Many living systems, from cells to brains to governments, are controlled by the activity of a small subset of their constituents. It has been argued that coherence is of evolutionary advantage and that this active subset of constituents results from competition between two processes, a Next process that brings about coherence over time, and a Now process that brings about coherence between the interior and the exterior of the system at a particular time. This competition has been termed competitive coherence and has been implemented in a toy-learning program in order to clarify the concept and to generate—and ultimately test—new hypotheses covering subjects as diverse as complexity, emergence, DNA replication, global mutations, dreaming, bioputing (computing using either the parts of biological system or the entire biological system), and equilibrium and nonequilibrium structures. Here, we show that a program using competitive coherence, Coco, can learn to respond to a simple input sequence 1, 2, 3, 2, 3, with responses to inputs that differ according to the position of the input in the sequence and hence require competition between both Next and Now processes. 1. Introduction The quest for universal laws in biology and other sciences has led to the development—and sometimes the acceptance—of concepts such as tensegrity [1], edge of chaos [2, 3], small worlds [4], and self-organised criticality [5]. This quest has also led to the pioneering ( ) model developed by Kauffman in which is the number of nodes in an arbitrarily defined Boolean network and is the fixed degree of connectivity between them [6]. The actual use of the ( ) model to the microbiologist, for example, is that it might help explain how a bacterium negotiates the enormity of phenotype space so as to generate a limited number of reproducible phenotypes on which natural selection can act. Although the ( ) model successfully generates a small number of short state cycles from an inexplorable vast number of combinations—which might be equated to generating a few phenotypes from the vast number apparently available to the cell—the model has its limitations for the microbiologist as, for example, it has a fixed connectivity, it does not evolve, and it does not actually do anything. In a different attempt to find a universal law in biology, one of us began working on the idea of network coherence in the seventies. This idea is related to neural networks (though the idea was developed with no knowledge of them) which have indeed been proposed as important in generating phenotypes [7]. The network
References
[1]
D. E. Ingber, “The origin of cellular life,” Bioessays, vol. 22, no. 12, pp. 1160–1170, 2000.
[2]
J. P. Crutchfield and K. Young, “Computation at the edge of chaos,” in Complexity, Entropy and the Physics of Information: SFI Studies in the Sciences of Complexity, W. H. Zurek, Ed., pp. 223–269, Addison-Wesley, Reading, Mass, USA, 1990.
[3]
C. G. Langton, “Computation at the edge of chaos: phase transitions and emergent computation,” Physica D, vol. 42, no. 1–3, pp. 12–37, 1990.
[4]
D. J. Watts and S. H. Strogatz, “Collective dynamics of 'small-world9 networks,” Nature, vol. 393, no. 6684, pp. 440–442, 1998.
[5]
P. Bak, How Nature Works: The Science of Self-Organized Criticality, Copernicus, New York, NY, USA, 1996.
[6]
S. Kauffman, At Home in the Universe, the Search for the Laws of Complexity, Penguin, London, UK, 1996.
[7]
D. Bray, “Intracellular signalling as a parallel distributed process,” Journal of Theoretical Biology, vol. 143, no. 2, pp. 215–231, 1990.
[8]
V. Norris, “Modelling Escherichia coli The concept of competitive coherence,” Comptes Rendus de l'Academie des Sciences, vol. 321, no. 9, pp. 777–787, 1998.
[9]
V. Norris, “Competitive coherence,” in Encyclopedia of Sciences and Religions, N. P. Azari, A. Runehov, and L. Oviedo, Eds., Springer, New York, NY, USA, 2012.
[10]
V. Norris, A. Cabin, and A. Zemirline, “Hypercomplexity,” Acta Biotheoretica, vol. 53, no. 4, pp. 313–330, 2005.
[11]
V. Norris, A. Zemirline, P. Amar et al., “Computing with bacterial constituents, cells and populations: from bioputing to bactoputing,” Theory in Biosciences, pp. 1–18, 2011.
[12]
S. G. Wolf, D. Frenkiel, T. Arad, S. E. Finkeil, R. Kolter, and A. Minsky, “DNA protection by stress-induced biocrystallization,” Nature, vol. 400, no. 6739, pp. 83–85, 1999.
[13]
V. Norris and M. S. Madsen, “Autocatalytic gene expression occurs via transertion and membrane domain formation and underlies differentiation in bacteria: a model,” Journal of Molecular Biology, vol. 253, no. 5, pp. 739–748, 1995.
[14]
T. Katayama, S. Ozaki, K. Keyamura, and K. Fujimitsu, “Regulation of the replication cycle: conserved and diverse regulatory systems for DnaA and oriC,” Nature Reviews Microbiology, vol. 8, no. 3, pp. 163–170, 2010.
[15]
V. Norris, C. Woldringh, and E. Mileykovskaya, “A hypothesis to explain division site selection in Escherichia coli by combining nucleoid occlusion and Min,” FEBS Letters, vol. 561, no. 1–3, pp. 3–10, 2004.
[16]
Y. Grondin, D. J. Raine, and V. Norris, “The correlation between architecture and mRNA abundance in the genetic regulatory network of Escherichia coli,” BMC Systems Biology, vol. 1, p. 30, 2007.
[17]
C. L. Woldringh and N. Nanninga, “Structure of the nucleoid and cytoplasm in the intact cell,” in Molecular Cytology of Escherichia coli, N. Nanninga, Ed., pp. 161–197, Academic Press, London, UK, 1985.
[18]
V. Norris, L. Janniere, and P. Amar, “Hypothesis: variations in the rate of DNA replication determine the phenotype of daughter cells,” in Modelling Complex Biological Systems in the Context of Genomics, EDP Sciences, Evry, France, 2007.
[19]
L. H. Hartwell and T. A. Weinert, “Checkpoints: controls that ensure the order of cell cycle events,” Science, vol. 246, no. 4930, pp. 629–634, 1989.
[20]
A. L. Barabási and R. Albert, “Emergence of scaling in random networks,” Science, vol. 286, no. 5439, pp. 509–512, 1999.
[21]
M. H. V. Van Regenmortel, “Emergence in Biology,” in Modelling and Simulation of Biological Processes in the Context of Genomics, P. Amar, V. Norris, G. Bernot, et al., Eds., pp. 123–132, Genopole, Evry, France, 2004.
[22]
K. S. Jeong, Y. Xie, H. Hiasa, and A. B. Khodursky, “Analysis of pleiotropic transcriptional profiles: a case study of DNA gyrase inhibition.,” PLoS Genetics, vol. 2, no. 9, p. e152, 2006.
[23]
V. Norris, M. Demarty, D. Raine, A. Cabin-Flaman, and L. Le Sceller, “Hypothesis: hyperstructures regulate initiation in Escherichia coli and other bacteria,” Biochimie, vol. 84, no. 4, pp. 341–347, 2002.
[24]
A. Minsky, E. Shimoni, and D. Frenkiel-Krispin, “Stress, order and survival,” Nature Reviews Molecular Cell Biology, vol. 3, no. 1, pp. 50–60, 2002.
[25]
V. Norris, T. Den Blaauwen, R. H. Doi et al., “Toward a hyperstructure taxonomy,” Annual Review of Microbiology, vol. 61, pp. 309–329, 2007.
[26]
V. Norris, “Speculations on the initiation of chromosome replication in Escherichia coli: the dualism hypothesis,” Medical Hypotheses, vol. 76, no. 5, pp. 706–716, 2011.
[27]
V. Norris and P. Amar, “Life on the scales: initiation of replication in Escherichia coli,” in Modelling Complex Biological Systems in the Context of Genomics, EDF Sciences, Evry, France, 2012.
[28]
E. P. C. Rocha, J. Fralick, G. Vediyappan, A. Danchin, and V. Norris, “A strand-specific model for chromosome segregation in bacteria,” Molecular Microbiology, vol. 49, no. 4, pp. 895–903, 2003.
[29]
M. A. White, J. K. Eykelenboom, M. A. Lopez-Vernaza, E. Wilson, and D. R. F. Leach, “Non-random segregation of sister chromosomes in Escherichia coli,” Nature, vol. 455, no. 7217, pp. 1248–1250, 2008.
[30]
D. J. Raine and V. Norris, Metabolic cycles and self-organised criticality. Interjournal of complex systems, Paper 361, http://www.interjournal.org/, 2000.
[31]
A. L. Barabási and Z. N. Oltvai, “Network biology: understanding the cell's functional organization,” Nature Reviews Genetics, vol. 5, no. 2, pp. 101–113, 2004.
[32]
Y. Y. Liu, J. J. Slotine, and A. L. Barabási, “Controllability of complex networks,” Nature, vol. 473, no. 7346, pp. 167–173, 2011.
[33]
N. Guelzim, S. Bottani, P. Bourgine, and F. Képès, “Topological and causal structure of the yeast transcriptional regulatory network,” Nature Genetics, vol. 31, no. 1, pp. 60–63, 2002.
[34]
M. Thellier, G. Legent, P. Amar, V. Norris, and C. Ripoll, “Steady-state kinetic behaviour of functioning-dependent structures,” FEBS Journal, vol. 273, no. 18, pp. 4287–4299, 2006.
[35]
C. Ripoll, V. Norris, and M. Thellier, “Ion condensation and signal transduction,” BioEssays, vol. 26, no. 5, pp. 549–557, 2004.
[36]
G. Reguera, K. D. McCarthy, T. Mehta, J. S. Nicoll, M. T. Tuominen, and D. R. Lovley, “Extracellular electron transfer via microbial nanowires,” Nature, vol. 435, no. 7045, pp. 1098–1101, 2005.
[37]
G. P. Dubey and S. Ben-Yehuda, “Intercellular nanotubes mediate bacterial communication,” Cell, vol. 144, no. 4, pp. 590–600, 2011.
[38]
M. Matsuhashi, A. N. Pankrushina, K. Endoh et al., “Bacillus carboniphilus cells respond to growth-promoting physical signals from cells of homologous and heterologous bacteria,” Journal of General and Applied Microbiology, vol. 42, no. 4, pp. 315–323, 1996.
[39]
G. Reguera, “When microbial conversations get physical,” Trends in Microbiology, vol. 19, no. 3, pp. 105–113, 2011.
[40]
G. Dueck, “New optimization heuristics; The great deluge algorithm and the record-to-record travel,” Journal of Computational Physics, vol. 104, no. 1, pp. 86–92, 1993.
[41]
G. Paperin, D. G. Green, and S. Sadedin, “Dual-phase evolution in complex adaptive systems,” Journal of the Royal Society Interface, vol. 8, no. 58, pp. 609–629, 2011.
[42]
J. Vohradsky and J. J. Ramsden, “Genome resource utilization during prokaryotic development,” The FASEB Journal, vol. 15, no. 11, pp. 2054–2056, 2001.
[43]
X. Wang, C. Lesterlin, R. Reyes-Lamothe, G. Ball, and D. J. Sherratt, “Replication and segregation of an Escherichia coli chromosome with two replication origins,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 26, pp. E243–E250, 2011.
[44]
J. J. Hopfield, “Neural networks and physical systems with emergent collective computational abilities,” Proceedings of the National Academy of Sciences of the United States of America, vol. 79, no. 8, pp. 2554–2558, 1982.
[45]
D. O. Hebb, The Organization of Behavior, Wiley and Sons, New York, NY, USA, 1949.
[46]
M. Kaufman, J. Urbain, and R. Thomas, “Towards a logical analysis of the immune response,” Journal of Theoretical Biology, vol. 114, no. 4, pp. 527–561, 1985.
[47]
R. Thomas, D. Thieffry, and M. Kaufman, “Dynamical behaviour of biological regulatory networks I. Biological role of feedback loops and practical use of the concept of the loop-characteristic state,” Bulletin of Mathematical Biology, vol. 57, no. 2, pp. 247–276, 1995.
[48]
A. Hunding, F. Kepes, D. Lancet et al., “Compositional complementarity and prebiotic ecology in the origin of life,” BioEssays, vol. 28, no. 4, pp. 399–412, 2006.
[49]
H. Fr？hlich, “Long range coherence and energy storage in biological systems,” International Journal of Quantum Chemistry, vol. 42, no. 5, pp. 641–649, 1968.
[50]
V. Norris and G. J. Hyland, “Do bacteria sing? Sonic intercellular communication between bacteria may reflect electromagnetic intracellular communication involving coherent collective vibrational modes that could integrate enzyme activities and gene expression,” Molecular Microbiology, vol. 24, no. 4, pp. 879–880, 1997.
[51]
D. E. Ingber, “The architecture of life,” Scientific American, vol. 278, no. 1, pp. 48–57, 1998.
[52]
A. Travers and G. Muskhelishvili, “DNA supercoiling—a global transcriptional regulator for enterobacterial growth?” Nature Reviews Microbiology, vol. 3, no. 2, pp. 157–169, 2005.
[53]
J. L. Elman, “An alternative view of the mental lexicon,” Trends in Cognitive Sciences, vol. 8, no. 7, pp. 301–306, 2004.
[54]
R. Narayanaswamy, M. Levy, M. Tsechansky et al., “Widespread reorganization of metabolic enzymes into reversible assemblies upon nutrient starvation,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 25, pp. 10147–10152, 2009.
[55]
P. M. Llopis, A. F. Jackson, O. Sliusarenko et al., “Spatial organization of the flow of genetic information in bacteria,” Nature, vol. 466, no. 7302, pp. 77–81, 2010.
[56]
V. Norris, P. Amar, G. Bernot, et al., “Questions for cell cyclists,” Journal of Biological Physics and Chemistry, vol. 4, pp. 124–130, 2004.
