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MIT student blogger Anastassia B. '16

My Awesome Biology UROP: florescent plants, genomes, metabolomes, big data, puzzles + more! by Anastassia B. '16

Bonus: A VIDEO!

When I tell people that I’m majoring in Biology, they typically assume that I am pre-med, or else shudder at high school memories of endless memorization and quickly change the topic. But to me, Biology isn’t either of those things. Biology is an incredibly challenging, multi-dimensional puzzle; and in our post-genomic age, it has become an INFORMATION SCIENCE.

So Biology is not just “anatomy and physiology”, but also: biochemistry, bioengineering, bioinformatics, biomechanics, pharmacology, biophysics, biotechnology/synthetic biology, cognitive biology, developmental biology, ecology, evolutionary biology, genetics/epigenetics, molecular biology, neurobiology, population biology, structural biology, and much more!

My branch is Computational Systems Biology, which can be explored at MIT from three different majors: 6-7, 7, and 20. I am fascinated by the workings of complex systems, and I love using big data to look at the “big picture”. Because of this, and the bonus that I get to work with plants (Arabidopsis thaliana) as the model organism, I joined the Weng Lab 8 months ago. It has been an amazing UROP experience through sophomore spring, my entire summer, and junior fall (now).

In the summer, for Elizabeth C. 13’s Science Out Loud series, I decided to make an episode about some things I do in the lab! It was just released to youtube, so check it out:

My video doesn’t really describe the specifics of what I do, but gives a general idea of why. It also shows you where I work– at the wonderful Whitehead Institute for Biomedical Research, with shots from my lab and our greenhouse. It’s a pretty simplified overview– being aimed at the K-12 level– so I wanted to include some more images as to what I actually look at and analyze:
The white bands are pieces of DNA. After I have performed Polymerase Chain Reaction in order to amplify the correct fragment I’m interested in, I can run it on an agarose gel which sits in an electric field, in order to separate the fragments by length. I can then extract the DNA from the gel and use it in subsequent reactions, knowing I am working with the right sequence.
This is a data sample of a portion of the Arabidopsis metabolome. The rows are the variating Arabidopsis lines, and each column is a metabolite. The colors represent deviation from average– blue means the metabolite is present below average, and red means it is accumulating above average, to various degrees. To understand biological big data, I’ve been working closely with the Bioinformatics resources at the Whitehead, and learning everything that they do. By comparing the genomic sequences to the metabolomic data (two huge data sets with a lot of unknowns), I can start to piece together the system I am working with. It’s almost like a giant puzzle, where the metabolomic data provides you with all of the “blank” pieces, and the genome provides you with the overall picture, but it’s up to you to piece them together.
And this is what some of my plants look like under UV light! I love being able to work in all stages of my experiments– the greenhouse, the wet lab, and the data analysis. If you have any questions or comments, always feel free to email me at [email protected].
Huge thank you and shout out to Science Out Loud for this great opportunity! Everyone should come to the premiere of Season 2 on November 4, at 5 pm, in the Simmons MPR. I will be there, along with food, and all the other episode hosts. :)