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      3D mesh processing using GAMer 2 to enable reaction-diffusion simulations in realistic cellular geometries

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          Abstract

          Recent advances in electron microscopy have enabled the imaging of single cells in 3D at nanometer length scale resolutions. An uncharted frontier for in silico biology is the ability to simulate cellular processes using these observed geometries. Enabling such simulations requires watertight meshing of electron micrograph images into 3D volume meshes, which can then form the basis of computer simulations of such processes using numerical techniques such as the finite element method. In this paper, we describe the use of our recently rewritten mesh processing software, GAMer 2, to bridge the gap between poorly conditioned meshes generated from segmented micrographs and boundary marked tetrahedral meshes which are compatible with simulation. We demonstrate the application of a workflow using GAMer 2 to a series of electron micrographs of neuronal dendrite morphology explored at three different length scales and show that the resulting meshes are suitable for finite element simulations. This work is an important step towards making physical simulations of biological processes in realistic geometries routine. Innovations in algorithms to reconstruct and simulate cellular length scale phenomena based on emerging structural data will enable realistic physical models and advance discovery at the interface of geometry and cellular processes. We posit that a new frontier at the intersection of computational technologies and single cell biology is now open.

          Author summary

          3D imaging of cellular components and associated reconstruction methods have made great strides in the past decade, opening windows into the complex intracellular organization. These advances also mean that computational tools need to be developed to work with these images not just for purposes of visualization but also for biophysical simulations. In this work, we present our recently rewritten mesh processing software, GAMer 2, which features both mesh conditioning algorithms and tools to support simulation setup including boundary marking. Using a workflow that consists of other open-source software along with GAMer 2, we demonstrate the process of going from electron micrographs to simulations for several scenes of increasing length scales. In our preliminary finite element simulations of reaction-diffusion in the generated geometries, we reaffirm that the complex morphology of the cell can impact processes such as signaling. Technologies such as these presented here are set to enable a new frontier in biophysical simulations in realistic geometries.

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          Most cited references63

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          Mechanisms determining the morphology of the peripheral ER.

          The endoplasmic reticulum (ER) consists of the nuclear envelope and a peripheral network of tubules and membrane sheets. The tubules are shaped by the curvature-stabilizing proteins reticulons and DP1/Yop1p, but how the sheets are formed is unclear. Here, we identify several sheet-enriched membrane proteins in the mammalian ER, including proteins that translocate and modify newly synthesized polypeptides, as well as coiled-coil membrane proteins that are highly upregulated in cells with proliferated ER sheets, all of which are localized by membrane-bound polysomes. These results indicate that sheets and tubules correspond to rough and smooth ER, respectively. One of the coiled-coil proteins, Climp63, serves as a "luminal ER spacer" and forms sheets when overexpressed. More universally, however, sheet formation appears to involve the reticulons and DP1/Yop1p, which localize to sheet edges and whose abundance determines the ratio of sheets to tubules. These proteins may generate sheets by stabilizing the high curvature of edges. Copyright © 2010 Elsevier Inc. All rights reserved.
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            • Record: found
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            • Article: not found

            The postsynaptic organization of synapses.

            The postsynaptic side of the synapse is specialized to receive the neurotransmitter signal released from the presynaptic terminal and transduce it into electrical and biochemical changes in the postsynaptic cell. The cardinal functional components of the postsynaptic specialization of excitatory and inhibitory synapses are the ionotropic receptors (ligand-gated channels) for glutamate and γ-aminobutyric acid (GABA), respectively. These receptor channels are concentrated at the postsynaptic membrane and embedded in a dense and rich protein network comprised of anchoring and scaffolding molecules, signaling enzymes, cytoskeletal components, as well as other membrane proteins. Excitatory and inhibitory postsynaptic specializations are quite different in molecular organization. The postsynaptic density of excitatory synapses is especially complex and dynamic in composition and regulation; it contains hundreds of different proteins, many of which are required for cognitive function and implicated in psychiatric illness.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Serial section scanning electron microscopy of adult brain tissue using focused ion beam milling.

                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Visualization
                Role: ConceptualizationRole: Funding acquisitionRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                April 2020
                6 April 2020
                : 16
                : 4
                : e1007756
                Affiliations
                [1 ] Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla, California, United States of America
                [2 ] Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California, United States of America
                [3 ] Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California, United States of America
                [4 ] Department of Mathematics, University of California, San Diego, La Jolla, California, United States of America
                Inria, FRANCE
                Author notes

                I have read the journals policy and the authors of this manuscript have the following competing interests: R.E.A. has equity interest in, is a cofounder of, and on the scientific advisory board of Actavalon, Inc.

                Author information
                http://orcid.org/0000-0002-0670-2308
                http://orcid.org/0000-0001-8229-9760
                http://orcid.org/0000-0001-6052-2976
                http://orcid.org/0000-0002-9275-9553
                http://orcid.org/0000-0002-3064-4697
                http://orcid.org/0000-0001-5953-4347
                Article
                PCOMPBIOL-D-19-01230
                10.1371/journal.pcbi.1007756
                7162555
                32251448
                1334e10a-5375-47ea-8a74-d30618bdbf6e
                © 2020 Lee et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 July 2019
                : 1 March 2020
                Page count
                Figures: 13, Tables: 2, Pages: 35
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: P41-GM103426
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: RO1-GM31749
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: T32-GM008326
                Funded by: funder-id http://dx.doi.org/10.13039/100000121, Division of Mathematical Sciences;
                Award ID: DMS-CM1620366
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000121, Division of Mathematical Sciences;
                Award ID: DMS-FRG1262982
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000181, Air Force Office of Scientific Research;
                Award ID: FA9550-18-1-0051
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100006792, Hartwell Foundation;
                Award ID: Postdoctoral Fellowship
                Award Recipient :
                CTL, REA, JAM, and MH are supported in part by the National Institutes of Health ( https://www.nih.gov) under grant number P41-GM103426. CTL, and JAM are also supported by the National Institutes of Health ( https://www.nih.gov) under RO1-GM31749. CTL also acknowledges support from the National institutes of Health ( https://www.nih.gov) Molecular Biophysics Training Grant T32-GM008326 and a Hartwell Foundation Postdoctoral Fellowship. RR was supported in part by the Ronald L. Graham endowed chair. MH was supported in part by the National Science Foundation ( https://www.nsf.gov) under awards DMS-CM1620366 and DMS-FRG1262982. PR was supported by the Air Force Office of Scientific Research (AFOSR, https://www.wpafb.af.mil/afrl/afosr/) Multidisciplinary University Research Initiative (MURI) FA9550-18-1-0051 and JGL was supported by a fellowship from the UCSD Center for Transscale Structural Biology and Biophysics/Virtual Molecular Cell Consortium ( https://vmcc.ucsd.edu/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Physical Sciences
                Mathematics
                Geometry
                Curvature
                Biology and Life Sciences
                Cell Biology
                Cellular Structures and Organelles
                Cell Membranes
                Physical Sciences
                Mathematics
                Applied Mathematics
                Finite Element Analysis
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Biology and Life Sciences
                Biophysics
                Biophysical Simulations
                Physical Sciences
                Physics
                Biophysics
                Biophysical Simulations
                Biology and Life Sciences
                Computational Biology
                Biophysical Simulations
                Research and Analysis Methods
                Microscopy
                Electron Microscopy
                Biology and Life Sciences
                Cell Biology
                Cellular Structures and Organelles
                Endoplasmic Reticulum
                Biology and Life Sciences
                Cell Biology
                Cell Processes
                Secretory Pathway
                Endoplasmic Reticulum
                Research and Analysis Methods
                Simulation and Modeling
                Custom metadata
                vor-update-to-uncorrected-proof
                2020-04-16
                The latest GAMer 2 code can be found on GitHub https://github.com/ctlee/gamer. Snapshots of GAMer 2 are also archived on Zenodo https://doi.org/10.5281/zenodo.2340294. High resolution versions of supplemental movies and meshes can be found at https://github.com/RangamaniLabUCSD/Lee-Laughlin-GAMer2. The EM data used in this work are from Wu, Y.; Whiteus, C.; Xu, C. S.; Hayworth, K. J.; Weinberg, R. J.; Hess, H. F.; Camilli, P. D. Contacts between the Endoplasmic Reticulum and Other Membranes in Neurons. PNAS 2017, 114 (24), E4859–E4867. https://doi.org/10.1073/pnas.1701078114. The original EM datasets are available by request from the corresponding author of this work, Pietro de Camilli ( Pietro.decamilli@ 123456yale.edu ), as pursuant to PNAS data availability guidelines.

                Quantitative & Systems biology
                Quantitative & Systems biology

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