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B. Robert Franza on Systems Biology and the UW Cell Systems Initiative


At A Glance

Name: B. Robert Franza

Position: Research Professor, since 1996 and Director of Cell Systems Initiative, Bioengineering Department, University of Washington

Background: Scientific staff, Cold Spring Harbor Laboratory — 1982-1994; Medical resident, Dartmouth Medical School — 1979-1982; M.D., Georgetown University Medical School — 1975-1979

Tell me a little about your background and how you got started in this field?

My M.D. is from Georgetown University, and I was a publishing scientist before I went to Georgetown, and I published papers while I was at Georgetown. Then I continued doing science in my residency program for three years at Dartmouth, and then I spent 12 years on the scientific staff at Cold Spring Harbor Laboratory, where I worked extensively in the areas of quantitative analysis of cellular proteins for the purposes of understanding processes like the cell division cycle and the regulation of transcription. During that time I was involved in helping some commercial entities get started. After that, I was recruited to the University of Washington. Four years ago I founded a think tank within the bioengineering department — the UW Cell Systems Initiative (CSI) — that is focused on understanding information control systems in living cells, so all of what we do is focused on that task.

What spurred you to develop this think tank?

We decided in an academic setting to test a new model. We're a think tank that creates intellectual capital and moves that capital into commercial activities as quickly as possible. We're a think tank that creates more than reports. We gather experts around very difficult problems — the experts are very often not biologists — and we see if ideas and inventions occur. If they do, we evaluate whether a prototype should be developed within CSI or whether it should be developed elsewhere. In the four years that we've been in operation, we've been extensively involved in collaborations with Amnis Inc., which has developed a high-throughput multispectral flow imaging platform, and we've been involved in creating a procedural language for the biologist, which is now a product developed by a company that was spun out of CSI, called Teranode Corporation, and more recently we're in the final stages of protecting intellectual property and creating a commercial entity to carry forward a conceptual language that we've created for the biologist.

What motivates us is the fact that living systems are dense, organizational, dynamic entities. Understanding them is likely to stand waiting until we begin looking at that organization and those dynamics in the context of the living system.

We spend our time looking at methods for observing ever more dense information about the molecular events that are occurring in living cells. Since this is science, we realize we have to look at lots of those cells, because we have more than ample evidence that even if we have genetically identical cells, there is going to be phenotypic variation. That's one of the things that motivated us early on to work with Amnis.

What are the major technological challenges that need to be overcome in this field?

There are several significant challenges, two of which we faced right away. First, the biologist has not had an unambiguous representation of what it is they wanted to do in their observations, nor have they had an unambiguous representation of what they actually did. So the VLX Designer tool that used to be called Labscape, that Teranode now is delivering into the market, addresses that fundamental problem. As an analogy, if you look at electronic design automation as an industry, if you step back 25 years before that industry was created, and you ask yourself whether you could have ever built an integrated circuit with the complexity of the Pentium chip without the evolution of that type of approach to design and testing, the answer would be "No," you would have never gotten there.

And so we decided that walking into rooms or buildings with vast amounts of stuff on shelves, or Google searching across that type of stuff, is just not an adequate answer to this ever-expanding challenge of creating all kinds of data, and potential information and not being able to use it effectively. So we addressed that by creating this procedural language.

Similarly, we've been very concerned that the biologist has not had an adequate symbolic language for expressing the concepts, the things that they're thinking about when they're thinking about a cell or the interactions of molecules in that cell. We spent a lot of time creating a lot of software, as well as an alphabet, and a grammar, and a compiler to deal with that grammar, and that is what we refer to as Bioglyphics for the symbols, Balsa for the grammar-checking, graphical modeling and simulation environment. In the Balsa environment, the biologist uses the symbols to build compiled models, and it’s also integrated with a software suite we call SigTran, which enables you to simulate what you're thinking about. And so that integrated platform, which we first presented in a poster at the NIH digital biology meeting in 2003 in Bethesda, is now on its way to becoming a commercial entity.

It's very clear that we're going to have to observe at the level of molecular interaction, which is a very significant challenge, because those are occurring over distances over some tens of nanometers: we're going to have to deal with the organization and events that are occurring within cells while they're still alive. That poses major imaging challenges, major chemistry challenges, and major platform challenges.

We view things that are emerging under the rubric of nanotechnology, microfluidics, 3rd and 4th generation oligonucliotide chemistry, fluorescence resonance energy transfer and fluorescence speckle microscopy, we view all of these technologies as early steps to coming to grips with the fact that the universe of biology is the living cell, the organism. And we have ample evidence that the minute you break that thing open, it is no longer what it was. If you're going to understand things like metabolic or transcriptional regulation, or how it is that a genome effectively decides which portion of it is going to be open for business, we're going to have to do that work with the system intact. And much of the stuff that we've tried to infer from biochemistry has proven to be inadequate when we try to infer them into what's happening in the cell.

And so there's a whole slew of decades-long challenges facing us to do with the cell what our physicist colleagues have managed to do with their observations. One of the things that guided those efforts is the integration of computational simulation and their experimental design. We think that one of the issues in biology is creating pedagogy for the biologist very early in their training that is quantitative, that insures that the budding biologist is not afraid of using computational simulation to guide what it is you do. And the other trait that we consider the grandest challenge of all is learning how to work as a team. So those are the challenges that we see — they span everything from chemistry and optics to a fundamental shift in how we work with one another in the realm of biology.

Where do you see the field of systems biology going and what do you think about its commercial potential?

Well, here's this little tiny entity called the CSI, which has never had a core staff of larger than 11 people, we've been involved in two significant breakthrough technologies that are commercial, and we're about to nurture a third one, and that's with a tiny amount of funding and a very small staff. So I think the potential by taking a systems viewpoint of biology is large, both for the insights we will need to create, and all of those activities have commercial consequences. So everything from creating a new pedagogy for the young biologist all the way to new imaging platforms and new kinds of probes will eventuate into products and services we do not have now.

Throughout history, numerous thoughtful individuals have perceived the systems properties of anything that was alive, and they also perceived that they didn't have the tools to deal with it. Anywhere you want to look over the last 130 years or so, people were well aware of what it is they were going to have to step up to, and unfortunately they got a bit sidetracked. There's nothing wrong about reductionism, but you have to do it in context, and the context has to be "What is it that I'm reducing and how much am I destroying in the process, and how important is what I'm destroying to what I'm trying to understand" — that's the framework that needs to get reestablished.

I think the commercial potential in any realm of understanding is always large, if the thing you're trying to understand is complex and the consequences of understanding it are significant. So we're talking about understanding the cell, and that's the most complex thing anybody has stepped up to try to understand. The implications of understanding it better are that we find cancer way earlier, or we understand inflammatory disease processes way better, or we understand the context of many neurogenerative diseases.

What is next for your CSI group?

We have recognized in the Amnis’ imaging platform, an opportunity to do something even more novel — having large numbers of cells in discrete living environments and being able to do multispectral imaging over very large numbers of cells. And so we have things at the design stage with regards to the optics and the microfluidic environment, and the control systems software you would need to deal with that kind of observation space. We're very focused on advancing that front as well as advancing a new pedagogy for the young biologist. Of course the “old-timers” may want to take a look at those courses as well, but our focus is on the youngest individuals stepping up and wanting to know something about biology.

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