The authors acknowledge the financial support of the School of Dental Medicine at the University of Pittsburgh, the National Institutes of Health award K01 AR062598, and grant P30 DE030740. The authors also thank Dr. Jin Zhang for the ICUE1 plasmid, Wayne Rasband for developing ImageJ and Michael Cammer for the ImageJ macro.

The authors have no conflicts to declare.

This work demonstrates how FRET imaging can be used to analyze cellular signaling in 3D hydrogels. While prior studies have demonstrated FRET imaging of cells seeded on hydrogel substrates35-37, of extracellular interactions with hydrogels38, and of molecules trapped in hydrogels39-41, this is the first publication to describe FRET imaging based intracellular analysis of cells embedded within 3D hydrogels. The work solves several implementation issues when translating FRET imaging from 2D to 3D. First, high numerical aperture objectives are needed for FRET imaging to gather sufficient emission signal, but they limit the depth of field. The cells here are allowed to slightly settle via centrifuging to increase the number of cells in a focal plane near the glass to compensate for this. Second, 3D hydrogel scaffolds may drift across the field of view during imaging which complicates analysis. The hydrogels here are bonded to the coverslip so that they remain fixed throughout the experiment. Third, selection of appropriate hydrogel compositions for 3D FRET is essential because hydrogels may hinder visualization of the cells. Here transparent hydrogels of PC-gel and TR-gel are used. However, gathering the cells with centrifugation to a focal plane near the coverslip can be used to image cells in hydrogels with higher diffraction.The choice of hydrogel depends on the microenvironment conditions that must be simulated, which can be found in a review on hydrogels42. Fourth, an alternate calculation is employed here for the FRET ratio of the single chain ICUE1 probe (i.e., EQE&#160;= QE/cAem) to minimize the number of image channels required for analysis and thereby minimize photobleaching. The average FRET ratio per cell is calculated as the average of the ratios per pixel within a cell to minimize underestimation of the actual FRET ratio. Finally, a linear ratiometric analysis and means to calculate the activated fraction of single chain binary probes is described.
There are several critical aspects of carrying out successful FRET experiments using widefield microscopy. With respect to hardware, the camera must be sensitive enough to resolve small signal changes, leaving newer scientific CMOS cameras and electron multiplying CCDs better suited than conventional CCDs. To best analyze the spatial distribution of the FRET ratio, the camera must at minimum possess twice the spatial resolution of the point spread function of the objective (Nyquist criterion). This makes dual-view systems less suited to the task. More crucial is to select an appropriate exposure and image acquisition rate for the given FRET pair so as to minimize photobleaching of the fluorophores. A decreased acquisition rate is recommended as experiment duration increases. The use of rapid filter wheels increases acquisition rate and the number of FOVs for analysis while avoiding the image registration issues with dual-view and turret filter cubes. The inhomogeneous illumination field complicates correction for background fluorescence that arises from sample autofluorescence and camera system noise. Some hydrogels, particularly those containing collagenous proteins are highly autofluorescent43,44. The FRET ratios are underestimated without background correction. Here we employ a simple background correction method that relies on the relatively flat illumination field which can often be configured with epi-fluorescence illumination over the center of the image (Figure 3B, Step 7.2). This method therefore restricts cells of interest to those within this illumination field. The background correction described here does not account for cellular autofluorescence in the wavelengths read for the binary probe. In such a case, unlabeled cells (no probe transfection) should be imaged under the same conditions and background subtracted. A mix of labeled and unlabeled cells may be used and the unlabeled cells selected for the background ROI. Alternate methods which provide for cell analysis over the entire image field include use of a shading mask, multiple background ROIs, or identical samples without cells and a protocol is available upon request.
Specific to 3D FRET imaging, probe response is highly sensitive to the hydrogel permeability to the analyte (Figure 6). Therefore the same hydrogel regions are compared across experimental treatments, preferably at a point of geometry symmetry such as near the scaffold center as used here. Alternatively, microfluidic chambers/bioreactors may be employed to rapidly and uniformly perfuse the hydrogel with analyte solution45. A FRET signal may not be detected (signal to noise ratio is too low) when the hydrogel&#39;s autofluorescence is too high; a thinner hydrogel or different probe (different fluorophores) should be used. With respect to 3D FRET imaging in photocrosslinked hydrogels, use of minimum irradiation exposure and wavelengths outside the excitation spectrums of the probe fluorophores is recommended. LAP may be used with a visible light source at 405 nm to further minimize potential cellular damage31,46. However, using LAP with 365 nm irradiation is recommended because this minimizes probe bleaching. 365 nm lies at the tail end of the CFP donor excitation spectrum, whereas 405 nm lies at the peak excitation. Alternatively, the probe expression may be allowed to recover for one day. Use of binary probes minimizes issues of sensitivity to differences in expression levels and in molecular diffusion of the donor and acceptor fluorophores. Non-binary probes may be used, but with SE instead of QE imaging and additional correction for spectral bleed-through of excitation and emission spectra (see below). Furthermore, the low commercial availability and the complexity in designing FRET probes may be a hindrance. The most critical factor for successful experiments remains proper correction and analysis of the fluorescence signals.
An alternate calculation of the FRET ratio is utilized for several additional reasons besides minimization of photobleaching. For binary single-chain probes, the commonly reported ratio is acceptor emission under donor excitation (sensitized emission, SE) to donor emission under donor excitation (quenched emission, QE), i.e., FRET ratio = SE/QE25,47,48. SE/QE is non-linear relative to changes in FRET efficiency21,22,47. Namely, the ratio has an exponentially non-linear relationship to inherent FRET efficiency of the probe (Ei)(Donius, A. E.,Taboas, J. M. unpublished work. (2015)), with the ratio most linear for Ei less than approximately 15% . SE/QE will also underestimate the fraction of activated probes (FAP, i.e., fraction of probes binding analyte). Therefore, analysis of SE/QE requires a cumbersome equilibrium dose response study and curve fit. Fortunately, the ratios of SE or QE to the acceptor emission under acceptor excitation (Aem) are linear with respect to Ei and the FAP, i.e., the FRET ratios SE/Aem and QE/Aem. SE/Aem is often used for binary probes and only requires end-point calibration (at no probe activity and full probe activity), but basal cellular signaling makes this difficult. To eliminate the need for endpoint calibration, SE can be corrected (cSE) for spectral overlap of donor and acceptor excitation and emission spectrums (spectral bleed-through) and for the quantum yield and spectral sensitivity (QS) of the combined probe fluorophores and microscope imaging system. The corrected SE FRET ratio based on cSE defines the observed FRET efficiency of the probes within each pixel of an image, i.e., ESE&#160;= cSE/Aem. Commercial and free software is available to correct SE for these effects and the reader is referred to the work of Chen and Periasamy 2006 for a detailed explanation of the methods50. However, calculating ESE requires capture of three image channels per time-point (SE, QE, Aem). Therefore, in this work we also employ an alternate FRET ratio EQE&#160;= 1 - QE/cAem, which requires capture of only two image channels (QE and Aem). Calculating EQE from these channels only requires correcting Aem for QS (cAem = Aem x&#160;QS). QS = Dem/Aem is easily estimated using two images from the one calibration sample, where Dem is the donor emission under donor excitation with acceptor bleached. The FAP at any instant can be calculated by comparing ESE or EQE to the Ei of the probe.
Ultimately, FRET ratio selection (ESE&#160;= cSE/Aem&#160;vs. EQE&#160;= QE/cAem) should be based on consideration of the probe type and the channels with best signal. Both approaches include background noise correction of images per frame as described above to account for changes in autofluorescence over time. They assume no overlap of Aem excitation light into the Dem excitation spectrum, which is often the case due to probe design and microscope filter configuration. Single-chain probes can use either and selection is based on best probe signal (brightness) to camera noise and to background signal on SE and QE channels. For the ICUE1 probe and experimental conditions used here (cell and hydrogel types), SE has a stronger signal than QE. Dual-chain probes require use of ESE due to non-equimolar distribution of donor and acceptor fluorophores. For probes that decrease in FRET upon binding analyte such as ICUE1, FRET efficiency can be &#34;inverted&#34; to present a positive signaling change upon binding the analyte as we do here, with ESE&#160;= 1 - cSE/Aem or EQE = QE/(Aem x QS).
Analysis of the FAP is sensitive to proper correction of the FRET ratios and to the estimate of Ei. It can be estimated with the same calibration sample used for QS and a conventional endpoint FRET efficiency assay as Ei = 1-(QE/Dem) (QE image followed by acceptor photobleaching and a Dem image)28, but care must be taken to minimize accidental bleaching of the donor. We describe a modified version where the estimate of Dem based on Aem adjusted for QS is substituted, i.e., Ei = 1 - (QE/(Aem x QS)). Alternately, Ei = cSE/Aem may be used. Estimation of Ei in living cells requires that all probes be driven to full FRET. This is difficult to achieve in practice for probes,&#160;such as ICUE1 that decrease in FRET upon binding the analyte. An in vitro based calculation of Ei using cell lysates and purified analyte is best, but outside the scope of this work. Here we recommend using 2&#8242;,5&#8242;-Dideoxyadenosine to decrease cAMP in the cells. However, a relative FAP may be calculated using an Ei estimate derived from the baseline level of signaling. For these reasons, studies most often report the FRET ratio (as done here) or a relative FAP based on endpoint calibration, where the signaling baseline before adding agonist is the lower bound and the signal after adding a second agonist that saturates signaling is the upper bound. Forskolin is often used as a control agonist to saturate cAMP signal. Alternately, a cAMP analog may be used such as 8-Bromoadenosine 3&#39;,5&#39;-cyclic monophosphate. Positive controls used at the completion of studies to identify potential changes in the signaling pathway among experimental treatments are recommended.
Calculation of the average signaling response per cell requires consideration of several factors. First, the average FRET ratio should be calculated as the average of the ratios at each pixel within a cell, i.e., (&#8721;(QE&#8260;cAem))/(number of pixels), instead of the ratio of the average QE and Aem in a cell, i.e., (&#8721;QE)&#8260;(&#8721;cAem). Though the latter does not require careful masking as background noise is low, it severely underestimates the true average FRET ratio. However, pixel ratios require floating-point calculation and careful binary masking of the cell area to define the ROIs and avoid inclusion of spurious ratios generated from background noise outside the cell. The entire cell area must be quantified to avoid biasing results on cell shape. The masking may need to be redefined over time depending on changes in cell shape and migration. Alternately, ROIs larger than the cell may be used if exclusion criteria are defined to remove pixel ratios from QE and Aem signals that fall well below cellular levels and are near background levels. The described analysis methods detail the basic steps used in this work for FRET analysis without specialized software/plugins. Microscope manufacturers and other vendors sell add-on modules for their microscope software, which support automated ratiometric and FRET analysis. Likewise, the public domain ImageJ software has several plugins available for particle and FRET analysis, such as RiFRET. Second, the pixel-based average FRET ratio underestimates the true average ratio of the 3D cellular structure because a 2D image is used. The 2D signals represent and average along the z-axis. Calculation of the 3D spatial distribution of FRET ratios in live cells is not possible without high speed 3D imaging (e.g., using spinning disk confocal microscopy). This is a problem for both 2D and 3D cultures, but has a larger effect in 3D as more of the cellular structure exists out of plane. This is of great concern for probes that localize to cellular structures, such as the plasma membrane EPAC1 probe PM-ICUE. See Spiering et al. 2013 for suggestions to correct for cell thickness effects on ratio calculations24. Analysis of the distribution of Aem can be used to detect if probe accumulates in regions of the cell and imaging plane adjusted. This will also help to interpret the spatial distribution of FRET ratios and to eliminate spurious results, e.g., identifying probe saturation (i.e., a low Aem region will have low probe concentration and may exhibit probe saturation and high FRET ratio). Third, different FRET baseline levels may indicate a difference in transfection efficiency, probe expression, or basal signaling between experimental groups. &#34;Relative Analysis&#34; (Step 10.1.1) helps remove drift in the FRET ratio over time if present. It facilitates comparison of the relative magnitude of responses between samples, but impedes comparison to the time-course of response for the reference sample (control plot is a flat line). &#34;Absolute Analysis&#34; (Step 10.1.2) facilitates comparison of the rate of response across samples, but hampers comparison of the magnitude of response because each line is scaled by a dissimilar constant. Studies often use a linear regression on the baseline to correct for drift in the FRET ratio over time.
The described 3D FRET method is a useful and practical way to fabricate and perform time-lapse imaging of cell laden 3D hydrogels, which can be applied to other probes and imaging modalities. Other FRET system besides single chain binary probes will require more complex correction of intensity based signals, as discussed above. Alternately, fluorescence lifetime imaging of FRET (FLIM-FRET) may be used to calculate FRET efficiency via a change in emission lifetime of the probe donor. Unlike intensity based FRET, FLIM-FRET is insensitive to background noise, spectral bleed-through, quantum efficiency, and detector spectral sensitivity2. However, FLIM systems are expensive, complex, and uncommon, and work best with fluorophores with single exponent decay and no FLIM run-off 49. The described method may also be used with more advanced microscope platforms (e.g., FRET-TIRF, fluorescence anisotropy, and spectral correlation FRET). Applying this method to 3D imaging with high speed confocal and multiphoton microscopy will facilitate analysis of the sub-cellular distribution of signaling response and increase the accuracy of signaling analysis. This 3D FRET method will enable advanced cell biology studies in simulated 3D cellular microenvironments. As such, it can be readily applied to pharmacology and regenerative medicine needs, including studying intercellular signaling and screening drug response in engineered hydrogel-based microtissues.

Cellular signaling is both complex and consequential for numerous fields, including pharmacology, tissue engineering, and regenerative medicine. Useful investigational tools are needed to further our understanding of cell biology and to develop optimal materials for tissue regeneration. F&#246;rster resonance energy transfer (FRET) imaging is an essential tool enabling analysis of receptor activation, molecular conformation, and supramolecular interactions (e.g., protein/DNA complexation) in live cells. FRET is a type of non-radiative energy transfer between fluorophores1. It has an efficiency that is inversely proportional to the sixth power of the distance between a donor fluorophore and acceptor fluorophore. Thus, it can provide information on the spatial distance between two different molecules or across regions of one molecule at the nanometer scale (typically 1 - 10 nm)2. The donor and acceptor fluorophores may be different molecule types (hetero-FRET), in which the donor has the higher energy emission (shorter wavelength), or of the same type (homo-FRET). FRET imaging can be performed on fixed or live cells, but in general fixed cells are used for imaging of molecular interactions at high spatial resolution when high speed confocal systems are unavailable. Live cells are used to study interactions and processes that are inhibited or altered by fixation, such as the real-time intracellular signaling response3.
Live cell studies that employ FRET imaging use two-dimensional (2D) cellular cultures in part because of simplicity and lower background (no emission from out of plane cells). However, 2D cultures also alter numerous cellular processes compared to the physiologic microenvironment and three-dimensional (3D) culture4,5. For example, native cell to cell and cell to extracellular matrix interactions are drastically altered in 2D culture leading to the easily observed changes in cell morphology and polarity6. Membrane microdomains (e.g., caveolae and lipid rafts) and receptor signaling are strongly regulated by the culture environment, in part because they bind cytoskeletal components7,8 and the cell shape and cytoskeletal structure are strongly regulated by the spatial culture environment9. Mechanotransduction is not only influenced by the 3D matrix, but by the more complex secondary loading conditions engendered in 3D environments compared to 2D cultures10. Finally, the permeability of 3D matrices is less than the culture medium, in general with decreased diffusion and increased binding of cell signaling molecules compared to 2D cultures. With 3D cultures one is able to create and observe a microenvironment more similar to the physiologic with respect to adhesive, chemical, and mechanical cues. Cell to cell interactions can be promoted and the adhesive properties can be controlled with the structure, composition, and architecture (patterning) of the 3D material11-13. The mechanical properties of the material can likewise be tailored by the composition and structure14,15. Culturing cells in hydrogels therefore permits FRET studies on primary cells that would otherwise de-differentiate or change in phenotype using conventional techniques, e.g., cells from articular cartilage. Thus, a method is needed to enable FRET assays in live 3D cultures.
Hydrogel scaffolds are ideal for 3D FRET based studies because they can be made optically transparent and tailored to control the microenvironment and to provide cellular cues. Hydrogels made from natural polymers have been used in cell culture for decades, including gelatin and fibrin16. Greater control over the cellular microenvironment can be achieved with chemical modification of these polymers and with the use of synthetic polymers17,18. Hydrogel mechanical stiffness and permeability can be controlled by changing their polymeric composition and mesh size (polymer and crosslink density)19,20. Further, hydrogels can be made bioactive through the incorporation of growth factors and cellular ligands. Because of these possibilities, the development of hydrogels for biosensing, drug delivery, and tissue engineering applications is a very active area of research21. 3D printing of hydrogels is also undergoing development for fabrication of micro-tissues and -organs15. Thus, FRET imaging of cells in hydrogels is not only useful as a means to approximate physiologic cellular behavior, but also as a tool to study and optimize engineered tissue growth.
Binary ratiometric FRET probes are very useful in studying cellular signaling and can be utilized in hydrogel cultures. For a partial list of published fluorescent and FRET probes, see the Cell Migration Consortium website22. The most common probe type contains two different fluorophores that are associated or linked by a recognition element(s) (analyte sensitive region). These regions undergo a conformational change, association, or disassociation upon detection of the analyte (e.g., binding of an ion or molecule, enzymatic cleavage of the region) that alters the distance between fluorophores and therefore the FRET magnitude (either higher or lower)23. A less common yet useful probe type relies on an analyte sensitive change in the spectral overlap of the two fluorophores, which alters FRET magnitude. &#34;Single-chain&#34; ratiometric probes utilize a fluorophore pair linked on a single molecule. &#34;Dual-chain&#34; probes utilize fluorophore pairs on separate molecules, but their expression can be coupled under the same expression cassette24. Unlike studies with single fluorophore expression (e.g., fluorescent fusion proteins), studies with ratiometric FRET probes do not require dual transfection to control for transfection efficiency or cell viability. Ratiometric FRET probes are relatively insensitive to transfection efficiency when expressed above a minimum threshold (concentration insensitive)23,25. They are insensitive to excitation source fluctuations and other intracellular environment factors (e.g., pH, ions) so long as both fluorophores are similarly responsive. In addition, their response is not subject to transcriptional delay, unlike fluorescent and bioluminescent promoter-reporter constructs26,27.
Ratiometric FRET probes are easily and frequently employed in conventional widefield epifluorescence microscope systems. Widefield microscopes are preferred over line scanning confocal systems for live cell imaging because of concerns over system cost, fluorophore bleaching, and capture of signal changes with sufficient temporal resolution. In addition, single cell analysis over a large population of cells is possible with a motorized stage and image capture over multiple fields of view. Widefield microscopy requires intensity based analysis of the hetero-FRET probe signals. Though intensity analysis does not require complex hardware like other FRET methods, more post-acquisition work is needed to correct for the effects of fluorophore behaviors and microscope/imaging system configurations28. The captured emission intensity of a fluorophore is a function of the excitation energy, fluorophore quantum yield, and the combined filter and camera/detector spectral sensitivity and linearity2. These may be dissimilar for the donor and acceptor and will require calibration for quantitative analysis. In addition, imaging of the acceptor emission is influenced by the spectral overlap of the fluorophores (excitation of acceptor by donor excitation light and bleed-through of donor emission into the acceptor emission spectra)2. &#34;Single-chain&#34; probes are internally normalized because their fluorophores are equimolar at the nanoscale, while the fluorophores of &#34;dual-chain&#34; probes may exist at different stoichiometries throughout a cell25,28. If the fluorophores of &#34;single-chain&#34; probes are of similar brightness (function of extinction coefficient and quantum yield), the effects of non-linear detector sensitivity are small and only correction for the background fluorescence and the coupled quantum yield/detector sensitivity is needed23. Thus &#34;single-chain&#34; ratiometric FRET probes are most easily implemented in widefield microscopy24.
This paper describes a straightforward technique to perform FRET imaging of live cells in 3D hydrogel cultures using a conventional widefield epifluorescent microscope. It can be easily adopted by laboratories already carrying out FRET experiments in 2D, as well laboratories interested in intercellular signaling in microtissues. Here we demonstrate the method with FRET imaging based measurement of cyclic adenosine monophosphate (cAMP) levels in live chondrocytes within photocrosslinking (PC-gel, polyethylene glycol dimethacrylate) and thermoresponsive (TR-gel, Matrigel) hydrogels. A ratiometric FRET probe is utilized based on EPAC1 (ICUE1) to detect cAMP levels in response to forskolin, a chemical agonist for adenylyl cyclase which catalyzes the conversion of ATP to cAMP. cAMP is one of the principal second messengers mediating G protein-coupled receptor signaling and it activates various factors, including downstream exchange proteins directly activated by cAMP (EPACs). The fluorophores move apart upon cAMP binding to the EPAC domain resulting in a decrease in FRET. Described here is the preparation of the hydrogel materials, cell transfection with the ICUE1 probe, and embedding of the cells in 3D hydrogels. The 3D FRET experiment procedure and the image analysis necessary to evaluate probe activity per cell are explained. We also discuss the inherent limitations of FRET analysis in 2D and 3D using widefield microscopy. The technique presented here is an improvement over the existing 2D methods since it enables analysis in a more physiological context and requires less image correction and calibration. Great utility lies in the fact that many transparent materials can be used while cell and transfection preferences can be maintained.

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			<td height="42" style="height:42px;width:216px;">Cell culture dish (6-well)</td>
			<td style="width:71px;">Falcon</td>
			<td style="width:119px;">351146</td>
			<td style="width:167px;">Disposable lab equipment</td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:216px;">Epifluorescent Microscope with motorized stage</td>
			<td style="width:71px;">Nikon</td>
			<td style="width:119px;">MEA53100 (Eclipse TiE Inverted)</td>
			<td style="width:167px;">Large/non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Adjustable Specimen Holder for XY Stage</td>
			<td style="width:71px;">Nikon</td>
			<td style="width:119px;">77011393</td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">60x (1.3 NA) objective (CFI Plan Apochromat 60XH Lamda)</td>
			<td style="width:71px;">Nikon</td>
			<td style="width:119px;">MRD01605</td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="106">
			<td height="106" style="height:106px;width:216px;">CFP/YFP light source and excitation / emission filter holders (Lambda light source &#38; wheel, Lambda emission filter system)</td>
			<td style="width:71px;">Nikon (Sutter Instrument reseller)</td>
			<td style="width:119px;">77016231, 77016088</td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="85">
			<td height="85" style="height:85px;width:216px;">CYF/YFP filter set</td>
			<td style="width:71px;">Nikon (Chroma Technology Corp)</td>
			<td style="width:119px;">77014928</td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="59">
			<td height="59" style="height:59px;width:216px;">Camera (ORCA Flash 4.0 v1)</td>
			<td style="width:71px;">Nikon (Hamamatsu reseller)</td>
			<td style="width:119px;">77054076</td>
			<td style="width:167px;">Non-disposable lab-equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">NIS-Elements 40.20.02 microscope software)</td>
			<td style="width:71px;">Nikon</td>
			<td style="width:119px;">MQS31100&#160;</td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:216px;">Prism (spreadsheet and graphing software)</td>
			<td style="width:71px;">GraphPad Software, Inc</td>
			<td style="width:119px;">Version 6</td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="85">
			<td height="85" style="height:85px;width:216px;">OmniCure S1000 UV Spot Curing Lamp System with 365nm filter or other light source (&#955;=365 or 405)</td>
			<td style="width:71px;">OmniCure</td>
			<td style="width:119px;">S1000</td>
			<td style="width:167px;">Large/non-disposable lab equipment</td>
		</tr>
		<tr height="85">
			<td height="85" style="height:85px;width:216px;">Pipette Aid&#160;</td>
			<td style="width:71px;">Drummond Scientific Co.&#160;</td>
			<td style="width:119px;">DP-100</td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Hemacytometer</td>
			<td style="width:71px;">Hausser Scientific</td>
			<td style="width:119px;">Reichert Bright-Line 1475</td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Vacuum desiccator chamber/degasser&#160;</td>
			<td style="width:71px;">Any</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Large/non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Tissue Culture Hood&#160;</td>
			<td style="width:71px;">Any</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Large/non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Chemical Fume Hood&#160;</td>
			<td style="width:71px;">Any</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Large/non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Oven</td>
			<td style="width:71px;">Any</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Large/non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Spatula</td>
			<td style="width:71px;">Any</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Beaker</td>
			<td style="width:71px;">Any</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Non-disposable lab equipment</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Incubator&#160;</td>
			<td style="width:71px;">Any</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Large/non-disposable lab equipment</td>
		</tr>
	</tbody>
</table>

fret imaging in three-dimensional hydrogels

Imaging of F&#246;rster resonance energy transfer (FRET)&#160;is a powerful tool for examining cell biology in real-time. Studies utilizing FRET commonly employ two-dimensional (2D) culture, which does not mimic the three-dimensional (3D) cellular microenvironment. A method to perform quenched emission FRET imaging using conventional widefield epifluorescence microscopy of cells within a 3D hydrogel environment is presented. Here an analysis method for ratiometric FRET probes that yields linear ratios over the probe activation range is described. Measurement of intracellular cyclic adenosine monophosphate (cAMP) levels is demonstrated in chondrocytes under forskolin stimulation using a probe for EPAC1 activation (ICUE1) and the ability to detect differences in cAMP signaling dependent on hydrogel material type, herein a photocrosslinking hydrogel (PC-gel, polyethylene glycol dimethacrylate) and a thermoresponsive hydrogel (TR-gel). Compared with 2D FRET methods, this method requires little additional work. Laboratories already utilizing FRET imaging in 2D can easily adopt this method to perform cellular studies in a 3D microenvironment. It can further be applied to high throughput drug screening in engineered 3D microtissues. Additionally, it is compatible with other forms of FRET imaging, such as anisotropy measurement and fluorescence lifetime imaging (FLIM), and with advanced microscopy platforms using confocal, pulsed, or modulated illumination.

All hydrogel precursors, cells, and casting molds were prepared as described above. The cell laden precursor solutions were cast in PDMS molds and then centrifuged before gelation/photocrosslinking to immobilize cells near the coverslip and facilitate FRET imaging analysis (Figure 1). The hydrogels with attached coverslips were placed within prepared PDMS imaging wells for microscopic imaging (Figure 2). The optical configurations and image acquisition parameters were then set as shown in Figure 3A. Capture of all four FRET related image channels for CFP-YFP fluorophore pairs is demonstrated (see under &#34;Optical Conf.&#34; in Figure 3), as is needed for non-binary probes. However in this work only two images are required for the single chain binary ICUE1 probe, QE = &#34;CFP CFP&#34; and Aem = &#34;YFP YFP&#34; (excitation emission). Multiple FOVs (xy positions) were selected in which several cells resided within the homogenous illumination area (Figure 3B). After time lapse acquisition, the signal data for the probe was exported. ROIs for background correction of channel signals and for cell analysis were designated using thresholded Aem images from the start of the experiments (Figure 4). Cells were selected from among the cell pool as those expressing sufficient (not too dim), but not too high (excessively bright) probe (Figure 4B). The QE and SE FRET ratios per pixel at each acquisition were calculated using floating-point division of the background subtracted image channels. The average FRET ratio per cell (i.e., per ROI) was calculated, normalized to the baseline signal prior to stimulation (i.e., a regression on the baseline subtracted from all time-points), and plotted with error bars as the standard error of the mean (SEM). Both the QE and cSE based FRET ratios detect the increased cAMP activity in chondrocytes under forskolin stimulation (100 nM, Figure 5). The QE FRET ratio was more sensitive to background correction than the cSE FRET ratio because the QE signal was lower due to the low basal level of cAMP activity in chondrocytes embedded within the hydrogels. Both hydrogel types (TR-gel and PC-gel) showed an increase in FRET ratio over time (Figure 6), indicating an increased cAMP signaling response to the addition of Forskolin. As indicated by the QE FRET ratio, chondrocytes in PC-gel hydrogels show a greater change in cAMP (shown) and a higher basal level of cAMP (EQE = 0.19 in PC-gel vs. EQE = 0.09 in TR-gel, not shown in baseline subtracted figure).
<img alt="Figure 1" src="/files/ftp_upload/54135/54135fig1.jpg" /> 
Figure 1: Cell Distribution in Photocrosslinked Hydrogel (PC-gel) 
A: The cell laden hydrogel precursor was centrifuged to maximize the number of cells at a focal plane near the coverslip. B: This increases the number of cells in the FOV and minimizes background signal from out of plane cells. (Scale bar = 200 &#181;m) <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54135/54135fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54135/54135fig2.jpg" /> 
Figure 2: Hydrogel in PDMS Dish 
The hydrogel was placed inside a tall PDMS well (10x volume of hydrogel) with a coverslip base for microscopic imaging and analyte stimulation. The PC-gel hydrogels are transparent and bonded to the coverslip so that they remain in place throughout the assay. The PDMS well can be made larger to contain 10x more medium than the hydrogel volume using a wider biopsy punch in addition to a thicker PDMS sheet. (Scale bar = 2 mm) <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54135/54135fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54135/54135fig3.jpg" /> 
Figure 3: Acquisition Configuration for FRET Imaging 
A: The acquisition was configured for image capture every 7 sec at multiple locations. For QE FRET ratio calculation, only two image channels are needed for the ICUE1 probe used here (binary single chain probe), QE = &#34;CFP CFP&#34; and Aem = &#34;YFP YFP&#34; (excitation emission) under the &#34;Optical Conf.&#34; column in the&#160;&#955; tab of the microscope software. B: FOVs (&#34;XY&#34; positions) were selected in which several cells resided within the homogenous illumination area. The plot below the image shows the illumination intensity along the blue arrowed line that traverses through the center of the FOV. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54135/54135fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54135/54135fig4.jpg" /> 
Figure 4: Selection of ROIs for FRET Imaging Analysis 
A: A region of interest (ROI) free of cells was selected to correct for background signal on each channel. An image of a cell-free hydrogel may instead be used for background subtraction if cell density or migration is high, or if a shading mask is not used when cells do not lie within a homogeneous illumination field. B: The cell ROIs were selected using image thresholding and binary masking of the Aem channel. Selecting a ROI larger than the cells will adversely affect calculation of the average FRET ratio per cell due to inclusion of extracellular ratios generated from background noise. Calculation of the cellular FRET ratio using the average of each channel per cell is not recommended as this underestimates the ratio. (Scale bar = 50 &#181;m) <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54135/54135fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/54135/54135fig5.jpg" /> 
Figure 5: Comparison of FRET Ratios in Thermoresponsive Hydrogel (TR-gel) 
Both QE and SE based FRET ratios detect the increased cAMP activity in chondrocytes under forskolin stimulation. Forskolin is an adenyl cyclase agonist which induces cAMP production. FRET decreases when the ICUE1 probe binds cAMP, and thus the QE FRET ratio (EQE&#160;= sQE/(sAem x QS)) increases. Conversely, the SE FRET ratio decreases and is thus plotted as ESE&#160;= 1 - cSE/sAem. In hydrogel embedded chondrocytes, the QE FRET ratio is more sensitive to background correction than the SE FRET ratio because the QE signal is low due to the low basal cAMP activity. Error bars = SEM, n = 25. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54135/54135fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/54135/54135fig6.jpg" /> 
Figure 6: Comparison of FRET Ratio in Different Hydrogels 
The chondrocytes in both hydrogel types responded to forskolin stimulation with an increase in cAMP activity as demonstrated by the increased QE FRET ratio over time. The hydrogel type impacts the cellular response through several effects, including differences in permeability to forskolin and in basal cellular cAMP activity (EQE = 0.19 in PC-gel vs. EQE = 0.09 in TR-gel, not shown). Error bars = SEM, n for TR-gel = 25, n for PC-gel = 15. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54135/54135fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about FRET Imaging in Three-dimensional Hydrogels at JoVE.com

FRET Imaging in Three-dimensional Hydrogels

F&#246;rster resonance energy transfer (FRET) imaging is a powerful tool for real-time cell biology studies. Here a method for FRET imaging cells in physiologic three-dimensional (3D) hydrogel microenvironments using conventional epifluorescence microscopy is presented. An analysis for ratiometric FRET probes that yields linear ratios over the activation range is described.

Imaging of F&#246;rster resonance energy transfer (FRET)&#160;is a powerful tool for examining cell biology in real-time. Studies utilizing FRET commonly ...

fret-imaging-in-three-dimensional-hydrogels

Nanyang Technological University

Research

JoVE Journal

Biology

13.0K Views.  University of Pittsburgh. Förster resonance energy transfer (FRET) imaging is a powerful tool for real-time cell biology studies. Here a method for FRET imaging cells in physiologic three-dimensional (3D) hydrogel microenvironments using conventional epifluorescence microscopy is presented. An analysis for ratiometric FRET probes that yields linear ratios over the activation range is described.

Video: FRET Imaging in Three-dimensional Hydrogels

Chip-based Three-dimensional Cell Culture in Perfused Micro-bioreactors

We have developed a chip-based cell culture system for the three-dimensional cultivation of cells. The chip is typically manufactured from non-biodegradable polymers, e.g., polycarbonate or polymethyl methacrylate by micro injection molding, micro hot embossing or micro thermoforming. But, it can also be manufactured from bio-degradable polymers. Its overall dimensions are 0.7 1 x 20 x 20 x 0.7 1 mm (h x w x l). The main features of the chips used are either a grid of up to 1156 cubic micro-containers (cf-chip) each the size of 120-300 x 300 x 300 &mu; (h x w x l) or round recesses with diameters of 300 &mu; and a depth of 300 &mu; (r-chip). The scaffold can house 10 Mio. cells in a three-dimensional configuration. For an optimal nutrient and gas supply, the chip is inserted in a bioreactor housing. The bioreactor is part of a closed steril circulation loop that, in the simplest configuration, is additionaly comprised of a roller pump and a medium reservoir with a gas supply. The bioreactor can be run in perfusion, superfusion, or even a mixed operation mode. We have successfully cultivated cell lines as well as primary cells over periods of several weeks. For rat primary liver cells we could show a preservation of organotypic functions for more than 2 weeks. For hepatocellular carcinoma cell lines we could show the induction of liver specific genes not or only slightly expressed in standard monolayer culture. The system might also be useful as a stem cell cultivation system since first differentiation experiments with stem cell lines were promising.

We describe a chip-based platform for the three-dimensional cultivation of cells in micro-bioreactors. One chip can house up to 10 Mio. cells that can be cultivated under precisely defined conditions with regard to fluid flow, oxygen tension etc. in a sterile, closed circulation loop.

We have developed a chip-based cell culture system for the three-dimensional cultivation of cells. The chip is typically manufactured from ...

Microfabrication of Chip-sized Scaffolds for Three-dimensional Cell cultivation

Using microfabrication technologies is a prerequisite to create scaffolds of reproducible geometry and constant quality for three-dimensional cell cultivation. These technologies offer a wide spectrum of advantages not only for manufacturing but also for different applications. The size and shape of formed cell clusters can be influenced by the exact and reproducible architecture of the microfabricated scaffold and, therefore, the diffusion path length of nutrients and gases can be controlled.1 This is unquestionably a useful tool to prevent apoptosis and necrosis of cells due to an insufficient nutrient and gas supply or removal of cellular metabolites.
Our polymer chip, called CellChip, has the outer dimensions of 2 x 2 cm with a central microstructured area. This area is subdivided into an array of up to 1156 microcontainers with a typical dimension of 300 m edge length for the cubic design (cp- or cf-chip) or of 300 m diameter and depth for the round design (r-chip).2
So far, hot embossing or micro injection moulding (in combination with subsequent laborious machining of the parts) was used for the fabrication of the microstructured chips. Basically, micro injection moulding is one of the only polymer based replication techniques that, up to now, is capable for mass production of polymer microstructures.3 However, both techniques have certain unwanted limitations due to the processing of a viscous polymer melt with the generation of very thin walls or integrated through holes. In case of the CellChip, thin bottom layers are necessary to perforate the polymer and provide small pores of defined size to supply cells with culture medium e.g. by microfluidic perfusion of the containers.
In order to overcome these limitations and to reduce the manufacturing costs we have developed a new microtechnical approach on the basis of a down-scaled thermoforming process. For the manufacturing of highly porous and thin walled polymer chips, we use a combination of heavy ion irradiation, microthermoforming and track etching. In this so called "SMART" process (Substrate Modification And Replication by Thermoforming) thin polymer films are irradiated with energetic heavy projectiles of several hundred MeV introducing so-called "latent tracks" Subsequently, the film in a rubber elastic state is formed into three dimensional parts without modifying or annealing the tracks. After the forming process, selective chemical etching finally converts the tracks into cylindrical pores of adjustable diameter.

We present two processes for the microfabrication of porous polymer chips for three-dimensional cell cultivation. The first one is hot embossing combined with a solvent vapour welding process. The second one uses a recently developed microthermoforming process combined with ion track technology leading to a significant simplification of manufacture.

Using microfabrication technologies is a prerequisite to create scaffolds of reproducible geometry and constant quality for three-dimensional cell ...

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

The three-dimensional folding of chromosomes compartmentalizes the genome and and can bring distant functional elements, such as promoters and enhancers, into close spatial proximity 2-6. Deciphering the relationship between chromosome organization and genome activity will aid in understanding genomic processes, like transcription and replication. However, little is known about how chromosomes fold. Microscopy is unable to distinguish large numbers of loci simultaneously or at high resolution. To date, the detection of chromosomal interactions using chromosome conformation capture (3C) and its subsequent adaptations required the choice of a set of target loci, making genome-wide studies impossible 7-10.
We developed Hi-C, an extension of 3C that is capable of identifying long range interactions in an unbiased, genome-wide fashion. In Hi-C, cells are fixed with formaldehyde, causing interacting loci to be bound to one another by means of covalent DNA-protein cross-links. When the DNA is subsequently fragmented with a restriction enzyme, these loci remain linked. A biotinylated residue is incorporated as the 5' overhangs are filled in. Next, blunt-end ligation is performed under dilute conditions that favor ligation events between cross-linked DNA fragments. This results in a genome-wide library of ligation products, corresponding to pairs of fragments that were originally in close proximity to each other in the nucleus. Each ligation product is marked with biotin at the site of the junction. The library is sheared, and the junctions are pulled-down with streptavidin beads. The purified junctions can subsequently be analyzed using a high-throughput sequencer, resulting in a catalog of interacting fragments.
Direct analysis of the resulting contact matrix reveals numerous features of genomic organization, such as the presence of chromosome territories and the preferential association of small gene-rich chromosomes. Correlation analysis can be applied to the contact matrix, demonstrating that the human genome is segregated into two compartments: a less densely packed compartment containing open, accessible, and active chromatin and a more dense compartment containing closed, inaccessible, and inactive chromatin regions. Finally, ensemble analysis of the contact matrix, coupled with theoretical derivations and computational simulations, revealed that at the megabase scale Hi-C reveals features consistent with a fractal globule conformation.

The Hi-C method allows unbiased, genome-wide identification of chromatin interactions (1). Hi-C couples proximity ligation and massively parallel sequencing. The resulting data can be used to study genomic architecture at multiple scales: initial results identified features such as chromosome territories, segregation of open and closed chromatin, and chromatin structure at the megabase scale.

The three-dimensional folding of chromosomes compartmentalizes the genome and and can bring distant functional elements, such as promoters and enhancers, ...

Two- and Three-Dimensional Live Cell Imaging of DNA Damage Response Proteins

Double-strand breaks (DSBs) are the most deleterious DNA lesions a cell can encounter. If left unrepaired, DSBs harbor great potential to generate mutations and chromosomal aberrations1. To prevent this trauma from catalyzing genomic instability, it is crucial for cells to detect DSBs, activate the DNA damage response (DDR), and repair the DNA. When stimulated, the DDR works to preserve genomic integrity by triggering cell cycle arrest to allow for repair to take place or force the cell to undergo apoptosis. The predominant mechanisms of DSB repair occur through nonhomologous end-joining (NHEJ) and homologous recombination repair (HRR) (reviewed in2). There are many proteins whose activities must be precisely orchestrated for the DDR to function properly. Herein, we describe a method for 2- and 3-dimensional (D) visualization of one of these proteins, 53BP1.
The p53-binding protein 1 (53BP1) localizes to areas of DSBs by binding to modified histones3,4, forming foci within 5-15 minutes5. The histone modifications and recruitment of 53BP1 and other DDR proteins to DSB sites are believed to facilitate the structural rearrangement of chromatin around areas of damage and contribute to DNA repair6. Beyond direct participation in repair, additional roles have been described for 53BP1 in the DDR, such as regulating an intra-S checkpoint, a G2/M checkpoint, and activating downstream DDR proteins7-9. Recently, it was discovered that 53BP1 does not form foci in response to DNA damage induced during mitosis, instead waiting for cells to enter G1 before localizing to the vicinity of DSBs6. DDR proteins such as 53BP1 have been found to associate with mitotic structures (such as kinetochores) during the progression through mitosis10.
In this protocol we describe the use of 2- and 3-D live cell imaging to visualize the formation of 53BP1 foci in response to the DNA damaging agent camptothecin (CPT), as well as 53BP1's behavior during mitosis. Camptothecin is a topoisomerase I inhibitor that primarily causes DSBs during DNA replication. To accomplish this, we used a previously described 53BP1-mCherry fluorescent fusion protein construct consisting of a 53BP1 protein domain able to bind DSBs11. In addition, we used a histone H2B-GFP fluorescent fusion protein construct able to monitor chromatin dynamics throughout the cell cycle but in particular during mitosis12. Live cell imaging in multiple dimensions is an excellent tool to deepen our understanding of the function of DDR proteins in eukaryotic cells.

This protocol describes a method for visualizing a DNA double-strand break signaling protein activated in response to DNA damage as well as its localization during mitosis.

Double-strand breaks (DSBs) are the most deleterious DNA lesions a cell can encounter. If left unrepaired, DSBs harbor great potential to generate ...

Mouse Fetal Whole Intestine Culture System for Ex Vivo Manipulation of Signaling Pathways and Three-dimensional Live Imaging of Villus Development

Most morphogenetic processes in the fetal intestine have been inferred from thin sections of fixed tissues, providing snapshots of changes over developmental stages. Three-dimensional information from thin serial sections can be challenging to interpret because of the difficulty of reconstructing serial sections perfectly and maintaining proper orientation of the tissue over serial sections. Recent findings by Grosse et al., 2011 highlight the importance of three- dimensional information in understanding morphogenesis of the developing villi of the intestine1. Three-dimensional reconstruction of singly labeled intestinal cells demonstrated that the majority of the intestinal epithelial cells contact both the apical and basal surfaces. Furthermore, three-dimensional reconstruction of the actin cytoskeleton at the apical surface of the epithelium demonstrated that the intestinal lumen is continuous and that secondary lumens are an artifact of sectioning. Those two points, along with the demonstration of interkinetic nuclear migration in the intestinal epithelium, defined the developing intestinal epithelium as a pseudostratified epithelium and not stratified as previously thought1. The ability to observe the epithelium three-dimensionally was seminal to demonstrating this point and redefining epithelial morphogenesis in the fetal intestine. With the evolution of multi-photon imaging technology and three-dimensional reconstruction software, the ability to visualize intact, developing organs is rapidly improving. Two-photon excitation allows less damaging penetration deeper into tissues with high resolution. Two-photon imaging and 3D reconstruction of the whole fetal mouse intestines in Walton et al., 2012 helped to define the pattern of villus outgrowth2. Here we describe a whole organ culture system that allows ex vivo development of villi and extensions of that culture system to allow the intestines to be three-dimensionally imaged during their development.

Mouse Fetal Whole Intestine Culture System for Ex Vivo Manipulation of Signaling Pathways and Three-dimensional Live Imaging of Villus Development

Improved imaging technology is allowing three-dimensional imaging of organs during development. Here we describe a whole organ culture system that allows live imaging of the developing villi in the fetal mouse intestine.

Most morphogenetic processes in the fetal intestine have been inferred from thin sections of fixed tissues, providing snapshots of changes over ...

Adipo-Clear: A Tissue Clearing Method for Three-Dimensional Imaging of Adipose Tissue

Adipose tissue plays a central role in energy homeostasis and thermoregulation. It is composed of different types of adipocytes, as well as adipocyte precursors, immune cells, fibroblasts, blood vessels, and nerve projections. Although the molecular control of cell type specification and how these cells interact have been increasingly delineated, a more comprehensive understanding of these adipose-resident cells can be achieved by visualizing their distribution and architecture throughout the whole tissue. Existing immunohistochemistry and immunofluorescence approaches to analyze adipose histology rely on thin paraffin-embedded sections. However, thin sections capture only a small portion of tissue; as a result, the conclusions can be biased by what portion of tissue is analyzed. We have therefore developed an adipose tissue clearing technique, Adipo-Clear, to permit comprehensive three-dimensional visualization of molecular and cellular patterns in whole adipose tissues. Adipo-Clear was adapted from iDISCO/iDISCO+, with specific modifications made to completely remove the lipid stored in the tissue while preserving native tissue morphology. In combination with light-sheet fluorescence microscopy, we demonstrate here the use of the Adipo-Clear method to obtain high-resolution volumetric images&#160;of an entire adipose tissue.

Due to the high lipid content, adipose tissue has been challenging to visualize using traditional histological methods. Adipo-Clear is a tissue clearing technique that allows robust labeling and high-resolution volumetric fluorescent imaging of adipose tissue. Here, we describe the methods for sample preparation, pretreatment, staining, clearing, and mounting for imaging.

Adipose tissue plays a central role in energy homeostasis and thermoregulation. It is composed of different types of adipocytes, as well as adipocyte ...

Single-Cell Resolution Three-Dimensional Imaging of Intact Organoids

Organoid technology, in vitro 3D culturing of miniature tissue, has opened a new experimental window for cellular processes that govern organ development and function as well as disease. Fluorescence microscopy has played a major role in characterizing their cellular composition in detail and demonstrating their similarity to the tissue they originate from. In this article, we present a comprehensive protocol for high-resolution 3D imaging of whole organoids upon immunofluorescent labeling. This method is widely applicable for imaging of organoids differing in origin, size and shape. Thus far we have applied the method to airway, colon, kidney, and liver organoids derived from healthy human tissue, as well as human breast tumor organoids and mouse mammary gland organoids. We use an optical clearing agent, FUnGI, which enables the acquisition of whole 3D organoids with the opportunity for single-cell quantification of markers. This three-day protocol from organoid harvesting to image analysis is optimized for 3D imaging using confocal microscopy.

The entire 3D structure and cellular content of organoids, as well as their phenotypic resemblance to the original tissue can be captured using the single-cell resolution 3D imaging protocol described here. This protocol can be applied to a wide range of organoids varying in origin, size and shape.

Organoid technology, in vitro 3D culturing of miniature tissue, has opened a new experimental window for cellular processes that govern organ development ...

Proteolytically Degraded Alginate Hydrogels and Hydrophobic Microbioreactors for Porcine Oocyte Encapsulation

In reproductive biology, the biotechnology revolution that began with artificial insemination and embryo transfer technology led to the development of assisted reproduction techniques such as oocyte in vitro maturation (IVM), in vitro fertilization (IVF) and cloning of domestic animals by nuclear transfer from somatic cell. IVM is the method particularly of significance. It is the platform technology for the supply of mature, good quality oocytes for applications such as reduction of the generation interval in commercially important or endangered species, research concerning in vitro human reproduction, and production of transgenic animals for cell therapies. The term oocyte quality includes its competence to complete maturation, be fertilized, thereby resulting in healthy offspring. This means that oocytes of good quality are paramount for successful fertilization including IVF procedures. This poses many difficulties to develop a reliable culture method that would support growth not only of human oocytes but also of other large mammalian species. The first step in IVM is the in vitro culture of oocytes. This work describes two protocols for the 3D culture of porcine oocytes. In the first, 3D model cumulus-oocyte complexes (COCs) are encapsulated in a fibrin-alginate bead interpenetrating network, in which a mixture of fibrin and alginate are gelled simultaneously. In the second one, COCs are suspended in a drop of medium and encapsulated with fluorinated ethylene propylene (FEP; a copolymer of hexafluoropropylene and tetrafluoroethylene) powder particles to form microbioreactors defined as Liquid Marbles (LM). Both 3D systems maintain the gaseous in vitro culture environment. They also maintain COCs 3D organization by preventing their flattening and consequent disruption of gap junctions, thereby preserving the functional relationship between the oocyte, and surrounding follicular cells.

Presented here are two protocols for the encapsulation of porcine oocytes in 3D culture conditions. In the first, cumulus-oocyte complexes (COCs) are encapsulated in fibrin-alginate beads. In the second, they are enclosed with fluorinated ethylene propylene powder particles (microbioreactors). Both systems ensure optimal conditions to maintain their 3D organization.

In reproductive biology, the biotechnology revolution that began with artificial insemination and embryo transfer technology led to the development of ...

Staining and High-Resolution Imaging of Three-Dimensional Organoid and Spheroid Models

In vitro three-dimensional (3D) cell culture models, such as organoids and spheroids, are valuable tools for many applications including development and disease modeling, drug discovery, and regenerative medicine. To fully exploit these models, it is crucial to study them at cellular and subcellular levels. However, characterizing such in vitro 3D cell culture models can be technically challenging and requires specific expertise to perform effective analyses. Here, this paper provides detailed, robust, and complementary protocols to perform staining and subcellular resolution imaging of fixed in vitro 3D cell culture models ranging from 100 &#181;m to several millimeters. These protocols are applicable to a wide variety of organoids and spheroids that differ in their cell-of-origin, morphology, and culture conditions. From 3D structure harvesting to image analysis, these protocols can be completed within 4-5 days. Briefly, 3D structures are collected, fixed, and can then be processed either through paraffin-embedding and histological/immunohistochemical staining, or directly immunolabeled and prepared for optical clearing and 3D reconstruction (200 &#181;m depth) by confocal microscopy.

Here, we provide detailed, robust, and complementary protocols to perform staining and subcellular resolution imaging of fixed three-dimensional cell culture models ranging from 100 &#181;m to several millimeters, thus enabling the visualization of their morphology, cell-type composition, and interactions.

In vitro three-dimensional (3D) cell culture models, such as organoids and spheroids, are valuable tools for many applications including development and ...

Three-dimensional Characterization of Interorganelle Contact Sites in Hepatocytes using Serial Section Electron Microscopy

Transmission electron microscopy has been long considered to be the gold standard for the visualization of cellular ultrastructure. However, analysis is often limited to two dimensions, hampering the ability to fully describe the three-dimensional (3D) ultrastructure and functional relationship between organelles. Volume electron microscopy (vEM) describes a collection of techniques that enable the interrogation of cellular ultrastructure in 3D at mesoscale, microscale, and nanoscale resolutions. 
This protocol provides an accessible and robust method to acquire vEM data using serial section transmission EM (TEM) and covers the technical aspects of sample processing through to digital 3D reconstruction in a single, straightforward workflow. To demonstrate the usefulness of this technique, the 3D ultrastructural relationship between the endoplasmic reticulum and mitochondria and their contact sites in liver hepatocytes is presented. Interorganelle contacts serve vital roles in the transfer of ions, lipids, nutrients, and other small molecules between organelles. However, despite their initial discovery in hepatocytes, there is still much to learn about their physical features, dynamics, and functions. 
Interorganelle contacts can display a range of morphologies, varying in the proximity of the two organelles to one another (typically ~10-30 nm) and the extent of the contact site (from punctate contacts to larger 3D cisternal-like contacts). The examination of close contacts requires high-resolution imaging, and serial section TEM is well suited to visualize the 3D ultrastructural of interorganelle contacts during hepatocyte differentiation, as well as alterations in hepatocyte architecture associated with metabolic diseases.

A simple and comprehensive protocol to acquire three-dimensional details of membrane contact sites between organelles in hepatocytes from the liver or cells in other tissues.

Transmission electron microscopy has been long considered to be the gold standard for the visualization of cellular ultrastructure. However, analysis is ...