scholarly journals The Roles of Space and Stochasticity in Computational Simulations of Cellular Biochemistry: Quantitative Analysis and Qualitative Insights

2020 ◽  
Author(s):  
M. E. Johnson ◽  
A. Chen ◽  
J. R. Faeder ◽  
P. Henning ◽  
I. I. Moraru ◽  
...  
Keyword(s):  
Cell Biology ◽  
Computational Models ◽  
Computational Simulation ◽  
Three Dimensional ◽  
Building Blocks ◽  
Molecular Structures ◽  
Stochastic Methods ◽  
Specific Cell ◽  
Test Cases ◽  
Computational Approaches

ABSTRACTMost of the fascinating phenomena studied in cell biology emerge from interactions among highly organized multi-molecular structures and rapidly propagating molecular signals embedded into complex and frequently dynamic cellular morphologies. For the exploration of such systems, computational simulation has proved to be an invaluable tool, and many researchers in this field have developed sophisticated computational models for application to specific cell biological questions. However it is often difficult to reconcile conflicting computational results that use different simulation approaches (for example partial differential equations versus particle-based stochastic methods) to describe the same phenomenon. Moreover, the details of the computational implementation of any particular algorithm may give rise to quantitatively or even qualitatively different results for the same set of starting assumptions and parameters. In an effort to address this issue systematically, we have defined a series of computational test cases ranging from very simple (bimolecular binding in solution) to moderately complex (spatial and temporal oscillations generated by proteins binding to membranes) that represent building blocks for comprehensive three-dimensional models of cellular function. Having used two or more distinct computational approaches to solve each of these test cases with consistent parameter sets, we generally find modest but measurable differences in the solutions of the same problem, and a few cases where significant deviations arise. We discuss the strengths and limitations of commonly used computational approaches for exploring cell biological questions and provide a framework for decision-making by researchers wishing to develop new models for cell biology. As computational power and speed continue to increase at a remarkable rate, the dream of a fully comprehensive computational model of a living cell may be drawing closer to reality, but our analysis demonstrates that it will be crucial to evaluate the accuracy of such models critically and systematically.

scholarly journals Quantifying the Roles of Space and Stochasticity in Computer Simulations for Cell Biology and Cellular Biochemistry

2020 ◽  
pp. mbc.E20-08-0530
Author(s):  
M. E. Johnson ◽  
A. Chen ◽  
J. R. Faeder ◽  
P. Henning ◽  
I. I. Moraru ◽  
...  
Keyword(s):  
Cell Biology ◽  
Computational Models ◽  
Reaction Network ◽  
Molecular Structures ◽  
Specific Cell ◽  
Test Cases ◽  
Enzymatic Reactions ◽  
Invaluable Tool ◽  
Cellular Biochemistry ◽  
Reaction Speed

Most of the fascinating phenomena studied in cell biology emerge from interactions among highly organized multi-molecular structures embedded into complex and frequently dynamic cellular morphologies. For the exploration of such systems, computer simulation has proved to be an invaluable tool, and many researchers in this field have developed sophisticated computational models for application to specific cell biological questions. However, it is often difficult to reconcile conflicting computational results that use different approaches to describe the same phenomenon. To address this issue systematically, we have defined a series of computational test cases ranging from very simple to moderately complex, varying key features of dimensionality, reaction type, reaction speed, crowding, and cell size. We then quantified how explicit spatial and/or stochastic implementations alter outcomes, even when all methods use the same reaction network, rates, and concentrations. For simple cases we generally find minor differences in solutions of the same problem. However, we observe increasing discordance as the effects of localization, dimensionality reduction, and irreversible enzymatic reactions are combined. We discuss the strengths and limitations of commonly used computational approaches for exploring cell biological questions and provide a framework for decision-making by researchers developing new models. As computational power and speed continue to increase at a remarkable rate, the dream of a fully comprehensive computational model of a living cell may be drawing closer to reality, but our analysis demonstrates that it will be crucial to evaluate the accuracy of such models critically and systematically.

scholarly journals Computational Simulation of Fully Trimmed Flight of a Helicopter in Hover

2019 ◽  
Vol 26 (1) ◽  
pp. 175-181
Author(s):  
Wieńczysław Stalewski ◽  
Wiesław Zalewski ◽  
Katarzyna Surmacz ◽  
Maximilian Pulfer ◽  
Frieder Hirsch
Keyword(s):  
Computational Models ◽  
Computational Simulation ◽  
Three Dimensional ◽  
Rotor Blades ◽  
Navier Stokes ◽  
Ansys Fluent ◽  
Precise Adjustment ◽  
Flight Controls ◽  
Independent Parameters ◽  
Geometry And Kinematics

Abstract In trimmed flight of a helicopter, all the forces and moments, aerodynamic, inertial, and gravitational, are in balance. Keeping the helicopter in trimmed state, needs a precise adjustment of flight controls. The methodology of simulation of a fully trimmed flight of rotorcraft has been developed and applied to simulate hover of a helicopter. The presented approach is based on a solution of Unsteady Reynolds-Averaged Navier-Stokes (URANS) equations. In contrast to typical solutions of such problem, in the newly developed methodology, the flight controls corresponding to the trimmed-flight conditions are also determined based on the solution of URANS equations. The methodology is based on coupling of several computational models of Computational Fluid Dynamics and Flight Dynamic. The URANS equations are solved in a three-dimensional region surrounding the flying helicopter, using the ANSYS FLUENT code. The approach is truly three-dimensional, with truly modelled geometry and kinematics of main and tail rotor blades. This applies to modelling of blade flapping and lead-lag motion, too. The trimming procedure uses six independent parameters (i.e. collective and cyclic pitch of main rotor blades, collective pitch of tail rotor blades, pitch, and bank angles of a helicopter) that should be adjusted so as to balance all forces and moments acting on the helicopter. The detailed description of the developed methodology as well as the results of simulation of trimmed hover of the helicopter was presented.

scholarly journals Cryo-electron tomography: The challenge of doing structural biology in situ

2013 ◽  
Vol 202 (3) ◽  
pp. 407-419 ◽  
Author(s):  
Vladan Lučić ◽  
Alexander Rigort ◽  
Wolfgang Baumeister
Keyword(s):  
Cell Biology ◽  
Structural Information ◽  
Electron Tomography ◽  
Three Dimensional ◽  
Molecular Structures ◽  
New Techniques ◽  
Preparation Methods ◽  
Technical Advances ◽  
Macromolecular Organization

Electron microscopy played a key role in establishing cell biology as a discipline, by producing fundamental insights into cellular organization and ultrastructure. Many seminal discoveries were made possible by the development of new sample preparation methods and imaging modalities. Recent technical advances include sample vitrification that faithfully preserves molecular structures, three-dimensional imaging by electron tomography, and improved image-processing methods. These new techniques have enabled the extraction of high fidelity structural information and are beginning to reveal the macromolecular organization of unperturbed cellular environments.

scholarly journals An optical method to quantify the density of ligands for cell adhesion receptors in three-dimensional matrices

2010 ◽  
Vol 7 (suppl_5) ◽  
Author(s):  
Dimitrios S. Tzeranis ◽  
Amit Roy ◽  
Peter T. C. So ◽  
Ioannis V. Yannas
Keyword(s):  
Cell Adhesion ◽  
Cell Biology ◽  
Quantitative Description ◽  
Three Dimensional ◽  
Specific Cell ◽  
Adhesion Receptors ◽  
Cell Matrix ◽  
The Matrix ◽  
Cell Matrix Interactions ◽  
Cell Phenotypes

The three-dimensional matrix that surrounds cells is an important insoluble regulator of cell phenotypes. Examples of such insoluble surfaces are the extracellular matrix (ECM), ECM analogues and synthetic polymeric biomaterials. Cell–matrix interactions are mediated by cell adhesion receptors that bind to chemical entities (adhesion ligands) on the surface of the matrix. There are currently no established methods to obtain quantitative estimates of the density of adhesion ligands recognized by specific cell adhesion receptors. This article presents a new optical-based methodology for measuring ligands of adhesion receptors on three-dimensional matrices. The study also provides preliminary quantitative results for the density of adhesion ligands of integrins α 1 β 1 and α 2 β 1 on the surface of collagen-based scaffolds, similar to biomaterials that are used clinically to induce regeneration in injured skin and peripheral nerves. Preliminary estimates of the surface density of the ligands of these two major collagen-binding receptors are 5775 ± 2064 ligands µm −2 for ligands of α 1 β 1 and 17 084 ± 5353 ligands µm −2 for ligands of α 2 β 1 . The proposed methodology can be used to quantify the surface chemistry of insoluble surfaces that possess biological activity, such as native tissue ECM and biomaterials, and therefore can be used in cell biology, biomaterials science and regenerative medical studies for quantitative description of a matrix and its effects on cells.

scholarly journals Education Catching Up with Science: Preparing Students for Three-Dimensional Literacy in Cell Biology

2012 ◽  
Vol 11 (4) ◽  
pp. 437-447 ◽  
Author(s):  
IJsbrand M. Kramer ◽  
Hassen-Reda Dahmani ◽  
Pamina Delouche ◽  
Marissa Bidabe ◽  
Patricia Schneeberger
Keyword(s):  
Cell Biology ◽  
Three Dimensional ◽  
Data Bank ◽  
Molecular Structures ◽  
Control Group ◽  
Multiple Choice Questions ◽  
Semiotic System ◽  
Single Text ◽  
Comprehension Process ◽  
Cellular Components

The large number of experimentally determined molecular structures has led to the development of a new semiotic system in the life sciences, with increasing use of accurate molecular representations. To determine how this change impacts students’ learning, we incorporated image tests into our introductory cell biology course. Groups of students used a single text dealing with signal transduction, which was supplemented with images made in one of three iconographic styles. Typically, we employed realistic renderings, using computer-generated Protein Data Bank (PDB) structures; realistic-schematic renderings, using shapes inspired by PDB structures; or schematic renderings, using simple geometric shapes to represent cellular components. The control group received a list of keywords. When students were asked to draw and describe the process in their own style and to reply to multiple-choice questions, the three iconographic approaches equally improved the overall outcome of the tests (relative to keywords). Students found the three approaches equally useful but, when asked to select a preferred style, they largely favored a realistic-schematic style. When students were asked to annotate “raw” realistic images, both keywords and schematic representations failed to prepare them for this task. We conclude that supplementary images facilitate the comprehension process and despite their visual clutter, realistic representations do not hinder learning in an introductory course.

scholarly journals A Stochastic Spatiotemporal Model of Rat Ventricular Myocyte Calcium Dynamics Demonstrated Necessary Features for Calcium Wave Propagation

Membranes ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 989
Author(s):  
Tuan Minh Hoang-Trong ◽  
Aman Ullah ◽  
William Jonathan Lederer ◽  
Mohsin Saleet Jafri
Keyword(s):  
Computational Model ◽  
Cell Biology ◽  
Computational Models ◽  
Calcium Release ◽  
Ryanodine Receptors ◽  
Three Dimensional ◽  
Ionic Currents ◽  
Cardiac Contraction ◽  
Calcium Dynamics ◽  
Deterministic Models

Calcium (Ca2+) plays a central role in the excitation and contraction of cardiac myocytes. Experiments have indicated that calcium release is stochastic and regulated locally suggesting the possibility of spatially heterogeneous calcium levels in the cells. This spatial heterogeneity might be important in mediating different signaling pathways. During more than 50 years of computational cell biology, the computational models have been advanced to incorporate more ionic currents, going from deterministic models to stochastic models. While periodic increases in cytoplasmic Ca2+ concentration drive cardiac contraction, aberrant Ca2+ release can underly cardiac arrhythmia. However, the study of the spatial role of calcium ions has been limited due to the computational expense of using a three-dimensional stochastic computational model. In this paper, we introduce a three-dimensional stochastic computational model for rat ventricular myocytes at the whole-cell level that incorporate detailed calcium dynamics, with (1) non-uniform release site placement, (2) non-uniform membrane ionic currents and membrane buffers, (3) stochastic calcium-leak dynamics and (4) non-junctional or rogue ryanodine receptors. The model simulates spark-induced spark activation and spark-induced Ca2+ wave initiation and propagation that occur under conditions of calcium overload at the closed-cell condition, but not when Ca2+ levels are normal. This is considered important since the presence of Ca2+ waves contribute to the activation of arrhythmogenic currents.

Exploration of cell wall architecture with the rapid-freeze deep-etch technique

1993 ◽  
Vol 51 ◽  
pp. 128-129
Author(s):  
Béatrice Satiat-Jeunemaitre ◽  
Chris Hawes
Keyword(s):  
Plant Cell ◽  
Cell Walls ◽  
Cell Biology ◽  
Molecular Model ◽  
Three Dimensional ◽  
Secretory Activity ◽  
Wall Structure ◽  
Specimen Preparation ◽  
Molecular Architecture ◽  
Plant Cell Walls

The comprehension of the molecular architecture of plant cell walls is one of the best examples in cell biology which illustrates how developments in microscopy have extended the frontiers of a topic. Indeed from the first electron microscope observation of cell walls it has become apparent that our understanding of wall structure has advanced hand in hand with improvements in the technology of specimen preparation for electron microscopy. Cell walls are sub-cellular compartments outside the peripheral plasma membrane, the construction of which depends on a complex cellular biosynthetic and secretory activity (1). They are composed of interwoven polymers, synthesised independently, which together perform a number of varied functions. Biochemical studies have provided us with much data on the varied molecular composition of plant cell walls. However, the detailed intermolecular relationships and the three dimensional arrangement of the polymers in situ remains a mystery. The difficulty in establishing a general molecular model for plant cell walls is also complicated by the vast diversity in wall composition among plant species.

Factors Affecting Molecular Self-Assembly and Its Mechanism

2012 ◽  
Vol 9 (1) ◽  
pp. 43 ◽  
Author(s):  
Hueyling Tan
Keyword(s):  
Self Assembly ◽  
Building Blocks ◽  
Molecular Engineering ◽  
Molecular Structures ◽  
Polymer Science ◽  
New Approach ◽  
Factors Affecting ◽  
Dna Structures ◽  
Self Assembling ◽  
Wide Range

Molecular self-assembly is ubiquitous in nature and has emerged as a new approach to produce new materials in chemistry, engineering, nanotechnology, polymer science and materials. Molecular self-assembly has been attracting increasing interest from the scientific community in recent years due to its importance in understanding biology and a variety of diseases at the molecular level. In the last few years, considerable advances have been made in the use ofpeptides as building blocks to produce biological materials for wide range of applications, including fabricating novel supra-molecular structures and scaffolding for tissue repair. The study ofbiological self-assembly systems represents a significant advancement in molecular engineering and is a rapidly growing scientific and engineering field that crosses the boundaries ofexisting disciplines. Many self-assembling systems are rangefrom bi- andtri-block copolymers to DNA structures as well as simple and complex proteins andpeptides. The ultimate goal is to harness molecular self-assembly such that design andcontrol ofbottom-up processes is achieved thereby enabling exploitation of structures developed at the meso- and macro-scopic scale for the purposes oflife and non-life science applications. Such aspirations can be achievedthrough understanding thefundamental principles behind the selforganisation and self-synthesis processes exhibited by biological systems.

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