The authors acknowledge the support of an infrastructure research grant from Science Foundation Ireland (SFI) (16/RI/3745) to JCS. Work in the UCD Cell Screening Laboratory is supported by the UCD College of Science. ASC is funded by an Irish Research Council (IRC) Government of Ireland Postgraduate Scholarship (GOIPG/2019/68). The authors also thank all members of the lab for their input and helpful discussions. The artwork in Figure 1 was generated in BioRender.

1. Cell culture
<ol>
	<li>Prepare media
	<ol>
		<li>Prepare specific cell culture media depending on the type of cell line. Ensure that all media for cell maintenance contains 10% Foetal Bovine Serum (FBS). 
		NOTE: Different cell lines use different media. HT-29 colon carcinoma cells (ATCC HTB-38) are grown in McCoys 5A + 10% FBS. HepG2 hepatocellular carcinoma cells (ATCC HB-8065) are grown in Minimum Essential Medium + 1% L-glutamine + 10% FBS. H358 bronchoalveolar carcinoma cells (ATCC CRL-5807) are grown in RPMI 1640 medium + 1% L-glutamine + 10% FBS. All media containing L-glutamine and FBS are referred to as complete media. When plating cells to grow as spheroids, a phenol red-free medium with 10% FBS is required to avoid coloring of the ECM basement material, which in turn can cause artifacts during the imaging process.</li>
	</ol>
	</li>
	<li>Subculture cells
	<ol>
		<li>When cells are approximately 80% confluent, wash briefly with 2 mL of trypsin-EDTA (0.25% (w/v) trypsin/0.53 mM EDTA). Aspirate the trypsin-EDTA, add 3 mL of fresh trypsin-EDTA and incubate for 3-5 min at 37 &#176;C.</li>
		<li>When cells are detached from the cell culture dish, add 7 mL of fresh complete medium.</li>
		<li>Pipette 1 mL of cell suspension into a new 10 cm cell culture dish and add 9 mL of fresh complete medium to give a 1:10 dilution of cells.</li>
		<li>Culture the cells at 37 &#176;C in a humidified incubator with 5% CO2.</li>
		<li>Subculture the cells every 3-5 days, depending on the cell line.</li>
	</ol>
	</li>
</ol>
2. Generation of spheroids
<ol>
	<li>Coat 96-well plates with ECM basement material
	<ol>
		<li>Thaw ECM basement material on ice overnight.</li>
		<li>Dilute ECM basement material in cold phenol red-free serum-free medium using pre-chilled tips kept at -20 &#176;C. 
		NOTE: The final concentration of ECM basement material depends on the cell line used. For HT-29 and H358 cells, use 4 mg&#183;mL-1 of ECM basement material. For HepG2 cells, use 4 mg&#183;mL-1 of reduced growth factor ECM basement material.</li>
		<li>Pipette 15 &#181;L of the ECM basement material/medium solution into a 96-well imaging plate. 
		NOTE: For large-scale spheroid production, this step can be performed with both an 8-channel pipette and a 96-channel pipetting head, as long as the tips and reservoir containing the ECM basement material are chilled.</li>
		<li>Centrifuge the plate for 20 min at 91 x g at 4 &#176;C.</li>
		<li>Incubate the plate for no longer than 30 min at 37 &#176;C.</li>
	</ol>
	</li>
	<li>Subculture and count cells
	<ol>
		<li>During the plate incubation period, incubate the cells with trypsin-EDTA and resuspend them in a complete medium containing 10% FBS.</li>
		<li>Pipette 10 &#181;L of the cell suspension into a hemocytometer counting chamber. Count the number of cells in 4 quadrants of the chamber.</li>
		<li>Calculate the number of cells within the cell suspension by determining the mean number of cells within the 4 quadrants. 
		NOTE: Cells can also be counted using automated cell-counting devices.</li>
		<li>Centrifuge the cells at 135 x g for 4 min at room temperature (RT).</li>
		<li>Once the cells are pelleted, aspirate the supernatant and resuspend the cells in a phenol red-free complete medium to obtain a concentration of 1 x 106 cells per mL.</li>
	</ol>
	</li>
	<li>Seed cells into ECM basement material-coated plates
	<ol>
		<li>Dilute the cells in a phenol red-free complete medium. 
		NOTE: The density of cells seeded is dependent on the cell line used. For HT-29 and HepG2 cells, 3 x 104 cells are seeded per well; for H358 cells, 4 x 104 cells are seeded per well.</li>
		<li>Seed the cells in a total volume of 35 &#181;L per well. Ensure to add them dropwise in a circular motion. 
		&#8203;NOTE: For large-scale spheroid production, this step can be performed with an 8-channel pipette, as long as the pipetting circular motion can be achieved.</li>
		<li>Incubate the cells for 1 h at 37 &#176;C in a humidified incubator with 5% CO2.</li>
		<li>Prepare a solution of ECM basement material in phenol red-free complete medium, which results in a final concentration of 2% ECM basement material in the well. To achieve this, add 1.2 &#181;L of ECM basement material to 23.8 &#181;L of phenol red-free complete medium per well, resulting in a final volume of 60 &#181;L per well.</li>
		<li>Incubate the cells at 37 &#176;C in a humidified incubator with 5% CO2.</li>
		<li>The following day, replace the medium with 100 &#181;L of fresh phenol red-free complete medium.</li>
		<li>Replace the medium every second day with 100 &#181;L of fresh phenol red-free complete medium.</li>
	</ol>
	</li>
</ol>
3. Immunofluorescence staining of spheroids
NOTE: This protocol is adapted from N&#252;rnberg et al., 202015. These adaptations are primarily based on the fact that the spheroids described in this protocol are smaller than those used in the N&#252;rnberg et al. work15 and, as such, facilitate shorter incubation times. For example, blocking times are reduced from 2 h to 1 h. In addition, as the protocol is designed for high-throughput production of spheroids, all of the processing steps are carried out in the well in which the spheroids are cultured, meaning that transfer of individual spheroids into tubes is not required.
<ol>
	<li>Prepare all solutions and buffers required for fixing and staining
	<ol>
		<li>Prepare Phosphate Buffered Saline (PBS) by adding 1 PBS tablet per 200 mL of water. Autoclave the PBS.</li>
		<li>Prepare paraformaldehyde (PFA) following steps 3.1.3-3.1.4.</li>
		<li>Use a heated stirrer to heat 400 mL of PBS to 60-70 &#176;C in a fume hood. Add 15 g of PFA while stirring. Once the PFA has dissolved, add 50 &#181;L of 1 M CaCl2 and 50 &#181;L of 1 M MgCl2.</li>
		<li>Add 100 mL of PBS to make a final volume of 500 mL. Use NaOH to equilibrate the PFA to pH 7.4. Filter the PFA through sterile vacuum filters (pore size 0.22 &#181;m), aliquot, and store at -20 &#176;C.</li>
		<li>Prepare a 1 M glycine stock solution by adding 3.75 g of glycine to 50 mL of PBS. Store at 4 &#176;C.</li>
		<li>Prepare 5 mL of permeabilization buffer by adding 100 &#181;L of Triton X-100, 1 mL of dimethyl sulfoxide (DMSO) and 1.5 mL of 1 M glycine to 2.4 mL of PBS. Store at 4 &#176;C for no longer than 2 weeks.</li>
		<li>Prepare 5 mL of blocking buffer by adding 100 &#181;L of Triton X-100, 0.5 mL of DMSO and 0.05 g of bovine serum albumin (BSA) to 4.9 mL of PBS. Aliquot the blocking buffer into 1.5 mL tubes and store at -20 &#176;C.</li>
		<li>Prepare 5 mL of antibody incubation buffer by adding 10 &#181;L of polysorbate 20, 0.05 g of BSA, and 250 &#181;L of DMSO to 4.74 mL of PBS. Aliquot the antibody incubation buffer into 1.5 mL tubes and store it at -20 &#176;C. 
		NOTE: In the protocol described here, spheroids are only assembled in the inner 60 wells of a 96-well plate, although they can be prepared in all 96 wells of the plate. The reason for only preparing spheroids in the inner 60 wells is that some high numerical aperture objective lenses are not capable of physically being able to image the entire well of the outer wells due to the &#39;skirt&#39; on some plate types. The above volumes are sufficient for the preparation of 60 wells containing spheroids.</li>
	</ol>
	</li>
	<li>Fix and permeabilize the spheroids
	<ol>
		<li>Carefully remove the medium from the spheroids, ensuring that the ECM basement material layer is not disturbed.</li>
		<li>Wash the spheroids twice with 70 &#181;L of PBS for 3 min each time.</li>
		<li>Fix the spheroids with 70 &#181;L of 3% PFA for 1 h at 37 &#176;C.</li>
		<li>Wash the spheroids twice with 70 &#181;L of PBS for 3 min each time.</li>
		<li>Quench with 70 &#181;L of 0.5 M glycine solution for 30 min at 37 &#176;C.</li>
		<li>Permeabilize the spheroids using 70 &#181;L of the permeabilization buffer for 30 min at RT.</li>
		<li>Wash the spheroids twice with 70 &#181;L of PBS for 3 min each time.</li>
		<li>Incubate the spheroids in 70 &#181;L of blocking buffer for 1 h at 37 &#176;C. 
		NOTE: Once the spheroids have been fixed, all subsequent processing steps can be performed using an 8-channel pipette, or a 96-well pipetting head, if available. This increases the speed of spheroid preparation prior to imaging.</li>
	</ol>
	</li>
	<li>Immunostain spheroids using primary and secondary antibodies
	<ol>
		<li>Dilute the primary antibody to an appropriate dilution in the antibody incubation buffer and add 70 &#181;L to each well. Incubate the spheroids with the primary antibody overnight. 
		NOTE: The dilution depends on the specific antibody used. In the example shown here, lysosomes are immunostained with mouse anti-LAMP1 antibodies using a dilution of 1:500.</li>
		<li>The following day, wash the spheroids 5 times with 70 &#181;L of PBS for 3 min each time.</li>
		<li>Dilute the secondary antibody at a dilution of 1:500, fluorescently-conjugated phalloidin at 1:500, and Hoechst 33342 (from a 1 mg mL-1 stock) at 1:5000 in the antibody incubation buffer and add 70 &#181;L to each well. Incubate overnight. 
		NOTE: The antibody dilution depends on the specific antibody used. Highly cross-adsorbed secondary antibodies that show high photostability and high brightness are recommended.</li>
		<li>The following day, wash the spheroids 5 times with 70 &#181;L of PBS for 3 min each time. 
		&#8203;NOTE: Plates can be stored for up to two weeks at RT prior to imaging, as long as the spheroids remain covered with PBS.</li>
	</ol>
	</li>
</ol>
4. Image acquisition and analysis of spheroids
<ol>
	<li>Image acquisition
	<ol>
		<li>Insert the 96-well plate containing spheroids into a confocal high-content screening microscope.</li>
		<li>Select the appropriate lasers to excite the fluorophores used.</li>
		<li>Acquire the channels sequentially to avoid cross-talk.</li>
		<li>Image the spheroids using appropriate objectives. 
		NOTE: The use of water immersion objectives is recommended if available. For example, a 20x/1.0 NA objective can image an entire well in ~77 fields of view. A 63x/1.15 NA objective can image an entire well in approximately 826 fields of view.</li>
		<li>Image ~30-40 slices, depending on the depth of the spheroid, with each slice taken at an interval of 1.5 &#181;m from the preceding one.</li>
	</ol>
	</li>
	<li>Image analysis
	<ol>
		<li>For morphological analysis of spheroids, follow steps 4.2.2-4.2.6.</li>
		<li>Segment the spheroids based on the fluorescently-conjugated phalloidin staining.</li>
		<li>Segment the nuclei based on the Hoechst 33342 staining.</li>
		<li>Segment the cytoplasm of each cell by the residual Hoechst 33342 stain that is present in the cell cytoplasm.</li>
		<li>Calculate different morphological properties of the spheroids, including volume, surface area, sphericity, and the number of nuclei per spheroid. 
		NOTE: This information is extracted using various algorithms that are in-built in the image analysis software of choice.</li>
		<li>Process images further to remove spheroids smaller than 75,000 &#181;m3 and larger than 900,000 &#181;m3. 
		NOTE: These values are suggestions to allow the removal of very small cell assemblies and large assemblies that may have arisen as a result of the fusion of multiple spheroids. Spheroids can also be categorized into different size classes at this step.</li>
		<li>To analyze single cells within spheroids, follow steps 4.2.8-4.2.12.</li>
		<li>Segment the spheroids based on the fluorescently-conjugated phalloidin staining.</li>
		<li>Segment the nuclei based on the Hoechst 33342 staining.</li>
		<li>Segment the cytoplasm of each cell by the residual Hoechst 33342 stain that is present in the cell cytoplasm.</li>
		<li>Segment the lysosomes based on the secondary antibody staining.</li>
		<li>Calculate different morphological properties of the cells within each spheroid, including the number of lysosomes per cell, cell volume, and cell surface area. 
		NOTE: This information is extracted using various algorithms that are in-built in the image analysis software of choice.</li>
	</ol>
	</li>
</ol>

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The authors declare that there are no competing interests associated with this work.

The approach described here details a platform for generating several hundred spheroids per well in a manner that is suitable for HCS and HCA. In comparison to other popular methods, such as the use of flat-bottomed and round-bottomed ULA plates, which allow the formation of only one spheroid per well18,19, this method provides the opportunity for high-resolution information to be extracted from large numbers of spheroids in a screening format. Notably, this method has been demonstrated in 3 different cell lines, representing various tumor types, highlighting its broad suitability to study a range of cellular processes in different models. Although the spheroids generated using this method shows some variability in size and shape, HCA can easily classify them by size (or any other parameters of interest). Our lab has successfully used this approach to study nanoparticle-induced toxicity as a function of spheroid size. Importantly, all the different size classes of spheroids can be studied in the same well, meaning that all were exposed to identical treatments, giving highly robust outputs from a large spheroid population17. The methodology described here could easily be adapted for use with other cell types representing different tissues. In addition, such spheroids could be used to assess different biological processes14. If the spheroids are generated with cells stably expressing fluorescently-tagged proteins, live cell imaging is also possible.
One critical step in this protocol is the production of the ECM basement material layer on which the cells are plated. When the layer is too thick, it can form a meniscus20 that promotes the growth of monolayers in the center of the well and spheroids only at the outer rims of the well. Therefore, it is essential that the correct concentration and volume of the ECM basement material is chosen to allow uniform spheroid formation throughout the well; this is always cell line-dependent. Also of note is that excess ECM basement material can cause issues during the immunostaining process, as it is not easily dissolved. This can in turn, lead to complications during image acquisition when using a HCS confocal microscope system. One other consideration is that different cell lines can require different ECM formulations. For example, HepG2 spheroids require ECM basement material with a reduced concentration of growth factors, compared to that used by H358 and HT-29 spheroids. The method of cell plating is also important, as this determines how the cells are distributed in the well. When either too many cells are seeded or when they are poorly distributed, this can lead to spheroid fusion (Figure 6). One other challenge of using ECM scaffolds is that they need to be handled at low temperatures (below 10 &#176;C), which is particularly problematic when using automation for HCS. However, this problem was recently solved by Eismann and colleagues (2020), who employed microarray technology to spot 0.2 &#181;L droplets of ECM basement material and cells into chambered slides. This was sufficient material to facilitate the growth of small spheroids21. Whether such an approach would also work for plating larger volumes of ECM basement material into wells of multi-well plates remains to be demonstrated. 
One problem associated with the analysis of 3D cell models using microscopy is the ability to extract information from the central planes of these assemblies. In this regard, permeabilization and antibody access during the immunostaining process can be problematic. However, the protocol published by N&#252;rnberg and colleagues15 enables highly consistent immunostaining of the entire spheroid. Using slight modifications to this protocol, this technique can immunostain even small subcellular structures (for example, lysosomes), with a high degree of consistency, regardless of whether the cells are central or peripheral with respect to the overall spheroid structure. It is important that this step is carefully optimized when using new antibodies. 
Another critical step is the imaging regime chosen. Imaging the appropriate number of z-slices through the spheroid is important, as this determines the volume of data that needs to be analyzed and stored. For example, imaging a limited number of z-planes at too great an interval can result in an underestimation of the overall spheroid size and volume. On the other hand, capturing too many z-planes can result in data analysis and storage problems. Very large datasets also require more intensive computational power for their analysis, particularly in volumetric mode. The optimal sampling interval in the z-plane is largely dictated by the characteristics of the objective lens, but for the examples shown here, ca. 40 confocal slices are required at an interval of 1.5 &#181;m to facilitate imaging through the entire depth of the spheroid. 
As mentioned, in order to reduce bias from analysis of selected planes, the use of a volumetric-based image analysis approach is strongly recommended. This allows not only spheroid-level information to be extracted but also cell-level data from each individual spheroid. Ultimately, the HCA pipelines need to be designed in such a way that they address the specific biological question being asked. Multiparametric outputs enable complex phenotypes to be quantitatively described. This has been demonstrated to work for 3D cell assemblies using commercial HCA software16,17, as well as freely-accessible software such as CellProfiler22,23. Volumetric analysis methods have the potential to be applied to other 3D cell model types, such as organoids and ex vivo patient-derived explants (PDEs), which even better replicate in vivo conditions. Recently, a high-throughput pipeline for producing brain organoids has been described24. This involves generating organoids in a 96-well plate and subsequently imaging them using a high-content screening microscope24. PDEs are highly advantageous in that they exhibit the original histology from the tumor, thus providing a cell model that recapitulates in vivo conditions, including features such as the tumor microenvironment25. These models can also, in principle, be immunostained, imaged, and analyzed using the approach described here26,27.
In summary, this protocol describes an accessible and robust method for the large-scale production of spheroids for HCS and HCA applications. Its applicability is shown with three different cell lines, producing spheroids that can be imaged at high resolution. This protocol also demonstrates that volumetric analysis can provide quantitative information about the spheroid population, as well as at the single-cell and subcellular levels, thereby making it useful for a wide variety of assays.

Traditionally, cell-based assays have been performed in monolayers growing on a solid substrate, which effectively can be considered as a two-dimensional (2D) environment. However, it is becoming increasingly recognized that 2D cell culture models lack physiological relevance in some contexts and cannot replicate many of the complex interactions that occur between cells1. Three-dimensional (3D) cell culture methods are rapidly becoming popular among researchers, and 3D cell models show high potential to better mimic the physiological conditions encountered by cells in the tissue environment2. There are several different types of 3D cell assemblies that have been employed, but the two most common types are spheroids and organoids. Spheroids can be grown from many different cell lines, and they can adopt various shapes and sizes depending on the cell type used and their method of assembly3. Moreover, spheroids can also be referred to as multicellular tumor spheroids (MCTS) when they are grown from cancer cell lines, and these models have found particular use for preclinical in vitro drug delivery and toxicity studies4,5. Organoids, on the other hand, aim to better mimic the tissues and organs in our body and can adopt more complex morphological arrangements. The production of organoids involves the use of adult stem cells or pluripotent stem cells, which can be reprogrammed into the appropriate cells to resemble the tissue or organ of interest. They are primarily used to investigate the development of organs and to model diseases and host-pathogen interactions6.
There is a range of different methods used to generate 3D cell assemblies. Scaffold-based methods provide a substrate or support to which cells can either attach or grow within. These scaffolds can have various shapes and can be made from a variety of different materials. The most common are extracellular matrix (ECM) components and hydrogels, and they are designed to resemble the natural extracellular environment of cells and thereby facilitate physiological interactions4,7. ECM basement material has been extracted from Engelbreth-Holm-Swarm mouse sarcoma tumor and shown to contain a rich mixture of ECM components, including laminin, type IV collagen, and perlecan8. However, despite its advantageous composition, there are two main challenges with its use, namely its batch-to-batch variability and that it has two different aggregate states below and above 10 &#176;C8,9. In contrast, hydrogels have the advantage of being flexible with respect to their components and rigidity, and they can be customized to suit the specific 3D cell assembly desired7,10. Scaffold-based methods are essential for organoid growth but are also widely used for spheroids. Scaffold-free methods, which work by preventing cells from attaching to the surface they are growing on, are usually only compatible with spheroid assembly. Examples include ultra-low attachment (ULA) plates, with either a flat bottom or U-bottom, which allow aggregation of the cells into spheroids, or the use of continuous agitation of the cells in spinner/rotation flasks10.
The use of 3D cell assemblies to study a wide variety of biological events is rapidly gaining popularity; however, it is essential that the method chosen for their culture is appropriate and compatible with the plans for their downstream analysis. For example, the use of ULA plates generates spheroids of high consistency; however, this method is restricted to the production of a single spheroid per well, thereby limiting throughput. Particular consideration is needed when fluorescence imaging of the 3D structure is planned. The substrate or plate on which the assembly is grown needs to be optically compatible, and care must be taken to minimize the effects of light scattering caused by any scaffolds that may have been used11. This particular problem becomes more acute as the numerical aperture of the microscope objective lenses increases.
Arguably one of the major reasons for selecting to work with a 3D cell model is to extract volumetric imaging data about not only the entire assembly but also the individual cells within it. MCTS models, in particular, are beginning to prove very powerful for deepening our understanding of how therapeutics transit from the outside to central cells (as they would need to in a tumor)12, and so gaining knowledge from individual cells at different layers is essential. The imaging technology that extracts quantitative information from individual cells is termed high-content analysis (HCA) and is a powerful approach in the context of screening13. To date, HCA has almost exclusively been applied to monolayer cultures, but there is an increasing realization that this approach has the power to be applied to 3D cultures enabling a wide range of cellular functions and processes to be studied14. It would have the clear advantage that large numbers of 3D assemblies could be analyzed, potentially providing cell-level data from across each structure. However, challenges associated with imaging of potentially thick cell assemblies, as well as the large data sets generated, need to be overcome.
In this article, a robust scaffold-based method for the large-scale production of MCTS in a 96-well format is presented. The method facilitates the production of several hundred 3D cell assemblies in each well. Examples are shown for three different cell types, representing solid tumor models of the liver, lung, and colon. The spheroids that form can be of a variety of sizes, and so HCA is used to select structures of a particular size and/or morphology. This feature provides the additional advantage that any phenotypes observed can be compared across spheroids of different sizes, but all treated in the same way in the same well. This approach is compatible with high-resolution imaging, importantly providing both cell-level and subcellular level quantitative data from the same cellular assemblies. This method of spheroid production has the additional advantage over methods that generate a single spheroid per well, that the large numbers of spheroids produced in each well potentially provide sufficient biomass for other downstream analyses, such as transcriptome and proteome profiling.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>0.05% Trypsin-EDTA (1x), phenol red</td>
			<td>Gibco</td>
			<td>25300054</td>
			<td></td>
		</tr>
		<tr>
			<td>Bovine Serum Albumin (BSA)</td>
			<td>Sigma Aldrich</td>
			<td>A6003</td>
			<td></td>
		</tr>
		<tr>
			<td>Calcium chloride</td>
			<td>Fisher Scientific</td>
			<td>10050070</td>
			<td></td>
		</tr>
		<tr>
			<td>CellCarrier-96 Ultra Microplates, tissue culture treated, black, 96-well with lid</td>
			<td>Perkin Elmer</td>
			<td>6055302</td>
			<td>These plates have been renamed as Phenoplates</td>
		</tr>
		<tr>
			<td>Dimethyl sulfoxide (DMSO)</td>
			<td>Sigma Aldrich</td>
			<td>D2650</td>
			<td></td>
		</tr>
		<tr>
			<td>Foetal Bovine Serum (FBS), qualified, EU approved, South America origin, heat inactivated</td>
			<td>Gibco</td>
			<td>10500064</td>
			<td></td>
		</tr>
		<tr>
			<td>Glycine</td>
			<td>Fisher Scientific</td>
			<td>BP381-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Goat anti-Mouse IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor 488</td>
			<td>Invitrogen</td>
			<td>A-11029</td>
			<td></td>
		</tr>
		<tr>
			<td>L-Glutamine solution, 200 mM</td>
			<td>Gibco</td>
			<td>25030024</td>
			<td></td>
		</tr>
		<tr>
			<td>Hoechst 33342</td>
			<td>Sigma Aldrich</td>
			<td>14533</td>
			<td></td>
		</tr>
		<tr>
			<td>Magnesium chloride</td>
			<td>Fisher Scientific</td>
			<td>10647032</td>
			<td></td>
		</tr>
		<tr>
			<td>Matrigel Basement Membrane Matrix, Phenol Red-free, LDEV-free, 10 mL</td>
			<td>Corning</td>
			<td>356237</td>
			<td>This Matrigel formulation can be also found with the same catalogue number at BD Biosciences</td>
		</tr>
		<tr>
			<td>Matrigel Growth Factor Reduced Matrigel</td>
			<td>BD Biosciences</td>
			<td>356231</td>
			<td>This Matrigel formulation can be also found with the same catalogue number at Corning</td>
		</tr>
		<tr>
			<td>McCoy&#39;s 5A medium</td>
			<td>Gibco</td>
			<td>26600023</td>
			<td></td>
		</tr>
		<tr>
			<td>McCoy&#39;s 5A medium with L glutamine and sodium bicarbonate, without phenol red</td>
			<td>Hyclone</td>
			<td>10358633</td>
			<td></td>
		</tr>
		<tr>
			<td>Minimum Essential Medium (MEM)</td>
			<td>Gibco</td>
			<td>21090022</td>
			<td></td>
		</tr>
		<tr>
			<td>Minimum Essential Medium (MEM), without glutamine, without phenol red</td>
			<td>Gibco</td>
			<td>51200046</td>
			<td></td>
		</tr>
		<tr>
			<td>Mouse monoclonal anti-LAMP1 antibody (concentrate)</td>
			<td>Developmental Studies Hybridoma Bank</td>
			<td>H4A3-a</td>
			<td></td>
		</tr>
		<tr>
			<td>Neubauer counting chamber</td>
			<td>Hirschmann</td>
			<td>8100203</td>
			<td></td>
		</tr>
		<tr>
			<td>Nunclon tissue culture dish with lid, polystyrene, 92 mm x 17 mm</td>
			<td>ThermoFisher Scientific</td>
			<td>150350</td>
			<td></td>
		</tr>
		<tr>
			<td>Opera Phenix HCS System and Harmony HCA software</td>
			<td>Perkin Elmer</td>
			<td>HCSHH14000000</td>
			<td></td>
		</tr>
		<tr>
			<td>Paraformaldehyde (PFA)</td>
			<td>Sigma Aldrich</td>
			<td>P6148</td>
			<td></td>
		</tr>
		<tr>
			<td>Phalloidin Alexa Fluor 568</td>
			<td>Invitrogen</td>
			<td>A12380</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (PBS) tablets</td>
			<td>Sigma Aldrich</td>
			<td>P4417</td>
			<td></td>
		</tr>
		<tr>
			<td>Polysorbate 20</td>
			<td>Sigma Aldrich</td>
			<td>P5927</td>
			<td></td>
		</tr>
		<tr>
			<td>RPMI 1640 Medium, GlutaMAX Supplement</td>
			<td>Gibco</td>
			<td>61870010</td>
			<td></td>
		</tr>
		<tr>
			<td>RPMI 1640 Medium, without glutamine, without phenol red</td>
			<td>Gibco</td>
			<td>11835063</td>
			<td></td>
		</tr>
		<tr>
			<td>Triton X-100</td>
			<td>Sigma Aldrich</td>
			<td>T9284</td>
			<td></td>
		</tr>
		<tr>
			<td>Stericup sterile vacuum filter units</td>
			<td>Millipore</td>
			<td>SCGVU05RE</td>
			<td></td>
		</tr>
	</tbody>
</table>

a robust method for the large-scale production of spheroids for high-content screening and analysis applications

High-content screening (HCS) and high-content analysis (HCA) are technologies that provide researchers with the ability to extract large-scale quantitative phenotypic measurements from cells. This approach has proved powerful for deepening our understanding of a wide range of both fundamental and applied events in cell biology. To date, the majority of applications for this technology have relied on the use of cells grown in monolayers, although it is increasingly realized that such models do not recapitulate many of the interactions and processes that occur in tissues. As such, there has been an emergence in the development and use of 3-dimensional (3D) cell assemblies, such as spheroids and organoids. Although these 3D models are particularly powerful in the context of cancer biology and drug delivery studies, their production and analysis in a reproducible manner suitable for HCS and HCA present a number of challenges. The protocol detailed here describes a method for the generation of multicellular tumor spheroids (MCTS), and demonstrates that it can be applied to three different cell lines in a manner that is compatible with HCS and HCA. The method facilitates the production of several hundred spheroids per well, providing the specific advantage that when used in a screening regime, data can be obtained from several hundred structures per well, all treated in an identical manner. Examples are also provided, which detail how to process the spheroids for high-resolution fluorescence imaging and how HCA can extract quantitative features at both the spheroid level as well as from individual cells within each spheroid. This protocol could easily be applied to answer a wide range of important questions in cell biology.

In this protocol, a robust method to produce 3D cell culture assemblies in the form of spheroids, using different cell types to represent various tumor tissues, is detailed. This method allows for the generation of hundreds of spheroids per well, which enables cell-based assays to be performed in a high-content manner (Figure 1). This approach has previously been used to study nanoparticle uptake in HT-29 spheroids16 and nanoparticle-induced toxicity in HepG2 spheroids17. The method relies on producing a thin and even distribution of scaffold material across the well bottom of an optical quality plate. Cells are seeded into each well, and further scaffold material, at a low concentration, is added as an overlay on the cells. This results in a base that supports even growth of spheroids, meaning that several hundred spheroids can be cultured in each well of a 96-well plate. A low magnification objective is used to generate an overview image of the entire population (Figure 2). Sub-regions of the well can then be selected and imaged using a high-resolution objective, and in each position, a complete confocal stack is acquired. This provides the necessary information for subsequent volumetric analysis of each spheroid.
The individual spheroids can then be analyzed by HCA, thereby providing information about the morphological properties of the spheroids. Typically the first step is to identify each spheroid as a single object. To do this, a fluorescence channel that is likely to give consistent staining or distribution throughout the spheroid is selected. In the example shown here, the signal in the fluorescently-conjugated phalloidin channel is used, as actin is found close to the plasma membrane in all cells in the different spheroid types (Figure 2 and Figure 3A). As a result of complete confocal stacks being generated, all HCA steps can be carried out in a volumetric manner rather than on a slice by slice basis. This is important as it removes any bias associated with the analysis of a small number of selected planes. This volumetric approach is then applied to the other channels in the image. The nuclei were detected and segmented based on the Hoechst 33342 staining, and this same channel can be used to detect the cell cytoplasm, as there is residual Hoechst 33342 present at low levels (Figure 3B). If downstream analysis of individual cells within the spheroid is needed, the other channels (for example, lysosomes immunostained with anti-LAMP1 antibodies) can also be processed in a similar manner. The volumetric approach allows all fluorescently-labeled structures to be visualized from all views (Figure 3C).
Having identified the spheroid as a distinct object, various morphological measurements at the spheroid level can be made. These measurements include calculation of the number of nuclei per spheroid (Figure 4A), as well as the sphericity (Figure 4B), volume (Figure 4C), and surface area (Figure 4D) of the spheroid. Depending on the HCA software used, other morphological features such as cross-sectional area, inner disk radius, and inner sphere radius can also be calculated. In the examples shown here, spheroids below 75,000 &#181;m3 and above 900,000 &#181;m3 were discarded from the measurements, but these parameters can be set by the user, depending on the desired spheroid properties for analysis. Spreadsheets were generated by the image analysis software and imported into RStudio for analysis. Boxplot graphs were produced to display the morphological properties of the different types of spheroids (Figure 4). These boxplots reveal the level of spheroid heterogeneity in the population, which is why it is important to quantify a large number of spheroids in any one experiment. This is a key advantage over methods that generate a single spheroid per well. The three spheroid types shown here show a high level of similarity with respect to their volume and surface area, although it is notable that the sphericity of HepG2 spheroids is somewhat lower than that of the other types shown here (Figure 4B).
Imaging spheroids with a high-resolution objective, such as the 63x water immersion objective used here, allows subcellular resolution of individual cells within the spheroid to be achieved. The different organelles can be segmented depending on the antibodies used. In the example shown here, lysosomes were identified based on immunostaining using anti-LAMP1 antibodies, followed by secondary antibody addition (Figure 3C). The segmentation of each organelle within each cell then allows the quantification of cell-level measurements. The typical volume of each cell in the three spheroid types (Figure 5A), as well as the number of lysosomes per cell (Figure 5B), are shown. The need for such subcellular detail is determined by the assay in which the spheroids will be used.
Optimizing the initial cell seeding density at the start of spheroid generation is a critical step. Adding too many cells still allows spheroid formation; however, this can result in the fusion of spheroids (Figure 6). This leads to the generation of irregularly shaped assemblies, which in turn can be highly problematic for the downstream identification of the spheroids. When spheroids are incorrectly identified as distinct structures, there can also be problems with the analysis of the individual cells. As such, careful optimization of each cell line used for the spheroid generation, including the cell seeding density and length of growth time, are critical parameters to establish.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63436/63436fig01v2.jpg" /> 
Figure 1: Schematic detailing the protocol used to generate spheroids for HCS and HCA. 96-well plates are coated with a layer of ECM basement material, followed by seeding of cells, which then initiate spheroid formation. Medium is replaced the following day and every second day thereafter. In preparation for imaging, spheroids are fixed, permeabilized, and immunostained with specific antibodies. Spheroids are then imaged using a confocal HCS microscope. Graphic created with BioRender.com. <a href="https://www.jove.com/files/ftp_upload/63436/63436fig01largev2.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/63436/63436fig02.jpg" /> 
Figure 2: Example images of H358, HepG2, and HT-29 spheroids. Fully automated HCS confocal imaging of (A) H358, (B) HepG2, and (C) HT-29 spheroids. Panels show a single well overview, as well as three example confocal slices and the volumetric reconstruction of one spheroid from each cell line. Nuclei stained with Hoechst 33342 are shown in blue, actin stained with fluorescently-conjugated phalloidin in red, and lysosomes immunostained for LAMP1 in green. Images of the well overview were acquired with a 20x water immersion objective (NA 1.0). Images of individual spheroids were acquired with a 63x water immersion objective (NA 1.15). <a href="https://www.jove.com/files/ftp_upload/63436/63436fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/63436/63436fig03.jpg" /> 
Figure 3: Example key steps in image analysis. (A) Each spheroid is first identified in volumetric mode by detection of the fluorescently-conjugated phalloidin staining. (B) Using this information as a mask, the cytoplasm of each cell is segmented by the residual Hoechst 33342 stain that is present in the cell cytoplasm. The nuclei are segmented by the Hoechst 33342 stain. The lysosomes are segmented using the antibody (anti-LAMP1) immunostaining. Volumetric views are shown. (C) 3-plane views of the same spheroid. The example shown is of a H358 cell spheroid. Images were acquired with a 63x water immersion objective (NA 1.15) <a href="https://www.jove.com/files/ftp_upload/63436/63436fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/63436/63436fig04.jpg" /> 
Figure 4: Examples of spheroid-level measurements. All measurements were made using an automated image analysis pipeline, and for three types of spheroids, namely H358, HepG2 and HT-29, imaged with a 20x objective. Shown are (A) mean number of nuclei per spheroid, (B) spheroid sphericity, (C) spheroid volume, and (D) spheroid surface area. All boxplots show the median value and quartiles for each spheroid type. Data are from 3 replicate wells; the total number of spheroids analyzed were 1259 (H358), 1522 (HepG2), and 1326 (HT-29). Images were acquired with a 20x water immersion objective (NA 1.0). <a href="https://www.jove.com/files/ftp_upload/63436/63436fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/63436/63436fig05.jpg" /> 
Figure 5: Examples of cell-level measurements from spheroids. All measurements were made using an automated image analysis pipeline, and for three types of spheroids, namely H358, HepG2, and HT-29, imaged with a 63x objective. Shown are (A) volumes of individual cells, and (B) mean numbers of lysosomes per cell. The total number of cells analyzed were 1410 (H358), 1625 (HepG2), and 1401 (HT-29), from 20 spheroids of each cell line. Images were acquired with a 63x water immersion objective (NA 1.15) <a href="https://www.jove.com/files/ftp_upload/63436/63436fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/63436/63436fig06v2.jpg" /> 
Figure 6: Example images showing effects of over-plating of cells on spheroid formation. Example images are shown for H358, HepG2, and HT-29 spheroids. Arrows indicate places where spheroids have likely fused. Images were acquired with a 20x water immersion objective (NA 1.0). <a href="https://www.jove.com/files/ftp_upload/63436/63436fig06largev2.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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A Robust Method for the Large-Scale Production of Spheroids for High-Content Screening and Analysis Applications

This protocol details a method for the production of three different types of spheroids in a manner that makes them suitable for large-scale high-content screening and analysis. In addition, examples are presented showing how they can be analyzed at spheroid and individual cell levels.

High-content screening (HCS) and high-content analysis (HCA) are technologies that provide researchers with the ability to extract large-scale ...

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3.1K Views.  University College Dublin. This protocol details a method for the production of three different types of spheroids in a manner that makes them suitable for large-scale high-content screening and analysis. In addition, examples are presented showing how they can be analyzed at spheroid and individual cell levels.

Video: A Robust Method for the Large-Scale Production of Spheroids for High-Content Screening and Analysis Applications

A Neuronal and Astrocyte Co-Culture Assay for High Content Analysis of Neurotoxicity

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing measurement of multiple cellular phenotypes within a single assay. In this study, we utilized HCA to develop a novel assay for neurotoxicity. Neurotoxicity assessment represents an important part of drug safety evaluation, as well as being a significant focus of environmental protection efforts. Additionally, neurotoxicity is also a well-accepted in vitro marker of the development of neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Recently, the application of HCA to neuronal screening has been reported. By labeling neuronal cells with &beta;III-tubulin, HCA assays can provide high-throughput, non-subjective, quantitative measurements of parameters such as neuronal number, neurite count and neurite length, all of which can indicate neurotoxic effects. However, the role of astrocytes remains unexplored in these models. Astrocytes have an integral role in the maintenance of central nervous system (CNS) homeostasis, and are associated with both neuroprotection and neurodegradation when they are activated in response to toxic substances or disease states. GFAP is an intermediate filament protein expressed predominantly in the astrocytes of the CNS. Astrocytic activation (gliosis) leads to the upregulation of GFAP, commonly accompanied by astrocyte proliferation and hypertrophy. This process of reactive gliosis has been proposed as an early marker of damage to the nervous system. The traditional method for GFAP quantitation is by immunoassay. This approach is limited by an inability to provide information on cellular localization, morphology and cell number. We determined that HCA could be used to overcome these limitations and to simultaneously measure multiple features associated with gliosis - changes in GFAP expression, astrocyte hypertrophy, and astrocyte proliferation - within a single assay. In co-culture studies, astrocytes have been shown to protect neurons against several types of toxic insult and to critically influence neuronal survival. Recent studies have suggested that the use of astrocytes in an in vitro neurotoxicity test system may prove more relevant to human CNS structure and function than neuronal cells alone. Accordingly, we have developed an HCA assay for co-culture of neurons and astrocytes, comprised of protocols and validated, target-specific detection reagents for profiling &beta;III-tubulin and glial fibrillary acidic protein (GFAP). This assay enables simultaneous analysis of neurotoxicity, neurite outgrowth, gliosis, neuronal and astrocytic morphology and neuronal and astrocytic development in a wide variety of cellular models, representing a novel, non-subjective, high-throughput assay for neurotoxicity assessment. The assay holds great potential for enhanced detection of neurotoxicity and improved productivity in neuroscience research and drug discovery.

This article describes a novel protocol and reagent set designed for sensitive measurement of neurotoxic effects of compounds and treatments on co-cultures of neurons and astrocytes using high content analysis. Results demonstrate that high content analysis represents an exciting novel technology for neurotoxicity assessment.

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing ...

Infinium Assay for Large-scale SNP Genotyping Applications

Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of variants within families or populations can facilitate identification of the genetic factors of disease. Illumina&#39;s panel of genotyping BeadChips allows investigators to genotype thousands or millions of single nucleotide polymorphisms (SNPs) or to analyze other genomic variants, such as copy number, across a large number of DNA samples. These SNPs can be spread throughout the genome or targeted in specific regions in order to maximize potential discovery. The Infinium assay has been optimized to yield high-quality, accurate results quickly. With proper setup, a single technician can process from a few hundred to over a thousand DNA samples per week, depending on the type of array. This assay guides users through every step, starting with genomic DNA and ending with the scanning of the array. Using propriety reagents, samples are amplified, fragmented, precipitated, resuspended, hybridized to the chip, extended by a single base, stained, and scanned on either an iScan or Hi Scan high-resolution optical imaging system. One overnight step is required to amplify the DNA. The DNA is denatured and isothermally amplified by whole-genome amplification; therefore, no PCR is required. Samples are hybridized to the arrays during a second overnight step. By the third day, the samples are ready to be scanned and analyzed. Amplified DNA may be stockpiled in large quantities, allowing bead arrays to be processed every day of the week, thereby maximizing throughput.

A protocol is described that uses Illumina&#39;s Infinium assays to perform large-scale genotyping. These assays can reliably genotype millions of SNPs across hundreds of individual DNA samples in three days. Once generated, these genotypes can be used to check for associations with a variety of different diseases or phenotypes.

Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of ...

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.&#160; Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. Utilizing normal-phased liquid chromatography coupled to high-resolution mass spectrometry with polarity switching and a rapid duty cycle, we describe a protocol to analyze the polar metabolic composition of biological material with high sensitivity, accuracy, and resolution.

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting ...

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application &#8211; SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min&#160;on a minimally configured laptop, or around 1 min&#160;on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary &#8220;Manual Initialize&#8221; and &#8220;Hand Draw&#8221; tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.

We present a high-throughput image analysis software application to measure the size of three-dimensional tumor spheroids imaged with bright-field microscopy. This application provides a fast and effective way to examine the effects of therapeutic drugs on spheroids, which is beneficial for researchers who wish to use spheroids in drug screens.

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to ...

Measurement and Analysis of Extracellular Acid Production to Determine Glycolytic Rate

Extracellular measurement of oxygen consumption and acid production is a simple and powerful way to monitor rates of respiration and glycolysis1. Both mitochondrial (respiration) and non-mitochondrial (other redox) reactions consume oxygen, but these reactions can be easily distinguished by chemical inhibition of mitochondrial respiration. However, while mitochondrial oxygen consumption is an unambiguous and direct measurement of respiration rate2, the same is not true for extracellular acid production and its relationship to glycolytic rate 3-6. Extracellular acid produced by cells is derived from both lactate, produced by anaerobic glycolysis, and CO2, produced in the citric acid cycle during respiration. For glycolysis, the conversion of glucose to lactate- + H+ and the export of products into the assay medium is the source of glycolytic acidification. For respiration, the export of CO2, hydration to H2CO3 and dissociation to HCO3- + H+ is the source of respiratory acidification. The proportions of glycolytic and respiratory acidification depend on the experimental conditions, including cell type and substrate(s) provided, and can range from nearly 100% glycolytic acidification to nearly 100% respiratory acidification 6. Here, we demonstrate the data collection and calculation methods needed to determine respiratory and glycolytic contributions to total extracellular acidification by whole cells in culture using C2C12 myoblast cells as a model.

Glycolysis is a defining metabolic marker in multiple biological systems. Monitoring glycolysis by measuring the extracellular flux of H+ is common, but requires correction to be quantitative and unambiguous. Here, we demonstrate how to gather and correct extracellular flux data to distinguish between respiratory and glycolytic sources of extracellular acidification.

Extracellular measurement of oxygen consumption and acid production is a simple and powerful way to monitor rates of respiration and glycolysis1. Both ...

High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents (HPHC)

Cigarette smoke (CS) is a major risk factor for cardiovascular and lung diseases. Because CS is a complex aerosol containing more than 7,000 chemicals1 it is challenging to assess the contributions of individual constituents to its overall toxicity. Toxicological profiles of individual constituents as well as mixtures can be however established in vitro, by applying high through-put screening tools, which enable the profiling of Harmful and Potentially Harmful Constituents (HPHCs) of tobacco smoke, as defined by the U.S. Food and Drug Administration (FDA).2
For an initial assessment, an impedance-based instrument was used for a real-time, label-free assessment of the compound&#39;s toxicity. The instrument readout relies on cell adhesion, viability and morphology that all together provide an overview of the cell status. A dimensionless parameter, named cell index, is used for quantification. A set of different staining protocols was developed for a fluorescence imaging-based investigation and a HCS platform was used to gain more in-depth information on the kind of cytotoxicity elicited by each HPHC.
Of the 15 constituents tested, only five were selected for HCS-based analysis as they registered a computable LD50 (&#60; 20 mM). These included 1-aminonaphtalene, Arsenic (V), Chromium (VI), Crotonaldehyde and Phenol. Based on their effect in the HCS, 1-aminonaphtalene and Phenol could be identified to induce mitochondrial dysfunction, and, together with Chromium (VI) as genotoxic based on the increased histone H2AX phosphorylation. Crotonaldehyde was identified as an oxidative stress inducer and Arsenic as a stress kinase pathway activator.
This study demonstrates that a combination of impedance-based and HCS technologies provides a robust tool for in vitro assessment of CS constituents.

High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC

The objective of the study was to assess the biological impact of 15 cigarette smoke constituents using a combination of an impedance-based real time cell analyzer and a high-content screening (HCS)-based platform for toxicological assessment in vitro. This study provides information on effective doses, toxicity and modes of action of the tested compounds.

Cigarette smoke (CS) is a major risk factor for cardiovascular and lung diseases. Because CS is a complex aerosol containing more than 7,000 chemicals1 it ...

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.

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 ...

ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth

Growth phenotypes of microorganisms are a strong indicator of their underlying genetic fitness and can be segregated into 3 growth regimes: lag-phase, log-phase, and stationary-phase. Each growth phase can reveal different aspects of fitness that are related to various environmental and genetic conditions. High-resolution and quantitative measurements of all 3 phases of growth are generally difficult to obtain. Here we present a detailed method to characterize all 3 growth phases on solid media using an assay called One-cell Doubling Evaluation of Living Arrays of Yeast (ODELAY). ODELAY quantifies growth phenotypes of individual cells growing into colonies on solid media using time-lapse microscopy. This method can directly observe population heterogeneity with each growth parameter in genetically identical cells growing into colonies. This population heterogeneity offers a unique perspective for understanding genetic and epigenetic regulation, and responses to genetic and environmental perturbations. While the ODELAY method is demonstrated using yeast, it can be utilized on any colony forming microorganism that is visible by bright field microscopy.

We present a method for quantifying growth phenotypes of individual yeast cells as they grow into colonies on solid media using time-lapse microscopy termed, One-cell Doubling Evaluation of Living Arrays of Yeast (ODELAY). Population heterogeneity of genetically identical cells growing into colonies can be directly observed and quantified.

Growth phenotypes of microorganisms are a strong indicator of their underlying genetic fitness and can be segregated into 3 growth regimes: lag-phase, ...

A Semiautomated ChIP-Seq Procedure for Large-scale Epigenetic Studies

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) is a powerful and widely used approach to profile chromatin DNA associated with specific histone modifications, such as H3K27ac, to help identify cis-regulatory DNA elements. The manual process to complete a ChIP-Seq is labor intensive, technically challenging, and often requires large-cell numbers (&#62;100,000 cells). The method described here helps to overcome those challenges. A complete semiautomated, microscaled H3K27ac ChIP-Seq procedure including cell fixation, chromatin shearing, immunoprecipitation, and sequencing library preparation, for batch of 48 samples for cell number inputs less than 100,000 cells is described in detail. The semiautonomous platform reduces technical variability, improves signal-to-noise ratios, and drastically reduces labor. The system can thereby reduce costs by allowing for reduced reaction volumes, limiting the number of expensive reagents such as enzymes, magnetic beads, antibodies, and hands-on time required. These improvements to the ChIP-Seq method suit perfectly for large-scale epigenetic studies of clinical samples with limited cell numbers in a highly reproducible manner.

This paper describes a semiautomated, microscaled ChIP-Seq protocol of DNA regions associated with a specific histone modification (H3K27ac) using a ChIP liquid-handler platform, followed by library preparation using tagmentation. The procedure includes control assessment for quality and quantity purposes and can be adopted to other histone modifications or transcription factors.

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) is a powerful and widely used approach to profile chromatin DNA associated with specific ...

A Simple Dry Sectioning Method for Obtaining Whole-Seed-Sized Resin Section and Its Applications

The morphology, size and quantity of cells, starch granules&#160;and protein bodies in seed determine the weight and quality of seed. They are significantly different among different regions of seed. In order to view the morphologies of cells, starch granules and protein bodies clearly, and quantitatively analyze their morphology parameters accurately, the whole-seed-sized section is needed. Though the whole-seed-sized paraffin section can investigate the accumulation of storage materials in seeds, it is very difficult to quantitatively analyze the morphology parameters of cells and storage materials due to the low resolution of the thick section. The thin resin section has high resolution, but the routine resin sectioning method is not suitable to prepare the whole-seed-sized section of mature seeds with a large volume and high starch content. In this study, we present a simple dry sectioning method for preparing the whole-seed-sized resin section. The technique can prepare the cross and longitudinal whole-seed-sized sections of developing, mature, germinated, and cooked seeds embedded in LR White resin, even for large seeds with high starch content. The whole-seed-sized section can be stained with fluorescent brightener 28, iodine, and Coomassie brilliant blue R250 to specifically exhibit the morphology of cells, starch granules, and protein bodies clearly, respectively. The image obtained can also be analyzed quantitatively to show the morphology parameters of cells, starch granules, and protein bodies in different regions of seed.

This technique allows for the fast and simple preparation of whole-seed-sized resin section for the observation and analysis of cells, starch granules, and protein bodies in different regions of the seed.