From L'homme Machine to Metabolic Closure Steps Towards
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Prebiological Evolution and the Metabolic Origins of Life
Prebiological Evolution and the Andrew J. Pratt* Metabolic Origins of Life University of Canterbury Keywords Abiogenesis, origin of life, metabolism, hydrothermal, iron Abstract The chemoton model of cells posits three subsystems: metabolism, compartmentalization, and information. A specific model for the prebiological evolution of a reproducing system with rudimentary versions of these three interdependent subsystems is presented. This is based on the initial emergence and reproduction of autocatalytic networks in hydrothermal microcompartments containing iron sulfide. The driving force for life was catalysis of the dissipation of the intrinsic redox gradient of the planet. The codependence of life on iron and phosphate provides chemical constraints on the ordering of prebiological evolution. The initial protometabolism was based on positive feedback loops associated with in situ carbon fixation in which the initial protometabolites modified the catalytic capacity and mobility of metal-based catalysts, especially iron-sulfur centers. A number of selection mechanisms, including catalytic efficiency and specificity, hydrolytic stability, and selective solubilization, are proposed as key determinants for autocatalytic reproduction exploited in protometabolic evolution. This evolutionary process led from autocatalytic networks within preexisting compartments to discrete, reproducing, mobile vesicular protocells with the capacity to use soluble sugar phosphates and hence the opportunity to develop nucleic acids. Fidelity of information transfer in the reproduction of these increasingly complex autocatalytic networks is a key selection pressure in prebiological evolution that eventually leads to the selection of nucleic acids as a digital information subsystem and hence the emergence of fully functional chemotons capable of Darwinian evolution. 1 Introduction: Chemoton Subsystems and Evolutionary Pathways Living cells are autocatalytic entities that harness redox energy via the selective catalysis of biochemical transformations. -
Nicolas Rashevsky's Mathematical Biophysics
Journal of the History of Biology 37: 333–385, 2004. 333 Ó 2004 Kluwer Academic Publishers. Printed in the Netherlands. Nicolas Rashevsky’s Mathematical Biophysics TARA H. ABRAHAM Max Planck Institute for the History of Science Wilhelmstrae 44 10117 Berlin Germany E-mail: [email protected] Abstract. This paper explores the work of Nicolas Rashevsky, a Russian e´ migre´ the- oretical physicist who developed a program in ‘‘mathematical biophysics’’ at the Uni- versity of Chicago during the 1930s. Stressing the complexity of many biological phenomena, Rashevsky argued that the methods of theoretical physics – namely mathematics – were needed to ‘‘simplify’’ complex biological processes such as cell division and nerve conduction. A maverick of sorts, Rashevsky was a conspicuous figure in the biological community during the 1930s and early 1940s: he participated in several Cold Spring Harbor symposia and received several years of funding from the Rockefeller Foundation. However, in contrast to many other physicists who moved into biology, Rashevsky’s work was almost entirely theoretical, and he eventually faced resistance to his mathematical methods. Through an examination of the conceptual, institutional, and scientific context of Rashevsky’s work, this paper seeks to understand some of the reasons behind this resistance. Keywords: Mathematical biology, Neurophysiology, Nicolas Rashevsky, Physiology, Rockefeller Foundation, Theory, University of Chicago, Warren Weaver Introduction The migration of physicists into the biological sciences during the early 20th century has been a topic of interest in the history and philosophy of biology, with associated issues of the disciplinary authority of physics, the autonomy of biology, and the reduction of biological phenomena to physical terms.1 Most often, these migrations 1 The relationship between physics and biology has occupied Anglo-American phi- losophers of science in the 20th century, as they inherited a set of questions posed by logical positivists during the 1930s. -
Artificial Cell Research As a Field That Connects Chemical, Biological and Philosophical Questions
Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2016 Artificial cell research as a field that connects chemical, biological and philosophical questions Deplazes-Zemp, Anna Abstract: This review article discusses the interdisciplinary nature and implications of artificial cell research. It starts from two historical theories: Gánti’s chemoton model and the autopoiesis theory by Maturana and Varela. They both explain the transition from chemical molecules to biological cells. These models exemplify two different ways in which disciplines of chemistry, biology and philosophy canprofit from each other. In the chemoton model, conclusions from one disciplinary approach are relevant for the other disciplines. In contrast, the autopoiesis model itself (rather than its conclusions) is transferred from one discipline to the other. The article closes by underpinning the relevance of artificial cell research for philosophy with reference to the on-going philosophical debates on emergence, biological functions and biocentrism. DOI: https://doi.org/10.2533/chimia.2016.443 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-135057 Journal Article Published Version Originally published at: Deplazes-Zemp, Anna (2016). Artificial cell research as a field that connects chemical, biological and philosophical questions. CHIMIA International Journal for Chemistry, 70(6):443-448. DOI: https://doi.org/10.2533/chimia.2016.443 NCCR MoleCulaR SySteMS eNgiNeeRiNg CHIMIA 2016, 70, No. 6 443 doi:10.2533/chimia.2016.443 Chimia 70 (2016) 443–448 © Swiss Chemical Society Artificial Cell Research as a Field that Connects Chemical, Biological and Philosophical Questions Anna Deplazes-Zemp* Abstract: This review article discusses the interdisciplinary nature and implications of artificial cell research. -
Outsiders As Innovators in the Life Sciences
Dartmouth College Dartmouth Digital Commons Open Dartmouth: Published works by Dartmouth faculty Faculty Work 12-1-2006 Outsiders as Innovators in the Life Sciences Michael Dietrich Dartmouth College Follow this and additional works at: https://digitalcommons.dartmouth.edu/facoa Part of the Biology Commons Dartmouth Digital Commons Citation Dietrich, Michael, "Outsiders as Innovators in the Life Sciences" (2006). Open Dartmouth: Published works by Dartmouth faculty. 34. https://digitalcommons.dartmouth.edu/facoa/34 This Book Chapter is brought to you for free and open access by the Faculty Work at Dartmouth Digital Commons. It has been accepted for inclusion in Open Dartmouth: Published works by Dartmouth faculty by an authorized administrator of Dartmouth Digital Commons. For more information, please contact [email protected]. oren harman & michael r. dietrich introduction outsiders as innovators in the life sciences introduction Both intellectually and institutionally, the life sciences oc- cupy a fascinating middle ground between the physical and exact sciences, on the one hand, and the social sciences and humanities on the other. If biology were an animal, it would be a duck- billed platypus— something that appears chimeric, yet is fully rooted in its own historical lineage of accumu- lating adaptations, tinkering, and change. Like that strange aquatic mammal, “half bird, half beast,”1 its features point to its origins and ecol ogy. Biology as a science has come into being as a patchwork, assuming its present visage as a consequence of myriad interactions between diff erent traditions of knowledge, method, and phi- losophy while maintaining an overarching quest for understanding of the natural world. -
THE INTELLECTUAL ORIGINS of the Mcculloch
JHBS—WILEY RIGHT BATCH Top of ID Journal of the History of the Behavioral Sciences, Vol. 38(1), 3–25 Winter 2002 ᭧ 2002 John Wiley & Sons, Inc. (PHYSIO)LOGICAL CIRCUITS: THE INTELLECTUAL ORIGINS OF THE Base of 1st McCULLOCH–PITTS NEURAL NETWORKS line of ART TARA H. ABRAHAM This article examines the intellectual and institutional factors that contributed to the col- laboration of neuropsychiatrist Warren McCulloch and mathematician Walter Pitts on the logic of neural networks, which culminated in their 1943 publication, “A Logical Calculus of the Ideas Immanent in Nervous Activity.” Historians and scientists alike often refer to the McCulloch–Pitts paper as a landmark event in the history of cybernetics, and funda- mental to the development of cognitive science and artificial intelligence. This article seeks to bring some historical context to the McCulloch–Pitts collaboration itself, namely, their intellectual and scientific orientations and backgrounds, the key concepts that contributed to their paper, and the institutional context in which their collaboration was made. Al- though they were almost a generation apart and had dissimilar scientific backgrounds, McCulloch and Pitts had similar intellectual concerns, simultaneously motivated by issues in philosophy, neurology, and mathematics. This article demonstrates how these issues converged and found resonance in their model of neural networks. By examining the intellectual backgrounds of McCulloch and Pitts as individuals, it will be shown that besides being an important event in the history of cybernetics proper, the McCulloch– Pitts collaboration was an important result of early twentieth-century efforts to apply mathematics to neurological phenomena. ᭧ 2002 John Wiley & Sons, Inc. -
Phenotypic Diversity and Chaos in a Minimal Cell Model
ARTICLE IN PRESS Journal of Theoretical Biology 240 (2006) 434–442 www.elsevier.com/locate/yjtbi Phenotypic diversity and chaos in a minimal cell model Andreea Munteanua,Ã, Ricard V. Sole´a,b aICREA-Complex Systems Lab, Universitat Pompeu Fabra (GRIB), Dr. Aiguader 80, 08003 Barcelona, Spain bSanta Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA Received 4 April 2005; received in revised form 10 October 2005; accepted 12 October 2005 Available online 5 December 2005 Abstract Ga´nti’s chemoton model (Ga´nti, T., 2002. On the early evolution of biological periodicity. Cell. Biol. Int. 26, 729) is considered as an iconic example of a minimal protocell including three key subsystems: membrane, metabolism and information. The three subsystems are connected through stoichiometrical coupling which ensures the existence of a replication cycle for the chemoton. Our detailed exploration of a version of this model indicates that it displays a wide range of complex dynamics, from regularity to chaos. Here, we report the presence of a very rich set of dynamical patterns potentially displayed by a protocell as described by this implementation of a chemoton-like model. The implications for early cellular evolution and synthesis of artificial cells are discussed. r 2005 Elsevier Ltd. All rights reserved. Keywords: Protocell; Origins of life; Chemoton; Cellular networks; Chaos 1. Introduction pursued in the experiments. For the latter, no intentional implications concerning the birth of primordial cells are Cells are the basic building blocks of all life on our sought and its proper functioning is based on present planet. They are the minimal systems able to self-replicate biogenic and/or abiogenic chemistry. -
SMB Newsletter Volume 23 #2 - May 2010
SMB Newsletter Volume 23 #2 - May 2010 Inside this Issue: Letter from President.......................................................................................................................................2 2010 SIAM Great Lakes conference on Modeling and Numerical PDEs in Mathematical Biology..............3 VCU/NHLBI Spring 2010 Conference........................................................................................................4-5 African Society for Biomathematics Inaugural Conference........................................................................6-7 Nicolas Rashevsky...........................................................................................................................................7 Systems approaches in immunology: advances and challenges in multi-scale modeling...........................8-9 My Career in Math Biology: Leon Glass.................................................................................................10-11 First International Workshop “Mathematical Methods in Systems Biology”..........................................12-13 Center and Institute Updates....................................................................................................................14-15 Dynamical Systems Applied to Biology and Natural Science................................................................16-17 Positions Available..................................................................................................................................17-19 SMB 2010 Updates....................................................................................................................................20 -
Mathematical Biology, an Interdisciplinary Future
Quarterly newsletter Last quarter 2014 / First quarter 2015 CSIC - UAM - UC3M - UCM EDITORIAL Mathematical Biology, an interdisciplinary future Mathematical Biology is a scientific field devoted to the study networks in epidemiology requires ideas belonging to graph theory; of biological processes using mathematical techniques. It is an combinatorial algebra is applied to systems control in ecology; the area where the interests of biologists and mathematicians mainly topological branch of knot theory describes the way in which a DNA converge, and to a lesser extent those of researchers from other molecule is configured; research into molecular genetics requires branches of knowledge. certain stochastic processes (Markov chains and processes, branching processes, Brownian motion, diffusion processes); Monte Carlo It is without doubt an attractive field that is now on the rise. It has Markov chains and numerical methods based on the theory of large progressed rapidly during the last two decades and has modified deviations are found in the simulation of rare events in biological the controversial, historical relation between experimental science, models; linear and nonlinear models in neurobiology employ Biology, and Mathematics, the latter being characterized by its deterministic and stochastic partial differential equations; in addition, degree of abstraction. Traditionally, biologists have not disguised measured or sampled data lead to goodness of fit and estimation their mistrust in the contributions made by mathematicians, on the procedures in statistics. grounds that the level of complexity of living beings could not be translated into terms provided by a handful of equations. At present, Computational advances in recent decades and the development of the close interaction between professionals belonging to both fields new numerical methods have enabled the diverse challenges faced has made these equations into a mathematical synthesis capable of encapsulating the essential aspects of a biological reality while leaving other superficial considerations aside. -
Computer Simulation of Neural Networks Using Spreadsheets: the Dawn of the Age of Camelot
Педагогiка вищої та середньої школи 2019. Випуск 51. C. 159–191 УДК 004.94:37.091.39 Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot Serhiy O. Semerikov1[0000−0003−0789−0272], Illia O. Teplytskyi1, Yuliia V. Yechkalo2[0000−0002−0164−8365] and Arnold E. Kiv3 1 Kryvyi Rih State Pedagogical University, 54, Gagarina Ave., Kryvyi Rih, 50086, Ukraine [email protected] 2 State Institution of Higher Education “Kryvyi Rih National University”, 11, Vitali Matusevich St., Kryvyi Rih, 50027, Ukraine [email protected] 3 Ben-Gurion University of the Negev, Beer Sheba, Israel [email protected] Abstract. The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins and macros. After analyzing a collection of writings of 1890–1950, the research determines the role of the scientific journal “Bulletin of Mathematical Biophysics”, its founder Nicolas Rashevsky and the scientific community around the journal in creating and developing models and methods of computational neuroscience. There are identified psychophysical basics of creating neural networks, mathematical foundations of neural computing and methods of neuroengineering (image recognition, in particular). -
An Interview with Jack Cowan1
An Interview with Jack Cowan1 Jack Cowan was born in Leeds, England in 1933. Educated at Edinburgh University, Imperial College and MIT, he is one of the pioneers of continuous approaches to neural networks and brain modelling. He has made many important contributions to machine learning, neural networks and computational neuroscience. In 1967 he took over from Nicolas Rashevsky as Chair of the Committee on Mathematical Biology at the University of Chicago where he has remained ever since; he is currently Professor in the Mathematics Department. This is an edited transcript of an interview conducted on the 6th November 2006. Phil Husbands: Can you start by saying a little about your family background, in particular any influences that might have steered you towards a career in science. Jack Cowan: My grandparents emigrated from Poland and Lithuania at the turn of the last century; I think they left after the 1908 pogroms and they ended up in England, on my mother’s side, and Scotland on my father’s. My mother’s parents had a clothing business in Leeds and my father’s family sold fruit in Edinburgh. My father became a baker. My mother was clever and did get a scholarship to go to University but she had to decline because of the family finances. So I was the first member of my family to go to University. PH: Did you get much influence from school? JC: Yes, in that I went to a good school. My parents were very encouraging from an early age – my mother claims that I started reading when I was very young and that I was bossing the other kids in kindergarten! Anyway, we moved to Edinburgh from Leeds when I was six years old and I went to a local school there for about three years, but my parents could see that I had some aptitude so they got me into George Heriot’s School, a very good private school. -
Life Before LUCA∗
Life before LUCA∗ Athel Cornish-Bowden and María Luz Cárdenas Aix Marseille Univ, CNRS, BIP, IMM, Marseille, France AUTHORS’ CONTACT INFORMATION email [email protected] [email protected] telephone + 33 491 16 41 38 ARTICLE INFO Keywords: Lynn Sagan, Lynn Margulis, LUCA, cenancestor, last universal common ancestor, origin of life, definition of life NOTE. This file is printed from the final accepted version of the paper. The PDF file typeset by the Journal will be available later. ABSTRACT We see the last universal common ancestor of all living organisms, or LUCA, at the evolutionary separation of the Archaea from the Eubacteria, and before the symbiotic event believed to have led to the Eukarya. LUCA is often implicitly taken to be close to the origin of life, and sometimes this is even stated explicitly. However, LUCA already had the capacity to code for many proteins, and had some of the same bioenergetic capacities as modern ∗This paper is dedicated to the memory of Lynn Sagan (Margulis), and especially of her paper “On the origin of mitosing cells”. 1 organisms. An organism at the origin of life must have been vastly simpler, and this invites the question of how to define a living organism. Even if acceptance of the giant viruses as living organisms forces the definition of LUCA to be revised, it will not alter the essential point that LUCA should be regarded as a recent player in the evolution of life. 1. Introduction In general I avoid the last 3 million years of evolution and any other studies that require detailed knowledge of mammalian, including human, biology. -
Contrasting Theories of Life: Historical Context, Current Theories
BioSystems 188 (2020) 104063 Contents lists available at ScienceDirect BioSystems journal homepage: www.elsevier.com/locate/biosystems Review article Contrasting theories of life: Historical context, current theories. In search of an ideal theory Athel Cornish-Bowden <, María Luz Cárdenas Aix Marseille Univ, CNRS, BIP, IMM, Marseille, France ARTICLEINFO ABSTRACT Keywords: Most attempts to define life have concentrated on individual theories, mentioning others hardly at all, but here Autocatalytic sets we compare all of the major current theories. We begin by asking how we know that an entity is alive, and Autopoiesis continue by describing the contributions of La Mettrie, Burke, Leduc, Herrera, Bahadur, D'Arcy Thompson and, Chemoton especially, Schrödinger, whose book What is Life? is a vital starting point. We then briefly describe and discuss Closure (M, R) systems, the hypercycle, the chemoton, autopoiesis and autocatalytic sets. All of these incorporate the Hypercycle Metabolic circularity idea of circularity to some extent, but all of them fail to take account of mechanisms of metabolic regulation, (M, R) systems which we regard as crucial if an organism is to avoid collapsing into a mass of unregulated reactions. In Origin of life a final section we study the extent to which each of the current theories can aid in the search for a more Self-organization complete theory of life, and explain the characteristics of metabolic control analysis that make it essential for an adequate understanding of organisms. Contents 1. General introduction