We would like to thank Dr. Alana Welms, Huntsman Cancer Institute, University of Utah, for providing us with the patient-derived xenografts (HCI-010). This work was supported by NIH grants R01CA205632, R21CA226542, and in part, by a grant from Agilent Technologies.

The study was reviewed and considered as &#34;exempt&#34; by the Institutional Review Board of Georgetown University (IRB # 2002-022). Freshly harvested bone marrow tissues were collected from discarded healthy human bone marrow collection filters that had been de-identified.
1. New chamber design (Figure 2)
<ol>
	<li>Open a new dual-chamber cell analyzer plate. Set aside the top chamber with electrodes.</li>
	<li>Using a milling machine, shave off 2 mm of the U-shaped bottom wells of the cell analyzer plate.</li>
	<li>Attach a 2 cm x 7 cm polyethersulfone (PES) membrane with 0.2 &#181;m pore size to the bottom of the shaved wells using UV-curated adhesive. Allow 30 min curation time to ensure the glue is completely cured and inert.</li>
	<li>Using a milling machine, cut out two longitudinal slits (1.5 mm x 5.6 mm) along the sides to snap into the ridges of the newly fabricated third chamber.</li>
	<li>Using a milling machine, create a third polycarbonate chamber that replicates the overall dimensions of the cell analyzer plate; 72 mm x 18 mm (Table of Materials).</li>
	<li>Create wells 4.8 mm deep and 4.75 mm in diameter to replicate the 16-well design of the cell analyzer plate. This allows 90 &#181;L of volume per well.</li>
	<li>On the sides, create two triangular ridges so that the chamber locks into the original slits created in step 1.4. The horizontal part of the triangle is 1.5 mm, the vertical is 1.4 mm, and the hypotenuse is 2.052 mm.</li>
	<li>Create a knob on the short side that is 50.8 mm in diameter and 1.397 mm in height to fit into the original plate&#39;s notch (Figure 2, Middle).</li>
	<li>Use a 0.9 mm thick rubber washer for each well to provide a sealed fit.</li>
</ol>
2. Cell culture (MDA-MB-231, DCIS, DCIS-&#916;4, J2-fibroblasts)
<ol>
	<li>Wash adherent cell cultures (~70% confluence) with 1x phosphate-buffered saline (PBS).</li>
	<li>Add 0.05% trypsin-EDTA solution to lift the cells off.</li>
	<li>Neutralize the trypsin solution with cell culture media containing serum and count the cells using an aliquot of the cell suspension. 
	&#8203;NOTE: The specific cell culture media can be found in Table 1.</li>
</ol>
3. Patient-derived xenograft dissociation
<ol>
	<li>Chop a fresh tumor piece (1 cm2) into fine mush using a sterile scalpel.</li>
	<li>Place in a 50 mL conical tube with 20 mL of DMEM F12 media supplemented with 3 mg/mL trypsin and 2 mg/mL collagenase.</li>
	<li>Incubate in a thermal shaker (150 RPM) at 37 &#176;C for 20 min.</li>
	<li>Spin the tube at 500 x g for 5 min; remove the supernatant.</li>
	<li>Add 20 &#956;L of DMEM F12 + 2% FBS to wash the cells; spin at 300 x g for 5 min and remove the supernatant. Repeat wash two more times.</li>
	<li>Resuspend in 1 mL of PDX media (Table 1) to count the cells.</li>
</ol>
4. Bone marrow cell extraction
<ol>
	<li>Flush the bone marrow (BM) collection filter with 25 mL of 1x PBS. 
	NOTE: In this study, PBS was added to a used BM collection filter from the hospital to collect the remaining BM in the filter.</li>
	<li>Add the flushed BM slowly to a 50 mL conical tube with 25 mL of density gradient medium, taking care to keep the layers as separate as possible.</li>
	<li>Spin at 800 x g for 20 min at 18 &#176;C</li>
	<li>Siphon off the top layers after centrifugation (fat/plasma) and transfer 5 mL of the white layer above the density gradient medium that has the BM cells to a 15 mL conical tube. 
	&#8203;NOTE: Alternatively, dip a 5 mL pipette into the top layer until it touches the middle layer (BM) and pipette out the middle layer very slowly without moving the pipette.</li>
	<li>Fill the 15 mL conical tube with 1x PBS (~10 mL) and spin at 300 x g for 15 min.</li>
	<li>Remove the supernatant; the remaining white pellet is the BM.</li>
	<li>If red blood cells are observed in the pellet, add 5 mL of RBC lysis solution (Table of Materials) and let it sit for 5 min at room temperature (RT). Spin at 300 x g for 5 min and remove the supernatant.</li>
	<li>Add 10 mL of 1x PBS to wash the cells, spin at 300 x g for 5 min&#160;and remove the supernatant. Repeat the RBC lysis (step 4.7) until the pellet is white.</li>
</ol>
5. Cell seeding and assembly
<ol>
	<li>Place all three sterile chambers in the tissue culture hood.</li>
	<li>Locate the knob on the short side of the lower chamber. Orient the lower chamber so that the knob is facing the experimenter.</li>
	<li>Add 30,000-50,000 cells in 90 &#956;L of media to each well of the lower chamber. Avoid forming bubbles. These are the stromal cells that will provide secreted factors but will not be detected by the electrodes of the top chamber.</li>
	<li>Use 5% fetal bovine serum-supplemented media in two lower chamber wells as a positive control for cell motility. Use 0% serum-supplemented media as a negative control.</li>
	<li>Let the lower chamber with the cells sit for 10-15 min in the hood to settle. 
	NOTE: This step is recommended if cells are adherent or grow in suspension.</li>
	<li>Rotate the lower chamber at 90&#176; and place the middle chamber on top so that the knob on the lower chamber slides into the notch on the middle chamber. 
	NOTE: The knob on the lower chamber and the blue dot on the middle chamber are at opposite ends of the assembly.</li>
	<li>Push vertically down until a click sound is heard from each of the long sides of the assembly.</li>
	<li>Add 160 &#956;L&#160;of serum-free media to all the wells of the middle chamber.</li>
	<li>Make sure a dome-shaped meniscus is visible after wells are filled; otherwise, adjust the final volume based on the pipette calibration. Avoid forming bubbles.</li>
	<li>Place the top chamber with electrodes facing down onto the middle chamber making sure to align the blue dots on the middle and top chambers.</li>
	<li>Push vertically down until a click sound is heard from each of the long sides of the assembly.</li>
	<li>Add 25-50 &#956;L&#160;of serum-free media to the top chamber.</li>
	<li>Mount the assembly on the dual purpose cell analyzer in the tissue culture incubator and wait for 30 min before measuring the background. 
	NOTE: This time is necessary to equilibrate the array and can be used to prepare the cell lines to be added to the top chamber.</li>
	<li>Measure the background (see section 6) and place the assembly back into the tissue culture hood.</li>
	<li>Add 30,000-50,000 cells in 100 &#956;L&#160;of serum-free media to each well of the top chamber. These are the cells that the electrode will detect once they successfully migrate through the membrane. 
	NOTE: To achieve maximum response, it is recommended to grow cells in serum-free or low serum media for 6-18 h before performing the assay.</li>
	<li>Let the assembly stand in the hood for 30 min before mounting on the dual purpose cell analyzer for impedance measurement.</li>
</ol>
6. Background and impedance measurement
<ol>
	<li>Place the array into the cradle in the dual purpose cell analyzer instrument.</li>
	<li>Open the cell analyzer software and select the cradle to be used.</li>
	<li>Click on the Message tab and make sure it says Connections OK to ensure the array is well placed in the cradle and the electrodes are well aligned with the sensors.</li>
	<li>Click on the Experiment Notes tab and fill in as much information about the experiment as possible.</li>
	<li>Click on the Layout tab and fill in the description of the array layout.</li>
	<li>Click on the Schedule tab and add two steps from the Steps menu; a background step (one sweep) and a test step with 100 sweeps-a sweep every 15 min, totaling 25 h.</li>
	<li>After the array has been in the dual purpose cell analyzer incubator for 30 min, click on the Play button to start background measurement. A window asking to choose the folder to save the data will pop up.</li>
	<li>After the background measurement is done, remove the array from the cradle and place it back in the cell culture hood.</li>
	<li>Add cells to the top chamber as described in step 5.13, and keep the assembly in the tissue culture hood for 30 min for the cells to settle.</li>
	<li>Place the array back into the dual purpose cell analyzer and check the Message tab for the Connections OK message.</li>
	<li>Click on the Play button to start impedance measurement.</li>
	<li>Click on the Plot tab to monitor the progress of the signal.</li>
	<li>If the endpoint is reached before 25 h, click on the Abort step from the Execute drop-down menu.</li>
	<li>To export data, right-click on the graph, choose Copy in the list format, and then paste the data in a spreadsheet. 
	&#8203;NOTE: The data can be exported as cell index or delta cell index. Graph and/or layout information can also be chosen for export.</li>
</ol>
7. Detachment and cell collection
<ol>
	<li>Monitor the migration rate in real-time on the dual purpose cell analyzer to determine the stopping point of interest (6-18 h). 
	NOTE: The stopping point depends on the cell&#39;s invasion rate and when a distinct invasion signal from the negative control is achieved.</li>
	<li>Once achieved, unmount the assembly from the dual purpose cell analyzer and place it in the tissue culture hood.</li>
	<li>Prepare an appropriate number of 1.5 mL microcentrifuge tubes to collect the cells from the wells of interest.</li>
	<li>Place the assembly in a 10 cm dish to contain liquids when the chambers detach.</li>
	<li>Push the flexible snapping ends on the long side of the middle chamber inward until a click sound is heard.</li>
	<li>Dismantle the top chamber and invert it into a new 10 cm dish.</li>
	<li>Use a cell lifter with a 13 mm blade to collect the cells from all the wells harboring the same experimental condition (i.e., cell type, drug treatment, etc.). 
	NOTE: Design the setup to have at least two wells for each experimental condition to achieve statistically significant change from negative controls.</li>
	<li>Rinse or dip the blade in 1x phosphate buffered saline to collect the cells in 1.5 mL microcentrifuge tubes.</li>
	<li>Spin down the cells at 500 x g for 5 min.</li>
	<li>Propagate the collected cells (see section 8) or perform end point analysis such as single-cell RNA-seq. 
	&#8203;NOTE: For bulk RNA-seq, use a low cell number RNA extraction kit.</li>
</ol>
8. 3D cell propagation and retrieval
NOTE: Due to the small number of cells collected, seed the cells in 3D using an extracellular matrix (ECM) to enhance viability. That said, 2D culture is also an option at this point, especially if the cells used are from established cell lines.
<ol>
	<li>Thaw an aliquot of the basement membrane matrix at 4 &#176;C overnight. Keep the basement membrane matrix on ice until ready to use.</li>
	<li>Add 25 &#956;L&#160;of cold basement membrane matrix to the pellet of live cells collected and gently pipette up and down to mix. Avoid forming bubbles.</li>
	<li>Add the cell-basement membrane matrix mix to the bottom of a small tissue culture well (i.e., in a 96-well plate), forming a dome. Try not to touch the walls of the well. Incubate at 37 &#176;C for 20 min before gently adding 100 &#956;L&#160;of media dropwise.</li>
	<li>To retrieve cells, aspirate the media and add 100 &#956;L&#160;of dispase to each well.</li>
	<li>Incubate at RT for 10 min, pipetting up and down occasionally.</li>
	<li>Transfer the cells and the dissolved basement membrane matrix into a 1.5 mL microcentrifuge tube. Add 1 mL of 1x PBS, spin at 300 x g for 5 min and remove the supernatant. Repeat the wash once.</li>
	<li>Aspirate the supernatant. Split the cells in the pellet or perform endpoint analysis.</li>
</ol>

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C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+single-chain+antibody+targeting+of+the+ligand-binding+domain+in+the+anaplastic+lymphoma+kinase+receptor.">Effect of single-chain antibody targeting of the ligand-binding domain in the anaplastic lymphoma kinase receptor.</a> Oncogene. 28 (37), 3296-3306 (2009).</li><li>Abassi, Y. A., Wang, X., Xu, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real+time+electronic+cell+sensing+system+and+applications+for+cytotoxcity+profiling+and+compound+assays.">Real time electronic cell sensing system and applications for cytotoxcity profiling and compound assays.</a> United States Patent. , 1-88 (2013).</li><li>Abassi, Y. 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Georgetown University filed a patent related to some of the approaches described in this manuscript. G.M.S, A.W, L.D, and M.P are named as inventors on this application and declare that as a potential conflict of interest.

We have modified the design of a dual-chambered array to include a third chamber for monitoring cell invasion in real-time in the presence of stromal cells. We have observed distinct effects of co-cultured fibroblasts on invasive and non-invasive cancer cells indicating that the array can be used to distinguish between cancer cell subpopulations that respond differently to factors produced by co-cultured stromal cells. The array was also used to monitor endothelial cell invasion into stromal tissues, a critical step duri...

Cell invasion is an important process that allows cells to cross basement membrane barriers in response to environmental cues provided by stromal cells. It is a crucial step during several stages of development for immune responses, wound healing, tissue repair, and malignancies that can progress from local lesions to invasive and metastatic cancers1. Assays developed early on to measure the invasive potential of cell populations typically generate a single endpoint measurement or require pre-labeling of invasive cells2. The integration of microelectronics and microfluidics techniques is now developed to detect different aspects of cell biology such as viability, movement, and attachment using the electric impedance of live cells on microelectrodes3,4. Impedance measurement allows for a label-free, non-invasive and quantitative assessment of cell status3. Here we describe a three-chambered array based on the design of the Real-Time Cellular Analysis (RTCA) system that was developed by Abassi et al.5. The three-chambered array allows for the assessment of co-cultured cells on cellular invasion and recovery of invasive cells for additional analyses or expansion.
In the cell analyzer system, cells invade through an extracellular matrix coated onto a porous membrane and reach an interdigitated electrode array positioned on the opposite side of the barrier. As the invasive cells continue to attach and occupy this electrode array over time, the electrical impedance changes in parallel. The current system comprises a cell invasion and migration (CIM) 16-well plate with two chambers. The RTCA-DP (dual purpose) (called dual purpose cell analyzer henceforth) instrument contains sensors for impedance measurement and integrated software to analyze and process the impedance data. Impedance values at baseline depend on the ionic strength of media in the wells and are changed as cells attach to the electrodes. The impedance changes depend on the number of cells, their morphology, and the extent to which cells attach to the electrodes. A measurement of the wells with media before the cells are added is considered as the background signal. The background is subtracted from impedance measurements after reaching equilibrium with cells attaching and spreading onto the electrodes. A unitless parameter of the status of the cells on an electrode termed Cell Index (CI) is calculated as follows: CI = (impedance after equilibrium - impedance in the absence of cells) / nominal impedance value6. When migration rates of different cell lines are compared, the Delta CI can be used to compare cell status regardless of the difference in attachment that is represented in the first few measurements.
The newly designed three-chambered array builds on the existing design and uses the top chamber from the dual purpose cell analyzer system that contains the electrodes. The modified middle and bottom chambers are adapted to fit the assembly into the dual purpose cell analyzer for impedance measurement and analysis using the integrated software. The two major advances that the new design provides over the existing dual-chamber CIM-plate (called cell analyzer plate henceforth) are: i) the ability to recover, and then analyze invasive cell subpopulations that are present in heterogeneous cell mixes and ii) the option to assess the impact of secreted factors from co-cultured stromal or immune cells on cell invasion (Figure 1).
This technology can be useful in studying the subpopulations of cells with different invasive capacities. That includes (a) invasive cancer cells that invade surrounding tissues or blood and lymphatic vessels or extravasate at metastatic seeding sites in distant organs, (b) cells from the immune system that invade tissues to tackle pathogens or diseased cells, (c) endothelial cells that invade tissues to form new blood vessels during tissue reorganization or wound healing, as well as (d) stromal cells from the tumor microenvironment that support and invade along with cancer cells. The approach allows the inclusion of stromal cross-talk that can modulate cell motility and invasion. The feasibility studies shown here use this modified array focused on cancer cell invasion and the interaction with the stroma as a model system, including endothelial invasion in response to differential signals from cancer cells. The approach can be extrapolated to isolate cancer cells and other cell types such as subpopulations of immune cells, fibroblasts, or endothelial cells. We tested invasive and non-invasive established breast cancer cell lines as a proof of principle. We also used cells from patient-derived xenograft (PDX) invasion in response to immune cells from human bone marrow to show feasibility for future use also in clinical diagnostic settings. PDX are patient tumor tissues that are implanted in immunocompromised or humanized mice model to allow for studying of growth, progression, and treatment options for the original patient7,8.

<table><tbody><tr><td>0.05% Trypsin-EDTA</td><td>Thermofisher</td><td>25300-054</td><td></td></tr><tr><td>Adhesive</td><td>Norland Optical Adhesive</td><td>NOA63</td><td></td></tr><tr><td>Bovine serum albumin (BSA)</td><td>Sigma</td><td>A9418</td><td></td></tr><tr><td>Cell lifter</td><td>Sarstedt</td><td>83.1832</td><td></td></tr><tr><td>Cholera Toxin from Vibrio cholerae</td><td>Thermofisher</td><td>12585-014</td><td></td></tr><tr><td>CIM-plate</td><td>Agilent</td><td>5665817001</td><td>Cell analyzer plate</td></tr><tr><td>Collagenase from Clostridium histolyticum</td><td>Sigma</td><td>C0130</td><td></td></tr><tr><td>Dispase</td><td>StemCell</td><td>7913</td><td></td></tr><tr><td>DMEM</td><td>Thermofisher</td><td>11995-065</td><td></td></tr><tr><td>DMEM-F12</td><td>Thermofisher</td><td>11875-093</td><td></td></tr><tr><td>Fetal Bovine Serum (FBS), Heat Inactivated</td><td>Omega Scientific</td><td>FB-12</td><td></td></tr><tr><td>HEPES</td><td>Thermofisher</td><td>15630106</td><td></td></tr><tr><td>Horse serum (HS)</td><td>Gibco</td><td>16050-122</td><td></td></tr><tr><td>Human EGF</td><td>Peprotech</td><td>AF-100-15</td><td></td></tr><tr><td>Human umbilical Vein endothelail cells (HUVEC)</td><td>LONZA (RRID:CVCL_2959)</td><td>C-2517A</td><td></td></tr><tr><td>HUVEC media</td><td>LONZA</td><td>CC-3162</td><td></td></tr><tr><td>Hydrocortisone</td><td>Sigma</td><td>H4001</td><td></td></tr><tr><td>Insulin Transferrin Selenium Ethanolamine (ITSX) (100x)</td><td>Thermofisher</td><td>51500056</td><td></td></tr><tr><td>Insulin, Human Recombinant, Zinc Solution</td><td>Sigma</td><td>C8052</td><td></td></tr><tr><td>J2 Fibroblasts</td><td>Stemcell (RRID:CVCL_W667)</td><td>100-0353</td><td></td></tr><tr><td>LymphoPrep</td><td>Stemcell</td><td>7851</td><td>Density gradient medium for the isolation of mononuclear cells</td></tr><tr><td>Matrigel</td><td>Corning</td><td>354230</td><td>Basement membrane matrix</td></tr><tr><td>MCFDCIS.com cells ( DCIS)</td><td>RRID:CVCL_5552</td><td></td><td></td></tr><tr><td>MDA-MB-231 cells</td><td>RRID:CVCL_0062</td><td></td><td></td></tr><tr><td>Milling machine</td><td></td><td></td><td>Bridgeport Series 1 Vertical</td></tr><tr><td>Phosphate-buffered saline (1x)</td><td>Thermofisher</td><td>10010049</td><td></td></tr><tr><td>Polyethersulfone (PES) membrane</td><td>Sterlitech</td><td>PCTF029030</td><td></td></tr><tr><td>RBC lysis solution</td><td>Stemcell</td><td>7800</td><td></td></tr><tr><td>RNeasy Micro Kit</td><td>Qiagen</td><td>74004</td><td></td></tr><tr><td>RTCA DP analyzer</td><td>Agilent</td><td>3X16</td><td>Dual purpose cell analyzer</td></tr><tr><td>Trypsin</td><td>Sigma</td><td>T4799</td><td></td></tr></tbody></table>

real-time detection and capture of invasive cell subpopulations from co-cultures

Invasion and metastatic spread of cancer cells are the major cause of death from cancer. Assays developed early on to measure the invasive potential of cancer cell populations typically generate a single endpoint measurement that does not distinguish between cancer cell subpopulations with different invasive potential. Also, the tumor microenvironment consists of different resident stromal and immune cells that alter and participate in the invasive behavior of cancer cells. Invasion into tissues also plays a role in immune cell subpopulations fending off microorganisms or eliminating diseased cells from the parenchyma and endothelial cells during tissue remodeling and angiogenesis. Real-Time Cellular Analysis (RTCA) that utilizes impedance biosensors to monitor cell invasion was a major step forward beyond endpoint measurement of invasion: this provides continuous measurements over time and thus can reveal differences in invasion rates that are lost in the endpoint assay. Using current RTCA technology, we expanded dual-chamber arrays by adding a further chamber that can contain stromal and/or immune cells and allows measuring the rate of invasion under the influence of secreted factors from co-cultured stromal or immune cells over time. Beyond this, the unique design allows for detaching chambers at any time and isolating of the most invasive cancer cell, or other cell subpopulations that are present in heterogeneous mixes of tumor isolates tested. These most invasive cancer cells and other cell subpopulations drive malignant progression to metastatic disease, and their molecular characteristics are important for in-depth mechanistic studies, the development of diagnostic probes for their detection, and the assessment of vulnerabilities. Thus, the inclusion of small- or large-molecule drugs can be used to test the potential of therapies that target cancer and/or stromal cell subpopulations with the goal of inhibiting (e.g., cancer cells) or enhancing (e.g., immune cells) invasive behavior.

Using the newly designed three-chambered array, invasion of the cells was tested in the presence or absence of stromal cells such as fibroblasts. MDA-MB-231 cell invasion was enhanced when irradiated Swiss 3T3 fibroblasts (J2 strain) were seeded in the bottom chamber, allowing for the exchange of factors between the two cell lines. Interestingly, MDA-MB-231 invasion increased when 3T3-J2 cells were doubled in number (Figure 3A). On the other hand, the invasion rate of an invasive clone of MC...

Watch this Scientific Journal Video about Real-Time Detection and Capture of Invasive Cell Subpopulations from Co-Cultures at JoVE.com

Real-Time Detection and Capture of Invasive Cell Subpopulations from Co-Cultures

We describe an approach to detect and capture invasive cell subpopulations in real-time. The experimental design uses Real-Time Cellular Analysis by monitoring changes in the electric impedance of cells. Invasive cancer, immune, endothelial or stromal cells in complex tissues can be captured, and the impact of co-cultures can be assessed.

Invasion and metastatic spread of cancer cells are the major cause of death from cancer. Assays developed early on to measure the invasive potential of ...

real-time-detection-capture-invasive-cell-subpopulations-from-co

Universidad de Cartagena UDEC

Research

JoVE Journal

Cancer Research

2.3K Views.  Georgetown University Medical Center. We describe an approach to detect and capture invasive cell subpopulations in real-time. The experimental design uses Real-Time Cellular Analysis by monitoring changes in the electric impedance of cells. Invasive cancer, immune, endothelial or stromal cells in complex tissues can be captured, and the impact of co-cultures can be assessed.

Video: Real-Time Detection and Capture of Invasive Cell Subpopulations from Co-Cultures

A Versatile Automated Platform for Micro-scale Cell Stimulation Experiments

Study of cells in culture (in vitro analysis) has provided important insight into complex biological systems. Conventional methods and equipment for in vitro analysis are well suited to study of large numbers of cells (&ge;105) in milliliter-scale volumes (&ge;0.1 ml). However, there are many instances in which it is necessary or desirable to scale down culture size to reduce consumption of the cells of interest and/or reagents required for their culture, stimulation, or processing. Unfortunately, conventional approaches do not support precise and reproducible manipulation of micro-scale cultures, and the microfluidics-based automated systems currently available are too complex and specialized for routine use by most laboratories. To address this problem, we have developed a simple and versatile technology platform for automated culture, stimulation, and recovery of small populations of cells (100 - 2,000 cells) in micro-scale volumes (1 - 20 &mu;l). The platform consists of a set of fibronectin-coated microcapillaries ("cell perfusion chambers"), within which micro-scale cultures are established, maintained, and stimulated; a digital microfluidics (DMF) device outfitted with "transfer" microcapillaries ("central hub"), which routes cells and reagents to and from the perfusion chambers; a high-precision syringe pump, which powers transport of materials between the perfusion chambers and the central hub; and an electronic interface that provides control over transport of materials, which is coordinated and automated via pre-determined scripts. As an example, we used the platform to facilitate study of transcriptional responses elicited in immune cells upon challenge with bacteria. Use of the platform enabled us to reduce consumption of cells and reagents, minimize experiment-to-experiment variability, and re-direct hands-on labor. Given the advantages that it confers, as well as its accessibility and versatility, our platform should find use in a wide variety of laboratories and applications, and prove especially useful in facilitating analysis of cells and stimuli that are available in only limited quantities.

We have developed an automated cell culture and interrogation platform for micro-scale cell stimulation experiments. The platform offers simple, versatile, and precise control in cultivating and stimulating small populations of cells, and recovering lysates for molecular analyses. The platform is well suited to studies that use precious cells and/or reagents.

Study of cells in culture (in vitro analysis) has provided important insight into complex biological systems. Conventional methods and equipment for in ...

Bioengineering

Monitoring Cancer Cell Invasion and T-Cell Cytotoxicity in 3D Culture

Significant progress has been made in treating cancer with immunotherapy, although a large number of cancers remain resistant to treatment. A limited number of assays allow for direct monitoring and mechanistic insights into the interactions between tumor and immune cells, amongst which, T-cells play a significant role in executing the cytotoxic response of the adaptive immune system to cancer cells. Most assays are based on two-dimensional (2D) co-culture of cells due to the relative ease of use but with limited representation of the invasive growth phenotype, one of the hallmarks of cancer cells. Current three-dimensional (3D) co-culture systems either require special equipment or separate monitoring for invasion of co-cultured cancer cells and interacting T-cells.
Here we describe an approach to simultaneously monitor the invasive behavior in 3D of cancer cell spheroids and T-cell cytotoxicity in co-culture. Spheroid formation is driven by enhanced cell-cell interactions in scaffold-free agarose microwell casts with U-shaped bottoms. Both T-cell co-culture and cancer cell invasion into type I collagen matrix are performed within the microwells of the agarose casts without the need to transfer the cells, thus maintaining an intact 3D co-culture system throughout the assay. The collagen matrix can be separated from the agarose cast, allowing for immunofluorescence (IF) staining and for confocal imaging of cells. Also, cells can be isolated for further growth or subjected to analyses such as for gene expression or fluorescence activated cell sorting (FACS). Finally, the 3D co-culture can be analyzed by immunohistochemistry (IHC) after embedding and sectioning. Possible modifications of the assay include altered compositions of the extracellular matrix (ECM) as well as the inclusion of different stromal or immune cells with the cancer cells.

The presented approach simultaneously evaluates cancer cell invasion in 3D spheroid assays and T-cell cytotoxicity. Spheroids are generated in a scaffold-free agarose multi-microwell cast. Co-culture and embedding in type I collagen matrix are performed within the same device which allows to monitor cancer cell invasion and T-cell mediated cytotoxicity.

Significant progress has been made in treating cancer with immunotherapy, although a large number of cancers remain resistant to treatment. A limited ...

A Microfluidic Platform for High-throughput Single-cell Isolation and Culture

Studying the heterogeneity of single cells is crucial for many biological questions, but is technically difficult. Thus, there is a need for a simple, yet high-throughput, method to perform single-cell culture experiments. Here, we report a microfluidic chip-based strategy for high-efficiency single-cell isolation (~77%) and demonstrate its capability of performing long-term single-cell culture (up to 7 d) and cellular heterogeneity analysis using clonogenic assay. These applications were demonstrated with KT98 mouse neural stem cells, and A549 and MDA-MB-435 human cancer cells. High single-cell isolation efficiency and long-term culture capability are achieved by using different sizes of microwells on the top and bottom of the microfluidic channel. The small microwell array is designed for precisely isolating single-cells, and the large microwell array is used for single-cell clonal culture in the microfluidic chip. This microfluidic platform constitutes an attractive approach for single-cell culture applications, due to its flexibility of adjustable cell culture spaces for different culture strategies, without decreasing isolation efficiency.

Here, we present a protocol for isolating and culturing single cells with a microfluidic platform, which utilizes a new microwell design concept to allow for high-efficiency single cell isolation and long-term clonal culture.

Studying the heterogeneity of single cells is crucial for many biological questions, but is technically difficult. Thus, there is a need for a simple, yet ...

Establishing Single-Cell Based Co-Cultures in a Deterministic Manner with a Microfluidic Chip

Cell co-culture assays have been widely used for studying cell-cell interactions between different cell types to better understand the biology of diseases including cancer. However, it is challenging to clarify the complex mechanism of intercellular interactions in highly heterogeneous cell populations using conventional co-culture systems because the heterogeneity of the cell subpopulation is obscured by the average values; the conventional co-culture systems can only be used to describe the population signal, but are incapable of tracking individual cells behavior. Furthermore, conventional single-cell experimental methods have low efficiency in cell manipulation because of the Poisson distribution. Microfabricated devices are an emerging technology for single-cell studies because they can accurately manipulate single cells at high-throughput and can reduce sample and reagent consumption. Here, we describe the concept and application of a microfluidic chip for multiple single-cell co-cultures. The chip can efficiently capture multiple types of single cells in a culture chamber (~46%) and has a sufficient culture space useful to study the cells&#39; behavior (e.g., migration, proliferation, etc.) under cell-cell interaction at the single-cell level. Lymphatic endothelial cells and oral squamous cell carcinoma were used to perform a single-cell co-culture experiment on the microfluidic platform for live multiple single-cell interaction studies.

This report describes a microfluidic chip-based method to set up a single cell culture experiment in which high-efficiency pairing and microscopic analysis of multiple single cells can be achieved.

Cell co-culture assays have been widely used for studying cell-cell interactions between different cell types to better understand the biology of diseases ...

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Quantification of cells is necessary for a wide range of biological and biochemical studies. Conventional image analysis of cells typically employs either fluorescence detection approaches, such as immunofluorescent staining or transfection with fluorescent proteins or edge detection techniques, which are often error-prone due to noise and other non-idealities in the image background. 
We designed a new algorithm that could accurately count and distinguish macrophages and fibroblasts, cells of different phenotypes that often colocalize during tissue regeneration. MATLAB was used to implement the algorithm, which differentiated distinct cell types based on differences in height from the background. A primary algorithm was developed using an area-based method to account for variations in cell size/structure and high-density seeding conditions. 
Non-idealities in cell structures were accounted for with a secondary, iterative algorithm utilizing internal parameters such as cell coverage computed using experimental data for a given cell type. Finally, an analysis of coculture environments was carried out using an isolation algorithm in which various cell types were selectively excluded based on the evaluation of relative height differences within the image. This approach was found to accurately count cells within a 5% error margin for monocultured cells and within a 10% error margin for cocultured cells.

We present a method, which utilizes a generalizable area-based image analysis approach to identify cell counts. Analysis of different cell populations exploited the significant cell height and structure differences between distinct cell types within an adaptive algorithm.

Quantification of cells is necessary for a wide range of biological and biochemical studies. Conventional image analysis of cells typically employs either ...

Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

Polymicrobial communities are ubiquitous in nature, yet studying their interactions at the single-cell level is difficult. Thus, a microscopy-based method has been developed for observing interspecies interactions between two bacterial pathogens. The use of this method to interrogate interactions between a motile Gram-negative pathogen, Pseudomonas aeruginosa and a non-motile Gram-positive pathogen, Staphylococcus aureus is demonstrated here. This protocol consists of co-inoculating each species between a coverslip and an agarose pad, which maintains the cells in a single plane and allows for visualization of bacterial behaviors in both space and time.
Furthermore, the time-lapse microscopy demonstrated here is ideal for visualizing the early interactions that take place between two or more bacterial species, including changes in bacterial species motility in monoculture and in coculture with other species. Due to the nature of the limited sample space in the microscopy setup, this protocol is less applicable for studying later interactions between bacterial species once cell populations are too high. However, there are several different applications of the protocol which include the use of staining for imaging live and dead bacterial cells, quantification of gene or protein expression through fluorescent reporters, and tracking bacterial cell movement in both single species and multispecies experiments.

This live-bacterial cell imaging protocol allows for visualization of interactions between multiple bacterial species at the single-cell level over time. Time-lapse imaging allows for observation of each bacterial species in monoculture or coculture to interrogate interspecies interactions in multispecies bacterial communities, including individual cell motility and viability.

Polymicrobial communities are ubiquitous in nature, yet studying their interactions at the single-cell level is difficult. Thus, a microscopy-based method ...

Immunology and Infection

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Complex disease models demand cutting-edge tools able to deliver physiologically and pathologically relevant, actionable insights, and unveil otherwise invisible processes. Advanced cell assays closely mimicking in vivo scenery are establishing themselves as novel ways to visualize and measure the bidirectional tumor-host interplay influencing the progression of cancer. Here we describe two versatile protocols to recreate highly controllable 2D and 3D co-cultures in microdevices, mimicking the complexity of the tumor microenvironment (TME), under natural and therapy-induced immunosurveillance. In section 1, an experimental setting is provided to monitor crosstalk between adherent tumor cells and floating immune populations, by bright field time-lapse microscopy. As an applicative scenario, we analyze the effects of anti-cancer treatments, such as the so-called immunogenic cancer cell death inducers on the recruitment and activation of immune cells. In section 2, 3D tumor-immune microenvironments are assembled in a competitive layout. Differential immune infiltration is monitored by fluorescence snapshots up to 72 h, to evaluate combination therapeutic strategies. In both settings, image processing steps are illustrated to extract a plethora of immune cell parameters (e.g., immune cell migration and interaction, response to therapeutic agents). These simple and powerful methods can be further tailored to simulate the complexity of the TME encompassing the heterogeneity and plasticity of cancer, stromal and immune cells subtypes, as well as their reciprocal interactions as drivers of cancer evolution. The compliance of these rapidly evolving technologies with live-cell high-content imaging can lead to the generation of large informative datasets, bringing forth new challenges. Indeed, the triangle &#39;&#39;co-cultures/microscopy/advanced data analysis&#34; sets the path towards a precise problem parametrization that may assist tailor-made therapeutic protocols. We expect that future integration of cancer-immune on-a-chip with artificial intelligence for high-throughput processing will synergize a large step forward in leveraging the capabilities as predictive and preclinical tools for precision and personalized oncology.

In the age of immunotherapy and single-cell genomic profiling, cancer biology requires novel in vitro and computational tools for investigating the tumor-immune interface in a proper spatiotemporal context. We describe protocols to exploit tumor-immune microfluidic co-cultures in 2D and 3D settings, compatible with dynamic, multiparametric monitoring of cellular functions.

Complex disease models demand cutting-edge tools able to deliver physiologically and pathologically relevant, actionable insights, and unveil otherwise ...

Using Coculture to Detect Chemically Mediated Interspecies Interactions

In nature, bacteria rarely exist in isolation; they are instead surrounded by a diverse array of other microorganisms that alter the local environment by secreting metabolites. These metabolites have the potential to modulate the physiology and differentiation of their microbial neighbors and are likely important factors in the establishment and maintenance of complex microbial communities. We have developed a fluorescence-based coculture screen to identify such chemically mediated microbial interactions. The screen involves combining a fluorescent transcriptional reporter strain with environmental microbes on solid media and allowing the colonies to grow in coculture. The fluorescent transcriptional reporter is designed so that the chosen bacterial strain fluoresces when it is expressing a particular phenotype of interest (i.e. biofilm formation, sporulation, virulence factor production, etc.) Screening is performed under growth conditions where this phenotype is not expressed (and therefore the reporter strain is typically nonfluorescent). When an environmental microbe secretes a metabolite that activates this phenotype, it diffuses through the agar and activates the fluorescent reporter construct. This allows the inducing-metabolite-producing microbe to be detected: they are the nonfluorescent colonies most proximal to the fluorescent colonies. Thus, this screen allows the identification of environmental microbes that produce diffusible metabolites that activate a particular physiological response in a reporter strain. This publication discusses how to: a) select appropriate coculture screening conditions, b) prepare the reporter and environmental microbes for screening, c) perform the coculture screen, d) isolate putative inducing organisms, and e) confirm their activity in a secondary screen. We developed this method to screen for soil organisms that activate biofilm matrix-production in Bacillus subtilis; however, we also discuss considerations for applying this approach to other genetically tractable bacteria.

Bacteria produce secreted compounds that have the potential to affect the physiology of their microbial neighbors. Here we describe a coculture screen that allows detection of such chemically mediated interspecies interactions by mixing soil microbes with fluorescent transcriptional reporter strains of Bacillus subtilis on solid media.

In nature, bacteria rarely exist in isolation; they are instead surrounded by a diverse array of other microorganisms that alter the local environment by ...

Biology

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Cellular processes are complex and result from the interplay between multiple cell types and their environment. Existing cell biology techniques often do not allow for accurate interpretation of this interplay. Using a quantitative imaging-based approach, we present a high-content protocol for characterizing the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations to changes in environmental stimuli. We highlight our ability to distinguish between cell types based upon either fluorescence intensity or inherent morphology features depending on the application. This platform allows for a more comprehensive characterization of subpopulation response to perturbation while utilizing shorter time, smaller amounts of reagents, and lower likelihood of error than traditional cell biology assays. However, in some cases, cell populations may be difficult to identify and quantitate based on complex cellular features and will require additional troubleshooting; we highlight some of these circumstances in the protocol. We demonstrate this application using response to drug in a cancer model; however, it can easily be applied more broadly to other physiological processes. This protocol allows one to identify subpopulations within a co-culture system and characterize the particular response of each to external stimuli.

We have developed a novel protocol for studying heterocellular population dynamics in response to perturbations. This manuscript describes an imaging-based platform that produces quantitative datasets for simultaneous characterization of multiple cellular phenotypes of heterocellular populations in a robust manner.

Cellular processes are complex and result from the interplay between multiple cell types and their environment. Existing cell biology techniques often do ...

3D-Printed Scaffold Model to Investigate Embryo Implantation Mechanisms

Co-culture Model Using Two Types of Adherent Cell Lines

Embryo implantation is affected by the interactions among different cell types in the mother-embryo interface. The direct and indirect communications between various cell types within the decidua are crucial for regulating endometrial receptivity; however, the molecular mechanisms mediating this interaction are still unclear. In this regard, a model to study the implantation process is needed to establish a comprehensive in vitro model that can recapitulate the biology of endometrial epithelium-stroma interaction. This model is composed of regular cell-culture plates and a matching scaffold, which is generated by three-dimensional (3D) printing from low-cost materials. Here, we detail a set of protocols for model construction, cell preparation, cell seeding, cell culture, observation, and evaluation. Furthermore, we have included representative results with cells exhibiting good growth conditions under the microscope. This study aimed to develop in vitro models that would mimic the interaction between endometrial stromal cells and epithelial cells, as well as between trophoblast cells and endometrial cells.

Author Spotlight: In Vitro Endometrial Models to Study Epithelial-Stroma and Embryo Interactions

The protocol shows a novel in vitro experimental model that can recapitulate the biology of two kinds of adherent cell lines with a three-dimensional (3D)-printed scaffold. The construction of this model and operating procedures, from cell preparation and cell culture to analysis and evaluation, are described.

Embryo implantation is affected by the interactions among different cell types in the mother-embryo interface. The direct and indirect communications ...