One of the things I have learned the hard way during my first year as group leader is how easy it is to overestimate the ability of beginner scientists – graduate students, interns, undergraduates – to grasp the “big picture” of the project. Beginners are usually quite good at performing experiments and processing results, but they typically find it very hard to visualize where the experiment fits in the grand scheme of their project. I would like to propose a framework that will make it easier for beginners and their mentors to stay on the same page when it comes to the big picture of their projects. I think it is very useful to look on projects in terms of a tree or a mind map. The root of the tree is the overarching goal of the project. For the sake of simplicity, we will work with an example – we have a protein called bunnyhoppin that is involved in bunny hopping. We want to know the mechanism. So the root of the project is “Bunnyhoppin mechanism of action”. For visualizations, I will use Freeplane, a freeware mind mapping program.
One of the ways to determine the mechanism of action would be to identify proteins that bind to bunnyhoppin and are functionally involved in hopping behavior. Another way would be to look at changes in gene expression in bunnies that lack bunnyhoppin. These sub-goals would correspond to grant specific aims. Here’s how we picture that:
Let’s look at the left sub-aim (proteins that bind to bunnyhoppin and their functional relevance). There is a specific sequence of experiments that we would have to follow here:
- Identify binding partners by a bulk method
- Pick candidate proteins with potential relevance to bunny hopping
- Confirm binding by alternative methods
- Test confirmed binding partners in a functional assay
For 1. we could use a coimmunoprecipitation followed by mass spectrometry from a relevant tissue or cell line, let’s say from bunny muscle tissue. For 2. we would probably eliminate all contaminants, such as chaperones and then do a literature search for each of the remaining binding partners for hints of its potential relevance for hopping. For 3. we could do reciprocal co-IP/immunoblot or proximity ligation assay. For 4. we could create bunnies with candidate protein knockout or test function in a muscle cell line if we suspect that bunnyhoppin is involved in muscle contractility. So here’s how all that would look:
Please note that each step is dependent on the previous step, so there is a natural progression. Some steps might need multiple previous steps. For instance, IP/MS might require picking the right antibody and elution method. We might also want to use an alternative method to increase the validity of our results, so instead of IP/MS from muscle tissue, we might want to do pulldown using bunnyhoppin produced in E. coli. Or even IP/MS from cultured muscle cells:
Perhaps you have not done muscle contraction assays or siRNA transfection in vitro, so you may need to develop the methodology in the lab as well:
Sometimes it is also useful to know alternative paths to the same goal. For instance it may be very difficult or expensive to make KO animals, but maybe instead you can test the function in vivo by electroporating shRNA or CRISPR constructs into bunny muscles:
And so on for all branches and subbranches of your project. So as your project crystallizes, you get a better and better idea of the sequence of experiments that need to be done in order to reach your main goal (“Bunnyhoppin mechanism of action”). This is what I call the “tree of life” of your research project. You start at the leaves and make your way to the root. Knowing where you are on that tree makes it much easier for a beginner researcher to orient themselves:
- Boosts their morale. They can see the light at the end of the tunnel (the root/overarching goal).
- Knowing the immediate significance of the experiment that they are doing not only helps their motivation, but also allows them to design the experiment in a way that will allow them to move forward towards the root.
- They know what it will take to accomplish the goal of their project and allows them to prioritize and plan ahead.
- They know alternative approaches, so they don’t get discouraged if things go wrong in one of the branches.
In the companion post, I outline how the “tree of life” of the project can help with experimental design and interpretation of the results.
One final remark: the “tree of life” of your project is a living thing – some branches will wither, new ones will grow, and some acorns that fall of the tree (unexpected results, serendipitous finds in “fishing expeditions”) will give rise to new trees. Make sure you update your “tree of life” as your project matures. Please leave a comment if you like the idea or if you have some feedback. And don’t forget to have fun in your forest!