Founded in 2000 by well-known scientists who defected from their academic posts at the nearby University of Washington, the Institute for Systems Biology laid the groundwork for academic and for-profit organizations alike to buy into the nascent concept of large-scale biology.
And buy in they did: institutes for high-throughput, systems-level science have flourished around the world. "I think as a field we have done very, very well given that it has been less than 10 years," says Alan Aderem, who co-founded ISB with Ruedi Aebersold and Lee Hood in 2000. "All of us had a very strong feeling that we needed to find a way to use the information that was embedded within the genome."
They also knew that collaboration would be key to the success of the institute. Hampered by the disciplinary boundaries at the university, they founded ISB on several guiding principles, including collaboration and a focus on systems research. The idea — relatively new at the time — was that researchers who were encouraged to collaborate across disciplines could truly leverage their expertise to study complex systems. "We established the ISB as this very broad interdisciplinary scientific place, ranging from hardcore theoretical mathematicians to physicists, chemists, biologists, physicians, ecologists, the whole spread," Aderem says.
At the time, the founders decided that it should be a private, nonprofit research organization unaffiliated with any academic institution. "We wanted to place the ISB halfway between academia and biotech, hoping to capture the advantages of both and the disadvantages of neither," Aderem says. The major advantage of academia is that you don’t have to answer to shareholders while the draw of biotech is teamwork — "a kiss of death in an academic environment," he adds.
Despite eschewing the traditional academic mindset, ISB incorporates structure by having faculty groups and senior researchers. Their -research runs the gamut, but uses model organisms as well as having a translational focus. Lee Hood’s espousal of the four P’s — predictive, preventive, personalized, and -participatory medicine — is a driving force behind many of the tools and technologies ISB scientists hope to develop.
To that end, ISB scientists are studying blood biomarkers for type I diabetes, breast cancer, and prostate cancer. The ISB also pioneers the development of new technologies, one of the most talked about being microfluidics for examining single cells. "Our model is that biology drives technology and technology enables biology," Aderem says.
Under the hood
Aderem takes a strong translational focus in his lab, which primarily studies infectious diseases such as HIV and influenza, and also seeks biomarkers for atherosclerosis. In particular, Aderem is using systems biology to find biomarkers, such as antibodies, that definitively signal whether someone is immune to a particular pathogen. "Systems biology, I think, can result in rational vaccine design," he says. "You can figure out when a person is becoming immune to a specific pathogen and what the mechanisms are." To do this, he studies the networks within immune cells and determines how to reprogram them with proteomic and genomic approaches.
Nitin Baliga also takes a system-wide look at networks in his research, focusing on microbial systems and their responses to diverse environments. After collecting a range of molecular responses, like gene expression, protein, and metabolite levels as well as protein interaction data, he constructs global gene and protein response networks. "The goal is to take all of these global measurements and to integrate them in a meaningful way in a statistical framework that allows you to then construct the model of the cellular response that you’re studying," he says. "In doing so, you can test or refute some of the original understanding that you had, and gain new insights."
Creating useful molecular networks is a common goal among Baliga’s research projects. In one, he’s studying how the extremophile Halobacterium salinarum responds to oxidative stress, specifically system-wide responses for detoxifying reactive oxygen species. In another, he monitors how abnormal levels of certain metal ions can cause disease. "The heart of the problem is, what are the mechanisms that identify and distinguish between metal ions," he says, "and what ways do these mechanisms crosstalk with one another?" Identifying networks also helps him to associate genes with one another. "These types of functional associations are difficult to get when you have a very focused approach," Baliga says.
Ilya Shmulevich is using a computational approach to incorporate all this research data from experiments like Baliga’s into comprehensive maps. "We model everything from small molecular circuits — several genes or proteins — all the way up to large-scale circuits involving hundreds or even thousands of nodes," he says. Two areas that he specifically focuses on are innate immunity and cancer, and recently he’s begun incorporating microRNA data into his analyses. "We’re basically putting all of those data together to make sense of biological systems and how they operate — how they function and also how they dysfunction in disease. A major effort in our group is integrating all of these heterogeneous types of data and building predictive models of biomolecular networks in cells," Shmulevich says.
Shmulevich’s team applied such data to develop an algorithm to distinguish between two different types of cancer. In collaboration with MD Anderson Cancer Center, his group used cancer data sets to derive a classifying algorithm that uses a subset of genes to distinguish between two subtypes of sarcoma, gastrointestinal stromal tumor and leiomeiosarcoma. "[They] are really difficult to distinguish using traditional pathological assays," Shmulevich says, adding that MD Anderson doctors are already using the real-time PCR test on patient samples.
The big picture
Collaboration is a critical aspect at ISB, and it is encouraged among its faculty and with outside researchers and companies. ISB draws its faculty from a wide range of disciplines and its open-lab model has become a standard for many other systems biology centers. Baliga says that it’s easy to collaborate, but finding a standard vocabulary that cuts across different scientific disciplines is still a work in progress. "The biggest fear that people have sometimes is appearing as morons when they cross disciplinary lines," he says. "[It’s] a two-way street. Once you get past this fear of communication, and you gain respect for the resources that other disciplines have to offer, you can approach other people, and you have the patience" to understand each other.
In terms of translational research, Aderem sees systems biology playing a bigger role in reducing the time it takes to screen for drug targets and synthesize drugs as well as to find its niche in the study of infectious diseases and immunity.
It’s also going to continue to drive functional biology. "We’ve gone from the genetics of a few molecules to genomic analysis and global modeling, and now we’re going back to the drawing board to couple the global analysis back to the detailed few-gene models," Baliga says. "It’s just only recently that I’ve [begun] to fully appreciate how the whole process comes together." N
Institute for Systems Biology
Co-founders: Alan Aderem, Ruedi Aebersold, and Leroy Hood
Size: ISB is housed in a 65,000-square-foot facility with an open-lab model.
Staff: About 300
Funding: Initial funding came from philanthropic donations and NIH grant funding. Recently, ISB received $100 million from the government of
Luxembourg to focus on systems genetics and disease biomarkers.
Focus: ISB faculty span many scientific disciplines and their work focuses on both basic and translational system-wide analysis using model organisms. Other key areas are technology development and realizing the goals of predictive, preventive, personalized medicine.
Facilities: ISB has DNA sequencing, microarray, genotyping, proteomics, and cell sorting core facilities. A new facility for microfluidics and molecular imaging is under development. ISB also has high-performance computational resources and support for data storage, management, and analysis.