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Henning P, Köster T, Haack F, Burrage K, Uhrmacher AM. Implications of different membrane compartmentalization models in particle-based in silico studies. ROYAL SOCIETY OPEN SCIENCE 2023; 10:221177. [PMID: 37416823 PMCID: PMC10320350 DOI: 10.1098/rsos.221177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 06/12/2023] [Indexed: 07/08/2023]
Abstract
Studying membrane dynamics is important to understand the cellular response to environmental stimuli. A decisive spatial characteristic of the plasma membrane is its compartmental structure created by the actin-based membrane-skeleton (fences) and anchored transmembrane proteins (pickets). Particle-based reaction-diffusion simulation of the membrane offers a suitable temporal and spatial resolution to analyse its spatially heterogeneous and stochastic dynamics. Fences have been modelled via hop probabilities, potentials or explicit picket fences. Our study analyses the different approaches' constraints and their impact on simulation results and performance. Each of the methods comes with its own constraints; the picket fences require small timesteps, potential fences might induce a bias in diffusion in crowded systems, and probabilistic fences, in addition to carefully scaling the probability with the timesteps, induce higher computational costs for each propagation step.
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Affiliation(s)
- Philipp Henning
- Institute for Visual and Analytic Computing, University of Rostock, Rostock, Germany
| | - Till Köster
- Institute for Visual and Analytic Computing, University of Rostock, Rostock, Germany
| | - Fiete Haack
- Institute for Visual and Analytic Computing, University of Rostock, Rostock, Germany
| | - Kevin Burrage
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
- Visiting Professor, Department of Computer Science, University of Oxford, Oxford, UK
| | - Adelinde M. Uhrmacher
- Institute for Visual and Analytic Computing, University of Rostock, Rostock, Germany
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2
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A multiscale model of the regulation of aquaporin 2 recycling. NPJ Syst Biol Appl 2022; 8:16. [PMID: 35534498 PMCID: PMC9085758 DOI: 10.1038/s41540-022-00223-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 03/24/2022] [Indexed: 11/08/2022] Open
Abstract
The response of cells to their environment is driven by a variety of proteins and messenger molecules. In eukaryotes, their distribution and location in the cell are regulated by the vesicular transport system. The transport of aquaporin 2 between membrane and storage region is a crucial part of the water reabsorption in renal principal cells, and its malfunction can lead to Diabetes insipidus. To understand the regulation of this system, we aggregated pathways and mechanisms from literature and derived three models in a hypothesis-driven approach. Furthermore, we combined the models to a single system to gain insight into key regulatory mechanisms of Aquaporin 2 recycling. To achieve this, we developed a multiscale computational framework for the modeling and simulation of cellular systems. The analysis of the system rationalizes that the compartmentalization of cAMP in renal principal cells is a result of the protein kinase A signalosome and can only occur if specific cellular components are observed in conjunction. Endocytotic and exocytotic processes are inherently connected and can be regulated by the same protein kinase A signal.
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3
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Styles KM, Brown AT, Sagona AP. A Review of Using Mathematical Modeling to Improve Our Understanding of Bacteriophage, Bacteria, and Eukaryotic Interactions. Front Microbiol 2021; 12:724767. [PMID: 34621252 PMCID: PMC8490754 DOI: 10.3389/fmicb.2021.724767] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 08/27/2021] [Indexed: 12/27/2022] Open
Abstract
Phage therapy, the therapeutic usage of viruses to treat bacterial infections, has many theoretical benefits in the ‘post antibiotic era.’ Nevertheless, there are currently no approved mainstream phage therapies. One reason for this is a lack of understanding of the complex interactions between bacteriophage, bacteria and eukaryotic hosts. These three-component interactions are complex, with non-linear or synergistic relationships, anatomical barriers and genetic or phenotypic heterogeneity all leading to disparity between performance and efficacy in in vivo versus in vitro environments. Realistic computer or mathematical models of these complex environments are a potential route to improve the predictive power of in vitro studies for the in vivo environment, and to streamline lab work. Here, we introduce and review the current status of mathematical modeling and highlight that data on genetic heterogeneity and mutational stochasticity, time delays and population densities could be critical in the development of realistic phage therapy models in the future. With this in mind, we aim to inform and encourage the collaboration and sharing of knowledge and expertise between microbiologists and theoretical modelers, synergising skills and smoothing the road to regulatory approval and widespread use of phage therapy.
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Affiliation(s)
- Kathryn M Styles
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - Aidan T Brown
- School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
| | - Antonia P Sagona
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
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4
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Warren T, McAllister R, Morgan A, Rai TS, McGilligan V, Ennis M, Page C, Kelly C, Peace A, Corfe BM, Mc Auley M, Watterson S. The Interdependency and Co-Regulation of the Vitamin D and Cholesterol Metabolism. Cells 2021; 10:2007. [PMID: 34440777 PMCID: PMC8392689 DOI: 10.3390/cells10082007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 07/27/2021] [Accepted: 07/28/2021] [Indexed: 12/30/2022] Open
Abstract
Vitamin D and cholesterol metabolism overlap significantly in the pathways that contribute to their biosynthesis. However, our understanding of their independent and co-regulation is limited. Cardiovascular disease is the leading cause of death globally and atherosclerosis, the pathology associated with elevated cholesterol, is the leading cause of cardiovascular disease. It is therefore important to understand vitamin D metabolism as a contributory factor. From the literature, we compile evidence of how these systems interact, relating the understanding of the molecular mechanisms involved to the results from observational studies. We also present the first systems biology pathway map of the joint cholesterol and vitamin D metabolisms made available using the Systems Biology Graphical Notation (SBGN) Markup Language (SBGNML). It is shown that the relationship between vitamin D supplementation, total cholesterol, and LDL-C status, and between latitude, vitamin D, and cholesterol status are consistent with our knowledge of molecular mechanisms. We also highlight the results that cannot be explained with our current knowledge of molecular mechanisms: (i) vitamin D supplementation mitigates the side-effects of statin therapy; (ii) statin therapy does not impact upon vitamin D status; and critically (iii) vitamin D supplementation does not improve cardiovascular outcomes, despite improving cardiovascular risk factors. For (iii), we present a hypothesis, based on observations in the literature, that describes how vitamin D regulates the balance between cellular and plasma cholesterol. Answering these questions will create significant opportunities for advancement in our understanding of cardiovascular health.
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Affiliation(s)
- Tara Warren
- Northern Ireland Centre for Stratified Medicine, C-TRIC, Altnagelvin Hospital Campus, School of Biomedical Sciences, Ulster University, Derry BT47 6SB, UK; (T.W.); (R.M.); (T.S.R.); (V.M.); (M.E.); (C.P.); (C.K.)
| | - Roisin McAllister
- Northern Ireland Centre for Stratified Medicine, C-TRIC, Altnagelvin Hospital Campus, School of Biomedical Sciences, Ulster University, Derry BT47 6SB, UK; (T.W.); (R.M.); (T.S.R.); (V.M.); (M.E.); (C.P.); (C.K.)
| | - Amy Morgan
- Department of Chemical Engineering, Faculty of Science & Engineering, University of Chester, Parkgate Road, Chester CH1 4BJ, UK; (A.M.); (M.M.A.)
| | - Taranjit Singh Rai
- Northern Ireland Centre for Stratified Medicine, C-TRIC, Altnagelvin Hospital Campus, School of Biomedical Sciences, Ulster University, Derry BT47 6SB, UK; (T.W.); (R.M.); (T.S.R.); (V.M.); (M.E.); (C.P.); (C.K.)
| | - Victoria McGilligan
- Northern Ireland Centre for Stratified Medicine, C-TRIC, Altnagelvin Hospital Campus, School of Biomedical Sciences, Ulster University, Derry BT47 6SB, UK; (T.W.); (R.M.); (T.S.R.); (V.M.); (M.E.); (C.P.); (C.K.)
| | - Matthew Ennis
- Northern Ireland Centre for Stratified Medicine, C-TRIC, Altnagelvin Hospital Campus, School of Biomedical Sciences, Ulster University, Derry BT47 6SB, UK; (T.W.); (R.M.); (T.S.R.); (V.M.); (M.E.); (C.P.); (C.K.)
| | - Christopher Page
- Northern Ireland Centre for Stratified Medicine, C-TRIC, Altnagelvin Hospital Campus, School of Biomedical Sciences, Ulster University, Derry BT47 6SB, UK; (T.W.); (R.M.); (T.S.R.); (V.M.); (M.E.); (C.P.); (C.K.)
| | - Catriona Kelly
- Northern Ireland Centre for Stratified Medicine, C-TRIC, Altnagelvin Hospital Campus, School of Biomedical Sciences, Ulster University, Derry BT47 6SB, UK; (T.W.); (R.M.); (T.S.R.); (V.M.); (M.E.); (C.P.); (C.K.)
| | - Aaron Peace
- Cardiology Unit, Western Health and Social Care Trust, Altnagelvin Regional Hospital, Derry BT47 6SB, UK;
| | - Bernard M. Corfe
- Human Nutrition Research Centre, Institute of Cellular Medicine, William Leech Building, Medical School, Newcastle University, Framlington Place, Newcastle upon Tyne NE2 4HH, UK;
| | - Mark Mc Auley
- Department of Chemical Engineering, Faculty of Science & Engineering, University of Chester, Parkgate Road, Chester CH1 4BJ, UK; (A.M.); (M.M.A.)
| | - Steven Watterson
- Northern Ireland Centre for Stratified Medicine, C-TRIC, Altnagelvin Hospital Campus, School of Biomedical Sciences, Ulster University, Derry BT47 6SB, UK; (T.W.); (R.M.); (T.S.R.); (V.M.); (M.E.); (C.P.); (C.K.)
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5
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Neutron diffusion coefficient for disordered arrays of TRISO particles in spherical nuclear fuel. ANN NUCL ENERGY 2020. [DOI: 10.1016/j.anucene.2020.107635] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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6
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Synak J, Rybarczyk A, Blazewicz J. Multi-agent approach to sequence structure simulation in the RNA World hypothesis. PLoS One 2020; 15:e0238253. [PMID: 32857812 PMCID: PMC7455006 DOI: 10.1371/journal.pone.0238253] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 08/12/2020] [Indexed: 12/03/2022] Open
Abstract
The origins of life on Earth have been the subject of inquiry since the early days of philosophical thought and are still intensively investigated by the researchers around the world. One of the theories explaining the life emergence, that gained the most attention recently is the RNA World hypothesis, which assumes that life on Earth was sparked by replicating RNA chains. Since wet lab analysis is time-consuming, many mathematical and computational approaches have been proposed that try to explain the origins of life. Recently proposed one, based on the work by Takeuchi and Hogeweg, addresses the problem of interplay between RNA replicases and RNA parasitic species, which is crucial for understanding the first steps of prebiotic evolution. In this paper, the aforementioned model has been extended and modified by introducing RNA sequence (structure) information and mutation rate close to real one. It allowed to observe the simple evolution mechanisms, which could have led to the more complicated systems and eventually, to the formation of the first cells. The main goal of this study was to determine the conditions that allowed the spontaneous emergence and evolution of the prebiotic replicases equipped with simple functional domains within a large population. Here we show that polymerase ribozymes could have appeared randomly and then quickly started to copy themselves in order for the system to reach equilibrium. It has been shown that evolutionary selection works even in the simplest systems.
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Affiliation(s)
- Jaroslaw Synak
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- European Center for Bioinformatics and Genomics, Poznan, Poland
| | - Agnieszka Rybarczyk
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- European Center for Bioinformatics and Genomics, Poznan, Poland
- * E-mail: (JB); (AR)
| | - Jacek Blazewicz
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- European Center for Bioinformatics and Genomics, Poznan, Poland
- * E-mail: (JB); (AR)
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7
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Ascolani G, Skerry TM, Lacroix D, Dall'Ara E, Shuaib A. Revealing hidden information in osteoblast's mechanotransduction through analysis of time patterns of critical events. BMC Bioinformatics 2020; 21:114. [PMID: 32183690 PMCID: PMC7079370 DOI: 10.1186/s12859-020-3394-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 02/04/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix by mechanical load and intracellular activity. By controlling the balance between the intracellular and extracellular domains, mechanotransduction determines the optimum functionality of skeletal dynamics. Failure of this relationship was suggested to contribute to bone-related diseases such as osteoporosis. RESULTS A hybrid mechanical and agent-based model (Mech-ABM), simulating mechanotransduction in a single osteoblast under external mechanical perturbations, was utilised to simulate and examine modulation of the activation dynamics of molecules within mechanotransduction on the cellular response to mechanical stimulation. The number of molecules and their fluctuations have been analysed in terms of recurrences of critical events. A numerical approach has been developed to invert subordination processes and to extract the direction processes from the molecular signals in order to derive the distribution of recurring events. These predict that there are large fluctuations enclosing information hidden in the noise which is beyond the dynamic variations of molecular baselines. Moreover, studying the system under different mechanical load regimes and altered dynamics of feedback loops, illustrate that the waiting time distributions of each molecule are a signature of the system's state. CONCLUSIONS The behaviours of the molecular waiting times change with the changing of mechanical load regimes and altered dynamics of feedback loops, presenting the same variation of patterns for similar interacting molecules and identifying specific alterations for key molecules in mechanotransduction. This methodology could be used to provide a new tool to identify potent molecular candidates to modulate mechanotransduction, hence accelerate drug discovery towards therapeutic targets for bone mass upregulation.
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Affiliation(s)
- Gianluca Ascolani
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
- Insigneo Institute of In Silico Medicine, University of Sheffield, Sheffield, UK
| | - Timothy M Skerry
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Damien Lacroix
- Insigneo Institute of In Silico Medicine, University of Sheffield, Sheffield, UK
- Department of Mechanical Engineering, University of Sheffield, Sheffield, UK
| | - Enrico Dall'Ara
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
- Insigneo Institute of In Silico Medicine, University of Sheffield, Sheffield, UK
| | - Aban Shuaib
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK.
- Insigneo Institute of In Silico Medicine, University of Sheffield, Sheffield, UK.
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8
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Arjunan SNV, Miyauchi A, Iwamoto K, Takahashi K. pSpatiocyte: a high-performance simulator for intracellular reaction-diffusion systems. BMC Bioinformatics 2020; 21:33. [PMID: 31996129 PMCID: PMC6990473 DOI: 10.1186/s12859-019-3338-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Accepted: 12/30/2019] [Indexed: 12/19/2022] Open
Abstract
Background Studies using quantitative experimental methods have shown that intracellular spatial distribution of molecules plays a central role in many cellular systems. Spatially resolved computer simulations can integrate quantitative data from these experiments to construct physically accurate models of the systems. Although computationally expensive, microscopic resolution reaction-diffusion simulators, such as Spatiocyte can directly capture intracellular effects comprising diffusion-limited reactions and volume exclusion from crowded molecules by explicitly representing individual diffusing molecules in space. To alleviate the steep computational cost typically associated with the simulation of large or crowded intracellular compartments, we present a parallelized Spatiocyte method called pSpatiocyte. Results The new high-performance method employs unique parallelization schemes on hexagonal close-packed (HCP) lattice to efficiently exploit the resources of common workstations and large distributed memory parallel computers. We introduce a coordinate system for fast accesses to HCP lattice voxels, a parallelized event scheduler, a parallelized Gillespie’s direct-method for unimolecular reactions, and a parallelized event for diffusion and bimolecular reaction processes. We verified the correctness of pSpatiocyte reaction and diffusion processes by comparison to theory. To evaluate the performance of pSpatiocyte, we performed a series of parallelized diffusion runs on the RIKEN K computer. In the case of fine lattice discretization with low voxel occupancy, pSpatiocyte exhibited 74% parallel efficiency and achieved a speedup of 7686 times with 663552 cores compared to the runtime with 64 cores. In the weak scaling performance, pSpatiocyte obtained efficiencies of at least 60% with up to 663552 cores. When executing the Michaelis-Menten benchmark model on an eight-core workstation, pSpatiocyte required 45- and 55-fold shorter runtimes than Smoldyn and the parallel version of ReaDDy, respectively. As a high-performance application example, we study the dual phosphorylation-dephosphorylation cycle of the MAPK system, a typical reaction network motif in cell signaling pathways. Conclusions pSpatiocyte demonstrates good accuracies, fast runtimes and a significant performance advantage over well-known microscopic particle methods in large-scale simulations of intracellular reaction-diffusion systems. The source code of pSpatiocyte is available at https://spatiocyte.org.
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Affiliation(s)
| | - Atsushi Miyauchi
- Research Organization for Information Science and Technology, Chuo, Kobe, Japan
| | - Kazunari Iwamoto
- RIKEN Center for Biosystems Dynamics Research, Suita, Osaka, Japan
| | - Koichi Takahashi
- RIKEN Center for Biosystems Dynamics Research, Suita, Osaka, Japan
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9
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Köster T, Henning P, Uhrmacher AM. Potential based, spatial simulation of dynamically nested particles. BMC Bioinformatics 2019; 20:607. [PMID: 31775608 PMCID: PMC6880518 DOI: 10.1186/s12859-019-3092-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Accepted: 09/10/2019] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND To study cell biological phenomena which depend on diffusion, active transport processes, or the locations of species, modeling and simulation studies need to take space into account. To describe the system as a collection of discrete objects moving and interacting in continuous space, various particle-based reaction diffusion simulators for cell-biological system have been developed. So far the focus has been on particles as solid spheres or points. However, spatial dynamics might happen at different organizational levels, such as proteins, vesicles or cells with interrelated dynamics which requires spatial approaches that take this multi-levelness of cell biological systems into account. RESULTS Based on the perception of particles forming hollow spheres, ML-Force contributes to the family of particle-based simulation approaches: in addition to excluded volumes and forces, it also supports compartmental dynamics and relating dynamics between different organizational levels explicitly. Thereby, compartmental dynamics, e.g., particles entering and leaving other particles, and bimolecular reactions are modeled using pair-wise potentials (forces) and the Langevin equation. In addition, forces that act independently of other particles can be applied to direct the movement of particles. Attributes and the possibility to define arbitrary functions on particles, their attributes and content, to determine the results and kinetics of reactions add to the expressiveness of ML-Force. Its implementation comprises a rudimentary rule-based embedded domain-specific modeling language for specifying models and a simulator for executing models continuously. Applications inspired by cell biological models from literature, such as vesicle transport or yeast growth, show the value of the realized features. They facilitate capturing more complex spatial dynamics, such as the fission of compartments or the directed movement of particles, and enable the integration of non-spatial intra-compartmental dynamics as stochastic events. CONCLUSIONS By handling all dynamics based on potentials (forces) and the Langevin equation, compartmental dynamics, such as dynamic nesting, fusion and fission of compartmental structures are handled continuously and are seamlessly integrated with traditional particle-based reaction-diffusion dynamics within the cell. Thereby, attributes and arbitrary functions allow to flexibly describe diverse spatial phenomena, and relate dynamics across organizational levels. Also they prove crucial in modeling intra-cellular or intra-compartmental dynamics in a non-spatial manner, and, thus, to abstract from spatial dynamics, on demand which increases the range of multi-compartmental processes that can be captured.
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Affiliation(s)
- Till Köster
- Institute of Computer Science, University of Rostock, Albert-Einstein-Straße 22, Rostock, 18059 Germany
| | - Philipp Henning
- Institute of Computer Science, University of Rostock, Albert-Einstein-Straße 22, Rostock, 18059 Germany
| | - Adelinde M. Uhrmacher
- Institute of Computer Science, University of Rostock, Albert-Einstein-Straße 22, Rostock, 18059 Germany
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Smith S, Grima R. Spatial Stochastic Intracellular Kinetics: A Review of Modelling Approaches. Bull Math Biol 2019; 81:2960-3009. [PMID: 29785521 PMCID: PMC6677717 DOI: 10.1007/s11538-018-0443-1] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Accepted: 05/03/2018] [Indexed: 01/22/2023]
Abstract
Models of chemical kinetics that incorporate both stochasticity and diffusion are an increasingly common tool for studying biology. The variety of competing models is vast, but two stand out by virtue of their popularity: the reaction-diffusion master equation and Brownian dynamics. In this review, we critically address a number of open questions surrounding these models: How can they be justified physically? How do they relate to each other? How do they fit into the wider landscape of chemical models, ranging from the rate equations to molecular dynamics? This review assumes no prior knowledge of modelling chemical kinetics and should be accessible to a wide range of readers.
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Affiliation(s)
- Stephen Smith
- School of Biological Sciences, University of Edinburgh, Mayfield Road, Edinburgh, EH9 3JR, Scotland, UK
| | - Ramon Grima
- School of Biological Sciences, University of Edinburgh, Mayfield Road, Edinburgh, EH9 3JR, Scotland, UK.
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11
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Li G, Ni A, Yu M. Pretumor microenvironment of hepatocellular carcinoma: Cancerization or anticancerization? Gene 2019; 701:46-54. [PMID: 30902783 DOI: 10.1016/j.gene.2019.03.034] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 03/11/2019] [Accepted: 03/18/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Tumor microenvironment (TM) has been deeply concerned. However, the pretumor microenvironment (PTM) was poorly understood. The purpose in this study was to explore the possible pathophysiological features of PTM before hepatocellular carcinoma (HCC) appearance. METHODS Mouse livers with no swelling but with tumors present elsewhere in the body after subcutaneous injection of H22 in the fore underarm were considered a PTM, HCC tumors presenting far away from the PTM were regarded as a TM, and the healthy livers of mice without injection of H22 were regarded as a physiological microenvironment (PM). The transcriptomes of samples were generated using RNA-seq and validated using RT-qPCR. RESULTS Overall, 4483 differentially expressed genes (DEGs) were found in the TM compared with the PTM (TM/PTM), but only 194 were altered in the PTM compared with the PM (PTM/PM). Among those 194 DEGs, 104 displayed upregulation and 90 downregulation. Some of these DEGs could promote the ability to resist cancerization or facilitate cancer metastasis, while others indicated liver impairment. The DEGs were involved in 16 relevant pathways. Additionally, the frequency of alternative splicing (AS) in the DEGs in various samples was positively related to the expression of those DEGs. CONCLUSIONS The PTM initiatively armed itself to combat cancerization when its indications appeared although the PTM did not manifest any tissue swelling. However, the cancer cells were negatively influencing immunity to prevent clearance and positively promoting transformation to construct a suitable environment. During transformation by cancer cells, some genes with acquired AS participated in the construction of the PTM. This alteration created an invadable space and an appropriate environment for cancer cells.
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Affiliation(s)
- Genliang Li
- Youjiang Medical University for Nationalities, Baise 533000, Guangxi, China.
| | - Anni Ni
- Youjiang Medical University for Nationalities, Baise 533000, Guangxi, China
| | - Mengyao Yu
- Donghai county hospital, Lianyungang 222000, Jiangsu, China
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12
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Generalizing Gillespie's Direct Method to Enable Network-Free Simulations. Bull Math Biol 2018; 81:2822-2848. [PMID: 29594824 DOI: 10.1007/s11538-018-0418-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Accepted: 03/19/2018] [Indexed: 12/22/2022]
Abstract
Gillespie's direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie's direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termed network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie's direct method for network-free simulation. Finally, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.
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Abstract
As quantitative biologists get more measurements of spatially regulated systems such as cell division and polarization, simulation of reaction and diffusion of proteins using the data is becoming increasingly relevant to uncover the mechanisms underlying the systems. Spatiocyte is a lattice-based stochastic particle simulator for biochemical reaction and diffusion processes. Simulations can be performed at single molecule and compartment spatial scales simultaneously. Molecules can diffuse and react in 1D (filament), 2D (membrane), and 3D (cytosol) compartments. The implications of crowded regions in the cell can be investigated because each diffusing molecule has spatial dimensions. Spatiocyte adopts multi-algorithm and multi-timescale frameworks to simulate models that simultaneously employ deterministic, stochastic, and particle reaction-diffusion algorithms. Comparison of light microscopy images to simulation snapshots is supported by Spatiocyte microscopy visualization and molecule tagging features. Spatiocyte is open-source software and is freely available at http://spatiocyte.org .
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14
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Lehnert T, Figge MT. Dimensionality of Motion and Binding Valency Govern Receptor-Ligand Kinetics As Revealed by Agent-Based Modeling. Front Immunol 2017; 8:1692. [PMID: 29250071 PMCID: PMC5714874 DOI: 10.3389/fimmu.2017.01692] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 11/16/2017] [Indexed: 11/23/2022] Open
Abstract
Mathematical modeling and computer simulations have become an integral part of modern biological research. The strength of theoretical approaches is in the simplification of complex biological systems. We here consider the general problem of receptor–ligand binding in the context of antibody–antigen binding. On the one hand, we establish a quantitative mapping between macroscopic binding rates of a deterministic differential equation model and their microscopic equivalents as obtained from simulating the spatiotemporal binding kinetics by stochastic agent-based models. On the other hand, we investigate the impact of various properties of B cell-derived receptors—such as their dimensionality of motion, morphology, and binding valency—on the receptor–ligand binding kinetics. To this end, we implemented an algorithm that simulates antigen binding by B cell-derived receptors with a Y-shaped morphology that can move in different dimensionalities, i.e., either as membrane-anchored receptors or as soluble receptors. The mapping of the macroscopic and microscopic binding rates allowed us to quantitatively compare different agent-based model variants for the different types of B cell-derived receptors. Our results indicate that the dimensionality of motion governs the binding kinetics and that this predominant impact is quantitatively compensated by the bivalency of these receptors.
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Affiliation(s)
- Teresa Lehnert
- Research Group Applied Systems Biology, Leibniz Institute of Natural Product Research and Infection Biology - Hans Knöll Institute (HKI), Jena, Germany.,Center for Sepsis Control and Care (CSCC), Jena University Hospital, Jena, Germany
| | - Marc Thilo Figge
- Research Group Applied Systems Biology, Leibniz Institute of Natural Product Research and Infection Biology - Hans Knöll Institute (HKI), Jena, Germany.,Center for Sepsis Control and Care (CSCC), Jena University Hospital, Jena, Germany.,Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, Jena, Germany
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15
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Szostak N, Synak J, Borowski M, Wasik S, Blazewicz J. Simulating the origins of life: The dual role of RNA replicases as an obstacle to evolution. PLoS One 2017; 12:e0180827. [PMID: 28700697 PMCID: PMC5507279 DOI: 10.1371/journal.pone.0180827] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2017] [Accepted: 06/21/2017] [Indexed: 01/08/2023] Open
Abstract
Despite years of study, it is still not clear how life emerged from inanimate matter and evolved into the complex forms that we observe today. One of the most recognized hypotheses for the origins of life, the RNA World hypothesis, assumes that life was sparked by prebiotic replicating RNA chains. In this paper, we address the problems caused by the interplay between hypothetical prebiotic RNA replicases and RNA parasitic species. We consider the coexistence of parasite RNAs and RNA replicases as well as the impact of parasites on the further evolution of replicases. For these purposes, we used multi-agent modeling techniques that allow for realistic assumptions regarding the movement and spatial interactions of modeled species. The general model used in this study is based on work by Takeuchi and Hogeweg. Our results confirm that the coexistence of parasite RNAs and replicases is possible in a spatially extended system, even if we take into consideration more realistic assumptions than Takeuchi and Hogeweg. However, we also showed that the presence of trade-off that takes into the account an RNA folding process could still pose a serious obstacle to the evolution of replication. We conclude that this might be a cause for one of the greatest transitions in life that took place early in evolution-the separation of the function between DNA templates and protein enzymes, with a central role for RNA species.
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Affiliation(s)
- Natalia Szostak
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- European Centre for Bioinformatics and Genomics, Poznan, Poland
| | - Jaroslaw Synak
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Marcin Borowski
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- European Centre for Bioinformatics and Genomics, Poznan, Poland
| | - Szymon Wasik
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- European Centre for Bioinformatics and Genomics, Poznan, Poland
| | - Jacek Blazewicz
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- European Centre for Bioinformatics and Genomics, Poznan, Poland
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16
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van Niel EWJ, Bergdahl B, Hahn-Hägerdal B. Close to the Edge: Growth Restrained by the NAD(P)H/ATP Formation Flux Ratio. Front Microbiol 2017; 8:1149. [PMID: 28690597 PMCID: PMC5479917 DOI: 10.3389/fmicb.2017.01149] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Accepted: 06/07/2017] [Indexed: 11/13/2022] Open
Abstract
Most fermentative microorganisms grow well-under anaerobic conditions managing a balanced redox and appropriate energy metabolism, but a few species do exist in which cells have to cope with inadequate energy recovery or capture and/or redox balancing. Two cases of these species, i.e., the metabolically engineered Saccharomyces cerevisiae enabling it to ferment xylose and Lactobacillus reuteri fermenting glucose via the phosphoketolase pathway, are here used to introduce a quantification parameter to capture what limits the growth rate of these microorganisms under anaerobic conditions. This dimensionless parameter, the cofactor formation flux ratio (RJ), is the ratio between the redox formation flux (JNADH+NADPH), and the energy carrier formation flux (JATP), which are mainly connected to the central carbon pathways. Data from metabolic flux analyses performed in previous and present studies were used to estimate the RJ-values. Even though both microorganisms possess different central pathways, a similar relationship between RJ and the specific growth rate (μ) was found. Furthermore, for both microorganisms external electron acceptors moderately reduced the RJ-value, thereby raising the μ accordingly. Based on the emerging profile of this relationship an interpretation is presented suggesting that this quantitative analysis can be applied beyond the two microbial species experimentally investigated in the current study to provide data for future targeted strain development strategies.
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Affiliation(s)
- Ed W J van Niel
- Division of Applied Microbiology, Lund UniversityLund, Sweden
| | - Basti Bergdahl
- Division of Applied Microbiology, Lund UniversityLund, Sweden
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17
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Roberts CC, Chang CEA. Modeling of enhanced catalysis in multienzyme nanostructures: effect of molecular scaffolds, spatial organization, and concentration. J Chem Theory Comput 2016; 11:286-92. [PMID: 26574226 DOI: 10.1021/ct5007482] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Colocalized multistep enzymatic reaction pathways within biological catabolic and metabolic processes occur with high yield and specificity. Spatial organization on membranes or surfaces may be associated with increased efficiency of intermediate substrate transfer. Using a new Brownian dynamics package, GeomBD, we explored the geometric features of a surface-anchored enzyme system by parallel coarse-grained Brownian dynamics simulations of substrate diffusion over microsecond (μs) to millisecond (ms) time scales. We focused on a recently developed glucose oxidase (GOx), horseradish peroxidase (HRP), and DNA origami-scaffold enzyme system, where the H2O2 substrate of HRP is produced by GOx. The results revealed and explained a significant advantage in catalytic enhancement by optimizing interenzyme distance and orientation in the presence of the scaffold model. The planar scaffold colocalized the enzymes and provided a diffusive barrier that enhanced substrate transfer probability, becoming more relevant with increasing interenzyme distance. The results highlight the importance of protein geometry in the proper assessment of distance and orientation dependence on the probability of substrate transfer. They shed light on strategies for engineering multienzyme complexes and further investigation of enhanced catalytic efficiency for substrate diffusion between membrane-anchoring proteins.
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Affiliation(s)
- Christopher C Roberts
- Department of Chemistry, University of California , Riverside, California 92521, United States
| | - Chia-en A Chang
- Department of Chemistry, University of California , Riverside, California 92521, United States
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18
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Klein HCR, Guichard P, Hamel V, Gönczy P, Schwarz US. Computational support for a scaffolding mechanism of centriole assembly. Sci Rep 2016; 6:27075. [PMID: 27272020 PMCID: PMC4897622 DOI: 10.1038/srep27075] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Accepted: 05/13/2016] [Indexed: 12/29/2022] Open
Abstract
Centrioles are essential for forming cilia, flagella and centrosomes. Successful centriole assembly requires proteins of the SAS-6 family, which can form oligomeric ring structures with ninefold symmetry in vitro. While important progress has been made in understanding SAS-6 protein biophysics, the mechanisms enabling ring formation in vivo remain elusive. Likewise, the mechanisms by which a nascent centriole forms near-orthogonal to an existing one are not known. Here, we investigate possible mechanisms of centriole assembly using coarse-grained Brownian dynamics computer simulations in combination with a rate equation approach. Our results suggest that without any external factors, strong stabilization associated with ring closure would be needed to enable efficient ring formation. Strikingly, our simulations reveal that a scaffold-assisted assembly mechanism can trigger robust ring formation owing to local cooperativity, and that this mechanism can also impart orthogonalilty to centriole assembly. Overall, our findings provide novel insights into the organizing principles governing the assembly of this important organelle.
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Affiliation(s)
- Heinrich C. R. Klein
- Institute for Theoretical Physics and BioQuant, Heidelberg University, D-69120 Heidelberg, Germany
| | - Paul Guichard
- Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Virginie Hamel
- Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Pierre Gönczy
- Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Ulrich S. Schwarz
- Institute for Theoretical Physics and BioQuant, Heidelberg University, D-69120 Heidelberg, Germany
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19
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Spatial Representations and Analysis Techniques. FORMAL METHODS FOR THE QUANTITATIVE EVALUATION OF COLLECTIVE ADAPTIVE SYSTEMS 2016. [DOI: 10.1007/978-3-319-34096-8_5] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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20
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In Situ Cryo-Electron Tomography: A Post-Reductionist Approach to Structural Biology. J Mol Biol 2016; 428:332-343. [DOI: 10.1016/j.jmb.2015.09.030] [Citation(s) in RCA: 128] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2015] [Revised: 09/28/2015] [Accepted: 09/30/2015] [Indexed: 11/24/2022]
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21
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Bronstein L, Zechner C, Koeppl H. Bayesian inference of reaction kinetics from single-cell recordings across a heterogeneous cell population. Methods 2015; 85:22-35. [PMID: 25986935 DOI: 10.1016/j.ymeth.2015.05.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Revised: 04/19/2015] [Accepted: 05/10/2015] [Indexed: 11/30/2022] Open
Abstract
Single-cell experimental techniques provide informative data to help uncover dynamical processes inside a cell. Making full use of such data requires dedicated computational methods to estimate biophysical process parameters and states in a model-based manner. In particular, the treatment of heterogeneity or cell-to-cell variability deserves special attention. The present article provides an introduction to one particular class of algorithms which employ marginalization in order to take heterogeneity into account. An overview of alternative approaches is provided for comparison. We treat two frequently encountered scenarios in single-cell experiments, namely, single-cell trajectory data and single-cell distribution data.
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Affiliation(s)
- L Bronstein
- Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, Darmstadt, Germany
| | - C Zechner
- Department of Biosystems Sciences and Engineering, ETH Zürich, Basel, Switzerland
| | - H Koeppl
- Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, Darmstadt, Germany.
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22
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Bittig AT, Matschegewski C, Nebe JB, Stählke S, Uhrmacher AM. Membrane related dynamics and the formation of actin in cells growing on micro-topographies: a spatial computational model. BMC SYSTEMS BIOLOGY 2014; 8:106. [PMID: 25200251 PMCID: PMC4363941 DOI: 10.1186/s12918-014-0106-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2013] [Accepted: 08/18/2014] [Indexed: 01/07/2023]
Abstract
Background Intra-cellular processes of cells at the interface to an implant surface are influenced significantly by their extra-cellular surrounding. Specifically, when growing osteoblasts on titanium surfaces with regular micro-ranged geometry, filaments are shorter, less aligned and they concentrate at the top of the geometric structures. Changes to the cytoskeleton network, i. e., its localization, alignment, orientation, and lengths of the filaments, as well as the overall concentration and distribution of key-actors are induced. For example, integrin is distributed homogeneously, whereas integrin in activated state and vinculin, both components of focal adhesions, have been found clustered on the micro-ranged geometries. Also, the concentration of Rho, an intracellular signaling protein related to focal adhesion regulation, was significantly lower. Results To explore whether regulations associated with the focal adhesion complex can be responsible for the changed actin filament patterns, a spatial computational model has been developed using ML-Space, a rule-based model description language, and its associated Brownian-motion-based simulator. The focus has been on the deactivation of cofilin in the vicinity of the focal adhesion complex. The results underline the importance of sensing mechanisms to support a clustering of actin filament nucleations on the micro-ranged geometries, and of intracellular diffusion processes, which lead to spatially heterogeneous distributions of active (dephosphorylated) cofilin, which in turn influences the organization of the actin network. We find, for example, that the spatial heterogeneity of key molecular actors can explain the difference in filament lengths in cells on different micro-geometries partly, but to explain the full extent, further model assumptions need to be added and experimentally validated. In particular, our findings and hypothesis referring to the role, distribution, and amount of active cofilin have still to be verified in wet-lab experiments. Conclusion Letting cells grow on surface structures is a possibility to shed new light on the intricate mechanisms that relate membrane and actin related dynamics in the cell. Our results demonstrate the need for declarative expressive spatial modeling approaches that allow probing different hypotheses, and the central role of the focal adhesion complex not only for nucleating actin filaments, but also for regulating possible severing agents locally.
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Affiliation(s)
- Arne T Bittig
- Modeling and Simulation Group, Institute of Computer Science, University of Rostock, Albert-Einstein-Str. 22, Rostock, 18059, Germany.
| | - Claudia Matschegewski
- Department of Cell Biology, University Medical Center Rostock, Schillingallee 69Rostock, 18057, Germany. .,Present address: Agronomy and Crop Science, Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany.
| | - J Barbara Nebe
- Department of Cell Biology, University Medical Center Rostock, Schillingallee 69Rostock, 18057, Germany.
| | - Susanne Stählke
- Department of Cell Biology, University Medical Center Rostock, Schillingallee 69Rostock, 18057, Germany.
| | - Adelinde M Uhrmacher
- Modeling and Simulation Group, Institute of Computer Science, University of Rostock, Albert-Einstein-Str. 22, Rostock, 18059, Germany.
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23
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Hasnain S, McClendon CL, Hsu MT, Jacobson MP, Bandyopadhyay P. A new coarse-grained model for E. coli cytoplasm: accurate calculation of the diffusion coefficient of proteins and observation of anomalous diffusion. PLoS One 2014; 9:e106466. [PMID: 25180859 PMCID: PMC4152264 DOI: 10.1371/journal.pone.0106466] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2014] [Accepted: 07/30/2014] [Indexed: 01/07/2023] Open
Abstract
A new coarse-grained model of the E. coli cytoplasm is developed by describing the proteins of the cytoplasm as flexible units consisting of one or more spheres that follow Brownian dynamics (BD), with hydrodynamic interactions (HI) accounted for by a mean-field approach. Extensive BD simulations were performed to calculate the diffusion coefficients of three different proteins in the cellular environment. The results are in close agreement with experimental or previously simulated values, where available. Control simulations without HI showed that use of HI is essential to obtain accurate diffusion coefficients. Anomalous diffusion inside the crowded cellular medium was investigated with Fractional Brownian motion analysis, and found to be present in this model. By running a series of control simulations in which various forces were removed systematically, it was found that repulsive interactions (volume exclusion) are the main cause for anomalous diffusion, with a secondary contribution from HI.
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Affiliation(s)
- Sabeeha Hasnain
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
| | - Christopher L. McClendon
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, California, United States of America
| | - Monica T. Hsu
- Graduate Group in Biophysics, University of California San Francisco, San Francisco, California, United States of America
| | - Matthew P. Jacobson
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America
| | - Pradipta Bandyopadhyay
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
- * E-mail:
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24
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Klein HCR, Schwarz US. Studying protein assembly with reversible Brownian dynamics of patchy particles. J Chem Phys 2014; 140:184112. [DOI: 10.1063/1.4873708] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
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25
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Roberts E. Cellular and molecular structure as a unifying framework for whole-cell modeling. Curr Opin Struct Biol 2014; 25:86-91. [PMID: 24509245 DOI: 10.1016/j.sbi.2014.01.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2013] [Accepted: 01/07/2014] [Indexed: 10/25/2022]
Abstract
Whole-cell modeling has the potential to play a major role in revolutionizing our understanding of cellular biology over the next few decades. A computational model of the entire cell would allow cellular biologists to integrate data from many disparate sources in a single consistent framework. Such a comprehensive model would be useful both for hypothesis testing and in the discovery of new behaviors that emerge from complex biological networks. Cellular and molecular structure can and should be a key organizing principle in a whole-cell model, connecting models across time and length scales in a multiscale approach. Here I present a summary of recent research centered around using molecular and cellular structure to model the behavior of cells.
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Affiliation(s)
- Elijah Roberts
- Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218, USA.
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26
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SANCHEZ-OSORIO ISMAEL, RAMOS FERNANDO, MAYORGA PEDRO, DANTAN EDGAR. FOUNDATIONS FOR MODELING THE DYNAMICS OF GENE REGULATORY NETWORKS: A MULTILEVEL-PERSPECTIVE REVIEW. J Bioinform Comput Biol 2014; 12:1330003. [DOI: 10.1142/s0219720013300037] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
A promising alternative for unraveling the principles under which the dynamic interactions among genes lead to cellular phenotypes relies on mathematical and computational models at different levels of abstraction, from the molecular level of protein-DNA interactions to the system level of functional relationships among genes. This review article presents, under a bottom–up perspective, a hierarchy of approaches to modeling gene regulatory network dynamics, from microscopic descriptions at the single-molecule level in the spatial context of an individual cell to macroscopic models providing phenomenological descriptions at the population-average level. The reviewed modeling approaches include Molecular Dynamics, Particle-Based Brownian Dynamics, the Master Equation approach, Ordinary Differential Equations, and the Boolean logic abstraction. Each of these frameworks is motivated by a particular biological context and the nature of the insight being pursued. The setting of gene network dynamic models from such frameworks involves assumptions and mathematical artifacts often ignored by the non-specialist. This article aims at providing an entry point for biologists new to the field and computer scientists not acquainted with some recent biophysically-inspired models of gene regulation. The connections promoting intuition between different abstraction levels and the role that approximations play in the modeling process are highlighted throughout the paper.
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Affiliation(s)
- ISMAEL SANCHEZ-OSORIO
- Department of Computer Science, Monterrey Institute of Technology and Higher Education Campus Cuernavaca, Autopista del Sol km 104, Xochitepec, Morelos 62790, Mexico
| | - FERNANDO RAMOS
- Department of Computer Science, Monterrey Institute of Technology and Higher Education Campus Cuernavaca, Autopista del Sol km 104, Xochitepec, Morelos 62790, Mexico
| | - PEDRO MAYORGA
- Department of Computer Science, Monterrey Institute of Technology and Higher Education Campus Cuernavaca, Autopista del Sol km 104, Xochitepec, Morelos 62790, Mexico
| | - EDGAR DANTAN
- Centro de Investigación en Biotecnología, Universidad Autónoma del Estado de Morelos, Avenida Universidad 1001, Cuernavaca, Morelos 62209, Mexico
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27
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Rekhi R, Qutub AA. Systems approaches for synthetic biology: a pathway toward mammalian design. Front Physiol 2013; 4:285. [PMID: 24130532 PMCID: PMC3793170 DOI: 10.3389/fphys.2013.00285] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2013] [Accepted: 09/19/2013] [Indexed: 01/08/2023] Open
Abstract
We review methods of understanding cellular interactions through computation in order to guide the synthetic design of mammalian cells for translational applications, such as regenerative medicine and cancer therapies. In doing so, we argue that the challenges of engineering mammalian cells provide a prime opportunity to leverage advances in computational systems biology. We support this claim systematically, by addressing each of the principal challenges to existing synthetic bioengineering approaches—stochasticity, complexity, and scale—with specific methods and paradigms in systems biology. Moreover, we characterize a key set of diverse computational techniques, including agent-based modeling, Bayesian network analysis, graph theory, and Gillespie simulations, with specific utility toward synthetic biology. Lastly, we examine the mammalian applications of synthetic biology for medicine and health, and how computational systems biology can aid in the continued development of these applications.
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Affiliation(s)
- Rahul Rekhi
- Department of Bioengineering, Rice University Houston, TX, USA
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28
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Martins TV, Evans MJ, Woolfenden HC, Morris RJ. Towards the Physics of Calcium Signalling in Plants. PLANTS (BASEL, SWITZERLAND) 2013; 2:541-88. [PMID: 27137393 PMCID: PMC4844391 DOI: 10.3390/plants2040541] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2013] [Revised: 09/17/2013] [Accepted: 09/22/2013] [Indexed: 12/21/2022]
Abstract
Calcium is an abundant element with a wide variety of important roles within cells. Calcium ions are inter- and intra-cellular messengers that are involved in numerous signalling pathways. Fluctuating compartment-specific calcium ion concentrations can lead to localised and even plant-wide oscillations that can regulate downstream events. Understanding the mechanisms that give rise to these complex patterns that vary both in space and time can be challenging, even in cases for which individual components have been identified. Taking a systems biology approach, mathematical and computational techniques can be employed to produce models that recapitulate experimental observations and capture our current understanding of the system. Useful models make novel predictions that can be investigated and falsified experimentally. This review brings together recent work on the modelling of calcium signalling in plants, from the scale of ion channels through to plant-wide responses to external stimuli. Some in silico results that have informed later experiments are highlighted.
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Affiliation(s)
- Teresa Vaz Martins
- Computational and Systems Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Matthew J Evans
- Computational and Systems Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Hugh C Woolfenden
- Computational and Systems Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Richard J Morris
- Computational and Systems Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK.
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29
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Schöneberg J, Noé F. ReaDDy--a software for particle-based reaction-diffusion dynamics in crowded cellular environments. PLoS One 2013; 8:e74261. [PMID: 24040218 PMCID: PMC3770580 DOI: 10.1371/journal.pone.0074261] [Citation(s) in RCA: 89] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2013] [Accepted: 08/02/2013] [Indexed: 12/14/2022] Open
Abstract
We introduce the software package ReaDDy for simulation of detailed spatiotemporal mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with particle resolution. In contrast to other particle-based reaction kinetics programs, ReaDDy supports particle interaction potentials. This permits effects such as space exclusion, molecular crowding and aggregation to be modeled. The biomolecules simulated can be represented as a sphere, or as a more complex geometry such as a domain structure or polymer chain. ReaDDy bridges the gap between small-scale but highly detailed molecular dynamics or Brownian dynamics simulations and large-scale but little-detailed reaction kinetics simulations. ReaDDy has a modular design that enables the exchange of the computing core by efficient platform-specific implementations or dynamical models that are different from Brownian dynamics.
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30
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Feig M, Sugita Y. Reaching new levels of realism in modeling biological macromolecules in cellular environments. J Mol Graph Model 2013; 45:144-56. [PMID: 24036504 DOI: 10.1016/j.jmgm.2013.08.017] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2013] [Revised: 08/14/2013] [Accepted: 08/19/2013] [Indexed: 12/21/2022]
Abstract
An increasing number of studies are aimed at modeling cellular environments in a comprehensive and realistic fashion. A major challenge in these efforts is how to bridge spatial and temporal scales over many orders of magnitude. Furthermore, there are additional challenges in integrating different aspects ranging from questions about biomolecular stability in crowded environments to the description of reactive processes on cellular scales. In this review, recent studies with models of biomolecules in cellular environments at different levels of detail are discussed in terms of their strengths and weaknesses. In particular, atomistic models, implicit representations of cellular environments, coarse-grained and spheroidal models of biomolecules, as well as the inclusion of reactive processes via reaction-diffusion models are described. Furthermore, strategies for integrating the different models into a comprehensive description of cellular environments are discussed.
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Affiliation(s)
- Michael Feig
- Department of Biochemistry & Molecular Biology and Department of Chemistry, Michigan State University, 603 Wilson Road, BCH 218, East Lansing, MI 48824, United States; RIKEN Quantitative Biology Center, International Medical Device Alliance (IMDA) 6F, 1-6-5 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
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31
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32
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Klann M, Koeppl H. Reaction schemes, escape times and geminate recombinations in particle-based spatial simulations of biochemical reactions. Phys Biol 2013; 10:046005. [DOI: 10.1088/1478-3975/10/4/046005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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33
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Ibrahim B, Henze R, Gruenert G, Egbert M, Huwald J, Dittrich P. Spatial rule-based modeling: a method and its application to the human mitotic kinetochore. Cells 2013; 2:506-44. [PMID: 24709796 PMCID: PMC3972674 DOI: 10.3390/cells2030506] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2013] [Revised: 06/05/2013] [Accepted: 06/25/2013] [Indexed: 12/23/2022] Open
Abstract
A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models.
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Affiliation(s)
- Bashar Ibrahim
- Bio Systems Analysis Group, Institute of Computer Science, Jena Centre for Bioinformatics and Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, D-0007743 Jena, Germany.
| | - Richard Henze
- Bio Systems Analysis Group, Institute of Computer Science, Jena Centre for Bioinformatics and Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, D-0007743 Jena, Germany.
| | - Gerd Gruenert
- Bio Systems Analysis Group, Institute of Computer Science, Jena Centre for Bioinformatics and Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, D-0007743 Jena, Germany.
| | - Matthew Egbert
- Bio Systems Analysis Group, Institute of Computer Science, Jena Centre for Bioinformatics and Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, D-0007743 Jena, Germany.
| | - Jan Huwald
- Bio Systems Analysis Group, Institute of Computer Science, Jena Centre for Bioinformatics and Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, D-0007743 Jena, Germany.
| | - Peter Dittrich
- Bio Systems Analysis Group, Institute of Computer Science, Jena Centre for Bioinformatics and Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, D-0007743 Jena, Germany.
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Geyer T. Modeling metabolic processes between molecular and systems biology. Curr Opin Struct Biol 2013; 23:218-23. [DOI: 10.1016/j.sbi.2012.12.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2012] [Accepted: 12/03/2012] [Indexed: 10/27/2022]
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