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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

3. Microbial Colonies

    Individual bacteria, such as the amoeba or paramecium we met in school, were long thought to act as isolated, competive entities. But as lately advised by the nonlinear theories, microbes are now understood to exist and prosper within social assemblies engaged in constant chemical dialogue. Such microbial communities are often seen as an exemplary model of a complex adaptive system. This image of a self-organizing bacterial community is from the website (http://star.tau.ac.il/~eshel/gallery.html) of the prime researcher in this regard Eshel Ben Jacob, Maguy-Glass Chair in Physics of Complex Systems at Tel Aviv University, Israel.


In 2000, an initial paper about biological phenomena was published in the Advances in Physics (49/4) journal, in print since 1952, namely Cooperative Self-Organization of Microorganisms by Eshel Ben Jacob, the late Israeli physicist, with Inon Cohen and Herbert Levine. The second lively paper in that physics publication was Biological Evolution and Statistical Physics by Barbara Drossel (50/2). As the image description notes, bacteria are no longer seen to exist in isolation but as communal exemplars of naturomic self-organizing, network forces. A notable trait is known as quorum sensing via chemical and/or electrical signals by which bacterial colonies of infinite kind “decide” what to do when perturbed or on the move (Bonnie Bassler).

2020: As this vastly basic, omnipresent prokaryote, bioflim phase gains all manner environmental, human microbiome, medical status and respect, it has become appreciated as an iconic model and occasion of life’s universal, self-organizing dynamics.

Allen, Rosalind and Bartlomiej Waclaw. Bacterial Growth: A Statistical Physicist’s Guide. Reports on Progress in Physics. 82/1, 2018.

Ben Jacob, Eshel. Social Behavior of Bacteria: From Physics to Complex Organization. European Physical Journal B. 65/3, 2008.

Cunha, Danilo, et al.Bacterial Colonies as Complex Adaptive Systems. Natural Computing. Online June, 2018.

Hahn, Aria, et al. The Information Science of Microbial Ecology. Current Opinion in Microbiology. 31/209, 2016.

Hussa, Elizabeth and Heidi Goodrich-Blair. It Takes a Village: Ecological and Fitness Impacts of Multipartite Mutualism. Annual Review of Microbiology. 67/161, 2013.

Lan, Ganhui and Yuhai Tu. Information Processing in Bacteria: Memory, Computation, and Statistical Physics. Reports on Progress in Physics. 79/5, 2016.

Sapp, Jan. The New Foundations of Evolution. Oxford: Oxford University Press, 2009.

Adamatzky, Andy, et al. On Creativity of Slime Mold. International Journal of General Systems. 42/5, 2013. Over past decades and years, against an academic ban on the projection of human traits to animal fauna, “anthropomorphic” validations are indeed being traced across creaturely kingdoms to their ancient evolutionary origins. Here University of the West of England, University of Greenwich, and University of Kobe, Japan, computational microbiologists find group living primordial bacteria to possess an intrinsic modicum of smart cohabitation. What is seen as amazing is that this bacterial, prokaryotic realm seems able to react and adapt on its own so as to survive and prosper. Section 2 is titled “Intelligence of Slime Molds and Morphological Meaning.”

Slime mould Physarum polycephalum is large single cell with intriguingly smart behaviour. The slime mould shows outstanding abilities to adapt its protoplasmic network to varying environmental conditions. The slime mould can solve tasks of computational geometry, image processing, logics and arithmetics when data are represented by configurations of attractants and repellents. We attempt to map behavioural patterns of slime onto the cognitive control versus schizotypy spectrum phase space and thus interpret slime mould's activity in terms of creativity. (Abstract)

Plasmodium's foraging behaviour can be interpreted as a computation as follows. Data are represented by spatial configurations of attractants and repellents. Results are represented by the structure of the protoplasmic network. Plasmodium can solve computational problems with natural parallelism, e.g. related to shortest path and hierarchies of planar proximity graphs, computation of plane tessellations, execution of logical computing schemes, planar shapes and concave hulls, and natural implementation of spatial logic and process algebra. (442)

Allen, Rosalind and Bartlomiej Waclaw. Bacterial Growth: A Statistical Physicist’s Guide. Reports on Progress in Physics. 82/1, 2018. University of Edinburgh researchers post a joint tutorial for microbiologists and physicists so as to illustrate new findings of persistent cross-affinities such as modularity and self-propelled activity.

Bacterial growth presents many beautiful phenomena that pose new theoretical challenges to statistical physicists, and are also amenable to laboratory experimentation. This review provides some of the essential biological background, discusses recent applications of statistical physics in this field, and highlights the potential for future research. (Abstract) In this review we argue that the dynamics of growing bacterial populations provides another class of systems to which the methods of statistical physics can naturally be applied. To briefly illustrate this, we notice that the above example of the growth of an antibiotic resistant infection involves stochastic phenomena on scale ranging from macroscopic to molecular. (1)

Almaas, E., et al. Global Organization of Metabolic Fluxes in the Bacterium Escherichia coli. Nature. 427/839, 2004. Which the authors take to indicate a universal scale-invariant, power-law topology in cellular metabolism networks.

Andrews, John. Bacteria as Modular Organisms. Annual Review of Microbiology. 52/105, 1998. A recurrent, iterative modularity is proposed to characterize microbial and cellular assemblies.

Armitage, Judith, et al. “Neural Networks” in Bacteria. Journal of Bacteriology. 187/1, 2005. A report about the May 2004 European Science Foundation conference on “Bacterial Neural Networks” held in San Feliu, Spain. Please compare this work with Stephen Read’s neural net model for human personality, as examples how this version of a complex adaptive system is being realized across disparate realms. All of which may infer our universe as a grand learning experience that we participate in.

Bassler, Bonnie. Cell to Cell Communication. Proceedings of the American Philosophical Society. 154/3, 2010. In a paper accessed together with Tom Misteli’s Scientific American genome article, the Princeton University biologist and finder of microbial “quorum sensing,” (see her Publications page) explains that by this emerging view of bacterial cooperation, as per the quote, microbes seem to be acting as if they know what needs to be done. As this phenomena is strikingly similar to Misteli’s cell nucleus, it might appear as if both domains are moved by the same self-organizing source.

What the bacteria are doing with this chemical language is counting one another, recognizing when they have a proper number of neighbors present, so that if they all act together, they will be able to accomplish tasks they could never accomplish if they simply acted as individuals. Using this chemical mechanism, bacteria are acting as a collective; in essence, the actions of these groups of cells are similar to the way groups of cells act together in multicellular organisms. Because bacteria have been here for billions of years, we now know that the ability to carry out collective behaviors is ancient. Thus, bacteria invented multicellularity long ago. (308)

Bassler, Bonnie. Small-Talk: Cell-to-Cell Communication in Bacteria. Cell. 109/4, 2003. The constant complementarity of autonomous individual and communal group is evident even in this prokaryotic phase.

In a process called quorum sensing, groups of bacteria communicate with one another to coordinate their behavior and function like a multicellular organism. A diverse array of secreted chemical signal molecules and signal detection apparatuses facilitate highly productive intra- and interspecies relationships. (421)

Ben Jacob, Eshel. Social Behavior of Bacteria: From Physics to Complex Organization. European Physical Journal B. 65/3, 2008. In a special issue on Ecological Complex Systems, Prof. Ben Jacob continues to explain how microbial communities both exemplify a universal self-organization, and in so doing, exhibit a modicum of responsive intelligence. Such proper understanding it is said will better aid drug design and agriculture.

I describe how bacteria develop complex colonial patterns by utilizing intricate communication capabilities, such as quorum sensing, chemotactic signaling and exchange of genetic information (plasmids) Bacteria do not store genetically all the information required for generating the patterns for all possible environments. Instead, additional information is cooperatively generated as required for the colonial organization to proceed. Each bacterium is, by itself, a biotic autonomous system with its own internal cellular informatics capabilities (storage, processing and assessments of information). (315)

Ben Jacob, Eshel, et al. Bacterial Linguistic Communication and Social Intelligence. Trends in Microbiology. 12/8, 2004. An update on the discovery that microbes not only live in self-organized, hierarchical, cooperative communities, but express a collective modicum of intelligence. We note once again that this prokaryotic realm provides an archetypal example of the universal complex system at work which persistently develops toward emergent, individual cognizance.

Ben-Jacob, Eshel. Bacterial Self-organization. Philosophical Transactions of the Royal Society of London A. 361/1283, 2003. Ben-Jacob further articulates how the busy microbes provide an exemplary expression of complex emergence at work. What is notable is that at this elementary phase, both for evolution and living systems, the incentive to organize into larger groups actually enhances the welfare of its members, a good example early on of creative union. In an Epilogue he goes on to suggest that cognitive processes are a similar case of self-generated, cooperative freedom.

The ‘smart’ bacteria have ‘realized’ (over evolution) that increasing informative communication between individuals results in increased freedom and cooperation of the individuals. (1285)

Ben-Jacob, Eshel. Bacterial Wisdom, Godel’s Theorem and Creative Genomic Webs. Physica A. 248/57, 1998. Tel Aviv University biologist Ben-Jacob is a pioneer in applying complexity principles to the microbial realm. The “complex colonial patterning as an example of adaptive self-organization” is seen to possess self-reference, information, and a modicum of awareness. As an assembly of microbes interact with “mutual dependence” through a common “language,” they give rise to a distinct communal “self.”

My proposed solution to the above paradox (Darwinism vs. Vitalism) leads to a new evolutionary picture where progress is not the result of successful accumulation of mistakes in replication of the genetic code, but is rather the outcome of designed creative processes. (58)

Ben-Jacob, Eshel. Learning from Bacteria about Natural Information Processing. Annals of the New York Academy of Science. Vol. 1178, 2009. In the edition Natural Genetic Engineering and Natural Genome Editing, an exemplary paper from the Tel Aviv University biophysicist upon how well microbial colonies imbue and epitomize complex, self-organizing, modular networks. By these reciprocities they achieve a modicum of social intelligence that displays a distributed, neural-like cognition and collective decision making, indeed a colonial “super-brain.”

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