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

Summary

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.

Abstract

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’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 µm-sized membrane regions in the micro-to-milli-second time range.

Introduction

Starting from the original “fluid mosaic” model by Singer and Nicolson, the picture of cellular plasma membrane has been continuously updated during the last decades in order to include the emerging role of cytoskeleton and lipid domains^1,2.

The first observations were obtained by fluorescent recovery after photobleaching (FRAP) unveiling that a significant fraction of membrane proteins is immobile^3-5. These pioneering studies, although very informative, suffered from the relatively poor resolution in space (microns) and time (seconds) of FRAP setups. Also, being an ensemble averaging measurement, FRAP lacks in giving ....

Protocol

1. System Calibration

1. Point Spread Function (PSF) calibration
   1. Dilute 10 µl of 30 nm fluorescent bead solution (about 5 μM) in 90 µl of distilled water and then sonicate the solution for 20 min. Cut a square (1 cm x 1 cm) piece of agarose gel (3%) and deposit 10 µl of the solution on the top of the gel. Overturn the piece of gel on the bottom glass of a 2 cm Petri dish and squeeze the drop on the glass.
   2. Turn on the acquisition setup, put the sample in the holder, set the camera exposure and EMgain (100 msec and 1,000 are good parameters but optimize according to the system) and wait for the camera to cool down.

Results

In order to calibrate the instrumental waist, the image of a single fluorescent nano-bead can be measure as described in Protocol step 1.1. A typical fluorescent image of these beads is presented in Figure 1. The fitting of intensity distribution by a 2D Gaussian function gives back good residuals and allows measuring the instrumental waist at 270 nm. This value is in good agreement with the expected diffraction limit estimated by the Rayleigh equation. This calibration is not necessary for the measureme.......

Discussion

Single particle tracking (SPT) represents one of the most common strategies to study molecular dynamics and it has the great advantage of measuring particle trajectories. This in turn allows probing the behavior of even few labeled particles in a complex system. However, to reach this advantage SPT typically needs a low density of the probe and very bright labels. Particularly, to gain high temporal resolution (μsec range) inorganic probe are usually required (e.g., quantum dots or metal nanoparticles): in .......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
iXon Ultra 897	Andor	DU-897U-CS0
Solis	Andor
CHO-K1	ATCC	CCL-61
ATTO 488 labeled PPE	ATTO-TEC GmbH	AD 488-151
DOPE	Avanti Polar Lipids, Inc.	850725
DOTAP	Avanti Polar Lipids, Inc.	890890
100x Penicillin-Streptomycin-Glutamine	Gibco	10378-016
DMEM/F-12	Gibco	21331
FBS	Gibco	10082147
HEPES	Gibco	15630-106
PBS	Gibco	10010-023
SimFCS 3.0	Globals Software		the software can be downloaded here: http://www.lfd.uci.edu/globals/
DMI6000 with TIRF modulus	Leica
LAS AF	Leica
Lipofectamine 2000	Lipofectamine	11668019
Matlab	MathWork
ImageJ	NIH
[header]
C-terminal GFP tagged Tranferrin Receptor	OriGene	RG200980
Agar	Sigma Aldrich	A5306
Chloroform	Sigma Aldrich	528730
Latex beads, fluorescent yellow-green, 30 nm	Sigma Aldrich	L5155
SONICA Ultrasonic Cleaners	SOLTEC	ETH S3
Petri Dishes	Willco	GWSt-3522
Bio-Format importer for Matlab			http://www.openmicroscopy.org/site/support/bio-formats5/users/matlab/
ICS-MatLab Tools			https://www.cellmigration.org/resource/imaging/software/ICSMATLAB_28-02-06.zip
Simulation by Matlab Tutorial			https://www.cellmigration.org/resource/imaging/icsmatlab/ICSTutorial.html
Simulation by SimFCS Tutorial			https://www.cellmigration.org/resource/imaging/ppt-pdf/RICS%20Simulations.ppt