Rapid creation, Monte Carlo simulation, and visualization of realistic 3D cell models

Cell4D: a general purpose spatial stochastic simulator for cellular pathways

BACKGROUND

With the generation of vast compendia of biological datasets, the challenge is how best to interpret 'omics data alongside biochemical and other small-scale experiments to gain meaningful biological insights. Key to this challenge are computational methods that enable domain-users to generate novel hypotheses that can be used to guide future experiments. Of particular interest are flexible modeling platforms, capable of simulating a diverse range of biological systems with low barriers of adoption to those with limited computational expertise.

RESULTS

We introduce Cell4D, a spatial-temporal modeling platform combining a robust simulation engine with integrated graphics visualization, a model design editor, and an underlying XML data model capable of capturing a variety of cellular functions. Cell4D provides an interactive visualization mode, allowing intuitive feedback on model behavior and exploration of novel hypotheses, together with a non-graphics mode, compatible with high performance cloud compute solutions, to facilitate generation of statistical data. To demonstrate the flexibility and effectiveness of Cell4D, we investigate the dynamics of CEACAM1 localization in T-cell activation. We confirm the importance of Ca2+ microdomains in activating calmodulin and highlight a key role of activated calmodulin on the surface expression of CEACAM1. We further show how lymphocyte-specific protein tyrosine kinase can help regulate this cell surface expression and exploit spatial modeling features of Cell4D to test the hypothesis that lipid rafts regulate clustering of CEACAM1 to promote trans-binding to neighbouring cells.

CONCLUSIONS

Through demonstrating its ability to test and generate hypotheses, Cell4D represents an effective tool to help integrate knowledge across diverse, large and small-scale datasets.

A roadmap for translational cancer glycoimmunology at single cell resolution

Cancer cells can evade immune responses by exploiting inhibitory immune checkpoints. Immune checkpoint inhibitor (ICI) therapies based on anti-CTLA-4 and anti-PD-1/PD-L1 antibodies have been extensively explored over the recent years to unleash otherwise compromised anti-cancer immune responses. However, it is also well established that immune suppression is a multifactorial process involving an intricate crosstalk between cancer cells and the immune systems. The cancer glycome is emerging as a relevant source of immune checkpoints governing immunosuppressive behaviour in immune cells, paving an avenue for novel immunotherapeutic options. This review addresses the current state-of-the-art concerning the role played by glycans controlling innate and adaptive immune responses, while shedding light on available experimental models for glycoimmunology. We also emphasize the tremendous progress observed in the development of humanized models for immunology, the paramount contribution of advances in high-throughput single-cell analysis in this context, and the importance of including predictive machine learning algorithms in translational research. This may constitute an important roadmap for glycoimmunology, supporting careful adoption of models foreseeing clinical translation of fundamental glycobiology knowledge towards next generation immunotherapies.

A stochastic simulation of skeletal muscle calcium transients in a structurally realistic sarcomere model using MCell

Skeletal muscle contraction is initiated when an action potential triggers the release of Ca2+ into the sarcomere in a process referred to as excitation-contraction coupling. The speed and scale of this process makes direct observation very challenging and invasive. To determine how the concentration of Ca2+ changes within the myofibril during a single activation, several simulation models have been developed. These models follow a common pattern; divide the half sarcomere into a series of compartments, then use ordinary differential equations to solve reactions occurring within and between the compartments. To further develop this type of simulation, we have created a realistic structural model of a skeletal muscle myofibrillar half-sarcomere using MCell software that incorporates the myofilament lattice structure. Using this simulation model, we were successful in reproducing the averaged calcium transient during a single activation consistent with both the experimental and previous simulation results. In addition, our simulation demonstrated that the inclusion of the myofilament lattice within our model produced an asymmetric distribution of Ca2+, with more Ca2+ accumulating near the Z-disk and less Ca2+ reaching the m-line. This asymmetric distribution of Ca2+ is also apparent when we examine how the Ca2+ are bound to the troponin-C proteins along the actin filaments. Our simulation model also allowed us to produce advanced visualizations of this process, including two simulation animations, allowing us to view Ca2+ release, diffusion, binding and uptake within the myofibrillar half-sarcomere.

The Interplay of Structural and Cellular Biophysics Controls Clustering of Multivalent Molecules

Dynamic molecular clusters are assembled through weak multivalent interactions and are platforms for cellular functions, especially receptor-mediated signaling. Clustering is also a prerequisite for liquid-liquid phase separation. It is not well understood, however, how molecular structure and cellular organization control clustering. Using coarse-grained kinetic Langevin dynamics, we performed computational experiments on a prototypical ternary system modeled after membrane-bound nephrin, the adaptor Nck1, and the actin nucleation promoting factor NWASP. Steady-state cluster size distributions favored stoichiometries that optimized binding (stoichiometry matching) but still were quite broad. At high concentrations, the system can be driven beyond the saturation boundary such that cluster size is limited only by the number of available molecules. This behavior would be predictive of phase separation. Domains close to binding sites sterically inhibited clustering much less than terminal domains because the latter effectively restrict access to the cluster interior. Increased flexibility of interacting molecules diminished clustering by shielding binding sites within compact conformations. Membrane association of nephrin increased the cluster size distribution in a density-dependent manner. These properties provide insights into how molecular ensembles function to localize and amplify cell signaling.

Heterogeneities in Axonal Structure and Transporter Distribution Lower Dopamine Reuptake Efficiency

Efficient clearance of dopamine (DA) from the synapse is key to regulating dopaminergic signaling. This role is fulfilled by DA transporters (DATs). Recent advances in the structural characterization of DAT from Drosophila (dDAT) and in high-resolution imaging of DA neurons and the distribution of DATs in living cells now permit us to gain a mechanistic understanding of DA reuptake events in silico. Using electron microscopy images and immunofluorescence of transgenic knock-in mouse brains that express hemagglutinin-tagged DAT in DA neurons, we reconstructed a realistic environment for MCell simulations of DA reuptake, wherein the identity, population and kinetics of homology-modeled human DAT (hDAT) substates were derived from molecular simulations. The complex morphology of axon terminals near active zones was observed to give rise to large variations in DA reuptake efficiency, and thereby in extracellular DA density. Comparison of the effect of different firing patterns showed that phasic firing would increase the probability of reaching local DA levels sufficiently high to activate low-affinity DA receptors, mainly owing to high DA levels transiently attained during the burst phase. The experimentally observed nonuniform surface distribution of DATs emerged as a major modulator of DA signaling: reuptake was slower, and the peaks/width of transient DA levels were sharper/wider under nonuniform distribution of DATs, compared with uniform. Overall, the study highlights the importance of accurate descriptions of extrasynaptic morphology, DAT distribution, and conformational kinetics for quantitative evaluation of dopaminergic transmission and for providing deeper understanding of the mechanisms that regulate DA transmission.

A Computational Modeling and Simulation Approach to Investigate Mechanisms of Subcellular cAMP Compartmentation

Subcellular compartmentation of the ubiquitous second messenger cAMP has been widely proposed as a mechanism to explain unique receptor-dependent functional responses. How exactly compartmentation is achieved, however, has remained a mystery for more than 40 years. In this study, we developed computational and mathematical models to represent a subcellular sarcomeric space in a cardiac myocyte with varying detail. We then used these models to predict the contributions of various mechanisms that establish subcellular cAMP microdomains. We used the models to test the hypothesis that phosphodiesterases act as functional barriers to diffusion, creating discrete cAMP signaling domains. We also used the models to predict the effect of a range of experimentally measured diffusion rates on cAMP compartmentation. Finally, we modeled the anatomical structures in a cardiac myocyte diad, to predict the effects of anatomical diffusion barriers on cAMP compartmentation. When we incorporated experimentally informed model parameters to reconstruct an in silico subcellular sarcomeric space with spatially distinct cAMP production sites linked to caveloar domains, the models predict that under realistic conditions phosphodiesterases alone were insufficient to generate significant cAMP gradients. This prediction persisted even when combined with slow cAMP diffusion. When we additionally considered the effects of anatomic barriers to diffusion that are expected in the cardiac myocyte dyadic space, cAMP compartmentation did occur, but only when diffusion was slow. Our model simulations suggest that additional mechanisms likely contribute to cAMP gradients occurring in submicroscopic domains. The difference between the physiological and pathological effects resulting from the production of cAMP may be a function of appropriate compartmentation of cAMP signaling. Therefore, understanding the contribution of factors that are responsible for coordinating the spatial and temporal distribution of cAMP at the subcellular level could be important for developing new strategies for the prevention or treatment of unfavorable responses associated with different disease states.

Subcellular compartmentation of the ubiquitous second messenger cAMP has been widely proposed as a mechanism to explain how this one signaling molecule produces unique receptor-dependent functional responses. But, how exactly compartmentation occurs, is unknown. This is because there has been no way to measure the regulation and movement of cAMP in cells with intact subcellular structures. In this study, we applied novel computational approaches to predict whether PDE activity alone or in conjunction with restricted diffusion is sufficient to produce cAMP gradients in submicroscopic signaling domains. We also used the models to test the effect of a range of experimentally measured diffusion rates on cAMP compartmentation. Our simulations suggest that PDE activity alone is not sufficient to explain compartmentation, but if diffusion of cAMP is limited by potential factors such as molecular crowding, PKA buffering, and anatomical barriers, then compartmentation is predicted to occur.

Three-dimensional visualization of nanostructured surfaces and bacterial attachment using Autodesk® Maya®

There has been a growing interest in understanding the ways in which bacteria interact with nano-structured surfaces. As a result, there is a need for innovative approaches to enable researchers to visualize the biological processes taking place, despite the fact that it is not possible to directly observe these processes. We present a novel approach for the three-dimensional visualization of bacterial interactions with nano-structured surfaces using the software package Autodesk Maya. Our approach comprises a semi-automated stage, where actual surface topographic parameters, obtained using an atomic force microscope, are imported into Maya via a custom Python script, followed by a ‘creative stage', where the bacterial cells and their interactions with the surfaces are visualized using available experimental data. The ‘Dynamics' and ‘nDynamics' capabilities of the Maya software allowed the construction and visualization of plausible interaction scenarios. This capability provides a practical aid to knowledge discovery, assists in the dissemination of research results, and provides an opportunity for an improved public understanding. We validated our approach by graphically depicting the interactions between the two bacteria being used for modeling purposes, Staphylococcus aureus and Pseudomonas aeruginosa, with different titanium substrate surfaces that are routinely used in the production of biomedical devices.

An excess-calcium-binding-site model predicts neurotransmitter release at the neuromuscular junction

Despite decades of intense experimental studies, we still lack a detailed understanding of synaptic function. Fortunately, using computational approaches, we can obtain important new insights into the inner workings of these important neural systems. Here, we report the development of a spatially realistic computational model of an entire frog active zone in which we constrained model parameters with experimental data, and then used Monte Carlo simulation methods to predict the Ca(2+)-binding stoichiometry and dynamics that underlie neurotransmitter release. Our model reveals that 20-40 independent Ca(2+)-binding sites on synaptic vesicles, only a fraction of which need to bind Ca(2+) to trigger fusion, are sufficient to predict physiological release. Our excess-Ca(2+)-binding-site model has many functional advantages, agrees with recent data on synaptotagmin copy number, and is the first (to our knowledge) to link detailed physiological observations with the molecular machinery of Ca(2+)-triggered exocytosis. In addition, our model provides detailed microscopic insight into the underlying Ca(2+) dynamics during synapse activation.

Sharp Ca²⁺ nanodomains beneath the ribbon promote highly synchronous multivesicular release at hair cell synapses

Hair cell ribbon synapses exhibit several distinguishing features. Structurally, a dense body, or ribbon, is anchored to the presynaptic membrane and tethers synaptic vesicles; functionally, neurotransmitter release is dominated by large EPSC events produced by seemingly synchronous multivesicular release. However, the specific role of the synaptic ribbon in promoting this form of release remains elusive. Using complete ultrastructural reconstructions and capacitance measurements of bullfrog amphibian papilla hair cells dialyzed with high concentrations of a slow Ca²⁺ buffer (10 mM EGTA), we found that the number of synaptic vesicles at the base of the ribbon correlated closely to those vesicles that released most rapidly and efficiently, while the rest of the ribbon-tethered vesicles correlated to a second, slower pool of vesicles. Combined with the persistence of multivesicular release in extreme Ca²⁺ buffering conditions (10 mM BAPTA), our data argue against the Ca²⁺-dependent compound fusion of ribbon-tethered vesicles at hair cell synapses. Moreover, during hair cell depolarization, our results suggest that elevated Ca²⁺ levels enhance vesicle pool replenishment rates. Finally, using Ca²⁺ diffusion simulations, we propose that the ribbon and its vesicles define a small cytoplasmic volume where Ca²⁺ buffer is saturated, despite 10 mM BAPTA conditions. This local buffer saturation permits fast and large Ca²⁺ rises near release sites beneath the synaptic ribbon that can trigger multiquantal EPSCs. We conclude that, by restricting the available presynaptic volume, the ribbon may be creating conditions for the synchronous release of a small cohort of docked vesicles.

Spatial modeling of cell signaling networks

The shape of a cell, the sizes of subcellular compartments, and the spatial distribution of molecules within the cytoplasm can all control how molecules interact to produce a cellular behavior. This chapter describes how these spatial features can be included in mechanistic mathematical models of cell signaling. The Virtual Cell computational modeling and simulation software is used to illustrate the considerations required to build a spatial model. An explanation of how to appropriately choose between physical formulations that implicitly or explicitly account for cell geometry and between deterministic versus stochastic formulations for molecular dynamics is provided, along with a discussion of their respective strengths and weaknesses. As a first step toward constructing a spatial model, the geometry needs to be specified and associated with the molecules, reactions, and membrane flux processes of the network. Initial conditions, diffusion coefficients, velocities, and boundary conditions complete the specifications required to define the mathematics of the model. The numerical methods used to solve reaction-diffusion problems both deterministically and stochastically are then described and some guidance is provided in how to set up and run simulations. A study of cAMP signaling in neurons ends the chapter, providing an example of the insights that can be gained in interpreting experimental results through the application of spatial modeling.

Molecular diffusion model of neurotransmitter homeostasis around synapses supporting gradients

Neurotransmitter homeostasis in and around a synapse involves complex random processes such as diffusion, molecular binding, and uptake by glial transporters. A three-dimensional stochastic diffusion model of a synapse was developed to provide molecular-level details of neurotransmitter homeostasis not predicted by alternative models based on continuum approaches. The development was illustrated through an example case cortico-accumbens synapse that successfully integrated neuroadaptations observed after chronic cocaine. By incorporating cystine-glutamate exchanger as a nonsynaptic release site for glutamate, the stochastic model was used to quantify the relative contributions of synaptic and nonsynaptic sources to extracellular concentration and to estimate molecular influx rates into the perisynapse. A perturbation analysis showed that among the parameters considered, variation in surface density of glial transporters had the largest effect on glutamate concentrations. The stochastic diffusion model of the example synapse was further generalized to characterize glial morphology by studying the role of diffusion path length in supporting neurotransmitter gradients and isolating the synapse. For the same set of parameters, diffusion path length was found to be proportional to the gradient supported.

Effects of macromolecular crowding on intracellular diffusion from a single particle perspective

Compared to biochemical reactions taking place in relatively well-defined aqueous solutions in vitro, the corresponding reactions happening in vivo occur in extremely complex environments containing only 60-70% water by volume, with the remainder consisting of an undefined array of bio-molecules. In a biological setting, such extremely complex and volume-occupied solution environments are termed 'crowded'. Through a range of intermolecular forces and pseudo-forces, this complex background environment may cause biochemical reactions to behave differently to their in vitro counterparts. In this review, we seek to highlight how the complex background environment of the cell can affect the diffusion of substances within it. Engaging the subject from the perspective of a single particle's motion, we place the focus of our review on two areas: (1) experimental procedures for conducting single particle tracking experiments within cells along with methods for extracting information from these experiments; (2) theoretical factors affecting the translational diffusion of single molecules within crowded two-dimensional membrane and three-dimensional solution environments. We conclude by discussing a number of recent publications relating to intracellular diffusion in light of the reviewed material.