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ScienceWeek
THEORETICAL BIOLOGY: ON COMPUTATIONAL AND SYSTEMS BIOLOGY
The following points are made by Albert Goldbeter (Current Biology 2004 14:R601):
1) Systems biology, computational biology, integrative biology --many names are being used to describe an emerging field that is characterized by the application of quantitative theoretical methods and a tendency to take a global view of problems in biology. This field is not entirely novel, but what is clear and significant is that the life sciences community recognizes its increasing importance. This is the really new aspect: many experimentalists are beginning to accept the view that theoretical models and computer simulations can be useful to address the dynamic behavior of complex regulatory networks in biological systems.
2) Theoretical or mathematical biology has existed for many decades, as attested by the journals that carry these terms as part of their names. Until recently, however, these journals were outside of the mainstream and largely ignored by the majority of molecular and cell biologists. As the attitude to theoretical approaches in biology is shifting, it is not surprising to see their revival under new names, if only because a change in name is often needed to focus attention. After all, even at the cellular level, many sensory systems are built to respond to changes in stimulus intensity and adapt to constant signals.
3) The hype that currently surrounds computational and systems biology has the beneficial consequences of triggering further interest and creating a momentum for new opportunities, but it also carries some dangers [1], in particular that of making the field appear merely a fashion. The French stylist Coco Chanel once said la mode, c'est ce qui se demode - fashion is what comes out of fashion . In the view of the author, this does not apply to computational approaches to biological dynamics, which are here to stay.
4) Regarding the surge of interest in theoretical approaches to biology it is natural to ask: why now? One triggering factor is undoubtedly the completion of genome projects for a number of species and realization that the sequences alone cannot tell us how cells and organisms function. Understanding dynamic cellular behavior and making sense of the data that are accumulating at an ever increasing pace requires the study of protein and gene regulatory networks. This network approach naturally encourages one to take a more integrative view of the cell and, at an even higher level, of the whole organism.
5) Quantitative models show that certain types of biological behavior occur only in precise conditions, within a domain bounded by critical parameter values. This can contrast with the intuitive expectations from simple verbal descriptions. This is well illustrated by cellular rhythms [2,3]. Thus, cytosolic Ca2+ oscillations are triggered in various types of cell by treatment with a hormone or neurotransmitter. But repetitive Ca2+ spiking only occurs in a range of stimulation bounded by two critical values: below and above this range, the intracellular Ca2+ concentration reaches a low or a high steady-state level, respectively. Another example is the well-known generation of oscillations in models based on negative feedback. It is straightforward to explain in words why oscillations can readily be generated by negative feedback; but this verbal explanation largely misses the point, as it fails to explain why oscillations only occur in precise conditions, which critically affect both the degree of cooperativity of repression and the delay in the negative feedback loop.(2-5)
References (abridged):
1. North, G. (2003). Biophysics and the place of theory in biology. Curr. Biol. 13, R719-R720
2. Goldbeter, A. (1996). Biochemical Oscillations and Cellular Rhythms. (Cambridge, UK: Cambridge Univ. Press)
3. Goldbeter, A. (2002). Computational approaches to cellular rhythms. Nature 420, 238-245
4. Thomas, R. and d'Ari, R. (1990). Biological Feedback. (Boca Raton, FL: CRC Press)
5. Pomerening, J.R., Sontag, E.D., and Ferrell, J.E.Jr. (2003). Building a cell cycle oscillator: hysteresis and bistability in the activation of Cdc2. Nat. Cell Biol. 5, 346-351
Current Biology http://www.current-biology.com
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THEORETICAL BIOLOGY: ON BIOLOGICAL ANALYSIS
The following points are made by Eors Szathmary (Current Biology 2004 14:R145):
1) Billions of years of evolution have produced organisms of stunning diversity. Some of these are relatively simple, like the bacteria; others show impressive complexity. For two decades, the author has worked on a theoretical reconstruction and understanding of the major transitions that generated the levels of biological organization that we see today. Although many in biology have an antipathy to mathematics, the author "simply cannot live without it." A large part of his research consists of making models of intermediate stages of organization and the evolutionary transitions between them.
2) Although theoretical biology is avoided by many biologists because of their formulae phobia, theoretical biology is not necessarily mathematical, at least not when important ideas and concepts are conceived for the first time. The theory of Charles Darwin (1809-1882), as he presented it, was not mathematical (although later he commented that his reluctance to embrace mathematics was foolish, as mathematically minded persons seem to have an "extra sense"). But neither was the conceptualization by Michael Faraday (1791-1867) of the electromagnetic field: the mathematical structure was built later by James Clerk Maxwell (1831-1879). The theoretical evolutionary embryologist August Weismann (1834-1914) was often more rigorous than Darwin, but still not mathematical.
3) The Golden Age of theoretical biology was the first half of the 20th century, when Ronald Fisher (1860-1962), John Burdon Sanderson Haldane (1892-1964) and Sewall Wright (1889-1988) founded population genetics and Alfred Lotka (1880-1949), Vito Volterra (1860-1940) and Vladimir Kostitzin (1883-1963) started to build up theoretical ecology. These seeds have born many fruits since then. Take evolutionary biology, for example. A few decades after the Golden Age, evolutionary biologists started to tackle (ultimately with considerable success) questions where the Darwinian answer is far from obvious. Why do we age? Why are there sterile insect castes? At first it does not seem to make much sense to argue that your death or sterility increases your fitness. But evolutionary theory can provide satisfactory resolutions of these conundrums. In some cases even the question itself cannot be formulated well enough without some modeling: the problem of the evolutionary maintenance of sex is a case in point. Whole sub-disciplines, like evolutionary game theory, have been set up to meet such challenges.
4) The problems become a lot harder when we come to the large-scale dynamics of evolution. Imagine, say, a thousand Earth-like planets with exactly the same initial conditions of planetary development. After one, two, three billion years (and so on), how many of them would still have living creatures? And would they be like the eukaryotes? We have simply no knowledge about the time evolution of this distribution, and "educated" guesses differ widely.(1-4)
References:
1> Benner, S.A. (2003). Synthetic biology: Act natural. Nature 421, 118
2. Ganti, T. (1971). The Principle of Life (in Hungarian). (Budapest: Gondolat)
3. Ganti, T. (2003). The Principles of Life. ( Oxford University Press)
4. Maynard Smith, J. and Szathmary, E. (1995). The Major Transitions in Evolution. (Oxford: Freeman/Spektrum),
Current Biology http://www.current-biology.com
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THEORETICAL BIOLOGY: ON THEORY IN CELL BIOLOGY
The following points are made by John J. Tyson (Current Biology 2004 14:R262):
1) Many areas of modern science and engineering owe their strength and vitality to a rich interplay of experiment, theory, and computation. For example, quantum chemistry, aerodynamics, meteorology, and membrane electrophysiology are all firmly based on extensive quantitative observations, sound theoretical formalisms, and accurate predictive calculations. Molecular cell biology, on the other hand, is still, for the most part, proudly and precariously balanced on one leg -- experimental observations -- and its staunchest defenders believe that theoretical and computational approaches have little or nothing to contribute to our understanding of cell physiology(1).
2) This view is surely wrong. A living cell is an intrinsically dynamical system, ceaselessly adapting in space, time, and internal state to environmental challenges. Catalogs of genes and static diagrams of the structural and functional relationships of proteins, though necessary for full understanding, can never adequately account for the dynamism of organelles and cells. Take, for example, cilia: these beautiful tiny whips, attached to many cells, lash back and forth in wondrous synchrony, propelling cells through liquids or liquids past cells. Without cilia you would not have been born (they transport eggs from ovary to uterus) and you could not breathe (they continually sweep mucus and debris from the lungs and airways). How do these elegant little machines accomplish their essential tasks?
3) Open any modern textbook of cell biology and you will find an attempt to answer this fundamental question. What you will see is a parts list of a typical cilium -- dynein, tubulin, nexin, and so on -- and a pseudo-color, artist's rendition of how the parts seem to be connected. Then a few words about how dynein molecules can pull on microtubules, causing then to slide past each other. End of story.
4) This explanation leaves one unsatisfied. How are we to understand the dynamic function of a cilium from this static textbook picture? The essence of a cilium is to move in space and time. What principles organize the tiny pulls of each dynein motor into the "power stroke" that sweeps along the cilium from base to tip? What forces drive the recovery stroke along a trajectory so different from the power stroke? What invisible choreographer synchronizes the movements of vast fields of cilia to carry the egg to its destination?
5) These sorts of questions cannot be answered by cataloging parts, defining their connections, and drawing schematic diagrams. The problem demands a movie. “Well then, if you want a movie, go to the electronic version of the textbook and click on the icon for the quick time movie of a beating cilium.” What you will see is either a living cilium observed through a microscope or an animated cartoon of how the author imagines a cilium to move. But animation is not scientific explanation; it is likely to be as entertaining and as fundamentally mistaken as a Road Runner cartoon. What we desire is a realistic computation of the coordinated motion of a field of cilia, based on solid principles of biochemistry and biophysics, including the forces exerted by motor proteins on the stiff and elastic components of the axoneme, and the forces exerted by cilia on the viscoelastic liquid in which they are immersed. Although much interesting work has been done on this problem [2-5], a full and satisfying solution remains for the future.
References (abridged):
1 Lawrence, P. (2004). Theoretical embryology: a route to extinction?. Curr. Biol. 14, R7-R8
2 Dillon, R.H. and Fauci, L.J. (2000). An integrative model of internal axoneme mechanics and external fluid dynamics in ciliary beating. J. Theor. Biol. 207, 415-430
3 Gueron, S. and Levit-Gurevich, K. (2001). A three-dimensional model for ciliary motion based on the internal 9+2 structure. Proc. R. Soc. Lond. B. Biol. Sci. 268, 599-607
4 Brokaw, C.J. (2002). Computer simulation of flagellar movement VIII: Coordination of dynein by local curvature control can generate helical bending waves. Cell Motil. Cytoskeleton 53, 103-124
5 Lindemann, C.B. (2002). Geometric clutch model version 3: The role of the inner and outer arm dyneins in the ciliary beat. Cell Motil. Cytoskel. 52, 242-254
Current Biology http://www.current-biology.com
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