When the Human Proteome Organization begins its meeting in Beijing on Oct. 25, pioneer proteomics scientist Ruedi Aebersold will not be there. Instead, Aebersold, a co-founder of the Institute for Systems Biology, will be heading to Zurich where he will create an interdisciplinary "faculty cluster" focused on systems biology at the Swiss Federal Institute of Technology Zurich (ETH Zurich). Aebersold will remain at ISB in Seattle full time into 2006 and will then transition to full-time professor of systems biology at ETH while retaining his faculty position with ISB.
BioCommerce Week spoke to Aebersold in August to learn about his move to Europe and his vision for systems biology in Europe.
You are one of the co-founders of the Institute of Systems Biology. Are you figuratively ‘taking the franchise to Europe?’ Is this globalization of the Institute of Systems Biology?
Yes. It is a big move. A lot of things came together, and it certainly in no way reflects on the Institute for Systems Biology. It was a simply a unique opportunity that was presented to me. I am from Switzerland and I have been living in the US for 20 years now. Our kids have grown up and the youngest just left high school and is starting college. We said we wouldn't move until our kids are in college. This opportunity is very good, and the timing a good match. The opportunity is to build up a significant initiative in systems biology. There is a lot of support behind it. Like many countries in Europe, Switzerland missed out largely on the genomics revolution, the sequencing part of it. Most European countries, except for England, really weren't participants and they want to change that.
As genomics science moves into the area of figuring out what the information actually encoded in the genome actually means, and how this digital information translates into physiological function, [Europe] wants to be a part of this type of research.
Perhaps it was the scientific culture that was behind these European states not participating in the human genome project. Has anything changed?
Clearly, this type of science requires a deconstruction of culture, of how research groups are built. I would have certainly not decided to go there if I had not noticed that there is a cultural and structural change. I am convinced that, in this institution that I'm going to join, this change has happened. But, I'm much less optimistic about other institutions in the US and Europe, too.
How about support and funding, the bigger picture in Europe?
The Sixth Framework program is quite heavily slated towards biological research. I don't particularly think that the way it is implemented, the programs that they have, are particularly good programs, structurally. The focus on the scientific programs that they want to advance [is] excellent and tightly aligned with systems biology. How they go about funding these in my mind is not a very good idea. They asked applicants to constitute very large groups, on the order of 15 groups, to form a very large conglomerate that then applies for funding and that these 15 groups have to be spread out over a very large geographic area.
So, these efforts lack proximity?
One of the things that we learned here is really how important proximity is. Geographically, here [Seattle] it's not a big distance from the medical school to the computer science department — may be a seven-minute walk — but that is enough of a distance to represent a substantial hurdle. We learned here how important it is that we run into each other and that you have different disciplines in the same building. Having 15 groups spread out over 10 countries with 10 languages is not particularly promising.
What are your research goals?
Basically, my laboratory is a technology laboratory. The research goal we have, particularly in the proteomics field, is to develop proteomic technologies, to apply them in a broad range of biological and clinical research questions at very robust and very high-throughput levels to drive utility. One of the themes of the ISB is to very early provide early detection for diagnosing and preventing disease.
Is mass spec technology developed to the level where it can enable that?
It's a key technology and it has not been fully developed. I think the machines themselves are quite sophisticated and well developed. I'm not saying at all that we don't welcome further advances in terms of sensitivity and robustness. It's not the actual machines that are the bottleneck, it's how we implement the machines in a workflow to yield the best results. We take the instrumentation that is available to us and we want to get better performance and better data out by optimizing what comes out.
What are technologies that can be developed to get to this systems biology view?
Generally, what we need to achieve is obviously robust, good quality data. Since systems biology is essentially genomic science, we need to have throughput and analytical depth to do really global or comprehensive measurements of every single element of that type. So in the case of expression arrays, it's measuring every type of messenger RNA; in metabolites, you want to detect proteins to very low-abundance levels. You would like to do measurements of proteins in the whole diversity of modifications and splice forms. That's an enormous challenge. We need to get the technology to the stage where these measurements can be made. Expression arrays are probably very close. In proteomics, it's a long way away.
Another area where a lot of advancement can take place is happening and it's being pioneered by the expression array community. There are a large number of research groups, academic and industrial and private sector, that collect data. The overall whole combination of the data tells us a lot about biology. So if every laboratory does their 10 expression array measurements and looks at these 10 patterns, and the next researcher looks at another 10 measurements, and the next one looks at maybe 50. The significance of the technology is way, way undersold. There is a huge benefit to be able to compare data over laboratories that applies a particular technology. How can this be achieved? The naïve view is to say make the data all public. That is an important component, but that is by no means sufficient. Comparing data is only useful if you compare apples to apples. You need to have to have formats that can talk to each other, you need quality control of the data, and some form of numerical value associated with the data that tells you how good the data is, so that you are comparing like with like. It's been achieved in expression, but not in proteomics and metabolomics.
Who are the people you are thinking about hiring?
The group I'm building up there consists of three areas — biology, so we're hiring biologists. Also, technology development and data collection, so we're hiring senior mass spectrometrists; and the third component is data management and analysis. There, we have hired senior bioinformaticists.
What is emerging in Zurich is a cluster of a number of faculty positions that are going to be filled in the next year or two. They are going to be filled thematically around the systems-biology strategy.
What are your thoughts on the commercialization of systems biology technologies?
There have already been attempts to start companies on the systems-biology concept, and, earlier on expression-array technologies or proteomics. These companies, by and large, have not done all that well. I have come to the conclusion that it is a bad idea to start a company based on a temporary technological advantage. There is no guarantee that you can maintain that technological edge.