V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An EarthWinian Genesis Synthesis
2. Microbial Colonies
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).
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)
Aguilar-Trigueros, C. A., et al. Network Traits Predict Ecological Strategies in Fungi. ISME Communications. December, 2021. (Nature journal for microbial ecology.) Free University of Berlin, Cardiff University and Oxford University researchers contribute insightful perceptions of how these endemic interconnectivities are a prime formative factor for these colonial eukaryotes.
Colonization of terrestrial environments by filamentous fungi relies on their ability to form networks to connect resource patches and foster foraging. But these features have been difficult to quantify. Here we describe our work to translate images of fungal mycelia across micro- and macro-scales, to weighted network graphs to reveal fungal behaviour. Our view shows how fungi get resources, make connections, transport goods, and resist fungivores. Thus, we propose this approach represents a significant advance in quantifying ecological strategies for fungi using network information. (Abstract excerpt)
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.
Artiga, Marc. Bacterial Communication. Biology and Philosophy. 36/4, 2021. A University of Valencia, Spain natural philosopher advances our understandings about how this microbial phase persists by way of biosemiotic molecular cross-messaging. Aka quorum sensing, this active facility informs and sustains biofilm colonies within variable environs. With a copious bibliography in support, life’s prokaryotic stage is viewed an iconic exemplar a consistent recurrence in kind of cooperative qualities along with an emergent individuality, an episodic evolution thus courses to our Earthuman sapience which can lately proceed to reconstruct all this. Into the 2020s we peoples altogether be able to glimpse a grand phenomenal discovery and vista so to carry on forward?
Recent research on bacteria and other microorganisms has provided interesting insights into the nature of life, cooperation, evolution, individuality or species. In this paper, I focus on the capacity of bacteria to produce molecules that are usually classified as ’signals’ and I defend two claims. First, I argue that certain interactions between bacteria should actually qualify as genuine forms of communication. Second, I use this case study to revise our general theories of signaling. Among other things, I argue that a plausible requirement for a state to qualify as a signal is that it is a minimal cause. (Abstract)
Astacioa, Luis, et al. Closed Microbial Communities Self-Organize to Persistently Cycle Carbon. Proceedings of the National Academy of Sciences. 118/45, 2021. University of Illinois, Center for the Physics of Living Cells and University of Chicago, Center for the Physics of Evolving Systems researchers describe a robust tendency to spontaneously form a conserved set of metabolic processes. In regard, as the late Eshel Ben Jacob foresaw years ago, bacterial colonies can well serve as archetypal ecosystem exemplars.
Life on Earth depends on ecologically driven nutrient cycles to regenerate resources. Understanding how nutrient cycles emerge from a complex web of ecological processes is a central challenge in ecology. However, we lack model ecosystems that can be replicated, manipulated, and quantified in the laboratory, making it hard to quantify how changes in composition and the environment impact cycling. Enabled by a new high-precision method, we show that microbial ecosystems (CES) with only light self-organize can robustly cycle carbon. Our study helps establish CES as model biospheres for studying how ecosystems persistently cycle nutrients. (Significance)
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)
Beavan, Alan, et al. Contingency, repeatability, and predictability in the evolution of a prokaryotic pangenome. PNAS. 121/1, 2024. University of Nottingham life scientists describe an extensive AI-based analysis of a microbial species by which to discern a broadly recurrent consistency in effect. While the colonial complexity of bacteria would not seem to be an orderly process, deep down nature seems to be suffused by an inherent coherence.
Pangenomes exhibit remarkable variability in many prokaryotic species through horizontal gene transfer. In this study, we present a machine learning method that predicts the presence or absence of genes in the Escherichia coli pangenome based on complex patterns of other accessory genes within a genome. We find that the presence or absence of a substantial set of genes is highly predictable, indicating that selection maintains gene–gene co-occurrence over long-term bacterial evolution. Our findings indicate that intragenomic gene fitness effects may be key drivers of prokaryotic evolution, influencing the repeated emergence of complex gene–gene relationships across the pangenome. (Abstract)
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)