At A Glance
Name: Akhilesh Pandey
Position: Assistant professor, department of biological chemistry and oncology, Johns Hopkins University, since 2002. Founder of Institute of Bioinformatics in Bangalore, India.
Background: Instructor, department of pathology, Harvard Medical School, 1998-2002.
Visiting Scientist, Matthias Mann’s laboratory, Center for Experimental Bioinformatics, University of Southern Denmark in Odense, 1999-2002.
Postdoc, Harvey Lodish’s laboratory, Whitehead Institute for Biomedical Research, Cambridge, Mass., 1996-1999.
PhD and Postdoc, Vishva Dixit’s laboratory, University of Michigan, Ann Arbor, 1996.
MD, Armed Forces Medical College, Pune, India, 1988.
What is your educational background? Were you always involved in mass spectrometry?
No. I got involved in mass spec part of things about six year’s ago when I joined Matthias Mann’s mass spec group, but I started out getting my MD at the Armed Forces Medical College in Pune, in India. So this is one of the top two med schools in India. And then I did my internship in India also.
But I felt that treating a small number of patients was not that appealing and I wanted to do something more global. There were way too many things that we didn’t understand — mechanisms, for example. I felt that we were treating people without really understanding too much. I felt I should learn molecular biology so we could get to the mechanism.
So I decided to do a PhD, even though there was no one in my family or circle of friends to guide me. It was just a concept in my head, because what I thought was even in medicine, you’re pretty much just following text books. You have no gut feelings — it’s what the experts in the field tell you — this works better than this, and therefore you use that. I said you know, these guys are researchers, so if I can do research, others will follow what I discover.
So to get on that side of things I came to the University of Michigan, and I did my PhD with Vishva Dixit. He’s a pioneer of apoptosis, and he was at the University of Michigan. Now he’s a vice president of oncology at Genentech. So I did my PhD under him. After that, I went to Boston and I finished a residency in pathology in Brigham and Women’s Hospital. After I finished that, I went to Harvey Lotish’s lab at the Whitehead Institute and I did my postdoc there.
While I was there I saw there were so many different postdocs in the lab doing different variations of signal transduction, but something was missing and I decided to go to Matthias Mann’s lab. He was initially at EMBL, but then he moved to the University of Southern Denmark.
I thought I would learn things in nine months, but it ended up being three years. And then I came back and two and a half years ago I started at Johns Hopkins.
What did you do during your first few years at Hopkins?
I felt that I was in a very unique position, so I brought back a lot of people who were either working with me or were collaborators from labs next door from Denmark to here. So in some ways, I had a running start.
In my own lab here, I have a chemist, mass spectrometrist, molecular biologist, biochemist and bioinformatician. We have spent a lot of time developing tools and techniques that now allow us to take a global view of pathways — signal transduction pathways, which is how I started out in my molecular biology world.
So we are still trying to develop detailed maps of tyrosine kinase signal transduction pathways, and to look at dynamics of those pathways. And one thing that is very essential for some of these things is when I was in Matthias Mann’s lab, I developed something called stable isotope labeling with amino acids in cell culture. We call it SILAC. It’s a way where you can use heavy amino acids and you can label all cellular proteins in a cell line that grows as cell culture. Then you can use this to distinguish labeled cells from non-labeled cells. You can mix them. And you can look at signal transduction pathways.
We are using this in many of the things that we are doing. We’ve also developed a website at www.silac.org to keep the community updated on the different papers, the different tweaks of the methods, who are the suppliers of the different reagents for the methods, because I think this is going to change the way we do biology. We still use cell culture-based models, and this is how we’re going to come closer to systems biology-type approaches.
What other things are you working on?
We have made this human protein reference database. Today, this database, I would like to say that it has already become the gold standard for data on human protein-protein interaction and post-translational modifications. There are over 20,000 interactions and more than 6,000 post-translational modifications, and what we’re doing is we’re taking the human interactome data and comparing it to two other two other proteome-wide study that were done recently and published — one in the worm and one in the fly.
So this is the interaction data. What we’ve also done is a bioinformatics analysis of all the phosphorylation sites that we have collected from the literature. So these are experimentally derived sites, and what we’ve done is our own experimental analysis to figure out — if we look at all the data out there, can we find new motifs that everyone has missed? So this is doing systems biology from the ground up.
And the answer is yes. We have found many new motifs, and now we are looking at what are the proteins that are not known to be phosphorylated that have these motifs. We don’t want to only do bioinformatics where we make predictions — we want to be part of the solution.
When did you establish the Institute of Bioinformatics in Bangalore?
So, when I was returning from Denmark and joining Hopkins, right around that time, it was started. Basically, as I was joining here, it started and now it’s been running for about two and a half years. We started with 15 or so people and today there’s 70 people. And this is at a time when most biotech companies that are engaged in bioinformatics are folding.
I think this a very new model. I think our idea is simple in that if you want to do bioinformatics connected to wet lab and you want give out data in the public field, and if your goal was not to make money, but to publish and contribute, life is easy. If your goal is to make money, well, everyone in the world is figuring it out — making money is not easy. We can do the science. I can drive the science and figure out what are the kinds of things that we want to do.
But I do not know how to make money, and the good news is I don’t want to make money. So in that way we have a much more sustainable model. Of course we have to try to worry about grants and things like that, but we really only need to worry about science and we want to be a systems biology type of institute. So that’s really what we are about.
Did you have the vision for a long time to start an institute in Bangalore?
No, not specifically. What happened was, my parents happened to be settled in Bangalore now. So it was just easy — Bangalore is also like the silicon city of India, so we could get people with all kinds of background. We could get software engineers, bioinformatics people, molecular biology people. So my vision was not specifically Bangalore no, and India no, but what I wanted was, for the kind of vision that I had, I needed a bigger team. And I knew that the resources that I would have in any conventional appointment, including the one at Hopkins, I wouldn’t get what I think I needed. So I said, ‘We’re going to do it like this.’ It’s a little unusual, but what can I say? If we just keep repeating what happened historically, I think we’re not going to move forward. I believe that there is no one standard model or 100 standard models. We can do something that is on the verge of being peculiar or weird and only time will tell who was right.
I think based on the progress we have made, it was not a bad decision. Two and a half years later we are running a non-profit institute and we have published so many papers together, and what is the most important thing is we have a lot of exciting things in the offering. This is what’s going to make people convinced that this is interesting and this is also viable.
What are some database projects that IOB is working on at the moment?
We are developing what I think will be a model for disease oriented databases and we are calling it Breast Cancer Database. It is really a database of all known molecular alterations in breast cancer. We’ve also developed a genome browser, where you go from a gene and you display transcriptome information, protein and pathway information, all in the context of a genome browser.
Is your focus for the future to develop well-curated databases?
That is one focus, and basically to lay a strong foundation for systems biology by working on building blocks — that is what I call curated databases. Also from the other end, being the actual users to analyze the data and continue with our global studies for signaling and protein complexes. We’re also doing small scale studies in the lab to figure out the functions of some of the molecules we find from the big experiments. From the IOB side, we’re starting a wet lab there to do high-throughput studies such as looking at protein families together.