Curator

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Prof. Jonathon Howard

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden

Phone: +49 351 210-2500
Fax: +49 351 210-2020

Email: howard@­mpi-cbg.de

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Behavioural Biology . Cell Biology . Developmental Biology . Evolutionary Biology . Genetics . Immunobiology . Infection Biology . Medicine . Microbiology . Neurosciences . Physiology . Plant Research . Structural Biology

Self-organisation in biology

New theoretical approaches are required to understand self-organization in biology; theory will drive discovery as it does in the physical sciences. A huge amount of biological data will be generated over the coming years from technological advances, not just in DNA sequencing, proteomics and other ‘omics’ disciplines, but in imaging of cells and tissues. Understanding biological self-organization may change the way we think about development, cell differentiation and disease pathogenesis.

Through self-organization, a system becomes ordered in space and/or time, often leading to emergent properties that qualitatively differ from those of its individual units.

DEDUCTIONS FROM REDUCTIONS

The reductionist approach — systematically dismantling complex systems to examine individual components — has been successful for the sciences over the past few centuries, from the isolation of the elements in chemistry, the discovery of atomic and subatomic particles in physics, to the purification and study of proteins, DNA and RNA in biology.

Although this reductionist approach in biology will continue, there is increasing interest in determining the properties of systems of interacting biomolecules. How do networks of proteins and genes integrate and respond to signals? How do dynamic organelle structures, such as the mitotic spindle, form? What controls growth and division? How does the genome create an organism? Self-organization is central in these processes1, at various sizes (Fig. 2).

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Fig. 1 | Cell patterns. Purified cell-division proteins can form spiral waves.

Self-organized systems differ from self-assembled ones as they rely on a continuous input of energy for maintenance and are far from thermal equilibrium. Classical thermodynamics — successful in the physical sciences — does not apply. Instead of self-assembling into the lowest energy state, such as a crystal, energy-dissipating components self-organize into highly complex structures through which there is a constant flux of energy and material.

Established theories, such as those of dynamical systems and control (from physics and engineering) can provide a basis for understanding self-organization in biology; however, the unique properties of biological systems — their multiple components and energy-dissipation mechanisms, and wide ranges in time and space — pose practical and intellectual challenges.

 
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