Author Archives: Nina Sun

“Started from the bottom now we’re here”     –   Well-known Canadian poet

As the program comes to close, I cannot believe how quickly the summer has passed. Eight weeks ago, the title of my first post was “Started from the bottom” so naturally my final post is “Now I’m here.”

Where is here exactly?  Here is feeling comfortable with the lab and the people in it.  Here is knowing things that I never would have learned in a classroom.  Here is leaps and bounds beyond where I began in terms of experience and knowledge about research. Yet, here is still pretty undecided about what I want to do after college.

I have learned so much in my time at the Donald lab, both about computational protein design and about research in general.  If I have learned anything, I have learned how important collaboration is.  The sharing of ideas within the lab and with other labs plays such an integral part in research.  Asking questions, making comments,and asking more questions is the quickest way to learn.  Reading scientific literature is also a skill that I didn’t expect to learn this summer.  It is incredible to think about just how much information is out there, the amazing strides people have taken, and still how much is left to explore.

I don’t know if I will ultimately end up in research, but regardless, this experience was invaluable. Coming into the summer, I had barely thought of the upcoming year, let alone graduate school. But I discovered it is impossible to listen to faculty talks and people’s journeys in research without thinking of maybe having my own.  At this point, I think I will go to graduate school. Maybe not immediately, but someday.

Last but not least, I would like to thank the HHRF program, Dr. Grunwald, KP, and Paul for giving me a chance.  I’ve come a long way in my eight weeks, and I’m glad to be where I am.

Between biweekly faculty talks with the Howard Hughes program and the weekly talks in the Computer Science department, this summer has been truly a plunge into academia.  While I enjoyed listening to all the research, what I liked most about the faculty talks had nothing to do with the science (usually).  My favorite part of the seminars was hearing about how everyone got involved in research.  No one’s story is the same.  There is no one path into the life of academia.  For a lot of speakers, it was a matter of chance.  The chance of taking a life-changing course in college.  The chance of reading a specific paper at a specific time.  The chance of having a professor have faith in you.

No matter how they got started, it’s the passion people have for what they are studying that I find truly interesting.  One talk that stood out to me was that of Dr. Huntington Willard. Unlike other speakers, he didn’t spend much time at all on his work and instead spoke entirely about getting into research.  It is so clear that he loves what he does and really wants to help young people find what they love.

The way that he got into research: being in the right place at the right time.  What are the chances of him stumbling across a paper on X inactivation while waiting in the library, the topic that would be his research focus for the next twenty years? What are the chances that he would find something that he is so passionate about? What are the chances of anyone finding that passion, really? The way Dr. Willard described it, it was fate.  His advice about research came from years of experience and from years of perseverance in his field, and I appreciate him taking the time to share what he has learned.

Regardless of whether I end up in research, I truly am thankful for the faculty talks this summer.  They opened my eyes to the passion people can have for their work.  No matter what path each of the speakers took to get to where they are today, they all ended up with the opportunity to spend their life studying what they love.  Maybe it was chance, maybe it was fate. Either way, it sounds pretty great.

If I have learned anything in the last six weeks, I have learned how short six weeks is (and eight weeks for that matter).  I feel like I have learned so much, but also like I don’t have much to show for it.  It’s not that I was expecting groundbreaking research to have already been accomplished, but it is unsettling how preliminary my preliminary results are.

So far, I have designed a straight alpha helix that interacts with identical helices. Together, they would sit comfortably in a membrane–however, in the process of redesigning the side chains, I no longer think the sequence would actually form a helix.  I’m not that optimistic about my “results.”

Other than that, I am grateful for all the help I have received from everyone in the lab.  I am especially grateful for the reassurance that having the most preliminary of preliminary results is not a failure but just a part of the long process of research.  I have really enjoyed the time I have spent in the lab and having a chance to meet so many fantastic people. As things come to an end, I am feeling the time crunch to finish my poster and a write-up for my PI, but I just have to remember how lucky I am to have this opportunity in the first place.

This week we had the chance to hear about everyone’s research through chalk talks.  I really enjoyed finally hearing about what each of us were working on.  It’s always fun to listen to people talk about what they are interested in, and it was impressive how varied our research focuses were.

One that I found particularly interesting was Wilson’s research in the Groh lab (hey Wilson, apparently our PI’s are married). His research is to study motor learning and the neuroscience behind music. Using an Xbox Kinect camera, they are tracking the movements of people’s fingers as they play the piano and press keys.  Using test subjects of varying musical background and piano ability, they are studying how the patterns change as you learn how to play.  It is really cool that you could write scripts to use an Xbox Kinect to measure movements of the hand so precisely.

Finding a way of empirically measuring something that is so abstract and not quantifiable like music seems like a daunting task, yet one that could yield really fascinating results.  I am looking forward to hearing how it all turns out!

A “typical” day in the lab for me has varied over the past four weeks, but here are the basics.

Using a protein visualization software called PyMol, I look at the 3D structure of proteins.  For the past few weeks, I have been looking at transmembrane proteins and becoming familiar with using different functions of PyMol.  I also look at the different properties of the side chains and look at how they interact.

I also use OSPREY, a software developed by the Donald lab to redesign proteins. While I understand the basics of OSPREY, my knowledge of its functions and settings is very minimal at this point. Using OSPREY, I can change a protein then use PyMol to see the changes. Depending on the input, the program to take a while to run, so I usually read articles while I wait.

Of course, however, there is a good amount of time I spend trying to figure out why something is not working. I have had fairly good luck with most of my runs, but there is always some troubleshooting involved when trying something for the first time.

The lab itself looks like an ordinary computer lab. There are usually 3-4 of us in the lab, and some of the graduate students work in their offices. Usually the World Cup is playing somewhere in the room, and my PI comes in about every other day in the afternoon to discuss how people’s projects are going. Overall, I really like all the people in lab, the relaxed environment, and having the opportunity to be learning so many new things.

Being able to study animals while they behave naturally is key in understanding the brain. Using carbon nanotube electrodes, the firing on individual neurons can be recorded, which can lead to further information about how the brain functions.  These intracellular recordings in a freely behaving animal can give insight to how an animal learns and interacts with its environment.  This carbon nanotube electrode has already been made in Dr. Donald’s lab, and my project is designing a protein to improve on the cell membrane penetration of these electrodes.

Currently, puncturing a cell with an electrode does not lend itself to longterm cellular recordings because the cell will be damaged. However, perhaps we could lessen this damage by creating a “seal” between the membrane and the electrode.  Over at Stanford, Dr. Nick Melosh used a probe that would specifically interact with the hydrophilic-hydrophobic-hydrophilic properties of the lipid bilayer.  The probe was hydrophilic with a hydrophobic band in the middle.  When this probe pierced the bilayer, the hydrophobic band would interact with the hydrophobic tails of the phospholipids in the membrane, which made a “seal” between the probe and membrane.  Greater force was required to move the probe past the membrane.

Using this idea of a hydrophobic “collar”, my project is to design proteins that could replicate this effect for a the carbon nanotube electrode.  This would create the potential for longterm intracellular recordings. In my design I must consider the interaction between the protein and the carbon nanotube, interaction between the protein and the membrane, and interaction between the protein and other identical protein subunits.

My project is somewhat different than other projects in the lab in terms of the de novo design aspect and the carbon nanotube focus, but it fits the overall theme of using algorithms and protein design programs to solve problems.

This week I had the opportunity to have lunch with Dr. Bruce Donald and ask him a bit about his life.

Dr. Donald graduated from Yale with a major in Russian Language and Literature.  He had been always been interested in language, taking French and Latin, and became interested in Russian philosophy.  A visit to the Soviet Union during high school also proved influential.  He notes that the accomplished professors at Yale had a significant impact on him.

So the obvious question is how a major in Russian Language and Literature became the first step to becoming a professor of computer science, biochemistry, and electrical and computer engineering. Dr. Donald programmed throughout high school, and worked as a research analyst at the Harvard University Graduate School of Design during most summers of his undergraduate years.  After graduating from Yale, he essentially walked into Harvard, sat down at a computer, and convinced them he could program. Harvard hired him.

For graduate school, he applied two places: Oxford for Russian literature and MIT for Computer Science.  After being accepted to both, he chose the latter. After MIT, he became a professor at Cornell, then a visiting professor at Stanford.  For a few years he worked at Paul Allen’s company (Paul Allen, the cofounder of Microsoft). When I asked about choosing between academia and industry, he noted the constraints of projects in companies.  Although he enjoyed his time working in Palo Alto, he preferred having his own lab and having the freedom of working on projects that could take 10-15 years.

At Stanford, he met his wife and together they found jobs at Dartmouth, and now they are both professors here at Duke.

Looking at his research, he has collaborated with several departments, worked in several fields.  When I asked him what it was like to have such a variety of projects, he looked kind of confused.  While I saw article titles that looked very different, projects related to artificial intelligence, robotics, neuroscience, and molecular biology, he saw several related aspects of a larger idea.  He tells me, there is an idea of abstraction in computer science that doesn’t exist in biology.  His lab applies computer science to biology, applying algorithms to solve a variety of problems. The projects are a way of proving by example a larger idea.

After speaking with him, I feel even more grateful to be a part of his lab, to have the incredible opportunity to learn from him.  His long, impressive resume speaks for itself. He’s also in a band, which is pretty cool.

New summer, new lab, new people, new operating systems.

The first thing I learned at Dr. Bruce Donald’s lab was how to open a file.  Yes, I was making progress at record-breaking pace with the help from my undergraduate mentor, who has been working in the Donald lab officially for a whole two weeks (which is insane because he has such a solid  grasp for everything that’s going on). He has been so incredibly helpful, and I definitely foresee myself bombarding him regularly with questions.

Which brings me to the second thing I learned: how much of research is talking to people. All I did this week was read papers, which was challenging and informative, but a lot of unexpected learning happened just by being surrounded by people discussing science. I was surprised by the atmosphere of academia, the amount of excitement people had when talking about the latest research. This summer, I expect to be continually surprised at the amount of passion people have for what they do (and how long they can talk about it).  It’s incredible to hear my PI go on and on about the various projects in progress, projects ranging from HIV vaccines to de novo protein design and updating their own lab-created software.  This is not my first time in a research lab with enthusiastic professors, but I will continually be amazed by people doing what they love for a living.

Through sitting in on lab meetings, I can tell that the lab has several collaborators from all sorts of different fields, again attesting to the fact that science is social. From the lab website, the Donald lab is a part of the Department of Computer Science, Department of Biochemistry, Department of Electrical and Computer Engineering, Department of Chemistry, and more.  It would honestly not surprise me if it were also part of the Department of Magical Law Enforcement and the Department of Mysteries.  Oh, and probably also the Department of Russian Literature (more on that in a later blog post).  My point is that combining several disciplines involves a steep learning curve for me. I am standing at the bottom of this giant mountain of things to learn in biochemistry and computer science, but at least I can only go up from here.

#candid

My expectations for the summer include learning how to use some really cool software, becoming a pro at making more than peanut butter and jelly for lunch, and getting to know a bit more about the frustrations and rewards of research.  Completing my project would be a plus, but right now I’m much more excited about the possibility of looking at a 3-D protein structure and seeing more than pretty colors. I have a long way to go, but I’m excited.