An Interview with Dr. Leroy Hood

by Bruce Stewart

The Human Genome project is widely considered the most revolutionary scientific achievement of modern times, and Dr. Leroy Hood was one of its first advocates and a key player in its success. He continues to lead the way in challenging traditional methods of scientific research, and he is now championing the new discipline of systems biology, which treats biology as an informational science and attempts to solve fundamental problems in biology and medicine by taking more of a big picture approach.

Dr. Hood started down this path when he created the cross-disciplinary Department of Molecular Biotechnology at the University of Washington, bringing together chemists, engineers, computer scientists, applied physicists, and biologists. He has recently expanded these efforts and moved them outside the walls of academia by creating the unique and independent Institute for Systems Biology in Seattle, Washington. We took him away from his busy schedule to discuss his work in systems biology, bioinformatics, and the ethical questions raised by the advance of predictive and preventative medicine.

Stewart: What is systems biology?

Hood: Systems biology is basically the ability to study complex biological systems looking at all genes or all proteins, in terms of perturbations and model organisms. It's studying systems by looking at all the elements in the system rather than looking at things one at a time. That's a simple explanation.

Stewart: What are some of the promising areas of application for systems biology?

Hood: It's absolutely global. That is any biological system that you're interested in can really be approached with these technologies. So at the Institute we're studying microbial organisms and how their systems for energy metabolism and things like that work. We're studying the immune response and how, for example, one can come to understand how different types of immune cells talk to one another so you can make them more efficiently generate vaccines. We're interested in taking a systems approach toward cancer, and we've studied prostate cancer for the last six or seven years using this approach and I think it's been remarkably revealing.

O'Reilly Bioinformatics Technology Conference

Dr. Hood will be delivering the closing keynote, on Integrative Systems Biology: Genomics, Proteomics, and Computation, at O'Reilly's upcoming Bioinformatics Technology Conference,.

We're interested in stem cell developments and again, using a systems approach to understand the multiplicity of choices that a stem cell makes in going down its pathway to differentiation. We're studying stem cells in the bone marrow, hematopoietic stem cells. We're also interested in applying systems approaches toward looking at issues of genetic predisposition to disease, and this will move us toward more of a predictive kind of medicine. And then ultimately, to take genes that predispose to disease, put them in the context of the systems in which they operate using the systems approaches, and learn how to circumvent whatever limitations they impose.

This is moving to the final phase, which is preventive medicine. That is you can actually design ways that will prevent people from getting the predispositions to which their genes have made them susceptible, if you can figure out how to circumvent whatever limitations those genes are causing. So there is a broad spectrum of different kinds of interest that we have.

Stewart: How is systems biology changing the face of biological research?

Hood: The revolution that systems biology has caused is really an interesting one because whereas when molecular biology arrived in the late '60s and early '70s, it was a paradigm change in biology that fit in nicely with both academic structures and funding structures. It was a discipline based on individual investigators and small laboratories, and it was all based on looking at genes and proteins one at a time.

The systems approach is really a striking contrast with that because if you're to take these more global analyses that systems approaches require it means two things: one, that you have to have the tools for looking globally at RNA and how it changes when you do perturbations, or protein and how it changes when you do perturbations, or complex cellular responses and how they change. So it means you have to have lots of technologies for sequencing DNA arrays, genotyping various aspects of proteomics, multiparameter cell sorting, single-cell assays, all of these kinds of things. It means that systems biology requires an infrastructure that is significantly greatly than what molecular biology, or biochemistry, or cell biology requires.

The second thing it requires, which is very unusual, is sophisticated computational technologies. Because if you're to acquire these global data sets, you have to have the tools for being able to capture and store them, and ultimately to display them, analyze them, and mathematically model them.

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Stewart: How does bioinformatics fit into systems biology?

Hood: The integration of bioinformatics with these systems approaches is an integral, essential feature. One of the things that we stress is that in the future it's going to be increasingly important for people in bioinformatics to be intimately associated with data producers, because no matter how smart you are you can't model biological complexity--it's just too complex. The only way we're going to understand it is through the integration of these global experimental observations, together with powerful computational tools for analysis, and ultimately, for modeling.

A mistake that a lot of people in bioinformatics have tended to make is thinking that you can set up a bioinformatics center and it can work in isolation from the biology, and it can study all these great databases and learn lots and lots about biology. In vitro biology and in silico biology are all popular terms, but it isn't true, and it isn't going to be true in the future.

This whole iterative process of systems biology means you do a global set of experiments, you model it, you find that theory and experiment don't quite jive so you have to do more experiments, and you have to change your model and it goes around and around in a continuous iterative kind of process. The people in computational biology that aren't very closely allied with data producers and those people who don't have the capacity to integrate experiments with their events are going to be left behind in the world of systems biology. Now, that doesn't mean you can't search genomes and find interesting things, or you can't search proteoms and find them, but if you want to understand the systems and how they work you're going to have to integrate biology with computation.

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