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Big-Picture Biotech

Systems biology aims to provide a clearer picture of how diseases work-and how to prevent them.
December 1, 2003

Laboratories at the Institute for Systems Biology sport magnificent views across the sailboat-cluttered waters of Lake Union, with the hilly downtown of Seattle as a backdrop. On this unusually sunny and warm June day, graced by an endless turquoise sky, the large windows provide an entrancing, even romantic, view. And it well suits the young institute, which has built itself around one of the grandest of biological visions.

Systems biology, one of the hottest fields to spring from the Human Genome Project, defies a simple description. It promises nothing less than to reshape the way that scientists think about how the human body works, providing clues to unraveling the complexities of illness and ultimately leading to new medicines to prevent and treat disease. But even the Institute for Systems Biology’s Web site prominently raises the question “What is systems biology?”, then offers an answer that fills six full screens of a computer monitor.

As the site struggles to explain, systems biology aspires to connect the dots of all of the body’s RNA, DNA, genes, proteins, cells, and tissues, elucidating how they interact with each other to create a breathing, blood-pumping, disease-fighting, food-processing, problem-solving human. “Systems biology is a holistic view of what’s going on,” says Alan Aderem, cofounder and director of the institute. It looks beyond the individual actors and tries to discover the script they are following, and that marks a radical shift for biology. “The focus for the last century has been on individual molecules,” says Marvin Cassman, executive director of the California Institute for Quantitative Biomedical Research, a fledgling systems biology program that joins researchers from the University of California schools at Berkeley, San Francisco, and Santa Cruz. “What’s been missing is an understanding of the way individual molecules operate together.”

Using this new approach, researchers have begun to address some of medicine’s most basic questions: Why do some people become gravely ill from an infectious agent that only causes mild disease in most? Will a clearer picture of how immune-system cells interact with each other guide the development of new vaccines? If scientists identify a defective gene, or an aberrant protein, can they correct it without doing harm somewhere else?

Scientists have dreamed about doing systems biology for decades, but explaining the workings of even a single cell has proved too daunting. Now a confluence of developments has fundamentally altered biology. An explosion of blazingly fast, highly automated machines has enabled the analysis of biological molecules in a fraction of the time it took a mere five years ago. Similarly, the torrent of new information from the Human Genome Project and related projects that comprehensively examine entire families of such molecules has presented scientists with dizzying new “parts lists” for humans. Add in the ever increasing computational muscle of today’s computers, and the systems biology approach that once seemed implausible becomes not only possible but also necessary to make sense of it all.

The formation of the Institute for Systems Biology four years ago fanned the flames, with a dozen universities and biotech firms subsequently announcing new interdisciplinary programs with a systems biology bent (see table “Other Systems-Biology Hubs). But the Seattle institute remains the highest-profile player, in part because of its founders’ combination of scientific expertise and machine-making prowess. It helps, too, that one of the cofounders, Leroy Hood, has something akin to celebrity status.

In the mid-1980s, Hood became famous in the biotech community when his lab at Caltech developed the automated DNA sequencer, a machine that made the Human Genome Project possible and helped to reconfigure biology. With support from Microsoft’s Bill Gates, Hood in 1992 came to the University of Washington and started an interdisciplinary molecular biotechnology program. The program planted the seeds of systems biology, but by 1999, Hood had become frustrated with the limitations of academia, and he decided with two other researchers at the school, Aderem and Ruedi Aebersold, to start the Institute for Systems Biology. “In the end, we decided we needed more freedom, and that’s why we took this pretty drastic step,” says Hood. Aderem came to systems biology through a less obvious route and with a more pragmatic motivation. A pioneering immunologist, he had earned a sterling scientific reputation for his work on a single family of proteins. Still, he says, “At the end of 10 years, I was tired and realized I wouldn’t live long enough to get any real understanding of a system if I was going to do it one by one.”

Despite the excitement it inspires, systems biology remains very much in its infancy. The institute has so far churned out papers that begin to establish the virtues of the approach with arcane biological systems like yeast and sea urchins. But at the institute’s core are far more ambitious programs in cancer, heart disease, infectious diseases, autoimmunity, and inflammation. And as they make the leap from relatively simple models to critical human problems, Aderem and his colleagues believe that their work will move medicine toward an era in which our life spans increase by 10 to 30 years. That’s a terrifically bold claim. But a closer look at what Aderem and others at the institute have begun to explore shows it may be more than just a daydream inspired by the splendid view.

Other Systems-Biology Hubs Institution/Company Strategy Beyond Genomics (Waltham, MA) Startup will use proprietary informatics technology to research new medicines for heart disease, central-nervous-system problems, and cancer California Institute for Quantitative Biomedical Research (University of California at Berkeley, San Francisco, and Santa Cruz) A cross-campus effort will link biology, computer science, and engineering in a multidisciplinary systems approach Computational and Systems Biology Initiative (MIT, Cambridge, MA) About 40 researchers from 10 disciplines will collaborate on cell death, toxicology, biochemical networks, models, tissues on a chip, and synthetic biology Department of Systems Biology
(Harvard Medical School, Boston, MA) More than 20 faculty from biology, physics, computer science, and engineering will study networks of cells and organs to identify new approaches to treatment Ingenuity Systems (Mountain View, CA) Startup will use its proprietary “pathways analysis” software and database to speed drug R&D Lewis-Sigler Institute for Integrative Genomics (Princeton University, Princeton, NJ) Up to 15 interdisciplinary research groups will conduct basic research on the systems that control cell growth, neural circuits, synthesis of carbohydrates, and protein-protein interactions Life Sciences Institute (University of Michigan, Ann Arbor, MI) Up to 30 research teams will collaborate on projects that emphasize the networks that genes and proteins in a cell use to sense and adapt to stimuli Merrimack Pharmaceuticals
(Cambridge, MA) Biotech firm will exploit “network biology” to find new drugs for cancer and autoimmune diseases Okinawa Institute of Science and Technology (Onna Village, Okinawa, Japan) New graduate university now being planned will emphasize integrative research in biosystems

Testing Ground

A native of South Africa who spent five years under house arrest for actively opposing apartheid, Aderem grows animated as he leads a tour of the institute’s 6,000-square-meter lab complex, thrilling as much to the scientists themselves as to the facility’s wealth of new equipment. In his baggy shorts, he looks like a safari guide as he points out a man and woman together at a microscope. “She’s a cardiologist working with a physicist,” he says. Aderem’s lab also includes a mathematician and an engineer, in addition to the more usual assortment of biology and medical specialists. “My job is to integrate everybody,” he says.

This integration of different scientific perspectives and different types of data is key to puzzling out the complexity of a network like the immune system, which is responsible for the body’s exquisitely orchestrated response to microbial attack. And even with a diverse team in place, Aderem is starting with a small part of the puzzle: the various cells that make up the so-called innate immune system, the body’s first line of defense. Innate immune cells are somewhat dimwitted; they have no memory and have trouble making fine distinctions between microbes. (In contrast, the acquired immune system, which includes antibodies and more troops of cells, remembers how to recognize and destroy every invader it meets.) But the innate system plays an essential role in keeping people healthy by destroying some intruders and by shuttling others to the acquired immune system.

Because it is a relatively simple network, innate immunity makes an excellent testing ground for systems biology. In January 2003, the National Institute of Allergy and Infectious Diseases awarded a $24 million grant to the Institute for Systems Biology, Rockefeller University, and the Scripps Research Institute in La Jolla, CA, to create an “encyclopedia” of the innate immune system. Using the tools of systems biology, the researchers have started to catalogue precisely how the network reacts to microbial attack, exploring specific biochemical pathways and behaviors of genes and proteins. Compared to acquired immunity, “the players are much more well defined in innate immunity. And it will be possible to ask how important they are in the various pathways,” says Richard Ulevitch, chair of immunology at the Scripps Research Institute and head of the encyclopedia project. Aderem, for instance, has long focused on one particular innate immune player, a type of white blood cell called a macrophage. “The macrophage really opens up a whole window” on systems biology, Hood says.

An early test of the macrophage-centric approach came after an unlikely event: death at a Dutch flower show. In February 1999, an annual flower show in the Netherlands attracted 77,061 visitors. Of these, 178 developed Legionnaire’s disease, as did 10 exhibitors. Caused by a bacterium, Legionnaire’s disease leads to severe pneumonia, which in this outbreak killed 21 people. Dutch scientists quickly identified the likely source of the infection: a contaminated whirlpool spa on exhibit. But the outbreak raised a question that Aderem and his team thought they could help answer: why had these 188 people developed severe cases of Legionnaire’s disease, while others who paused at the whirlpool exhibit had not? Aderem was certain it was not simply bad luck.

When a bug like Legionella pneumophila infects a person, the cellular sentinels of the innate immune system sample it and carry off pieces of it to alert the acquired immune system. That sounds simple enough, but it’s actually an intricate, tangled drama that cries out for a systems biology approach. It turns out, for instance, that innate immune cells aren’t quite as mindless as was once thought. Proteins called toll-like receptors, which stud the surfaces of macrophages, allow them to detect, at least on a crude level, differences between microbes. Since the discovery of the first toll-like receptor in 1997, Aderem’s group has played a major role in describing how macrophages use the molecules to distinguish a virus from, say, a bacterium. “There’s a bar code on the membranes of microbes that the toll-like receptors can read,” says Aderem. Thanks to these bar codes, different microbes prod different toll-like receptors into action, which in turn triggers different biochemical cascades that can activate or suppress genes, cause or prevent inflammation, and steer the eventual response by the acquired immune system. If that seems complex, factor in that researchers have so far found 10 different toll-like receptors, and that the proteins work in concert. For example, three different receptors together recognize the category of bacteria that includes Legionella pneumophila.

Aderem’s lab at the institute began its study of the Legionnaire’s outbreak by hunting through thousands of blood samples to find mutated versions of one of the receptors. The task required sorting through millions of blood cells to pluck out minute variations in the billions of DNA letters that make up each person’s genome. To aid in this search, the team turned to a myriad of souped-up lab machines, many modified in-house to more quickly collect the massive amounts of data that a systems-level approach requires. Cell-sorting machines, for example, typically deposit cells on plastic plates that have 96 wells each. But the institute’s sorter operates so quickly that the researchers devised a new contraption to collect the cells: a long strip of wells that spools continuously off of a reel and through the sorter.

In all, the researchers found four mutations of the targeted receptor. They then studied the DNA of people who had stopped at the contaminated whirlpool-both those who got sick and those who did not. “This was a blessed study, because we had the controls,” says Aderem. Using more high-throughput tools, they hunted through the DNA samples for the mutations they had earlier identified. By comparing the gene patterns of the people who developed Legionnaire’s disease and the healthy controls, they discovered that a mutant version of the receptor tripled a person’s risk of getting sick. The speed with which the researchers were able to make the discovery illustrates the power of the Institute for Systems Biology’s strategy. “If I had been in a genetics lab where everything was set up, I assume it would have taken many months, if not years,” says Aderem. “Here, it took not more than one week.” And in uncovering the mutation and linking it to a heightened risk of contracting Legionnaire’s disease, they had taken a small but important step toward understanding how individual receptors and other molecules interact within the innate immune system to dramatically affect human health.

Working with pediatrician David Speert of the University of British Columbia in Vancouver, Aderem and his team hope to expand that understanding. Speert is investigating several more “experiments of nature” similar to the Netherlands flower show, with the aim of explaining how innate immunity can determine whether children get sick from infections such as tuberculosis and E. coli. “With every infectious disease, most people who are exposed do not become sick,” says Speert. “We’re trying to figure out what’s different about the small percentage who get sick.” Young children provide an interesting study population, he notes, because they often have not seen a particular infectious agent before and have no acquired immunity to confuse analyses of the innate system. For similar reasons, the young have the most to gain from new therapies, and unraveling how harmful microbes interact with the innate immune system could speed the development of new antimicrobial drugs and vaccines.

Connecting the Dots

In many ways, biology is becoming a numbers game. The human genome contains more than three billion DNA letters, representing some 40,000 genes, which actually encode untold billions of proteins, thanks to a complicated system of enzymes that slice, dice, and otherwise modify proteins as they’re made. Detailed information on all these players, and on their counterparts in other organisms, is filling gargantuan databases around the world. The job of the Institute for Systems Biology is to draw connections between the data its researchers accumulate and all of the information they can scrounge from these databases and the scientific literature. It is a breathtakingly ambitious mission, marked by huge challenges in the gathering, storing, and crunching of data, so the institute has coupled its state-of-the-art computers via extremely high-bandwidth connections to machines at a supercomputing center in Fairbanks, AK, that has the capacity to store more than 300 terabytes of information.

One homemade software program called Cytoscape helps the researchers make sense of the data. Developed collaboratively by the Institute for Systems Biology, the Whitehead Institute for Biomedical Research in Cambridge, MA, and New York’s Memorial Sloan-Kettering Cancer Center, Cytoscape creates visual representations of systems. To the untrained eye, the program’s collection of circles connected by lines to other circles looks like some hugely complicated engineering chart that spells out the production process at a manufacturing plant. But Aderem emphasizes that without Cytoscape, the researchers would be lost. “Humans can extract huge amounts of data, but no human can juggle more than 20 parameters,” says Aderem. “By visualization, though, they can do 100,000 parameters or more.”

Sitting at his computer, Aderem opens a Cytoscape representation of yeast metabolism. Although yeast metabolism offers an exceedingly simplified model of human metabolism, the same rules that control a single-celled fungus inform how the trillions of cells in a person operate. Each circle in Cytoscape, known as a node, represents a gene or protein. “If you perturb the nodes, that will result in large changes,” Aderem notes. For humans, he says, “these are obvious drug targets.” The visualization of the system also allows scientists to predict a medicine’s side effects: if a drug interferes with a specific protein, Cytoscape shows researchers how that might have a negative effect on a connected pathway that controls such critical functions as respiration or metabolism of sugar. “This would take 15 years and billions of dollars to see in the terms of standard drug development,” says Aderem.

Indeed, researchers typically spend years studying a drug in laboratory and animal experiments before moving it into cumbersome, expensive human trials, which often fail because surprising side effects suddenly surface. Such failures can cost pharmaceutical companies hundreds of millions of dollars and patients their lives. But with a detailed map of the systems that go haywire during bad drug reactions, drug companies might one day be able to substitute a quick computer analysis for many of those costly experiments.

Dream Machine

Just as systems biology aggressively strives to piece together biological networks, the Institute for Systems Biology has pieced together networks of leading scientists. And in perhaps the most intriguing joint effort to date, called the NanoSystems Biology Alliance, the institute is collaborating with leading nanotechnologists at Caltech and medical researchers at the University of California, Los Angeles. The goal is to squeeze many of the highly automated processes used in systems biology onto a one-square-centimeter silicon chip. If the NanoSystems group delivers on its promise, it will create a “nanolab,” a chip that will have the power to outperform entire laboratories. In that systems biology is an approach that prizes technology that is smaller, cheaper, and faster, the nanolab is a dream machine. “It has the possibility of utterly revolutionizing systems biology,” says Hood.

The researchers hope that, given just one drop of blood, the nanolab will separate thousands of cells from each other and, as Aderem says, “interrogate them individually.” The soul of the new machine is an intricate network of microfluidic channels, developed by Caltech physicist Stephen Quake, that range from five to 100 micrometers wide. After being treated with labels that mark specific cell types, the blood sample enters these nanopipes, which can sort, say, macrophages from other white blood cells. Another series of nanopipes equipped with tiny detectors can then identify and separate into various channels the different proteins secreted by the macrophage.

Caltech chemist James Heath has designed one of these detection systems, an array of nanowires that he coats with molecular “hooks” to fish for proteins. Each wire, which measures a mere eight nanometers in diameter, can hook a different prey. Heath is designing the system so that only one nanowire is “live” at a time, endowing the nanolab with such exquisite sensitivity that, currently, a sample need contain only 50 to 500 molecules of a specific protein for the nanowires to detect its presence. In the future, the hooks will also be able to snare specific sequences of DNA. Meanwhile, Caltech physicist Michael Roukes and his group are making nanocantilevers that can detect protein-protein interactions, the critical interplays that determine many of the biological events in the body. Roukes attaches protein receptors to the tips of the nanocantilevers. When a specific protein binds to a receptor, it causes a tiny movement, which induces an electrical impulse that indicates both that a protein-protein dalliance has occurred and the strength of the interaction.

The alliance hopes to move the nanolab into clinical applications by working with two researchers at UCLA: Michael Phelps, who invented the positron emission tomography scan, and oncologist Charles Sawyer, a leading expert in prostate cancer. But Aderem stresses that the nanolab project remains in its infancy. “If we get this functioning in 10 years, I’d be delighted,” he says.

It takes a leap of faith to think that a decade from now, a nanolab will be able to decipher from a single drop of blood what Aderem calls “the molecular fingerprint of a cell,” and that this information will tie into a systems biology database that will give drugmakers and clinicians a dramatically improved ability to help people live healthier, longer lives. But great accomplishments begin with great visions, and this one has spectacular technologies behind it, the likes of which biomedicine has never seen. “When I first got into this, I felt the same way I did when we originally cloned genes,” Aderem says. “My god. The power.’”

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