M.K.K. thanks the U.K.'s Engineering and Physical Science Research Council (EPSRC) Life Sciences Interface program for a personal Fellowship. We would also like to acknowledge funding by the U.K.'s Biotechnology and Biological Sciences Research Council (BBSRC).

The protocols for FLIM sample preparation do not differ from those for confocal or wide-field intensity-based fluorescence microscopy. The data acquisition is followed by the main task of data analysis, i.e. extracting the fluorescence lifetimes from the raw data. Once these have been obtained, data interpretation helps to verify or falsify hypotheses.
1. Staining cells with molecular rotors
<ol>
	<li>Prepare a stock solution (10 ml) by dissolving approximately 1 mg/ml of the dye in an appropriate solvent (e.g. methanol for BODIPY-C12)6,7 using an accurate balance and a pipette.</li>
	<li>The cells (a model cancer cell line, HeLa in our case) to be stained are grown on in a multiwell plate with a coverslide underside for microscopy, in an incubator at 37 &deg;C with a 5 % CO2 atmosphere until ~ 80% confluent.</li>
	<li>Add 10 - 20 &mu;l of the stock solution to the living cells growing in a multi-well plate (SmartSlide 50 micro-incubation system, Wafergen) in 4 ml of Opti-MEM medium (GIBCO) per well for a 6-well plate. This yields a micro-molar dye concentration in the well.</li>
	<li>Return the multi-well plate to an incubator at 37 &deg;C with a 5 % CO2 atmosphere for 10-45 mins for staining.</li>
	<li>Remove the multiwell plate from the incubator and wash the cells 3-4 times with 4 ml optically clear cell culture medium (e.g. Opti-MEM) to remove excess dye.</li>
	<li>Transfer the multiwell plate to the microscope stage and connect to a temperature controller / 5 % CO2 gas inlet as required, in preparation for imaging.</li>
</ol>
2. FLIM of fluorescent molecular rotors in cells
<ol>
	<li>Place the sample on the microscope stage and obtain a transmission and fluorescence image to identify fluorescent cells. A schematic diagram of the experimental set-up is shown in Fig. 1.Verify that the fluorescence emanates from the locations expected (e.g. cell membrane, cytoplasm). Obtain a fluorescence emission spectrum, and verify that it is that of the dye or protein expected, in this case the spectrum of the molecular rotor. As a negative control, image a non-stained sample and verify that it does not fluoresce. Although this step is not essential specifically for FLIM, it is good practice in general and does help to verify that the sample is what you think it is.</li>
	<li>Switch to FLIM mode - this is easily accomplished by moving a mirror out of the fluorescence detection beam path ("external detector" button on "beam path setting" panel on the Leica TCS SP2 acquisition control software). An appropriate fluorescence emission filter to block any exciting light from reaching the detector must be in the fluorescence detection beampath.</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/2925/2925fig1.jpg" /> 
Figure 1. Experimental arrangement for time-domain FLIM using a confocal laser scanning microscope.
<ol start="3">
	<li>Scan the sample and check, on the computer controlling the FLIM acquisition, that the detector count rate (black bar labeled CFD on acquisition control software of the Becker &amp; Hickl SPC 830 board) is no more than about 1% of the laser repetition rate (green bar labeled SYNC acquisition control software). If it is, reduce the laser excitation intensity, e.g. by placing a neutral density filter in the laser beam path, to avoid collecting pile-up distorted fluorescence decay curves.</li>
	<li>Acquire a FLIM image, typically for 3-5 min, stop scanning and save the raw data (a 3D data "cube" consisting of spatial coordinates x and y, and time).</li>
	<li>Open the raw data in the fluorescence decay analysis software package, for example TRI-214 or commercial software, to display the fluorescence intensity image. This is simply the integrated fluorescence decay, i.e. the area under the fluorescence decay curve, in each pixel.</li>
	<li>Select a typical pixel by placing the cursor on it, and inspect the fluorescence decay in that pixel. If the peak count is below 100, use spatial binning of pixels. The counts of adjacent pixels (e.g. 3x3 or 5x5) are added into the central pixel, so that a higher peak count is obtained there. This provides a higher statistical accuracy for the next step. Alternatively, the measurement could be repeated for a longer acquisition time (step 5). For 30-50min, an approximately 10 times higher peak count (and total counts) is obtained, but this is far too long an acquisition time for most biological samples because of the danger of introducing artifacts due to sample movement, microscope drift, phototoxicity and photobleaching.</li>
	<li>Select a global pixel threshold value (above which the decay in a pixel is fitted) and apply a single exponential decay fit to the image. The result yields a fluorescence lifetime for each pixel above the threshold, which is then encoded in color. Each pixel is colored with the result of the fit, and a FLIM map is obtained. Check the reduced chi-squared values for various pixels - around 1 (and up to 1.3) indicates a good fit. Inspect the corresponding residuals, which should be randomly distributed around zero.</li>
	<li>The fluorescence lifetime histogram plots how often certain fluorescence lifetimes occur versus the fluorescence lifetime itself. Adjust the colour range such that the fluorescence lifetime distribution fits into the colour range.</li>
	<li>If a monoexponential fit does not yield a chi-squared value of around 1 (and up to 1.3), and there is a systematic deviation of the residuals from zero, a more sophisticated model is required. For example, try fitting a double exponential model to the fluorescence decays, to account for two different environments the probe may be in. The fit will also yield the pre-exponential factors or amplitudes which give an indication of the relative amount of dye in one environment or the other. Alternatively, a stretched exponential function may be appropriate to account for a distribution of fluorescence lifetimes.</li>
	<li>The results for the fluorescence lifetimes, pre-exponential factors, and the lifetime ratio and the pre-exponential factor ratio for each pixel can then be encoded in color. Each pixel is coloured according to its value, and contrast due to fluorescence lifetimes, pre-exponential factors and their ratios is obtained. Again, check the reduced chi-squared values (which can also be encoded in colour and displayed as an image) - around 1 (and up to 1.3) indicates a good fit. Inspect the residuals, which should be randomly distributed around zero.</li>
	<li>Fluorescence lifetime histograms should accompany all images for easy visualisation of average fluorescence lifetime values, and the fluorescence lifetime distribution.</li>
</ol>
3. Representative Results
Fluorescence decays measured for the fluorescent molecular rotor at increasing viscosity in methanol/glycerol mixtures are shown in Fig. 2. The fluorescence decays are monoexponential, and the fluorescence lifetime varies markedly as a function of viscosity. It increases from around 300 ps in methanol (viscosity 0.6 cP) to 3.4 ns in 95% glycerol (viscosity 950 cP).
<img alt="Figure 2" src="/files/ftp_upload/2925/2925fig2.jpg" /> 
Figure 2. Fluorescence decay profiles for BODIPY-C12 in methanol/glycerol mixtures of varying viscosity.6
The logarithmic calibration plot of fluorescence lifetime &tau; versus viscosity &eta; for the fluorescent molecular rotor is shown in Fig. 3. It is a straight line as demanded by the F&ouml;rster Hoffman equation9
<img src="/files/ftp_upload/2925/2925eq1.jpg" alt="Equation 1" />
where k0 is the radiative rate constant, and z and x are constants, with 0&lt;x&lt;1. Taking the logarithm on both sides yields
<img src="/files/ftp_upload/2925/2925eq2.jpg" alt="Equation 2" />
where x is the gradient of the straight line.
<img alt="Figure 3" src="/files/ftp_upload/2925/2925fig3.jpg" /> 
Figure 3. A plot of log fluorescence lifetime vs log viscosity for BODIPY-C12 yields a straight line in accordance with the F&ouml;rster-Hoffmann equation.6
Following incubation of living cells with the fluorescent molecular rotor a punctate dye distribution is observed in the fluorescence images. FLIM images of HeLa cells incubated with a meso-substituted BODIPY dye are shown in Fig. 4. The fluorescence decays in every pixel of the image can be adequately fitted using a single exponential decay model.
<img alt="Figure 4" src="/files/ftp_upload/2925/2925fig4.jpg" /> 
Figure 4. (a) Fluorescence intensity and (b) FLIM images of HeLa cells stained with BODIPY-C12. The bright, punctuate regions exhibit a shorter lifetime than other regions. This shorter liftime corresponds to a lower viscosity in the puncta, probably lipid droplets, according to the F&ouml;rster-Hoffmann equation.
By plotting the lifetimes extracted from every pixel, we obtain a fluorescence lifetime histogram of the whole image as shown in Fig. 5.
<img alt="Figure 5" src="/files/ftp_upload/2925/2925fig5.jpg" /> 
Figure 5. Histograms of fluorescence lifetimes from FLIM images of HeLa cells stained with meso-substituted BODIPY molecular rotors.

<ol>
	<li>Luby-Phelps, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cytoarchitecture+and+physical+properties+of+cytoplasm:+Volume,+viscosity.+diffusion,+intracellular+surface+area.">Cytoarchitecture and physical properties of cytoplasm: Volume, viscosity. diffusion, intracellular surface area.</a> International Review of Cytology - a Survey of Cell Biology. , 192-1189 (2000).</li><li>Stutts, M. J., Canessa, C. M., Olsen, J. C., Hamrick, M., Cohn, J. A., Rossier, B. C., Boucher, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CFTR+as+a+CAMP-dependent+regulator+of+sodium+channels.">CFTR as a CAMP-dependent regulator of sodium channels.</a> Science. 269, 847-850 (1995).</li><li>Dondorp, A. M., Angus, B. J., Hardeman, M. R., Chotivanich, K. T., Silamut, K., Ruangveerayuth, R., Kager, P. A., White, N. J., Vreeken, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prognostic+significance+of+reduced+red+blood+cell+deformability+in+severe+falciparum+malaria.">Prognostic significance of reduced red blood cell deformability in severe falciparum malaria.</a> Am. J. Trop. Med. Hyg. 57, 507-511 (1997).</li><li>Haidekker, M. A., Nipper, M., Mustafic, A., Lichlyter, D., Dakanali, M., Theodorakis, E. A., Demchenko, A. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Advanced Fluorescence Reporters in Chemistry and Biology I. Fundamentals and Molecular Design. 8, 267-308 (2010).</li><li>Haidekker, M. A., Theodorakis, E. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Environment-sensitive+behavior+of+fluorescent+molecular+rotors.">Environment-sensitive behavior of fluorescent molecular rotors.</a> J. Biol. Eng. 4, (2010).</li><li>Kuimova, M. K., Yahioglu, G., Levitt, J. A., Suhling, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+Rotor+Measures+Viscosity+of+Live+Cells+via+Fluorescence+Lifetime+Imaging.">Molecular Rotor Measures Viscosity of Live Cells via Fluorescence Lifetime Imaging.</a> Journal of the American Chemical Society. 130, 6672-6673 (2008).</li><li>Levitt, J. A., Kuimova, M. K., Yahioglu, G., Chung, P. 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Fluores. 15, 377-413 (2005).</li><li>Becker, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Advanced Time-Correlated Single Photon Counting Techniques. , (2005).</li><li>O'Connor, D. V., Phillips, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Time-correlated single-photon counting. , (1984).</li><li>Suhling, K., French, P. M. W., Phillips, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time-resolved+fluorescence+microscopy.">Time-resolved fluorescence microscopy.</a> Photochem. Photobiol. Sci. 4, 13-22 (2005).</li><li>Barber, P. R., Ameer-Beg, S. M., Gilbey, J., Carlin, L. M., Keppler, M. D., Ng, T. 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No conflicts of interest declared.

FLIM offers some key advantages over intensity-based fluorescence imaging. It can report on photophysical events that are difficult or impossible to observe by fluorescence intensity imaging, because it can separate them from fluorophore concentration effects. This is particularly useful for mapping intracellular viscosity by imaging fluorescent molecular rotors. The fluorescence lifetime can readily be converted into a viscosity using a calibration graph, as shown in Fig. 3, independent of the concentration of fluorescent molecular rotors.
In FLIM there may be artifacts that may complicate data interpretation.10 Instrumental artifacts include scattered light which will show up as a peak on top of the beginning of the fluorescence decay and may be confused with a short decay time, or a small peak after the IRF which may be caused by reflections inside the microscope. These scattered light artifacts can be identified as such because they can be distinguished with spectral discrimination &#x2013; they are always at the same wavelength as the exciting light. Remembering that in air, light travels 30 cm in 1 nanosecond helps to pinpoint the origin of reflections. 
Filter or glass fluorescence could also cause an artifact, especially at low sample fluorescence, but this can easily be identified by taking a measurement without the sample: if a decay is obtained under these circumstances, it is due to the instrument and has nothing to do with the sample! On the other hand, note that sample autofluorescence may also contribute to a fluorescence decay. 
In time-correlated single photon counting (TCSPC), time-to-amplitude converter (TAC) non-linearities may cause poor fits, but can be identified by blocking the excitation and shining ambient light, e.g. from the transmitted light source onto the sample and measuring the timing. A constant background should be obtained in each pixel of the image. Regions where deviations from a constant background occur, will never yield a good fit and should be avoided for the measurement if they cannot be eliminated by adjusting the parameters for the TCSPC card.
One infamous artifact in TCSPC is photon pile-up which is caused by too high a photon detection rate.11,12 This leads to only the first photon being timed, ignoring any subsequent photons because the electronics are busy timing and processing the first photon. Pile-up leads to a shortening of the fluorescence lifetime, and the best way to avoid this is to keep the photon count rate at around 1% of the laser repetition rate. 
Outlook
There are various implementations of FLIM, and, depending on the application, each has its advantages and drawbacks.13 The ideal fluorescence microscope would acquire the entire multidimensional fluorescence emission contour of intensity, position, lifetime, wavelength and polarization in a single measurement, with single photon sensitivity, maximum spatial resolution and minimum acquisition time. There is presently no technology with this unique combination of features, and to build one remains a challenge for instrumentation developers. The application of new physical techniques to important problems in cell biology is often the path to unexpected discoveries, and there is a long way to go before we are close to saturating the capabilities of fluorescence imaging for cell biology. Indeed, imaging fluorescence parameters such as lifetime, spectrum and polarization, as well as imaging more rapidly in 3D at higher spatial resolution, are certain to reveal new aspects in cell biology.

Sample with fluorescent molecular rotors
Hardware:
 inverted Leica TCS SP2 confocal scanning microscope 
Coherent Mira 900 Ti:Sapphire femtosecond laser with a Verdi V6 pump laser or Hamamatsu PLP-10 470 picosecond pulsed diode laser excitation sources
Becker &amp; Hickl SPC 830 board in 3GHz, pentium IV, 1GB RAM computer with Windows XP
cooled Becker &amp; Hickl PMC100-01 detector head based on Hamamatsu H5773P-01 photomultipliers, mounted on microscope's X1 port, or hybrid detectors
DCC 100 detector control module
Software:
 TRI-214 or SPCImage 2.8 by Becker &amp; Hickl

fluorescence lifetime imaging of molecular rotors in living cells

Diffusion is often an important rate-determining step in chemical reactions or biological processes and plays a role in a wide range of intracellular events. Viscosity is one of the key parameters affecting the diffusion of molecules and proteins, and changes in viscosity have been linked to disease and malfunction at the cellular level.1-3 While methods to measure the bulk viscosity are well developed, imaging microviscosity remains a challenge. Viscosity maps of microscopic objects, such as single cells, have until recently been hard to obtain. Mapping viscosity with fluorescence techniques is advantageous because, similar to other optical techniques, it is minimally invasive, non-destructive and can be applied to living cells and tissues.
Fluorescent molecular rotors exhibit fluorescence lifetimes and quantum yields which are a function of the viscosity of their microenvironment.4,5 Intramolecular twisting or rotation leads to non-radiative decay from the excited state back to the ground state. A viscous environment slows this rotation or twisting, restricting access to this non-radiative decay pathway. This leads to an increase in the fluorescence quantum yield and the fluorescence lifetime. Fluorescence Lifetime Imaging (FLIM) of modified hydrophobic BODIPY dyes that act as fluorescent molecular rotors show that the fluorescence lifetime of these probes is a function of the microviscosity of their environment.6-8 A logarithmic plot of the fluorescence lifetime versus the solvent viscosity yields a straight line that obeys the F&ouml;rster Hoffman equation.9 This plot also serves as a calibration graph to convert fluorescence lifetime into viscosity.
Following incubation of living cells with the modified BODIPY fluorescent molecular rotor, a punctate dye distribution is observed in the fluorescence images. The viscosity value obtained in the puncta in live cells is around 100 times higher than that of water and of cellular cytoplasm.6,7 Time-resolved fluorescence anisotropy measurements yield rotational correlation times in agreement with these large microviscosity values. Mapping the fluorescence lifetime is independent of the fluorescence intensity, and thus allows the separation of probe concentration and viscosity effects. 
In summary, we have developed a practical and versatile approach to map the microviscosity in cells based on FLIM of fluorescent molecular rotors.

Watch this Scientific Journal Video about Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells at JoVE.com

Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells

Fluorescence Lifetime Imaging (FLIM) has emerged as a key technique to image the environment and interaction of specific proteins and dyes in living cells. FLIM of fluorescent molecular rotors allows mapping of viscosity in living cells.

Diffusion is often an important rate-determining step in chemical reactions or biological processes and plays a role in a wide range of intracellular ...

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24.8K Views.  King's College London. Fluorescence Lifetime Imaging (FLIM) has emerged as a key technique to image the environment and interaction of specific proteins and dyes in living cells. FLIM of fluorescent molecular rotors allows mapping of viscosity in living cells.

Video: Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells

Measuring the Mechanical Properties of Living Cells Using Atomic Force Microscopy

Mechanical properties of cells and extracellular matrix (ECM) play important roles in many biological processes including stem cell differentiation, tumor formation, and wound healing. Changes in stiffness of cells and ECM are often signs of changes in cell physiology or diseases in tissues. Hence, cell stiffness is an index to evaluate the status of cell cultures. Among the multitude of methods applied to measure the stiffness of cells and tissues, micro-indentation using an Atomic Force Microscope (AFM) provides a way to reliably measure the stiffness of living cells. This method has been widely applied to characterize the micro-scale stiffness for a variety of materials ranging from metal surfaces to soft biological tissues and cells. The basic principle of this method is to indent a cell with an AFM tip of selected geometry and measure the applied force from the bending of the AFM cantilever. Fitting the force-indentation curve to the Hertz model for the corresponding tip geometry can give quantitative measurements of material stiffness. This paper demonstrates the procedure to characterize the stiffness of living cells using AFM. Key steps including the process of AFM calibration, force-curve acquisition, and data analysis using a MATLAB routine are demonstrated. Limitations of this method are also discussed.

This paper demonstrates a protocol to characterize the mechanical properties of living cells by means of microindentation using an Atomic Force Microscope (AFM).

Mechanical  properties of cells and extracellular matrix (ECM) play important roles in many  biological processes including stem cell differentiation, ...

3D Orbital Tracking in a Modified Two-photon Microscope: An Application to the Tracking of Intracellular Vesicles

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a modified two-photon microscope1. As opposed to conventional approaches (raster scan or wide field based on a stack of frames), the 3D orbital tracking allows to localize and follow with a high spatial (10 nm accuracy) and temporal resolution (50 Hz frequency response) the 3D displacement of a moving fluorescent particle on length-scales of hundreds of microns2. The method is based on a feedback algorithm that controls the hardware of a two-photon laser scanning microscope in order to perform a circular orbit around the object to be tracked: the feedback mechanism will maintain the fluorescent object in the center by controlling the displacement of the scanning beam3-5. To demonstrate the advantages of this technique, we followed a fast moving organelle, the lysosome, within a living cell6,7. Cells were plated according to standard protocols, and stained using a commercially lysosome dye. We discuss briefly the hardware configuration and in more detail the control software, to perform a 3D orbital tracking experiment inside living cells. We discuss in detail the parameters required in order to control the scanning microscope and enable the motion of the beam in a closed orbit around the particle. We conclude by demonstrating how this method can be effectively used to track the fast motion of a labeled lysosome along microtubules in 3D within a live cell. Lysosomes can move with speeds in the range of 0.4-0.5 &#181;m/sec, typically displaying a directed motion along the microtubule network8.

In this video protocol we track - at high speed and in three dimensions - fluorescently labeled lysosomes within living cells, using the orbital tracking method in a modified two-photon microscope.

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a ...

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 ...

Electrotaxis Studies of Lung Cancer Cells using a Multichannel Dual-electric-field Microfluidic Chip

The behavior of directional cell migration under a direct current electric-field (dcEF) is referred to as electrotaxis. The significant role of physiological dcEF in guiding cell movement during embryo development, cell differentiation, and wound healing has been demonstrated in many studies. By applying microfluidic chips to an electrotaxis assay, the investigation process is shortened and experimental errors are minimized. In recent years, microfluidic devices made of polymeric substances (e.g., polymethylmethacrylate, PMMA, or acrylic) or polydimethylsiloxane (PDMS) have been widely used in studying the responses of cells to electrical stimulation. However, unlike the numerous steps required to fabricate a PDMS device, the simple and rapid construction of the acrylic micro&#64258;uidic chip makes it suitable for both device prototyping and production. Yet none of the reported devices facilitate the efficient study of the simultaneous chemical and dcEF effects on cells. In this report, we describe our design and fabrication of an acrylic-based multichannel dual-electric-field (MDF) chip to investigate the concurrent effect of chemical and electrical stimulation on lung cancer cells. The MDF chip provides eight combinations of electrical/chemical stimulations in a single test. The chip not only greatly shortens the required experimental time but also increases accuracy in electrotaxis studies.

Many microfluidic devices have been developed for use in the study of electrotaxis. Yet, none of these chips allows the efficient study of the simultaneous chemical and electric-field (EF) effects on cells. We developed a polymethylmethacrylate-based device that offers better-controlled coexisting EF and chemical stimulation for use in electrotaxis research.

The behavior of directional cell migration under a direct current electric-field (dcEF) is referred to as electrotaxis. The significant role of ...

Optical Control of Living Cells Electrical Activity by Conjugated Polymers

Hybrid interfaces between organic semiconductors and living tissues represent a new tool for in-vitro and in-vivo applications. In particular, conjugated polymers display several optimal properties as substrates for biological systems, such as good biocompatibility, excellent mechanical properties, cheap and easy processing technology, and possibility of deposition on light, thin and flexible substrates. These materials have been employed for cellular interfaces like neural probes, transistors for excitation and recording of neural activity, biosensors and actuators for drug release. Recent experiments have also demonstrated the possibility to use conjugated polymers for all-optical modulation of the electrical activity of cells. Several in-vitro study cases have been reported, including primary neuronal networks, astrocytes and secondary line cells. Moreover, signal photo-transduction mediated by organic polymers has been shown to restore light sensitivity in degenerated retinas, suggesting that these devices may be used for artificial retinal prosthesis in the future. All in all, light sensitive conjugated polymers represent a new approach for optical modulation of cellular activity.
In this work, all the steps required to fabricate a bio-polymer interface for optical excitation of living cells are described. The function of the active interface is to transduce the light stimulus into a modulation of the cell membrane potential. As a study case, useful for in-vitro studies, a polythiophene thin film is used as the functional, light absorbing layer, and Human Embryonic Kidney (HEK-293) cells are employed as the biological component of the interface. Practical examples of successful control of the cell membrane potential upon stimulation with light pulses of different duration are provided. In particular, it is shown that both depolarizing and hyperpolarizing effects on the cell membrane can be achieved depending on the duration of the light stimulus. The reported protocol is of general validity and can be straightforwardly extended to other biological preparations.

A method for stimulation of in-vitro cell cultures electrical activity with visible light, based on the use of organic semiconducting polymers is described.

Hybrid interfaces between organic semiconductors and living tissues represent a new tool for in-vitro and in-vivo applications. In particular, conjugated ...

Conducting Multiple Imaging Modes with One Fluorescence Microscope

Fluorescence microscopy is a powerful tool to detect biological molecules in situ and monitor their dynamics and interactions in real-time. In addition to conventional epi-fluorescence microscopy, various imaging techniques have been developed to achieve specific experimental goals. Some of the widely used techniques include single-molecule fluorescence resonance energy transfer (smFRET), which can report conformational changes and molecular interactions with angstrom resolution, and single-molecule detection-based super-resolution (SR) imaging, which can enhance the spatial resolution approximately ten&#160;to twentyfold compared to diffraction-limited microscopy. Here we present a customer-designed integrated system, which merges multiple imaging methods in one microscope, including conventional epi-fluorescent imaging, single-molecule detection-based SR imaging, and multi-color single-molecule detection, including smFRET imaging. Different imaging methods can be achieved easily and reproducibly by switching optical elements. This set-up is easy to adopt by any research laboratory in biological sciences with a need for routine and diverse imaging experiments at a reduced cost and space relative to building separate microscopes for individual purposes.

Here we present a practical guide of building an integrated microscopy system, which merges conventional epi-fluorescent imaging, single-molecule detection-based super-resolution imaging, and multi-color single-molecule detection, including single-molecule fluorescence resonance energy transfer imaging, into one set-up in a cost-efficient way.

Fluorescence microscopy is a powerful tool to detect biological molecules in situ and monitor their dynamics and interactions in real-time. In addition to ...

Measurement of Force-Sensitive Protein Dynamics in Living Cells Using a Combination of Fluorescent Techniques

Cells sense and respond to physical cues in their environment by converting mechanical stimuli into biochemically-detectable signals in a process called mechanotransduction. A crucial step in mechanotransduction is the transmission of forces between the external and internal environments. To transmit forces, there must be a sustained, unbroken physical linkage created by a series of protein-protein interactions. For a given protein-protein interaction, mechanical load can either have no effect on the interaction, lead to faster disassociation of the interaction, or even stabilize the interaction. Understanding how molecular load dictates protein turnover in living cells can provide valuable information about the mechanical state of a protein, in turn elucidating its role in mechanotransduction. Existing techniques for measuring force-sensitive protein dynamics either lack direct measurements of protein load or rely on the measurements performed outside of the cellular context. Here, we describe a protocol for the F&#246;rster resonance energy transfer-fluorescence recovery after photobleaching (FRET-FRAP) technique, which enables the measurement of force-sensitive protein dynamics within living cells. This technique is potentially applicable to any FRET-based tension sensor, facilitating the study of force-sensitive protein dynamics in variety of subcellular structures and in different cell types.

Here, we present a protocol for the simultaneous use of F&#246;rster resonance energy transfer-based tension sensors to measure protein load and fluorescence recovery after photobleaching to measure protein dynamics enabling the measurement of force-sensitive protein dynamics within living cells.

Cells sense and respond to physical cues in their environment by converting mechanical stimuli into biochemically-detectable signals in a process called ...

Visualizing Adhesion Formation in Cells by Means of Advanced Spinning Disk-Total Internal Reflection Fluorescence Microscopy

In living cells, processes such as adhesion formation involve extensive structural changes in the plasma membrane and the cell interior. In order to visualize these highly dynamic events, two complementary light microscopy techniques that allow fast imaging of live samples were combined: spinning disk microscopy (SD) for fast and high-resolution volume recording and total internal reflection fluorescence (TIRF) microscopy for precise localization and visualization of the plasma membrane. A comprehensive and complete imaging protocol will be shown for guiding through sample preparation, microscope calibration, image formation and acquisition, resulting in multi-color SD-TIRF live imaging series with high spatio-temporal resolution. All necessary image post-processing steps to generate multi-dimensional live imaging datasets, i.e. registration and combination of the individual channels, are provided in a self-written macro for the open source software ImageJ. The imaging of fluorescent proteins during initiation and maturation of adhesion complexes, as well as the formation of the actin cytoskeletal network, was used as a proof of principle for this novel approach. The combination of high resolution 3D microscopy and TIRF provided a detailed description of these complex processes within the cellular environment and, at the same time, precise localization of the membrane-associated molecules detected with a high signal-to-background ratio.

An advanced microscope that permit fast and high-resolution imaging of both, the isolated plasma membrane and the surrounding intracellular volume, will be presented. The integration of spinning disk and total internal reflection fluorescence microscopy in one setup allows live imaging experiments at high acquisition rates up to 3.5 s per image stack.

In living cells, processes such as adhesion formation involve extensive structural changes in the plasma membrane and the cell interior. In order to ...

Lipidico Injection Protocol for Serial Crystallography Measurements at the Australian Synchrotron

A facility for performing serial crystallography measurements has been developed at the Australian synchrotron. This facility incorporates a purpose built high viscous injector, Lipidico, as part of the macromolecular crystallography (MX2) beamline to measure large numbers of small crystals at room temperature. The goal of this technique is to enable crystals to be grown/transferred to&#160;glass syringes to be used directly in the injector for serial crystallography data collection. The advantages of this injector include the ability to respond rapidly&#160;to changes in the flow rate without interruption of the stream. Several limitations for this high viscosity injector (HVI) exist which include a restriction on the allowed sample viscosities to &#62;10 Pa.s. Stream stability can also potentially be an issue depending on the specific properties of the sample. A detailed protocol for how to set up samples and operate the injector for serial crystallography measurements at the Australian synchrotron is presented here. The method demonstrates preparation of the sample, including the transfer of lysozyme crystals into a high viscous media (silicone grease), and the operation of the injector for data collection at MX2.

The goal of this protocol is to demonstrate how to prepare serial crystallography samples for data collection on a high viscous injector, Lipidico, recently commissioned at the Australian synchrotron.

A facility for performing serial crystallography measurements has been developed at the Australian synchrotron. This facility incorporates a purpose built ...

Controlled Strain of 3D Hydrogels under Live Microscopy Imaging

External forces are an important factor in tissue formation, development, and maintenance. The effects of these forces are often studied using specialized in vitro stretching methods. Various available systems use 2D substrate-based stretchers, while the accessibility of 3D techniques to strain soft hydrogels, is more restricted. Here, we describe a method that allows external stretching of soft hydrogels from their circumference, using an elastic silicone strip as the sample carrier. The stretching system utilized in this protocol is constructed from 3D-printed parts and low-cost electronics, making it simple and easy to replicate in other labs. The experimental process begins with polymerizing thick (&#62;100 &#956;m) soft fibrin hydrogels (Elastic Modulus of ~100 Pa) in a cut-out at the center of a silicone strip. Silicone-gel constructs are then attached to the printed-stretching device and placed on the confocal microscope stage. Under live microscopy the stretching device is activated, and the gels are imaged at various stretch magnitudes. Image processing is then used to quantify the resulting gel deformations, demonstrating relatively homogenous strains and fiber alignment throughout the gel&#8217;s 3D thickness (Z-axis). Advantages of this method include the ability to strain extremely soft hydrogels in 3D while executing in situ microscopy, and the freedom to manipulate the geometry and size of the sample according to the user&#8217;s needs. Additionally, with proper adaptation, this method can be used to stretch other types of hydrogels (e.g., collagen, polyacrylamide or polyethylene glycol) and can allow for analysis of cells and tissue response to external forces under more biomimetic 3D conditions.

The presented method involves uniaxial stretching of 3D soft hydrogels embedded in silicone rubber while allowing live confocal microscopy. Characterization of the external and internal hydrogel strains as well as fiber alignment are demonstrated. The device and protocol developed can assess the response of cells to various strain regimes.

External forces are an important factor in tissue formation, development, and maintenance. The effects of these forces are often studied using specialized ...