Name: single-molecule tracking microscopy - a tool for determining the diffusive states of cytosolic molecules
Uploaded: 2019-09-05T12:30:00.000+00:00
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Description: Watch this Scientific Journal Video about Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules at JoVE.com

We thank Alecia Achimovich and Ting Yan for critical reading of the manuscript. We thank Ed Hall, senior staff scientist in the Advanced Research Computing Services group at the University of Virginia, for help with setting up the optimization routines used in this work. Funding for this work was provided by the University of Virginia.

The authors have nothing to disclose.

A critical factor for the successful application of the presented protocol is to ensure that single-molecule signals are well-separated from each other (i.e., they need to be sparse in space and in time (Supplementary Mov. 1)). If there is more than one fluorescing molecule in a cell at the same time, then localization could be incorrectly assigned to another molecules&#8217; trajectory. This is referred to as the linking problem30. Experimental conditions, such as protein expression levels and excitation laser intensity can be chosen to avoid the linking problem. However, care should be taken to obtain wild-type protein expression levels to ensure representative results. Here, we used allelic replacements under the control of the native promoters instead of chemically inducible expression, to ensure native expression levels of the labeled proteins. Thus, the excitation laser intensity (for eYFP blinking) or the activation laser intensity (for photo-activatable fluorescent probes) can be used to control the concentration of active emitters in time. Alternatively, when chemical dye labeling is used in conjunction with HALO and SNAP tags31,32, then the dye concentration can be reduced until fluorescent signals are sparse enough to track single molecules33. The protocol presented here further eliminates the linking problem by discarding any trajectories for which two or more localizations are simultaneously present in the same cell (Supplementary Mov. 2). Thus, if single-molecule signals are too dense, a large amount of&#160; data is&#160;automatically discarded during processing. Under the excitation conditions used here (&#955;ex = 514&#160;nm at 350 W/cm2), we obtained 10-150 trajectories per bacterial cell when acquiring 20,000 frames over the course of 8 min. On the other hand, if experimental conditions are chosen such that single-molecule signals are sparse, then the data acquisition throughput may be low, so that obtaining a sufficiently large number of single-molecule trajectories would require imaging additional cells in additional fields-of-view. Acquiring a large number of trajectories is beneficial, because the errors in the fitted parameters (the diffusion coefficients and the population fractions) decrease as the number of trajectories that are analyzed increase29.
Achieving large numbers of single-molecule trajectories requires high data-acquisition throughput. As a wide-field technique, single-molecule localization microscopy acquires data for each cell in the FOV simultaneously, and researchers have begun to take advantage of new sCMOS detectors that afford large FOVs26,34,35. However, excitation laser powers of several Watts are required to achieve uniform intensities sufficient for single-molecule localization microscopy throughout such large FOVs. Such laser powers may be above the damage threshold of commercially available objective lenses. Lenslet arrays employed to make the excitation laser intensities uniform in large FOVs may be able to circumvent this issue34. Additionally, optical aberrations become pronounced when imaging far away from the optical axis. As a result, the shape of the DHPSF may become too distorted to be successfully fit by a double Gaussian model employed in easy DHPSF. When imaging in an ultrawide FOV, more sophisticated spatially-varying PSF models are required36. To avoid these complicating factors, the data presented here were acquired in a relatively small FOV (diameter = 55 &#181;m) and data from 10 FOVs were pooled to obtain more than 75,000 single-molecule trajectories.
Fitting of the experimentally measured apparent diffusion coefficient distributions with simulated distributions requires realistic simulation of the experimental data. Static and dynamic localization errors in camera-based tracking can affect the quality of the measurement11,13. Static localization errors are due to the finite numbers of photons collected per fluorescence emitter, which results in an imprecise PSF shape and thus result in single-molecule localizations of limited precision2,37,38. Dynamic localization errors arise due to moving emitters that generate blurred PSFs39. When an algorithm is applied to fit the shape of the PSF, motion-blurred images provide localizations with limited accuracy and precision39. In severe cases of rapid molecule movement, the image may be too distorted to fit, resulting in an unsuccessful fit and thus no recorded localization. Simulating spatially blurred PSFs with realistic signal to-noise ratios and localizing with the same fitting algorithm as experimental data accounts for both static and dynamic localization error. Second, rapidly diffusing molecules can be strongly confined to small volumes, such as the cytosol of a bacterial cell. As a result, the apparent diffusion coefficients are smaller, on average, than those expected for unconfined motion. Spatial confinement results in an overall left-shift of the distribution towards smaller diffusive values. Importantly, the shape of the distribution is no longer expressible as an analytical function. By explicitly accounting for static and dynamic localization errors due to motion blurring and confinement effects through stochastic simulations, realistic distributions can be obtained23.
The described diffusion analysis relies on two key assumptions regarding the dynamic behavior of the molecules in the biological environment. It assumes that diffusive states are described by confined Brownian motion and that they do not interconvert on the timescale of a single-molecule trajectory. We have experimentally verified that the assumption of confined Brownian motion is justified for free eYFP diffusion in Y.&#160;enterocolitica23. These results are in agreement with a number of studies in various bacterial species that have established that the motion of cytosolic proteins, fusion proteins, and biomolecular complexes smaller than 30&#160;nm can be described by Brownian motion18,40,41,42,43,44,45. Non-specific collisions of small fluorescently labeled proteins with other cellular components may slow down the diffusion rates,45,46 but do not lead to deviations from Brownian diffusion. By contrast, specific interaction with cognate binding partners can produce a change in the diffusion coefficient, as recently shown for the Y.&#160;enterocolitica Type 3 secretion protein YscQ23. The validity of the second assumption is difficult to assess, especially for systems for which neither the diffusive states nor the binding kinetics are known. The situation is further complicated because any oligomerization states and binding kinetics measured in vitro, may not reflect the structures and dynamics that occur in vivo. A recent theoretical study based on the analysis framework presented here suggests that it may be possible to extract the state switching kinetics in addition to the diffusion coefficients and population fractions29.
In summary, we present an integrated protocol for resolving the diffusive states of fluorescently labeled molecules based on single-molecule trajectories measured in living bacterial cells. As presented here, the protocol is applied to 3D single-molecule localization microscopy using the double-helix PSF for imaging in Y.&#160;enterocolitica, a bacterial pathogen. However, with only a few modifications, the protocol can be applied to any type of 2D or 3D single-molecule localization microscopy and specimen geometry.

Examining the diffusive behavior of biomolecules provides insight into their biological functions. Fluorescence microscopy-based techniques have become valuable tools for observing biomolecules in their native cell environment. Fluorescence recovery after photobleaching (FRAP) and fluorescence correlation spectroscopy (FCS)1 provide ensemble-averaged diffusive behaviors. Conversely, single-molecule localization microscopy enables observation of individual fluorescently tagged molecules with high spatial and temporal resolution2,3,4. Observing individual molecules is advantageous since a protein of interest may exist in different diffusive states. For example, two readily distinguishable diffusive states arise when a transcriptional regulator, such as CueR in Escherichia coli, diffuses freely in the cytosol or binds to a DNA sequence and becomes immobilized on the timescale of measurement5. Single-molecule tracking provides a tool for observing these different states directly, and sophisticated analyses are not required to resolve them. However, it becomes more challenging to resolve multiple diffusive states and their population fractions in cases where their diffusive rates are more similar. For example, due to the size dependence of the diffusion coefficient, different oligomerization states of a protein manifest themselves as different diffusive states6,7,8,9,10. Such cases require an integrated approach in terms of data acquisition, processing and analysis.
A critical factor influencing diffusive rates of cytosolic molecules is the effect of confinement by the cell boundary. The restrictions placed on molecular motion by a bacterial cell boundary cause a cytosolic molecules&#8217; measured diffusion rate to appear slower than if the same motion had occurred in an unconfined space. For very slowly diffusing molecules, the effect of cellular confinement is negligible due to the lack of collisions with the boundary. In such cases, it may be possible to accurately resolve diffusive states by fitting the distributions of molecular displacements, r, or apparent diffusion coefficients, D*, using analytical models based on the equations for Brownian motion (random diffusion)11,12,13. However, for fast diffusing cytosolic molecules, the experimental distributions no longer resemble those obtained for unconfined Brownian motion due to collisions of diffusing molecules with the cell boundaries. Confinement effects must be accounted for to accurately determine the unconfined diffusion coefficients of the fluorescently labeled molecules. Several approaches have recently been developed to account for confinement effects either (semi-)analytically 5,14,15,16 or numerically through Monte Carlo simulations of Brownian diffusion6,10,16,17,18,19.
Here, we provide an integrated protocol for collecting and analyzing single-molecule localization microscopy data with a particular focus on single-molecule tracking. The end goal of the protocol is to resolve diffusive states of fluorescently labeled cytosolic proteins inside, in this case, rod-shaped bacterial cells. Our work builds on a previous protocol for single-molecule tracking, in which a DNA polymerase, PolI, was shown to exist in a DNA bound and unbound state by diffusion analysis20. Here, we expand single-molecule tracking analysis to 3D measurements and perform more realistic computational simulations to resolve and quantify multiple diffusive states simultaneously present in cells. The data is acquired using a home-built 3D super-resolution fluorescence microscope which is capable of determining the 3D position of fluorescent emitters by imaging with the double-helix point-spread-function (DHPSF)21,22. The raw single-molecule images are processed using custom-written software to extract the 3D single-molecule localizations, which are then combined into single-molecule trajectories. Thousands of trajectories are pooled to generate distributions of apparent diffusion coefficients. In a final step, the experimental distributions are fit with numerically generated distributions obtained through Monte-Carlo simulations of Brownian motion in a confined volume. We apply this protocol to resolve the diffusive states of the Type 3 secretion system protein YscQ in living Yersinia enterocolitica. Due to its modular nature, our protocol is generally applicable to any type of single-molecule or single-particle tracking experiment in arbitrary cell geometries.

<table><tbody><tr><td>2,6-diaminopimelic acid</td><td>Chem Impex International</td><td>5411</td><td>Necessary for growth of &lt;em&gt;Y. enterocolitica&lt;/em&gt; cells used.</td></tr><tr><td>4f lenses</td><td>Thorlabs</td><td>AC508-080-A</td><td>f = 80mm, 2&quot;</td></tr><tr><td>514 nm laser</td><td>Coherent</td><td>Genesis MX514 MTM</td><td>Use for fluorescence excitation</td></tr><tr><td>agarose</td><td>Inivtrogen</td><td>16520100</td><td>Used to make gel pads to mount liquid bacterial sample on microscope.</td></tr><tr><td>ammonium chloride</td><td>Sigma Aldrich</td><td>A9434</td><td>M2G ingredient.</td></tr><tr><td>bandpass filter</td><td>Chroma</td><td>ET510/bp</td><td>Excitation pathway.</td></tr><tr><td>Brain Heart Infusion</td><td>Sigma Aldrich</td><td>53286</td><td>Growth media for &lt;em&gt;Y. enterocolitica&lt;/em&gt;.</td></tr><tr><td>calcium chloride</td><td>Sigma Aldrich</td><td>223506</td><td>M2G ingredient.</td></tr><tr><td>camera</td><td>Imaging Source</td><td>DMK 23UP031</td><td>Camera for phase contrast imaging.</td></tr><tr><td>dielectric phase mask</td><td>Double Helix, LLC</td><td>N/A</td><td>Produces DHPSF signal.</td></tr><tr><td>disodium phosphate</td><td>Sigma Aldrich</td><td>795410</td><td>M2G ingredient.</td></tr><tr><td>ethylenediaminetetraacetic acid</td><td>Fisher Scientific</td><td>S311-100</td><td>Chelates Ca&lt;sup&gt;2+&lt;/sup&gt;. Induces secretion in the T3SS.</td></tr><tr><td>flip mirror</td><td>Newport</td><td>8892-K</td><td>Allows for switching between fluorescence and phase contrast pathways.</td></tr><tr><td>fluospheres</td><td>Invitrogen</td><td>F8792</td><td>Fluorescent beads. 540/560 exication and emission wavelengths. 40 nm diameter.</td></tr><tr><td>glass cover slip</td><td>VWR</td><td>16004-302</td><td>#1.5, 22mmx22mm</td></tr><tr><td>glucose</td><td>Chem Impex International</td><td>811</td><td>M2G ingredient.</td></tr><tr><td>immersion oil</td><td>Olympus</td><td>Z-81025</td><td>Placed on objective lens.</td></tr><tr><td>iron(II) sulfate</td><td>Sigma Aldrich</td><td>F0518</td><td>M2G ingredient.</td></tr><tr><td>long pass filter</td><td>Semrock</td><td>LP02-514RU-25</td><td>Emission pathway.</td></tr><tr><td>magnesium sulfate</td><td>Fisher Scientific</td><td>S25414A</td><td>M2G ingredient.</td></tr><tr><td>microscope platform</td><td>Mad City Labs</td><td>custom</td><td>Platform for inverted microscope.</td></tr><tr><td>nalidixic acid</td><td>Sigma Aldrich</td><td>N4382</td><td>&lt;em&gt;Y. enterocolitica&lt;/em&gt; cells used are resistant to nalidixic acid.</td></tr><tr><td>objective lens</td><td>Olympus</td><td>1-U2B991</td><td>60X, 1.4 NA</td></tr><tr><td>Ozone cleaner</td><td>Novascan</td><td>PSD-UV4</td><td>Used to eliminate background fluorescence on glass cover slips.</td></tr><tr><td>potassium phosphate</td><td>Sigma Aldrich</td><td>795488</td><td>M2G ingredient.</td></tr><tr><td>Red LED</td><td>Thorlabs</td><td>M625L3</td><td>Illuminates sample for phase contrast imaging. 625nm.</td></tr><tr><td>sCMOS camera</td><td>Hamamatsu</td><td>ORCA-Flash 4.0 V2</td><td>Camera for fluorescence imaging.</td></tr><tr><td>short pass filter</td><td>Chroma</td><td>ET700SP-2P8</td><td>Emission pathway.</td></tr><tr><td>Tube lens</td><td>Thorlabs</td><td>AC508-180-A</td><td>f=180 mm, 2&quot;</td></tr><tr><td>&lt;em&gt;Yersinia enterocolitica&lt;/em&gt; dHOPEMTasd</td><td>N/A</td><td>N/A</td><td>Strain AD4442, eYFP-YscQ</td></tr><tr><td>zero-order quarter-wave plate</td><td>Thorlabs</td><td>WPQ05M-514</td><td>Excitation pathway.</td></tr></tbody></table>

single-molecule tracking microscopy - a tool for determining the diffusive states of cytosolic molecules

Single-molecule localization microscopy probes the position and motions of individual molecules in living cells with tens of nanometer spatial and millisecond temporal resolution. These capabilities make single-molecule localization microscopy ideally suited to study molecular level biological functions in physiologically relevant environments. Here, we demonstrate an integrated protocol for both acquisition and processing/analysis of single-molecule tracking data to extract the different diffusive states a protein of interest may exhibit. This information can be used to quantify molecular complex formation in living cells. We provide a detailed description of a camera-based 3D single-molecule localization experiment, as well as the subsequent data processing steps that yield the trajectories of individual molecules. These trajectories are then analyzed using a numerical analysis framework to extract the prevalent diffusive states of the fluorescently labeled molecules and the relative abundance of these states. The analysis framework is based on stochastic simulations of intracellular Brownian diffusion trajectories that are spatially confined by an arbitrary cell geometry. Based on the simulated trajectories, raw single-molecule images are generated and analyzed in the same way as experimental images. In this way, experimental precision and accuracy limitations, which are difficult to calibrate experimentally, are explicitly incorporated into the analysis workflow. The diffusion coefficient and relative population fractions of the prevalent diffusive states are determined by fitting the distributions of experimental values using linear combinations of simulated distributions. We demonstrate the utility of our protocol by resolving the diffusive states of a protein that exhibits different diffusive states upon forming homo- and hetero-oligomeric complexes in the cytosol of a bacterial pathogen.

Under the experimental conditions described here (20,000 frames, trajectory length minimum of 4 localizations) and depending on the expression levels of the fluorescently labeled fusion proteins, approximately 200-3,000 localizations yielding 10-150 trajectories can be generated per cell (Figure 2a,b). A large number of trajectories is necessary to produce a well-sampled distribution of apparent diffusion coefficients. The size of FOV collected here is ~55 x 55 &#181;m, with 10 FOV collected per experiment. Therefore, to obtain &#62;5,000 trajectories per experiment each FOV should contain at least 50 cells. Ideally, the cell population should be made as dense as possible, but without having cells touch each other. If the cell density is too high, then the presence of touching or overlapping cells makes it challenging to segment them successfully using OUFTI(28), as described in Data Post Processing. Poor segmentation can lead to localizations and trajectories assigned incorrectly between cells.
Here, we present apparent diffusion coefficient data on the Y. enterocolitica Type 3 secretion protein YscQ, which we N-terminally labeled with the fluorescent protein eYFP. YscQ is a structural component of a membrane-spanning molecular machine, called the injectisome. The injectisome is comprised of over 20 different proteins, many of which are present in multiple copy numbers. Type 3 secretion injectisomes are broadly utilized by pathogenic gram-negative bacteria to deliver virulent effector proteins directly into host cell during infection. YscQ dynamically binds and unbinds to and from the cytosolic side of the injectisome. As a result, YscQ is also found freely diffusing in the cytosol. By applying the data acquisition, processing, and analysis protocol described above, we determined that unbound YscQ exists in at least 3 distinct diffusive states (Figure 3). These 3 diffusive states correspond to different homo- and hetero-oligomeric complexes of YscQ and other Type 3 secretion proteins23.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59387/59387fig1.jpg" /> 
Figure 1: Optical diagram of microscope pathways. The microscope has a pathway for detection of fluorescence signal and a separate pathway for taking a phase contrast image. A motorized &#8216;flip-mirror&#8217; is used to switch between the pathways. The camera detectors, excitation lasers, LED, and &#8216;flip-mirror&#8217; are controlled remotely by computer. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/59387fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59387/59387fig2.jpg" /> 
Figure 2: Single-molecule localizations and trajectories. (A). 3D single-molecule localizations of eYFP-YscQ in a Y. enterocolitica cell obtained in different frames (1,766 localizations). The localizations are overlaid on a phase contrast image of the cell. The green line indicates the cell outline based on the phase contrast image. (B). 3D single-molecule trajectories of eYFP-YscQ obtained from the localizations shown in panel A (142 trajectories). Different colors represent different single-molecule trajectories. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/59387fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59387/59387fig3.jpg" /> 
Figure 3: Apparent diffusion coefficient distribution fitting of eYFP-YscQ in Y. enterocolitica. The apparent diffusion coefficient distribution for eYFP-YscQ in Y. enterocolitca was best fit with 3 diffusive states. Note that the probability density function (PDF) is shown here, while the data fitting was done by fitting the cumulative distribution function (CDF, Experimental Apparent Diffusion Coefficient Distribution Fitting). Figure adapted from Rocha et al23. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/59387fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary Figure 1. Microscope Control GUI. The microscope GUI controls the micropositioner of the stage, excitation lasers, LED, and cameras for fluorescence emission. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/FigS1.png">Please click here to download this file.</a>
Supplementary Figure 2. Easy-DHPSF GUI. The Easy-DHPSF software is used to extract single-molecule localizations from the DHPSF signals. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/FigS2.png">Please click here to download this file.</a>
Supplementary Figure 3. Oufti Segmentation. The open source software OUFTI28 is used to sement the cells. Here, the results of the cell segmentation are shown in green. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/FigS3.png">Please click here to download this file.</a>
Supplementary Figure 4. Selection of control points. Five points are selected in both the cell outline data and the localization data. The cell poles are used as reference points. These points are used to transform the data so that the cell outlines and localizations are correctly overlaid. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/FigS4.png">Please click here to download this file.</a>
Supplementary Figure 5. Delete unwanted cells. After the cell overlay, unwanted cells are manually deleted. Cells with unusually low/high amounts of localizations should be deleted, as well as any cells which are at the edge of the FOV. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/FigS5.png">Please click here to download this file.</a>
Supplementary Figure 6. Final overlay of cell outlines and localizations. After deletion of unwanted cells, the cell outlines and single-molecule localizations are finely transformed to get the final overlay. Localizations outside of cell outlines are deleted. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/FigS6.png">Please click here to download this file.</a>
Supplementary Mov. 1: Raw data for a single-molecule trajectory. Example of detection of eYFP-YscQ on the sCMOS camera. In frame 1, there is no fluorescence signal. In frames 2-10, fluorescence is detected from a single molecule. In each successive frame, the position and orientation of the DHPSF changes, indicating diffusion of this molecule. Finally, in frame 11, there is once again an absence in fluorescence signal, indicating the end of the trajectory. Each pixel is 108 x 108 nm. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/Mov1.avi">Please click here to download this file.</a>
Supplementary Mov. 2: Raw data for a missed single-molecule trajectory. Frames 1-3 show fluorescence signal for a single emitter. However, frames 4-6 show the presence of two overlapping DHPSFs, indicating the presence of two emitters in close proximity. In such cases, the individual DHPSFs may not be correctly fit because of their overlap. Even if both DHPSFs are successfully fit, any trajectory observed containing these localizations would be discarded. Two or more localizations in the same cell may lead to incorrect assignments of localizations to a given trajectory. Each pixel is 108 x 108 nm. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59387/Mov2.avi">Please click here to download this file.</a>

Watch this Scientific Journal Video about Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules at JoVE.com

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

3D single-molecule localization microscopy is utilized to probe the spatial positions and motion trajectories of fluorescently labeled proteins in living bacterial cells. The experimental and data analysis protocol described herein determines the prevalent diffusive behaviors of cytosolic proteins based on pooled single-molecule trajectories.

Single-molecule localization microscopy probes the position and motions of individual molecules in living cells with tens of nanometer spatial and ...

single-molecule-tracking-microscopy-tool-for-determining-diffusive

Nanyang Technological University

Research

JoVE Journal

Biochemistry

8.1K Views.  University of Virginia. 3D single-molecule tracking kan de subcellulaire lokalisaties en bewegingsgedrag van individuele eiwitten bepalen. Het observeren van de beweging van een eiwit in een levende cel geeft belangrijke inzichten over de interactie met bindende partners in zijn eigen omgeving. De hier gepresenteerde methode biedt een algemeen kader voor het analyseren van trackinggegevens van één molecuul om de verspreidingstoestanden van biologische moleculen op te lossen.Het kan worden toegepast op zowel...

Video: Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., kinetics, coexistence of different states and populations, transient interactions), which are typically hidden in ensemble measurements, such as those obtained with standard biochemical or microscopy methods. Thus, dynamic events, such as receptor-receptor interactions, can be followed in real time in a living cell with high spatiotemporal resolution. This protocol describes a method based on labeling with small and bright organic fluorophores and total internal reflection fluorescence (TIRF) microscopy to directly visualize single receptors on the surface of living cells. This approach allows one to precisely localize receptors, measure the size of receptor complexes, and capture dynamic events such as transient receptor-receptor interactions. The protocol provides a detailed description of how to perform a single-molecule experiment, including sample preparation, image acquisition and image analysis. As an example, the application of this method to analyze two G-protein-coupled receptors, i.e., &#946;2-adrenergic and &#947;-aminobutyric acid type B (GABAB) receptor, is reported. The protocol can be adapted to other membrane proteins and different cell models, transfection methods and labeling strategies.

This protocol describes how to use total internal reflection fluorescence microscopy to visualize and track single receptors on the surface of living cells and thereby analyze receptor lateral mobility, size of receptor complexes as well as to visualize transient receptor-receptor interactions. This protocol can be extended to other membrane proteins.

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., ...

Bioengineering

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn&#8217;t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on &#181;m-sized membrane regions in the micro-to-milli-second time range.

Spatial distribution and temporal dynamics of plasma membrane proteins and lipids is a hot topic in biology. Here this issue is addressed by a spatio-temporal image fluctuation analysis that provides conceptually the same physical quantities of single particle tracking, but it uses small molecular labels and standard microscopy setups.

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the ...

Visualizing Protein-DNA Interactions in Live Bacterial Cells Using Photoactivated Single-molecule Tracking

Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome organization are governed by DNA-binding proteins that recognize specific DNA structures or sequences. In vitro experiments have helped to generate detailed models for the function of many types of DNA-binding proteins, yet, the exact mechanisms of these processes and their organization in the complex environment of the living cell remain far less understood. We recently introduced a method for quantifying DNA-repair activities in live Escherichia coli cells using Photoactivated Localization Microscopy (PALM) combined with single-molecule tracking. Our general approach identifies individual DNA-binding events by the change in the mobility of a single protein upon association with the chromosome. The fraction of bound molecules provides a direct quantitative measure for the protein activity and abundance of substrates or binding sites at the single-cell level. Here, we describe the concept of the method and demonstrate sample preparation, data acquisition, and data analysis procedures.

Photoactivated localization microscopy (PALM) combined with single-molecule tracking allows direct observation and quantification of protein-DNA interactions in live Escherichia coli cells.

Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome ...

Immunology and Infection

Spot Variation Fluorescence Correlation Spectroscopy for Analysis of Molecular Diffusion at the Plasma Membrane of Living Cells

Dynamic biological processes in living cells, including those associated with plasma membrane organization, occur on various spatial and temporal scales, ranging from nanometers to micrometers and microseconds to minutes, respectively. Such a broad range of biological processes challenges conventional microscopy approaches. Here, we detail the procedure for implementing spot variation Fluorescence Correlation Spectroscopy (svFCS) measurements using a classical fluorescence microscope that has been customized. The protocol includes a specific performance check of the svFCS setup and the guidelines for molecular diffusion measurements by svFCS on the plasma membrane of living cells under physiological conditions. Additionally, we provide a procedure for disrupting plasma membrane raft nanodomains by cholesterol oxidase treatment and demonstrate how these changes in the lateral organization of the plasma membrane might be revealed by svFCS analysis. In conclusion, this fluorescence-based method can provide unprecedented details on the lateral organization of the plasma membrane with the appropriate spatial and temporal resolution.

This article aims to present a protocol on how to build a spot variation Fluorescence Correlation Spectroscopy (svFCS) microscope to measure molecular diffusion at the plasma membrane of living cells.

Dynamic biological processes in living cells, including those associated with plasma membrane organization, occur on various spatial and temporal scales, ...

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics

Short-lived or transient interactions of macromolecules at and with lipid membranes, an interface where a multitude of essential biological reactions take place, are inherently difficult to assess with standard biophysical methods. The introduction of mass-sensitive particle tracking (MSPT) constitutes an important step toward a thorough quantitative characterization of such processes. Technically, this was made possible through the advent of interferometric scattering microscopy (iSCAT)-based mass photometry (MP). When the background removal strategy is optimized to reveal the two-dimensional motion of membrane-associated particles, this technique allows the real-time analysis of both diffusion and molecular mass of unlabeled macromolecules on biological membranes. Here, a detailed protocol to perform and analyze mass-sensitive particle tracking of membrane-associated systems is described. Measurements performed on a commercial mass photometer achieve time resolution in the millisecond regime and, depending on the MP system, a mass detection limit down to 50 kDa. To showcase the potential of MSPT for the in-depth analysis of membrane-catalyzed macromolecule dynamics in general, results obtained for exemplary protein systems such as the native membrane interactor annexin V are presented.

This protocol describes an iSCAT-based image processing and single-particle tracking approach that enables the simultaneous investigation of the molecular mass and the diffusive behavior of macromolecules interacting with lipid membranes. Step-by-step instructions for sample preparation, mass-to-contrast conversion, movie acquisition, and post-processing are provided alongside directions to prevent potential pitfalls.

Short-lived or transient interactions of macromolecules at and with lipid membranes, an interface where a multitude of essential biological reactions take ...

Single-Molecule Imaging of Nuclear Transport

The utility of single molecule fluorescence microscopy approaches has been proven to be of a great avail in understanding biological reactions over the last decade. The investigation of molecular interactions with high temporal and spatial resolutions deep within cells has remained challenging due to the inherently weak signals arising from individual molecules. Recent works by Yang et al. demonstrated that narrow-field epifluorescence microscopy allows visualization of nucleocytoplasmic transport at the single molecule level. By the single molecule approach, important kinetics, such as nuclear transport time and efficiency, for signal-dependent and independent cargo molecules have been obtained. Here we described a protocol for the methodological approach with an improved spatiotemporal resolution of 0.4 ms and 12 nm. The improved resolution enabled us to capture transient active transport and passive diffusion events through the nuclear pore complexes (NPC) in semi-intact cells. We expect this method to be used in elucidating other binding and trafficking events within cells.

Single molecule microscopy approch provided novel insights into nuclear transport.

The utility of single molecule fluorescence microscopy approaches has been proven to be of a great avail in understanding biological reactions over the ...

Biology

Single-Molecule Diffusion and Assembly on Polymer-Crowded Lipid Membranes

Cellular membranes are highly crowded environments for biomolecular reactions and signaling. Yet, most in vitro experiments probing protein interaction with lipids employ naked bilayer membranes. Such systems lack the complexities of crowding by membrane-embedded proteins and glycans and exclude the associated volume effects encountered on cellular membrane surfaces. Also, the negatively charged glass surface onto which the lipid bilayers are formed prevents the free diffusion of transmembrane biomolecules. Here, we present a well-characterized polymer-lipid membrane as a mimic for crowded lipid membranes. This protocol utilizes polyethylene glycol (PEG)-conjugated lipids as a generalized approach for incorporating crowders into the supported lipid bilayer&#160;(SLB). First, a cleaning procedure of the microscopic slides and coverslips for performing single-molecule experiments is presented. Next, methods for characterizing the PEG-SLBs and performing single-molecule experiments of the binding, diffusion, and assembly of biomolecules using single-molecule tracking and photobleaching are discussed. Finally, this protocol demonstrates how to monitor the nanopore assembly of bacterial pore-forming toxin Cytolysin A (ClyA) on crowded lipid membranes with single-molecule photobleaching analysis. MATLAB codes with example datasets are also included to perform some of the common analyses such as particle tracking, extracting diffusive behavior, and subunit counting.

Here, a protocol to perform and analyze the binding, mobility, and assembly of single molecules on artificial crowded lipid membranes using single-molecule total internal reflection fluorescence (smTIRF) microscopy is presented.

Cellular membranes are highly crowded environments for biomolecular reactions and signaling. Yet, most in vitro experiments probing protein interaction ...

Single-Molecule Imaging of Lateral Mobility and Ion Channel Activity in Lipid Bilayers using Total Internal Reflection Fluorescence (TIRF) Microscopy

High-resolution imaging techniques have shown that many ion channels are not static, but subject to highly dynamic processes, including the transient association of pore-forming and auxiliary subunits, lateral diffusion, and clustering with other proteins. However, the relationship between lateral diffusion and function is poorly understood. To approach this problem, we describe how lateral mobility and activity of individual channels in supported lipid membranes can be monitored and correlated using total internal reflection fluorescence (TIRF) microscopy. Membranes are fabricated on an ultrathin hydrogel substrate using the droplet interface bilayer (DIB) technique. Compared to other types of model membranes, these membranes have the advantage of being mechanically robust and suitable for highly sensitive analytical techniques. This protocol measures Ca2+ ion flux through single channels by observing the fluorescence emission of a Ca2+-sensitive dye in close proximity to the membrane. In contrast to classical single-molecule tracking approaches, no fluorescent fusion proteins or labels, which can interfere with lateral movement and function in the membrane, are required. Possible changes in ion flux associated with conformational changes of the protein are only due to protein lateral motion in the membrane. Representative results are shown using the mitochondrial protein translocation channel TOM-CC and the bacterial channel OmpF. In contrast to OmpF, the gating of TOM-CC is very sensitive to molecular confinement and the nature of lateral diffusion. Hence, supported droplet-interface bilayers are a powerful tool to characterize the link between lateral diffusion and the function of ion channels.

Single-Molecule Imaging of Lateral Mobility and Ion Channel Activity in Lipid Bilayers using Total Internal Reflection Fluorescence TIRF Microscopy

This protocol describes how to use TIRF microscopy to track individual ion channels and determine their activity in supported lipid membranes, thereby defining the interplay between lateral membrane movement and channel function. It describes how to prepare the membranes, record the data, and analyze the results.

High-resolution imaging techniques have shown that many ion channels are not static, but subject to highly dynamic processes, including the transient ...

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing (MTT)

Our goal is to obtain a comprehensive description of molecular processes occurring at cellular membranes in different biological functions. We aim at characterizing the complex organization and dynamics of the plasma membrane at single-molecule level, by developing analytic tools dedicated to Single-Particle Tracking (SPT) at high density: Multiple-Target Tracing (MTT)1. Single-molecule videomicroscopy, offering millisecond and nanometric resolution1-11, allows a detailed representation of membrane organization12-14 by accurately mapping descriptors such as cell receptors localization, mobility, confinement or interactions.
We revisited SPT, both experimentally and algorithmically. Experimental aspects included optimizing setup and cell labeling, with a particular emphasis on reaching the highest possible labeling density, in order to provide a dynamic snapshot of molecular dynamics as it occurs within the membrane. Algorithmic issues concerned each step used for rebuilding trajectories: peaks detection, estimation and reconnection, addressed by specific tools from image analysis15,16. Implementing deflation after detection allows rescuing peaks initially hidden by neighboring, stronger peaks. Of note, improving detection directly impacts reconnection, by reducing gaps within trajectories. Performances have been evaluated using Monte-Carlo simulations for various labeling density and noise values, which typically represent the two major limitations for parallel measurements at high spatiotemporal resolution.
The nanometric accuracy17 obtained for single molecules, using either successive on/off photoswitching or non-linear optics, can deliver exhaustive observations. This is the basis of nanoscopy methods17 such as STORM18, PALM19,20, RESOLFT21 or STED22,23, which may often require imaging fixed samples. The central task is the detection and estimation of diffraction-limited peaks emanating from single-molecules. Hence, providing adequate assumptions such as handling a constant positional accuracy instead of Brownian motion, MTT is straightforwardly suited for nanoscopic analyses. Furthermore, MTT can fundamentally be used at any scale: not only for molecules, but also for cells or animals, for instance. Hence, MTT is a powerful tracking algorithm that finds applications at molecular and cellular scales.

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing MTT

Multiple-Target Tracing is a homemade algorithm developed for tracking individually labeled molecules within the plasma membrane of living cells. Efficiently detecting, estimating and tracing molecules over time at high-density provide a user-friendly, comprehensive tool to investigate nanoscale membrane dynamics.

Our goal is to obtain a comprehensive description of molecular processes occurring at cellular membranes in different biological functions. We aim at ...

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Particle tracking on a video sequence and the posterior analysis of their trajectories is nowadays a common operation in many biological studies. Using the analysis of cell membrane receptor clusters as a model, we present a detailed protocol for this image analysis task using Fiji (ImageJ) and Matlab routines to: 1) define regions of interest and design masks adapted to these regions; 2) track the particles in fluorescence microscopy videos; 3) analyze the diffusion and intensity characteristics of selected tracks. The quantitative analysis of the diffusion coefficients, types of motion, and cluster size obtained by fluorescence microscopy and image processing provides a valuable tool to objectively determine particle dynamics and the consequences of modifying environmental conditions. In this article we present detailed protocols for the analysis of these features. The method described here not only allows single-molecule tracking detection, but also automates the estimation of lateral diffusion parameters at the cell membrane, classifies the type of trajectory and allows complete analysis thus overcoming the difficulties in quantifying spot size over its entire trajectory at the cell membrane.

Here, we present a protocol for single particle tracking image analysis that allows quantitative evaluation of diffusion coefficients, types of motion and cluster sizes of single particles detected by fluorescence microscopy.

Particle tracking on a video sequence and the posterior analysis of their trajectories is nowadays a common operation in many biological studies. Using ...

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

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