III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

2. A Consilience as Physics, Biology and People Become One

Fodor, Etienne and M. Cristina Marchetti. The Statistical Physics of Active Matter: From Self-Catalytic Colloids to Living Cells. arXiv:1708.08652. Some seven years since Sriram Ramaswamy (search) recognized and named this facility of organic physiologies to exhibit spontaneous formations traceable to physical forces, Cambridge University and Cornell University researchers provide a tutorial overview with 101 references of the now popular field, aka Soft Matter. I enter a day after hearing Dr. Marchetti speak at the University of Massachusetts, Amherst, second quote, where she reported on their common recurrence over a range of lively movements from tissue cultures and embryogenesis to starling flocks. An independent, universal source thus seems to be implied as interactive elements proceed to dynamically cooperate and self-organize. The third quote is a capsule for her Soft Matter Laboratory.

These lecture notes are designed to provide a brief introduction into the phenomenology of active matter and to present some of the analytical tools used to rationalize the emergent behavior of active systems. Such systems are made of interacting agents able to extract energy stored in the environment to produce sustained directed motion. The local conversion of energy into mechanical work drives the system far from equilibrium, yielding new dynamics and phases. The emerging phenomena can be classified depending on the symmetry of the active particles and on the type of microscopic interactions. We focus here on steric and aligning interactions, as well as interactions driven by shape changes. The models that we present are all inspired by experimental realizations of either synthetic, biomimetic or living systems. Based on minimal ingredients, they are meant to bring a simple and synthetic understanding of the complex phenomenology of active matter. (Abstract)

Collections of self-propelled entities, from living cells to engineered microswimmers, organize in a rich variety of active fluid and solid states, with unusual properties. For instance, active fluids can flow with no externally applied driving forces and active gases do not fill their container. In this talk I will describe the behavior of such “active materials” and highlight two examples of active phase transitions. The first is the formation of cohesive matter with no cohesive forces in collections of purely repulsive active colloids. The second is a new density-independent solid-liquid transition in epithelial tissues controlled by cell motility and a cell-shape parameter measuring the interplay of cortical tension and cell-cell adhesion. An important insight of this work is that cell shape correlates with the mechanical properties of living tissues. (MCM Presentation – U Mass Amherst, Sept. 13, 2017)

Our (MCM) group is interested in the emergent behavior of soft and biological materials that are driven out of equilibrium by an external drive, internal activity or quenched disorder. We use theory and computation to investigate the rich dynamics of a broad range of systems, from vibrated granular matter to bacterial suspensions, the cell cytoskeleton and living tissues. Our work makes complementary use of bottom-up modeling and top-down phenomenology to highlight the role of physical interactions relative to genetically and biochemically- regulated signaling in controlling the large scale structural organization and the mechanical properties of these complex systems. (https://mcmarche.expressions.syr.edu/)

Fort, Hugo. Statistical Mechanics Ideas and Techniques Applied to Selected Problems in Ecology. Entropy. Online December, 2013. A Universidad de la República, Uruguay, physicist and Complex Systems Group leader with international collaborations such as Marten Scheffer, contributes to a recent, growing trend to uncover deep consistencies between condensed matter principles and all areas of life’s organic and social evolution (e.g., search Moretti). In this case, three ecosystem features, as the Abstract explains, can be seen to take on quite similar forms to physical phenomena. By this overdue merger a worldwide systems project begins to reassemble the sciences and a common natural cosmos.

Ecosystem dynamics provides an interesting arena for the application of a plethora concepts and techniques from statistical mechanics. Here I review three examples corresponding each one to an important problem in ecology. First, I start with an analytical derivation of clumpy patterns for species relative abundances (SRA) empirically observed in several ecological communities involving a high number n of species, a phenomenon which have puzzled ecologists for decades. An interesting point is that this derivation uses results obtained from a statistical mechanics model for ferromagnets. Second, going beyond the mean field approximation, I study the spatial version of a popular ecological model involving just one species representing vegetation.

It is shown that different quantities—like the variance, the two-point correlation function and the patchiness—may serve as early warnings for the desertification of arid lands. Remarkably, in the onset of a desertification transition the distribution of vegetation patches exhibits scale invariance typical of many physical systems in the vicinity a phase transition. I comment on similarities of and differences between these catastrophic shifts and paradigmatic thermodynamic phase transitions like the liquid-vapor change of state for a fluid. Third, I analyze the case of many species interacting in space. I choose tropical forests, which are mega-diverse ecosystems that exhibit remarkable dynamics. Therefore these ecosystems represent a research paradigm both for studies of complex systems dynamics as well as to unveil the mechanisms responsible for the assembly of species-rich communities. The more classical equilibrium approaches are compared versus non-equilibrium ones and in particular I discuss a recently introduced cellular automaton model in which species compete both locally in physical space and along a niche axis. (Abstract excerpts)

Freeman, Walter, et al. Brain Dynamics, Chaos and Bessel Functions. Journal of Physics: Conference Series. 626/012069, 2015. A paper presented at the 7th International Workshop on Spacetime – Matter – Quantum Mechanics, September 2014, Castiglioncello, Italy. Walter Freeman is a UC Berkeley systems neuroscientist, now 88 years young, a third generation of a legendary family of brain researchers and physicians. Coauthors are Antonio Capolupo, Robert Kozma, Andres Olivares del Campo and Giuseppe Vitiello. (Bessel functions are complex differential equations, please Google.) We cite in this section for its representation of neural qualities in statistical physics and mathematical terms, which can show how much our own brains and thought are rooted in and a continuance of this cosmic cerebral essence. See also arXiv:1506.04393 for more.

A paper presented at the 7th International Workshop on Spacetime – Matter – Quantum Mechanics, September 2014, Castiglioncello, Italy. Walter Freeman is a UC Berkeley systems neuroscientist, now 88 years young, a third generation of a legendary family of brain researchers and physicians. Coauthors are Antonio Capolupo, Robert Kozma, Andres Olivares del Campo and Giuseppe Vitiello. (Bessel functions are complex differential equations, please Google.) We cite in this section for its representation of neural qualities in statistical physics and mathematical terms, which can show how much our own brains and thought are rooted in and a continuance of this cosmic cerebral essence. See also arXiv:1506.04393 for more.

Frey, Erwin and Tobias Reichenbach. Bacterial Games. Meyer-Ortmanns, Hildegard and Stefan Thurner, eds. Principles of Evolution: From the Planck Epoch to Complex Multicellular Life. Berlin: Springer, 2011. Ludwig-Maximilians-Universitat biophysicists view communal bacteria as an exemplar of interactive agent, nonlinear self-organization, to which an “evolutionary game theory” such as public goods games can then contribute. All this on-going phenomena is further seen as a facet of a “nonequilibrium physics.”

Microbial laboratory communities have become model systems for studying the complex interplay between nonlinear dynamics of evolutionary selection forces, stochastic fluctuations arising from the probabilistic nature of interactions, and spatial organization. Major research goals are to identify and understand mechanisms that ensure viability of microbial colonies by allowing for species diversity, cooperative behavior and other kinds of “social” behavior. A synthesis of evolutionary game theory, nonlinear dynamics, and the theory of stochastic processes provides the mathematical tools and conceptual framework for a deeper understanding of these ecological systems. We give an introduction to the modern formulation of these theories and illustrate their effectiveness, focusing on selected examples of microbial systems. (297)

Microbial systems are complex assemblies of large numbers of individuals, interacting competitively under multifaceted environmental conditions. Bacteria often grow in complex, dynamical communities, pervading the earth’s ecological systems, from hot springs to rivers and the human body. (298) The ensuing complexity of bacterial communities has conveyed the idea that they constitute “social groups,” where the coordinated action of individuals leads to various kinds of system-level functionalities. (298)

Gadiyaram, Vasundhara, et al. From Quantum Chemistry to Networks in Biology: A Graph Spectral Approach to Protein Structure Analyses. arXiv:1912.11609. Indian Institute of Science, Karnataka and University of Illinois, Urbana researchers provide a good example of the present integrative frontiers as 2020 science fulfills its stage of common unification from universe to humankinder.

This perspective presents a multidisciplinary characterization of protein structure networks. Our approach will be to synthesize concepts from quantum chemistry, polymer conformations, matrix mathematics, and percolation theory. We then construct protein networks in terms of non-covalently interacting amino acid side chains and to distill information from their graph spectra such as structural integrity. In conclusion, we suggest a further unifying approach to protein structure analyses for larger, more complex networks, such as metabolic and disease networks. (Abstract excerpt)

Garcia-Ojalvo, Jordi and Alfonso Martinex Arias. Towards a Statistical Mechanics of Cell Fate Decisions. Current Opinion in Genetics and Development. 22/6, 2012. In a special issue on the Genetics of System Biology (Briscoe), Pompeu Fabra University, Barcelona, and Cambridge University, UK biomedical researchers offer another example of affinities between biological and physical phenomena. By these insights, cellular dynamics can take on the guise of universal, critical phase transitions. A graphic image is used to depict parallels between the title domains. A notable surmise is that in both cases a stochastic variability on a micro level – say molecules or cells – will average out to a predictable macroscopic order. See also a cited paper Origin and Function of Fluctuations in Cell Behaviour and the Emergence of Patterns by Ana Mateus, et al in Seminars in Cell & Developmental Biology (20/877, 2009).

The spatiotemporal organization of a developing organism requires carefully orchestrated sequences of cellular differentiation events. These events are triggered by decisions made by individual cells about their fate, which are in turn controlled by gene and protein regulation processes. While these cell fate decisions are subject to stochasticity and are not reproducible at the single-cell level, they result in highly consistent, almost deterministic patterns at the level of the whole cell population. The question of how this macroscopic order arises from a disordered microscopic behaviour is still outstanding, and is reminiscent of problems in physical systems that are readily addressed by statistical mechanics. (Abstract)

Geyer, Delphine, et al. Freezing a Flock: Motility-Induced Phase Separation in Polar Active Liquids. Physical Review X.. 9/031043, 2019. University of Lyon and University of Paris researchers including Denis Bartolo deftly perceive in their experimental setup how particulate densities in a flowing stream seem to exhibit their an inherent propensity to transform into more organized groupings. The work merited an editorial Viewpoint: A Crowd Freezes Up which highlights deep affinities between physics and people.

Combining experiments and theory, we investigate the dense phases of polar active matter beyond the conventional flocking picture. We show that above a critical density flocks assembled from self-propelled colloids arrest their collective motion, lose their orientational order, and form solids that actively rearrange their local structure while continuously melting and freezing at their boundaries. We argue that the suppression of collective motion in the form of solid jams is a generic feature of flocks assembled from motile units that reduce their speed as density increases, a feature common to a broad class of active bodies, from synthetic colloids to living creatures. (Abstract)

Gilpin, William and Marcus Feldman. A Phase Transition Induces Chaos in a Predator-Prey Ecosystem with a Dynamic Fitness landscape. PLoS Computational Biology. July, 2017. A Stanford University physicist and a biologist contribute to later 2010s rootings of life’s creaturely development and eco-activities into a naturally conducive cosmos. As the Abstract cites, by this view statistical physical phenomena are manifestly in effect in evolutionary and environmental processes.

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the “edge of chaos” while creating a wide distribution of opportunities for speciation during epochs of disruptive selection. (Abstract)

Goldenfeld, Nigel and Carl Woese. Life is Physics: Evolution as a Collective Phenomenon Far from Equilibrium. Annual Review of Condensed Matter Physics. Volume 2, 2011. This extensive paper by a University of Illinois biophysicist and a microbiologist is one of the strongest statements of a much overdue reunion of these physical and animate realms. Carl Woese (1928-2012) was a premier biological theorist of the past half century. Credits say the paper was also vetted by Freeman Dyson, Barbara Drossel, James Shapiro, Leo Kadanoff, Michael Deem, and others. While these fields long co-existed as separate, contradictory domains, today as complexity science joins with statistical, many-body concepts, a grand synthesis is at hand. Section headings include Evolution as a Problem in Condensed Matter Physics, The Need for a Physics of Living Systems, Beyond the Modern Synthesis, and Is Evolution Random?. To wit “There is compelling evidence that not only may mutations be non-random, but horizontal gene transfer too need not be random.” As a consequence, more than another theory or model, a creative genesis universe seems on the implied horizon.

Apropos, I heard Nigel Goldenfeld speak at a University of Massachusetts, Amherst, physics colloquium on October 9, 2013 on “Collective Dynamics and Phase Transitions in Early Life: Clues to the Genetic Code.” He indeed advised, two days after the Nobel Prize for the Higgs boson, that “biology is the new condensed matter physics.” As a field that studies collective phenomena, life’s evolution ought to be seen more as an on-going “process.” From an initial regime of “horizontal gene transfer,” the molecular DNA version appears to be in an optimum form. In this physical sense then, a genome can be dubbed an “information-sharing protocol.” Might we imagine closure to a past century of necessary particle, relativity, and quantum phases, which has ran its course, and on cue a 21st century “systems physics” of matter come to life again? Goldenfeld tacitly alluded that life’s common genome is universally suitable because it has manifestly arisen from a conducive cosmos.

This review focuses on evolution as a problem in non-equilibrium statistical mechanics, where the key dynamical modes are collective, as evidenced by the plethora of mobile genetic elements whose role in shaping evolution has been revealed by modern genomic surveys. We discuss how condensed matter physics concepts might provide a useful perspective in evolutionary biology, the conceptual failings of the modern evolutionary synthesis, the open-ended growth of complexity, and the quintessentially self-referential nature of evolutionary dynamics. (Abstract)

With the growing recognition of the importance of collective phenomena in evolution,, but also in ecology, immunology, microbiology and even global climate change, it is timely to assess the extent to which a condensed matter physics perspective—with its unifying principles of collective behavior arising from interactions—can be illuminating in biology. Equally fascinating is the notion that biology may extend the frontier of non-equilibrium physics, revealing principles of self-organization that seem absent in purely physical processes such as pattern formation. (376)

Physics was able to delay serious consideration of collective effects for nearly 300 years, and only in the past 30 years or so has it confronted complex collective phenomena involving multiple scales of space and time, unpredictable dynamics, and large fluctuations. Biology was not so lucky: At its outset, complex phenomena were encountered, but tools were lacking to cope with the difficulty. Rather than abiding by ignorance, a language culture was developed to explain away the conceptual difficulties using guesswork solutions such as “natural selection.” Today the development of sophisticated technology has allowed biology to take refuge in single-molecule biophysics, genomics, and molecular biology. But the stultifying language culture still remains. This sanctuary is an illusionary respite: The core problems of biology remain irksome to some and are inextricably interwoven with evolution. Indeed, the very existence of biological phenomena is an expression of physical laws that represent a new asymptotic realm in nonequilibrium statistical physics. (392)

Hakim, Vincent and Pascal Silberzan. Collective Cell Migration: A Physics Perspective. Reports on Progress in Physics. 80/7, 2017. CNRS Research University, Paris biophysicists quantify how individual cells actually abide and move in a cohesive group phase manner.

Cells have traditionally been viewed either as independently moving entities or as somewhat static parts of tissues. However, it is now clear that in many cases, multiple cells coordinate their motions and move as collective entities. Well-studied examples comprise development events, as well as physiological and pathological situations. Different ex vivo model systems have also been investigated. Several recent advances have taken place at the interface between biology and physics, and have benefitted from progress in imaging and microscopy, from the use of microfabrication techniques, as well as from the introduction of quantitative tools and models. We review these interesting developments in quantitative cell biology that also provide rich examples of collective out-of-equilibrium motion. (Abstract)

Harder, Malte and Daniel Polani. Self-Organizing Particle Systems. Advances in Complex Systems. 16/2, 2013. Adaptive Systems Research Group, University of Hertfortshire computer scientists contribute another example of scientific reevaluations of the nature of cellular biology by way of the prior activity of self-organizing physical and informational processes.

The self-organization of cells into a living organism is a very intricate process. Under the surface of orchestrating regulatory networks there are physical processes which make the information processing possible, that is required to organize such a multitude of individual entities. We use a quantitative information theoretic approach to assess self-organization of a collective system. In particular, we consider an interacting particle system, that roughly mimics biological cells by exhibiting differential adhesion behavior. Employing techniques related to shape analysis, we show that these systems in most cases exhibit self-organization. Moreover, we consider spatial constraints of interactions, and additionally show that particle systems can self-organize without the emergence of pattern-like structures. However, we will see that regular pattern-like structures help to overcome limitations of self-organization that are imposed by the spatial structure of interactions. (Abstract)

Hauser, Marcus and Lutz Schimansky-Geier. Statistical Physics of Self-Propelled Particles. European Physical Journal Special Topics. 224/7, 2015. Otto von Guericke University, and Humboldt University biophysicists introduce an issue on realizations of a natural materiality that seems to exhibit biological behaviors. Papers include Active Particles in Heterogeneous Media Display New Physics, and The Unlikely High Efficiency of a Molecular Motor Based on Active Motion.

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