Emergence (biology)

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Systems biologists study, among other things, the phenomenon of emergence, whereby properties, functions and behaviors appear in living systems though not exhibited by any individual component of the system, and not explainable or predictable from complete understanding the components' properties/behaviors considered in isolation from the system that embeds them. Every cellular system exhibits emergent behaviors. Emergent behaviors of living systems include such things as locomotion, sexual display, flocking, and conscious experiencing. Even the biological components of living cells, such as mitochondria and other organelles, exhibit emergent properties.

This article will explore emergence as a concept with a long history, differing interpretations, and much controversy.

Emergence vs. vitalism

Some biologists might find it tempting to see a type of 'vitalism', or 'life force', in living systems, given that some whole-system properties/behaviors of organisms, including even the activity of living itself, exemplify emergent phenomena as defined in the introduction. One could not explain, for example, the behavior of an organism fleeing from a predator from a study of the properties of an organism's component subsystems. The properties of the component parts in a living system depend on the organization of those parts in the system, differing from those found .[1]. Because biologists and their co-scientists can explain emergent properties/phenomena, if only sometimes in principle, by mechanisms that do not transcend interactions of matter and energy, any such ‘vitalism’ properly qualifies only as a ‘materialistic vitalism’.

One example of emergence: When components of a signaling pathway, which enable between-cell communication, interact to form the signaling system, properties can emerge — such as a self-sustaining feedback loop and generation of the signals themselves — that one cannot explain from the individuated properties of the separate components of the system.[2]

For another example, in studying a protein separated from the system it belongs to, one can observe many of its properties, but in so studying the protein one cannot explain any of the properties it has only in the context of the system that embeds it, such as the property of catalyzing a biochemical reaction, or of binding to other proteins to form a functional protein complex. Those properties of the protein emerge in the context of the protein’s environment — how it interacts in the context of the system as a whole. Moreover, those emergent properties may result in effects within the system that, in a feedback way, further alters the properties of the protein in the system, as when a reaction product alters the catalytic properties of the protein.

Why do not all of the properties/behaviors of a system predictably result from the properties of its components? After all, the reductionist paradigm that dominated the Scientific method in the 20th century operated on the exactly opposite assumption. For one thing, the intrinsic properties of a system’s components themselves do not determine those of the whole system; rather, their 'organizational dynamics' does — how the components interact coordinately in time and space. Those organizational dynamics include not only the interrelations among the components themselves, but also interactions among the many different organizational units in the system. [3] Secondly, the living system always operates in a certain context (its external environment, or surroundings), and those surroundings, in turn, always affect the properties of the system-as-a-whole. For example, nutrient gradients in its environment influence the direction a bacterium’s locomotion. The impact of environmental context affects the dynamic organization of the components within the system — a 'downward causation'. [4] For another example, environmental signals can activate or suppress a metabolic pathway, reorganizing cellular activity[5] One cannot simply take a living system apart and predict how it will behave in its natural environment.

As Gilbert and Sarkar[1] puts it: “Thus, when we try to explain how the whole system behaves, we have to talk about its parts the context of the whole and cannot get away talking only about the parts.”

Philosopher of science D.M. Walsh puts it this way: "The constituent parts and processes of a living thing are related to the organism as a whole by a kind of 'reciprocal causation'."[6] In other words, the organization of the components determine the behavior of the system, but that organization arises from more than the set of its internal components. How the whole system behaves as it interacts with its environment determines how those components organize themselves, and so novel properties of the system 'emerge' that characterize neither the environment nor that set of internal components. For example, the behavior of a human kidney cell depends not only on its cellular physiology, but also on all the properties of the organ (kidney) which constitutes its environment. The kidney's overall structure and function influence the cell’s structure and behavior (e.g., by physical confinement and by cell-to-cell signaling), which in turn influence the organization of its intracellular components. The kidney in turn responds to its environment, namely the individual body that it lives in, and that body responds to its environment, which includes such factors as the availability of particular food items, fresh water, and ambient temperature and humidity. Systems biologists regard emergent properties as arising from a combination of bottom-up and top-down effects — Walsh's 'reciprocal causation'.

Emergent processes have been recognised as, for example, contributing to understanding:

  • subcellular morphology [7],
  • developmental biology [8],
  • metabolic networks [9],
  • proteomics [10] [11]
  • evolution of complexity in living things</ref>

Emergent phenomena appear even in non-biological physical systems. [12]  Emergent phenomena attract the attention of cellular neuroscientists; [13]  and cognitive scientists [14].  At still higher systems levels, emergent properties appear for example in the behaviour of ant colonies and the concept of swarm intelligence, [15]  Systems scientists have simulated emergent phenomena [16]  Emergent phenomena in human societies has also received attention. [17].  Biologists even explain the biosphere itself as emergent. [18]

Emergent systems always display what we recognize as ‘complexity’, a feature we have a difficult time precisely defining. Complex systems appear to require more bits of information (words, sentences, lines of computer code, etc.) to describe than the bits of information in the system itself. [19]  The operation of the system itself supplies its own most economical model.

According the paleontologist and origin of life researcher, Robert Hazen, four basic complexity elements underpin emergence in a system: [20]

  • a sufficiently large ‘density’ of components, with increasing complexity as the concentration increases, up to a point;
  • sufficient interconnectivity of the components, with increasing complexity with greater and more varied types of interconnectivity, up to a point;
  • a sufficient energy flow through the system to enable the system’s components to perform the work of interacting in the self-organized way characteristic of the energized system;
  • flow of energy through the system in a cyclic manner, presumably facilitating the spatiotemporal patterning characteristic of organized systems.

Other basic concepts that systems biologists consider crucial in explaining living systems as-a-whole include 'robustness', 'modularity', and 'networks' — all discussed in sections below. Quantitative modeling and simulation guided by experimental biological data provide the mainstay methodologies of systems biologists. (See Systems biology and Denis Noble's 2006 book on systems biology, The Music of Life, written for the general reader.[21])

  1. 1.0 1.1 Cite error: Invalid <ref> tag; no text was provided for refs named gilbert00
  2. Bhalla US, Iyengar R (1999) Emergent properties of networks of biological signaling pathways. 381-387 PMID 9888852 Link-1 Link-2
  3. Note: For example, physical chemists cannot predict the properties of water from knowledge of its components, hydrogen and oxygen. The way hydrogen and water interact to form H2O, and the way H2O molecules interact, enables the properties of water to 'emerge'.
  4. Note: Following up on the example of water, the properties of its environment (e.g., temperature, pressure) affect the way the H2O molecules organize themselves, as ice, or liquid, or steam
  5. Note: In relation to downward causation, the environment’s effect can sometimes reach down to the genetic database with molecular signals, altering its expression and consequently the characteristics of the cells without altering the database itself — so-called 'epigenetic' effects. When epigenetic alterations of gene expression occur in the reproductive organs, the system changes can be transmitted to the next generation. See
    • Jablonka E, Lamb MJ (2005) Evolution in Four Dimension: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge: MIT Press
    • Gorelick R (2004) Neo-Lamarckian medicine. Med Hypotheses 62:299-303 PMID 14962644
  6. Walsh DM (2006) Organisms as natural purposes: the contemporary evolutionary perspective. Stud Hist Philos Biol Biomed Sci 37: 771-91
  7. Tabony J (2006) Microtubules viewed as molecular ant colonies. Biol Cell 98:603-17 PMID 16968217
  8. Theise ND, d'Inverno M (2004) Understanding cell lineages as complex adaptive systems. Blood Cells Mol Dis 32:17-20 PMID 14757407 and Ruiz i Altaba A et al. (2003) The emergent design of the neural tube: prepattern, SHH morphogen and GLI code. Curr Opin Genet Dev 13:513-21 PMID 14550418
  9. Jeong H et al.(2000) The large scale organisation of metabolic networks. Nature 407:651-4
  10. e.g. Grindrod P, Kibble M (2004) Review of uses of network and graph theory concepts within proteomics. Expert Rev Proteomics 1:229-38 PMID 15966817
  11. Ye X et al.(2005) Multi-scale methodology: a key to deciphering systems biology. Front Biosci 10:961-5 PMID 15569634
  12. Cho YS et al. (2005) Self-organization of bidisperse colloids in water droplets. J Am Chem Soc 127:15968-75 PMID 16277541
  13. see e.g. Burak Y, Fiete I (2006) Do we understand the emergent dynamics of grid cell activity? J Neurosci 26:9352-4 PMID 16977716
  14. e.g. Courtney SM (2004) Attention and cognitive control as emergent properties of information representation in working memory. Cogn Affect Behav Neurosci 4:501-16 PMID 15849893
  15. Theraulaz G et al (2002) Spatial patterns in ant colonies. Proc Natl Acad Sci USA 99:9645-9 PMID 12114538
  16. Theraulaz G, Bonabeau E (1999)A brief history of stigmergy. Artif Life 5:97-116 PMID 10633572
  17. Bonabeau E, Meyer C (2001) Swarm intelligence. A whole new way to think about business. Harv Bus Rev 79:106-14 PMID 11345907
  18. Field CB, Behrenfeld MJ, Randerson JT, Falkowski P (1998) Primary Production of the Biosphere: Integrating Terrestrial and Oceanic Components. Science 281:237-40
  19. (1991) Zurek WJ (ed) Complexity, Entropy, and the Physics of Information: The Proceedings of the Workshop on the Complexity, Entropy, and the Physics of Information May-June, 1989, Santa Fe, New Mexico. Addison-Wesley Publishing Company, The Advanced Book Program, Redwood City. ISBN 0201515091
  20. Hazen RM (2005) Genesis: The Scientific Quest for Life's Origin. Joseph Henry Press, Washington DC. ISBN 0309094321
  21. Nobel D. (2006) The Music of Life: Biology Beyond the Genome. Oxford University Press, New York. ISBN 978-0-19-929573-9 Brief Biography Multiple Chapter Excerpts Online