Over a half-century ago, the renowned (and eccentric)2 mathematician, Norbert Wiener, suggested that living organisms be viewed as systems governed by feedback control.3 Wiener attempted to found a new disciplineâ€”â€œcyberneticsâ€?â€”for the study of such systems. In spite of Wienerâ€™s impassioned proselytization on behalf of the new discipline, cybernetics didnâ€™t amount to much. It generated some excitement in the social sciences in the 1950s4 and then fizzled out. Engineers occasionally referred to cybernetic concepts (especially feedback) but thatâ€™s about it. In biology, especially in the emerging field of molecular biology, cybernetics proved to be a disaster.5 Strangely, at the beginning of the twenty-first century, Wienerâ€™s vision has returned with a vengeance.
The context of Wienerâ€™s return is the new â€œsystems biologyâ€? approach to the organism. â€œSince the days of Norbert Wiener,â€? argues Hiroaki Kitano, one of the proponents of the new approach, â€œsystem-level understanding has been a recurrent theme in biological science.â€?6 Kitano is partly right: ecosystem ecology, also going back to the 1950s, and large-scale studies of the immune system, starting in the 1960s, have both been important parts of biology even though Wienerâ€™s direct influence has been negligible. But, in the new molecular biology that has since come to dominate most of biological research, systems thinking was at best an irrelevant footnote. Research was dominated by a newly-resurgent reductionism, trying to explain wholes by constructing them out of smaller and smaller parts.7
Systems biologists reject reductionism8 even though the new approach emerged from the large-scale genome sequencing project which had taken reductionism to its limits within biology.9 Contrary to most expectations, the results of sequencing only showed how little functional biology could be read off from sequences alone.10 Consequently, the new field of genomics largely focused on developing better technologies to put sequences to some biological use besides fingerprinting and the reconstruction of phylogenies. But genomics remained saddled with the legacy of traditional molecular genetics in which the temporal sequence of events and processes within the cell remained beyond the reach of the methodologies. Proteomics was an important advance: its focus was on a dynamic changing feature of the organism, the protein complement of cells which changes in response to the environment. The emergence of proteomics marked a somewhat stunning retreat from the early days of sequencing projects when geneticists expected to predict phenotypes from DNA sequences alone.11 An old guard continues occasionally to defend that view12 but it is largely becoming irrelevant to modern biology.
Systems biology claims to be the culmination of these trends. Its aim is to study cells and larger units within organisms as composite systems described in terms of both the structures within them and the processes that occur in these structures.13 Some practitioners explicitly abandon reductionism to endorse philosophical doctrines such as emergence, according to which properties of wholes cannot be predicted or explained from the properties and organization of parts.14 Few philosophers who defend reductionism will accept emergence that easily, but the question can only be decided when the anti-reductionists have specific examples in which properties of composite systems have deep explanations but none in terms of their parts. It will be a while before systems biology models get to that stage.
Almost all advocates of systems biology endorse a collaborative technology-driven enterprise using rhetoric very similar to that of the ecosystem ecologists in the 1960s.15 Biologists, engineers, and computer scientists (among others) are supposed to collaborate to set up the necessary technological infrastructure to track all relevant processes within the cell and record the massive amounts of data that are produced. Integration at all levelsâ€”intellectual disciplines, conceptual framework, technology creation, and research cultureâ€”is critical to the success of the approach.
The most important innovation of the systems biology approach is its explicit reintroduction of considerations of time into molecular biology. One of the peculiar characteristics of molecular biology has been its avoidance of explicit reference to time: flows of information between nucleic acids, and from them to proteins, control of gene expression through negative feedback and switchesâ€”these mechanisms all replace explicit discussion of how the chemical composition of cells change over time. This is one of the salient features that makes molecular biology look so different from the biochemistry that preceded it. Systems biology seems to be returning to the older biochemical view, worrying about processes, and how they change over time, but with a radical expansion of scale. In systems biology, thousands of reactants are potentially tracked over time rather than the ten or so which were the limit of classical biochemistry. Systems biology presents a much more dynamic view of biology than traditional molecular biology or even genomics. It promises both conceptual and technological innovations. If it leads to a successful model of even a single cell, it will already have justified the massive spending of the genome sequencing projects.
Will the new approach succeed? Itâ€™s too early to tell. But it remains among the most interesting innovations in recent biology.
1 Â© 2005 Sahotra Sarkar.
2 Heims, S. J. 1980. John von Neumann and Norbert Wiener: From Mathematics to the Technologies of Life and Death. Cambridge, MA: MIT Press.
3 Wiener, N. 1948. Cybernetics. Cambridge, MA: MIT Press.
4 Heims, S. J. 1991. The Cybernetics Group. Cambridge, MA: MIT Press.
5 Sarkar, S. 1996. â€œBiological Information: A Skeptical Look at Some Central Dogmas of Molecular Biology.â€? In Sarkar, S. Ed. The Philosophy and History of Molecular Biology: New Perspectives. Dordrecht: Kluwer, pp. 187 -231.
6 Kitano, H. 2002. â€œSystems Biology: A Brief Overview.â€? Science 295: 1662 -1664.
7 Sarkar, S. 1998. Genetics and Reductionism. New York: Cambridge University Press.
8 Aderem, A. 2005. â€œSystems Biology: Its Practice and Challenges.â€? Cell 121: 511 -513.
9 Tauber, A. I. and Sarkar, S. 1992. â€œThe Human Genome Project: Has Blind Reductionism Gone Too Far?â€? Perspectives on Biology and Medicine 35(2): 220 -235.
10 Stephens, C. 1998. â€œBacterial Sporulation: A Question of Commitment?â€? Current Biology 8: R45 -R48.
11 Gilbert, W. 1992. â€œA Vision of the Grail.â€? In Kevles, D. J. and Hood, L. Eds. The Code of Codes. Cambridge, MA: Harvard University Press, pp. 83 -97.
12 Watson, J. D. 2003. â€œA Molecular Genetics Perspective.â€? In Plomin, R., DeFries, J. C., Craig, I. W., and McGuffin, P. Eds. Behavioral Genetics in the Postgenomic Era. Washington, DC: American Psychological Association, pp. xxi â€“xxii.
13 Ideker, T., Galitski, T., and Hood, L. 2001. â€œA New Approach to Decoding Life: Systems Biology.â€? Annual Review of Genomics and Human Genetics 2: 343 -372; Weston, A. D. and Hood, L. 2004. â€œSystems Biology, Proteomics, and the Future of Health Care: Towards Predictive, Preventative, and Personalized Medicine.â€? Journal of Proteome Research 3: 179 -196.
14 Aderem, A. 2005. â€œSystems Biology: Its Practice and Challenges.â€? Cell 121: 511 -513.
15 Golley, F. B. 1993. A History of the Ecosystem Concept in Ecology : More than the Sum of the Parts. New Haven: Yale University Press.