Critical-like self-organization and natural selection: Two facets of a single evolutionary process?

A Unified Genomic Mechanism of Cell-Fate Change

The purpose of our studies is to elucidate the nature of massive control of the whole genome expression with a particular emphasis on cell-fate change. The whole genome expression is coordinated by the emergence of a critical point (CP: a peculiar set of biphasic genes) with the genome acting as an integrated dynamical system. In response to stimuli, the genome expression self-organizes into local sub-, near-, and super-critical states, each exhibiting distinct collective behaviors with its center of mass acting as a local attractor, coexisting with the whole genome attractor (GA). The CP serves as the organizing center of cell-fate change, and its activation makes local perturbation to spread over the genome affecting GA. The activation of CP is in turn elicited by genes with elevated temporal variance (oscillating-mode genes), normally in charge to keep genome expression at pace with microenvironment fluctuations. When oscillation exceeds a given threshold, the CP synchronizes with the GA driving genome expression state transition. The expression synchronization wave invading the entire genome is fostered by the fusion-splitting dynamics of silencing pericentromere-associated heterochromatin domains and the consequent folding-unfolding transitions of transcribing euchromatin domains. The proposed mechanism is a unified step toward a time-evolutional transition theory of biological regulation.

Forest Climax Phenomenon: An Invariance of Scale

We can think of forests as multiscale multispecies networks, constantly evolving toward a climax or potential natural community—the successional process-pattern of natural regeneration that exhibits sensitivity to initial conditions. This is why I look into forest succession in light of the Red Queen hypothesis and focus on the key aspects of ecological self-organisation: dynamical criticality, evolvability and intransitivity. The idea of the review is that forest climax should be associated with habitat dynamics driven by a large continuum of ecologically equivalent time scales, so that the same ecological conclusions could be drawn statistically from any scale. A synthesis of the literature is undertaken in order to (1) present the framework for assessing habitat dynamics and (2) present the types of successional trajectories based on tree regeneration mode in forest gaps. In general, there are four types of successional trajectories within the process-pattern of forest regeneration that exhibits sensitivity to initial conditions: advance reproduction specialists, advance reproduction generalists, early reproduction generalists and early reproduction specialists. A successional trajectory is an expression of a fractal connectivity among certain patterns of natural regeneration in the multiscale multispecies networks of landscape habitats. Theoretically, the organically derived measures of pattern diversity, integrity and complexity, determined by the rates of recruitment, growth and mortality of forest tree species, are the means to test the efficacy of specific interventions to avert the disturbance-related decline in forest regeneration. That is of relevance to the emerging field of biocomplexity research.

Redefining Science: The Impact of Complexity on Theory Development in Social and Behavioral Research

Disciplinary differences in the development of scientific generalizations and explanations are reviewed in this article. The social and behavioral sciences have identified fewer laws, established fewer "paradigms," and developed "worse" theories than the physical sciences. We argue that the variability in the theoretical attainments of disciplines is due primarily to differences in the complexity of the topics studied. Accounts suggesting that differences in the maturity of disciplines are responsible for the variability are dismissed. In the study of complex phenomena, there is an extreme trade-off between generality and precision in which basic theories do not make the precise predictions needed for the development of applications and in which applied models are lacking in generality. The examination of proximal determinants and the generation of context-specific mathematical models are essential for prediction and application in complex disciplines. The impossibility of developing exacting theories of complex phenomena suggests that we need to redefine our conceptions of "good" and "bad" theories and "real" and "fake" science.

Biological conservation law as an emerging functionality in dynamical neuronal networks

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law-the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective.

A conceptual and computational framework for modelling and understanding the non-equilibrium gene regulatory networks of mouse embryonic stem cells

The capacity of pluripotent embryonic stem cells to differentiate into any cell type in the body makes them invaluable in the field of regenerative medicine. However, because of the complexity of both the core pluripotency network and the process of cell fate computation it is not yet possible to control the fate of stem cells. We present a theoretical model of stem cell fate computation that is based on Halley and Winkler’s Branching Process Theory (BPT) and on Greaves et al.’s agent-based computer simulation derived from that theoretical model. BPT abstracts the complex production and action of a Transcription Factor (TF) into a single critical branching process that may dissipate, maintain, or become supercritical. Here we take the single TF model and extend it to multiple interacting TFs, and build an agent-based simulation of multiple TFs to investigate the dynamics of such coupled systems. We have developed the simulation and the theoretical model together, in an iterative manner, with the aim of obtaining a deeper understanding of stem cell fate computation, in order to influence experimental efforts, which may in turn influence the outcome of cellular differentiation. The model used is an example of self-organization and could be more widely applicable to the modelling of other complex systems. The simulation based on this model, though currently limited in scope in terms of the biology it represents, supports the utility of the Halley and Winkler branching process model in describing the behaviour of stem cell gene regulatory networks. Our simulation demonstrates three key features: (i) the existence of a critical value of the branching process parameter, dependent on the details of the cistrome in question; (ii) the ability of an active cistrome to “ignite” an otherwise fully dissipated cistrome, and drive it to criticality; (iii) how coupling cistromes together can reduce their critical branching parameter values needed to drive them to criticality.

Pluripotent stem cells possess the capacity both to renew themselves indefinitely and to differentiate to any cell type in the body. Thus the ability to direct stem cell differentiation would have immense potential in regenerative medicine. There is a massive amount of biological data relevant to stem cells; here we exploit data relating to stem cell differentiation to help understand cell behaviour and complexity. These cells contain a dynamic, non-equilibrium network of genes regulated in part by transcription factors expressed by the network itself. Here we take an existing theoretical framework, Transcription Factor Branching Processes, which explains how these genetic networks can have critical behaviour, and can tip between low and full expression. We use this theory as the basis for the design and implementation of a computational simulation platform, which we then use to run a variety of simulation experiments, to gain a better understanding how these various transcription factors can combine, interact, and influence each other. The simulation parameters are derived from experimental data relating to the core factors in pluripotent stem cell differentiation. The simulation results determine the critical values of branching process parameters, and how these are modulated by the various interacting transcription factors.

Self-Organizing Global Gene Expression Regulated through Criticality: Mechanism of the Cell-Fate Change

BACKGROUND

A fundamental issue in bioscience is to understand the mechanism that underlies the dynamic control of genome-wide expression through the complex temporal-spatial self-organization of the genome to regulate the change in cell fate. We address this issue by elucidating a physically motivated mechanism of self-organization.

PRINCIPAL FINDINGS

Building upon transcriptome experimental data for seven distinct cell fates, including early embryonic development, we demonstrate that self-organized criticality (SOC) plays an essential role in the dynamic control of global gene expression regulation at both the population and single-cell levels. The novel findings are as follows: i) Mechanism of cell-fate changes: A sandpile-type critical transition self-organizes overall expression into a few transcription response domains (critical states). A cell-fate change occurs by means of a dissipative pulse-like global perturbation in self-organization through the erasure of initial-state critical behaviors (criticality). Most notably, the reprogramming of early embryo cells destroys the zygote SOC control to initiate self-organization in the new embryonal genome, which passes through a stochastic overall expression pattern. ii) Mechanism of perturbation of SOC controls: Global perturbations in self-organization involve the temporal regulation of critical states. Quantitative evaluation of this perturbation in terminal cell fates reveals that dynamic interactions between critical states determine the critical-state coherent regulation. The occurrence of a temporal change in criticality perturbs this between-states interaction, which directly affects the entire genomic system. Surprisingly, a sub-critical state, corresponding to an ensemble of genes that shows only marginal changes in expression and consequently are considered to be devoid of any interest, plays an essential role in generating a global perturbation in self-organization directed toward the cell-fate change.

CONCLUSION AND SIGNIFICANCE

'Whole-genome' regulation of gene expression through self-regulatory SOC control complements gene-by-gene fine tuning and represents a still largely unexplored non-equilibrium statistical mechanism that is responsible for the massive reprogramming of genome expression.

Scale-invariant entropy-based theory for dynamic ordering

Dynamically Ordered self-organized dissipative structure exists in various forms and at different scales. This investigation first introduces the concept of an isolated embedding system, which embeds an open system, e.g., dissipative structure and its mass and/or energy exchange with its surroundings. Thereafter, scale-invariant theoretical analysis is presented using thermodynamic principles for Order creation, existence, and destruction. The sustainability criterion for Order existence based on its structured mass and/or energy interactions with the surroundings is mathematically defined. This criterion forms the basis for the interrelationship of physical parameters during sustained existence of dynamic Order. It is shown that the sufficient condition for dynamic Order existence is approached if its sustainability criterion is met, i.e., its destruction path is blocked. This scale-invariant approach has the potential to unify the physical understanding of universal dynamic ordering based on entropy considerations.

Bibliometric Evidence for a Hierarchy of the Sciences

The hypothesis of a Hierarchy of the Sciences, first formulated in the 19(th) century, predicts that, moving from simple and general phenomena (e.g. particle dynamics) to complex and particular (e.g. human behaviour), researchers lose ability to reach theoretical and methodological consensus. This hypothesis places each field of research along a continuum of complexity and "softness", with profound implications for our understanding of scientific knowledge. Today, however, the idea is still unproven and philosophically overlooked, too often confused with simplistic dichotomies that contrast natural and social sciences, or science and the humanities. Empirical tests of the hypothesis have usually compared few fields and this, combined with other limitations, makes their results contradictory and inconclusive. We verified whether discipline characteristics reflect a hierarchy, a dichotomy or neither, by sampling nearly 29,000 papers published contemporaneously in 12 disciplines and measuring a set of parameters hypothesised to reflect theoretical and methodological consensus. The biological sciences had in most cases intermediate values between the physical and the social, with bio-molecular disciplines appearing harder than zoology, botany or ecology. In multivariable analyses, most of these parameters were independent predictors of the hierarchy, even when mathematics and the humanities were included. These results support a "gradualist" view of scientific knowledge, suggesting that the Hierarchy of the Sciences provides the best rational framework to understand disciplines' diversity. A deeper grasp of the relationship between subject matter's complexity and consensus could have profound implications for how we interpret, publish, popularize and administer scientific research.

Field-Control, Phase-Transitions, and Life's Emergence

Instances of critical-like characteristics in living systems at each organizational level (bio-molecules to ecosystems) as well as the spontaneous emergence of computation (Langton), do suggest the relevance of self-organized criticality (SOC). But extrapolating complex bio-systems to life's origins, brings up a paradox: how could simple organics - lacking the "soft-matter" response properties of today's complex bio-molecules - have dissipated energy from primordial reactions (eventually reducing CO(2)) in a controlled manner for their "ordering"? Nevertheless, a causal link of life's macroscopic irreversible dynamics to the microscopic reversible laws of statistical mechanics is indicated via the "functional-takeover" of a soft magnetic scaffold by organics (c.f. Cairns-Smith's "crystal-scaffold"). A field-controlled structure offers a mechanism for boot-strapping - bottom-up assembly with top-down control: its super-paramagnetic colloidal components obey reversible dynamics, but its dissipation of magnetic (H)-field energy for aggregation breaks time-reversal symmetry. The responsive adjustments of the controlled (host) mineral system to environmental changes would bring about mutual coupling between random organic sets supported by it; here the generation of long-range correlations within organic (guest) networks could include SOC-like mechanisms. And, such cooperative adjustments enable the selection of the functional configuration by altering the inorganic dipolar network's capacity to assist a spontaneous process. A non-equilibrium dynamics could now drive the kinetically oriented system (trimming the phase-space via sterically coupled organics) toward a series of phase-transitions with appropriate organic replacements "taking-over" its functions. Where available, experiments are cited in support of these speculations and for designing appropriate tests.

Self-organizing circuitry and emergent computation in mouse embryonic stem cells

Pluripotency is a cellular state of multiple options. Here, we highlight the potential for self-organization to contribute to stem cell fate computation. A new way of considering regulatory circuitry is presented that describes the expression of each transcription factor (TF) as a branching process that propagates through time, interacting and competing with others. In a single cell, the interactions between multiple branching processes generate a collective process called 'critical-like self-organization'. We explain how this phenomenon provides a valid description of whole genome regulatory circuit dynamics. The hypothesis of exploratory stem cell decision-making proposes that critical-like self-organization (also called rapid self-organized criticality) provides the backbone for cell fate computation in regulative embryos and pluripotent stem cells. Unspecific amplification of TF expression is predicted to initiate this self-organizing circuitry, where cascades of gene expression propagate and may interact either synergistically or antagonistically. The emergent and highly dynamic circuitry is affected by various sources of selection pressure, such as the expression of TFs with disproportionate influence over other genes, and extrinsic biological and physical stimuli that differentially modulate particular gene expression cascades. Extrinsic conditions continuously trigger waves of transcription that ripple throughout regulatory networks on multiple spatiotemporal scales, providing the context within which circuitry self-organizes. In this framework, a distinction between instructive and selective mechanisms of fate determination is misleading because it is the 'interference pattern', rather than any single instructing or selecting factor, that is ultimately responsible for computing and directing cell fate. Using this framework, we consider whether the idea of a naïve ground state of pluripotency and that of a fluctuating transcriptome are compatible, and whether a ground state like that captured in vitro could exist in vivo.

The developmental renaissance in adaptationism

From an adaptation perspective, unoccupied patches of morphological space are inferred to be empty because they are of low fitness and selected against. These inferences hinge on venturesome assumptions, because emptiness is explained by low fitness and low fitness is inferred from emptiness. Moreover, non-adaptive factors, such as developmental constraint, could also plausibly account for empty morphospace. In response, biologists increasingly study ontogeny to test the assumption that unobserved phenotypes could be produced if selection were to favor them; finding that empty space morphologies can be readily produced in development helps reject constraint and lends support to adaptive hypotheses. This developmental approach to adaptation calls on manifold techniques, including embryology, artificial selection and comparative methods. Belying their diversity, all of these methods examine the causes of empty morphospace and mark a return of development, long excluded from traditional evolutionary biology, to adaptationist practice.

Self-organization of developing embryo using scale-invariant approach

BACKGROUND

Self-organization is a fundamental feature of living organisms at all hierarchical levels from molecule to organ. It has also been documented in developing embryos.

METHODS

In this study, a scale-invariant power law (SIPL) method has been used to study self-organization in developing embryos. The SIPL coefficient was calculated using a centro-axial skew symmetrical matrix (CSSM) generated by entering the components of the Cartesian coordinates; for each component, one CSSM was generated. A basic square matrix (BSM) was constructed and the determinant was calculated in order to estimate the SIPL coefficient. This was applied to developing C. elegans during early stages of embryogenesis. The power law property of the method was evaluated using the straight line and Koch curve and the results were consistent with fractal dimensions (fd). Diffusion-limited aggregation (DLA) was used to validate the SIPL method.

RESULTS AND CONCLUSION

The fractal dimensions of both the straight line and Koch curve showed consistency with the SIPL coefficients, which indicated the power law behavior of the SIPL method. The results showed that the ABp sublineage had a higher SIPL coefficient than EMS, indicating that ABp is more organized than EMS. The fd determined using DLA was higher in ABp than in EMS and its value was consistent with type 1 cluster formation, while that in EMS was consistent with type 2.