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Fruleux A, Hong L, Roeder AHK, Li CB, Boudaoud A. Growth couples temporal and spatial fluctuations of tissue properties during morphogenesis. Proc Natl Acad Sci U S A 2024; 121:e2318481121. [PMID: 38814869 PMCID: PMC11161797 DOI: 10.1073/pnas.2318481121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 04/27/2024] [Indexed: 06/01/2024] Open
Abstract
Living tissues display fluctuations-random spatial and temporal variations of tissue properties around their reference values-at multiple scales. It is believed that such fluctuations may enable tissues to sense their state or their size. Recent theoretical studies developed specific models of fluctuations in growing tissues and predicted that fluctuations of growth show long-range correlations. Here, we elaborated upon these predictions and we tested them using experimental data. We first introduced a minimal model for the fluctuations of any quantity that has some level of temporal persistence or memory, such as concentration of a molecule, local growth rate, or mechanical property. We found that long-range correlations are generic, applying to any such quantity, and that growth couples temporal and spatial fluctuations, through a mechanism that we call "fluctuation stretching"-growth enlarges the length scale of variation of this quantity. We then analyzed growth data from sepals of the model plant Arabidopsis and we quantified spatial and temporal fluctuations of cell growth using the previously developed cellular Fourier transform. Growth appears to have long-range correlations. We compared different genotypes and growth conditions: mutants with lower or higher response to mechanical stress have lower temporal correlations and longer-range spatial correlations than wild-type plants. Finally, we used theoretical predictions to merge experimental data from all conditions and developmental stages into a unifying curve, validating the notion that temporal and spatial fluctuations are coupled by growth. Altogether, our work reveals kinematic constraints on spatiotemporal fluctuations that have an impact on the robustness of morphogenesis.
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Affiliation(s)
- Antoine Fruleux
- Reproduction et Développement des Plantes, Université de Lyon, Ecole normale supérieure de Lyon, Université Claude Bernard Lyon 1, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, CNRS, 69364Lyon Cedex 07, France
- Laboratoire d’Hydrodynamique, CNRS, Ecole polytechnique, Institut Polytechnique de Paris, 91128Palaiseau Cedex, France
- Laboratoire de Physique Théorique et Modèles Statistiques, CNRS, Université Paris-Saclay, 91405Orsay, France
| | - Lilan Hong
- Institute of Nuclear Agricultural Sciences, Key Laboratory of Nuclear Agricultural Sciences of Ministry of Agriculture and Zhejiang Province, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou310058, Zhejiang, China
| | - Adrienne H. K. Roeder
- Weill Institute for Cell and Molecular Biology and Section of Plant Biology, School of Integrative Plant Science, Cornell University, Ithaca, NY14853
| | - Chun-Biu Li
- Department of Mathematics, Stockholm University, 106 91Stockholm, Sweden
| | - Arezki Boudaoud
- Reproduction et Développement des Plantes, Université de Lyon, Ecole normale supérieure de Lyon, Université Claude Bernard Lyon 1, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, CNRS, 69364Lyon Cedex 07, France
- Laboratoire d’Hydrodynamique, CNRS, Ecole polytechnique, Institut Polytechnique de Paris, 91128Palaiseau Cedex, France
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2
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Tower J. Selectively advantageous instability in biotic and pre-biotic systems and implications for evolution and aging. FRONTIERS IN AGING 2024; 5:1376060. [PMID: 38818026 PMCID: PMC11137231 DOI: 10.3389/fragi.2024.1376060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/15/2024] [Indexed: 06/01/2024]
Abstract
Rules of biology typically involve conservation of resources. For example, common patterns such as hexagons and logarithmic spirals require minimal materials, and scaling laws involve conservation of energy. Here a relationship with the opposite theme is discussed, which is the selectively advantageous instability (SAI) of one or more components of a replicating system, such as the cell. By increasing the complexity of the system, SAI can have benefits in addition to the generation of energy or the mobilization of building blocks. SAI involves a potential cost to the replicating system for the materials and/or energy required to create the unstable component, and in some cases, the energy required for its active degradation. SAI is well-studied in cells. Short-lived transcription and signaling factors enable a rapid response to a changing environment, and turnover is critical for replacement of damaged macromolecules. The minimal gene set for a viable cell includes proteases and a nuclease, suggesting SAI is essential for life. SAI promotes genetic diversity in several ways. Toxin/antitoxin systems promote maintenance of genes, and SAI of mitochondria facilitates uniparental transmission. By creating two distinct states, subject to different selective pressures, SAI can maintain genetic diversity. SAI of components of synthetic replicators favors replicator cycling, promoting emergence of replicators with increased complexity. Both classical and recent computer modeling of replicators reveals SAI. SAI may be involved at additional levels of biological organization. In summary, SAI promotes replicator genetic diversity and reproductive fitness, and may promote aging through loss of resources and maintenance of deleterious alleles.
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Affiliation(s)
- John Tower
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA, United States
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3
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Nikolić M, Antonetti V, Liu F, Muhaxheri G, Petkova MD, Scheeler M, Smith EM, Bialek W, Gregor T. Scale invariance in early embryonic development. ARXIV 2023:arXiv:2312.17684v1. [PMID: 38235065 PMCID: PMC10793483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
The body plan of the fruit fly is determined by the expression of just a handful of genes. We show that the spatial patterns of expression for several of these genes scale precisely with the size of the embryo. Concretely, discrete positional markers such as the peaks in striped patterns have absolute positions along the anterior-posterior axis that are proportional to embryo length, with better than 1% accuracy. Further, the information (in bits) that graded patterns of expression provide about position can be decomposed into information about fractional or scaled position and information about absolute position or embryo length; all of the available information is about scaled position, again with ~ 1% accuracy. These observations suggest that the underlying genetic network exhibits scale invariance in a deeper mathematical sense. Taking this mathematical statement seriously requires that the network dynamics have a zero mode, which connects to many other observations on this system.
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Affiliation(s)
- Miloš Nikolić
- Joseph Henry Laboratories of Physics and Princeton University, Princeton NJ 08544 USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton NJ 08544 USA
| | - Victoria Antonetti
- Joseph Henry Laboratories of Physics and Princeton University, Princeton NJ 08544 USA
- Center for Quantitative Biology and School of Physics, Peking University, Beijing 100871 China
| | - Feng Liu
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton NJ 08544 USA
- Center for Quantitative Biology and School of Physics, Peking University, Beijing 100871 China
| | - Gentian Muhaxheri
- Joseph Henry Laboratories of Physics and Princeton University, Princeton NJ 08544 USA
- Department of Physics, Lehman College, City University of New York, Bronx, NY 10468 USA
| | | | - Martin Scheeler
- Joseph Henry Laboratories of Physics and Princeton University, Princeton NJ 08544 USA
| | - Eric M Smith
- Joseph Henry Laboratories of Physics and Princeton University, Princeton NJ 08544 USA
| | - William Bialek
- Joseph Henry Laboratories of Physics and Princeton University, Princeton NJ 08544 USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton NJ 08544 USA
- Initiative for the Theoretical Sciences, The Graduate Center, City University of New York, 365 Fifth Ave., New York, NY 10016 USA
| | - Thomas Gregor
- Joseph Henry Laboratories of Physics and Princeton University, Princeton NJ 08544 USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton NJ 08544 USA
- Department of Developmental and Stem Cell Biology UMR3738, Institut Pasteur, 75015 Paris, France
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4
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Lefebvre M, Colen J, Claussen N, Brauns F, Raich M, Mitchell N, Fruchart M, Vitelli V, Streichan SJ. Learning a conserved mechanism for early neuroectoderm morphogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.22.573058. [PMID: 38187670 PMCID: PMC10769415 DOI: 10.1101/2023.12.22.573058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Morphogenesis is the process whereby the body of an organism develops its target shape. The morphogen BMP is known to play a conserved role across bilaterian organisms in determining the dorsoventral (DV) axis. Yet, how BMP governs the spatio-temporal dynamics of cytoskeletal proteins driving morphogenetic flow remains an open question. Here, we use machine learning to mine a morphodynamic atlas of Drosophila development, and construct a mathematical model capable of predicting the coupled dynamics of myosin, E-cadherin, and morphogenetic flow. Mutant analysis shows that BMP sets the initial condition of this dynamical system according to the following signaling cascade: BMP establishes DV pair-rule-gene patterns that set-up an E-cadherin gradient which in turn creates a myosin gradient in the opposite direction through mechanochemical feedbacks. Using neural tube organoids, we argue that BMP, and the signaling cascade it triggers, prime the conserved dynamics of neuroectoderm morphogenesis from fly to humans.
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Mim MS, Knight C, Zartman JJ. Quantitative insights in tissue growth and morphogenesis with optogenetics. Phys Biol 2023; 20:061001. [PMID: 37678266 PMCID: PMC10594237 DOI: 10.1088/1478-3975/acf7a1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 08/15/2023] [Accepted: 09/07/2023] [Indexed: 09/09/2023]
Abstract
Cells communicate with each other to jointly regulate cellular processes during cellular differentiation and tissue morphogenesis. This multiscale coordination arises through the spatiotemporal activity of morphogens to pattern cell signaling and transcriptional factor activity. This coded information controls cell mechanics, proliferation, and differentiation to shape the growth and morphogenesis of organs. While many of the molecular components and physical interactions have been identified in key model developmental systems, there are still many unresolved questions related to the dynamics involved due to challenges in precisely perturbing and quantitatively measuring signaling dynamics. Recently, a broad range of synthetic optogenetic tools have been developed and employed to quantitatively define relationships between signal transduction and downstream cellular responses. These optogenetic tools can control intracellular activities at the single cell or whole tissue scale to direct subsequent biological processes. In this brief review, we highlight a selected set of studies that develop and implement optogenetic tools to unravel quantitative biophysical mechanisms for tissue growth and morphogenesis across a broad range of biological systems through the manipulation of morphogens, signal transduction cascades, and cell mechanics. More generally, we discuss how optogenetic tools have emerged as a powerful platform for probing and controlling multicellular development.
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Affiliation(s)
- Mayesha Sahir Mim
- Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, United States of America
| | - Caroline Knight
- Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, United States of America
| | - Jeremiah J Zartman
- Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, United States of America
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Ngampruetikorn V, Nemenman I, Schwab DJ. Extrinsic vs Intrinsic Criticality in Systems with Many Components. ARXIV 2023:arXiv:2309.13898v1. [PMID: 37808085 PMCID: PMC10557788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Biological systems with many components often exhibit seemingly critical behaviors, characterized by atypically large correlated fluctuations. Yet the underlying causes remain unclear. Here we define and examine two types of criticality. Intrinsic criticality arises from interactions within the system which are fine-tuned to a critical point. Extrinsic criticality, in contrast, emerges without fine tuning when observable degrees of freedom are coupled to unobserved fluctuating variables. We unify both types of criticality using the language of learning and information theory. We show that critical correlations, intrinsic or extrinsic, lead to diverging mutual information between two halves of the system, and are a feature of learning problems, in which the unobserved fluctuations are inferred from the observable degrees of freedom. We argue that extrinsic criticality is equivalent to standard inference, whereas intrinsic criticality describes fractional learning, in which the amount to be learned depends on the system size. We show further that both types of criticality are on the same continuum, connected by a smooth crossover. In addition, we investigate the observability of Zipf's law, a power-law rank-frequency distribution often used as an empirical signature of criticality. We find that Zipf's law is a robust feature of extrinsic criticality but can be nontrivial to observe for some intrinsically critical systems, including critical mean-field models We further demonstrate that models with global dynamics, such as oscillatory models, can produce observable Zipf's law without relying on either external fluctuations or fine tuning. Our findings suggest that while possible in theory, fine tuning is not the only, nor the most likely, explanation for the apparent ubiquity of criticality in biological systems with many components. Our work offers an alternative interpretation in which criticality, specifically extrinsic criticality, results from the adaptation of collective behavior to external stimuli.
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Affiliation(s)
- Vudtiwat Ngampruetikorn
- Initiative for the Theoretical Sciences, The Graduate Center, CUNY, New York, New York 10016, USA
| | - Ilya Nemenman
- Department of Physics, Department of Biology, and Initiative in Theory and Modeling of Living Systems, Emory University, Atlanta, Georgia 30322, USA
| | - David J. Schwab
- Initiative for the Theoretical Sciences, The Graduate Center, CUNY, New York, New York 10016, USA
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7
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Hallatschek O, Datta SS, Drescher K, Dunkel J, Elgeti J, Waclaw B, Wingreen NS. Proliferating active matter. NATURE REVIEWS. PHYSICS 2023; 5:1-13. [PMID: 37360681 PMCID: PMC10230499 DOI: 10.1038/s42254-023-00593-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/02/2023] [Indexed: 06/28/2023]
Abstract
The fascinating patterns of collective motion created by autonomously driven particles have fuelled active-matter research for over two decades. So far, theoretical active-matter research has often focused on systems with a fixed number of particles. This constraint imposes strict limitations on what behaviours can and cannot emerge. However, a hallmark of life is the breaking of local cell number conservation by replication and death. Birth and death processes must be taken into account, for example, to predict the growth and evolution of a microbial biofilm, the expansion of a tumour, or the development from a fertilized egg into an embryo and beyond. In this Perspective, we argue that unique features emerge in these systems because proliferation represents a distinct form of activity: not only do the proliferating entities consume and dissipate energy, they also inject biomass and degrees of freedom capable of further self-proliferation, leading to myriad dynamic scenarios. Despite this complexity, a growing number of studies document common collective phenomena in various proliferating soft-matter systems. This generality leads us to propose proliferation as another direction of active-matter physics, worthy of a dedicated search for new dynamical universality classes. Conceptual challenges abound, from identifying control parameters and understanding large fluctuations and nonlinear feedback mechanisms to exploring the dynamics and limits of information flow in self-replicating systems. We believe that, by extending the rich conceptual framework developed for conventional active matter to proliferating active matter, researchers can have a profound impact on quantitative biology and reveal fascinating emergent physics along the way.
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Affiliation(s)
- Oskar Hallatschek
- Departments of Physics and Integrative Biology, University of California, Berkeley, CA US
- Peter Debye Institute for Soft Matter Physics, Leipzig University, Leipzig, Germany
| | - Sujit S. Datta
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ USA
| | | | - Jörn Dunkel
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Jens Elgeti
- Theoretical Physics of Living Matter, Institute of Biological Information Processing, Forschungszentrum Jülich, Jülich, Germany
| | - Bartek Waclaw
- Dioscuri Centre for Physics and Chemistry of Bacteria, Institute of Physical Chemistry PAN, Warsaw, Poland
- School of Physics and Astronomy, The University of Edinburgh, JCMB, Edinburgh, UK
| | - Ned S. Wingreen
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ USA
- Department of Molecular Biology, Princeton University, Princeton, NJ USA
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8
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Avchaciov K, Antoch MP, Andrianova EL, Tarkhov AE, Menshikov LI, Burmistrova O, Gudkov AV, Fedichev PO. Unsupervised learning of aging principles from longitudinal data. Nat Commun 2022; 13:6529. [PMID: 36319638 PMCID: PMC9626636 DOI: 10.1038/s41467-022-34051-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 10/06/2022] [Indexed: 11/07/2022] Open
Abstract
Age is the leading risk factor for prevalent diseases and death. However, the relation between age-related physiological changes and lifespan is poorly understood. We combined analytical and machine learning tools to describe the aging process in large sets of longitudinal measurements. Assuming that aging results from a dynamic instability of the organism state, we designed a deep artificial neural network, including auto-encoder and auto-regression (AR) components. The AR model tied the dynamics of physiological state with the stochastic evolution of a single variable, the "dynamic frailty indicator" (dFI). In a subset of blood tests from the Mouse Phenome Database, dFI increased exponentially and predicted the remaining lifespan. The observation of the limiting dFI was consistent with the late-life mortality deceleration. dFI changed along with hallmarks of aging, including frailty index, molecular markers of inflammation, senescent cell accumulation, and responded to life-shortening (high-fat diet) and life-extending (rapamycin) treatments.
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Affiliation(s)
| | - Marina P Antoch
- Department of Pharmacology and Therapeutics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | | | | | | | | | - Andrei V Gudkov
- Genome Protection, Inc., Buffalo, NY, USA
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
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9
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Latent space of a small genetic network: Geometry of dynamics and information. Proc Natl Acad Sci U S A 2022; 119:e2113651119. [PMID: 35737842 PMCID: PMC9245618 DOI: 10.1073/pnas.2113651119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
The high-dimensional character of most biological systems presents genuine challenges for modeling and prediction. Here we propose a neural network-based approach for dimensionality reduction and analysis of biological gene expression data, using, as a case study, a well-known genetic network in the early Drosophila embryo, the gap gene patterning system. We build an autoencoder compressing the dynamics of spatial gap gene expression into a two-dimensional (2D) latent map. The resulting 2D dynamics suggests an almost linear model, with a small bare set of essential interactions. Maternally defined spatial modes control gap genes positioning, without the classically assumed intricate set of repressive gap gene interactions. This, surprisingly, predicts minimal changes of neighboring gap domains when knocking out gap genes, consistent with previous observations. Latent space geometries in maternal mutants are also consistent with the existence of such spatial modes. Finally, we show how positional information is well defined and interpretable as a polar angle in latent space. Our work illustrates how optimization of small neural networks on medium-sized biological datasets is sufficiently informative to capture essential underlying mechanisms of network function.
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10
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Ngampruetikorn V, Sachdeva V, Torrence J, Humplik J, Schwab DJ, Palmer SE. Inferring couplings in networks across order-disorder phase transitions. PHYSICAL REVIEW RESEARCH 2022; 4:023240. [PMID: 37576946 PMCID: PMC10421637 DOI: 10.1103/physrevresearch.4.023240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Statistical inference is central to many scientific endeavors, yet how it works remains unresolved. Answering this requires a quantitative understanding of the intrinsic interplay between statistical models, inference methods, and the structure in the data. To this end, we characterize the efficacy of direct coupling analysis (DCA) - a highly successful method for analyzing amino acid sequence data-in inferring pairwise interactions from samples of ferromagnetic Ising models on random graphs. Our approach allows for physically motivated exploration of qualitatively distinct data regimes separated by phase transitions. We show that inference quality depends strongly on the nature of data-generating distributions: optimal accuracy occurs at an intermediate temperature where the detrimental effects from macroscopic order and thermal noise are minimal. Importantly our results indicate that DCA does not always outperform its local-statistics-based predecessors; while DCA excels at low temperatures, it becomes inferior to simple correlation thresholding at virtually all temperatures when data are limited. Our findings offer insights into the regime in which DCA operates so successfully, and more broadly, how inference interacts with the structure in the data.
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Affiliation(s)
- Vudtiwat Ngampruetikorn
- Initiative for the Theoretical Sciences, The Graduate Center, CUNY, New York, New York 10016, USA
| | - Vedant Sachdeva
- Department of Organismal Biology and Anatomy and Department of Physics, University of Chicago, Chicago, Illinois 60637, USA
| | - Johanna Torrence
- Department of Organismal Biology and Anatomy and Department of Physics, University of Chicago, Chicago, Illinois 60637, USA
| | - Jan Humplik
- Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria
| | - David J Schwab
- Initiative for the Theoretical Sciences, The Graduate Center, CUNY, New York, New York 10016, USA
| | - Stephanie E Palmer
- Department of Organismal Biology and Anatomy and Department of Physics, University of Chicago, Chicago, Illinois 60637, USA
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11
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Emergent phenomena in living systems: A statistical mechanical perspective. J Biosci 2022. [DOI: 10.1007/s12038-021-00247-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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12
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Abstract
Biological systems display a rich phenomenology of states that resemble the physical states of matter - solid, liquid and gas. These phases result from the interactions between the microscopic constituent components - the cells - that manifest in macroscopic properties such as fluidity, rigidity and resistance to changes in shape and volume. Looked at from such a perspective, phase transitions from a rigid to a flowing state or vice versa define much of what happens in many biological processes especially during early development and diseases such as cancer. Additionally, collectively moving confluent cells can also lead to kinematic phase transitions in biological systems similar to multi-particle systems where the particles can interact and show sub-populations characterised by specific velocities. In this Perspective we discuss the similarities and limitations of the analogy between biological and inert physical systems both from theoretical perspective as well as experimental evidence in biological systems. In understanding such transitions, it is crucial to acknowledge that the macroscopic properties of biological materials and their modifications result from the complex interplay between the microscopic properties of cells including growth or death, neighbour interactions and secretion of matrix, phenomena unique to biological systems. Detecting phase transitions in vivo is technically difficult. We present emerging approaches that address this challenge and may guide our understanding of the organization and macroscopic behaviour of biological tissues.
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Affiliation(s)
- Pierre-François Lenne
- Aix Marseille Univ, CNRS, UMR 7288, IBDM, Turing Center for Living Systems, Marseille, France.
| | - Vikas Trivedi
- European Molecular Biology Laboratory (EMBL), Barcelona, 08003, Spain.
- EMBL Heidelberg, Developmental Biology Unit, Heidelberg, 69117, Germany.
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olde Scheper TV. Controlled bio-inspired self-organised criticality. PLoS One 2022; 17:e0260016. [PMID: 35073308 PMCID: PMC8786161 DOI: 10.1371/journal.pone.0260016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 10/29/2021] [Indexed: 11/26/2022] Open
Abstract
Complex biological systems are considered to be controlled using feedback mechanisms. Reduced systems modelling has been effective to describe these mechanisms, but this approach does not sufficiently encompass the required complexity that is needed to understand how localised control in a biological system can provide global stable states. Self-Organised Criticality (SOC) is a characteristic property of locally interacting physical systems, which readily emerges from changes to its dynamic state due to small nonlinear perturbations. These small changes in the local states, or in local interactions, can greatly affect the total system state of critical systems. It has long been conjectured that SOC is cardinal to biological systems, that show similar critical dynamics, and also may exhibit near power-law relations. Rate Control of Chaos (RCC) provides a suitable robust mechanism to generate SOC systems, which operates at the edge of chaos. The bio-inspired RCC method requires only local instantaneous knowledge of some of the variables of the system, and is capable of adapting to local perturbations. Importantly, connected RCC controlled oscillators can maintain global multi-stable states, and domains where power-law relations may emerge. The network of oscillators deterministically stabilises into different orbits for different perturbations, and the relation between the perturbation and amplitude can show exponential and power-law correlations. This can be considered to be representative of a basic mechanism of protein production and control, that underlies complex processes such as homeostasis. Providing feedback from the global state, the total system dynamic behaviour can be boosted or reduced. Controlled SOC can provide much greater understanding of biological control mechanisms, that are based on distributed local producers, with remote consumers of biological resources, and globally defined control.
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Affiliation(s)
- Tjeerd V. olde Scheper
- School of Engineering, Computing and Mathematics, Oxford Brookes University, Wheatley Campus, Oxford, United Kingdom
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14
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Abstract
Dormancy is an evolutionarily conserved protective mechanism widely observed in nature. A pathological example is found during cancer metastasis, where cancer cells disseminate from the primary tumor, home to secondary organs, and enter a growth-arrested state, which could last for decades. Recent studies have pointed toward the microenvironment being heavily involved in inducing, preserving, or ceasing this dormant state, with a strong focus on identifying specific molecular mechanisms and signaling pathways. Increasing evidence now suggests the existence of an interplay between intracellular as well as extracellular biochemical and mechanical cues in guiding such processes. Despite the inherent complexities associated with dormancy, proliferation, and growth of cancer cells and tumor tissues, viewing these phenomena from a physical perspective allows for a more global description, independent from many details of the systems. Building on the analogies between tissues and fluids and thermodynamic phase separation concepts, we classify a number of proposed mechanisms in terms of a thermodynamic metastability of the tumor with respect to growth. This can be governed by interaction with the microenvironment in the form of adherence (wetting) to a substrate or by mechanical confinement of the surrounding extracellular matrix. By drawing parallels with clinical and experimental data, we advance the notion that the local energy minima, or metastable states, emerging in the tissue droplet growth kinetics can be associated with a dormant state. Despite its simplicity, the provided framework captures several aspects associated with cancer dormancy and tumor growth.
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15
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Rigidity transitions in development and disease. Trends Cell Biol 2022; 32:433-444. [DOI: 10.1016/j.tcb.2021.12.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 12/15/2021] [Accepted: 12/16/2021] [Indexed: 11/21/2022]
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16
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Manicka S, Marques-Pita M, Rocha LM. Effective connectivity determines the critical dynamics of biochemical networks. J R Soc Interface 2022; 19:20210659. [PMID: 35042384 PMCID: PMC8767216 DOI: 10.1098/rsif.2021.0659] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 12/02/2021] [Indexed: 11/12/2022] Open
Abstract
Living systems comprise interacting biochemical components in very large networks. Given their high connectivity, biochemical dynamics are surprisingly not chaotic but quite robust to perturbations-a feature C.H. Waddington named canalization. Because organisms are also flexible enough to evolve, they arguably operate in a critical dynamical regime between order and chaos. The established theory of criticality is based on networks of interacting automata where Boolean truth values model presence/absence of biochemical molecules. The dynamical regime is predicted using network connectivity and node bias (to be on/off) as tuning parameters. Revising this to account for canalization leads to a significant improvement in dynamical regime prediction. The revision is based on effective connectivity, a measure of dynamical redundancy that buffers automata response to some inputs. In both random and experimentally validated systems biology networks, reducing effective connectivity makes living systems operate in stable or critical regimes even though the structure of their biochemical interaction networks predicts them to be chaotic. This suggests that dynamical redundancy may be naturally selected to maintain living systems near critical dynamics, providing both robustness and evolvability. By identifying how dynamics propagates preferably via effective pathways, our approach helps to identify precise ways to design and control network models of biochemical regulation and signalling.
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Affiliation(s)
- Santosh Manicka
- Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, USA
- Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal
| | - Manuel Marques-Pita
- Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, USA
- Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal
- Universidade Lusófona, CICANT and COPELABS, Campo Grande 388, 1700-097 Lisbon, Portugal
| | - Luis M. Rocha
- Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, USA
- Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal
- Binghamton University, State University of New York, Binghamton, NY, USA
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17
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Hu L, Rech J, Bouet JY, Liu J. Spatial control over near-critical-point operation ensures fidelity of ParABS-mediated DNA partition. Biophys J 2021; 120:3911-3924. [PMID: 34418367 PMCID: PMC8511131 DOI: 10.1016/j.bpj.2021.08.022] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 06/26/2021] [Accepted: 08/13/2021] [Indexed: 01/20/2023] Open
Abstract
In bacteria, most low-copy-number plasmid and chromosomally encoded partition systems belong to the tripartite ParABS partition machinery. Despite the importance in genetic inheritance, the mechanisms of ParABS-mediated genome partition are not well understood. Combining theory and experiment, we provided evidence that the ParABS system-DNA partitioning in vivo via the ParA-gradient-based Brownian ratcheting-operates near a transition point in parameter space (i.e., a critical point), across which the system displays qualitatively different motile behaviors. This near-critical-point operation adapts the segregation distance of replicated plasmids to the half length of the elongating nucleoid, ensuring both cell halves to inherit one copy of the plasmids. Further, we demonstrated that the plasmid localizes the cytoplasmic ParA to buffer the partition fidelity against the large cell-to-cell fluctuations in ParA level. The spatial control over the near-critical-point operation not only ensures both sensitive adaptation and robust execution of partitioning but also sheds light on the fundamental question in cell biology: how do cells faithfully measure cellular-scale distance by only using molecular-scale interactions?
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Affiliation(s)
- Longhua Hu
- Center for Cell Dynamics, Department of Cell Biology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jérôme Rech
- Laboratoire de Microbiologie et Génétique Moléculaires, Centre de Biologie Intégrative, Centre National de la Recherche Scientifique, Université de Toulouse, UPS, Toulouse, France
| | - Jean-Yves Bouet
- Laboratoire de Microbiologie et Génétique Moléculaires, Centre de Biologie Intégrative, Centre National de la Recherche Scientifique, Université de Toulouse, UPS, Toulouse, France.
| | - Jian Liu
- Center for Cell Dynamics, Department of Cell Biology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
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18
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Abstract
The temporal coordination of events at cellular and tissue scales is essential for the proper development of organisms, and involves cell-intrinsic processes that can be coupled by local cellular signalling and instructed by global signalling, thereby creating spatial patterns of cellular states that change over time. The timing and structure of these patterns determine how an organism develops. Traditional developmental genetic methods have revealed the complex molecular circuits regulating these processes but are limited in their ability to predict and understand the emergent spatio-temporal dynamics. Increasingly, approaches from physics are now being used to help capture the dynamics of the system by providing simplified, generic descriptions. Combined with advances in imaging and computational power, such approaches aim to provide insight into timing and patterning in developing systems.
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19
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Moulia B, Douady S, Hamant O. Fluctuations shape plants through proprioception. Science 2021; 372:372/6540/eabc6868. [PMID: 33888615 DOI: 10.1126/science.abc6868] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Plants constantly experience fluctuating internal and external mechanical cues, ranging from nanoscale deformation of wall components, cell growth variability, nutating stems, and fluttering leaves to stem flexion under tree weight and wind drag. Developing plants use such fluctuations to monitor and channel their own shape and growth through a form of proprioception. Fluctuations in mechanical cues may also be actively enhanced, producing oscillating behaviors in tissues. For example, proprioception through leaf nastic movements may promote organ flattening. We propose that fluctuation-enhanced proprioception allows plant organs to sense their own shapes and behave like active materials with adaptable outputs to face variable environments, whether internal or external. Because certain shapes are more amenable to fluctuations, proprioception may also help plant shapes to reach self-organized criticality to support such adaptability.
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Affiliation(s)
- Bruno Moulia
- Université Clermont Auvergne, INRAE, PIAF, 63000 Clermont-Ferrand, France.
| | - Stéphane Douady
- Laboratoire Matières et Systèmes Complexes (MSC), Université de Paris, CNRS, 75205 Paris Cedex 13, France.
| | - Olivier Hamant
- Laboratoire de Reproduction et Développement des Plantes, Université de Lyon, ENS de Lyon, UCB Lyon 1, CNRS, INRAE, 69007 Lyon, France.
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20
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Petridou NI, Corominas-Murtra B, Heisenberg CP, Hannezo E. Rigidity percolation uncovers a structural basis for embryonic tissue phase transitions. Cell 2021; 184:1914-1928.e19. [PMID: 33730596 PMCID: PMC8055543 DOI: 10.1016/j.cell.2021.02.017] [Citation(s) in RCA: 78] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 12/09/2020] [Accepted: 02/04/2021] [Indexed: 12/15/2022]
Abstract
Embryo morphogenesis is impacted by dynamic changes in tissue material properties, which have been proposed to occur via processes akin to phase transitions (PTs). Here, we show that rigidity percolation provides a simple and robust theoretical framework to predict material/structural PTs of embryonic tissues from local cell connectivity. By using percolation theory, combined with directly monitoring dynamic changes in tissue rheology and cell contact mechanics, we demonstrate that the zebrafish blastoderm undergoes a genuine rigidity PT, brought about by a small reduction in adhesion-dependent cell connectivity below a critical value. We quantitatively predict and experimentally verify hallmarks of PTs, including power-law exponents and associated discontinuities of macroscopic observables. Finally, we show that this uniform PT depends on blastoderm cells undergoing meta-synchronous divisions causing random and, consequently, uniform changes in cell connectivity. Collectively, our theoretical and experimental findings reveal the structural basis of material PTs in an organismal context.
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Affiliation(s)
| | | | | | - Edouard Hannezo
- Institute of Science and Technology Austria, Klosterneuburg, Austria.
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21
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Klamser PP, Romanczuk P. Collective predator evasion: Putting the criticality hypothesis to the test. PLoS Comput Biol 2021; 17:e1008832. [PMID: 33720926 PMCID: PMC7993868 DOI: 10.1371/journal.pcbi.1008832] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 03/25/2021] [Accepted: 02/24/2021] [Indexed: 11/19/2022] Open
Abstract
According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the "criticality hypothesis", appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the "criticality hypothesis", but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality.
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Affiliation(s)
- Pascal P. Klamser
- Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Pawel Romanczuk
- Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
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22
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Oro D, Freixas L. Flickering body temperature anticipates criticality in hibernation dynamics. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201571. [PMID: 33614089 PMCID: PMC7890501 DOI: 10.1098/rsos.201571] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 12/14/2020] [Indexed: 05/25/2023]
Abstract
Hibernation has been selected for increasing survival in harsh climatic environments. Seasonal variability in temperature may push the body temperatures of hibernating animals across boundaries of alternative states between euthermic temperature and torpor temperature, typical of either hibernation or summer dormancy. Nowadays, wearable electronics present a promising avenue to assess the occurrence of criticality in physiological systems, such as body temperature fluctuating between attractors of activity and hibernation. For this purpose, we deployed temperature loggers on two hibernating edible dormice for an entire year and under Mediterranean climate conditions. Highly stochastic body temperatures with sudden switches over time allowed us to assess the reliability of statistical leading indicators to anticipate tipping points when approaching a critical transition. Hibernation dynamics showed flickering, a phenomenon occurring when a system rapidly moves back and forth between two alternative attractors preceding the upcoming major regime shift. Flickering of body temperature increased when the system approached bifurcations, which were also anticipated by several metric- and model-based statistical indicators. Nevertheless, some indicators did not show a pattern in their response, which suggests that their performance varies with the dynamics of the biological system studied. Gradual changes in air temperature drove transient between states of hibernation and activity, and also drove hysteresis. For hibernating animals, hysteresis may increase resilience when ending hibernation earlier than the optimal time, which may occur in regions where temperatures are sharply rising, especially during winter. Temporal changes in early indicators of critical transitions in hibernation dynamics may help to understand the effects of climate on evolutionary life histories and the plasticity of hibernating organisms to cope with shortened hibernation due to global warming.
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Affiliation(s)
- Daniel Oro
- Theoretical and Computational Ecology Laboratory, CEAB Center for Advanced Studies (CSIC), Acces Cala Sant Francesc 14, 17300 Blanes, Spain
| | - Lídia Freixas
- Granollers Natural Sciences Museum, Francesc Macià 51, 08402 Granollers, Spain
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23
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Vennettilli M, Erez A, Mugler A. Multicellular sensing at a feedback-induced critical point. Phys Rev E 2020; 102:052411. [PMID: 33327087 DOI: 10.1103/physreve.102.052411] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 10/06/2020] [Indexed: 11/07/2022]
Abstract
Feedback in sensory biochemical networks can give rise to bifurcations in cells' behavioral response. These bifurcations share many properties with thermodynamic critical points. Evidence suggests that biological systems may operate near these critical points, but the functional benefit of doing so remains poorly understood. Here we investigate a simple biochemical model with nonlinear feedback and multicellular communication to determine if criticality provides a functional benefit in terms of the ability to gain information about a stochastic chemical signal. We find that when signal fluctuations are slow, the mutual information between the signal and the intracellular readout is maximized at criticality, because the benefit of high signal susceptibility outweighs the detriment of high readout noise. When cells communicate, criticality gives rise to long-range correlations in readout molecule number among cells. Consequently, we find that communication increases the mutual information between a given cell's readout and the spatial average of the signal across the population. Finally, we find that both with and without communication, the sensory benefits of criticality compete with critical slowing down, such that the information rate, as opposed to the information itself, is minimized at the critical point. Our results reveal the costs and benefits of feedback-induced criticality for multicellular sensing.
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Affiliation(s)
- Michael Vennettilli
- Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana 47907, USA
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - Amir Erez
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
- The Racah Institute of Physics, Hebrew University, Jerusalem 91904, Israel
| | - Andrew Mugler
- Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana 47907, USA
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
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24
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Tsai A, Galupa R, Crocker J. Robust and efficient gene regulation through localized nuclear microenvironments. Development 2020; 147:147/19/dev161430. [PMID: 33020073 DOI: 10.1242/dev.161430] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Developmental enhancers drive gene expression in specific cell types during animal development. They integrate signals from many different sources mediated through the binding of transcription factors, producing specific responses in gene expression. Transcription factors often bind low-affinity sequences for only short durations. How brief, low-affinity interactions drive efficient transcription and robust gene expression is a central question in developmental biology. Localized high concentrations of transcription factors have been suggested as a possible mechanism by which to use these enhancer sites effectively. Here, we discuss the evidence for such transcriptional microenvironments, mechanisms for their formation and the biological consequences of such sub-nuclear compartmentalization for developmental decisions and evolution.
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Affiliation(s)
- Albert Tsai
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Rafael Galupa
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Justin Crocker
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
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25
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Min B. Interplay between degree and Boolean rules in the stability of Boolean networks. CHAOS (WOODBURY, N.Y.) 2020; 30:093121. [PMID: 33003927 DOI: 10.1063/5.0014191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 08/26/2020] [Indexed: 06/11/2023]
Abstract
Empirical evidence has revealed that biological regulatory systems are controlled by high-level coordination between topology and Boolean rules. In this study, we look at the joint effects of degree and Boolean functions on the stability of Boolean networks. To elucidate these effects, we focus on (1) the correlation between the sensitivity of Boolean variables and the degree and (2) the coupling between canalizing inputs and degree. We find that negatively correlated sensitivity with respect to local degree enhances the stability of Boolean networks against external perturbations. We also demonstrate that the effects of canalizing inputs can be amplified when they coordinate with high in-degree nodes. Numerical simulations confirm the accuracy of our analytical predictions at both the node and network levels.
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Affiliation(s)
- Byungjoon Min
- Department of Physics, Chungbuk National University, Cheongju, Chungbuk 28644, South Korea
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26
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Safron A. An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation. Front Artif Intell 2020; 3:30. [PMID: 33733149 PMCID: PMC7861340 DOI: 10.3389/frai.2020.00030] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 04/03/2020] [Indexed: 01/01/2023] Open
Abstract
The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.
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Affiliation(s)
- Adam Safron
- Indiana University, Bloomington, IN, United States
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27
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Hannezo E, Heisenberg CP. Mechanochemical Feedback Loops in Development and Disease. Cell 2020; 178:12-25. [PMID: 31251912 DOI: 10.1016/j.cell.2019.05.052] [Citation(s) in RCA: 179] [Impact Index Per Article: 44.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 05/17/2019] [Accepted: 05/24/2019] [Indexed: 12/31/2022]
Abstract
There is increasing evidence that both mechanical and biochemical signals play important roles in development and disease. The development of complex organisms, in particular, has been proposed to rely on the feedback between mechanical and biochemical patterning events. This feedback occurs at the molecular level via mechanosensation but can also arise as an emergent property of the system at the cellular and tissue level. In recent years, dynamic changes in tissue geometry, flow, rheology, and cell fate specification have emerged as key platforms of mechanochemical feedback loops in multiple processes. Here, we review recent experimental and theoretical advances in understanding how these feedbacks function in development and disease.
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Affiliation(s)
- Edouard Hannezo
- Institute of Science and Technology Austria, Klosterneuburg, Austria.
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28
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Khajehabdollahi S, Witkowski O. Evolution Towards Criticality in Ising Neural Agents. ARTIFICIAL LIFE 2020; 26:112-129. [PMID: 32027529 DOI: 10.1162/artl_a_00309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Criticality is thought to be crucial for complex systems to adapt at the boundary between regimes with different dynamics, where the system may transition from one phase to another. Numerous systems, from sandpiles to gene regulatory networks to swarms to human brains, seem to work towards preserving a precarious balance right at their critical point. Understanding criticality therefore seems strongly related to a broad, fundamental theory for the physics of life as it could be, which still lacks a clear description of how life can arise and maintain itself in complex systems. In order to investigate this crucial question, we model populations of Ising agents competing for resources in a simple 2D environment subject to an evolutionary algorithm. We then compare its evolutionary dynamics under different experimental conditions. We demonstrate the utility that arises at a critical state and contrast it with the behaviors and dynamics that arise far from criticality. The results show compelling evidence that not only is a critical state remarkable in its ability to adapt and find solutions to the environment, but the evolving parameters in the agents tend to flow towards criticality if starting from a supercritical regime. We present simulations showing that a system in a supercritical state will tend to self-organize towards criticality, in contrast to a subcritical state, which remains subcritical though it is still capable of adapting and increasing its fitness.
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Affiliation(s)
| | - Olaf Witkowski
- Cross Compass Ltd., Cross Labs
- Tokyo Institute of Technology, Earth-Life Science Institute
- Institute for Advanced Study
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29
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Jaeger J, Verd B. Dynamic positional information: Patterning mechanism versus precision in gradient-driven systems. Curr Top Dev Biol 2019; 137:219-246. [PMID: 32143744 DOI: 10.1016/bs.ctdb.2019.11.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
There is much talk about information in biology. In developmental biology, this takes the form of "positional information," especially in the context of morphogen-based pattern formation. Unfortunately, the concept of "information" is rarely defined in any precise manner. Here, we provide two alternative interpretations of "positional information," and examine the complementary meanings and uses of each concept. Positional information defined as Shannon information helps us understand decoding and error propagation in patterning systems. General relativistic positional information, in contrast, provides a metric to assess the output of pattern-forming mechanisms. Both interpretations provide powerful conceptual tools that do not compete, but are best used in combination to gain a proper mechanistic understanding of robust patterning.
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Affiliation(s)
- Johannes Jaeger
- Complexity Science Hub (CSH), Vienna, Austria; Department of Molecular Evolution & Development, University of Vienna, Vienna, Austria.
| | - Berta Verd
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
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30
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Meshulam L, Gauthier JL, Brody CD, Tank DW, Bialek W. Coarse Graining, Fixed Points, and Scaling in a Large Population of Neurons. PHYSICAL REVIEW LETTERS 2019; 123:178103. [PMID: 31702278 PMCID: PMC7335427 DOI: 10.1103/physrevlett.123.178103] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 08/01/2019] [Indexed: 06/10/2023]
Abstract
We develop a phenomenological coarse-graining procedure for activity in a large network of neurons, and apply this to recordings from a population of 1000+ cells in the hippocampus. Distributions of coarse-grained variables seem to approach a fixed non-Gaussian form, and we see evidence of scaling in both static and dynamic quantities. These results suggest that the collective behavior of the network is described by a nontrivial fixed point.
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Affiliation(s)
- Leenoy Meshulam
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA
- Joseph Henry Laboratories of Physics, Princeton University, Princeton, New Jersey 08544, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA
| | - Jeffrey L Gauthier
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
- Howard Hughes Medical Institute, Princeton University, Princeton, New Jersey 08544, USA
| | - David W Tank
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA
- Joseph Henry Laboratories of Physics, Princeton University, Princeton, New Jersey 08544, USA
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
| | - William Bialek
- Joseph Henry Laboratories of Physics, Princeton University, Princeton, New Jersey 08544, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA
- Initiative for the Theoretical Sciences, The Graduate Center, City University of New York, 365 Fifth Ave., New York, New York 10016, USA
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31
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Petridou NI, Heisenberg C. Tissue rheology in embryonic organization. EMBO J 2019; 38:e102497. [PMID: 31512749 PMCID: PMC6792012 DOI: 10.15252/embj.2019102497] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 07/12/2019] [Accepted: 07/17/2019] [Indexed: 12/18/2022] Open
Abstract
Tissue morphogenesis in multicellular organisms is brought about by spatiotemporal coordination of mechanical and chemical signals. Extensive work on how mechanical forces together with the well-established morphogen signalling pathways can actively shape living tissues has revealed evolutionary conserved mechanochemical features of embryonic development. More recently, attention has been drawn to the description of tissue material properties and how they can influence certain morphogenetic processes. Interestingly, besides the role of tissue material properties in determining how much tissues deform in response to force application, there is increasing theoretical and experimental evidence, suggesting that tissue material properties can abruptly and drastically change in development. These changes resemble phase transitions, pointing at the intriguing possibility that important morphogenetic processes in development, such as symmetry breaking and self-organization, might be mediated by tissue phase transitions. In this review, we summarize recent findings on the regulation and role of tissue material properties in the context of the developing embryo. We posit that abrupt changes of tissue rheological properties may have important implications in maintaining the balance between robustness and adaptability during embryonic development.
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32
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Verd B, Monk NAM, Jaeger J. Modularity, criticality, and evolvability of a developmental gene regulatory network. eLife 2019; 8:e42832. [PMID: 31169494 PMCID: PMC6645726 DOI: 10.7554/elife.42832] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 06/05/2019] [Indexed: 01/16/2023] Open
Abstract
The existence of discrete phenotypic traits suggests that the complex regulatory processes which produce them are functionally modular. These processes are usually represented by networks. Only modular networks can be partitioned into intelligible subcircuits able to evolve relatively independently. Traditionally, functional modularity is approximated by detection of modularity in network structure. However, the correlation between structure and function is loose. Many regulatory networks exhibit modular behaviour without structural modularity. Here we partition an experimentally tractable regulatory network-the gap gene system of dipteran insects-using an alternative approach. We show that this system, although not structurally modular, is composed of dynamical modules driving different aspects of whole-network behaviour. All these subcircuits share the same regulatory structure, but differ in components and sensitivity to regulatory interactions. Some subcircuits are in a state of criticality, while others are not, which explains the observed differential evolvability of the various expression features in the system.
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Affiliation(s)
- Berta Verd
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG)The Barcelona Institute of Science and TechnologyBarcelonaSpain
- Universitat Pompeu Fabra (UPF)BarcelonaSpain
- Konrad Lorenz Institute for Evolution and Cognition Research (KLI)KlosterneuburgAustria
- Department of GeneticsUniversity of CambridgeCambridgeUnited Kingdom
| | - Nicholas AM Monk
- School of Mathematics and StatisticsUniversity of SheffieldSheffieldUnited States
| | - Johannes Jaeger
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG)The Barcelona Institute of Science and TechnologyBarcelonaSpain
- Universitat Pompeu Fabra (UPF)BarcelonaSpain
- Konrad Lorenz Institute for Evolution and Cognition Research (KLI)KlosterneuburgAustria
- School of Mathematics and StatisticsUniversity of SheffieldSheffieldUnited States
- Wissenschaftskolleg zu BerlinBerlinGermany
- Center for Systems Biology Dresden (CSBD)DresdenGermany
- Complexity Science Hub (CSH)ViennaAustria
- Centre de Recherches Interdisciplinaires (CRI)ParisFrance
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33
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Erez A, Byrd TA, Vogel RM, Altan-Bonnet G, Mugler A. Universality of biochemical feedback and its application to immune cells. Phys Rev E 2019; 99:022422. [PMID: 30934371 DOI: 10.1103/physreve.99.022422] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2017] [Indexed: 11/06/2022]
Abstract
We map a class of well-mixed stochastic models of biochemical feedback in steady state to the mean-field Ising model near the critical point. The mapping provides an effective temperature, magnetic field, order parameter, and heat capacity that can be extracted from biological data without fitting or knowledge of the underlying molecular details. We demonstrate this procedure on fluorescence data from mouse T cells, which reveals distinctions between how the cells respond to different drugs. We also show that the heat capacity allows inference of the absolute molecule number from fluorescence intensity. We explain this result in terms of the underlying fluctuations, and we demonstrate the generality of our work.
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Affiliation(s)
- Amir Erez
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
| | - Tommy A Byrd
- Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana 47907, USA
| | - Robert M Vogel
- IBM T. J. Watson Research Center, Yorktown Heights, New York 10598, USA
| | - Grégoire Altan-Bonnet
- Immunodynamics Group, Cancer and Inflammation Program, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20814, USA
| | - Andrew Mugler
- Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana 47907, USA
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Silva KPT, Yusufaly TI, Chellamuthu P, Boedicker JQ. Disruption of microbial communication yields a two-dimensional percolation transition. Phys Rev E 2019; 99:042409. [PMID: 31108688 DOI: 10.1103/physreve.99.042409] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Indexed: 06/09/2023]
Abstract
Bacteria communicate with each other to coordinate macroscale behaviors including pathogenesis, biofilm formation, and antibiotic production. Empirical evidence suggests that bacteria are capable of communicating at length scales far exceeding the size of individual cells. Several mechanisms of signal interference have been observed in nature, and how interference influences macroscale activity within microbial populations is unclear. Here we examined the exchange of quorum sensing signals to coordinate microbial activity over long distances in the presence of a variable amount of interference through a neighboring signal-degrading strain. As the level of interference increased, communication over large distances was disrupted and at a critical amount of interference, large-scale communication was suppressed. We explored this transition in experiments and reaction-diffusion models, and confirmed that this transition is a two-dimensional percolation transition. These results demonstrate the utility of applying physical models to emergence in complex biological networks to probe robustness and universal quantitative features.
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Affiliation(s)
- Kalinga Pavan T Silva
- Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089, USA
| | - Tahir I Yusufaly
- Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089, USA
| | - Prithiviraj Chellamuthu
- Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089, USA
| | - James Q Boedicker
- Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089, USA
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
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35
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Borja da Rocha H, Truskinovsky L. Functionality of Disorder in Muscle Mechanics. PHYSICAL REVIEW LETTERS 2019; 122:088103. [PMID: 30932585 DOI: 10.1103/physrevlett.122.088103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2017] [Revised: 01/12/2018] [Indexed: 06/09/2023]
Abstract
A salient feature of skeletal muscles is their ability to take up an applied slack in a microsecond timescale. Behind this fast adaptation is a collective folding in a bundle of elastically interacting bistable elements. Since this interaction has a long-range character, the behavior of the system in force and length controlled ensembles is different; in particular, it can have two distinct order-disorder-type critical points. We show that the account of the disregistry between myosin and actin filaments places the elementary force-producing units of skeletal muscles close to both such critical points. The ensuing "double criticality" contributes to the system's ability to perform robustly and suggests that the disregistry is functional.
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Affiliation(s)
- Hudson Borja da Rocha
- LMS, CNRS-UMR 7649, Ecole Polytechnique, Université Paris-Saclay, 91128 Palaiseau, France
- PMMH, CNRS-UMR 7636 PSL-ESPCI, 10 Rue Vauquelin, 75005 Paris, France
| | - Lev Truskinovsky
- PMMH, CNRS-UMR 7636 PSL-ESPCI, 10 Rue Vauquelin, 75005 Paris, France
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36
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Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. Optimal Decoding of Cellular Identities in a Genetic Network. Cell 2019; 176:844-855.e15. [PMID: 30712870 DOI: 10.1016/j.cell.2019.01.007] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 11/04/2018] [Accepted: 01/02/2019] [Indexed: 11/24/2022]
Abstract
In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy.
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Affiliation(s)
- Mariela D Petkova
- Joseph Henry Laboratories of Physics and the Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Program in Biophysics, Harvard University, Cambridge, MA 02138, USA
| | - Gašper Tkačik
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - William Bialek
- Joseph Henry Laboratories of Physics and the Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Eric F Wieschaus
- Department of Molecular Biology and Howard Hughes Medical Institute, Princeton University, Princeton, NJ 08544, USA
| | - Thomas Gregor
- Joseph Henry Laboratories of Physics and the Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Department of Developmental and Stem Cell Biology, UMR3738, Institut Pasteur, 75015 Paris, France.
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37
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Pyrkov TV, Getmantsev E, Zhurov B, Avchaciov K, Pyatnitskiy M, Menshikov L, Khodova K, Gudkov AV, Fedichev PO. Quantitative characterization of biological age and frailty based on locomotor activity records. Aging (Albany NY) 2018; 10:2973-2990. [PMID: 30362959 PMCID: PMC6224248 DOI: 10.18632/aging.101603] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 10/15/2018] [Indexed: 12/29/2022]
Abstract
We performed a systematic evaluation of the relationships between locomotor activity and signatures of frailty, morbidity, and mortality risks using physical activity records from the 2003-2006 National Health and Nutrition Examination Survey (NHANES) and UK BioBank (UKB). We proposed a statistical description of the locomotor activity tracks and transformed the provided time series into vectors representing physiological states for each participant. The Principal Component Analysis of the transformed data revealed a winding trajectory with distinct segments corresponding to subsequent human development stages. The extended linear phase starts from 35-40 years old and is associated with the exponential increase of mortality risks according to the Gompertz mortality law. We characterized the distance traveled along the aging trajectory as a natural measure of biological age and demonstrated its significant association with frailty and hazardous lifestyles, along with the remaining lifespan and healthspan of an individual. The biological age explained most of the variance of the log-hazard ratio that was obtained by fitting directly to mortality and the incidence of chronic diseases. Our findings highlight the intimate relationship between the supervised and unsupervised signatures of the biological age and frailty, a consequence of the low intrinsic dimensionality of the aging dynamics.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Peter O. Fedichev
- Gero LLC, Moscow 1015064, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny 141700, Moscow Region, Russia
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Fedichev PO. Hacking Aging: A Strategy to Use Big Data From Medical Studies to Extend Human Life. Front Genet 2018; 9:483. [PMID: 30405692 PMCID: PMC6206166 DOI: 10.3389/fgene.2018.00483] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 09/28/2018] [Indexed: 12/26/2022] Open
Abstract
Age is the most important single factor associated with chronic diseases and ultimately, death. The mortality rate in humans doubles approximately every eight years, as described by the Gompertz law of mortality. The incidence of specific diseases, such as cancer or stroke, also accelerates after the age of about 40 and doubles at a rate that mirrors the mortality-rate doubling time. It is therefore, entirely plausible to think that there is a single underlying process, the driving force behind the progressive reduction of the organism's health leading to the increased susceptibility to diseases and death; aging. There is, however, no fundamental law of nature requiring exponential morbidity and mortality risk trajectories. The acceleration of mortality is thus the most important characteristics of the aging process. It varies dramatically even among closely related mammalian species and hence appears to be a tunable phenotype. Here, we follow how big data from large human medical studies, and analytical approaches borrowed from physics of complex dynamic systems can help to reverse engineer the underlying biology behind Gompertz mortality law. With such an approach we hope to generate predictive models of aging for systematic discovery of biomarkers of aging followed by identification of novel therapeutic targets for future anti-aging interventions.
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Affiliation(s)
- Peter O. Fedichev
- Gero LLC, Moscow, Russia
- Moscow Institute of Physics and Technology, Moscow, Russia
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39
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Realpe-Gómez J, Andrighetto G, Nardin LG, Montoya JA. Balancing selfishness and norm conformity can explain human behavior in large-scale prisoner's dilemma games and can poise human groups near criticality. Phys Rev E 2018; 97:042321. [PMID: 29758626 DOI: 10.1103/physreve.97.042321] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Indexed: 01/16/2023]
Abstract
Cooperation is central to the success of human societies as it is crucial for overcoming some of the most pressing social challenges of our time; still, how human cooperation is achieved and may persist is a main puzzle in the social and biological sciences. Recently, scholars have recognized the importance of social norms as solutions to major local and large-scale collective action problems, from the management of water resources to the reduction of smoking in public places to the change in fertility practices. Yet a well-founded model of the effect of social norms on human cooperation is still lacking. Using statistical-physics techniques and integrating findings from cognitive and behavioral sciences, we present an analytically tractable model in which individuals base their decisions to cooperate both on the economic rewards they obtain and on the degree to which their action complies with social norms. Results from this parsimonious model are in agreement with observations in recent large-scale experiments with humans. We also find the phase diagram of the model and show that the experimental human group is poised near a critical point, a regime where recent work suggests living systems respond to changing external conditions in an efficient and coordinated manner.
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Affiliation(s)
- John Realpe-Gómez
- Quantum Artificial Intelligence Laboratory, NASA Ames Research Center, Moffett Field, California 94035, USA; Instituto de Matemáticas Aplicadas, Universidad de Cartagena, Cartagena de Indias, Bolívar 13001, Colombia; and SGT Inc., 7701 Greenbelt Road, Greenbelt, Maryland 20770, USA
| | - Giulia Andrighetto
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome 00185, Italy; Mälardalen University, Högskoleplan 1, 721 23 Västerås, Sweden; and Institute for Futures Studies, Holländargatan 13, 101 31 Stockholm, Sweden
| | - Luis Gustavo Nardin
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome 00185, Italy and Brandenburg University of Technology, 03046 Cottbus, Brandenburg, Germany
| | - Javier Antonio Montoya
- Grupo de Modelado Computacional, Universidad de Cartagena, Cartagena de Indias, Bolívar 13001, Colombia and The Abdus Salam International Centre for Theoretical Physics, Strada Costiera 11, 34151 Trieste, Italy
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40
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41
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Daniels BC, Kim H, Moore D, Zhou S, Smith HB, Karas B, Kauffman SA, Walker SI. Criticality Distinguishes the Ensemble of Biological Regulatory Networks. PHYSICAL REVIEW LETTERS 2018; 121:138102. [PMID: 30312104 DOI: 10.1103/physrevlett.121.138102] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 07/21/2018] [Indexed: 06/08/2023]
Abstract
The hypothesis that many living systems should exhibit near-critical behavior is well motivated theoretically, and an increasing number of cases have been demonstrated empirically. However, a systematic analysis across biological networks, which would enable identification of the network properties that drive criticality, has not yet been realized. Here, we provide a first comprehensive survey of criticality across a diverse sample of biological networks, leveraging a publicly available database of 67 Boolean models of regulatory circuits. We find all 67 networks to be near critical. By comparing to ensembles of random networks with similar topological and logical properties, we show that criticality in biological networks is not predictable solely from macroscale properties such as mean degree ⟨K⟩ and mean bias in the logic functions ⟨p⟩, as previously emphasized in theories of random Boolean networks. Instead, the ensemble of real biological circuits is jointly constrained by the local causal structure and logic of each node. In this way, biological regulatory networks are more distinguished from random networks by their criticality than by other macroscale network properties such as degree distribution, edge density, or fraction of activating conditions.
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Affiliation(s)
- Bryan C Daniels
- ASU-SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, Arizona 85287, USA
| | - Hyunju Kim
- School of Earth and Space Exploration, Arizona State University, Tempe, Arizona 85287, USA
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, Arizona 85287, USA
| | - Douglas Moore
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, Arizona 85287, USA
| | - Siyu Zhou
- Department of Physics, Arizona State University, Tempe, Arizona 85287, USA
| | - Harrison B Smith
- School of Earth and Space Exploration, Arizona State University, Tempe, Arizona 85287, USA
| | - Bradley Karas
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, Arizona 85287, USA
| | | | - Sara I Walker
- ASU-SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, Arizona 85287, USA
- School of Earth and Space Exploration, Arizona State University, Tempe, Arizona 85287, USA
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, Arizona 85287, USA
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42
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Kang C, Aguilar B, Shmulevich I. Emergence of diversity in homogeneous coupled Boolean networks. Phys Rev E 2018; 97:052415. [PMID: 29906914 DOI: 10.1103/physreve.97.052415] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Indexed: 01/03/2023]
Abstract
The origin of multicellularity in metazoa is one of the fundamental questions of evolutionary biology. We have modeled the generic behaviors of gene regulatory networks in isogenic cells as stochastic nonlinear dynamical systems-coupled Boolean networks with perturbation. Model simulations under a variety of dynamical regimes suggest that the central characteristic of multicellularity, permanent spatial differentiation (diversification), indeed can arise. Additionally, we observe that diversification is more likely to occur near the critical regime of Lyapunov stability.
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Affiliation(s)
- Chris Kang
- Department of Applied Mathematics, University of Washington, Seattle, Washington 98195, USA
| | - Boris Aguilar
- Institute for Systems Biology, Seattle, Washington 98109, USA
| | - Ilya Shmulevich
- Institute for Systems Biology, Seattle, Washington 98109, USA
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43
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Aguilera M, Bedia MG. Adaptation to criticality through organizational invariance in embodied agents. Sci Rep 2018; 8:7723. [PMID: 29769565 PMCID: PMC5956029 DOI: 10.1038/s41598-018-25925-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 04/12/2018] [Indexed: 11/20/2022] Open
Abstract
Many biological and cognitive systems do not operate deep within one or other regime of activity. Instead, they are poised at critical points located at phase transitions in their parameter space. The pervasiveness of criticality suggests that there may be general principles inducing this behaviour, yet there is no well-founded theory for understanding how criticality is generated at a wide span of levels and contexts. In order to explore how criticality might emerge from general adaptive mechanisms, we propose a simple learning rule that maintains an internal organizational structure from a specific family of systems at criticality. We implement the mechanism in artificial embodied agents controlled by a neural network maintaining a correlation structure randomly sampled from an Ising model at critical temperature. Agents are evaluated in two classical reinforcement learning scenarios: the Mountain Car and the Acrobot double pendulum. In both cases the neural controller appears to reach a point of criticality, which coincides with a transition point between two regimes of the agent’s behaviour. These results suggest that adaptation to criticality could be used as a general adaptive mechanism in some circumstances, providing an alternative explanation for the pervasive presence of criticality in biological and cognitive systems.
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Affiliation(s)
- Miguel Aguilera
- Deptartment of Computer Science, University of Zaragoza, Zaragoza, Spain. .,IAS-Research Center for Life, Mind, and Society, University of the Basque Country, Donostia-San Sebastián, Spain. .,Institute for Cross-Disciplinary Physics and Complex Systems, Palma, Spain.
| | - Manuel G Bedia
- Deptartment of Computer Science, University of Zaragoza, Zaragoza, Spain.,Aragón Institute of Engineering Research, Zaragoza, Spain
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44
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A damped oscillator imposes temporal order on posterior gap gene expression in Drosophila. PLoS Biol 2018; 16:e2003174. [PMID: 29451884 PMCID: PMC5832388 DOI: 10.1371/journal.pbio.2003174] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 03/01/2018] [Accepted: 01/31/2018] [Indexed: 12/21/2022] Open
Abstract
Insects determine their body segments in two different ways. Short-germband insects, such as the flour beetle Tribolium castaneum, use a molecular clock to establish segments sequentially. In contrast, long-germband insects, such as the vinegar fly Drosophila melanogaster, determine all segments simultaneously through a hierarchical cascade of gene regulation. Gap genes constitute the first layer of the Drosophila segmentation gene hierarchy, downstream of maternal gradients such as that of Caudal (Cad). We use data-driven mathematical modelling and phase space analysis to show that shifting gap domains in the posterior half of the Drosophila embryo are an emergent property of a robust damped oscillator mechanism, suggesting that the regulatory dynamics underlying long- and short-germband segmentation are much more similar than previously thought. In Tribolium, Cad has been proposed to modulate the frequency of the segmentation oscillator. Surprisingly, our simulations and experiments show that the shift rate of posterior gap domains is independent of maternal Cad levels in Drosophila. Our results suggest a novel evolutionary scenario for the short- to long-germband transition and help explain why this transition occurred convergently multiple times during the radiation of the holometabolan insects. Different insect species exhibit one of two distinct modes of determining their body segments (known as segmentation) during development: they either use a molecular oscillator to position segments sequentially, or they generate segments simultaneously through a hierarchical gene-regulatory cascade. The sequential mode is ancestral, while the simultaneous mode has been derived from it independently several times during evolution. In this paper, we present evidence suggesting that simultaneous segmentation also involves an oscillator in the posterior end of the embryo of the vinegar fly, Drosophila melanogaster. This surprising result indicates that both modes of segment determination are much more similar than previously thought. Such similarity provides an important step towards our understanding of the frequent evolutionary transitions observed between sequential and simultaneous segmentation.
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45
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Wu A, Liao D, Kirilin V, Lin KC, Torga G, Qu J, Liu L, Sturm JC, Pienta K, Austin R. Cancer dormancy and criticality from a game theory perspective. CANCER CONVERGENCE 2018; 2:1. [PMID: 29623956 PMCID: PMC5876693 DOI: 10.1186/s41236-018-0008-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 01/05/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The physics of cancer dormancy, the time between initial cancer treatment and re-emergence after a protracted period, is a puzzle. Cancer cells interact with host cells via complex, non-linear population dynamics, which can lead to very non-intuitive but perhaps deterministic and understandable progression dynamics of cancer and dormancy. RESULTS We explore here the dynamics of host-cancer cell populations in the presence of (1) payoffs gradients and (2) perturbations due to cell migration. CONCLUSIONS We determine to what extent the time-dependence of the populations can be quantitively understood in spite of the underlying complexity of the individual agents and model the phenomena of dormancy.
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Affiliation(s)
- Amy Wu
- Banter AI, 408 Florence St., Palo Alto CA, 94301 USA
| | - David Liao
- Department of Pathology, University of California at San Francisco, San Francisco, 94143 USA
| | - Vlamimir Kirilin
- Department of Physics, Princeton University, Princeton, 08544 NJ USA
| | - Ke-Chih Lin
- Department of Electrical Engineering, Princeton University, Princeton, 08544 USA
| | - Gonzalo Torga
- The Johns Hopkins Hospital, 1800 Orleans St., Baltimore MD, 21287 USA
| | - Junle Qu
- College of Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060 China
| | - Liyu Liu
- College of Physics, Chongqing University, Chongqing China, 400044 China
| | - James C. Sturm
- Department of Electrical Engineering, Princeton University, Princeton, 08544 USA
| | - Kenneth Pienta
- The Johns Hopkins Hospital, 1800 Orleans St., Baltimore MD, 21287 USA
| | - Robert Austin
- Department of Physics, Princeton University, Princeton, 08544 NJ USA
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46
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Bialek W. Perspectives on theory at the interface of physics and biology. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2018; 81:012601. [PMID: 29214982 DOI: 10.1088/1361-6633/aa995b] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Theoretical physics is the search for simple and universal mathematical descriptions of the natural world. In contrast, much of modern biology is an exploration of the complexity and diversity of life. For many, this contrast is prima facie evidence that theory, in the sense that physicists use the word, is impossible in a biological context. For others, this contrast serves to highlight a grand challenge. I am an optimist, and believe (along with many colleagues) that the time is ripe for the emergence of a more unified theoretical physics of biological systems, building on successes in thinking about particular phenomena. In this essay I try to explain the reasons for my optimism, through a combination of historical and modern examples.
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Affiliation(s)
- William Bialek
- Joseph Henry Laboratories of Physics, and Lewis-Sigler Institute for Integrative Genomics, Princeton University, 08544, Princeton NJ, United States of America. Initiative for the Theoretical Sciences, The Graduate Center, City University of New York, 365 Fifth Ave, 10016, New York NY, United States of America
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48
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Abstract
Our sense of hearing boasts exquisite sensitivity, precise frequency discrimination, and a broad dynamic range. Experiments and modeling imply, however, that the auditory system achieves this performance for only a narrow range of parameter values. Small changes in these values could compromise hair cells' ability to detect stimuli. We propose that, rather than exerting tight control over parameters, the auditory system uses a homeostatic mechanism that increases the robustness of its operation to variation in parameter values. To slowly adjust the response to sinusoidal stimulation, the homeostatic mechanism feeds back a rectified version of the hair bundle's displacement to its adaptation process. When homeostasis is enforced, the range of parameter values for which the sensitivity, tuning sharpness, and dynamic range exceed specified thresholds can increase by more than an order of magnitude. Signatures in the hair cell's behavior provide a means to determine through experiment whether such a mechanism operates in the auditory system. Robustness of function through homeostasis may be ensured in any system through mechanisms similar to those that we describe here.
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49
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Yusufaly TI, Boedicker JQ. Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities. Phys Biol 2017; 14:046002. [PMID: 28656904 DOI: 10.1088/1478-3975/aa7c1e] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely understood in heterogeneous communities, where variant bacterial strains possess distinct QS systems that produce chemically unique AIs. AI molecules bind to 'cognate' receptors, but also to 'non-cognate' receptors found in other strains, resulting in inter-strain crosstalk. Understanding these interactions is a prerequisite for deciphering the consequences of crosstalk in real ecosystems, where multiple AIs are regularly present in the same environment. As a step towards this goal, we map crosstalk in a heterogeneous community of variant QS strains onto an artificial neural network model. This formulation allows us to systematically analyze how crosstalk regulates the community's capacity for flexible decision making, as quantified by the Boltzmann entropy of all QS gene expression states of the system. In a mean-field limit of complete cross-inhibition between variant strains, the model is exactly solvable, allowing for an analytical formula for the number of variants that maximize capacity as a function of signal kinetics and activation parameters. An analysis of previous experimental results on the Staphylococcus aureus two-component Agr system indicates that the observed combination of variant numbers, gene expression rates and threshold concentrations lies near this critical regime of parameter space where capacity peaks. The results are suggestive of a potential evolutionary driving force for diversification in certain QS systems.
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Affiliation(s)
- Tahir I Yusufaly
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, United States of America
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50
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Steiner PJ, Williams RJ, Hasty J, Tsimring LS. Criticality and Adaptivity in Enzymatic Networks. Biophys J 2017; 111:1078-87. [PMID: 27602735 DOI: 10.1016/j.bpj.2016.07.036] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Revised: 06/28/2016] [Accepted: 07/28/2016] [Indexed: 01/01/2023] Open
Abstract
The contrast between the stochasticity of biochemical networks and the regularity of cellular behavior suggests that biological networks generate robust behavior from noisy constituents. Identifying the mechanisms that confer this ability on biological networks is essential to understanding cells. Here we show that queueing for a limited shared resource in broad classes of enzymatic networks in certain conditions leads to a critical state characterized by strong and long-ranged correlations between molecular species. An enzymatic network reaches this critical state when the input flux of its substrate is balanced by the maximum processing capacity of the network. We then consider enzymatic networks with adaptation, when the limiting resource (enzyme or cofactor) is produced in proportion to the demand for it. We show that the critical state becomes an attractor for these networks, which points toward the onset of self-organized criticality. We suggest that the adaptive queueing motif that leads to significant correlations between multiple species may be widespread in biological systems.
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Affiliation(s)
- Paul J Steiner
- BioCircuits Institute, University of California, San Diego, La Jolla, California
| | - Ruth J Williams
- BioCircuits Institute, University of California, San Diego, La Jolla, California; Department of Mathematics, University of California, San Diego, La Jolla, California.
| | - Jeff Hasty
- BioCircuits Institute, University of California, San Diego, La Jolla, California; Molecular Biology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, California; Department of Bioengineering, University of California, San Diego, La Jolla, California; San Diego Center for Systems Biology, University of California, San Diego, La Jolla, California.
| | - Lev S Tsimring
- BioCircuits Institute, University of California, San Diego, La Jolla, California; San Diego Center for Systems Biology, University of California, San Diego, La Jolla, California.
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