PCR, for instance.
• PCR optimization is frustrating, partly due to the number of variables—and their dependent variables—to optimize.
• There is an art to taping up gel boxes such that agarose doesn’t leak out from them when you pour it.
• Taking images of gels is like photography: you initially want to adjust the exposure such that you capture the greatest possible dynamic range of light intensities. Once you take the image, you can adjust the white and black points from there.
• -80°C freezers are cold. Very cold. Even with gloves on.
• Never place ice boxes at the edge of ledges. Pandemonium will ensue.
• Expect Lazarus mice once in a while. They’ll look confused when they revive.
• If you don’t know how to do something or are unsure of something, just ask. People will generally be glad to help you out.
• Balancing lab work with bioinformatics is an insanely difficult balance…mostly because one supervisor will forget that you also have analyses on the bioinformatics side of things to perform. And vice versa. I know a balance can be achieved, though.
• 9 to 5, or some variation of consistent hours, is doable…but it’s important to understand that you’ll sometimes need to book in some extra time to finish experiments or analyze data. Maintaining an extremely rigid schedule is ill-advised.

Choosing a project and advisor

• Talk to everyone in the lab. Everyone. No matter how scary they appear to be.
• Ask lots of questions about projects; even banal, trivial questions at the beginning are a good way to show some initiative.
• It’s important to gauge the general mood of the lab. Perception is key. Are people satisfied?
• If you ask, people will tell you why they chose that lab, what they like about it, and what they don’t like about it.
• Even better, go for some beer with some people from that lab. Alcohol (excuse me, ethanol) makes for a very casual environment where people can be very frank about certain things.
• If you’re in a Masters program and you want eventually want to do a Ph.D, make that intention very clear.

And finally, as another student told me, choose wisely in the end. Choose not only with your mind, but also with your heart.

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