Modeling capping protein FRAP and CALI experiments reveals in vivo regulation of actin dynamics

Fluorescence Recovery after Photobleaching in Colloidal Science: Introduction and Application

FRAP (fluorescence recovery after photo bleaching) is a method for determining diffusion in material science. In industrial applications such as medications, foods, Medtech, hygiene, and textiles, the diffusion process has a substantial influence on the overall qualities of goods. All these complex and heterogeneous systems have diffusion-based processes at the local level. FRAP is a fluorescence-based approach for detecting diffusion; in this method, a high-intensity laser is made for a brief period and then applied to the samples, bleaching the fluorescent chemical inside the region, which is subsequently filled up by natural diffusion. This brief Review will focus on the existing research on employing FRAP to measure colloidal system heterogeneity and explore diffusion into complicated structures. This description of FRAP will be followed by a discussion of how FRAP is intended to be used in colloidal science. When constructing the current Review, the most recent publications were reviewed for this assessment. Because of the large number of FRAP articles in colloidal research, there is currently a dearth of knowledge regarding the growth of FRAP's significance to colloidal science. Colloids make up only 2% of FRAP papers, according to ISI Web of Knowledge.

Model of turnover kinetics in the lamellipodium: implications of slow- and fast- diffusing capping protein and Arp2/3 complex

Cell protrusion through polymerization of actin filaments at the leading edge of motile cells may be influenced by spatial gradients of diffuse actin and regulators. Here we study the distribution of two of the most important regulators, capping protein and Arp2/3 complex, which regulate actin polymerization in the lamellipodium through capping and nucleation of free barbed ends. We modeled their kinetics using data from prior single molecule microscopy experiments on XTC cells. These experiments have provided evidence for a broad distribution of diffusion coefficients of both capping protein and Arp2/3 complex. The slowly diffusing proteins appear as extended 'clouds' while proteins bound to the actin filament network appear as speckles that undergo retrograde flow. Speckle appearance and disappearance events correspond to assembly and dissociation from the actin filament network and speckle lifetimes correspond to the dissociation rate. The slowly diffusing capping protein could represent severed capped actin filament fragments or membrane-bound capping protein. Prior evidence suggests that slowly diffusing Apr2/3 complex associates with the membrane. We use the measured rates and estimates of diffusion coefficients of capping protein and Arp2/3 complex in a Monte Carlo simulation that includes particles in association with a filament network and diffuse in the cytoplasm. We consider two separate pools of diffuse proteins, representing fast and slowly diffusing species. We find a steady state with concentration gradients involving a balance of diffusive flow of fast and slow species with retrograde flow. We show that simulations of FRAP are consistent with prior experiments performed on different cell types. We provide estimates for the ratio of bound to diffuse complexes and calculate conditions where Arp2/3 complex recycling by diffusion may become limiting. We discuss the implications of slowly diffusing populations and suggest experiments to distinguish among mechanisms that influence long range transport.

Simultaneous quantification of actin monomer and filament dynamics with modeling-assisted analysis of photoactivation

Photoactivation allows one to pulse-label molecules and obtain quantitative data about their behavior. We have devised a new modeling-based analysis for photoactivatable actin experiments that simultaneously measures properties of monomeric and filamentous actin in a three-dimensional cellular environment. We use this method to determine differences in the dynamic behavior of β- and γ-actin isoforms, showing that both inhabit filaments that depolymerize at equal rates but that β-actin exists in a higher monomer-to-filament ratio. We also demonstrate that cofilin (cofilin 1) equally accelerates depolymerization of filaments made from both isoforms, but is only required to maintain the β-actin monomer pool. Finally, we used modeling-based analysis to assess actin dynamics in axon-like projections of differentiating neuroblastoma cells, showing that the actin monomer concentration is significantly depleted as the axon develops. Importantly, these results would not have been obtained using traditional half-time analysis. Given that parameters of the publicly available modeling platform can be adjusted to suit the experimental system of the user, this method can easily be used to quantify actin dynamics in many different cell types and subcellular compartments.

There is more than one way to model an elephant. Experiment-driven modeling of the actin cytoskeleton

Mathematical modeling has established its value for investigating the interplay of biochemical and mechanical mechanisms underlying actin-based motility. Because of the complex nature of actin dynamics and its regulation, many of these models are phenomenological or conceptual, providing a general understanding of the physics at play. But the wealth of carefully measured kinetic data on the interactions of many of the players in actin biochemistry cries out for the creation of more detailed and accurate models that could permit investigators to dissect interdependent roles of individual molecular components. Moreover, no human mind can assimilate all of the mechanisms underlying complex protein networks; so an additional benefit of a detailed kinetic model is that the numerous binding proteins, signaling mechanisms, and biochemical reactions can be computationally organized in a fully explicit, accessible, visualizable, and reusable structure. In this review, we will focus on how comprehensive and adaptable modeling allows investigators to explain experimental observations and develop testable hypotheses on the intracellular dynamics of the actin cytoskeleton.

Distributed actin turnover in the lamellipodium and FRAP kinetics

Studies of actin dynamics at the leading edge of motile cells with single-molecule speckle (SiMS) microscopy have shown a broad distribution of EGFP-actin speckle lifetimes and indicated actin polymerization and depolymerization over an extended region. Other experiments using FRAP with the same EGFP-actin as a probe have suggested, by contrast, that polymerization occurs exclusively at the leading edge. We performed FRAP experiments on XTC cells to compare SiMS to FRAP on the same cell type. We used speckle statistics obtained by SiMS to model the steady-state distribution and kinetics of actin in the lamellipodium. We demonstrate that a model with a single diffuse actin species is in good agreement with FRAP experiments. A model including two species of diffuse actin provides an even better agreement. The second species consists of slowly diffusing oligomers that associate to the F-actin network throughout the lamellipodium or break up into monomers after a characteristic time. Our work motivates studies to test the presence and composition of slowly diffusing actin species that may contribute to local remodeling of the actin network and increase the amount of soluble actin.

Stoichiometry of Nck-dependent actin polymerization in living cells

Regulation of actin dynamics through the Nck/N-WASp (neural Wiskott-Aldrich syndrome protein)/Arp2/3 pathway is essential for organogenesis, cell invasiveness, and pathogen infection. Although many of the proteins involved in this pathway are known, the detailed mechanism by which it functions remains undetermined. To examine the signaling mechanism, we used a two-pronged strategy involving computational modeling and quantitative experimentation. We developed predictions for Nck-dependent actin polymerization using the Virtual Cell software system. In addition, we used antibody-induced aggregation of membrane-targeted Nck SH3 domains to test these predictions and to determine how the number of molecules in Nck aggregates and the density of aggregates affected localized actin polymerization in living cells. Our results indicate that the density of Nck molecules in aggregates is a critical determinant of actin polymerization. Furthermore, results from both computational simulations and experimentation support a model in which the Nck/N-WASp/Arp2/3 stoichiometry is 4:2:1. These results provide new insight into activities involving localized actin polymerization, including tumor cell invasion, microbial pathogenesis, and T cell activation.

Advanced fluorescence microscopy techniques--FRAP, FLIP, FLAP, FRET and FLIM

Fluorescence microscopy provides an efficient and unique approach to study fixed and living cells because of its versatility, specificity, and high sensitivity. Fluorescence microscopes can both detect the fluorescence emitted from labeled molecules in biological samples as images or photometric data from which intensities and emission spectra can be deduced. By exploiting the characteristics of fluorescence, various techniques have been developed that enable the visualization and analysis of complex dynamic events in cells, organelles, and sub-organelle components within the biological specimen. The techniques described here are fluorescence recovery after photobleaching (FRAP), the related fluorescence loss in photobleaching (FLIP), fluorescence localization after photobleaching (FLAP), Förster or fluorescence resonance energy transfer (FRET) and the different ways how to measure FRET, such as acceptor bleaching, sensitized emission, polarization anisotropy, and fluorescence lifetime imaging microscopy (FLIM). First, a brief introduction into the mechanisms underlying fluorescence as a physical phenomenon and fluorescence, confocal, and multiphoton microscopy is given. Subsequently, these advanced microscopy techniques are introduced in more detail, with a description of how these techniques are performed, what needs to be considered, and what practical advantages they can bring to cell biological research.

Growth cone travel in space and time: the cellular ensemble of cytoskeleton, adhesion, and membrane

Growth cones, found at the tip of axonal projections, are the sensory and motile organelles of developing neurons that enable axon pathfinding and target recognition for precise wiring of the neural circuitry. To date, many families of conserved guidance molecules and their corresponding receptors have been identified that work in space and time to ensure billions of axons to reach their targets. Research in the past two decades has also gained significant insight into the ways in which growth cones translate extracellular signals into directional migration. This review aims to examine new progress toward understanding the cellular mechanisms underlying directional motility of the growth cone and to discuss questions that remain to be addressed. Specifically, we will focus on the cellular ensemble of cytoskeleton, adhesion, and membrane and examine how the intricate interplay between these processes orchestrates the directed movement of growth cones.

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.

Assessment of cellular mechanisms contributing to cAMP compartmentalization in pulmonary microvascular endothelial cells

Cyclic AMP signals encode information required to differentially regulate a wide variety of cellular responses; yet it is not well understood how information is encrypted within these signals. An emerging concept is that compartmentalization underlies specificity within the cAMP signaling pathway. This concept is based on a series of observations indicating that cAMP levels are distinct in different regions of the cell. One such observation is that cAMP production at the plasma membrane increases pulmonary microvascular endothelial barrier integrity, whereas cAMP production in the cytosol disrupts barrier integrity. To better understand how cAMP signals might be compartmentalized, we have developed mathematical models in which cellular geometry as well as total adenylyl cyclase and phosphodiesterase activities were constrained to approximate values measured in pulmonary microvascular endothelial cells. These simulations suggest that the subcellular localizations of adenylyl cyclase and phosphodiesterase activities are by themselves insufficient to generate physiologically relevant cAMP gradients. Thus, the assembly of adenylyl cyclase, phosphodiesterase, and protein kinase A onto protein scaffolds is by itself unlikely to ensure signal specificity. Rather, our simulations suggest that reductions in the effective cAMP diffusion coefficient may facilitate the formation of substantial cAMP gradients. We conclude that reductions in the effective rate of cAMP diffusion due to buffers, structural impediments, and local changes in viscosity greatly facilitate the ability of signaling complexes to impart specificity within the cAMP signaling pathway.