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Zha L, Matsu-ura T, Sluka JP, Murakawa T, Tsuta K. Morphological basis of the lung adenocarcinoma subtypes. iScience 2024; 27:109742. [PMID: 38706836 PMCID: PMC11066476 DOI: 10.1016/j.isci.2024.109742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 02/20/2024] [Accepted: 04/10/2024] [Indexed: 05/07/2024] Open
Abstract
Lung adenocarcinoma (LUAD), which accounts for a large proportion of lung cancers, is divided into five major subtypes based on histologic characteristics. The clinical characteristics, prognosis, and responses to treatments vary among subtypes. Here, we demonstrate that the variations of cell-cell contact energy result in the LUAD subtype-specific morphogenesis. We reproduced the morphologies of the papillary LUAD subtypes with the cellular Potts Model (CPM). Simulations and experimental validations revealed modifications of cell-cell contact energy changed the morphology from a papillary-like structure to micropapillary or solid subtype-like structures. Remarkably, differential gene expression analysis revealed subtype-specific expressions of genes relating to cell adhesion. Knockdown experiments of the micropapillary upregulated ITGA11 gene resulted in the morphological changes of the spheroids produced from an LUAD cell line PC9. This work shows the consequences of gene mutations and gene expressions on patient prognosis through differences in tissue composing physical forces among LUAD subtypes.
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Affiliation(s)
- Linjun Zha
- Department of Pathology, Kansai Medical University, Hirakata, Osaka 573-0033, Japan
| | - Toru Matsu-ura
- Department of Pathology, Kansai Medical University, Hirakata, Osaka 573-0033, Japan
| | - James P. Sluka
- Biocomplexity Institute, Indiana University, Bloomington, IN 47405-7105, USA
| | - Tomohiro Murakawa
- Department of Thoracic Surgery, Kansai Medical University, Hirakata, Osaka 573-0033, Japan
| | - Koji Tsuta
- Department of Pathology, Kansai Medical University, Hirakata, Osaka 573-0033, Japan
- Biocomplexity Institute, Indiana University, Bloomington, IN 47405-7105, USA
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2
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Koyama H, Okumura H, Ito AM, Nakamura K, Otani T, Kato K, Fujimori T. Effective mechanical potential of cell-cell interaction explains three-dimensional morphologies during early embryogenesis. PLoS Comput Biol 2023; 19:e1011306. [PMID: 37549166 PMCID: PMC10434874 DOI: 10.1371/journal.pcbi.1011306] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 08/17/2023] [Accepted: 06/26/2023] [Indexed: 08/09/2023] Open
Abstract
Mechanical forces are critical for the emergence of diverse three-dimensional morphologies of multicellular systems. However, it remains unclear what kind of mechanical parameters at cellular level substantially contribute to tissue morphologies. This is largely due to technical limitations of live measurements of cellular forces. Here we developed a framework for inferring and modeling mechanical forces of cell-cell interactions. First, by analogy to coarse-grained models in molecular and colloidal sciences, we approximated cells as particles, where mean forces (i.e. effective forces) of pairwise cell-cell interactions are considered. Then, the forces were statistically inferred by fitting the mathematical model to cell tracking data. This method was validated by using synthetic cell tracking data resembling various in vivo situations. Application of our method to the cells in the early embryos of mice and the nematode Caenorhabditis elegans revealed that cell-cell interaction forces can be written as a pairwise potential energy in a manner dependent on cell-cell distances. Importantly, the profiles of the pairwise potentials were quantitatively different among species and embryonic stages, and the quantitative differences correctly described the differences of their morphological features such as spherical vs. distorted cell aggregates, and tightly vs. non-tightly assembled aggregates. We conclude that the effective pairwise potential of cell-cell interactions is a live measurable parameter whose quantitative differences can be a parameter describing three-dimensional tissue morphologies.
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Affiliation(s)
- Hiroshi Koyama
- Division of Embryology, National Institute for Basic Biology, Myodaiji, Okazaki, Aichi, Japan
- SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
| | - Hisashi Okumura
- SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
- Biomolecular Dynamics Simulation Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Myodaiji, Okazaki, Aichi, Japan
- Institute for Molecular Science, National Institutes of Natural Sciences, Myodaiji, Okazaki, Aichi, Japan
| | - Atsushi M. Ito
- SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
- National Institute for Fusion Science, National Institutes of Natural Sciences, Toki, Gifu, Japan
| | - Kazuyuki Nakamura
- School of Interdisciplinary Mathematical Sciences, Meiji University, Nakano-ku, Tokyo, Japan
- JST, PRESTO, Kawaguchi, Saitama, Japan
| | - Tetsuhisa Otani
- SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
- Division of Cell Structure, National Institute for Physiological Sciences, Myodaiji, Okazaki, Aichi, Japan
| | - Kagayaki Kato
- SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
- Bioimage Informatics Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Myodaiji, Okazaki, Aichi, Japan
- Laboratory of Biological Diversity, National Institute for Basic Biology, Myodaiji, Okazaki, Aichi, Japan
| | - Toshihiko Fujimori
- Division of Embryology, National Institute for Basic Biology, Myodaiji, Okazaki, Aichi, Japan
- SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan
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3
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Ateshian GA, Spack KA, Hone JC, Azeloglu EU, Gusella GL. Computational study of biomechanical drivers of renal cystogenesis. Biomech Model Mechanobiol 2023; 22:1113-1127. [PMID: 37024601 PMCID: PMC10524738 DOI: 10.1007/s10237-023-01704-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 02/12/2023] [Indexed: 04/08/2023]
Abstract
Renal cystogenesis is the pathological hallmark of autosomal dominant polycystic kidney disease, caused by PKD1 and PKD2 mutations. The formation of renal cysts is a common manifestation in ciliopathies, a group of syndromic disorders caused by mutation of proteins involved in the assembly and function of the primary cilium. Cystogenesis is caused by the derailment of the renal tubular architecture and tissue deformation that eventually leads to the impairment of kidney function. However, the biomechanical imbalance of cytoskeletal forces that are altered in cells with Pkd1 mutations has never been investigated, and its nature and extent remain unknown. In this computational study, we explored the feasibility of various biomechanical drivers of renal cystogenesis by examining several hypothetical mechanisms that may promote morphogenetic markers of cystogenesis. Our objective was to provide physics-based guidance for our formulation of hypotheses and our design of experimental studies investigating the role of biomechanical disequilibrium in cystogenesis. We employed the finite element method to explore the role of (1) wild-type versus mutant cell elastic modulus; (2) contractile stress magnitude in mutant cells; (3) localization and orientation of contractile stress in mutant cells; and (4) sequence of cell contraction and cell proliferation. Our objective was to identify the factors that produce the characteristic tubular cystic growth. Results showed that cystogenesis occurred only when mutant cells contracted along the apical-basal axis, followed or accompanied by cell proliferation, as long as mutant cells had comparable or lower elastic modulus than wild-type cells, with their contractile stresses being significantly greater than their modulus. Results of these simulations allow us to focus future in vitro and in vivo experimental studies on these factors, helping us formulate physics-based hypotheses for renal tubule cystogenesis.
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Affiliation(s)
- Gerard A Ateshian
- Department of Mechanical Engineering, Columbia University, New York, NY, USA.
- Department of Biomedical Engineering, Columbia University, New York, NY, USA.
| | - Katherine A Spack
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - James C Hone
- Department of Mechanical Engineering, Columbia University, New York, NY, USA
| | - Evren U Azeloglu
- Department of Medicine, Division of Nephrology, Mount Sinai School of Medicine, New York, NY, USA
- Department of Pharmacological Sciences, Mount Sinai School of Medicine, New York, NY, USA
| | - G Luca Gusella
- Department of Medicine, Division of Nephrology, Mount Sinai School of Medicine, New York, NY, USA
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4
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Novel Ground-Up 3D Multicellular Simulators for Synthetic Biology CAD Integrating Stochastic Gillespie Simulations Benchmarked with Topologically Variable SBML Models. Genes (Basel) 2023; 14:genes14010154. [PMID: 36672895 PMCID: PMC9859520 DOI: 10.3390/genes14010154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 12/29/2022] [Accepted: 12/30/2022] [Indexed: 01/09/2023] Open
Abstract
The elevation of Synthetic Biology from single cells to multicellular simulations would be a significant scale-up. The spatiotemporal behavior of cellular populations has the potential to be prototyped in silico for computer assisted design through ergonomic interfaces. Such a platform would have great practical potential across medicine, industry, research, education and accessible archiving in bioinformatics. Existing Synthetic Biology CAD systems are considered limited regarding population level behavior, and this work explored the in silico challenges posed from biological and computational perspectives. Retaining the connection to Synthetic Biology CAD, an extension of the Infobiotics Workbench Suite was considered, with potential for the integration of genetic regulatory models and/or chemical reaction networks through Next Generation Stochastic Simulator (NGSS) Gillespie algorithms. These were executed using SBML models generated by in-house SBML-Constructor over numerous topologies and benchmarked in association with multicellular simulation layers. Regarding multicellularity, two ground-up multicellular solutions were developed, including the use of Unreal Engine 4 contrasted with CPU multithreading and Blender visualization, resulting in a comparison of real-time versus batch-processed simulations. In conclusion, high-performance computing and client-server architectures could be considered for future works, along with the inclusion of numerous biologically and physically informed features, whilst still pursuing ergonomic solutions.
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5
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Fuji K, Tanida S, Sano M, Nonomura M, Riveline D, Honda H, Hiraiwa T. Computational approaches for simulating luminogenesis. Semin Cell Dev Biol 2022; 131:173-185. [PMID: 35773151 DOI: 10.1016/j.semcdb.2022.05.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 12/14/2022]
Abstract
Lumens, liquid-filled cavities surrounded by polarized tissue cells, are elementary units involved in the morphogenesis of organs. Theoretical modeling and computations, which can integrate various factors involved in biophysics of morphogenesis of cell assembly and lumens, may play significant roles to elucidate the mechanisms in formation of such complex tissue with lumens. However, up to present, it has not been documented well what computational approaches or frameworks can be applied for this purpose and how we can choose the appropriate approach for each problem. In this review, we report some typical lumen morphologies and basic mechanisms for the development of lumens, focusing on three keywords - mechanics, hydraulics and geometry - while outlining pros and cons of the current main computational strategies. We also describe brief guidance of readouts, i.e., what we should measure in experiments to make the comparison with the model's assumptions and predictions.
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Affiliation(s)
- Kana Fuji
- Universal Biology Institute, Graduate School of Science, the University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Sakurako Tanida
- Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, Japan
| | - Masaki Sano
- Institute of Natural Sciences, School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Makiko Nonomura
- Department of Mathematical Information Engineering, College of Industrial Technology, Nihon University, 1-2-1 Izumicho, Narashino-shi, Chiba 275-8575, Japan
| | - Daniel Riveline
- Laboratory of Cell Physics IGBMC, CNRS, INSERM and Université de Strasbourg, Strasbourg, France
| | - Hisao Honda
- Division of Cell Physiology, Department of Physiology and Cell Biology, Graduate School of Medicine Kobe University, Kobe, Hyogo, Japan
| | - Tetsuya Hiraiwa
- Mechanobiology Institute, Singapore, National University of Singapore, 117411, Singapore.
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6
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Lam C, Saluja S, Courcoubetis G, Yu D, Chung C, Courte J, Morsut L. Parameterized Computational Framework for the Description and Design of Genetic Circuits of Morphogenesis Based on Contact-Dependent Signaling and Changes in Cell-Cell Adhesion. ACS Synth Biol 2022; 11:1417-1439. [PMID: 35363477 PMCID: PMC10389258 DOI: 10.1021/acssynbio.0c00369] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Synthetic development is a nascent field of research that uses the tools of synthetic biology to design genetic programs directing cellular patterning and morphogenesis in higher eukaryotic cells, such as mammalian cells. One specific example of such synthetic genetic programs was based on cell-cell contact-dependent signaling using synthetic Notch pathways and was shown to drive the formation of multilayered spheroids by modulating cell-cell adhesion via differential expression of cadherin family proteins in a mouse fibroblast cell line (L929). The design method for these genetic programs relied on trial and error, which limited the number of possible circuits and parameter ranges that could be explored. Here, we build a parameterized computational framework that, given a cell-cell communication network driving changes in cell adhesion and initial conditions as inputs, predicts developmental trajectories. We first built a general computational framework where contact-dependent cell-cell signaling networks and changes in cell-cell adhesion could be designed in a modular fashion. We then used a set of available in vitro results (that we call the "training set" in analogy to similar pipelines in the machine learning field) to parameterize the computational model with values for adhesion and signaling. We then show that this parameterized model can qualitatively predict experimental results from a "testing set" of available in vitro data that varied the genetic network in terms of adhesion combinations, initial number of cells, and even changes to the network architecture. Finally, this parameterized model is used to recommend novel network implementation for the formation of a four-layered structure that has not been reported previously. The framework that we develop here could function as a testing ground to identify the reachable space of morphologies that can be obtained by controlling contact-dependent cell-cell communications and adhesion with these molecular tools and in this cellular system. Additionally, we discuss how the model could be expanded to include other forms of communication or effectors for the computational design of the next generation of synthetic developmental trajectories.
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Affiliation(s)
- Calvin Lam
- Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90033-9080, United States
| | - Sajeev Saluja
- Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90033-9080, United States
| | - George Courcoubetis
- Department of Physics and Astronomy, University of Southern California, Los Angeles, California 90089-0484, United States
| | - Dottie Yu
- Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90033-9080, United States
| | - Christian Chung
- Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90033-9080, United States
| | - Josquin Courte
- Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90033-9080, United States
| | - Leonardo Morsut
- Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90033-9080, United States
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California 90089-1111, United States
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7
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Van Liedekerke P, Gannoun L, Loriot A, Johann T, Lemaigre FP, Drasdo D. Quantitative modeling identifies critical cell mechanics driving bile duct lumen formation. PLoS Comput Biol 2022; 18:e1009653. [PMID: 35180209 PMCID: PMC8856558 DOI: 10.1371/journal.pcbi.1009653] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 11/16/2021] [Indexed: 02/07/2023] Open
Abstract
Biliary ducts collect bile from liver lobules, the smallest functional and anatomical units of liver, and carry it to the gallbladder. Disruptions in this process caused by defective embryonic development, or through ductal reaction in liver disease have a major impact on life quality and survival of patients. A deep understanding of the processes underlying bile duct lumen formation is crucial to identify intervention points to avoid or treat the appearance of defective bile ducts. Several hypotheses have been proposed to characterize the biophysical mechanisms driving initial bile duct lumen formation during embryogenesis. Here, guided by the quantification of morphological features and expression of genes in bile ducts from embryonic mouse liver, we sharpened these hypotheses and collected data to develop a high resolution individual cell-based computational model that enables to test alternative hypotheses in silico. This model permits realistic simulations of tissue and cell mechanics at sub-cellular scale. Our simulations suggest that successful bile duct lumen formation requires a simultaneous contribution of directed cell division of cholangiocytes, local osmotic effects generated by salt excretion in the lumen, and temporally-controlled differentiation of hepatoblasts to cholangiocytes, with apical constriction of cholangiocytes only moderately affecting luminal size. The initial step in bile duct development is the formation of a biliary lumen, a process which involves several cellular mechanisms, such as cell division and polarization, and secretion of fluid. However, how these mechanisms are orchestrated in time and space is difficult to understand. Here, we built a computational model of biliary lumen formation which represents every cell and its function in detail. With the model we can simulate the effect of biophysical aspects that affect duct formation. We have tested the individual and combined effects of directed cell division, apical constriction, and osmotic effects on lumen expansion by varying the parameters that control their relative strength. Our simulations suggest that successful bile duct lumen formation requires the simultaneous contribution of directed cell division of cholangiocytes, local osmotic effects generated by salt excretion in the lumen, and temporally-controlled differentiation of hepatoblasts to cholangiocytes, with apical constriction of cholangiocytes only moderately affecting luminal size.
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Affiliation(s)
- Paul Van Liedekerke
- Inria Saclay Île-De-France, Palaiseau, France
- de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
- Inria de Paris & Sorbonne Université LJLL, Paris, France
- * E-mail: (PVL); (DD)
| | - Lila Gannoun
- de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - Axelle Loriot
- de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - Tim Johann
- Leibniz Research Centre for Working Environment and Human Factors at the Technical University Dortmund, Dortmund, Germany
| | | | - Dirk Drasdo
- Inria Saclay Île-De-France, Palaiseau, France
- Leibniz Research Centre for Working Environment and Human Factors at the Technical University Dortmund, Dortmund, Germany
- Inria de Paris & Sorbonne Université LJLL, Paris, France
- * E-mail: (PVL); (DD)
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8
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Yang Y, Filipovic D, Bhattacharya S. A Negative Feedback Loop and Transcription Factor Cooperation Regulate Zonal Gene Induction by 2, 3, 7, 8-Tetrachlorodibenzo-p-Dioxin in the Mouse Liver. Hepatol Commun 2021; 6:750-764. [PMID: 34726355 PMCID: PMC8948569 DOI: 10.1002/hep4.1848] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 10/02/2021] [Accepted: 10/10/2021] [Indexed: 01/04/2023] Open
Abstract
The cytochrome P450 (Cyp) proteins Cyp1A1 and Cyp1A2 are strongly induced in the mouse liver by the potent environmental toxicant 2, 3, 7, 8‐tetrachlorodibenzo‐p‐dioxin (TCDD), acting through the aryl hydrocarbon receptor (AHR). The induction of Cyp1A1 is localized within the centrilobular regions of the mouse liver at low doses of TCDD, progressing to pan‐lobular induction at higher doses. Even without chemical perturbation, metabolic functions and associated genes are basally zonated in the liver lobule along the central‐to‐portal axis. To investigate the mechanistic basis of spatially restricted gene induction by TCDD, we have developed a multiscale computational model of the mouse liver lobule with single‐cell resolution. The spatial location of individual hepatocytes in the model was calibrated from previously published high‐resolution images. A systems biology model of the network of biochemical signaling pathways underlying Cyp1A1 and Cyp1A2 induction was then incorporated into each hepatocyte in the model. Model simulations showed that a negative feedback loop formed by binding of the induced Cyp1A2 protein to TCDD, together with cooperative gene induction by the β‐catenin/AHR/TCDD transcription factor complex and β‐catenin, help produce the spatially localized induction pattern of Cyp1A1. Although endogenous WNT regulates the metabolic zonation of many genes, it was not a driver of zonal Cyp1A1 induction in our model. Conclusion: In this work, we used data‐driven computational modeling to identify the mechanistic basis of zonally restricted gene expression induced by the potent and persistent environmental pollutant TCDD. The multiscale model and derived results clarify the mechanisms of dose‐dependent hepatic gene induction responses to TCDD. Additionally, this work contributes to our broader understanding of spatial gene regulation along the liver lobule.
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Affiliation(s)
- Yongliang Yang
- Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA.,Institute for Quantitative Health Science & Engineering, Michigan State University, East Lansing, MI, USA
| | - David Filipovic
- Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA.,Institute for Quantitative Health Science & Engineering, Michigan State University, East Lansing, MI, USA.,Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Sudin Bhattacharya
- Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA.,Institute for Quantitative Health Science & Engineering, Michigan State University, East Lansing, MI, USA.,Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI, USA.,Institute for Integrative Toxicology, Michigan State University, East Lansing, MI, USA
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9
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Sego TJ, Aponte-Serrano JO, Gianlupi JF, Glazier JA. Generation of multicellular spatiotemporal models of population dynamics from ordinary differential equations, with applications in viral infection. BMC Biol 2021; 19:196. [PMID: 34496857 PMCID: PMC8424622 DOI: 10.1186/s12915-021-01115-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 08/02/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND The biophysics of an organism span multiple scales from subcellular to organismal and include processes characterized by spatial properties, such as the diffusion of molecules, cell migration, and flow of intravenous fluids. Mathematical biology seeks to explain biophysical processes in mathematical terms at, and across, all relevant spatial and temporal scales, through the generation of representative models. While non-spatial, ordinary differential equation (ODE) models are often used and readily calibrated to experimental data, they do not explicitly represent the spatial and stochastic features of a biological system, limiting their insights and applications. However, spatial models describing biological systems with spatial information are mathematically complex and computationally expensive, which limits the ability to calibrate and deploy them and highlights the need for simpler methods able to model the spatial features of biological systems. RESULTS In this work, we develop a formal method for deriving cell-based, spatial, multicellular models from ODE models of population dynamics in biological systems, and vice versa. We provide examples of generating spatiotemporal, multicellular models from ODE models of viral infection and immune response. In these models, the determinants of agreement of spatial and non-spatial models are the degree of spatial heterogeneity in viral production and rates of extracellular viral diffusion and decay. We show how ODE model parameters can implicitly represent spatial parameters, and cell-based spatial models can generate uncertain predictions through sensitivity to stochastic cellular events, which is not a feature of ODE models. Using our method, we can test ODE models in a multicellular, spatial context and translate information to and from non-spatial and spatial models, which help to employ spatiotemporal multicellular models using calibrated ODE model parameters. We additionally investigate objects and processes implicitly represented by ODE model terms and parameters and improve the reproducibility of spatial, stochastic models. CONCLUSION We developed and demonstrate a method for generating spatiotemporal, multicellular models from non-spatial population dynamics models of multicellular systems. We envision employing our method to generate new ODE model terms from spatiotemporal and multicellular models, recast popular ODE models on a cellular basis, and generate better models for critical applications where spatial and stochastic features affect outcomes.
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Affiliation(s)
- T J Sego
- Department of Intelligent Systems Engineering and Biocomplexity Institute, Indiana University, Bloomington, IN, USA.
| | - Josua O Aponte-Serrano
- Department of Intelligent Systems Engineering and Biocomplexity Institute, Indiana University, Bloomington, IN, USA
| | - Juliano F Gianlupi
- Department of Intelligent Systems Engineering and Biocomplexity Institute, Indiana University, Bloomington, IN, USA
| | - James A Glazier
- Department of Intelligent Systems Engineering and Biocomplexity Institute, Indiana University, Bloomington, IN, USA
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10
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A mechanical model of early somite segmentation. iScience 2021; 24:102317. [PMID: 33889816 PMCID: PMC8050378 DOI: 10.1016/j.isci.2021.102317] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 01/15/2021] [Accepted: 03/12/2021] [Indexed: 11/21/2022] Open
Abstract
Somitogenesis is often described using the clock-and-wavefront (CW) model, which does not explain how molecular signaling rearranges the pre-somitic mesoderm (PSM) cells into somites. Our scanning electron microscopy analysis of chicken embryos reveals a caudally-progressing epithelialization front in the dorsal PSM that precedes somite formation. Signs of apical constriction and tissue segmentation appear in this layer 3-4 somite lengths caudal to the last-formed somite. We propose a mechanical instability model in which a steady increase of apical contractility leads to periodic failure of adhesion junctions within the dorsal PSM and positions the future inter-somite boundaries. This model produces spatially periodic segments whose size depends on the speed of the activation front of contraction (F), and the buildup rate of contractility (Λ). The Λ/F ratio determines whether this mechanism produces spatially and temporally regular or irregular segments, and whether segment size increases with the front speed. Dorsal pre-somitic mesoderm of chicken embryos epithelializes before somite formation Dorsal epithelium shows signs of apical constriction and early segmentation A mechanical instability model can reproduce sequential segmentation A single ratio describes spatial and temporal patterns of segmentation
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11
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Liu R, Higley KA, Swat MH, Chaplain MAJ, Powathil GG, Glazier JA. Development of a coupled simulation toolkit for computational radiation biology based on Geant4 and CompuCell3D. Phys Med Biol 2021; 66:045026. [PMID: 33339019 DOI: 10.1088/1361-6560/abd4f9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Understanding and designing clinical radiation therapy is one of the most important areas of state-of-the-art oncological treatment regimens. Decades of research have gone into developing sophisticated treatment devices and optimization protocols for schedules and dosages. In this paper, we presented a comprehensive computational platform that facilitates building of the sophisticated multi-cell-based model of how radiation affects the biology of living tissue. We designed and implemented a coupled simulation method, including a radiation transport model, and a cell biology model, to simulate the tumor response after irradiation. The radiation transport simulation was implemented through Geant4 which is an open-source Monte Carlo simulation platform that provides many flexibilities for users, as well as low energy DNA damage simulation physics, Geant4-DNA. The cell biology simulation was implemented using CompuCell3D (CC3D) which is a cell biology simulation platform. In order to couple Geant4 solver with CC3D, we developed a 'bridging' module, RADCELL, that extracts tumor cellular geometry of the CC3D simulation (including specification of the individual cells) and ported it to the Geant4 for radiation transport simulation. The cell dose and cell DNA damage distribution in multicellular system were obtained using Geant4. The tumor response was simulated using cell-based tissue models based on CC3D, and the cell dose and cell DNA damage information were fed back through RADCELL to CC3D for updating the cell properties. By merging two powerful and widely used modeling platforms, CC3D and Geant4, we delivered a novel tool that can give us the ability to simulate the dynamics of biological tissue in the presence of ionizing radiation, which provides a framework for quantifying the biological consequences of radiation therapy. In this introductory methods paper, we described our modeling platform in detail and showed how it can be applied to study the application of radiotherapy to a vascularized tumor.
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Affiliation(s)
- Ruirui Liu
- School of Nuclear Science and Engineering, Oregon State University, 100 Radiation Center, Corvallis, OR 97331, United States of America.,Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63110, United States of America
| | - Kathryn A Higley
- School of Nuclear Science and Engineering, Oregon State University, 100 Radiation Center, Corvallis, OR 97331, United States of America
| | - Maciej H Swat
- Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America
| | - Mark A J Chaplain
- School of Mathematics and Statistics, Mathematical Institute, University of St Andrews, St Andrews KY16 9SS, Fife, United Kingdom
| | - Gibin G Powathil
- Department of Mathematics, College of Science, Swansea University, Swansea, SA2 8PP, United Kingdom
| | - James A Glazier
- Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America
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12
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Bustamante DJ, Basile EJ, Hildreth BM, Browning NW, Jensen SA, Moldovan L, Petrache HI, Moldovan NI. Biofabrication of spheroids fusion-based tumor models: computational simulation of glucose effects. Biofabrication 2021; 13. [PMID: 33498017 DOI: 10.1088/1758-5090/abe025] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 01/26/2021] [Indexed: 01/04/2023]
Abstract
In vitro tumor models consisting of cell spheroids are increasingly used for mechanistic studies and pharmacological testing. However, unless vascularized, the availability of nutrients such as glucose to deeper layers of multicellular aggregates is limited. In addition, recent developments in cells-only biofabrication (e.g. 'scaffold-free bioprinting'), allow the creation of more complex spheroid-based structures, further exposing the cells to nutrient deprivation within these constructs. To explore the impact of glucose availability on such tumor-like structures, we used the CompuCell3D (CC3D) platform for modeling of tumor spheroids. By monitoring the types of cells, fusing pairs geometry and the distance between spheroids centers of mass, we made novel heuristic observations on how binary- and multi-spheroid fusions are impacted by glucose availability. At limiting glucose concentrations mimicking hypoglycemia we noted an abrupt collapse of the tumor spheroids, unexpectedly amplified by the contact with normal cell spheroids. At higher glucose concentrations, we found an increased intermixing of cancerous cells, strong anti-phase oscillations between proliferating and quiescent tumor cells and a structural instability of fusing tumor spheroids, leading to their re-fragmentation. In a model of tumor microenvironment composed of normal cell spheroids fusing around a tumoral one, the competition for glucose lead to either the tumor's disappearance, or to its steady expansion. Moreover, the invasion of this microenvironment by individual tumor cells was also strongly depended on the available glucose. In conclusion, we demonstrate the value of computational simulations for anticipating the properties of biofabricated tumor models, and in generating testable hypotheses regarding the relationship between cancer, nutrition and diabetes.
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Affiliation(s)
- David J Bustamante
- IUPUI BME, 799 W. Michigan Street, Indianapolis, Indiana, 46202-5195, UNITED STATES
| | - Elijah J Basile
- IUPUI, 301 University Boulevard, Indianapolis, Indiana, 46202-5146, UNITED STATES
| | - Brady M Hildreth
- IUPUI, 301 University Boulevard, Indianapolis, Indiana, 46202-5146, UNITED STATES
| | - Nathan W Browning
- IUPUI, 301 University Boulevard, Indianapolis, Indiana, 46202-5146, UNITED STATES
| | - S Alexander Jensen
- IUPUI, 301 University Boulevard Suite, Indianapolis, Indiana, 46202-5146, UNITED STATES
| | - Leni Moldovan
- Surgery, Indiana University School of Medicine, 1481 W. 10th St., Room D-2008, Indianapolis, Indiana, 46202-5114, UNITED STATES
| | - Horia I Petrache
- Department of Physics, Indiana University - Purdue University at Indianapolis, 402 N. Blackford Street, LD 154, Indianapolis, Indiana, 46202, UNITED STATES
| | - Nicanor I Moldovan
- VA Medical Center, Indiana University Purdue University at Indianapolis, 1481 W. 10th St., Room C6128, Indianapolis, Indiana, 46202-5143, UNITED STATES
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13
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Fortuna I, Perrone GC, Krug MS, Susin E, Belmonte JM, Thomas GL, Glazier JA, de Almeida RMC. CompuCell3D Simulations Reproduce Mesenchymal Cell Migration on Flat Substrates. Biophys J 2020; 118:2801-2815. [PMID: 32407685 PMCID: PMC7264849 DOI: 10.1016/j.bpj.2020.04.024] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 04/20/2020] [Accepted: 04/20/2020] [Indexed: 11/16/2022] Open
Abstract
Mesenchymal cell crawling is a critical process in normal development, in tissue function, and in many diseases. Quantitatively predictive numerical simulations of cell crawling thus have multiple scientific, medical, and technological applications. However, we still lack a low-computational-cost approach to simulate mesenchymal three-dimensional (3D) cell crawling. Here, we develop a computationally tractable 3D model (implemented as a simulation in the CompuCell3D simulation environment) of mesenchymal cells crawling on a two-dimensional substrate. The Fürth equation, the usual characterization of mean-squared displacement (MSD) curves for migrating cells, describes a motion in which, for increasing time intervals, cell movement transitions from a ballistic to a diffusive regime. Recent experiments have shown that for very short time intervals, cells exhibit an additional fast diffusive regime. Our simulations' MSD curves reproduce the three experimentally observed temporal regimes, with fast diffusion for short time intervals, slow diffusion for long time intervals, and intermediate time -interval-ballistic motion. The resulting parameterization of the trajectories for both experiments and simulations allows the definition of time- and length scales that translate between computational and laboratory units. Rescaling by these scales allows direct quantitative comparisons among MSD curves and between velocity autocorrelation functions from experiments and simulations. Although our simulations replicate experimentally observed spontaneous symmetry breaking, short-timescale diffusive motion, and spontaneous cell-motion reorientation, their computational cost is low, allowing their use in multiscale virtual-tissue simulations. Comparisons between experimental and simulated cell motion support the hypothesis that short-time actomyosin dynamics affects longer-time cell motility. The success of the base cell-migration simulation model suggests its future application in more complex situations, including chemotaxis, migration through complex 3D matrices, and collective cell motion.
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Affiliation(s)
- Ismael Fortuna
- Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Gabriel C Perrone
- Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Monique S Krug
- Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Eduarda Susin
- Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Julio M Belmonte
- Biocomplexity Institute and Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana; Department of Physics, North Carolina State University, Raleigh, North Carolina
| | - Gilberto L Thomas
- Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
| | - James A Glazier
- Biocomplexity Institute and Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana
| | - Rita M C de Almeida
- Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Instituto Nacional de Ciência e Tecnologia, Sistemas Complexos, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Program de Pós Graduação em Bioinformática, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
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14
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Letort G, Montagud A, Stoll G, Heiland R, Barillot E, Macklin P, Zinovyev A, Calzone L. PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling. Bioinformatics 2020; 35:1188-1196. [PMID: 30169736 PMCID: PMC6449758 DOI: 10.1093/bioinformatics/bty766] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 07/28/2018] [Accepted: 08/30/2018] [Indexed: 01/22/2023] Open
Abstract
MOTIVATION Due to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intracellular signalling using Boolean modelling (MaBoSS) and multicellular behaviour using agent-based modelling (PhysiCell). RESULTS PhysiBoSS provides a flexible and computationally efficient framework to explore the effect of environmental and genetic alterations of individual cells at the population level, bridging the critical gap from single-cell genotype to single-cell phenotype and emergent multicellular behaviour. PhysiBoSS thus becomes very useful when studying heterogeneous population response to treatment, mutation effects, different modes of invasion or isomorphic morphogenesis events. To concretely illustrate a potential use of PhysiBoSS, we studied heterogeneous cell fate decisions in response to TNF treatment. We explored the effect of different treatments and the behaviour of several resistant mutants. We highlighted the importance of spatial information on the population dynamics by considering the effect of competition for resources like oxygen. AVAILABILITY AND IMPLEMENTATION PhysiBoSS is freely available on GitHub (https://github.com/sysbio-curie/PhysiBoSS), with a Docker image (https://hub.docker.com/r/gletort/physiboss/). It is distributed as open source under the BSD 3-clause license. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Gaelle Letort
- Institut Curie, PSL Research University, Paris, France.,INSERM, U900, Paris, France.,CBIO-Centre for Computational Biology, MINES ParisTech, PSL Research University, Paris, France
| | - Arnau Montagud
- Institut Curie, PSL Research University, Paris, France.,INSERM, U900, Paris, France.,CBIO-Centre for Computational Biology, MINES ParisTech, PSL Research University, Paris, France
| | - Gautier Stoll
- Université Paris Descartes/Paris V, Sorbonne Paris Cité, Paris, France.,Gustave Roussy Cancer Campus, Villejuif, France.,INSERM, U1138, Paris, France.,Equipe 11 Labellisée par la Ligue Nationale Contre le Cancer, Centre de Recherche des Cordeliers, Paris, France
| | - Randy Heiland
- Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Emmanuel Barillot
- Institut Curie, PSL Research University, Paris, France.,INSERM, U900, Paris, France.,CBIO-Centre for Computational Biology, MINES ParisTech, PSL Research University, Paris, France
| | - Paul Macklin
- Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Andrei Zinovyev
- Institut Curie, PSL Research University, Paris, France.,INSERM, U900, Paris, France.,CBIO-Centre for Computational Biology, MINES ParisTech, PSL Research University, Paris, France
| | - Laurence Calzone
- Institut Curie, PSL Research University, Paris, France.,INSERM, U900, Paris, France.,CBIO-Centre for Computational Biology, MINES ParisTech, PSL Research University, Paris, France
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15
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Prediction and quantification of bacterial biofilm detachment using Glazier-Graner-Hogeweg method based model simulations. J Theor Biol 2019; 482:109994. [PMID: 31487498 DOI: 10.1016/j.jtbi.2019.109994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 08/01/2019] [Accepted: 09/02/2019] [Indexed: 11/22/2022]
Abstract
Morphological changes in bacterial biofilm structures arise from the fluid-structure interactions between the biofilm and the surrounding fluid. Depending on the magnitude of the force acting on the structure, the bacteria rearrange to attain an equilibrium shape or get washed away by the moving fluid. Understanding the dynamics behind the evolution of such equilibrium or failed states can aid in development of tools for biofilm removal or eradication. We develop a Glazier-Graner-Hogeweg method-based model to explore the collective evolution of biofilm morphology arising from cell-cell and cell-fluid interactions. We show that low adherence and high motility of the cells leads to sloughing of biofilms. Also, streamers are found to form under laminar flow conditions in tightly packed biofilms. In mixed species biofilms, we found that a species with less cell-cell binding affinity gets eroded faster than its counterpart. Therefore, we hypothesize that in nature these less-adherent species should be present encapsulated within the biofilm structure to maximize their chances of survival.
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16
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Chowkwale M, Mahler GJ, Huang P, Murray BT. A multiscale in silico model of endothelial to mesenchymal transformation in a tumor microenvironment. J Theor Biol 2019; 480:229-240. [PMID: 31430445 DOI: 10.1016/j.jtbi.2019.08.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 08/01/2019] [Accepted: 08/16/2019] [Indexed: 12/12/2022]
Abstract
Endothelial to mesenchymal transformation (EndMT) is a process in which endothelial cells gain a mesenchymal-like phenotype in response to mechanobiological signals that results in the remodeling or repair of underlying tissue. While initially associated with embryonic development, this process has since been shown to occur in adult tissue remodeling including wound healing, fibrosis, and cancer. In an attempt to understand the role of EndMT in cancer progression and metastasis, we present a multiscale, three-dimensional, in silico model. The model couples tissue level phenomena such as extracellular matrix remodeling, cellular level phenomena such as migration and proliferation, and chemical transport in the tumor microenvironment to mimic in vitro tissue models of the cancer microenvironment. The model is used to study the presence of EndMT-derived activated fibroblasts (EDAFs) and varying substrate stiffness on tumor cell migration and proliferation. The simulations accurately model the behavior of tumor cells under given conditions. The presence of EDAFs and/or an increase in substrate stiffness resulted in an increase in tumor cell activity. This model lays the foundation of further studies of EDAFs in a tumor microenvironment on a cellular and subcellular physiological level.
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Affiliation(s)
- M Chowkwale
- Department of Biomedical Engineering, Binghamton University, PO Box 6000, Binghamton, NY 13902, USA
| | - G J Mahler
- Department of Biomedical Engineering, Binghamton University, PO Box 6000, Binghamton, NY 13902, USA
| | - P Huang
- Department of Mechanical Engineering, Binghamton University, PO Box 6000, Binghamton, NY 13902, USA
| | - B T Murray
- Department of Mechanical Engineering, Binghamton University, PO Box 6000, Binghamton, NY 13902, USA.
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17
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Santorelli M, Lam C, Morsut L. Synthetic development: building mammalian multicellular structures with artificial genetic programs. Curr Opin Biotechnol 2019; 59:130-140. [PMID: 31128430 PMCID: PMC6778502 DOI: 10.1016/j.copbio.2019.03.016] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 03/08/2019] [Accepted: 03/24/2019] [Indexed: 12/28/2022]
Abstract
Synthetic biology efforts began in simple single-cell systems, which were relatively easy to manipulate genetically (Cameron et al., 2014). The field grew exponentially in the last two decades, and one of the latest frontiers are synthetic developmental programs for multicellular mammalian systems (Black et al., 2017; Wieland and Fussenegger, 2012) to genetically control features such as patterning or morphogenesis. These programs rely on engineered cell-cell communications, multicellular gene regulatory networks and effector genes. Here, we contextualize the first of these synthetic developmental programs, examine molecular and computational tools that can be used to generate next generation versions, and present the general logic that underpins these approaches. These advances are exciting as they represent a novel way to address both control and understanding in the field of developmental biology and tissue development (Elowitz and Lim, 2010; Velazquez et al., 2018; White et al., 2018; Morsut, 2017). This field is just at the beginning, and it promises to be of major interest in the upcoming years of biomedical research.
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Affiliation(s)
- Marco Santorelli
- The Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, United States
| | - Calvin Lam
- The Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, United States
| | - Leonardo Morsut
- The Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, United States; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, United States.
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18
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Wolff HB, Davidson LA, Merks RMH. Adapting a Plant Tissue Model to Animal Development: Introducing Cell Sliding into VirtualLeaf. Bull Math Biol 2019; 81:3322-3341. [PMID: 30927191 PMCID: PMC6677868 DOI: 10.1007/s11538-019-00599-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Accepted: 03/11/2019] [Indexed: 11/16/2022]
Abstract
Cell-based, mathematical modeling of collective cell behavior has become a prominent tool in developmental biology. Cell-based models represent individual cells as single particles or as sets of interconnected particles and predict the collective cell behavior that follows from a set of interaction rules. In particular, vertex-based models are a popular tool for studying the mechanics of confluent, epithelial cell layers. They represent the junctions between three (or sometimes more) cells in confluent tissues as point particles, connected using structural elements that represent the cell boundaries. A disadvantage of these models is that cell-cell interfaces are represented as straight lines. This is a suitable simplification for epithelial tissues, where the interfaces are typically under tension, but this simplification may not be appropriate for mesenchymal tissues or tissues that are under compression, such that the cell-cell boundaries can buckle. In this paper, we introduce a variant of VMs in which this and two other limitations of VMs have been resolved. The new model can also be seen as on off-the-lattice generalization of the Cellular Potts Model. It is an extension of the open-source package VirtualLeaf, which was initially developed to simulate plant tissue morphogenesis where cells do not move relative to one another. The present extension of VirtualLeaf introduces a new rule for cell-cell shear or sliding, from which cell rearrangement (T1) and cell extrusion (T2) transitions emerge naturally, allowing the application of VirtualLeaf to problems of animal development. We show that the updated VirtualLeaf yields different results than the traditional vertex-based models for differential adhesion-driven cell sorting and for the neighborhood topology of soft cellular networks.
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Affiliation(s)
- Henri B Wolff
- Centrum Wiskunde and Informatica, Science Park 123, 1098 XG, Amsterdam, The Netherlands
- Departments of Bioengineering, Developmental Biology, and Computational and Systems Biology, University of Pittsburgh, Bioscience Tower 3-5059 3501 Fifth Avenue, Pittsburgh, PA, USA
- Department of Epidemiology and Biostatistics, Decision Modeling Center VUmc, Amsterdam UMC location VUmc, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Lance A Davidson
- Departments of Bioengineering, Developmental Biology, and Computational and Systems Biology, University of Pittsburgh, Bioscience Tower 3-5059 3501 Fifth Avenue, Pittsburgh, PA, USA.
| | - Roeland M H Merks
- Centrum Wiskunde and Informatica, Science Park 123, 1098 XG, Amsterdam, The Netherlands.
- Mathematical Institute, University Leiden, P.O. Box 9512, 2300 RA, Leiden, The Netherlands.
- Mathematical Institute and Institute of Biology, Leiden University, P.O. Box 9505, 2300 RA, Leiden, The Netherlands.
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19
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Fu X, Sluka JP, Clendenon SG, Dunn KW, Wang Z, Klaunig JE, Glazier JA. Modeling of xenobiotic transport and metabolism in virtual hepatic lobule models. PLoS One 2018; 13:e0198060. [PMID: 30212461 PMCID: PMC6136710 DOI: 10.1371/journal.pone.0198060] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 08/23/2018] [Indexed: 12/29/2022] Open
Abstract
Computational models of normal liver function and xenobiotic induced liver damage are increasingly being used to interpret in vitro and in vivo data and as an approach to the de novo prediction of the liver’s response to xenobiotics. The microdosimetry (dose at the level of individual cells) of xenobiotics vary spatially within the liver because of both compound-independent and compound-dependent factors. In this paper, we build model liver lobules to investigate the interplay between vascular structure, blood flow and cellular transport that lead to regional variations in microdosimetry. We then compared simulation results obtained using this complex spatial model with a simpler linear pipe model of a sinusoid and a very simple single box model. We found that variations in diffusive transport, transporter-mediated transport and metabolism, coupled with complex liver sinusoid architecture and blood flow distribution, led to three essential patterns of xenobiotic exposure within the virtual liver lobule: (1) lobular-wise uniform, (2) radially varying and (3) both radially and azimuthally varying. We propose to use these essential patterns of exposure as a reference for selection of model representations when a computational study involves modeling detailed hepatic responses to xenobiotics.
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Affiliation(s)
- Xiao Fu
- Biocomplexity Institute, Indiana University, Bloomington, IN, United States of America
- Department of Physics, Indiana University, Bloomington, IN, United States of America
| | - James P. Sluka
- Biocomplexity Institute, Indiana University, Bloomington, IN, United States of America
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, United States of America
- * E-mail:
| | - Sherry G. Clendenon
- Biocomplexity Institute, Indiana University, Bloomington, IN, United States of America
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, United States of America
| | - Kenneth W. Dunn
- School of Medicine, Indiana University, Indianapolis, IN, United States of America
| | - Zemin Wang
- School of Public Health, Indiana University, Bloomington, IN, United States of America
| | - James E. Klaunig
- School of Public Health, Indiana University, Bloomington, IN, United States of America
| | - James A. Glazier
- Biocomplexity Institute, Indiana University, Bloomington, IN, United States of America
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, United States of America
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20
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Rognoni E, Pisco AO, Hiratsuka T, Sipilä KH, Belmonte JM, Mobasseri SA, Philippeos C, Dilão R, Watt FM. Fibroblast state switching orchestrates dermal maturation and wound healing. Mol Syst Biol 2018; 14:e8174. [PMID: 30158243 PMCID: PMC6113774 DOI: 10.15252/msb.20178174] [Citation(s) in RCA: 98] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 08/02/2018] [Accepted: 08/03/2018] [Indexed: 01/25/2023] Open
Abstract
Murine dermis contains functionally and spatially distinct fibroblast lineages that cease to proliferate in early postnatal life. Here, we propose a model in which a negative feedback loop between extracellular matrix (ECM) deposition and fibroblast proliferation determines dermal architecture. Virtual-tissue simulations of our model faithfully recapitulate dermal maturation, predicting a loss of spatial segregation of fibroblast lineages and dictating that fibroblast migration is only required for wound healing. To test this, we performed in vivo live imaging of dermal fibroblasts, which revealed that homeostatic tissue architecture is achieved without active cell migration. In contrast, both fibroblast proliferation and migration are key determinants of tissue repair following wounding. The results show that tissue-scale coordination is driven by the interdependence of cell proliferation and ECM deposition, paving the way for identifying new therapeutic strategies to enhance skin regeneration.
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Affiliation(s)
- Emanuel Rognoni
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, UK
| | | | - Toru Hiratsuka
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, UK
| | - Kalle H Sipilä
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, UK
| | - Julio M Belmonte
- Developmental Biology Unit and Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | | | - Christina Philippeos
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, UK
| | - Rui Dilão
- Nonlinear Dynamics Group, Instituto Superior Técnico, Lisbon, Portugal
| | - Fiona M Watt
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, UK
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21
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Wear HM, Eriksson A, Yao HHC, Watanabe KH. Cell-based computational model of early ovarian development in mice. Biol Reprod 2018; 97:365-377. [PMID: 29088396 DOI: 10.1093/biolre/iox089] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Accepted: 08/09/2017] [Indexed: 11/13/2022] Open
Abstract
Despite its importance to reproduction, certain mechanisms of early ovarian development remain a mystery. To improve our understanding, we constructed the first cell-based computational model of ovarian development in mice that is divided into two phases: Phase I spans embryonic day 5.5 (E5.5) to E12.5; and Phase II spans E12.5 to postnatal day 2. We used the model to investigate four mechanisms: in Phase I, (i) whether primordial germ cells (PGCs) undergo mitosis during migration; and (ii) if the mechanism for secretion of KIT ligand from the hindgut resembles inductive cell-cell signaling or is secreted in a static manner; and in Phase II, (iii) that changes in cellular adhesion produce germ cell nest breakdown; and (iv) whether localization of primordial follicles in the cortex of the ovary is due to proliferation of granulosa cells. We found that the combination of the first three hypotheses produced results that aligned with experimental images and PGC abundance data. Results from the fourth hypothesis did not match experimental images, which suggests that more detailed processes are involved in follicle localization. Phase I and Phase II of the model reproduce experimentally observed cell counts and morphology well. A sensitivity analysis identified contact energies, mitotic rates, KIT chemotaxis strength, and diffusion rate in Phase I and oocyte death rate in Phase II as parameters with the greatest impact on model predictions. The results demonstrate that the computational model can be used to understand unknown mechanisms, generate new hypotheses, and serve as an educational tool.
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Affiliation(s)
- Hannah M Wear
- Institute of Environmental Health, Oregon Health & Science University, Portland, OR, USA
| | - Annika Eriksson
- Division of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University Portland, OR, USA
| | - Humphrey Hung-Chang Yao
- Reproductive Developmental Biology Group, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Karen H Watanabe
- Institute of Environmental Health, Oregon Health & Science University, Portland, OR, USA.,School of Public Health, Oregon Health & Science University, Portland, OR, USA
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22
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Hirashima T, Rens EG, Merks RMH. Cellular Potts modeling of complex multicellular behaviors in tissue morphogenesis. Dev Growth Differ 2017; 59:329-339. [DOI: 10.1111/dgd.12358] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 03/24/2017] [Indexed: 12/14/2022]
Affiliation(s)
- Tsuyoshi Hirashima
- Institute for Frontier Life and Medical Sciences Kyoto University 53 Kawahara, Shogoin, Sakyo‐ku Kyoto 606‐8507 Japan
| | - Elisabeth G. Rens
- Centrum Wiskunde & Informatica Life Sciences Group Science Park 123 1098 XG Amsterdam the Netherlands
- Mathematical Institute Leiden University Niels Bohrweg 1 2333 CA Leiden the Netherlands
| | - Roeland M. H. Merks
- Centrum Wiskunde & Informatica Life Sciences Group Science Park 123 1098 XG Amsterdam the Netherlands
- Mathematical Institute Leiden University Niels Bohrweg 1 2333 CA Leiden the Netherlands
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23
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Ong ACM. Making sense of polycystic kidney disease. Lancet 2017; 389:1780-1782. [PMID: 28495155 DOI: 10.1016/s0140-6736(17)30928-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Revised: 02/23/2017] [Accepted: 03/07/2017] [Indexed: 10/19/2022]
Affiliation(s)
- Albert C M Ong
- Academic Nephrology Unit, University of Sheffield Medical School, Sheffield S10 2RX, UK.
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