Microbial intelligence

Microbial intelligence (popularly known as bacterial intelligence) is the intelligence shown by microorganisms. The concept encompasses complex adaptive behaviour shown by single cells, and altruistic and/or cooperative behavior in populations of like or unlike cells mediated by chemical signalling that induces physiological or behavioral changes in cells and influences colony structures.

Complex cells, like protozoa or algae, show remarkable abilities to organise themselves in changing circumstances.^[1] Shell-building by amoebae reveals complex discrimination and manipulative skills that are ordinarily thought to occur only in multicellular organisms.

Even bacteria, which show primitive behavior as isolated cells, can display more sophisticated behavior as a population. These behaviors occur in single species populations, or mixed species populations. Examples are colonies of myxobacteria, quorum sensing, and biofilms.

It has been suggested that a bacterial colony loosely mimics a biological neural network. The bacteria can take inputs in form of chemical signals, process them and then produce output chemicals to signal other bacteria in the colony.

The mechanisms that enable single celled organisms to coordinate in populations presumably carried over in those lines that evolved multicellularity, and were co-opted as mechanisms to coordinate multicellular organisms.

Bacteria communication and self-organization in the context of network theory has been investigated by Eshel Ben-Jacob research group at Tel Aviv University which developed a fractal model of bacterial colony and identified linguistic and social patterns in colony lifecycle^[2] (also see Ben-Jacob's bacteria).

Examples of microbial intelligence

The formation of biofilms requires joint decision by the whole colony.
Under nutritional stress bacterial colonies can organise themselves in such a way so as to maximise nutrient availability.
Bacteria reorganise themselves under antibiotic stress.
Bacteria can swap genes (such as genes coding antibiotic resistance) between members of mixed species colonies.
Individual cells of myxobacteria and cellular slime moulds coordinate to produce complex structures or move as multicellular entities.
Populations of bacteria use quorum sensing to judge their own densities and change their behaviors accordingly. This occurs in the formation of biofilms, infectious disease processes, and the light organs of bobtail squid.
For any bacterium to enter a host's cell, the cell must display receptors to which bacteria can adhere and be able to enter the cell. Some strains of E. coli are able to internalize themselves into a host's cell even without the presence of specific receptors as they bring their own receptor to which they then attach and enter the cell.
Under rough circumstances, some bacteria transform into endospores to resist heat and dehydration.
A huge array of microorganisms have the ability to overcome being recognized by the immune system as they change their surface antigens so that any defense mechanisms directed against previously present antigens are now useless with the newly expressed ones.

Bacterial colony optimization

The algorithm is based on a lifecycle model that simulates some typical behaviors of E. coli bacteria during their whole lifecycle, including chemotaxis, communication, elimination, reproduction, and migration.^[3]

References

^ Ford, Brian J. (2004). "Are Cells Ingenious?" (PDF). Microscope. 52 (3/4): 135–144.
^ Cohen, Inon; et al. (1999). "Continuous and discrete models of cooperation in complex bacterial colonies" (PDF). Fractals. 7.03 (1999):: 235–247.{{cite journal}}: CS1 maint: extra punctuation (link)
^ Niu, Ben (2012). "Bacterial colony optimization". Discrete Dynamics in Nature and Society. 2012 (Article ID 698057).

External links

[1] Ford, Brian J. (2004). "Are Cells Ingenious?" (PDF). Microscope. 52 (3/4): 135–144.

[2] Cohen, Inon; et al. (1999). "Continuous and discrete models of cooperation in complex bacterial colonies" (PDF). Fractals. 7.03 (1999):: 235–247.{{cite journal}}: CS1 maint: extra punctuation (link)

[3] Niu, Ben (2012). "Bacterial colony optimization". Discrete Dynamics in Nature and Society. 2012 (Article ID 698057).

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v t e Ecology: Modelling ecosystems: Trophic components
General	Abiotic component Abiotic stress Behaviour Biogeochemical cycle Biomass Biotic component Biotic stress Carrying capacity Competition Ecosystem Ecosystem ecology Ecosystem model Green world hypothesis Keystone species List of feeding behaviours Metabolic theory of ecology Productivity Resource Restoration
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Decomposers	Chemoorganoheterotrophy Decomposition Detritivores Detritus
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Defense, counter	Animal coloration Anti-predator adaptations Camouflage Deimatic behaviour Herbivore adaptations to plant defense Mimicry Plant defense against herbivory Predator avoidance in schooling fish

v t e Ecology: Modelling ecosystems: Other components
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Outline of ecology

v t e Swarming
Biological swarming	Agent-based model in biology Collective animal behavior Droving Flock flocking sort sol Herd herd behavior Locust Mixed-species foraging flock Mobbing behavior feeding frenzy Pack pack hunter Patterns of self-organization in ants ant mill symmetry breaking of escaping ants Shoaling and schooling bait ball Swarming behaviour Swarming (honey bee) Swarming motility
Animal migration	Animal migration altitudinal tracking history coded wire tag Bird migration flyways reverse migration Cell migration Fish migration diel vertical Lessepsian salmon run sardine run Homing natal philopatry Insect migration butterflies monarch Sea turtle migration
Swarm algorithms	Agent-based models Ant colony optimization Boids Crowd simulation Particle swarm optimization Swarm intelligence Swarm (simulation)
Collective motion	Active matter Collective motion Self-propelled particles clustering Vicsek model BIO-LGCA
Swarm robotics	Ant robotics Microbotics Nanorobotics Swarm robotics Symbrion
Related topics	Allee effect Animal navigation Collective intelligence Decentralised system Eusociality Group size measures Microbial intelligence Mutualism Predator satiation Quorum sensing Spatial organization Stigmergy Military swarming Task allocation and partitioning of social insects

Microbial intelligence

Examples of microbial intelligence

Bacterial colony optimization

See also

References

Further reading

External links