Ruprecht Karls Universität Heidelberg
Ulrich Schwarz: IMPRS compact course on systems biology Jan 2004

Ulrich Schwarz
IMPRS compact course January 2004
each Tuesday and Thursday 2 pm in the theory seminar room
starting January 8 2004, ending January 29 2004

Systems biology

Due to the breathtaking advances in genomics and proteomics, today's biology is flooded with data. Probably everybody would agree that in order to understand an organism, it is not sufficient to simply list all of its parts (imagine doing this for an airplane). Therefore it is high time to step back and to try to see the big picture. During recent years, this endeavor has become known as systems biology. Many researchers now agree that cell biology is in a transition from the molecular to the systems point of view, but how this will be accomplished is far from clear. In this course, we will try to draw together the first emerging themes in the field of systems biology.

Although its use has become rather fashionable, the term systems biology is not well defined. However, it is well accepted now that the main feature of systems biology will be quantification. Systems biology in a narrow sense is the integration of biological experiments with large-scale data analysis and quantitative computer modelling. This part of systems biology is close to bioinformatics, its focus is on prediction and control, and it involves techniques from informatics and systems engineering. However, in a wider sense systems biology should also include the development of a new conceptual framework for biology. This part of systems biology is closer to physics, which is used to reducing complex systems to their essentials by integrating out some degrees of freedom. In general, systems biology can only succeed by drawing together knowledge from many different disciplines, including molecular biology, biochemistry, informatics, control theory and physics. Regarding the latter, biophysics, statistical mechanics, physics of dynamical systems and soft matter physics might provide helpful insights, due to their expertise in structural aspects of biological systems, hierarchical systems, complexity, cooperative effects and thermal noise. Due to the large research effort now being invested into systems biology, there is some hope that in the long run, biology (and, hopefully, medicine, too) will become a quantitative, hypothesis-driven science.

Recent initiatives in systems biology

This course will start with an overview on institutional activities in the field of systems biology. In the United States, a large number of new initiatives have recently been set up, for example
Systems biology is also a high priority research area in Japan, with at least two large research initiatives started:
In general, momentum in systems biology has not grown that much yet in the Euorpean area. In Germany, there is a strong tradition in biological cybernetics (eg the MPI at Tübingen), which however is focused more on cognitive rather than on molecular processes. There is also a strong tradition in systems control theory (eg the MPI at Magdeburg), which recently has moved towards systems biology. Here is a incomplete list of initiatives and research groups in this field:
In particular, the international conference on systems biology 2004 took place at Heidelberg (the first of the annual series of ICSBs took place in 2000 at Tokyo, the one in 2005 will take place in Boston). Currently, this field is growing at a very fast pace, including new journals like

Software for systems biology

Next we will discuss different software projects. The ultimate goal in this area is the complete simulation of all biochemical and structural processes inside a cell. Most software however only addresses the biochemical aspects. Usually there is GUI-interface for model definition and a fast ODE-solver. In some cases, one can switch between continuous and stochastic treatment of the rate equations. There is a large effort now to define platform-independent formats for input and output, usually as XML-based markup language. The course will give a overview including the following projects:

Conceptual framework for systems biology

The largest challenge in systems biology is the development of a new conceptual framework for a deeper understanding of biological systems design. Although this field has just opened, there are a few interesting concepts already emerging, including functional modules, networks, and robustness. Because it is much to early to give a definite account of these developments, we will start with a few general remarks on this subject and then focus on one particular system, which by now has become the paradigm for systems biology, namely bacterial chemotaxis.

Schedule

  1. Jan 8: Introduction: definition systems biology, recent initiatives in this field, introduction to E. Coli
  2. Jan 13 and 15: Control theory: steam engine with governor, thermostat, temperature control in human body, fever
  3. Jan 20: Genetic and biochemical networks, chemical kinetics, deterministic and stochastic descriptions, linear stability and bifurcation analysis
  4. Jan 22: Software for systems biology: overview and practical demonstration for Virtual Cell (presentation by Ilka Bischofs)
  5. Jan 27: Quantitative models for E Coli: lac operon and lambda switch (presentation by Stefan Klumpp); robustness of the chemotactic module in E. Coli I (presentation by Vessilin Nikolov on experiments by Leibler group)
  6. Jan 29: robustness of the chemotactic module in E. Coli II (presentations by Gunnar Linke and Thorsten Erdmann on theories by Leibler and Doyle groups, respectively); summary and outlook: control, feedback, stability, robustness, networks, modules, and all that stuff

Literature

For overview reading:
Some general textbooks which are helpful for subjects like chemical kinetics and feedback:
  • GB Benedek and FMH Villars, Physics with illustrative examples from medicine and biology, Vol. 1: Mechanics, 2nd ed, Springer 2000
  • James Murray, Mathematical Biology, 2nd edition, Springer 2003
For the historically minded:
  • Horace Freeland Judson, The eighth day of creation: makers of the revolution in biology, Cold Spring Harbor Laboratory Press, expanded edition 1996
  • Lily E Kay, Who wrote the book of life ? A history of the genetic code, Stanford University Press 2000
Interesting papers on general aspects of and recent advances in systems biology/computational cell biology:
  • D Bray, Reductionism for biochemists: how to survive the protein jungle, Trends in Biochemical Sciences 22: 325, 1997
  • LH Hartwell, JJ Hopfield, S Leibler and AW Murray, From molecular to modular cell biology, Nature 402: C47, 1999
  • H Kitano, Systems biology: a brief overview, Science 295: 1662, 2002
  • ME Csete and JC Doyle, Reverse Engineering of Biological Complexity, Science 295: 1664, 2002
  • CV Rao, DM Wolf and AP Arkin, Control, exploitation and tolerance of intracellular noise, Nature 420: 231, 2002
  • U Alon, Biological networks: The tinkerer as an engineer, Science 301: 1866, 2003
  • E Alm and AP Arkin, Biological networks, Current Opinion in Structural Biology 13: 193, 2003
  • JJ Tyson, KC Chen and B Novak, Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell, Current Opinion in Cell Biology 15: 221, 2003
For bacterial chemotaxis, we will use Howard Berg's work for an introduction to EColi and then go through recent work on robustness in the chemotactic network of EColi:
  • HC Berg, Random walks in biology, expanded ed, Princeton University Press 1993 (this little book has been motivated by two classical papers, Physics of Chemoreception by Berg and Purcell Biophys J 1977 and Life at low Reynolds number by Purcell Am J Phys 1977; a more recent review article by Berg is Motile behavior of bacteria, Physics Today Jan 2000)
  • JL Spudich and DE Koshland, Non-genetic individuality: chance in the single cell, Nature 262: 467, 1976
  • LA Segel, A Goldbeter, PN Devreotes and BEA Knox, A mechanism for exact sensory adaption based on receptor modification, J Theor Biol 120: 151, 1986
  • PA Spiro, JS Parkinson and HG Othmer, A model of excitation and adaption in bacterial chemotaxis, PNAS 94: 7263-7268, 1997
  • N Barkai and S Leibler, Robustness in simple biochemical networks, Nature 387: 913, 1997
  • U Alon, MG Surette, N Barkai and S Leibler, Robustness in bacterial chemotaxis, Nature 397: 168, 1999
  • N Barkai, U Alon and S Leibler, Robust amplification in adaptive signal transduction networks, C R Acad Sci Paris, 871-877, 2001
  • TM Yi, Y Huang, MI Simon and J. Doyle, Robust perfect adaption in bacterial chemotaxis through integral feedback control, PNAS 97: 4649, 2000
For the lac operon:
  • F Jacob and J Monod, Genetic regularory mechanisms in the synthesis of proteins, J Mol Biol 3: 318, 1961
  • MA Savageau, Genetic regulatory mechanisms and the ecological niche of Escherichia coli, PNAS 71: 2453, 1974; Demand theory of gene regulation I and II, Genetics 149: 1665 and 1677, 1998
  • JMG Vilar and CC Guet and S Leibler, Modeling network dynamics: the lac operon, a case study, J. Cell Biol. 161: 471-476, 2003
  • JMG Vilar and S Leibler, DNA Looping and physical constraints on transcription regulation, J. Mol. Biol. 331: 981-989, 2003
  • N Yildirim and MC Mackey, Feedback regulation in the lactose operon, Biophys. J. 84: 2841-2851, 2003
For the lambda switch:
  • HH McAdams and L Shapiro, Circuit simulation of genetic networks, Science 269: 650-656, 1995
  • A Arkin, J Ross and HH McAdams, Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia Coli cells, Genetics 149: 1633-1648, 1998
  • M Santillan and MC Mackey, Why the lysogenic state of phage lambda is so stable, Biophys. J. 86: 75-84, 2004
Finally, if you are not tired yet, there are other interesting systems for which quantitative modeling has been demonstrated, including:
  • MT Borisuk and JJ Tyson, Bifurcation analysis of a model of mitotic control in frog eggs, J. Theor. Biol. 195: 69-85, 1998
  • G von Dassow, E Meir, EM Munro and GM Odell, The segment polarity network is a robust developmental module, Nature 406: 188, 2000


Updated by Ulrich Schwarz Oct 19 2004

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