V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An Earthtwinian Genesis Synthesis

2. Microbial Colonies

Canzian, Luca, et al. A Dynamic Network Formation Model for Understanding Bacterial Self-Organization into Micro-Colonies. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 1/1, 2015. UCLA bioengineers explain how microbes persistently form vital, adaptable communal groupings in varying environments. The general intent is to employ such understandings to achieve a “synthetic microbiology” for everyone’s betterment.

We propose a general parametrizable model to capture the dynamic interaction among bacteria in the formation of micro-colonies. Micro-colonies represent the first social step towards the formation of structured multicellular communities known as bacterial biofilms, which protect the bacteria against antimicrobials. In our model, bacteria can form links in the form of intercellular adhesins (such as polysaccharides) to collaborate in the production of resources that are fundamental to protect them against antimicrobials. We rigorously characterize some of the key properties of the network evolution depending on the parameters of the system. In particular, we derive the parameters under which it is guaranteed that all bacteria will join micro- colonies and the parameters under which it is guaranteed that some bacteria will not join micro-colonies. Importantly, our study does not only characterize the properties of networks emerging in equilibrium, but it also provides important insights on how the network dynamically evolves and on how the formation history impacts the emerging networks in equilibrium. (Abstract)

Cavalier-Smith, Thomas, et al. Introduction: How and When did Microbes Change the World? Philosophical Transactions of the Royal Society B. 361/843, 2006. This volume contains many papers from a Discussion Meeting on Major Steps in Cell Evolution: Palaeontological, Molecular and Cellular Evidence of their Timing and Global Effects.

Cepelewicz, Jordana. Bacterial Complexity Revises Ideas About ‘Which Came First?’. Quanta. Online June 12, 2019. A science writer conducts a wide survey of microbiologists such as Arash Komeili, Damien Devos, Michael Rout, Mark Field, Kate Adamala (see her lab page), Joel Dacks, and Anthony Poole about revolutionary rethinkings in this field about the appearance, composition and import of prokaryotic and eukaryotic microbial cells. With a main reference to Ectosymbiotic Bacteria at the Origin of Magnetoreception in a Marine Protist by Caroline Monteil, et al in Nature Microbiology (4/1088, 2019), once more a formative symbiosis is in effect everywhere.

Chen, Chong, et al. Weak Synchronization and Large-Scale Collective Oscillation in Dense Bacterial Suspensions. Nature. 542/210, 2017. Chinese University of Hong Kong, Soochow University, and University Paris-Saclay (Hugues Chate) computational microbiologists achieve a clever discernment by way of physical, active matter, principles of how inherent self-organizational tendencies serve microbial assemblies. A science report, Swirling Bacteria Linked to the Physics of Phase Transitions by Gabriel Popkin in Quanta Magazine (May 2017), notes this advance and allies it with findings by Tamas Vicsek (search) and others of how condensed matter phenomena can meld with living, communal systems.

Collective oscillatory behaviour is ubiquitous in nature, having a vital role in many biological processes from embryogenesis and organ development to pace-making in neuron networks4. Elucidating the mechanisms that give rise to synchronization is essential to the understanding of biological self-organization. Collective oscillations in biological multicellular systems often arise from long-range coupling mediated by diffusive chemicals, by electrochemical mechanisms, or by biomechanical interaction between cells and their physical environment. Here, in contrast, we report the discovery of a weak synchronization mechanism that does not require long-range coupling or inherent oscillation of individual cells. We find that millions of motile cells in dense bacterial suspensions can self-organize into highly robust collective oscillatory motion, while individual cells move in an erratic manner, without obvious periodic motion but with frequent, abrupt and random directional changes. On such large scales, the oscillations appear to be in phase and the mean position of cells typically describes a regular elliptic trajectory. We present a model of noisy self-propelled particles with strictly local interactions that accounts faithfully for our observations, suggesting that self-organized collective oscillatory motion results from spontaneous chiral and rotational symmetry breaking. These findings reveal a previously unseen type of long-range order in active matter systems (those in which energy is spent locally to produce non-random motion). (Abstract excerpts)

Chen, Xiao, et al. Scale-Invariant Correlations in Dynamic Bacterial Clusters. Physical Review Letters. 108/148101, 2012. An international cluster from Shanghai Jiao Tong University, Ben-Gurion University of the Negev, and University of Texas, Austin, (Harry Swinney) continue forth to quantify in this archetypal microbial realm the ubiquitous presence of nature’s self-organizing, iterative universality.

In Bacillus subtilis colonies, motile bacteria move collectively, spontaneously forming dynamic clusters. These bacterial clusters share similarities with other systems exhibiting polarized collective motion, such as bird flocks or fish schools. Here we study experimentally how velocity and orientation fluctuations within clusters are spatially correlated. For a range of cell density and cluster size, the correlation length is shown to be 30% of the spatial size of clusters, and the correlation functions collapse onto a master curve after rescaling the separation with correlation length. Our results demonstrate that correlations of velocity and orientation fluctuations are scale invariant in dynamic bacterial clusters. (Abstract)

Collective motion can be found in systems of self-propelled objects ranging from flocking birds and fish schools to vibrating granular matter and even to the microscopic scale of swarming bacteria and molecular motors. Despite differences in length scales and the cognitive abilities of constituent individuals, collective motion in these systems produces similar patterns of extended spatiotemporal coherence, suggesting general principles of collective motion. (148101)

Copeland, Matthew and Douglas Weibel. Bacterial Swarming: A Model system for Studying Dynamic Self-Assembly. Soft Matter. 5/1174, 2009. A new journal from the Royal Society of Chemistry with this subtitle: “Where Physics meets Chemistry meets Biology for Fundamental Soft Matter Research.” University of Wisconsin biochemists provide a succinct tutorial for the on-going turn from discrete, isolate bacteria to a recognition and explanation of their pervasive communality.

Bacterial Swarming is an example of dynamic self-assembly in microbiology in which the collective interaction of a population of bacterial cells leads to emergent behavior. Swarming occurs when cells interact with surfaces, reprogram their physiology and behavior, and adapt to changes in their environment by coordinating their growth and motility with other cells in the colony. (1174)

Cordero, Otto, et al. Ecological Populations of Bacteria Act as Socially Cohesive Units of Antibiotic Production and Resistance. Science. 337/1228, 2012. MIT, Insititut Français de Recherche pour l’Exploitation de la Mer, and Woods Hole Oceanographic Institution, marine microbiologists achieve a deft quantification of how microbes form cooperative groupings that vie and compete with other colonies, similar to macro-organisms. A review “Microbial Cooperative Warfare” by Helene Morlon in the same issue notes the quality and import of this work.

In animals and plants, social structure can reduce conflict within populations and bias aggression toward competing populations; however, for bacteria in the wild it remains unknown whether such population-level organization exists. Here, we show that environmental bacteria are organized into socially cohesive units in which antagonism occurs between rather than within ecologically defined populations. By screening approximately 35,000 possible mutual interactions among Vibrionaceae isolates from the ocean, we show that genotypic clusters known to have cohesive habitat association also act as units in terms of antibiotic production and resistance. Genetic analyses show that within populations, broad-range antibiotics are produced by few genotypes, whereas all others are resistant, suggesting cooperation between conspecifics. Natural antibiotics may thus mediate competition between populations rather than solely increase the success of individuals. (Abstract)

Crespi, Bernard. The Evolution of Social Behavior in Microorganisms. Trends in Ecology & Evolution. 16/4, 2001. The systemic processes of modular division of labor, cooperation, chemical talk, and so on are found through sophisticated studies to occur in microbial societies just the same as in animal communities. Here is an example of convergent social phenomena across widely separated scales.

Cooperation and division of labor involving microbiology, ecology, and evolutionary theory should lead to accelerated progress in understanding social worlds both large and small. (182)

Cunha, Danilo, et al. Bacterial Colonies as Complex Adaptive Systems. Natural Computing. Online June, 2018. As the quotes convey, Mackenzie Presbyterian University (Google) and National Computing and Machine Learning Laboratory, Sao Paulo, biomathematicians Cunha, Rafael Xavier and Leandro de Castro (search) post a succinct summary of a 21st century scientific revolution as embodied by this iconic phase. Firstly, nature’s nonlinear dynamic propensities are reviewed so to perceive a universal recurrence via dual modes of individual components (nodes) and their communicative interactions (links), which altogether compose a viable CAS. Circa 2018, as in many other areas, a mutual reciprocity of entity and community is strongly evident. By this integral view, olden Darwinian selection is expanded and completed to include intrinsic, generative self-organizing qualities. In 2006 Leandro de Castro wrote Fundamentals of Natural Computing as a copious text to date of this visionary project (CRC Press, search). A dozen years later, as this sites tries to document, an emergent sapiensphere appears on the verge of qualifying a genesis evolutionary synthesis, not a moment too soon.

The present work explores bacterial colonies and their individual and social behaviours under the lens of complex adaptive systems. We initially provide a background on the biology of bacteria to describe important phenomena, such as quorum-sensing, individual and collective behaviours, adaptation, evolution and self-organization over the influence of mechanical effects on bacterial systems and connecting scales. We then explore some associations between bacterial colonies and complex adaptive systems by considering components and ownerships of self-organization. The main contribution of this paper places emphasis on individual decision-making and behaviour as a cause of bacterial colonies’ actions, i.e., how self-organization and collective behaviours impact the ability of a bacterial colony to address an environmental stimulus and maintain itself as an open biological and fault-tolerant system. (Abstract)

In the Darwinian view of the world, complexity is built only from natural selection, a blind and non-guided force, whilst in the Spencerian view, complexity is an inevitable manifestation of the system and is guided by an internal dynamic of complex systems: heterogeneity based on homogeneity and order from chaos. The Science of Complexity combines elements from internal and external forces, and an increased complexity emerges as a fundamental property of complex dynamical systems. Bacterial systems, being complex adaptive systems, can, through selection and local interactions, lead to the edge of chaos in a search for the information processing ability of the colony. (1)

Complex adaptive systems as well as bacterial colonies are systems involving many components able to adapt themselves or learn as they interact via their constituent parts or with the environment. In this paper, we try to show how CAS and bacterial colonies self-organize within a pool of environmental resources and constraints. Our approach relies on individual and collective decision-making to (1) improve the system, as the whole must be optimal in the same step; (2) deal with conflicting interests; (3) protect itself against intrusion; and (4) adapt, evolve, learn and organize. The individual decision-making is as crucial as collective decision-making and interactions to emergent patterns and self-organization births. (2, edits)

Davidson, Carla and Michael Surette. Individuality in Bacteria. Annual Review of Genetics. 42/253, 2008. While microbes are commonly perceived to act in large populations, a degree of autonomy for discrete prokaryotes, based on genetic attributes, can equally be discerned.

Diggle, Stephen, et al. Quorum Sensing. Current Biology. 17/21, 2007. University of Nottingham biologists provide a succinct tutorial on the discovery that microbes engage in constant chemical communication as they achieve viable biofilms and colonies.

If we examine more complex environments like the rhizosphere, where many different, quorum-sensing signal producing bacteria co-exist, it would be easy to imagine the existence of a highly complex intercellular quorum sensing-driven signaling network which enables these poly-microbial communities to maintain an ecological balance. (R909)

Dinet, Celine, et al. Linking Single-Cell Decisions to Collective Behaviors in Social Bacteria. Philosophical Transactions of the Royal Society B. Volume 1820, January, 2021. In this Basal Cognition issue, CNRS-Aix-Marseille University, Turing Center for Living Systems, find evidence even at this unitary phase of cognitive and communicative processes which serve reproduction and survival, akin to all other organismic domains.

Social bacteria display complex behaviours whereby thousands of cells collectively change their form and function in response to nutrient availability and environmental conditions. In this review, we focus on Myxococcus xanthus motility, which supports transitions based on access to prey across its life cycle. A large body of work suggests that these behaviours require sensory capacity at the single-cell level. Focusing on recent genetic work on a core cellular pathway required for single-cell directional decisions, we argue that signal integration, multi-modal sensing and memory are at the root of decision making leading to multicellular behaviours. (Abstract excerpt)

Myxococcus Xanthus is a gram-negative, rod-shaped species of myxobacteria that exhibits various forms of self-organizing behavior in response to environmental cues. Under normal conditions with abundant food, it exists as a predatory, saprophytic single-species biofilm called a swarm.

The Turing Centre for Living Systems (CENTURI) is an interdisciplinary project located in Marseille (France). CENTURI aims at developing an integrated interdisciplinary community, to decipher the complexity of biological systems through the understanding of how biological function emerges from the organization and dynamics of living systems.

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