Cell Membrane Derived Platform To Study Virus Binding Kinetics and Diffusion with Single Particle Sensitivity

Peerboom, Nadia; Schmidt, Eneas; Trybala, Edward; Block, Stephan; Bergström, Tomas; Pace, Hudson; Bally, Marta

doi:10.1021/acsinfecdis.7b00270

Cited by 26 publications

(58 citation statements)

References 52 publications

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“…Strong inhibition of IAV binding is reflected by a strong decrease in the IAV attachment rate, so that the change in the IAV attachment rate (with respect to its value in absence of any inhibitor) is indicative for the inhibition efficiency. [22] Hence, in the following all IAV attachment rates will be normalized by the value in absence of any inhibitor, which is denoted as relative on-rate in this work.…”

Section: (6 Of 12)mentioning

confidence: 99%

Mucin‐Inspired, High Molecular Weight Virus Binding Inhibitors Show Biphasic Binding Behavior to Influenza A Viruses

Wallert

Nie

Anilkumar

et al. 2020

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Multivalent binding inhibitors are a promising new class of antivirals that prevent virus infections by inhibiting virus binding to cell membranes. The design of these inhibitors is challenging as many properties, for example, inhibitor size and functionalization with virus attachment factors, strongly influence the inhibition efficiency. Here, virus binding inhibitors are synthesized, the size and functionalization of which are inspired by mucins, which are naturally occurring glycosylated proteins with high molecular weight (MDa range) and interact efficiently with various viruses. Hyperbranched polyglycerols (hPGs) with molecular weights ranging between 10 and 2600 kDa are synthesized, thereby hitting the size of mucins and allowing for determining the impact of inhibitor size on the inhibition efficiency. The hPGs are functionalized with sialic acids and sulfates, as suggested from the structure of mucins, and their inhibition efficiency is determined by probing the inhibition of influenza A virus (IAV) binding to membranes using various methods. The largest, mucin‐sized inhibitor shows potent inhibition at pm concentrations, while the inhibition efficiency decreases with decreasing the molecular weight. Interestingly, the concentration‐dependent IAV inhibition shows a biphasic behavior, which is attributed to differences in the binding affinity of the inhibitors to the two IAV envelope proteins, neuraminidase, and hemagglutinin.

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Section: (6 Of 12)mentioning

confidence: 99%

Mucin‐Inspired, High Molecular Weight Virus Binding Inhibitors Show Biphasic Binding Behavior to Influenza A Viruses

Wallert

Nie

Anilkumar

et al. 2020

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“…Blue, untreated; red, heparinase treated; black, negative control. Reproduced with permission from [ 106 , 101 ] …”

Section: Methodological Considerationsmentioning

confidence: 99%

“…The advantage of such nSLB platforms is that they display the full compositional complexity of the cell surface, at a given time, but are decoupled from the physiological processes present in live cells. Accordingly, nSLBs have been implemented to virus research [ 58 , 59 , 101 , 105 ], illustrating how they can be used to decouple the contribution of individual cell membrane components from the ones of other cellular factors, when studying virus-membrane interactions. The approach, originally presented by Pace at al.…”

Section: Methodological Considerationsmentioning

confidence: 99%

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Physicochemical tools for studying virus interactions with targeted cell membranes in a molecular and spatiotemporally resolved context

et al. 2021

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The objective of this critical review is to provide an overview of how emerging bioanalytical techniques are expanding our understanding of the complex physicochemical nature of virus interactions with host cell surfaces. Herein, selected model viruses representing both non-enveloped (simian virus 40 and human norovirus) and enveloped (influenza A virus, human herpes simplex virus, and human immunodeficiency virus type 1) viruses are highlighted. The technologies covered utilize a wide range of cell membrane mimics, from supported lipid bilayers (SLBs) containing a single purified host membrane component to SLBs derived from the plasma membrane of a target cell, which can be compared with live-cell experiments to better understand the role of individual interaction pairs in virus attachment and entry. These platforms are used to quantify binding strengths, residence times, diffusion characteristics, and binding kinetics down to the single virus particle and single receptor, and even to provide assessments of multivalent interactions. The technologies covered herein are surface plasmon resonance (SPR), quartz crystal microbalance with dissipation (QCM-D), dynamic force spectroscopy (DFS), total internal reflection fluorescence (TIRF) microscopy combined with equilibrium fluctuation analysis (EFA) and single particle tracking (SPT), and finally confocal microscopy using multi-labeling techniques to visualize entry of individual virus particles in live cells. Considering the growing scientific and societal needs for untangling, and interfering with, the complex mechanisms of virus binding and entry, we hope that this review will stimulate the community to implement these emerging tools and strategies in conjunction with more traditional methods. The gained knowledge will not only contribute to a better understanding of the virus biology, but may also facilitate the design of effective inhibitors to block virus entry.

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“…With the ability to localize particles with an accuracy far below the diffraction limit of light and to track particles across time, SPT continues to be an invaluable tool in understanding biology at the nanometer-scale by revealing details about particle dynamics and their local environment such as diffusion rates, confinement length, and other parameters [ 1 ]. SPT has been applied to a wide variety of molecules, including proteins [ 2 , 3 ], mRNA molecules [ 4 ], DNA [ 5 ], viruses [ 6 , 7 ], growth factor receptor [ 8 ], Janus colloids [ 9 ], and more [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Expectation maximization based framework for joint localization and parameter estimation in single particle tracking from segmented images

Lin

Andersson

2021

PLoS ONE

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Single Particle Tracking (SPT) is a well known class of tools for studying the dynamics of biological macromolecules moving inside living cells. In this paper, we focus on the problem of localization and parameter estimation given a sequence of segmented images. In the standard paradigm, the location of the emitter inside each frame of a sequence of camera images is estimated using, for example, Gaussian fitting (GF), and these locations are linked to provide an estimate of the trajectory. Trajectories are then analyzed by using Mean Square Displacement (MSD) or Maximum Likelihood Estimation (MLE) techniques to determine motion parameters such as diffusion coefficients. However, the problems of localization and parameter estimation are clearly coupled. Motivated by this, we have created an Expectation Maximization (EM) based framework for simultaneous localization and parameter estimation. We demonstrate this framework through two representative methods, namely, Sequential Monte Carlo combined with Expectation Maximization (SMC-EM) and Unscented Kalman Filter combined with Expectation Maximization (U-EM). Using diffusion in two-dimensions as a prototypical example, we conduct quantitative investigations on localization and parameter estimation performance across a wide range of signal to background ratios and diffusion coefficients and compare our methods to the standard techniques based on GF-MSD/MLE. To demonstrate the flexibility of the EM based framework, we do comparisons using two different camera models, an ideal camera with Poisson distributed shot noise but no readout noise, and a camera with both shot noise and the pixel-dependent readout noise that is common to scientific complementary metal-oxide semiconductor (sCMOS) camera. Our results indicate our EM based methods outperform the standard techniques, especially at low signal levels. While U-EM and SMC-EM have similar accuracy, U-EM is significantly more computationally efficient, though the use of the Unscented Kalman Filter limits U-EM to lower diffusion rates.

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Cell Membrane Derived Platform To Study Virus Binding Kinetics and Diffusion with Single Particle Sensitivity

Cited by 26 publications

References 52 publications

Mucin‐Inspired, High Molecular Weight Virus Binding Inhibitors Show Biphasic Binding Behavior to Influenza A Viruses

Mucin‐Inspired, High Molecular Weight Virus Binding Inhibitors Show Biphasic Binding Behavior to Influenza A Viruses

Physicochemical tools for studying virus interactions with targeted cell membranes in a molecular and spatiotemporally resolved context

Expectation maximization based framework for joint localization and parameter estimation in single particle tracking from segmented images

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