Imitation of Life
Can a computer program reproduce everything that happens inside a living cell?
The idea of building artificial life forms, whether in software or in synthetic cytoplasm, has always been controversial. Mary Shelley, almost 200 years ago, wrote a deep meditation on this theme: Frankenstein, or the Modern Prometheus. In Shelley’s time the debate was framed in terms of vitalism versus mechanism. The vitalists argued that living things are distinguished from inorganic matter by some “spark of life” or animating principle. The opposing mechanist view had its greatest early champion in René Descartes, who compared animals to clockwork automata.
Within the world of science, the doctrine of vitalism is long dead, and yet there is still resistance to the idea that life is something we can fully comprehend by disassembling an organism and cataloging its component parts. In the brash early years of molecular biology, DNA was “the blueprint of life,” a full set of instructions for building a cell. The core process of life was seen as symbol manipulation, a matter of pairing G with C and A with T, then mapping the 4-letter alphabet of nucleotides into the 20-letter alphabet of amino acids. If only we could learn to read the blueprints and decipher the genetic messages, we would know everything about how life works. Now that we read DNA sequences quite fluently, it seems clearer that there’s more to life than the “central dogma” of molecular biology.
The idea of simulating a living cell with a computer program stands in the crossfire of this argument between reductionism and a more integrative vision of biology. On one hand, the WholeCell project makes abundantly clear that the DNA sequence by itself is not the master key to life. Even though the transfer of information from DNA to RNA to protein is a central element of the model, it is not handled as a simple mapping between alphabets. The emphasis is on molecules, not symbols.
On the other hand, the very attempt to build such a model is a declaration that life is comprehensible, that there’s nothing supernatural about it, that it can be reduced to an algorithm—a finite computational process. Everything that happens in the simulated cell arises from rules that we can enumerate and understand, for the simple reason that we wrote those rules.
I would love to believe that the success of simulation methods in biology might forge a new synthesis and put an end to philosophical bickering over these questions. I’m not holding my breath.
- Barile, M. F., and S. Razin (eds). 1989. The Mycoplasmas. New York: Academic Press.
- Bonarius, H. P. J., G. Schmid and J. Tramper. 1997. Flux analysis of underdetermined metabolic networks: The quest for the missing constraints. Trends in Biotechnology 15:308–314.
- Brenner, S. 2010. Sequences and consequences. Philosophical Transactions of the Royal Society of London 365:207–212.
- Covert, M. W., et al. 2001. Metabolic modeling of microbial strains in silico. Trends in Biochemical Sciences 26:179–186.
- Covert, M. W., N. Xiao, T. J. Chen and J. R. Karr. 2008. Integrating metabolic, transcriptional regulatory and signal transduction models in Escherichia coli. Bioinformatics 24:2044–2050.
- Crick, F. H. C. 1973. Project K: The complete solution of E. coli. Perspectives in Biology and Medicine 17:67–70.
- Gibson, D. G., et al. 2010. Creation of a bacterial cell controlled by a chemically synthesized genome. Science 329:52–56.
- Karr, J. R., et al. 2012. A whole-cell computational model predicts phenotype from genotype. Cell 150:389–401. Supplemental material: http://dx.doi.org/10.1016/j.cell.2012.05.044. Source code: http://wholecell.stanford.edu
- Lerman, J. A., et al. 2012. In silico method for modelling metabolism and gene product expression at genome scale. Nature Communications 3:929.
- Loeb, J. 1912. The Mechanistic Conception of Life: Biological Essays. Chicago: University of Chicago Press.
- Morowitz, H. J. 1984. The completeness of molecular biology. Israel Journal of Medical Sciences 20:750–753.
- Orth, J. D., I. Thiele and B. Ø. Palsson. 2010. What is flux balance analysis? Nature Biotechnology 28:245–248.
- Suthers, P. F., et al. 2009. A genome-scale metabolic reconstruction of Mycoplasma genitalium, iPS189. PLoS Computational Biology 5:e1000285.
- Tomita, M., et al. 1999. E-CELL: Software environment for whole-cell simulation. Bioinformatics 15:72–84.
» Post Comment