Meet biology's next big intellectual challenge. It's called systems biology, and the discipline has begun to piece together the first detailed sketch of how cells process various biochemical signals, essential information that one day could push more molecular-based cancer treatments closer to reality.
In the last 5 years, universities and institutions such as Harvard and the Massachusetts Institute of Technology have created cross-disciplinary departments devoted to systems biology. New facilities such as Seattle's Institute for Systems Biology have formed with the discipline as their sole mission. So impressed is the National Cancer Institute with this initial work and the prospects of its eventual application in people that officials there recently launched the Integrative Cancer Biology Program to study cancer "as a complex biological system."
Although systems biologists have yet to leave their investigative mark on man or even mouse, they have generated a growing body of elegant research in more experimentally tractable model organisms such as yeast. But even as systems biology takes its first tentative steps, many traditional molecular biologists and biochemists have their doubts. They say the field remains long on speculation, short on analytical precision, and will be hard pressed to explain the subtle biochemical variations that distinguish tumors, one of the complex issues now facing cancer research.
Systems biologists see these assessments as points well taken. "The burden is on us," said Peter Sorger, Ph.D., who directs the systems biology program at MIT in Cambridge. "But I think the proof will be in the pudding, and it's not 5 years off. I think it will be in the next 2 to 3 years that we'll see the first examples emerge, where today's leaders of cancer research will actually say, Wow, that was pretty interesting. "
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Despite its revolutionary implications, systems biology remains more of a shared belief than a standard definition. The belief, in part, hinges on the availability of vast databases of biological information and the technical know-how to create detailed maps of proteinprotein interactions. These so-called interactomes are already being vigorously explored in yeast and other model organisms.
But more to the heart of systems biology, scientists in the field say the needed technology and computational power now exist to take the next necessary intellectual leap: defining the structural dynamics of the interactome. How do entire signaling pathways feed into dense 50- or 60-protein signaling networks with their complex cooperative inputs, outputs, and parallel processing? How do these networks sense, react, and keep our cells in working order?
Why go to all this trouble? As many systems biologists contend, biology stands at an intellectual crossroads. It has spent the last half century riding the experimental power of molecular biology to one breakthrough after the next. The problem, they say, is that molecular biology's focus on isolated genes and proteins misses the big picture. "A musical metaphor expresses it best: molecular biology could read the notes in the score, but it couldn't hear the music," the prominent microbiologist Carl Woese, Ph.D., of the University of Illinois at Urbana-Champaign, wrote last year in an essay calling for a "new biology."
To crack these songs of life, the field engages not only biologists of various advanced degrees but also engineers, computer scientists, mathematicians, and anyone else with a unique perspective on how these protein networks might work. Although their methodology continues to evolve, systems biologists generally are enabled by two things: databases of quantitative biological data, and mathematical or computational methods to model the qualitative dynamics of gene and/or protein networks contained in the data. As such, systems biology is hypothesis driven but highly iterative. Theoretical models are proposed, refined, and further tweaked on the computer screen, then tested experimentally in the laboratory.
Researchers also have adapted many concepts from systems theory to give context to the organization and behavior of the various components within the cell. These include concepts already common in biology, such as dynamics and feedback loops. But it also includes the somewhat controversial idea of emergent properties, which posits that the sum of the whole, e.g., a signaling network, generates a collective quality than none of the constituent parts alone possess.
Emergent properties in theory allow dense, hydra-like protein networks to rearrange their structure, adapt to change, and maintain their function. "The 21st century is the century of complexity," said Mihajlo Mesarovic, Ph.D., a systems biologist at Case Western Reserve University in Cleveland. "This is our challenge. Complexity is not a curse. It is our tool to understand the whole."
Culture Clash
Nowhere is the cultural divide between molecular and systems biologists more apparent than in their differing views of cell signaling pathways.
The broad consensus among molecular biologists is that these protein pathways exist to process the many external signals that arrive at the cell surface. According to this view, each signal binds to its appropriate receptor and prompts the appropriate pathway to initiate linked sets of sequential reactions that culminate in a cellular response.
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But many systems biologists say these pathways represent tiny components, or modules, of much larger protein networks. To focus on pathways in isolation, absent their greater network affiliation, they say would be "myopic," or a failure to see the forest for the trees. "I'd like to think of it as the cell integrates different processes at the same time," said Maya Said, Ph.D., a systems biology postdoc at MIT. "I think of it as processes as opposed to pathways."
Said and her colleagues reported in a study published recently in the Proceedings of the National Academy of Sciences that toxicity modulation in yeast leads to a ripple effect that impacts multiple processes and subprocesses at once. They also showed that toxicity-modulating networks have more hubs and protein complexes, which make them more interconnected and influential to cell behavior. "The traditional focus has been to pinpoint the one thing or sequence of events that go wrong to cause disease," she said. "But what if multiple things go wrong in the system at the same time? Then you miss the big picture studying pathways one by one."
Take the ras pathway. In the 1980s, scientists hailed it as the secret to understanding cancer. But today the pathway remains a puzzle, in part because the ras protein has so many faces. Or, as systems biologists contend, the faces reflect the fact that the protein functions as a circuit within its greater network. They point out that ras can act as a binary switch that senses the direction of information flow. But, because it is strategically located at the convergence and divergence of several pathways, it also has a hand in cell differentiation and apoptosis. Adding to the complexity are the various enzymes and phosphatases that help to regulate the ras circuit, each with its own web of molecular connections.
"The complexity of cellular networks is simply too overwhelming to employ any other strategy than a modular one to understand these networks," said Boris Kholodenko, Ph.D., a computational cell biologist at Thomas Jefferson University in Philadelphia.
Diverging Opinions
With such different biochemical worldviews, molecular and systems biologists may have to agree to disagree on some points. It's common knowledge, as Sorger noted in a recent opinion piece, that "the emergence of systems biology as a new discipline leaves many cell and molecular biologists unconvinced."
It's a point many in the more traditional disciplines readily echo when asked. "The broader concept of networks can in principle account for all aspects of biology," said Bert Vogelstein, M.D., oncology professor at Johns Hopkins University in Baltimore. "But it will be no easy task to understand the cell-type specificity associated with, for example, cancer cell mutations."
"In addition to the tremendous complexity of the human organism, many of the differences are likely to emanate from relatively small changes in biochemical parameters," he continued. "We cannot in general measure small changes of, for instance, 10% to 20% in gene expression, phosphorylation, and so on, and this will at some point limit the accuracy of network analyses, even if all of components of the network can be identified and linked."
For others, the heavy computation required to make systems biology work smacks of artificiality. "The cell of systems biology is like a reality show on TV," said Pontus Aspenstrom, Ph.D., a scientist at the Ludwig Institute for Cancer Research in Uppsala, Sweden. "Although we can sometimes mistake a TV show for a true representation of human behavior, we generally agree there is much more to life than what we see on Temptation Island or Big Brother. Systems biology can only work if we relate back to the cell, organism, or ecosystem. It is the behavior of our models that is complex, not necessarily the behavior of the cell."
Despite their reservations, those in the mainstream also seem to genuinely welcome the emergence of systems biology, even if they don't share all of its premises. "Both are true," said Vogelstein, referring to the need for molecular and systems biology in the 21st century. "We'll need new theories and models, as well as advances in molecular biology, to understand biological complexity."
For systems biologists, inclusive is the word. "One of the things that we say here at MIT is that we are not doing ourselves a favor if we give up the idea of mechanism in favor of the systems view," said Sorger. "We need to integrate the mechanistic view with the systems view."
As the field moves forward, systems biologists remain extremely drivenand confident. "I think systems biology will give us the most detailed, most accurate, and most high-resolution view of mechanism that we've ever had," Sorger said. "I also think it is going to be the fundamental advance necessary to make mechanism-based therapeutics work."
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