ScienceWeek

Receive free new issue announcements by Email: ScienceWeek TOC Alerts

ScienceWeek

SCIENCEWEEK

August 4, 2006

Vol. 10 - Number 31

-------------------------------

Back issues of ScienceWeek can be searched for subjects, names, terms, etc. at: http://scienceweek.com/swfr.htm

--------------------------------

It is impossible to express a really new principle in terms of a model following old laws.

-- Max Planck (1858-1947)

--------------------------------

Contents:

1. Cell Biology: On Simulations of Cell Dynamics

Science is an iterative process of experiments and hypotheses. Experiments produce surprising results; hypotheses are created to explain the results; new experiments are designed to test the hypotheses, of which some agree, some fail without yielding useful information and some produce more surprises; and the cycle continues. As a field matures, knowledge grows and the hypotheses become more elaborate, eventually exceeding the limits of what a scientist can mentally grasp. This is where computational modeling becomes necessary, and where cell biology is today.

2. Evolution: On the Future of Darwinism

Many regard the Darwinian theory of evolution by natural selection as one of the most important and powerful theories of our times, in the good company of the general theory of relativity and quantum theory. What will be Darwin's legacy in the 21st century? Will new work be mainly confirmatory, or can we expect new breakthroughs? What constitutes a Darwinian way of thinking in biology, or more broadly in science?

3. Astronomy: On Near-Field Cosmology

These are exciting times for astronomy and cosmology. On the one hand, we find that the main predictions of Big Bang inflationary cosmology are confirmed by observations of distant objects. On the other hand, nearby galaxies continue to surprise and inform us. In February 2006, a group of 50 scientists convened in Aspen, Colorado, to discuss what we are learning about cosmology from detailed observations of the nearest galaxies.

4. Structural biology: On the Folding of Proteins

The three-dimensional structures of proteins govern their activity, yet we know far less than we would like to about how these molecules fold into shape. Proteins use an intricate network of weak, non-covalent interactions to acquire the folded state. Conventional wisdom states that protein folding is a highly cooperative process -- proteins are either completely folded or completely unfolded.

--------------------------------

Also Noted:

Flies in the Face of Fashion, Mites Make Right, and Other Bugdacious Tales Tom Turpin Purdue University Press, West Lafayette, IN, 2006 Paperback: 262 pp., illus. $14.95. ISBN 1557534179 More information at: http://www.amazon.com/exec/obidos/ASIN/1557534179/scienceweek

Flower Breeding and Genetics Issues, Challenges and Opportunities for the 21st Century Neil O. Anderson, Ed. Springer, Dordrecht, Netherlands, 2006 Hardback: 830 pp., illus. $329. ISBN 1402044275 More information at: http://www.amazon.com/exec/obidos/ASIN/1402044275/scienceweek

Genomics and Society Legal, Ethical and Social Dimensions George Gaskell and Martin W. Bauer, Eds. Earthscan, London, 2006 Hardback: 276 pp., illus. £55. ISBN 1844071138 More information at: http://www.amazon.com/exec/obidos/ASIN/1844071138/scienceweek

Geometry of Quantum States An Introduction to Quantum Entanglement Ingemar Bengtsson and Karol Zyczkowski Cambridge University Press, Cambridge, 2006 Hardback: 478 pp., illus. $95. ISBN 0521814510 More information at: http://www.amazon.com/exec/obidos/ASIN/0521814510/scienceweek

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

1. CELL BIOLOGY: ON SIMULATIONS OF CELL DYNAMICS

The following points are made by S.S. Andrews and A.P. Arkin (Current Biology 2006 16:R523):

1) Science is an iterative process of experiments and hypotheses. Experiments produce surprising results; hypotheses are created to explain the results; new experiments are designed to test the hypotheses, of which some agree, some fail without yielding useful information and some produce more surprises; and the cycle continues. As a field matures, knowledge grows and the hypotheses become more elaborate, eventually exceeding the limits of what a scientist can mentally grasp. This is where computational modeling becomes necessary, and where cell biology is today.

2) Modeling serves the same purposes as scientific cartoons or calculations on the backs of envelopes, but is much more precise. A model can definitively show if an hypothesis can explain a set of data, make experimental predictions, and help identify system aspects that are poorly understood. After many iterations of experiments and theory, models are often sufficiently supported by evidence that they represent the current understanding of a system, against which new results are compared.

3) The authors focus on simulations of biochemical reaction networks, a core component of most cell biological models. The authors explore a range of simulation methods that vary in their level of physical approximation and abstraction. For concreteness, each is presented for the same generic elementary reversible chemical reaction. The molecules involved might be proteins, small molecules, DNA, RNA or other species. The molecular concentrations are variables that change over time, whereas the system volume, the initial concentrations and the reaction rate constants kf and kr are physical parameters that are specified by the modeler and kept constant throughout the simulation. When these parameters have not been directly measured and cannot be estimated from indirect data, model behavior is often explored as a function of them.

4) One of the most approximate physical models of biochemical networks, the kinetic ordinary differential equation (ODE), assumes that molecular concentrations are continuous (it ignores the discrete nature of molecules), that reactions occur in a homogeneous, well-stirred volume and that these reactions occur in a deterministic manner. This is by far the most common form of biological model and can represent both the transient dynamics and the long-term steady-state behavior of a system if the above approximations hold. ODE models of biochemical networks have been successfully applied to diverse systems. Metabolic networks are often investigated under constant conditions to identify the steady-state rates of metabolite flux and cellular growth. (1-5)

References (abridged):

1. Covert, M.W., Schilling, C.H., Famili, I., Edwards, J.S., Goryanin, I.I., Selkov, E., and Palsson, B.O. (2001). Metabolic modeling of microbial strains in silico. Trends Biochem. Sci. 26, 179-186

2. Tyson, J.J. (1991). Modeling the cell division cycle: cdc2 and cyclin interactions. Proc. Natl. Acad. Sci. USA 88, 7328-7332

3. Goldbeter, A. (2002). Computational approaches to cellular rhythms. Nature 420, 238-245

4. Fox, J.J., and Hill, C.C. (2001). From topology to dynamics in biochemical networks. Chaos 11, 809-815

5. Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T. (1988). Numerical Recipies in C. The Art of Scientific Computing. Cambridge University Press, Cambridge, UK

Current Biology http://www.current-biology.com

ScienceWeek http://scienceweek.com

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

2. EVOLUTION: ON THE FUTURE OF DARWINISM

The following points are made by Eörs Szathmáry (Science 2006 313:306:)

1) Many regard the Darwinian theory of evolution by natural selection as one of the most important and powerful theories of our times, in the good company of the general theory of relativity and quantum theory. What will be Darwin's legacy in the 21st century? Will new work be mainly confirmatory, or can we expect new breakthroughs? What constitutes a Darwinian way of thinking in biology, or more broadly in science? Is it still timely to think in a genuine Darwinian way, or should we resort only to some basic Darwinian principles? These questions were discussed by researchers at a recent conference at Trinity College, Cambridge, UK (1), which was hosted by the president of the Royal Society, Martin Rees.

2) There was fair agreement among the participants that Darwin's way of approaching problems remains valid and should be encouraged if possible. A feel for the organism, theoretical ideas guiding and aided by keen observations of meticulous details, excellent knowledge of natural history: These traits were characteristic of Darwin (as discussed by Randal Keynes), and there is little hope for biology in this century if at least some people will not walk in Darwin's footsteps. It seems mandatory that "professional generalists", when they rarely surface, should be cultivated and encouraged. Presumably such individuals arise by nature rather than nurture, but a mechanism to identify and support such rare people is badly needed. As Darwin said: "My mind seems to have become a kind of machine for grinding general laws out of large collections of facts" (2). We should facilitate the emergence of this mindset in able people.

3) At the beginning of the 21st century, we are well equipped with the knowledge of two disciplines that were practically closed books to Darwin: classical and molecular genetics, and mathematical modeling. Units of evolution must multiply, have heredity, and possess variability; and among the heritable traits, some must affect survival and/or reproduction. If these criteria are met, evolution by natural selection is possible in a population of such entities. There are at least three remarkable features of this short description. First, it is extremely short, but very powerful [this is why philosopher Daniel Dennett speaks about "Darwin's dangerous idea" (3)]. Second, it is not restricted to living organisms, and if the criteria are met, Darwinian evolution may unfold in the realm of chemistry and culture as well. Third, although we have learned a lot since Darwin's times, Darwin would have presumably agreed with this telegraphic description.

4) There are still enormous challenges ahead of us in areas where a Darwinian way of thinking could turn out to be fruitful. The origin of evolvability lies in chemistry, and the origin of replicators and life may be (one of) the greatest challenges for that field. We do not know how RNA originated. We do not know how the first cells got organized, and there is no full scenario for the origin of the genetic code either. Chemistry has helped biology enormously: The development of biochemistry and molecular biology, and their contributions to our understanding of some fundamental features of life, have been profound. This may be the era when biology pays back its debt: Many fields within chemistry are more and more adopting evolutionary approaches. The triumph of in vitro genetics in producing catalytic RNA molecules (ribozymes) is a success story beyond doubt. An evolutionary approach toward nanotechnology may bear further fruits. (3-5)

References:

1. Darwin and the 21st Century Science Seminar, 23 to 24 March 2006, Cambridge, UK; organized by the Charles Darwin Trust

2. C. Darwin, The Autobiography of Charles Darwin 1809-1882, N. Barlow, Ed. (Norton, New York, 1969), p. 139

3. D. Dennett, Darwin's Dangerous Idea (Simon and Schuster, New York, 1996)

4. M. Christiansen, S. Kirby, in Language Evolution, M. Christiansen, S. Kirby, eds. (Oxford University Press, Oxford, UK, 2003), pp. 1-15

5. B. Bryson, A Short History of Nearly Everything (Random House, New York, 2003)

Science http://www.sciencemag.org

ScienceWeek http://scienceweek.com

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

3. ASTRONOMY: ON NEAR-FIELD COSMOLOGY

The following points are made by J. Bland-Hawthorn and P.J. Peebles (Science 2006 313:311):

1) These are exciting times for astronomy and cosmology. On the one hand, we find that the main predictions of Big Bang inflationary cosmology are confirmed by observations of distant objects. On the other hand, nearby galaxies continue to surprise and inform us. In February 2006, a group of 50 scientists convened in Aspen, Colorado, to discuss what we are learning about cosmology from detailed observations of the nearest galaxies (1).

2) Approximately 380,000 years after the Big Bang, the expanding universe became cool enough to allow ions and electrons to combine to form a gas of atomic hydrogen and helium. The free electrons had scattered and trapped the thermal radiation from the hot Big Bang; the abrupt elimination of these free electrons allowed the thermal radiation to move nearly without scattering. Precision measurements of the distribution of this radiation, most recently by the Wilkinson Microwave Anisotropy Probe (WMAP) satellite (2), are in close agreement with the relativistic theory of how the present concentrations of mass in and around galaxies grew out of the distribution of mass at the time of release of the radiation.

3) But the story does not end there. The universe was ionized again in a process that is thought to have commenced some 100 million years after the Big Bang and is observed to be complete by the time the universe was 10 times that age. The study of this reionization is a topic for current research, but we do know that the first generations of massive stars likely played a major role. Observations of distant galaxies, seen as they were in the past because of the light travel time, show that many young galaxies were strong sources of ionizing radiation, but observations must reach still greater distances to show us the earliest generations of stars. This is a key science goal of the next generation of large telescopes, including the James Webb Space Telescope due to launch in the next decade.

4) A notable issue for Big Bang cosmology is that it requires only 4% of the mass of the universe to be in the form of baryons (particles such as protons and neutrons) of which stars and people are made. The rest is in "dark matter", which acts like a gas of particles that are not baryons, and "dark energy", which is the new name for Einstein's cosmological constant or something that acts like it. The evidence for the existence of these dark components is strong, but their properties are only loosely understood.(3-5)

References (abridged):

1. Aspen Center for Physics workshop on Local Group Cosmology, Aspen, CO, 5 to 11 February 2006

2. D. N. Spergel et al., http://arxiv.org/abs/astro-ph/0603449 (2006)

3. The Big Bang produced mostly hydrogen and helium, whereas most of the heavier elements were produced in stars and returned to the interstellar medium by supernovae and winds, in a process that cycled through generations of stars.

4. T. Beers, N. Christlieb, Annu. Rev. Astron. Astrophys. 43, 531 (2005)

5. A. R. Zentner, J. S. Bullock, Astrophys. J. 598, 49 (2003) and references therein.

Science http://www.sciencemag.org

ScienceWeek http://scienceweek.com

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

4. STRUCTURAL BIOLOGY: ON THE FOLDING OF PROTEINS

The following points are made by Jeffery W. Kelly (Nature 2006 442:255):

1) The three-dimensional structures of proteins govern their activity, yet we know far less than we would like to about how these molecules fold into shape. Proteins use an intricate network of weak, non-covalent interactions to acquire the folded state (1). Conventional wisdom states that protein folding is a highly cooperative process -- proteins are either completely folded or completely unfolded. This all-or-nothing model is convenient because it enables spectroscopic data to be converted into thermodynamic data, simply by measuring the distribution of folded and unfolded molecules at equilibrium. But is this model always correct? Muñoz et al (2) use nuclear magnetic resonance (NMR) spectroscopy to follow the unfolding of an all-helical protein known as BBL.

2) BBL folds in a "downhill" fashion -- that is, the process is characterized by very low energy barriers between the folded and unfolded states (3-5). When downhill folders are subjected to conditions that predispose them to unfold, such as heat stress, they are predicted to unfold gradually (5). The authors' findings (2) support this prediction, and suggest that protein folding is not necessarily an all-or-nothing process. Because unfolding is perceived to be the reverse of folding, the former process provides insight into the latter.

3) Every hydrogen atom in a protein is in a unique electronic environment because of the chemical groups surrounding it. As a result, each hydrogen atom gives rise to a distinct signal in an NMR spectrum, and the frequency of this signal changes when the protein unfolds, as the environment around the hydrogen atom alters. When heated to induce unfolding, BBL adopts many conformations that interchange rapidly, so the NMR frequency of each hydrogen atom reports on the extent of local unfolding.

4) Muñoz et al (2) plotted the NMR frequency changes of 158 hydrogen atoms in BBL as a function of temperature, producing 158 atomic-resolution graphs, known as unfolding curves. These atomic unfolding curves were not superimposable. Instead, the midpoint temperatures of the curves spanned a temperature range of 60 K. This demonstrates that, at any given temperature, some hydrogen atoms were in a folded environment whereas others were in an unfolded environment. This observation cannot be explained by the existence of only folded or unfolded BBL molecules (2).

References (abridged):

1. Fersht, A. R. , Matouschek, A. & Serrano, L. J. Mol. Biol. 224, 771-782 (1992)

2. Sadqi, M. , Fushman, D. & Muñoz, V. Nature 442, 317-321 (2006)

3. Bryngelson, J. D. , Onuchic, J. N. , Socci, N. D. & Wolynes, P. G. Proteins 21, 167-195 (1995)

4. Sabelko, J. , Ervin, J. & Gruebele, M. Proc. Natl Acad. Sci. USA 96, 6031-6036 (1999)

5. Muñoz, V. Int. J. Quantum Chem. 90, 1522-1528 (2002)

Nature http://www.nature.com/nature

ScienceWeek http://scienceweek.com

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

NOTICES

ScienceWeek is both a copyrighted publication and a free educational resource. Any issue in whole or in part should not be archived, posted, or distributed without full attribution, including a web link to the ScienceWeek original text or to the ScienceWeek home page. The publication is "open access", which means all issues are available free to the public online at the ScienceWeek website.

ScienceWeek copyright extends only to material originated by ScienceWeek. Other copyrights may obtain for other material.

All back issues of ScienceWeek 1998 to the present are available free at http://scienceweek.com

SCIENCEWEEK SUBSCRIPTIONS:

New or renewal full-text Email subscriptions are no longer available. Table of contents by Email with URLs for free access to reports are available free by sending Email to contents@scienceweek.com with CONTENTS as the subject header.

CHANGE OF EMAIL ADDRESS: If you have a current full-text Email subscription, you can change your Email address at any time. Please send both the old and new address to: request@scienceweek.com

We welcome comments, suggestions, and criticisms from our subscribers. Editorial contact: editors@scienceweek.com

Editor/Publisher: Dan Agin

Managing Editor: Claire Haller

Associate Editor: Joan Hartman


	Web ScienceWeek