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 °C with a 5 % CO2 atmosphere until ~ 80% confluent.</li>
	<li>Add 10 - 20 μl 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 °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="Fluorescence lifetime imaging system diagram with TCSPC for decay analysis and sample excitation." src="/files/ftp_upload/2925/2925fig1.jpg" data-altupdatedat="1747911167000" data-alt="Figure 1"> 
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="Fluorescence decay graph, normalized intensity vs. time; viscosity effects, spectroscopic analysis." src="/files/ftp_upload/2925/2925fig2.jpg" data-altupdatedat="1747911167000" data-alt="Figure 2"> 
Figure 2. Fluorescence decay profiles for BODIPY-C12 in methanol/glycerol mixtures of varying viscosity.6
The logarithmic calibration plot of fluorescence lifetime τ versus viscosity η for the fluorescent molecular rotor is shown in Fig. 3. It is a straight line as demanded by the Förster Hoffman equation9
<img src="/files/ftp_upload/2925/2925eq1.jpg" alt="Static equilibrium formula, τ = z/(k₀ηˣ), symbol in physics diagram for force equilibrium analysis." data-altupdatedat="1747911167000" data-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="Arrhenius equation for reaction rate; mathematical formula in physical chemistry research." data-altupdatedat="1747911167000" data-alt="Equation 2">
where x is the gradient of the straight line.
<img alt="log τ vs log η linear relationship chart, data analysis, slope fitting, research graph" src="/files/ftp_upload/2925/2925fig3.jpg" data-altupdatedat="1747911167000" data-alt="Figure 3"> 
Figure 3. A plot of log fluorescence lifetime vs log viscosity for BODIPY-C12 yields a straight line in accordance with the Förster-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="Fluorescence lifetime imaging microscopy results showing cellular protein distribution, color scale 1000-2600ps." src="/files/ftp_upload/2925/2925fig4.jpg" data-altupdatedat="1747911167000" data-alt="Figure 4"> 
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 Förster-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="Frequency vs. lifetime graph; Gaussian fit; decay analysis; photonic spectroscopy results." src="/files/ftp_upload/2925/2925fig5.jpg" data-altupdatedat="1747911167000" data-alt="Figure 5"> 
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/pubmed?term=((Cytoarchitecture+and+physical+properties+of+cytoplasm%3A+Volume%2C+viscosity.+diffusion%2C+intracellular+surface+area%5BTitle%5D)+AND+%22International+Review+of+Cytology+-+a+Survey+of+Cell+Biology%22%5BJournal%5D)">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/pubmed?term=((CFTR+as+a+CAMP-dependent+regulator+of+sodium+channels%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">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/pubmed?term=((Prognostic+significance+of+reduced+red+blood+cell+deformability+in+severe+falciparum+malaria%5BTitle%5D)+AND+%22Am.+J.+Trop.+Med.+Hyg%22%5BJournal%5D)">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. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aHaidekker%2C+MA+%22Advanced+Fluorescence+Reporters+in+Chemistry+and+Biology+I.+Fundamentals+and+Molecular+Design%22">Advanced Fluorescence Reporters in Chemistry and Biology I. Fundamentals and Molecular Design</a>. Demchenko, A. P. 8, Springer. Berlin Heidelberg. 267-308 (2010).</li>
<li>Haidekker, M. A., Theodorakis, E. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Environment-sensitive+behavior+of+fluorescent+molecular+rotors%5BTitle%5D)+AND+%22J.+Biol.+Eng%22%5BJournal%5D)">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/pubmed?term=((Molecular+Rotor+Measures+Viscosity+of+Live+Cells+via+Fluorescence+Lifetime+Imaging%5BTitle%5D)+AND+%22Journal+of+the+American+Chemical+Society%22%5BJournal%5D)">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. H., Suhling, K., Phillips, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Membrane-Bound+Molecular+Rotors+Measure+Viscosity+in+Live+Cells+via+Fluorescence+Lifetime+Imaging%5BTitle%5D)+AND+%22Journal+of+Physical+Chemistry+C%22%5BJournal%5D)">Membrane-Bound Molecular Rotors Measure Viscosity in Live Cells via Fluorescence Lifetime Imaging.</a> Journal of Physical Chemistry C. 113, 11634-11642 (2009).</li>
<li>Hungerford, G., Allison, A., McLoskey, D., Kuimova, M. K., Yahioglu, G., Suhling, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Monitoring+Sol-to-Gel+Transitions+via+Fluorescence+Lifetime+Determination+Using+Viscosity+Sensitive+Fluorescent+Probes%5BTitle%5D)+AND+%22J.+Phys.+Chem.+B%22%5BJournal%5D)">Monitoring Sol-to-Gel Transitions via Fluorescence Lifetime Determination Using Viscosity Sensitive Fluorescent Probes.</a> J. Phys. Chem. B. 113, 12067-12074 (2009).</li>
<li>Förster, T., Hoffmann, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Die+Viskosit%C3%A4tsabh%C3%A4ngigkeit+der+Fluoreszenzquantenausbeuten+einiger+Farbstoffsysteme%5BTitle%5D)+AND+%22Zeitschrift+f%C3%BCr+Physikalische+Chemie+Neue+Folge%22%5BJournal%5D)">Die Viskositätsabhängigkeit der Fluoreszenzquantenausbeuten einiger Farbstoffsysteme.</a> Zeitschrift für Physikalische Chemie Neue Folge. 75, 63-76 (1971).</li>
<li>vandeVen, M., Ameloot, M., Valeur, B., Boens, N. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Pitfalls+and+Their+Remedies+in+Time-Resolved+Fluorescence+Spectroscopy+and+Microscopy%5BTitle%5D)+AND+%22J.+Fluores%22%5BJournal%5D)">Pitfalls and Their Remedies in Time-Resolved Fluorescence Spectroscopy and Microscopy.</a> J. Fluores. 15, 377-413 (2005).</li>
<li>Becker, W. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aBecker%2C+W+%22Advanced+Time-Correlated+Single+Photon+Counting+Techniques%22">Advanced Time-Correlated Single Photon Counting Techniques</a>. , Springer. (2005).</li>
<li>O'Connor, D. V., Phillips, D. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aO%27Connor%2C+DV+%22Time-correlated+single-photon+counting%22">Time-correlated single-photon counting</a>. , Academic Press. New York. (1984).</li>
<li>Suhling, K., French, P. M. W., Phillips, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Time-resolved+fluorescence+microscopy%5BTitle%5D)+AND+%22Photochem.+Photobiol.+Sci%22%5BJournal%5D)">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. C., Vojnovic, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multiphoton+time-domain+fluorescence+lifetime+imaging+microscopy%3A+practical+application+to+protein-protein+interactions+using+global+analysis%5BTitle%5D)+AND+%22Journal+of+the+Royal+Society+-+Interface%22%5BJournal%5D)">Multiphoton time-domain fluorescence lifetime imaging microscopy: practical application to protein-protein interactions using global analysis.</a> Journal of the Royal Society - Interface. 6, S93-S105 (2009).</li>
</ol>

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.

<table><tbody><tr><td colspan="4">&lt;p class=&quot;jove_content&quot;&gt;Sample with fluorescent molecular rotors&lt;/p&gt;&lt;p class=&quot;jove_step&quot;&gt;Hardware:&lt;/p&gt;&lt;p class=&quot;jove_content&quot;&gt; inverted Leica TCS SP2 confocal scanning microscope &lt;/p&gt;&lt;p class=&quot;jove_content&quot;&gt;Coherent Mira 900 Ti:Sapphire femtosecond laser with a Verdi V6 pump laser or Hamamatsu PLP-10 470 picosecond pulsed diode laser excitation sources&lt;/p&gt;&lt;p class=&quot;jove_content&quot;&gt;Becker &amp;amp; Hickl SPC 830 board in 3GHz, pentium IV, 1GB RAM computer with Windows XP&lt;/p&gt;&lt;p class=&quot;jove_content&quot;&gt;cooled Becker &amp;amp; Hickl PMC100-01 detector head based on Hamamatsu H5773P-01 photomultipliers, mounted on microscope&amp;rsquo;s X1 port, or hybrid detectors&lt;/p&gt;&lt;p class=&quot;jove_content&quot;&gt;DCC 100 detector control module&lt;/p&gt;&lt;p class=&quot;jove_step&quot;&gt;Software:&lt;/p&gt;&lt;p class=&quot;jove_content&quot;&gt; TRI-2&lt;sup&gt;14&lt;/sup&gt; or SPCImage 2.8 by Becker &amp;amp; Hickl&lt;/p&gt;</td></tr></tbody></table>

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 ...

fluorescence-lifetime-imaging-of-molecular-rotors-in-living-cells

Research

JoVE Journal

Bioengineering

25.2K 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

Fluorescence detection methods for microfluidic droplet platforms

The development of microfluidic platforms for performing chemistry and biology has in large part been driven by a range of potential benefits that accompany system miniaturisation. Advantages include the ability to efficiently process nano- to femoto- liter volumes of sample, facile integration of functional components, an intrinsic predisposition towards large-scale multiplexing, enhanced analytical throughput, improved control and reduced instrumental footprints.1
In recent years much interest has focussed on the development of droplet-based (or segmented flow) microfluidic systems and their potential as platforms in high-throughput experimentation.2-4 Here water-in-oil emulsions are made to spontaneously form in microfluidic channels as a result of capillary instabilities between the two immiscible phases. Importantly, microdroplets of precisely defined volumes and compositions can be generated at frequencies of several kHz. Furthermore, by encapsulating reagents of interest within isolated compartments separated by a continuous immiscible phase, both sample cross-talk and dispersion (diffusion- and Taylor-based) can be eliminated, which leads to minimal cross-contamination and the ability to time analytical processes with great accuracy. Additionally, since there is no contact between the contents of the droplets and the channel walls (which are wetted by the continuous phase) absorption and loss of reagents on the channel walls is prevented.
Once droplets of this kind have been generated and processed, it is necessary to extract the required analytical information. In this respect the detection method of choice should be rapid, provide high-sensitivity and low limits of detection, be applicable to a range of molecular species, be non-destructive and be able to be integrated with microfluidic devices in a facile manner. To address this need we have developed a suite of experimental tools and protocols that enable the extraction of large amounts of photophysical information from small-volume environments, and are applicable to the analysis of a wide range of physical, chemical and biological parameters. Herein two examples of these methods are presented and applied to the detection of single cells and the mapping of mixing processes inside picoliter-volume droplets. We report the entire experimental process including microfluidic chip fabrication, the optical setup and the process of droplet generation and detection.

Droplet-based microfluidic platforms are promising candidates for high throughput experimentation since they are able to generate picoliter, self-compartmentalized vessels inexpensively at kHz rates. Through integration with fast, sensitive and high resolution fluorescence spectroscopic methods, the large amounts of information generated within these systems can be efficiently extracted, harnessed and utilized.

The development of microfluidic platforms for performing chemistry and biology has in large part been driven by a range of potential benefits that ...

Probing Metabolism and Viscosity of Cancer Cells using Fluorescence Lifetime Imaging Microscopy

Viscosity is an important physical property of a biological membrane, as it is one of the key parameters for the regulation of morphological and physiological state of living cells. Plasma membranes of tumor cells are known to have significant alterations in their composition, structure, and functional characteristics. Along with dysregulated metabolism of glucose and lipids, these specific membrane properties help tumor cells to adapt to the hostile microenvironment and develop resistance to drug therapies. Here, we demonstrate the use of fluorescence lifetime imaging microscopy (FLIM) to sequentially image cellular metabolism and plasma membrane viscosity in live cancer cell culture. Metabolic assessments are performed by detecting fluorescence of endogenous metabolic cofactors, such as reduced nicotinamide adenine dinucleotide NAD(P)H and oxidized flavins. Viscosity is measured using a fluorescent molecular rotor, a synthetic viscosity-sensitive dye, with a strong fluorescence lifetime dependence on the viscosity of the immediate environment. In combination, these techniques enable us to better understand the links between membrane state and metabolic profile of cancer cells and to visualize the changes induced by chemotherapy.

Here, we demonstrate the use of fluorescence lifetime imaging microscopy (FLIM) to sequentially image cellular metabolism and plasma membrane viscosity in live cancer cell culture. Metabolic assessments are performed by detecting endogenous fluorescence. Viscosity is measured using a fluorescent molecular rotor.

Viscosity is an important physical property of a biological membrane, as it is one of the key parameters for the regulation of morphological and ...

Cancer Research

Simultaneous Interference Reflection and Total Internal Reflection Fluorescence Microscopy for Imaging Dynamic Microtubules and Associated Proteins

Several techniques have been employed for the direct visualization of cytoskeletal filaments and their associated proteins. Total-internal-reflection-fluorescence (TIRF) microscopy has a high signal-to-background ratio, but it suffers from photobleaching and photodamage of the fluorescent proteins. Label-free techniques such as interference reflection microscopy (IRM) and interferometric scattering microscopy (iSCAT) circumvent the problem of photobleaching but cannot readily visualize single molecules. This paper presents a protocol for combining IRM with a commercial TIRF microscope for the simultaneous imaging of microtubule-associated proteins (MAPs) and dynamic microtubules in vitro. This protocol allows for high-speed observation of MAPs interacting with dynamic microtubules. This improves on existing two-color TIRF setups by eliminating both the need for microtubule labeling and the need for several additional optical components, such as a second excitation laser. Both channels are imaged on the same camera chip to avoid image registration and frame synchronization problems. This setup is demonstrated by visualizing single kinesin molecules walking on dynamic microtubules.

We present a protocol for implementing interference-reflection microscopy and total-internal-reflection-fluorescence microscopy for the simultaneous imaging of dynamic microtubules and fluorescently labeled microtubule-associated proteins.

Several techniques have been employed for the direct visualization of cytoskeletal filaments and their associated proteins. ...

Biochemistry

Visualizing Intracellular SNARE Trafficking by Fluorescence Lifetime Imaging Microscopy

Soluble N-ethylmaleimide sensitive fusion protein (NSF) attachment protein receptor (SNARE) proteins are key for membrane trafficking, as they catalyze membrane fusion within eukaryotic cells. The SNARE protein family consists of about 36 different members. Specific intracellular transport routes are catalyzed by specific sets of 3 or 4 SNARE proteins that thereby contribute to the specificity and fidelity of membrane trafficking. However, studying the precise function of SNARE proteins is technically challenging, because SNAREs are highly abundant and functionally redundant, with most SNAREs having multiple and overlapping functions. In this protocol, a new method for the visualization of SNARE complex formation in live cells is described. This method is based on expressing SNARE proteins C-terminally fused to fluorescent proteins and measuring their interaction by F&#246;rster resonance energy transfer (FRET) employing fluorescence lifetime imaging microscopy (FLIM). By fitting the fluorescence lifetime histograms with a multicomponent decay model, FRET-FLIM allows (semi-)quantitative estimation of the fraction of the SNARE complex formation at different vesicles. This protocol has been successfully applied to visualize SNARE complex formation at the plasma membrane and at endosomal compartments in mammalian cell lines and primary immune cells, and can be readily extended to study SNARE functions at other organelles in animal, plant, and fungal cells.

This protocol describes a new method allowing for the quantitative visualization of complex formation of SNARE proteins, based on F&#246;rster resonance energy transfer, and fluorescence lifetime imaging microscopy.

Soluble N-ethylmaleimide sensitive fusion protein (NSF) attachment protein receptor (SNARE) proteins are key for membrane trafficking, as they catalyze ...

Immunology and Infection

Autofluorescence Imaging to Evaluate Cellular Metabolism

Cellular metabolism is the process by which cells generate energy, and many diseases, including cancer, are characterized by abnormal metabolism. Reduced nicotinamide adenine (phosphate) dinucleotide (NAD(P)H) and oxidized flavin adenine dinucleotide (FAD) are coenzymes of metabolic reactions. NAD(P)H and FAD exhibit autofluorescence and can be spectrally isolated by excitation and emission wavelengths. Both coenzymes, NAD(P)H and FAD, can exist in either a free or protein-bound configuration, each of which has a distinct fluorescence lifetime-the time for which the fluorophore remains in the excited state. Fluorescence lifetime imaging (FLIM) allows quantification of the fluorescence intensity and lifetimes of NAD(P)H and FAD for label-free analysis of cellular metabolism. Fluorescence intensity and lifetime microscopes can be optimized for imaging NAD(P)H and FAD by selecting the appropriate excitation and emission wavelengths. Metabolic perturbations by cyanide verify autofluorescence imaging protocols to detect metabolic changes within cells. This article will demonstrate the technique of autofluorescence imaging of NAD(P)H and FAD for measuring cellular metabolism.

This protocol describes fluorescence imaging and analysis of the endogenous metabolic coenzymes, reduced nicotinamide adenine (phosphate) dinucleotide (NAD(P)H), and oxidized flavin adenine dinucleotide (FAD). Autofluorescence imaging of NAD(P)H and FAD provides a label-free, nondestructive method to assess cellular metabolism.

Cellular metabolism is the process by which cells generate energy, and many diseases, including cancer, are characterized by abnormal metabolism. Reduced ...

Visualizing Protein Kinase A Activity In Head-fixed Behaving Mice Using In Vivo Two-photon Fluorescence Lifetime Imaging Microscopy

Neuromodulation exerts powerful control over brain function. Dysfunction of neuromodulatory systems results in neurological and psychiatric disorders. Despite their importance, technologies for tracking neuromodulatory events with cellular resolution are just beginning to emerge. Neuromodulators, such as dopamine, norepinephrine, acetylcholine, and serotonin, trigger intracellular signaling events via their respective G protein-coupled receptors to modulate neuronal excitability, synaptic communications, and other neuronal functions, thereby regulating information processing in the neuronal network. The above mentioned neuromodulators converge onto the cAMP/protein kinase A (PKA) pathway. Therefore, in vivo PKA imaging with single-cell resolution was developed as a readout for neuromodulatory events in a manner analogous to calcium imaging for neuronal electrical activities. Herein, a method is presented to visualize PKA activity at the level of individual neurons in the cortex of head-fixed behaving mice. To do so, an improved A-kinase activity reporter (AKAR), called tAKAR&#945;, is used, which is based on F&#246;rster resonance energy transfer (FRET). This genetically-encoded PKA sensor is introduced into the motor cortex via in utero electroporation (IUE) of DNA plasmids, or stereotaxic injection of adeno-associated virus (AAV). FRET changes are imaged using two-photon fluorescence lifetime imaging microscopy (2pFLIM), which offers advantages over ratiometric FRET measurements for quantifying FRET signal in light-scattering brain tissue. To study PKA activities during enforced locomotion, tAKAR&#945; is imaged through a chronic cranial window above the cortex of awake, head-fixed mice, which run or rest on a speed-controlled motorized treadmill. This imaging approach will be applicable to many other brain regions to study corresponding behavior-induced PKA activities and to other FLIM-based sensors for in vivo imaging.

A procedure is presented to visualize protein kinase A activities in head-fixed, behaving mice. An improved A-kinase activity reporter, tAKAR&#945;, is expressed in cortical neurons and made accessible for imaging through a cranial window. Two-photon fluorescence lifetime imaging microscopy is used to visualize PKA activities in vivo during enforced locomotion.

Neuromodulation exerts powerful control over brain function. Dysfunction of neuromodulatory systems results in neurological and psychiatric disorders. ...

Neuroscience

Multicellular Spheroid Formation for FLIM-Based Metabolic and Hypoxia Analysis

Production and Multi-Parameter Live Cell Fluorescence Lifetime Imaging Microscopy (FLIM) of Multicellular Spheroids

Multicellular tumor spheroids are a popular 3D tissue microaggregate&#160;model for reproducing tumor microenvironment, testing and optimizing drug therapies&#160;and using bio- and nanosensors in a 3D context. Their ease of production, predictable size, growth, and observed nutrient and metabolite gradients are important to recapitulate the 3D niche-like&#160;cell microenvironment. However, spheroid heterogeneity and variability of their production methods can influence overall cell metabolism, viability, and drug response. This makes it difficult to choose the most appropriate&#160;methodology, considering the requirements in size, variability, needs of biofabrication, and use as in vitro 3D tissue models in stem and cancer cell biology. In particular, spheroid production can influence their compatibility with quantitative live microscopies, such as optical metabolic imaging, fluorescence lifetime imaging microscopy (FLIM), monitoring of spheroid&#160;hypoxia with nanosensors, or viability. Here, a number of conventional spheroid formation protocols are presented, highlighting their compatibility with the live widefield, confocal, and two-photon microscopies. The follow-up imaging to analysis&#160;pipeline with multiplexed autofluorescence FLIM and, using various types of cancer and stem cell spheroids, is also presented.

Author Spotlight: Standardizing Spheroid Formation Methods for Metabolic and Oxygenation Analysis Using Fluorescence Lifetime Imaging Microscopy

Here, we describe different multicellular spheroid formation methods to perform follow-up multi-parameter live cell microscopy. Using fluorescence lifetime imaging microscopy (FLIM), cellular autofluorescence, staining dyes, and nanoparticles, the approach for analysis of cell metabolism, hypoxia, and cell death in live three-dimensional (3D) cancer and stem cell-derived spheroids is demonstrated.

Multicellular tumor spheroids are a popular 3D tissue microaggregate&#160;model for reproducing tumor microenvironment, testing and optimizing drug ...

Real-Time Monitoring of Aurora kinase A Activation using Conformational FRET Biosensors in Live Cells

Epithelial cancers are often hallmarked by the overexpression of the Ser/Thr kinase Aurora A/AURKA. AURKA is a multifunctional protein that activates upon its autophosphorylation on Thr288. AURKA abundance peaks in mitosis, where it controls the stability and the fidelity of the mitotic spindle, and the overall efficiency of mitosis. Although well characterized at the structural level, a consistent monitoring of the activation of AURKA throughout the cell cycle is lacking. A possible solution consists in using genetically-encoded F&#246;rster&#8217;s Resonance Energy Transfer (FRET) biosensors to gain insight into the autophosphorylation of AURKA with sufficient spatiotemporal resolution. Here, we describe a protocol to engineer FRET biosensors detecting Thr288 autophosphorylation, and how to follow this modification during mitosis. First, we provide an overview of possible donor/acceptor FRET pairs, and we show possible cloning and insertion methods of AURKA FRET biosensors in mammalian cells. Then, we provide a step-by-step analysis for rapid FRET measurements by fluorescence lifetime imaging microscopy (FLIM) on a custom-built setup. However, this protocol is also applicable to alternative commercial solutions available. We conclude by considering the most appropriate FRET controls for an AURKA-based biosensor, and by highlighting potential future improvements to further increase the sensitivity of this tool.

The activation of the multifunctional Ser/Thr kinase AURKA is hallmarked by its autophosphorylation on Thr288. Fluorescent probes relying on FRET can discriminate between its inactive and activated states. Here, we illustrate some strategies for probe engineering, together with a rapid FRET protocol to follow the kinase activation throughout mitosis.

Epithelial cancers are often hallmarked by the overexpression of the Ser/Thr kinase Aurora A/AURKA. AURKA is a multifunctional protein that activates upon ...

Biology

Fluorescence Lifetime Macro Imager for Biomedical Applications

This paper presents a new photoluminescence lifetime imager designed to map the molecular oxygen (O2) concentration in different phosphorescent samples ranging from solid-state, O2-sensitive coatings to live animal tissue samples stained with soluble O2-sensitive probes. In particular, the nanoparticle-based near-infrared probe NanO2-IR, which is excitable with a 625 nm light-emitting diode (LED) and emits at 760 nm, was used. The imaging system is based on the Timepix3 camera (Tpx3Cam) and the opto-mechanical adaptor, which also houses an image intensifier. O2 phosphorescence lifetime imaging microscopy (PLIM) is commonly required for various studies, but current platforms have limitations in their accuracy, general flexibility, and usability.
The system presented here is a fast and highly sensitive imager, which is built on an integrated optical sensor and readout chip module, Tpx3Cam. It is shown to produce high-intensity phosphorescence signals and stable lifetime values from surface-stained intestinal tissue samples or intraluminally stained fragments of the large intestine and allows the detailed mapping of tissue O2 levels in about 20 s or less. Initial experiments on the imaging of hypoxia in grafted tumors in unconscious animals are also presented. We also describe how the imager can be re-configured for use with O2-sensitive materials based on Pt-porphyrin dyes using a 390 nm LED for the excitation and a bandpass 650 nm filter for emission. Overall, the PLIM imager was found to produce accurate quantitative measurements of lifetime values for the probes used and respective two-dimensional maps of the O2 concentration. It is also useful for the metabolic imaging of ex vivo tissue models and live animals.

This paper describes the use of a new, fast optical imager for the macroscopic photoluminescence lifetime imaging of long decay emitting samples. The integration, image acquisition, and analysis procedures are described, along with the preparation and characterization of the sensor materials for the imaging and the application of the imager in studying biological samples.

This paper presents a new photoluminescence lifetime imager designed to map the molecular oxygen (O2) concentration in different phosphorescent samples ...

FLIM-FRET Imaging for Characterization of Protein-Protein Interactions in Live Bacteria

Source: Manko, H. et al., <a href="https://app.jove.com/v/61602">FLIM-FRET Measurements of Protein-Protein Interactions in Live Bacteria.</a> J. Vis. Exp. (2020)
The video describes the FLIM-FRET imaging technique to determine the protein-protein interaction in live bacteria expressing cytoplasmic proteins labeled with fluorescent proteins, a donor eGFP, and acceptor mCherry. The combined technique also allows the quantification of the interacting proteins.

Source: Manko, H. et al., FLIM-FRET Measurements of Protein-Protein Interactions in Live Bacteria. J. Vis. Exp. (2020)
The video describes the FLIM-FRET ...