The authors gratefully acknowledge funding from the United Kingdom Biotechnology and Biological Sciences Research Council (BBSRC BB/E003621/1, BB/H00713X/1 and BB/M006786/1), the UK Technology Strategy Board (Technology Award CHBT/007/00030, EP/C54269X, in partnership with AstraZeneca, GE Healthcare, GSK, Kentech Instruments Ltd) and the Wellcome Trust (WT 095931/Z/11/Z). FG acknowledges a PhD studentship from the UK Engineering and Physical Sciences Research Council (EPSRC). DA, DK and SW acknowledge PhD studentships from the Institute of Chemical Biology EPSRC-funded Doctoral Training Centre.

1. Preparation of Multiwell Plate Array
<ol>
	<li>Prepare a solution of 75 &#956;M Coumarin 6 in ethanol (&#964; ~ 2.43 ns) for reference measurements to enable determination of t0.</li>
	<li>Seed 150,000 Cos cells into four wells of a 6 well plate and allow to attach overnight in culture medium (see Materials List).</li>
	<li>Transfect one well each with mTq5A, mTq5V, mTq17V and mTq32V using a commercial transfection reagent according to the manufacturer&#39;s instructions and culture for 24 h.</li>
	<li>Detach cells using a commercial trypsin/EDTA solution according to manufacturer&#39;s protocol.</li>
	<li>Pipette 5,000 Cos cells suspended in Hank&#39;s Balanced Salt Solution (HBSS) expressing mTq5A into each of wells A1-G3 of a #1.5 thickness glass-bottomed 96 multiwell plate that has previously been treated with poly-L-lysine. Repeat for mTq5V expressing cells into wells A4-G6, mTq17V into wells A5-G9 and mTq32V into wells A10-G12.</li>
	<li>Leave well H1 empty (to provide measurement of any static background from the multiwell plate).</li>
	<li>Pipette 200 &#181;L of HBSS only into well H2 (to provide measurement of any background signal from the cell culture medium).</li>
	<li>Pipette 5,000 non-transfected cells in HBSS into well H3 (to provide measurement of any background signal from cellular autofluorescence).</li>
	<li>Pipette 200 &#181;L of the 75 &#956;M Coumarin dye solution into well H4 (to provide a check on any variation of t0 during the multiwell plate acquisition, e.g., due to changes in ambient temperature or to fluctuations in laser or timing circuitry.</li>
</ol>
2. openFLIM-HCA Data Acquisition
NOTE: Detailed information can found on the openFLIM-HCA wiki33.
<ol>
	<li>Start &#181;Manager and the OpenFLIM-HCA Plugin</li>
	<li>Select the calibration file for the specific combination of delay generator unit and laser repetition rate under &#34;FLIM control: Delay box calibration file: Calibration Files&#34; .</li>
	<li>Set the folder where the data will be saved under &#34;File: Set Base Folder&#34;.</li>
	<li>Check the excitation beam path to ensure that coupling into the delivery optical fiber is stable and that the coupling efficiency is maximized by measuring power transmitted through delivery fiber using a power meter. Fluctuations lower than 5% are acceptable.</li>
	<li>Check that the GOI triggering is stable by displaying the monitor output signal from the GOI on an oscilloscope triggered by the GOI input trigger signal.</li>
	<li>Check the imaging of the GOI phosphor onto the CCD sensor by covering the photocathode of the GOI, setting its gain to 750 V and focusing one of the relay lenses such that images of sparse single photon events (due to background light leaking though the GOI cover) recorded on the CCD are as sharp as possible.</li>
	<li>Check that the sample field of view is uniformly illuminated by imaging a uniform fluorescent sample, such as a drop of the reference dye solution on a coverslip, using a sufficiently low excitation power (&#60; 1 &#181;W) to ensure that the GOI is not saturated.</li>
	<li>Select the appropriate plate definition file, i.e., select option for 96-well plates (&#34;File: Load Plate properties&#34;).</li>
	<li>Using the &#181;Manager GUI, ensure that there is no dichroic beam splitter cube in the microscope frame by selecting an empty position.</li>
	<li>Manually select a gate width of 4 ns at the GOI for the whole experiment.</li>
	<li>Acquire IRF image data:
	<ol>
		<li>Using the &#181;Manager GUI, ensure that there is no microscope objective in the beam path by selecting an empty position. Manually place a black anodized beam block above the objective turret to prevent any laser light escaping and angle it to minimize any reflection back into the microscope frame.</li>
		<li>Using the &#181;Manager GUI, set the filters in the CSUX (Excitation, Dichroic, Emission) such that the fraction of excitation light scattered from the spinning Nipkow disk can be imaged but ensure the intensity is not sufficient to saturate the system for a 200 ms CCD integration time. This is to avoid exposing the GOI photocathode to too much light, which could damage the photocathode.</li>
		<li>Use the Find maxpoint function over the full range of the delays covered by the programmable fast delay box. Check the output diagram displayed and then adjust the manual course delay box by pushing the forward button so that the full IRF profile is within the scan range of the fast delay box.</li>
		<li>Adjust the acquisition parameters (Neutral density, Exposure time, Frame accumulation) so the CCD is not saturated in the brightest time-gate and the effective integration time is &#62;200 ms.</li>
		<li>Set delay steps of 25 ps over the full delay range (&#34;FLIM control: Fast delay box: Populate delays&#34;).</li>
		<li>Acquire IRF image by pressing &#34;Snap FLIM image&#34;.</li>
		<li>Acquire a background image by blocking the laser (&#34;Light path control: Neutral density: blocked&#34;), reducing the number of delays (&#34;FLIM control: Fast delay box: Current delay setting (ps)&#34;), leave all other properties unaltered and press &#34;Snap FLIM image&#34;.</li>
	</ol>
	</li>
	<li>Acquire reference dye data:
	<ol>
		<li>Select well H4 by using the &#181;Manager GUI (&#34;XYZ control: Go to well: H4&#34;).</li>
		<li>Using the &#181;Manager GUI, select filters (Excitation 434/17 nm, Dichroic, Emission 482/25 nm) for imaging mTqFP.</li>
		<li>Use the Find maxpoint function over the full range of the fast delay box and then adjust the coarse delay box so the full decay profile is within the delay range of the fast delay box.</li>
		<li>Set the delay to the point of maximum intensity by changing &#34;FLIM control: Fast delay box: Current delay setting (ps)&#34;. Adjust the acquisition parameters (Neutral density, Exposure time) so that the CCD is not saturated.</li>
		<li>Set delay steps of 25 ps over the full delay range (&#34;FLIM control: Fast delay box: Populate delays).</li>
		<li>Acquire reference dye data by pressing &#34;Snap FLIM image&#34;.</li>
		<li>Acquire a second background CCD camera image by blocking the excitation laser (see 2.11.7)</li>
	</ol>
	</li>
	<li>Acquire FLIM data of the multiwell plate sample using the &#181;Manager acquisition software:
	<ol>
		<li>Set which wells should be imaged and the number of FOV to be acquired per well (&#34;Setup HCA sequenced acquisition: XYZ positions&#34;).</li>
		<li>Manually select an exemplar FOV containing the sample to be imaged. Use this FOV to determine the optimal neutral density filter, gate width at the GOI and integration time of the camera so as to reach 75% of the dynamic range of the CCD camera.</li>
		<li>Set autofocus (&#34;XYZ control: Autofocus&#34;): Press &#34;Return focus control only&#34;, and then manually focus on the cells or structure of interest. Set &#34;Autofocus search range&#34; to 2000 &#181;m and press &#34;Enter&#34;. Press &#34;AF now&#34; to initiate an autofocus procedure. An offset value will show up in the field &#34;FocusOffset (Autofocus)&#34;.</li>
		<li>Enter the offset value obtained in 2.13.3 into &#34;AF offset&#34; and repeat the autofocus procedure twice (&#34;AF now&#34;) to check that the offset value is now zero, indicating correct functioning of the autofocus system.</li>
		<li>Use the &#34;AutoGate&#34; function in the OpenFLIM-HCA acquisition software to choose a logarithmic sampling of the delay points. Alternatively, these can be selected manually, see reference 36 for more details.</li>
		<li>Set &#34;Accumulate Frames&#34; to a value that yields desired total data acquisition time. Increasing the number of accumulated frames increases signal to noise ratio of the FLIM data at the expense of also increasing total FLIM data acquisition time.</li>
		<li>Run the FLIM acquisition of the multiwell plate by pressing the &#34;Start HCA sequence&#34; button.</li>
	</ol>
	</li>
	<li>Acquire a further background CCD camera image by blocking the excitation laser (see 2.11.7) with identical acquisition settings as used for the FLIM data acquisition.</li>
</ol>
3. openFLIM-HCA Data Analysis Using FLIMfit
<ol>
	<li>Check that necessary ancillary files for FLIM data analysis are present (i.e., IRF and reference dye measurement).</li>
	<li>Load the data from the empty well (H1), the well containing culture medium (H2) and the well containing unlabeled cells in culture medium (H3) into FLIMfit (&#34;File: Load FLIM data&#34;) to check whether there are any background contributions larger than 1% of the signal from the cells expressing &#34;donor-only&#34;, i.e., in wells A1-G3.</li>
	<li>Prepare a time-varying background (TVB) file by loading the well with culture medium into FLIMfit (&#34;File: Load FLIM data&#34;). Load the camera background data acquired in section 2.14 (&#34;Background: Load Background&#34;) and use the FLIMfit option &#34;Tools: Create TVB Intensity Map&#34; to generate the TVB. See reference 31 for more detail on the TVB.</li>
	<li>Prepare the spatially varying IRF Shift Map by loading the IRF data acquired in section 2.11 and subtract the CCD camera background acquired in section 2.11.7. Use the FLIMfit option &#34;Tools: Create IRF Shift Map&#34; to calculate the spatially varying IRF Shift Map. See reference [31] for more detail on the IRF Shift Map.</li>
	<li>Fit a monoexponential decay to the reference dye data acquired in section 2.12. Load reference dye and the spatially varying IRF Map calculated in section 3.4, set fit parameters (&#34;Lifetime: No. Exp:1&#34;) with t0 set as a fitted parameter (&#34;Lifetime: FIT IRF Shift: Fitted&#34;). The value of t0 obtained is then reported in the table shown in the &#34;Parameters&#34; tab.</li>
	<li>Analyze the FLIM data by loading the experimental FLIM data acquired in section 2.13, the spatially varying IRF Map calculated in section 3.4, the camera background acquired in section 2.14, the TVB file prepared in section 3.3 and type in the negative value of t0 obtained in section 3.5 (&#34;IRF: IRF shift: t0&#34;). Then fit the experimental data to the desired decay model using FLIMfit36 according to the requirements of the experiment.</li>
</ol>

The authors have nothing to disclose. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

We have described an automated multiwell plate microscope designed for HCA using time-gated FLIM. This instrument is controlled using open source software written in &#181;Manager with the option of saving the data to an OMERO server and the FLIM data analysis being undertaken using FLIMfit36, an open source program written in MatLab and available as an OMERO client32 The &#181;Manager instrument control software, openFLIM-HCA, is available online33 with a list of the system components48 to enable academic researchers to construct their own FLIM HCA instruments.
In order to acquire robust FLIM data, it is necessary to optimize the GOI and CCD acquisition settings and to take account of any variations in t0. As described in 3.8.2, the GOI gain setting and CCD camera integration time should be set to reach ~75% of the CCD dynamic range. Using higher GOI voltages and multiple CCD frame accumulations at each time gate delay increases the signal to noise ratio49 but this increases the total FLIM acquisition time (since fewer fluorescence photons are acquired per frame before the CCD camera saturates and so the number of frame accumulations should be increased) and so this trade-off should be decided for each experiment. The calibration of the delay generator depends on the laser repetition rate and it is therefore necessary to ensure that the correct calibration file for the repetition rate used is loaded into the acquisition software. The procedure for calibrating the delay box can be found on the openFLIM-HCA wiki33.
If the cellular autofluorescence is low compared to the fluorescence signal, we use the signal from a well containing just culture medium to provide the time-varying background (TVB). To minimize background fluorescence from the cell culture medium, we avoid media containing phenol red. If the cellular autofluorescence is significant, then the TVB may be derived from measurements of the unlabeled cells. However, in this case care must be taken, as this assumes that the autofluorescence background is the same for every pixel in the image. This assumption will not be valid if the autofluorescence varies significantly across a cell or if the excitation beam or detection sensitivity is not uniform over the field of view.
The acquisition of an IRF image using scattered excitation light pulses provides the temporal IRF profile that is convolved with the data model in the fitting process and also provides a map of the spatial variation of the IRF across the field of view. The IRF can be measured by imaging a scattering sample such as a colloidal suspension although, in our instrument, using excitation light scattered from the Nipkow disk provides a cleaner measurement of the IRF. Accurate determination of the timing of the IRF is important because errors in the time delay between the excitation and time-gating can significantly impact the fitting process, particularly when fitting to complex exponential decay models. The IRF acquired using scattered excitation light is not exactly what is needed for the fitting process because it is recorded at the excitation wavelength rather than at the fluorescence emission wavelength, which can affect its timing, although the spatial variation of the IRF should be the same at both wavelengths. In addition, the scattered IRF may be globally shifted in time relative to the true IRF due to a differing optical path length from the scattering object, as is the case for an IRF acquired from the Nipkow disk in optically sectioned FLIM. This correction, t0, which is the required global temporal shift that should be applied to the acquired scattered excitation light IRF, is calculated from the monoexponential reference dye data as indicated in Protocol step 4.4. The following dyes can be used for different excitation wavelengths: a 75 &#956;M Coumarin 153 solution in methanol (&#964; ~ 4.3 ns50) can be used for excitation in the range 295-442 nm; a 75 &#956;M Coumarin 6 solution in ethanol (&#964; ~ 2.43 ns37) can be used for excitation in the range 430-500 nm; and a 75 &#956;M Rhodamine B solution in water (&#964; ~ 1.7 ns37) can be used for excitation in the range 488-575 nm. We note that, although it is possible in FLIMfit to use a different IRF for each pixel of the system, usually it is reasonable to make the assumption that the spatially varying IRF has the same temporal profile for every pixel in the image but presents a range of spatially varying temporal offsets relative to the global t0. We describe this as the IRF shift map, which is determined from the scattered light IRF. Together, the IRF profile, t0 and the IRF shift map are used to ensure that each pixel in the FOV is fitted with an appropriate IRF. Importantly, t0 can vary slowly over time so it should be measured before any FLIM data acquisition.
The user should decide how to sample the fluorescence decay profiles and is required to set the width of the time-gates and their relative delays after excitation. In general, it is desirable to use broad gate widths to maximize the detected signal and typically we use gate widths set to 4 ns for FLIM of cells labeled with fluorescence proteins. The number of time-gate delays should be sufficient to sample the fluorescent decay profile (including one gate set to measure the signal just before the excitation pulse) given the complexity of fitting model that will be used in the analysis. The optimum value can depend on the lifetimes and relative amplitudes of the decay components. In general, 4 gates are sufficient for fitting monoexponential decays while 7 or more gates may be used for more complex decay models.
We note that FLIM can be implemented using a range of time-domain or frequency domain techniques and automated FLIM HCA of multiwell plate arrays was first implemented in a (non-sectioning) wide-field microscope using frequency domain lifetime readouts of FRET51. The first automated optical sectioning FLIM multiwell plate reader for HCA utilizing wide-field time-gated imaging28 was then reported. Subsequently, wide-field (non-sectioning) frequency domain FLIM HCA was applied to screen for post translational modifications (tyrosine phosphorylation) across a gene library using FRET52 and time-gated FLIM HCA has been applied to FRET assays of HIV-1 Gag oligomerization53 and of SUMOylation of FOXM154 and of Raichu RhoA and Rac1 biosensors33. It is also possible to use TCSPC for multiwell plate FLIM26 but to date it has proved challenging to match the throughput of techniques exploiting wide-field detection. One emerging approach that could address this issue is the use of arrays of single photon counting detectors such as SPAD arrays55.
We note that any readouts of FRET using fluorescent proteins should be treated with caution and that the absolute values of parameters obtained from FLIMfit or any other FLIM analysis software will depend on the assumptions associated with the fitting model. For example, where the FRET donor has a significant second decay component, the use of a biexponential model to fit the FRET FLIM data can result in the contribution of the faster decay component, typically associated with the FRETing population appearing higher than it should. It is therefore desirable to use donors with a mono-exponential lifetime such as mTq2FP. Even then, recent studies have shown that FRET analysis can still be affected by dark states of acceptor fluorescence proteins or by heterogeneity of the orientation factor &#954;2 due to a distribution of fluorophore conformations with a variety of chromophore angles and distances56. Nevertheless, we and others have shown that fluorescence lifetime readouts of FRET do produce useful results that correlate with biochemical measurements and can be used to screen for protein interactions or to follow dynamics of biosensors. Thus this openFLIM HCA platform can be applied to a wide range of fluorescence lifetime-based assays utilizing FRET or cellular autofluorescence8, as well as providing quantitative readouts of dye-based probes25.

<table><tbody><tr><td>microscope frame</td><td>Olympus</td><td>IX81</td><td>http://www.olympusmicro.com/brochures/pdfs/ix71.pdf</td></tr><tr><td>optical autofocus</td><td>Olympus</td><td>ZDC</td><td>http://www.olympusmicro.com/brochures/pdfs/ix71.pdf</td></tr><tr><td>motorized (x-y-z) microscope stage</td><td>Marzhauser</td><td>00-24-565-0000</td><td>Stage with Corvus controlle</td></tr><tr><td>excitation laser source</td><td>Fianium</td><td>SC400-4</td><td>Supercontinuum laser http://www.nktphotonics.com/product/sc400-4-compact-supercontinuum-laser/</td></tr><tr><td>gated optical intensifier&amp;nbsp;</td><td>Kentech</td><td>High Rate Imager (HRI)</td><td></td></tr><tr><td>delay generators</td><td>Kentech</td><td>---</td><td>See agile delay generator and precision delay generator</td></tr><tr><td>camera</td><td>Hamamatsu</td><td>ORCA-ER-II</td><td></td></tr><tr><td>Nipkow disc scanner unit&amp;nbsp;</td><td>Yokogawa</td><td>CSU-X1&amp;nbsp;</td><td>http://www.yokogawa.com/solutions/products-platforms/life-science/confocal-scanner-unit-csu/csu-x1/</td></tr><tr><td>Top hat diffuser</td><td>Thorlabs</td><td>ED1-S20-MD</td><td>Engineered diffusers</td></tr><tr><td>mTq5V&amp;nbsp;</td><td>Oxford Genetics</td><td>P3850</td><td>mTurquoise Venus construct with 5 amino acid linker</td></tr><tr><td>mTq17V</td><td>Oxford Genetics</td><td>P3847</td><td>mTurquoise Venus construct with 17 amino acid linker</td></tr><tr><td>mTq32V</td><td>Oxford Genetics</td><td>P3848</td><td>mTurquoise Venus construct with 32 amino acid linker</td></tr><tr><td>mTq5A</td><td>Oxford Genetics</td><td>P3849</td><td>mTurquoise Amber construct</td></tr><tr><td>HEK293T</td><td>---</td><td>---</td><td>cell type used</td></tr><tr><td>phenol red-free HBSS</td><td>Sigma Aldrich</td><td>55021C-1000ML</td><td>imaging media</td></tr><tr><td>culture media</td><td></td><td></td><td>DMEM + 10% FBS + 0.5% Antibiotics</td></tr><tr><td>DMEM</td><td>Sigma Aldrich</td><td>D6046-500ML</td><td>for culture media</td></tr><tr><td>FBS</td><td>Sigma Aldrich</td><td>12003C-500ML</td><td>for culture media</td></tr><tr><td>xTremeGene9</td><td>Sigma Aldrich</td><td>6.37E+09</td><td>for transfection, follow online protocol from La Roche</td></tr><tr><td>trypsin/EDTA Solution</td><td>Thermo Fischer</td><td>R001100</td><td>for detaching cells, follow online protocol from Thermo Fischer</td></tr></tbody></table>

open source high content analysis utilizing automated fluorescence lifetime imaging microscopy

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using F&#246;rster resonance energy transfer (FRET) based readouts of fixed or live cells in multiwell plates. This provides a means to screen for cell signaling processes read out using intramolecular FRET biosensors or intermolecular FRET of protein interactions such as oligomerization or heterodimerization, which can be used to identify binding partners. We describe here the functionality of this automated multiwell plate FLIM instrumentation and present exemplar data from our studies of HIV Gag protein oligomerization and a time course of a FRET biosensor in live cells. A detailed description of the practical implementation is then provided with reference to a list of hardware components and a description of the open source data acquisition software written in &#181;Manager. The application of FLIMfit, an open source MATLAB-based client for the OMERO platform, to analyze arrays of multiwell plate FLIM data is also presented. The protocols for imaging fixed and live cells are outlined and a demonstration of an automated multiwell plate FLIM experiment using cells expressing fluorescent protein-based FRET constructs is presented. This is complemented by a walk-through of the data analysis for this specific FLIM FRET data set.

Watch this Scientific Journal Video about Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy at JoVE.com

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

We present an open source high content analysis (HCA) instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using F&#246;rster resonance energy transfer (FRET) based readouts. Data acquisition for this openFLIM-HCA instrument is controlled by software written in &#181;Manager and data analysis is undertaken in FLIMfit.

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions ...

open-source-high-content-analysis-utilizing-automated-fluorescence

Research

JoVE Journal

Biology

11.9K Views.  Imperial College London.  We presenteren een open source hoog gehalte analyse (HCA) instrument gebruik te maken van geautomatiseerde fluorescentie lifetime imaging (FLIM) voor het testen van eiwit interacties met behulp van Förster resonance energy transfer (FRET) op basis van uitlezingen. Data-acquisitie voor deze openFLIM-HCA instrument wordt bestuurd door software geschreven in μManager en data-analyse wordt uitgevoerd in FLIMfit. 

Video: Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

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.

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 ...

Bioengineering

Imaging Amyloid Tissues Stained with Luminescent Conjugated Oligothiophenes by Hyperspectral Confocal Microscopy and Fluorescence Lifetime Imaging

Proteins that deposit as amyloid in tissues throughout the body can be the cause or consequence of a large number of diseases. Among these we find neurodegenerative diseases such as Alzheimer&#39;s and Parkinson&#39;s disease afflicting primarily the central nervous system, and systemic amyloidosis where serum amyloid A, transthyretin and IgG light chains deposit as amyloid in liver, carpal tunnel, spleen, kidney, heart, and other peripheral tissues. Amyloid has been known and studied for more than a century, often using amyloid specific dyes such as Congo red and Thioflavin T (ThT) or Thioflavin (ThS). In this paper, we present heptamer-formyl thiophene acetic acid (hFTAA) as an example of recently developed complements to these dyes called luminescent conjugated oligothiophenes (LCOs). hFTAA is easy to use and is compatible with co-staining in immunofluorescence or with other cellular markers. Extensive research has proven that hFTAA detects a wider range of disease associated protein aggregates than conventional amyloid dyes. In addition, hFTAA can also be applied for optical assignment of distinct aggregated morphotypes to allow studies of amyloid fibril polymorphism. While the imaging methodology applied is optional, we here demonstrate hyperspectral imaging (HIS), laser scanning confocal microscopy and fluorescence lifetime imaging (FLIM). These examples show some of the imaging techniques where LCOs can be used as tools to gain more detailed knowledge of the formation and structural properties of amyloids. An important limitation to the technique is, as for all conventional optical microscopy techniques, the requirement for microscopic size of aggregates to allow detection. Furthermore, the aggregate should comprise a repetitive &#946;-sheet structure to allow for hFTAA binding. Excessive fixation and/or epitope exposure that modify the aggregate structure or conformation can render poor hFTAA binding and hence pose limitations to accurate imaging.

Amyloid deposition is a hallmark of different diseases and afflicts many different organs. This paper describes the application of luminescent conjugated oligothiophene fluorescence staining in combination with fluorescence microscopy techniques. This staining method represents a powerful tool for detection and exploration of protein aggregates in both clinical and scientific setups.

Proteins that deposit as amyloid in tissues throughout the body can be the cause or consequence of a large number of diseases. Among these we find ...

Biochemistry

Automated System for Single Molecule Fluorescence Measurements of Surface-immobilized Biomolecules

Fluorescence Resonance Energy Transfer (FRET) microscopy has been widely used to study the structure and dynamics of molecules of biological interest, such as nucleic acids and proteins. Single molecule FRET (sm-FRET) measurements on immobilized molecules permit long observations of the system -effectively until both dyes photobleach- resulting in time-traces that report on biomolecular dynamics with a broad range of timescales from milliseconds to minutes. To facilitate the acquisition of large number of traces for statistical analyses, the process must be automated and the sample environment should be tightly controlled over the entire measurement time (~12 hours). This is accomplished using an automated scanning confocal microscope that allows the interrogation of thousands of single molecules overnight, and a microfluidic cell that permits the controlled exchange of buffer, with restricted oxygen content and maintains a constant temperature throughout the entire measuring period. Here we show how to assemble the microfluidic device and how to activate its surface for DNA immobilization. Then we explain how to prepare a buffer to maximize the photostability and lifetime of the fluorophores. Finally, we show the steps involved in preparing the setup for the automated acquisition of time-resolved single molecule FRET traces of DNA molecules.

In this article we describe how we obtain FRET traces from individual DNA molecules immobilized to a surface using an automated scanning confocal microscope.

Fluorescence Resonance Energy Transfer (FRET) microscopy has been widely used to study the structure and dynamics of molecules of biological interest, ...

Automated Slide Scanning and Segmentation in Fluorescently-labeled Tissues Using a Widefield High-content Analysis System

Automated slide scanning and segmentation of fluorescently-labeled tissues is the most efficient way to analyze whole slides or large tissue sections. Unfortunately, many researchers spend large amounts of time and resources developing and optimizing workflows that are only relevant to their own experiments. In this article, we describe a protocol that can be used by those with access to a widefield high-content analysis system (WHCAS) to image any slide-mounted tissue, with options for customization within pre-built modules found in the associated software. Not originally intended for slide scanning, the steps detailed in this article make it possible to acquire slide scanning images in the WHCAS which can be imported into the associated software. In this example, the automated segmentation of brain tumor slides is demonstrated, but the automated segmentation of any fluorescently-labeled nuclear or cytoplasmic marker is possible. Furthermore, there are a variety of other quantitative software modules including assays for protein localization/translocation, cellular proliferation/viability/apoptosis, and angiogenesis that can be run. This technique will save researchers time and effort and create an automated protocol for slide analysis.

Here we describe a protocol for the automated segmentation of fluorescently labeled tissues on slides using a widefield high-content analysis system (WHCAS). This protocol has wide-ranging applications in any field which involves the quantitation of fluorescent markers in biological tissues including the biological sciences, medical engineering, and health sciences.

Automated slide scanning and segmentation of fluorescently-labeled tissues is the most efficient way to analyze whole slides or large tissue sections. ...

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

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

The last decade has been characterized by breakthroughs in fluorescence microscopy techniques illustrated by spatial resolution improvement but also in live-cell imaging and high-throughput microscopy techniques. This led to a constant increase in the amount and complexity of the microscopy data for a single experiment. Because manual analysis of microscopy data is very time consuming, subjective, and prohibits quantitative analyses, automation of bioimage analysis is becoming almost unavoidable. We built an informatics workflow called Substructure Analyzer to fully automate signal analysis in bioimages from fluorescent microscopy. This workflow is developed on the user-friendly open-source platform Icy and is completed by functionalities from ImageJ. It includes the pre-processing of images to improve the signal to noise ratio, the individual segmentation of cells (detection of cell boundaries) and the detection/quantification of cell bodies enriched in specific cell compartments. The main advantage of this workflow is to propose complex bio-imaging functionalities to users without image analysis expertise through a user-friendly interface. Moreover, it is highly modular and adapted to several issues from the characterization of nuclear/cytoplasmic translocation to the comparative analysis of different cell bodies in different cellular sub-structures. The functionality of this workflow is illustrated through the study of the Cajal (coiled) Bodies under oxidative stress (OS) conditions. Data from fluorescence microscopy show that their integrity in human cells is impacted a few hours after the induction of OS. This effect is characterized by a decrease of coilin nucleation into characteristic Cajal Bodies, associated with a nucleoplasmic redistribution of coilin into an increased number of smaller foci. The central role of coilin in the exchange between CB components and the surrounding nucleoplasm suggests that OS induced redistribution of coilin could affect the composition and the functionality of Cajal Bodies.

We present a freely available workflow built for rapid exploration and accurate analysis of cellular bodies in specific cell compartments in fluorescence microscopy images. This user-friendly workflow is designed on the open-source software Icy and also uses ImageJ functionalities. The pipeline is affordable without knowledge in image analysis.

The last decade has been characterized by breakthroughs in fluorescence microscopy techniques illustrated by spatial resolution improvement but also in ...

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 ...

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators.
Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software1&#160;to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.

Presented is a flexible informatics workflow enabling multiplexed image-based analysis of fluorescently labeled cells. The workflow quantifies nuclear and cytoplasmic markers and computes marker translocation between these compartments. Procedures are provided for perturbation of cells using siRNA and reliable methodology for marker detection by indirect immunofluorescence in 96-well formats.

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly ...

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 ...

Analyzing Amyloid Structures in a Tissue Section Using Fluorescence Lifetime Imaging Microscopy

<a href='https://app.jove.com/v/56279/imaging-amyloid-tissues-stained-with-luminescent-conjugated'>Source: Nystr&#246;m, S., et al.,&#160;Imaging Amyloid Tissues Stained with Luminescent Conjugated Oligothiophenes by Hyperspectral Confocal Microscopy and Fluorescence Lifetime Imaging. J. Vis. Exp.&#160;(2017).</a>This video demonstrates analyzing amyloid structures with fluorescence lifetime imaging microscopy or FLIM, using hFTAA dye to reveal compact cores as blue/green and unstable peripheries as red/yellow in color-coded images, reflecting amyloid organization.

Source: Nystr&#246;m, S., et al.,&#160;Imaging Amyloid Tissues Stained with Luminescent Conjugated Oligothiophenes by Hyperspectral Confocal Microscopy ...

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

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