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Gharibshahian M, Torkashvand M, Bavisi M, Aldaghi N, Alizadeh A. Recent advances in artificial intelligent strategies for tissue engineering and regenerative medicine. Skin Res Technol 2024; 30:e70016. [PMID: 39189880 PMCID: PMC11348508 DOI: 10.1111/srt.70016] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Accepted: 08/05/2024] [Indexed: 08/28/2024]
Abstract
BACKGROUND Tissue engineering and regenerative medicine (TERM) aim to repair or replace damaged or lost tissues or organs due to accidents, diseases, or aging, by applying different sciences. For this purpose, an essential part of TERM is the designing, manufacturing, and evaluating of scaffolds, cells, tissues, and organs. Artificial intelligence (AI) or the intelligence of machines or software can be effective in all areas where computers play a role. METHODS The "artificial intelligence," "machine learning," "tissue engineering," "clinical evaluation," and "scaffold" keywords used for searching in various databases and articles published from 2000 to 2024 were evaluated. RESULTS The combination of tissue engineering and AI has created a new generation of technological advancement in the biomedical industry. Experience in TERM has been refined using advanced design and manufacturing techniques. Advances in AI, particularly deep learning, offer an opportunity to improve scientific understanding and clinical outcomes in TERM. CONCLUSION The findings of this research show the high potential of AI, machine learning, and robots in the selection, design, and fabrication of scaffolds, cells, tissues, or organs, and their analysis, characterization, and evaluation after their implantation. AI can be a tool to accelerate the introduction of tissue engineering products to the bedside. HIGHLIGHTS The capabilities of artificial intelligence (AI) can be used in different ways in all the different stages of TERM and not only solve the existing limitations, but also accelerate the processes, increase efficiency and precision, reduce costs, and complications after transplantation. ML predicts which technologies have the most efficient and easiest path to enter the market and clinic. The use of AI along with these imaging techniques can lead to the improvement of diagnostic information, the reduction of operator errors when reading images, and the improvement of image analysis (such as classification, localization, regression, and segmentation).
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Affiliation(s)
- Maliheh Gharibshahian
- Nervous System Stem Cells Research CenterSemnan University of Medical SciencesSemnanIran
- Department of Tissue Engineering and Applied Cell SciencesSchool of MedicineSemnan University of Medical SciencesSemnanIran
| | | | - Mahya Bavisi
- Department of Tissue Engineering and Applied Cell SciencesSchool of Advanced Technologies in MedicineIran University of Medical SciencesTehranIran
| | - Niloofar Aldaghi
- Student Research CommitteeSchool of MedicineShahroud University of Medical SciencesShahroudIran
| | - Akram Alizadeh
- Nervous System Stem Cells Research CenterSemnan University of Medical SciencesSemnanIran
- Department of Tissue Engineering and Applied Cell SciencesSchool of MedicineSemnan University of Medical SciencesSemnanIran
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2
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Noble PA, Pozhitkov A, Singh K, Woods E, Liu C, Levin M, Javan G, Wan J, Abouhashem AS, Mathew-Steiner SS, Sen CK. Unraveling the Enigma of Organismal Death: Insights, Implications, and Unexplored Frontiers. Physiology (Bethesda) 2024; 39:0. [PMID: 38624244 PMCID: PMC11460531 DOI: 10.1152/physiol.00004.2024] [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: 01/12/2024] [Revised: 03/21/2024] [Accepted: 04/11/2024] [Indexed: 04/17/2024] Open
Abstract
Significant knowledge gaps exist regarding the responses of cells, tissues, and organs to organismal death. Examining the survival mechanisms influenced by metabolism and environment, this research has the potential to transform regenerative medicine, redefine legal death, and provide insights into life's physiological limits, paralleling inquiries in embryogenesis.
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Affiliation(s)
- Peter A Noble
- Department of Microbiology, University of Alabama Birmingham, Birmingham, Alabama, United States
| | - Alexander Pozhitkov
- Division of Research Informatics, Beckman Research Institute, City of Hope, Duarte, California, United States
| | - Kanhaiya Singh
- Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Erik Woods
- Ossium Health, Indianapolis, Indiana, United States
| | - Chunyu Liu
- Institute for Human Performance, Upstate Medical University, Syracuse, New York, United States
| | - Michael Levin
- Department of Biology, Tufts University, Medford, Massachusetts, United States
| | - Gulnaz Javan
- Department of Physical and Forensic Sciences, Alabama State University, Montgomery, Alabama, United States
| | - Jun Wan
- Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Ahmed Safwat Abouhashem
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, United States
| | - Shomita S Mathew-Steiner
- Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Chandan K Sen
- Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
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3
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Pio-Lopez L, Levin M. Aging as a loss of morphostatic information: A developmental bioelectricity perspective. Ageing Res Rev 2024; 97:102310. [PMID: 38636560 DOI: 10.1016/j.arr.2024.102310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 02/21/2024] [Accepted: 04/12/2024] [Indexed: 04/20/2024]
Abstract
Maintaining order at the tissue level is crucial throughout the lifespan, as failure can lead to cancer and an accumulation of molecular and cellular disorders. Perhaps, the most consistent and pervasive result of these failures is aging, which is characterized by the progressive loss of function and decline in the ability to maintain anatomical homeostasis and reproduce. This leads to organ malfunction, diseases, and ultimately death. The traditional understanding of aging is that it is caused by the accumulation of molecular and cellular damage. In this article, we propose a complementary view of aging from the perspective of endogenous bioelectricity which has not yet been integrated into aging research. We propose a view of aging as a morphostasis defect, a loss of biophysical prepattern information, encoding anatomical setpoints used for dynamic tissue and organ homeostasis. We hypothesize that this is specifically driven by abrogation of the endogenous bioelectric signaling that normally harnesses individual cell behaviors toward the creation and upkeep of complex multicellular structures in vivo. Herein, we first describe bioelectricity as the physiological software of life, and then identify and discuss the links between bioelectricity and life extension strategies and age-related diseases. We develop a bridge between aging and regeneration via bioelectric signaling that suggests a research program for healthful longevity via morphoceuticals. Finally, we discuss the broader implications of the homologies between development, aging, cancer and regeneration and how morphoceuticals can be developed for aging.
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Affiliation(s)
- Léo Pio-Lopez
- Allen Discovery Center, Tufts University, Medford, MA 02155, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA 02155, USA; Wyss Institute for Biologically Inspired Engineering, Boston, MA 02115, USA.
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4
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Mousavi R, Lobo D. Automatic design of gene regulatory mechanisms for spatial pattern formation. NPJ Syst Biol Appl 2024; 10:35. [PMID: 38565850 PMCID: PMC10987498 DOI: 10.1038/s41540-024-00361-5] [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: 11/21/2023] [Accepted: 03/19/2024] [Indexed: 04/04/2024] Open
Abstract
Gene regulatory mechanisms (GRMs) control the formation of spatial and temporal expression patterns that can serve as regulatory signals for the development of complex shapes. Synthetic developmental biology aims to engineer such genetic circuits for understanding and producing desired multicellular spatial patterns. However, designing synthetic GRMs for complex, multi-dimensional spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given two-dimensional spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms-including the number of genes necessary for the formation of the target spatial pattern-we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover complex genetic circuits producing spatial patterns.
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Affiliation(s)
- Reza Mousavi
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA
| | - Daniel Lobo
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA.
- Greenebaum Comprehensive Cancer Center and Center for Stem Cell Biology & Regenerative Medicine, University of Maryland, Baltimore, Baltimore, MD, USA.
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5
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Seifert G, Sealander A, Marzen S, Levin M. From reinforcement learning to agency: Frameworks for understanding basal cognition. Biosystems 2024; 235:105107. [PMID: 38128873 DOI: 10.1016/j.biosystems.2023.105107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/17/2023] [Accepted: 12/17/2023] [Indexed: 12/23/2023]
Abstract
Organisms play, explore, and mimic those around them. Is there a purpose to this behavior? Are organisms just behaving, or are they trying to achieve goals? We believe this is a false dichotomy. To that end, to understand organisms, we attempt to unify two approaches for understanding complex agents, whether evolved or engineered. We argue that formalisms describing multiscale competencies and goal-directedness in biology (e.g., TAME), and reinforcement learning (RL), can be combined in a symbiotic framework. While RL has been largely focused on higher-level organisms and robots of high complexity, TAME is naturally capable of describing lower-level organisms and minimal agents as well. We propose several novel questions that come from using RL/TAME to understand biology as well as ones that come from using biology to formulate new theory in AI. We hope that the research programs proposed in this piece shape future efforts to understand biological organisms and also future efforts to build artificial agents.
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Affiliation(s)
- Gabriella Seifert
- Department of Physics, University of Colorado, Boulder, CO 80309, USA; W. M. Keck Science Department, Pitzer, Scripps, and Claremont McKenna College, Claremont, CA 91711, USA
| | - Ava Sealander
- Department of Electrical Engineering, School of Engineering and Applied Sciences, Columbia University, New York, NY 10027, USA; W. M. Keck Science Department, Pitzer, Scripps, and Claremont McKenna College, Claremont, CA 91711, USA
| | - Sarah Marzen
- W. M. Keck Science Department, Pitzer, Scripps, and Claremont McKenna College, Claremont, CA 91711, USA.
| | - Michael Levin
- Department of Biology, Tufts University, Medford, MA 02155, USA; Allen Discovery Center at Tufts University, Medford, MA 02155, USA
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6
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Jeyaraman M, Ratna HVK, Jeyaraman N, Venkatesan A, Ramasubramanian S, Yadav S. Leveraging Artificial Intelligence and Machine Learning in Regenerative Orthopedics: A Paradigm Shift in Patient Care. Cureus 2023; 15:e49756. [PMID: 38161806 PMCID: PMC10757680 DOI: 10.7759/cureus.49756] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/28/2023] [Indexed: 01/03/2024] Open
Abstract
The integration of artificial intelligence (AI) and machine learning (ML) into regenerative orthopedics heralds a paradigm shift in clinical methodologies and patient management. This review article scrutinizes AI's role in augmenting diagnostic accuracy, refining predictive models, and customizing patient care in orthopedic medicine. Focusing on innovations such as KeyGene and CellNet, we illustrate AI's adeptness in navigating complex genomic datasets, cellular differentiation, and scaffold biodegradation, which are critical components of tissue engineering. Despite its transformative potential, AI's clinical adoption remains in its infancy, contending with challenges in validation, ethical oversight, and model training for clinical relevance. This review posits AI as a vital complement to human intelligence (HI), advocating for an interdisciplinary approach that merges AI's computational prowess with medical expertise to fulfill precision medicine's promise. By analyzing historical and contemporary developments in AI, from the foundational theories of McCullough and Pitts to sophisticated neural networks, the paper emphasizes the need for a synergistic alliance between AI and HI. This collaboration is imperative for improving surgical outcomes, streamlining therapeutic modalities, and enhancing the quality of patient care. Our article calls for robust interdisciplinary strategies to overcome current obstacles and harness AI's full potential in revolutionizing patient outcomes, thereby significantly contributing to the advancement of regenerative orthopedics and the broader field of scientific research.
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Affiliation(s)
- Madhan Jeyaraman
- Orthopaedics, ACS Medical College and Hospital, Dr. MGR Educational and Research Institute, Chennai, IND
| | | | - Naveen Jeyaraman
- Orthopaedics, ACS Medical College and Hospital, Dr. MGR Educational and Research Institute, Chennai, IND
| | | | | | - Sankalp Yadav
- Medicine, Shri Madan Lal Khurana Chest Clinic, New Delhi, IND
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7
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Mousavi R, Lobo D. Automatic design of gene regulatory mechanisms for spatial pattern formation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.26.550573. [PMID: 37546866 PMCID: PMC10402059 DOI: 10.1101/2023.07.26.550573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Synthetic developmental biology aims to engineer gene regulatory mechanisms (GRMs) for understanding and producing desired multicellular patterns and shapes. However, designing GRMs for spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms-including the number of genes necessary for the formation of the target pattern-we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover pattern-producing genetic circuits.
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Affiliation(s)
- Reza Mousavi
- Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
| | - Daniel Lobo
- Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
- Greenebaum Comprehensive Cancer Center and Center for Stem Cell Biology & Regenerative Medicine, University of Maryland, School of Medicine, 22 S. Greene Street, Baltimore, MD 21201, USA
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8
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Pio-Lopez L, Levin M. Morphoceuticals: perspectives for discovery of drugs targeting anatomical control mechanisms in regenerative medicine, cancer and aging. Drug Discov Today 2023; 28:103585. [PMID: 37059328 DOI: 10.1016/j.drudis.2023.103585] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/18/2023] [Accepted: 04/06/2023] [Indexed: 04/16/2023]
Abstract
Morphoceuticals are a new class of interventions that target the setpoints of anatomical homeostasis for efficient, modular control of growth and form. Here, we focus on a subclass: electroceuticals, which specifically target the cellular bioelectrical interface. Cellular collectives in all tissues form bioelectrical networks via ion channels and gap junctions that process morphogenetic information, controlling gene expression and allowing cell networks to adaptively and dynamically control growth and pattern formation. Recent progress in understanding this physiological control system, including predictive computational models, suggests that targeting bioelectrical interfaces can control embryogenesis and maintain shape against injury, senescence and tumorigenesis. We propose a roadmap for drug discovery focused on manipulating endogenous bioelectric signaling for regenerative medicine, cancer suppression and antiaging therapeutics. Teaser: By taking advantage of the native problem-solving competencies of cells and tissues, a new kind of top-down approach to biomedicine becomes possible. Bioelectricity offers an especially tractable interface for interventions targeting the software of life for regenerative medicine applications.
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Affiliation(s)
- Léo Pio-Lopez
- Allen Discovery Center, Tufts University, Medford, MA, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA.
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9
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Pio-Lopez L, Kuchling F, Tung A, Pezzulo G, Levin M. Active inference, morphogenesis, and computational psychiatry. Front Comput Neurosci 2022; 16:988977. [PMID: 36507307 PMCID: PMC9731232 DOI: 10.3389/fncom.2022.988977] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 10/17/2022] [Indexed: 11/26/2022] Open
Abstract
Active inference is a leading theory in neuroscience that provides a simple and neuro-biologically plausible account of how action and perception are coupled in producing (Bayes) optimal behavior; and has been recently used to explain a variety of psychopathological conditions. In parallel, morphogenesis has been described as the behavior of a (non-neural) cellular collective intelligence solving problems in anatomical morphospace. In this article, we establish a link between the domains of cell biology and neuroscience, by analyzing disorders of morphogenesis as disorders of (active) inference. The aim of this article is three-fold. We want to: (i) reveal a connection between disorders of morphogenesis and disorders of active inference as apparent in psychopathological conditions; (ii) show how disorders of morphogenesis can be simulated using active inference; (iii) suggest that active inference can shed light on developmental defects or aberrant morphogenetic processes, seen as disorders of information processing, and perhaps suggesting novel intervention and repair strategies. We present four simulations illustrating application of these ideas to cellular behavior during morphogenesis. Three of the simulations show that the same forms of aberrant active inference (e.g., deficits of sensory attenuation and low sensory precision) that have been used to explain psychopathological conditions (e.g., schizophrenia and autism) also produce familiar disorders of development and morphogenesis when implemented at the level of the collective behavior of a group of cells. The fourth simulation involves two cells with too high precision, in which we show that the reduction of concentration signaling and sensitivity to the signals of other cells treats the development defect. Finally, we present the results of an experimental test of one of the model's predictions in early Xenopus laevis embryos: thioridazine (a dopamine antagonist that may reduce sensory precision in biological systems) induced developmental (anatomical) defects as predicted. The use of conceptual and empirical tools from neuroscience to understand the morphogenetic behavior of pre-neural agents offers the possibility of new approaches in regenerative medicine and evolutionary developmental biology.
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Affiliation(s)
- Léo Pio-Lopez
- Allen Discovery Center, Tufts University, Medford, MA, United States
| | - Franz Kuchling
- Allen Discovery Center, Tufts University, Medford, MA, United States
| | - Angela Tung
- Allen Discovery Center, Tufts University, Medford, MA, United States
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, United States
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, United States
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10
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Maric DM, Velikic G, Maric DL, Supic G, Vojvodic D, Petric V, Abazovic D. Stem Cell Homing in Intrathecal Applications and Inspirations for Improvement Paths. Int J Mol Sci 2022; 23:ijms23084290. [PMID: 35457107 PMCID: PMC9027729 DOI: 10.3390/ijms23084290] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 03/26/2022] [Accepted: 04/01/2022] [Indexed: 02/04/2023] Open
Abstract
A transplanted stem cell homing is a directed migration from the application site to the targeted tissue. Intrathecal application of stem cells is their direct delivery to cerebrospinal fluid, which defines the homing path from the point of injection to the brain. In the case of neurodegenerative diseases, this application method has the advantage of no blood–brain barrier restriction. However, the homing efficiency still needs improvement and homing mechanisms elucidation. Analysis of current research results on homing mechanisms in the light of intrathecal administration revealed a discrepancy between in vivo and in vitro results and a gap between preclinical and clinical research. Combining the existing research with novel insights from cutting-edge biochips, nano, and other technologies and computational models may bridge this gap faster.
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Affiliation(s)
- Dusan M. Maric
- Department for Research and Development, Clinic Orto MD-Parks Dr Dragi Hospital, 21000 Novi Sad, Serbia;
- Faculty of Dentistry Pancevo, University Business Academy, 26000 Pancevo, Serbia
- Vincula Biotech Group, 11000 Belgrade, Serbia;
| | - Gordana Velikic
- Department for Research and Development, Clinic Orto MD-Parks Dr Dragi Hospital, 21000 Novi Sad, Serbia;
- Vincula Biotech Group, 11000 Belgrade, Serbia;
- Correspondence: (G.V.); (D.L.M.)
| | - Dusica L. Maric
- Department of Anatomy, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia
- Correspondence: (G.V.); (D.L.M.)
| | - Gordana Supic
- Institute for Medical Research, Military Medical Academy, 11000 Belgrade, Serbia; (G.S.); (D.V.)
- Medical Faculty of Military Medical Academy, University of Defense, 11000 Belgrade, Serbia
| | - Danilo Vojvodic
- Institute for Medical Research, Military Medical Academy, 11000 Belgrade, Serbia; (G.S.); (D.V.)
- Medical Faculty of Military Medical Academy, University of Defense, 11000 Belgrade, Serbia
| | - Vedrana Petric
- Infectious Diseases Clinic, Clinical Center of Vojvodina, 21000 Novi Sad, Serbia;
- Department of Infectious Diseases, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia
| | - Dzihan Abazovic
- Vincula Biotech Group, 11000 Belgrade, Serbia;
- Department for Regenerative Medicine, Biocell Hospital, 11000 Belgrade, Serbia
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Grodstein J, Levin M. A Computational Approach to Explaining Bioelectrically Induced Persistent, Stochastic Changes of Axial Polarity in Planarian Regeneration. Bioelectricity 2022; 4:18-30. [PMID: 39372228 PMCID: PMC11450330 DOI: 10.1089/bioe.2021.0036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Morphogenesis results when cells cooperate to construct a specific anatomical structure. The behavior of such cell swarms exhibits not only robustness but also plasticity with respect to what specific anatomies will be built. Important aspects of evolutionary biology, regenerative medicine, and cancer are impacted by the algorithms by which instructive information guides invariant or stochastic outcomes of such collective activity. Planarian flatworms are an important model system in this field, as flatworms reliably regenerate a primary body axis after diverse kinds of injury. Importantly, the number of heads to which they regenerate is not determined genetically: lines of worms can be produced, which, with no further manipulation, regenerate as two-headed (2H) worms, or as "Cryptic" worms. When cut into pieces, Cryptic worms produce one-headed (1H) and 2H regenerates stochastically. Neural and bioelectric mechanisms have been proposed to explain aspects of the regenerative dataset. However, these models have not been unified and do not explain all of the Cryptic worm data. In this study, we propose a model in which two separate systems (a bioelectric circuit and a neural polarity mechanism) compete to determine the anatomical structure of a regenerate. We show how our model accounts for existing data and provides a consistent synthesis of mechanisms that explain both the robustness of planarian regeneration and its remarkable re-writability toward novel stable and stochastic anatomical states.
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Affiliation(s)
- Joel Grodstein
- Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts, USA
| | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, Massachusetts, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, Massachusetts, USA
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12
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Martinez P, Ballarin L, Ereskovsky AV, Gazave E, Hobmayer B, Manni L, Rottinger E, Sprecher SG, Tiozzo S, Varela-Coelho A, Rinkevich B. Articulating the "stem cell niche" paradigm through the lens of non-model aquatic invertebrates. BMC Biol 2022; 20:23. [PMID: 35057814 PMCID: PMC8781081 DOI: 10.1186/s12915-022-01230-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 01/12/2022] [Indexed: 12/13/2022] Open
Abstract
Stem cells (SCs) in vertebrates typically reside in "stem cell niches" (SCNs), morphologically restricted tissue microenvironments that are important for SC survival and proliferation. SCNs are broadly defined by properties including physical location, but in contrast to vertebrates and other "model" organisms, aquatic invertebrate SCs do not have clearly documented niche outlines or properties. Life strategies such as regeneration or asexual reproduction may have conditioned the niche architectural variability in aquatic or marine animal groups. By both establishing the invertebrates SCNs as independent types, yet allowing inclusiveness among them, the comparative analysis will allow the future functional characterization of SCNs.
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Affiliation(s)
- P Martinez
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Av. Diagonal 643, 08028, Barcelona, Spain.
- Institut Català de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
| | - L Ballarin
- Department of Biology, University of Padova, Via U. Bassi 58/B, 35100, Padova, Italy
| | - A V Ereskovsky
- Aix Marseille University, Avignon Université, CNRS, IRD, IMBE, Marseille, France
- St. Petersburg State University, Biological Faculty, Universitetskaya emb. 7/9, St. Petersburg, 199034, Russia
- N. K. Koltzov Institute of Developmental Biology, Russian Academy of Sciences, Vavilova Street 26, Moscow, 119334, Russia
| | - E Gazave
- Université de Paris, CNRS, Institut Jacques Monod, F-75006, Paris, France
| | - B Hobmayer
- Department of Zoology and Center of Molecular Biosciences, University of Innsbruck, Technikerstr. 25, 6020, Innsbruck, Austria
| | - L Manni
- Department of Biology, University of Padova, Via U. Bassi 58/B, 35100, Padova, Italy
| | - E Rottinger
- Université Côte d'Azur, CNRS, INSERM, Institute for Research on Cancer and Aging, Nice (IRCAN), Nice, France
- Université Côte d'Azur, Federative Research Institute - Marine Resources (IFR MARRES), Nice, France
| | - S G Sprecher
- Department of Biology, University of Fribourg, Chemin du Musee 10, 1700, Fribourg, Switzerland
| | - S Tiozzo
- Sorbonne Université, CNRS, Laboratoire de Biologie du Développement de Villefranche-sur-mer (LBDV), Paris, France
| | - A Varela-Coelho
- ITQB NOVA, Instituto de Tecnologia Química e Biológica António Xavier, Av. da República, 2780-157, Oeiras, Portugal
| | - B Rinkevich
- Israel Oceanography and Limnological Research, National Institute of Oceanography, Tel Shikmona, P.O. Box 8030, 31080, Haifa, Israel.
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13
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Abstract
Extracting mechanistic knowledge from the spatial and temporal phenotypes of morphogenesis is a current challenge due to the complexity of biological regulation and their feedback loops. Furthermore, these regulatory interactions are also linked to the biophysical forces that shape a developing tissue, creating complex interactions responsible for emergent patterns and forms. Here we show how a computational systems biology approach can aid in the understanding of morphogenesis from a mechanistic perspective. This methodology integrates the modeling of tissues and whole-embryos with dynamical systems, the reverse engineering of parameters or even whole equations with machine learning, and the generation of precise computational predictions that can be tested at the bench. To implement and perform the computational steps in the methodology, we present user-friendly tools, computer code, and guidelines. The principles of this methodology are general and can be adapted to other model organisms to extract mechanistic knowledge of their morphogenesis.
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Affiliation(s)
- Jason M Ko
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA
| | - Reza Mousavi
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA
| | - Daniel Lobo
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA.
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14
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Metabolic cost of development, regeneration, and reproduction in the planarian Schmidtea mediterranea. Comp Biochem Physiol A Mol Integr Physiol 2021; 265:111127. [PMID: 34968657 DOI: 10.1016/j.cbpa.2021.111127] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 12/14/2021] [Accepted: 12/14/2021] [Indexed: 12/26/2022]
Abstract
Planaria are known for their ability to completely regenerate upon fissioning or experimental amputation. Yet, metabolic costs of regeneration have not been directly measured in planaria. Our goal was to establish the relationships between oxygen consumption (V̇O2), regeneration, and reproductive mode for asexual and sexual strains of Schmidtea mediterranea. We hypothesized that V̇O2 would vary by regeneration day for both sexual and asexual S. mediterranea, reflecting different costs of tissue reconstruction, but with an additional cost for regenerating sexual organs. Testes regeneration and body mass, as indicators of regeneration progress, and routine mass-specific V̇O2 as a function of maturity, regeneration, and reproductive mode, were measured over a 22-day regeneration period. Testes growth was highest in sexually mature adults, ~1/2 that in 14-day post-amputation sexual adults, and not detectable in juveniles and hatchlings. Mass-specific routine V̇O2 in sexuals was highest in mature controls at ~23 μl O2/g/h, but only half that in juveniles, hatchlings, and 14 day post-amputation adults. Both intact and 14-day post-amputation asexuals had a mass-specific routine V̇O2 of ~10-12 μl O2/g/h. The sum of V̇O2 of all amputated sections was ~100% higher than pre-amputation levels in the first 6 days of regeneration in asexuals, but not sexuals. There was no significant difference in V̇O2 of head, middle, and tail sections during regeneration. Overall, the highest metabolic costs associated with regeneration occurred during the initial 1-6 days of regeneration in both strains, but regeneration costs for sexual structures were not reflected in major V̇O2 differences between sexual and asexual strains.
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15
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Minh-Thai TN, Samarasinghe S, Levin M. A Comprehensive Conceptual and Computational Dynamics Framework for Autonomous Regeneration Systems. ARTIFICIAL LIFE 2021; 27:80-104. [PMID: 34473826 DOI: 10.1162/artl_a_00343] [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: 06/13/2023]
Abstract
Many biological organisms regenerate structure and function after damage. Despite the long history of research on molecular mechanisms, many questions remain about algorithms by which cells can cooperate towards the same invariant morphogenetic outcomes. Therefore, conceptual frameworks are needed not only for motivating hypotheses for advancing the understanding of regeneration processes in living organisms, but also for regenerative medicine and synthetic biology. Inspired by planarian regeneration, this study offers a novel generic conceptual framework that hypothesizes mechanisms and algorithms by which cell collectives may internally represent an anatomical target morphology towards which they build after damage. Further, the framework contributes a novel nature-inspired computing method for self-repair in engineering and robotics. Our framework, based on past in vivo and in silico studies on planaria, hypothesizes efficient novel mechanisms and algorithms to achieve complete and accurate regeneration of a simple in silico flatwormlike organism from any damage, much like the body-wide immortality of planaria, with minimal information and algorithmic complexity. This framework that extends our previous circular tissue repair model integrates two levels of organization: tissue and organism. In Level 1, three individual in silico tissues (head, body, and tail-each with a large number of tissue cells and a single stem cell at the centre) repair themselves through efficient local communications. Here, the contribution extends our circular tissue model to other shapes and invests them with tissue-wide immortality through an information field holding the minimum body plan. In Level 2, individual tissues combine to form a simple organism. Specifically, the three stem cells form a network that coordinates organism-wide regeneration with the help of Level 1. Here we contribute novel concepts for collective decision-making by stem cells for stem cell regeneration and large-scale recovery. Both levels (tissue cells and stem cells) represent networks that perform simple neural computations and form a feedback control system. With simple and limited cellular computations, our framework minimises computation and algorithmic complexity to achieve complete recovery. We report results from computer simulations of the framework to demonstrate its robustness in recovering the organism after any injury. This comprehensive hypothetical framework that significantly extends the existing biological regeneration models offers a new way to conceptualise the information-processing aspects of regeneration, which may also help design living and non-living self-repairing agents.
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Affiliation(s)
- Tran Nguyen Minh-Thai
- Lincoln University, Complex Systems, Big Data and Informatics Initiative (CSBII)
- Can Tho University, College of Information and Communication Technology
| | - Sandhya Samarasinghe
- Lincoln University, Complex Systems, Big Data and Informatics Initiative (CSBII).
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16
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Chen X, Liu Y, Zhu X, Lv Q. Comparative Proteome Analysis Indicates The Divergence between The Head and Tail Regeneration in Planarian. CELL JOURNAL 2021; 23:640-649. [PMID: 34939757 PMCID: PMC8665983 DOI: 10.22074/cellj.2021.7689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 12/06/2020] [Indexed: 11/04/2022]
Abstract
OBJECTIVE Even a small fragment from the body of planarian can regenerate an entire animal, implying that the different fragments from this flatworm eventually reach the same solution. In this study, our aim was to reveal the differences and similarities in mechanisms between different regenerating fragments from this worm. MATERIALS AND METHODS In this experimental study, we profiled the dynamic proteome of regenerating head and tail to reveal the differences and similarities between different regenerating fragments using 2-DE combined with MALDITOF/ TOF MS. RESULTS Proteomic profiles of head and tail regeneration identified a total of 516 differential expressed proteins (DEPs) and showed a great difference in quantity and fold changes of proteome profiles between the two scenarios. Briefly, out of the 516 DEPs, 314 were identified to be specific for anterior regeneration, while 165 were specific for posterior regeneration. Bioinformatics analysis showed a wide discrepancy in biological activities between two regenerative processes; especially, differentiation and development and signal transduction in head regeneration were much more complex than that in tail regeneration. Protein functional analysis combined with protein-protein interaction (PPI) analysis showed a significant contribution of both Wnt and BMP signaling pathways to head regeneration not but tail regeneration. Additionally, several novel proteins showed completely opposite expression between head and tail regeneration. CONCLUSION Proteomic profiles of head and tail regeneration identified a total of 516 differential expressed proteins (DEPs) and showed a great difference in quantity and fold changes of proteome profiles between the two scenarios. Briefly, out of the 516 DEPs, 314 were identified to be specific for anterior regeneration, while 165 were specific for posterior regeneration. Bioinformatics analysis showed a wide discrepancy in biological activities between two regenerative processes; especially, differentiation and development and signal transduction in head regeneration were much more complex than that in tail regeneration. Protein functional analysis combined with protein-protein interaction (PPI) analysis showed a significant contribution of both Wnt and BMP signaling pathways to head regeneration not but tail regeneration. Additionally, several novel proteins showed completely opposite expression between head and tail regeneration.
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Affiliation(s)
- Xiaoguang Chen
- Animal Science and Technology SchoolHenan University of Science and TechnologyLuoyangChina
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17
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Mukherjee S, Yadav G, Kumar R. Recent trends in stem cell-based therapies and applications of artificial intelligence in regenerative medicine. World J Stem Cells 2021; 13:521-541. [PMID: 34249226 PMCID: PMC8246250 DOI: 10.4252/wjsc.v13.i6.521] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/22/2021] [Accepted: 05/20/2021] [Indexed: 02/06/2023] Open
Abstract
Stem cells are undifferentiated cells that can self-renew and differentiate into diverse types of mature and functional cells while maintaining their original identity. This profound potential of stem cells has been thoroughly investigated for its significance in regenerative medicine and has laid the foundation for cell-based therapies. Regenerative medicine is rapidly progressing in healthcare with the prospect of repair and restoration of specific organs or tissue injuries or chronic disease conditions where the body’s regenerative process is not sufficient to heal. In this review, the recent advances in stem cell-based therapies in regenerative medicine are discussed, emphasizing mesenchymal stem cell-based therapies as these cells have been extensively studied for clinical use. Recent applications of artificial intelligence algorithms in stem cell-based therapies, their limitation, and future prospects are highlighted.
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Affiliation(s)
- Sayali Mukherjee
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow 226028, Uttar Pradesh, India
| | - Garima Yadav
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow 226028, Uttar Pradesh, India
| | - Rajnish Kumar
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow 226028, Uttar Pradesh, India
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18
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Abstract
It is well known that electrical signals are deeply associated with living entities. Much of our understanding of excitable tissues is derived from studies of specialized cells of neurons or myocytes. However, electric potential is present in all cell types and results from the differential partitioning of ions across membranes. This electrical potential correlates with cell behavior and tissue organization. In recent years, there has been exciting, and broadly unexpected, evidence linking the regulation of development to bioelectric signals. However, experimental modulation of electrical potential can have multifaceted and pleiotropic effects, which makes dissecting the role of electrical signals in development difficult. Here, I review evidence that bioelectric cues play defined instructional roles in orchestrating development and regeneration, and further outline key areas in which to refine our understanding of this signaling mechanism.
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Affiliation(s)
- Matthew P. Harris
- Department of Genetics, Harvard Medical School, Department of Orthopaedics, Boston Children's Hospital, 300 Longwood Avenue Enders 260, Boston MA 02115, USA
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19
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Pezzulo G, LaPalme J, Durant F, Levin M. Bistability of somatic pattern memories: stochastic outcomes in bioelectric circuits underlying regeneration. Philos Trans R Soc Lond B Biol Sci 2021; 376:20190765. [PMID: 33550952 PMCID: PMC7935058 DOI: 10.1098/rstb.2019.0765] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/06/2020] [Indexed: 02/06/2023] Open
Abstract
Nervous systems' computational abilities are an evolutionary innovation, specializing and speed-optimizing ancient biophysical dynamics. Bioelectric signalling originated in cells' communication with the outside world and with each other, enabling cooperation towards adaptive construction and repair of multicellular bodies. Here, we review the emerging field of developmental bioelectricity, which links the field of basal cognition to state-of-the-art questions in regenerative medicine, synthetic bioengineering and even artificial intelligence. One of the predictions of this view is that regeneration and regulative development can restore correct large-scale anatomies from diverse starting states because, like the brain, they exploit bioelectric encoding of distributed goal states-in this case, pattern memories. We propose a new interpretation of recent stochastic regenerative phenotypes in planaria, by appealing to computational models of memory representation and processing in the brain. Moreover, we discuss novel findings showing that bioelectric changes induced in planaria can be stored in tissue for over a week, thus revealing that somatic bioelectric circuits in vivo can implement a long-term, re-writable memory medium. A consideration of the mechanisms, evolution and functionality of basal cognition makes novel predictions and provides an integrative perspective on the evolution, physiology and biomedicine of information processing in vivo. This article is part of the theme issue 'Basal cognition: multicellularity, neurons and the cognitive lens'.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Joshua LaPalme
- Allen Discovery Center, Tufts University, Medford, MA, USA
| | - Fallon Durant
- Allen Discovery Center, Tufts University, Medford, MA, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, USA
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20
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Martinez O, Sire S, Saunier A, Malgouyres JM, Fournier A, Vignet C. Behavioral responses of three freshwater planaria species to light, visual and olfactory stimuli: Setting the stage for further ecotoxicological studies. Behav Processes 2020; 183:104295. [PMID: 33383124 DOI: 10.1016/j.beproc.2020.104295] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 12/07/2020] [Accepted: 12/07/2020] [Indexed: 11/17/2022]
Abstract
Planarians are freshwater flatworms commonly used as environmental bioindicator due to their sensitivity of response and their ease of culturing in lab. Nevertheless, to date, very few studies describing their behavior have been led. This work aims to fill the literature gap by providing preliminary results through six behavioral challenges (locomotion, exploration, light stress, planarian light/dark test, shoaling and foraging) conducted with three different species Dugesia tigrina, Schmidtea mediterranea and Schmidtea polychroa. The behavioral responses of every species in each of these six assays were recorded and differences between species were highlighted, depending on the assays and conditions. Schmidtea polychroa is less active than the two others and had the highest light aversion. Reactions observed in response to diverse and realistic stimuli helped us to select the most suitable tests and choose the species that seem the most appropriate for future ecotoxicological and neurophysiological tests. Four tests - out of the six tested- seem reliable in order to standardize planarian behavioral tests.
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Affiliation(s)
- Odile Martinez
- Biochimie et Toxicologie des Substances Bioactives (BTSB), EA7417, INU Champollion, Place de Verdun, 81000, Albi, France
| | - Sacha Sire
- Biochimie et Toxicologie des Substances Bioactives (BTSB), EA7417, INU Champollion, Place de Verdun, 81000, Albi, France
| | - Alice Saunier
- Biochimie et Toxicologie des Substances Bioactives (BTSB), EA7417, INU Champollion, Place de Verdun, 81000, Albi, France
| | - Jean-Michel Malgouyres
- Biochimie et Toxicologie des Substances Bioactives (BTSB), EA7417, INU Champollion, Place de Verdun, 81000, Albi, France
| | - Alice Fournier
- Biochimie et Toxicologie des Substances Bioactives (BTSB), EA7417, INU Champollion, Place de Verdun, 81000, Albi, France
| | - Caroline Vignet
- Biochimie et Toxicologie des Substances Bioactives (BTSB), EA7417, INU Champollion, Place de Verdun, 81000, Albi, France.
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21
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Cervera J, Levin M, Mafe S. Bioelectrical Coupling of Single-Cell States in Multicellular Systems. J Phys Chem Lett 2020; 11:3234-3241. [PMID: 32243754 DOI: 10.1021/acs.jpclett.0c00641] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
The spatiotemporal distributions of signaling ions and molecules that modulate biochemical pathways in nonexcitable cells are influenced by multicellular electric potentials. These potentials act as distributed controllers encoding instructive spatial patterns in development and regeneration. We review experimental facts and discuss recent bioelectrical models that provide new physical insights and complement biochemical approaches. Single-cell states are modulated at the multicellular level because of the coupling between neighboring cells, thus allowing memories and multicellular patterns. The model is based on (i) two generic voltage-gated ion channels that promote the polarized and depolarized cell states, (ii) a feedback mechanism for the transcriptional and bioelectrical regulations, and (iii) voltage-gated intercellular conductances that allow a dynamic intercellular connectivity. The simulations provide steady-state and oscillatory multicellular states that help explain aspects of development and guide experimental procedures attempting to establish instructive bioelectrical patterns based on electric potentials and currents to regulate cell behavior and morphogenesis.
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Affiliation(s)
- Javier Cervera
- Dept. Termodinàmica, Facultat de Física, Universitat de València, E-46100 Burjassot, Spain
| | - Michael Levin
- Dept. of Biology and Allen Discovery Center at Tufts University, Medford, Massachusetts 02155-4243, United States
| | - Salvador Mafe
- Dept. Termodinàmica, Facultat de Física, Universitat de València, E-46100 Burjassot, Spain
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22
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Tung A, Levin M. Extra-genomic instructive influences in morphogenesis: A review of external signals that regulate growth and form. Dev Biol 2020; 461:1-12. [PMID: 31981561 DOI: 10.1016/j.ydbio.2020.01.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 01/21/2020] [Accepted: 01/21/2020] [Indexed: 12/18/2022]
Abstract
Embryonic development and regeneration accomplish a remarkable feat: individual cells work together to create or repair complex anatomical structures. What is the source of the instructive signals that specify these invariant and robust organ-level outcomes? The most frequently studied source of morphogenetic control is the host genome and its transcriptional circuits. However, it is now apparent that significant information affecting patterning also arrives from outside of the body. Both biotic and physical factors, including temperature and various molecular signals emanating from pathogens, commensals, and conspecific organisms, affect developmental outcomes. Here, we review examples in which anatomical patterning decisions are strongly impacted by lateral signals that originate from outside of the zygotic genome. The endogenous pathways targeted by these influences often show transgenerational effects, enabling them to shape the evolution of anatomies even faster than traditional Baldwin-type assimilation. We also discuss recent advances in the biophysics of morphogenetic controls and speculate on additional sources of important patterning information which could be exploited to better understand the evolution of bodies and to design novel approaches for regenerative medicine.
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Affiliation(s)
- Angela Tung
- Department of Biology and Allen Discovery Center at Tufts University, Medford, MA, USA
| | - Michael Levin
- Department of Biology and Allen Discovery Center at Tufts University, Medford, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
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23
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Herath S, Lobo D. Cross-inhibition of Turing patterns explains the self-organized regulatory mechanism of planarian fission. J Theor Biol 2020; 485:110042. [DOI: 10.1016/j.jtbi.2019.110042] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 09/24/2019] [Accepted: 10/10/2019] [Indexed: 12/13/2022]
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24
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Dzobo K, Adotey S, Thomford NE, Dzobo W. Integrating Artificial and Human Intelligence: A Partnership for Responsible Innovation in Biomedical Engineering and Medicine. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2019; 24:247-263. [PMID: 31313972 DOI: 10.1089/omi.2019.0038] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Historically, the term "artificial intelligence" dates to 1956 when it was first used in a conference at Dartmouth College in the US. Since then, the development of artificial intelligence has in part been shaped by the field of neuroscience. By understanding the human brain, scientists have attempted to build new intelligent machines capable of performing complex tasks akin to humans. Indeed, future research into artificial intelligence will continue to benefit from the study of the human brain. While the development of artificial intelligence algorithms has been fast paced, the actual use of most artificial intelligence (AI) algorithms in biomedical engineering and clinical practice is still markedly below its conceivably broader potentials. This is partly because for any algorithm to be incorporated into existing workflows it has to stand the test of scientific validation, clinical and personal utility, application context, and is equitable as well. In this context, there is much to be gained by combining AI and human intelligence (HI). Harnessing Big Data, computing power and storage capacities, and addressing societal issues emergent from algorithm applications, demand deploying HI in tandem with AI. Very few countries, even economically developed states, lack adequate and critical governance frames to best understand and steer the AI innovation trajectories in health care. Drug discovery and translational pharmaceutical research stand to gain from AI technology provided they are also informed by HI. In this expert review, we analyze the ways in which AI applications are likely to traverse the continuum of life from birth to death, and encompassing not only humans but also all animal, plant, and other living organisms that are increasingly touched by AI. Examples of AI applications include digital health, diagnosis of diseases in newborns, remote monitoring of health by smart devices, real-time Big Data analytics for prompt diagnosis of heart attacks, and facial analysis software with consequences on civil liberties. While we underscore the need for integration of AI and HI, we note that AI technology does not have to replace medical specialists or scientists and rather, is in need of such expert HI. Altogether, AI and HI offer synergy for responsible innovation and veritable prospects for improving health care from prevention to diagnosis to therapeutics while unintended consequences of automation emergent from AI and algorithms should be borne in mind on scientific cultures, work force, and society at large.
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Affiliation(s)
- Kevin Dzobo
- International Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town Component, Wernher and Beit Building (South), UCT Medical Campus, Anzio Road, Observatory 7925, Cape Town, South Africa.,Division of Medical Biochemistry and Institute of Infectious Disease and Molecular Medicine, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Sampson Adotey
- International Development Innovation Network, D-Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Nicholas E Thomford
- Pharmacogenetics Research Group, Division of Human Genetics, Department of Pathology and Institute of Infectious Diseases and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Observatory 7925, Cape Town, South Africa
| | - Witness Dzobo
- Pathology and Immunology Department, University Hospital Southampton, Mail Point B, Tremona Road, Southampton, UK.,University of Portsmouth, Faculty of Science, St Michael's Building, White Swan Road, Portsmouth, UK
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25
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Beane WS, Adams DS, Morokuma J, Levin M. Live imaging of intracellular pH in planarians using the ratiometric fluorescent dye SNARF-5F-AM. Biol Methods Protoc 2019; 4:bpz005. [PMID: 31206034 PMCID: PMC6541873 DOI: 10.1093/biomethods/bpz005] [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] [Received: 02/11/2019] [Revised: 04/23/2019] [Accepted: 05/02/2019] [Indexed: 11/12/2022] Open
Abstract
Physiological parameters such as resting potential and pH are increasingly recognized as important regulators of cell activity and tissue-level events in regeneration, development, and cancer. The availability of fluorescent reporter dyes has greatly increased the ability to track these properties in vivo. The planarian flatworm is an important and highly tractable model system for regeneration, stem cell biology, and neuroscience; however, no protocols have been published for investigating pH in this system. Here, we report a simple and effective protocol for imaging pH gradients in living planaria suitable for intact and regenerating flatworms.
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Affiliation(s)
- Wendy Scott Beane
- Department of Biology and Center for Regenerative and Developmental Biology, Tufts University, Medford, MA 02155, USA
| | - Dany Spencer Adams
- Department of Biology and Center for Regenerative and Developmental Biology, Tufts University, Medford, MA 02155, USA
| | - Junji Morokuma
- Department of Biology and Center for Regenerative and Developmental Biology, Tufts University, Medford, MA 02155, USA
| | - Michael Levin
- Department of Biology and Center for Regenerative and Developmental Biology, Tufts University, Medford, MA 02155, USA
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26
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Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems. Phys Life Rev 2019; 33:88-108. [PMID: 31320316 DOI: 10.1016/j.plrev.2019.06.001] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 06/11/2019] [Indexed: 12/11/2022]
Abstract
Recent advances in molecular biology such as gene editing [1], bioelectric recording and manipulation [2] and live cell microscopy using fluorescent reporters [3], [4] - especially with the advent of light-controlled protein activation through optogenetics [5] - have provided the tools to measure and manipulate molecular signaling pathways with unprecedented spatiotemporal precision. This has produced ever increasing detail about the molecular mechanisms underlying development and regeneration in biological organisms. However, an overarching concept - that can predict the emergence of form and the robust maintenance of complex anatomy - is largely missing in the field. Classic (i.e., dynamic systems and analytical mechanics) approaches such as least action principles are difficult to use when characterizing open, far-from equilibrium systems that predominate in Biology. Similar issues arise in neuroscience when trying to understand neuronal dynamics from first principles. In this (neurobiology) setting, a variational free energy principle has emerged based upon a formulation of self-organization in terms of (active) Bayesian inference. The free energy principle has recently been applied to biological self-organization beyond the neurosciences [6], [7]. For biological processes that underwrite development or regeneration, the Bayesian inference framework treats cells as information processing agents, where the driving force behind morphogenesis is the maximization of a cell's model evidence. This is realized by the appropriate expression of receptors and other signals that correspond to the cell's internal (i.e., generative) model of what type of receptors and other signals it should express. The emerging field of the free energy principle in pattern formation provides an essential quantitative formalism for understanding cellular decision-making in the context of embryogenesis, regeneration, and cancer suppression. In this paper, we derive the mathematics behind Bayesian inference - as understood in this framework - and use simulations to show that the formalism can reproduce experimental, top-down manipulations of complex morphogenesis. First, we illustrate this 'first principle' approach to morphogenesis through simulated alterations of anterior-posterior axial polarity (i.e., the induction of two heads or two tails) as in planarian regeneration. Then, we consider aberrant signaling and functional behavior of a single cell within a cellular ensemble - as a first step in carcinogenesis as false 'beliefs' about what a cell should 'sense' and 'do'. We further show that simple modifications of the inference process can cause - and rescue - mis-patterning of developmental and regenerative events without changing the implicit generative model of a cell as specified, for example, by its DNA. This formalism offers a new road map for understanding developmental change in evolution and for designing new interventions in regenerative medicine settings.
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27
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Durant F, Bischof J, Fields C, Morokuma J, LaPalme J, Hoi A, Levin M. The Role of Early Bioelectric Signals in the Regeneration of Planarian Anterior/Posterior Polarity. Biophys J 2019; 116:948-961. [PMID: 30799071 DOI: 10.1016/j.bpj.2019.01.029] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 01/11/2019] [Accepted: 01/16/2019] [Indexed: 01/14/2023] Open
Abstract
Axial patterning during planarian regeneration relies on a transcriptional circuit that confers distinct positional information on the two ends of an amputated fragment. The earliest known elements of this system begin demarcating differences between anterior and posterior wounds by 6 h postamputation. However, it is still unknown what upstream events break the axial symmetry, allowing a mutual repressor system to establish invariant, distinct biochemical states at the anterior and posterior ends. Here, we show that bioelectric signaling at 3 h is crucial for the formation of proper anterior-posterior polarity in planaria. Briefly manipulating the endogenous bioelectric state by depolarizing the injured tissue during the first 3 h of regeneration alters gene expression by 6 h postamputation and leads to a double-headed phenotype upon regeneration despite confirmed washout of ionophores from tissue. These data reveal a primary functional role for resting membrane potential taking place within the first 3 h after injury and kick-starting the downstream pattern of events that elaborate anatomy over the following 10 days. We propose a simple model of molecular-genetic mechanisms to explain how physiological events taking place immediately after injury regulate the spatial distribution of downstream gene expression and anatomy of regenerating planaria.
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Affiliation(s)
- Fallon Durant
- Allen Discovery Center at Tufts University, Department of Biology, Tufts University, Medford, Massachusetts
| | - Johanna Bischof
- Allen Discovery Center at Tufts University, Department of Biology, Tufts University, Medford, Massachusetts
| | - Chris Fields
- Allen Discovery Center at Tufts University, Department of Biology, Tufts University, Medford, Massachusetts
| | - Junji Morokuma
- Allen Discovery Center at Tufts University, Department of Biology, Tufts University, Medford, Massachusetts
| | - Joshua LaPalme
- Allen Discovery Center at Tufts University, Department of Biology, Tufts University, Medford, Massachusetts
| | - Alison Hoi
- Allen Discovery Center at Tufts University, Department of Biology, Tufts University, Medford, Massachusetts
| | - Michael Levin
- Allen Discovery Center at Tufts University, Department of Biology, Tufts University, Medford, Massachusetts.
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28
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Cervera J, Manzanares JA, Mafe S. Cell-cell bioelectrical interactions and local heterogeneities in genetic networks: a model for the stabilization of single-cell states and multicellular oscillations. Phys Chem Chem Phys 2019; 20:9343-9354. [PMID: 29564429 DOI: 10.1039/c8cp00648b] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Genetic networks operate in the presence of local heterogeneities in single-cell transcription and translation rates. Bioelectrical networks and spatio-temporal maps of cell electric potentials can influence multicellular ensembles. Could cell-cell bioelectrical interactions mediated by intercellular gap junctions contribute to the stabilization of multicellular states against local genetic heterogeneities? We theoretically analyze this question on the basis of two well-established experimental facts: (i) the membrane potential is a reliable read-out of the single-cell electrical state and (ii) when the cells are coupled together, their individual cell potentials can be influenced by ensemble-averaged electrical potentials. We propose a minimal biophysical model for the coupling between genetic and bioelectrical networks that associates the local changes occurring in the transcription and translation rates of an ion channel protein with abnormally low (depolarized) cell potentials. We then analyze the conditions under which the depolarization of a small region (patch) in a multicellular ensemble can be reverted by its bioelectrical coupling with the (normally polarized) neighboring cells. We show also that the coupling between genetic and bioelectric networks of non-excitable cells, modulated by average electric potentials at the multicellular ensemble level, can produce oscillatory phenomena. The simulations show the importance of single-cell potentials characteristic of polarized and depolarized states, the relative sizes of the abnormally polarized patch and the rest of the normally polarized ensemble, and intercellular coupling.
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Affiliation(s)
- Javier Cervera
- Dept. Termodinàmica, Fac. Física, Universitat de València, 46100 Burjassot, Spain.
| | - José A Manzanares
- Dept. Termodinàmica, Fac. Física, Universitat de València, 46100 Burjassot, Spain.
| | - Salvador Mafe
- Dept. Termodinàmica, Fac. Física, Universitat de València, 46100 Burjassot, Spain.
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Lee FJ, Williams KB, Levin M, Wolfe BE. The Bacterial Metabolite Indole Inhibits Regeneration of the Planarian Flatworm Dugesia japonica. iScience 2018; 10:135-148. [PMID: 30521984 PMCID: PMC6280633 DOI: 10.1016/j.isci.2018.11.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 10/31/2018] [Accepted: 11/12/2018] [Indexed: 02/07/2023] Open
Abstract
Planarian flatworms have been used for over a century as models for regeneration. Planarians live in aquatic environments with constant exposure to microbes, but the mechanisms by which bacteria may mediate planarian regeneration are largely unknown. We characterized the microbiome of laboratory populations of the planarian Dugesia japonica and determined how individual bacteria impact D. japonica regeneration. Eight to ten taxa in the phyla Bacteroidetes and Proteobacteria consistently occur across planarian colonies housed in different research laboratories. Individual members of the D. japonica microbiome can delay regeneration including the development of eye spots and blastema formation. The microbial metabolite indole is produced in significant quantities by two bacteria that are consistently found in the D. japonica microbiome and contributes to delays in regeneration. Collectively, these results provide a baseline understanding of the bacteria associated with the planarian D. japonica and demonstrate how metabolite production by host-associated microbes can affect regeneration.
The planarian worm Dugesia japonica is colonized by Bacteroidetes and Proteobacteria Many of these bacteria can be cultured and experimentally manipulated Some bacteria can inhibit regeneration, including eye and blastema formation Indole produced by planarian-associated bacteria contributes to regeneration delays
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Affiliation(s)
- Fredrick J Lee
- Allen Discovery Center at Tufts University, Medford, MA 02155, USA.
| | | | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA 02155, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
| | - Benjamin E Wolfe
- Allen Discovery Center at Tufts University, Medford, MA 02155, USA.
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30
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Pietak A, Levin M. Bioelectrical control of positional information in development and regeneration: A review of conceptual and computational advances. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2018; 137:52-68. [PMID: 29626560 PMCID: PMC10464501 DOI: 10.1016/j.pbiomolbio.2018.03.008] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 03/23/2018] [Accepted: 03/26/2018] [Indexed: 12/16/2022]
Abstract
Positional information describes pre-patterns of morphogenetic substances that alter spatio-temporal gene expression to instruct development of growth and form. A wealth of recent data indicate bioelectrical properties, such as the transmembrane potential (Vmem), are involved as instructive signals in the spatiotemporal regulation of morphogenesis. However, the mechanistic relationships between Vmem and molecular positional information are only beginning to be understood. Recent advances in computational modeling are assisting in the development of comprehensive frameworks for mechanistically understanding how endogenous bioelectricity can guide anatomy in a broad range of systems. Vmem represents an extraordinarily strong electric field (∼1.0 × 106 V/m) active over the thin expanse of the plasma membrane, with the capacity to influence a variety of downstream molecular signaling cascades. Moreover, in multicellular networks, intercellular coupling facilitated by gap junction channels may induce directed, electrodiffusive transport of charged molecules between cells of the network to generate new positional information patterning possibilities and characteristics. Given the demonstrated role of Vmem in morphogenesis, here we review current understanding of how Vmem can integrate with molecular regulatory networks to control single cell state, and the unique properties bioelectricity adds to transport phenomena in gap junction-coupled cell networks to facilitate self-assembly of morphogen gradients and other patterns. Understanding how Vmem integrates with biochemical regulatory networks at the level of a single cell, and mechanisms through which Vmem shapes molecular positional information in multicellular networks, are essential for a deep understanding of body plan control in development, regeneration and disease.
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Affiliation(s)
| | - Michael Levin
- Allen Discovery Center at Tufts, USA; Center for Regenerative and Developmental Biology, Tufts University, Medford, MA, USA
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31
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Siregar P, Julen N, Hufnagl P, Mutter G. A general framework dedicated to computational morphogenesis Part I - Constitutive equations. Biosystems 2018; 173:298-313. [PMID: 30005999 DOI: 10.1016/j.biosystems.2018.07.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2018] [Revised: 05/30/2018] [Accepted: 07/05/2018] [Indexed: 01/14/2023]
Abstract
In order to understand living organisms, considerable experimental efforts and resources have been devoted to correlate genes and their expressions with cell, tissue, organ and whole organisms' phenotypes. This data driven approach to knowledge discovery has led to many breakthrough in our understanding of healthy and diseased states, and is paving the way to improve the diagnosis and treatment of diseases. Complementary to this data-driven approach, computational models of biological systems based on first principles have been developed in order to deepen our understanding of the multi-scale dynamics that drives normal and pathological biological functions. In this paper we describe the biological, physical and mathematical concepts that led to the design of a Computational Morphogenesis (CM) platform baptized Generic Modeling and Simulating Platform (GMSP). Its role is to generate realistic 3D multi-scale biological tissues from virtual stem cells and the intended target applications include in virtuo studies of normal and abnormal tissue (re)generation as well as the development of complex diseases such as carcinogenesis. At all space-scales of interest, biological agents interact with each other via biochemical, bioelectrical, and mechanical fields that operate in concert during embryogenesis, growth and adult life. The spatio-temporal dependencies of these fields can be modeled by physics-based constitutive equations that we propose to examine in relation to the landmark biological events that occur during embryogenesis.
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Affiliation(s)
| | | | - Peter Hufnagl
- Department of Digital Pathology and IT, Institute of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - George Mutter
- Department of Pathology, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
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32
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Sniecinski I, Seghatchian J. Artificial intelligence: A joint narrative on potential use in pediatric stem and immune cell therapies and regenerative medicine. Transfus Apher Sci 2018; 57:422-424. [PMID: 29784537 DOI: 10.1016/j.transci.2018.05.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Artificial Intelligence (AI) reflects the intelligence exhibited by machines and software. It is a highly desirable academic field of many current fields of studies. Leading AI researchers describe the field as "the study and design of intelligent agents". McCarthy invented this term in 1955 and defined it as "the science and engineering of making intelligent machines". The central goals of AI research are reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. In fact the multidisplinary AI field is considered to be rather interdisciplinary covering numerous number of sciences and professions, including computer science, psychology, linguistics, philosophy and neurosciences. The field was founded on the claim that a central intellectual property of humans, intelligence-the sapience of Homo Sapiens "can be so precisely described that a machine can be made to simulate it". This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence. Artificial Intelligence has been the subject of tremendous optimism but has also suffered stunning setbacks. The goal of this narrative is to review the potential use of AI approaches and their integration into pediatric cellular therapies and regenerative medicine. Emphasis is placed on recognition and application of AI techniques in the development of predictive models for personalized treatments with engineered stem cells, immune cells and regenerated tissues in adults and children. These intelligent machines could dissect the whole genome and isolate the immune particularities of individual patient's disease in a matter of minutes and create the treatment that is customized to patient's genetic specificity and immune system capability. AI techniques could be used for optimization of clinical trials of innovative stem cell and gene therapies in pediatric patients by precise planning of treatments, predicting clinical outcomes, simplifying recruitment and retention of patients, learning from input data and applying to new data, thus lowering their complexity and costs. Complementing human intelligence with machine intelligence could have an exponentially high impact on continual progress in many fields of pediatrics. However how long before we could see the real impact still remains the big question. The most pertinent question that remains to be answered therefore, is can AI effectively and accurately predict properties of newer DDR strategies? The goal of this article is to review the use of AI method for cellular therapy and regenerative medicine and emphasize its potential to further the progress in these fields of medicine.
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Affiliation(s)
- Irena Sniecinski
- Department of Transfusion Medicine, Department of Hematology and Hematopoietic Cell Transplantation, City of Hope Cancer Center, Duarte, CA, USA.
| | - Jerard Seghatchian
- International Consultancy in Blood Components Quality/Safety improvement, Audit/Inspection, and DDR Strategies, London, UK.
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Fields C, Levin M. Are Planaria Individuals? What Regenerative Biology is Telling Us About the Nature of Multicellularity. Evol Biol 2018. [DOI: 10.1007/s11692-018-9448-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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Morita N, Inaba K, Saito Y. Post-Embryonic Development and Genital-Complex Formation in Three Species of Polyclad Flatworms. Zoolog Sci 2018; 35:28-38. [PMID: 29417893 DOI: 10.2108/zs170114] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Without the establishment of effective culturing systems, little can be known about the late developmental stages of polyclad flatworms. Here, we report a laboratory culturing system for three polyclad species: Comoplana pusilla, Notocomplana koreana, and Pseudostylochus obscurus, and we describe changes in their morphology from hatching to reproductive maturity. These species hatch out as lobe-less larvae with four eyespots, but the number of eyespots increases in later development. Cross-like and triangularly shaped larvae are observed in N. koreana and P. obscurus, respectively. After settlement, a pale area appears on the body of juveniles and then develops into the copulatory complexes. All three species could be successfully reared on brine shrimp, but only C. pusilla and N. koreana achieved reproductive maturation in such a culturing system. In P. obscurus, switching the food to the gastropod Monodonta labio induced sexual maturation.
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Affiliation(s)
- Nozomi Morita
- Shimoda Marine Research Center, University of Tsukuba, 5-10-1 Shimoda, Shizuoka 415-0025, Japan
| | - Kazuo Inaba
- Shimoda Marine Research Center, University of Tsukuba, 5-10-1 Shimoda, Shizuoka 415-0025, Japan
| | - Yasunori Saito
- Shimoda Marine Research Center, University of Tsukuba, 5-10-1 Shimoda, Shizuoka 415-0025, Japan
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Pezzulo G, Levin M. Top-down models in biology: explanation and control of complex living systems above the molecular level. J R Soc Interface 2017; 13:rsif.2016.0555. [PMID: 27807271 DOI: 10.1098/rsif.2016.0555] [Citation(s) in RCA: 109] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Accepted: 10/11/2016] [Indexed: 12/23/2022] Open
Abstract
It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Michael Levin
- Biology Department, Allen Discovery Center at Tufts, Tufts University, Medford, MA 02155, USA
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36
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Pietak A, Levin M. Bioelectric gene and reaction networks: computational modelling of genetic, biochemical and bioelectrical dynamics in pattern regulation. J R Soc Interface 2017; 14:20170425. [PMID: 28954851 PMCID: PMC5636277 DOI: 10.1098/rsif.2017.0425] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 08/31/2017] [Indexed: 12/17/2022] Open
Abstract
Gene regulatory networks (GRNs) describe interactions between gene products and transcription factors that control gene expression. In combination with reaction-diffusion models, GRNs have enhanced comprehension of biological pattern formation. However, although it is well known that biological systems exploit an interplay of genetic and physical mechanisms, instructive factors such as transmembrane potential (Vmem) have not been integrated into full GRN models. Here we extend regulatory networks to include bioelectric signalling, developing a novel synthesis: the bioelectricity-integrated gene and reaction (BIGR) network. Using in silico simulations, we highlight the capacity for Vmem to alter steady-state concentrations of key signalling molecules inside and out of cells. We characterize fundamental feedbacks where Vmem both controls, and is in turn regulated by, biochemical signals and thereby demonstrate Vmem homeostatic control, Vmem memory and Vmem controlled state switching. BIGR networks demonstrating hysteresis are identified as a mechanisms through which more complex patterns of stable Vmem spots and stripes, along with correlated concentration patterns, can spontaneously emerge. As further proof of principle, we present and analyse a BIGR network model that mechanistically explains key aspects of the remarkable regenerative powers of creatures such as planarian flatworms. The functional properties of BIGR networks generate the first testable, quantitative hypotheses for biophysical mechanisms underlying the stability and adaptive regulation of anatomical bioelectric pattern.
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Affiliation(s)
- Alexis Pietak
- Allen Discovery Center, Tufts University, Medford, MA, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, USA
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37
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Durant F, Morokuma J, Fields C, Williams K, Adams DS, Levin M. Long-Term, Stochastic Editing of Regenerative Anatomy via Targeting Endogenous Bioelectric Gradients. Biophys J 2017; 112:2231-2243. [PMID: 28538159 PMCID: PMC5443973 DOI: 10.1016/j.bpj.2017.04.011] [Citation(s) in RCA: 93] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2017] [Revised: 03/30/2017] [Accepted: 04/14/2017] [Indexed: 12/22/2022] Open
Abstract
We show that regenerating planarians' normal anterior-posterior pattern can be permanently rewritten by a brief perturbation of endogenous bioelectrical networks. Temporary modulation of regenerative bioelectric dynamics in amputated trunk fragments of planaria stochastically results in a constant ratio of regenerates with two heads to regenerates with normal morphology. Remarkably, this is shown to be due not to partial penetrance of treatment, but a profound yet hidden alteration to the animals' patterning circuitry. Subsequent amputations of the morphologically normal regenerates in water result in the same ratio of double-headed to normal morphology, revealing a cryptic phenotype that is not apparent unless the animals are cut. These animals do not differ from wild-type worms in histology, expression of key polarity genes, or neoblast distribution. Instead, the altered regenerative bodyplan is stored in seemingly normal planaria via global patterns of cellular resting potential. This gradient is functionally instructive, and represents a multistable, epigenetic anatomical switch: experimental reversals of bioelectric state reset subsequent regenerative morphology back to wild-type. Hence, bioelectric properties can stably override genome-default target morphology, and provide a tractable control point for investigating cryptic phenotypes and the stochasticity of large-scale epigenetic controls.
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Affiliation(s)
- Fallon Durant
- Allen Discovery Center at Tufts University, and Department of Biology, Tufts University, Medford, Massachusetts
| | - Junji Morokuma
- Allen Discovery Center at Tufts University, and Department of Biology, Tufts University, Medford, Massachusetts
| | | | - Katherine Williams
- Allen Discovery Center at Tufts University, and Department of Biology, Tufts University, Medford, Massachusetts
| | - Dany Spencer Adams
- Allen Discovery Center at Tufts University, and Department of Biology, Tufts University, Medford, Massachusetts
| | - Michael Levin
- Allen Discovery Center at Tufts University, and Department of Biology, Tufts University, Medford, Massachusetts.
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38
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García-Quismondo M, Levin M, Lobo D. Modeling regenerative processes with membrane computing. Inf Sci (N Y) 2017. [DOI: 10.1016/j.ins.2016.11.017] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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39
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Transcriptomic, proteomic, and metabolomic landscape of positional memory in the caudal fin of zebrafish. Proc Natl Acad Sci U S A 2017; 114:E717-E726. [PMID: 28096348 DOI: 10.1073/pnas.1620755114] [Citation(s) in RCA: 69] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Regeneration requires cells to regulate proliferation and patterning according to their spatial position. Positional memory is a property that enables regenerating cells to recall spatial information from the uninjured tissue. Positional memory is hypothesized to rely on gradients of molecules, few of which have been identified. Here, we quantified the global abundance of transcripts, proteins, and metabolites along the proximodistal axis of caudal fins of uninjured and regenerating adult zebrafish. Using this approach, we uncovered complex overlapping expression patterns for hundreds of molecules involved in diverse cellular functions, including development, bioelectric signaling, and amino acid and lipid metabolism. Moreover, 32 genes differentially expressed at the RNA level had concomitant differential expression of the encoded proteins. Thus, the identification of proximodistal differences in levels of RNAs, proteins, and metabolites will facilitate future functional studies of positional memory during appendage regeneration.
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40
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Rost F, Rodrigo Albors A, Mazurov V, Brusch L, Deutsch A, Tanaka EM, Chara O. Accelerated cell divisions drive the outgrowth of the regenerating spinal cord in axolotls. eLife 2016; 5:20357. [PMID: 27885987 PMCID: PMC5182066 DOI: 10.7554/elife.20357] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 11/14/2016] [Indexed: 01/25/2023] Open
Abstract
Axolotls are unique in their ability to regenerate the spinal cord. However, the mechanisms that underlie this phenomenon remain poorly understood. Previously, we showed that regenerating stem cells in the axolotl spinal cord revert to a molecular state resembling embryonic neuroepithelial cells and functionally acquire rapid proliferative divisions (Rodrigo Albors et al., 2015). Here, we refine the analysis of cell proliferation in space and time and identify a high-proliferation zone in the regenerating spinal cord that shifts posteriorly over time. By tracking sparsely-labeled cells, we also quantify cell influx into the regenerate. Taking a mathematical modeling approach, we integrate these quantitative datasets of cell proliferation, neural stem cell activation and cell influx, to predict regenerative tissue outgrowth. Our model shows that while cell influx and neural stem cell activation play a minor role, the acceleration of the cell cycle is the major driver of regenerative spinal cord outgrowth in axolotls. DOI:http://dx.doi.org/10.7554/eLife.20357.001
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Affiliation(s)
- Fabian Rost
- Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany
| | - Aida Rodrigo Albors
- Deutsche Forschungsgemeinschaft - Center for Regenerative Therapies Dresden, Dresden, Germany.,Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Vladimir Mazurov
- Deutsche Forschungsgemeinschaft - Center for Regenerative Therapies Dresden, Dresden, Germany.,Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Lutz Brusch
- Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany.,Center for Advancing Electronics Dresden, Dresden, Germany
| | - Andreas Deutsch
- Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany.,Center for Advancing Electronics Dresden, Dresden, Germany
| | - Elly M Tanaka
- Deutsche Forschungsgemeinschaft - Center for Regenerative Therapies Dresden, Dresden, Germany.,Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Osvaldo Chara
- Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany.,Systems Biology Group, Institute of Physics of Liquids and Biological Systems, National Scientific and Technical Research Council, University of La Plata, La Plata, Argentina
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41
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Chan JD, Zhang D, Liu X, Zarowiecki M, Berriman M, Marchant JS. Utilizing the planarian voltage-gated ion channel transcriptome to resolve a role for a Ca 2+ channel in neuromuscular function and regeneration. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH 2016; 1864:1036-1045. [PMID: 27771293 DOI: 10.1016/j.bbamcr.2016.10.010] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 10/13/2016] [Accepted: 10/17/2016] [Indexed: 12/22/2022]
Abstract
The robust regenerative capacity of planarian flatworms depends on the orchestration of signaling events from early wounding responses through the stem cell enacted differentiative outcomes that restore appropriate tissue types. Acute signaling events in excitable cells play an important role in determining regenerative polarity, rationalized by the discovery that sub-epidermal muscle cells express critical patterning genes known to control regenerative outcomes. These data imply a dual conductive (neuromuscular signaling) and instructive (anterior-posterior patterning) role for Ca2+ signaling in planarian regeneration. Here, to facilitate study of acute signaling events in the excitable cell niche, we provide a de novo transcriptome assembly from the planarian Dugesia japonica allowing characterization of the diverse ionotropic portfolio of this model organism. We demonstrate the utility of this resource by proceeding to characterize the individual role of each of the planarian voltage-operated Ca2+ channels during regeneration, and demonstrate that knockdown of a specific voltage operated Ca2+ channel (Cav1B) that impairs muscle function uniquely creates an environment permissive for anteriorization. Provision of the full transcriptomic dataset should facilitate further investigations of molecules within the planarian voltage-gated channel portfolio to explore the role of excitable cell physiology on regenerative outcomes. This article is part of a Special Issue entitled: ECS Meeting edited by Claus Heizmann, Joachim Krebs and Jacques Haiech.
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Affiliation(s)
- John D Chan
- Department of Pharmacology, University of Minnesota Medical School, MN 55455, United States
| | - Dan Zhang
- Department of Pharmacology, University of Minnesota Medical School, MN 55455, United States
| | - Xiaolong Liu
- Department of Pharmacology, University of Minnesota Medical School, MN 55455, United States
| | - Magdalena Zarowiecki
- Parasite Genomics Group, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Matthew Berriman
- Parasite Genomics Group, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Jonathan S Marchant
- Department of Pharmacology, University of Minnesota Medical School, MN 55455, United States; The Stem Cell Institute, University of Minnesota Medical School, MN 55455, United States.
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42
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The interplay between genetic and bioelectrical signaling permits a spatial regionalisation of membrane potentials in model multicellular ensembles. Sci Rep 2016; 6:35201. [PMID: 27731412 PMCID: PMC5059667 DOI: 10.1038/srep35201] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Accepted: 09/26/2016] [Indexed: 12/12/2022] Open
Abstract
The single cell-centred approach emphasises ion channels as specific proteins that determine individual properties, disregarding their contribution to multicellular outcomes. We simulate the interplay between genetic and bioelectrical signals in non-excitable cells from the local single-cell level to the long range multicellular ensemble. The single-cell genetic regulation is based on mean-field kinetic equations involving the mRNA and protein concentrations. The transcription rate factor is assumed to depend on the absolute value of the cell potential, which is dictated by the voltage-gated cell ion channels and the intercellular gap junctions. The interplay between genetic and electrical signals may allow translating single-cell states into multicellular states which provide spatio-temporal information. The model results have clear implications for biological processes: (i) bioelectric signals can override slightly different genetic pre-patterns; (ii) ensembles of cells initially at the same potential can undergo an electrical regionalisation because of persistent genetic differences between adjacent spatial regions; and (iii) shifts in the normal cell electrical balance could trigger significant changes in the genetic regulation.
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43
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Neuhof M, Levin M, Rechavi O. Vertically- and horizontally-transmitted memories - the fading boundaries between regeneration and inheritance in planaria. Biol Open 2016; 5:1177-88. [PMID: 27565761 PMCID: PMC5051648 DOI: 10.1242/bio.020149] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
The Weismann barrier postulates that genetic information passes only from the germline to the soma and not in reverse, thus providing an obstacle to the inheritance of acquired traits. Certain organisms such as planaria – flatworms that can reproduce through asymmetric fission – avoid the limitations of this barrier, thus blurring the distinction between the processes of inheritance and development. In this paper, we re-evaluate canonical ideas about the interaction between developmental, genetic and evolutionary processes through the lens of planaria. Biased distribution of epigenetic effects in asymmetrically produced parts of a regenerating organism could increase variation and therefore affect the species' evolution. The maintenance and fixing of somatic experiences, encoded via stable biochemical or physiological states, may contribute to evolutionary processes in the absence of classically defined generations. We discuss different mechanisms that could induce asymmetry between the two organisms that eventually develop from the regenerating parts, including one particularly fascinating source – the potential capacity of the brain to produce long-lasting epigenetic changes. Summary: In this hypothesis paper we re-evaluate canonical ideas about the interaction between developmental, genetic and evolutionary processes through the lens of planaria, an invertebrate model organism which challenges fundamental assumptions regarding reproduction.
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Affiliation(s)
- Moran Neuhof
- Department of Neurobiology, Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Michael Levin
- Allen Discovery Center, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155, USA
| | - Oded Rechavi
- Department of Neurobiology, Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel Allen Discovery Center, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155, USA Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
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