What is a swarm?
When we think of a swarm, we usually think of swarms of insects, but the term swarm can be applied to different species (e.g herds, flocks, schools, societies (e.g I Couzin. ), and even different scales (e.g gluons, quarks, electrons, particles, cells, organisms, stars, etc).
These ideas are already being explored by a number of scientists, particularly in the field of artificial intelligence where swarm behaviours are used to explore collective behaviour/self organisation.
There are swarming behaviour and growth at various scales, including at cellular level. In their natural environments, cells often undertake complex collective behaviors in response to environmental and population cues. Thus, understanding how cells behave in the wild requires characterizing not only the behavior of isolated cells but also how environmental signals combine with cell-to-cell communication (such as quorum sensing and autocrine signaling to give rise to observed behaviors at the population level). Doing so requires us to examine how the cooperative behaviors of cell colonies differ from those of isolated cells and conversely, how the properties of single cells generate and explain the observed communal behavior. P Mehta 2010.
A particularly attractive system to study collective behaviors is provided by communicating cell populations that display rhythmic activities in the form of intracellular oscillations of signaling molecules or gene expression. Collective cellular oscillations play an important role in a wide variety of biological systems, ranging from neural systems to the social amoebae Dictyostelium discoideum, where synchronized oscillations lead starved cells to aggregate, to glycolytic and non-glycolytic oscillations in yeast populations, to oscillations in the pancreatic islets which control insulin secretion.
Bacteria have been synthetically engineered to exhibit collective oscillations e.g Danino et al 2010 engineered a genetic circuit in E. coli capable of generating synchronized oscillations in growing populations. One of the unique features of the system is that a population of cells, that in isolation is incapable of oscillating, exhibits collective oscillations when coupled using a quorum-sensing molecule. The genetic circuits utilized components of the naturally occurring quorum-sensing machinery in other bacterial species to induce a global coupling between cells. Systems that exhibit a cell-density dependent transition to collective oscillations that has been termed “dynamical quorum sensing”…. Collective oscillations emerge when the external concentration, or equivalently cell-density, exceeds some critical threshold. Thus, in dynamical quorum sensing, cell density information is encoded in the collective intracellular dynamical state of the entire population.
A key challenge facing researchers studying cellular rhythms is to relate the type of dynamical quorum sensing transition exhibited by a system to relevant microscopic details such as cell coupling. P Mehta 2010.
The above does not include a further model. Fritz London suggested that the application of superfluid like states to macro-molecules might explain the ability of large molecules to act as single units. Recently it has been found that in specific conditions, a simple shear of an active suspension of Escherichia coli displays a super-fluid like transition where the viscous resistance to shear vanishes. H M Lopez 2015.
Swarms and Self Organisation
Living systems provide many examples of self organisation by collective processes. Fish schools, bird clouds, wasp swarms, ant colonies, and colonies of certain types of unicellular organisms and bacteria, all self-organise in this way. Structures and organisations develop, not by action at the level of the individual, but rather by way of dynamic processes in which the individuals are strongly coupled to one another and behave as a collective ensemble. These are swarming phenomena in groups of self-propelled particles that locally exchange directional information. Paul Bourgine – 2010 .
A striking feature of this behaviour is that the same types of morphology often arise in spite of large differences in the size and nature of the individual unit. For example, star galaxies, hurricanes, New Mexico bat colonies, slime mould amoebae, and microtubules, all form spiral shapes. ..In fish schools, or bird clouds, tubular or tore-like morphologies occur. Striped arrangements often arise; when they do, they are nearly always the result of an outside external perturbation that induces a directional bias on the actions of the individual. For example, an insect nest may develop a striped morphology if it is exposed to an air current at some stage during its construction. J Tabony – 2007.
Far from Equilibrium
Since the 1930’s, certain theoreticians have proposed that some particular types of chemical or biochemical reactions might show non-linear dynamic properties by way of a coupling between reactive processes and molecular diffusion. Contrary to what is normally observed, they predicted that a chemical pattern comprised of periodic variations in the concentration of some of the reactants could spontaneously arise from an initially homogeneous solution. Structures of this type are called reaction-diffusion or Turing-like structures. They also go under the name of dissipative structures. The latter term was widely used by Prigogine and co-workers because a dissipation of chemical energy is required to drive and maintain the system sufficiently far-fromchemical equilibrium that self-organisation occurs. Even though such terms were not used at the time, what these theoreticians predicted was that biological self organisation could arise as an ’emergent’ phenomenon in a ‘complex’ system by molecular processes of reaction and diffusion. In addition to self-organisation, such reaction-diffusion systems can also show bifurcation properties. At a critical moment early in the process, the system may bifurcate between dynamic pathways leading to self organised states of different morphology. The presence of a small effect such as an external field, at a bifurcation point of the bistable type, can determine the morphology of the state that subsequently forms. Once the bifurcation has occurred, the system evolves progressively along the selected pathway to the pre-determined morphology. It behaves as though it retained a memory of the conditions prevailing at the bifurcation… The bifurcation point in any out-of equilibrium system, and at which point the system is sensitive to weak external fields coincides with a condition of instability in the homogenous state.J Tabony – 2007.
Reaction Diffusion and Phase Transition
Reaction-diffusion systems have also been used extensively in studies of self organization, development, and pattern formation principles in bacterial colonies.
For example, there is a large body of literature devoted to the mathematical modeling of aggregating Dictyostellium amoeba. Another important example is provided by Proteus mirabilis swarm colony development. The salient feature of the Proteus mirabilis colonies is the periodic character of their morphogenesis. These colonies undergo alternating phases of migration over the substrate and growth without change of the colony boundaries. These phases are called the swarming and consolidation phases respectively. GS Medvedev 2000.
Viscek observed that the swarm instability is a phase transition that separates chaotic randomness from complete alignment of particles. The system is subject to metastability and can persist for a long period of time in a phase which is not favoured by thermodynamic parameters.
Swarm models can be used to explore the relation of nonequilibrium phase transitions to at least three important issues encountered in artificial life. Firstly, that of emergence as complex adaptive behavior. Secondly, as an exploration of continuous phase transitions in biological systems. Lastly, to derive behavioral criteria for the evolution of collective behavior in social organisms. Mark M. Millonas 1993.
Reaction Diffusion, Circadian Rhythms, Cell Cycles, Redox, Growth
In a number of other postings on this site I have explored possible relationships between reaction diffusion, circadian rhythms, cell cycles, and redox, as drives of cellular and organ growth, and neural activity.
Circadian Rhythms are dissipative structures due to a negative feedback produced by a protein on the expression of its own gene (Goodwin, 1965; Hardin et al., 1990). They operate far-from- equilibrium and generate order spontaneously by exchanging energy with their external environment (Prigogine et al., 1974; Goldbeter, 2002; Lecarpentier et al., 2010). It is suggested that circadian rhythms and redox are providing the “timings and direction” needed to enable “swarm” behaviour in biological morphogenesis.
One species of commensal bacterium from the human gastrointestinal system, Enterobacter aerogenes, is sensitive to the neurohormone melatonin, which is secreted into the gastrointestinal lumen, and expresses circadian patterns of swarming and motility. Melatonin specifically increases the magnitude of swarming in cultures of E. aerogenes, but not in Escherichia coli or Klebsiella pneumoniae. The swarming appears to occur daily, and transformation of E. aerogenes with a flagellar motor-protein driven lux plasmid confirms a temperature-compensated circadian rhythm of luciferase activity, which is synchronized in the presence of melatonin. Jiffin K. Paulose 2016.
Social insects such as honeybees, ants, wasps and termites live in colonies consisting of up to a few million individuals who coordinate almost every aspect of their lives. The temporal coordination of their activities is thought to be important for efficient colony functioning and therefore colony fitness. The most intuitive aspect of their temporal coordination is synchronising their phase of activity (social entrainment). Honeybees show a colony level circadian rhythm that is maintained in constant light and can be phase-shifted as the rhythms of individual animals. The synchronization of individuals in insect societies is thought to be functionally significant because it improves colony efficiency..Temperature is an attractive time-giver for self-organized social synchronization. However it should be noted that while both scouts and forager bees look alike, research suggests that they represent stable subpopulations with distinctive patterns of gene expression in their brains. (See Liang, Z. S., et al. 9 March 2012).
Circadian driven behaviour (associated with the life-mating cycles of particular species) is also found in:
- some species of zooplankton, with the forming of swarms at dawn and dispersion at dusk,
- circadian rhythms have been identified in insect swarming (associated with mating) e.g in midges, cockroaches, fruitflies, and mosquitoes. Such rhythms might also be found in cicada.
The animals that feed on insects may also be effected by similar rhythms e.g Birds flocking together at dawn and dusk.
In Quorum Sensing, bacteria release diffusible signal molecules known as autoinducers, which by accumulating in the environment induce population-wide changes in gene expression…Modelling shows propagating waves of activation or deactivation of the QS circuit in a spatially extended colony, and the model equations possess a traveling wave solution….Analysis of the diffusivity dynamics also leads to an understanding of the swarming phase dynamics and the gradual transition to the consolidation phase that follows it. These analyses show that the concentrations at the beginning of the two phases naturally repeat in a time-periodic manner. JB Langebrake – 2014. Also see GS Medvedev 2000.
Timing, Collective Behaviour and Growth
In all vertebrate animals, the segmentation of the body plan proceeds during embryonic development in a process termed somitogenesis. During somitogenesis, the elongating body axis segments rhythmically and sequentially into somites, the precursors of vertebrae and ribs. Failure of proper segmentation, caused for instance by mutations, can give rise to birth defects such as congenital scoliosis. Somites are formed in characteristic time intervals from an unsegmented progenitor tissue, the presomitic mesoderm (PSM). The temporal regularity with which somites form has provoked the idea that a biological clock comprised of cellular oscillators coordinates the temporal progress of segmentation in the PSM. The so-called ‘clock-and-wavefront’ mechanism suggests that a wavefront at the anterior end of the PSM reads out the state of this clock and triggers the formation of a new segment upon each completed clock cycle. Indeed, patterns of oscillating gene expression have been found in the PSM of various vertebrates such as zebrafish, chick, mouse, frog, and snake. These patterns resemble traveling waves sweeping through the PSM and occur as a result of coordinated cellular oscillations in the concentration of gene products. Genetic oscillations are proposed to occur autonomously in single cells as a result of delayed autorepression of specific genes. DJ Jörg – 2015
2015-2016. This article merely joins up other peoples work into an overall system. These works have been referenced so it is clear that others have provided the individual pieces of evidence that have been used to shape a specific systems approach.