We gratefully acknowledge the open-source sharing of MATLAB particle-tracking code provided by Maria Kilfoil (<a href="http://people.umass.edu/kilfoil/">http://people.umass.edu/kilfoil/</a>), along with the earlier IDL code and extensive documentation provided by John C. Crocker and Eric R. Weeks. This work was made possible by funding from the National Cancer Institute (NCI/NIH), K99CA155045 and R00CA155045 (PI: JPC).

1. Culturing Tumor Spheroids
<ol>
	<li>Mix 10 ml of cell culture grade water with 0.1 g of agarose to obtain a 1% agarose solution.</li>
	<li>Heat agarose solution to above 70 &#176;C (roughly 14 sec&#160;in a standard microwave or by using a heating plate) before aliquoting 40 &#956;l&#160;of agarose solution into a well on a 96-well plate.</li>
	<li>Incubate plate at 37 &#176;C for at least 1 hr while harvesting cells using standard techniques.</li>
	<li>Use a hemacytometer to determine the concentration of cells in the suspension.</li>
	<li>Dilute cell suspension to 1,000 cells/ml&#160;and add 100 &#181;l&#160;of this dilution to the well containing the cured agarose bed.</li>
	<li>Place the sample on a shaker overnight in an incubator set at 37 &#176;C&#160;and 5% CO2.</li>
	<li>Remove sample from shaker and add 100 &#181;l&#160;of cell culture media.</li>
	<li>Incubate spheroids until desired diameter is reached. For example, after 9 days, a spheroid will be approximately 450 &#181;m in diameter. During this time, fresh growth media can be added to the wells but aspiration should be avoided since this will result in removal of the spheroid.</li>
</ol>
2. Preparing 3D Tumor Spheroids Embedded in ECM
<ol>
	<li>Prepare a work station with needed materials inside a laminar flow hood.</li>
	<li>Prepare a diluted mixture of carboxylate-modified 1 &#956;m diameter fluorescent tracer probes by adding 2 parts stock probes (2% solids) to 25 parts sterile water.</li>
	<li>Remove a bottle of 3.1 mg/ml&#160;bovine collagen from the refrigerator and place it on ice.</li>
	<li>Aliquot 125 &#956;l&#160;of collagen into an empty 2 ml&#160;vial.</li>
	<li>Add 50 &#956;l&#160;of diluted tracer probe solution to the vial containing the collagen and vortex briefly to distribute probes.</li>
	<li>Add 235 &#956;l&#160;of appropriate cell culture media containing phenol red (which will turn yellow) for a total volume of 410 ml&#160;and vortex briefly before removing 205 ml&#160;(half the total volume) and placing it in a new 2 ml&#160;vial. Vial 1 will contain the tumor spheroid and Vial 2 will be a control mixture.</li>
	<li>Add ~2 &#956;l&#160;of 1 M NaOH to Vial 1 to bring the solution back to neutral pH (culture media containing phenol red should return to red). Note that this will cause the mixture to begin curing if it is not kept on ice. Vortex briefly to mix, then return to ice rack immediately. 
	NOTE: The spheroid is barely visible to the naked eye after 9 days of culture and its removal from the agarose bed is a delicate task. Use of a dissection microscope may be helpful for some users. Maintaining the integrity of the spheroid during transfer is paramount.</li>
	<li>Using a wide-mouth pipette tip, gently remove 40 &#956;l&#160;of media from the well containing the tumor spheroid. Retain this 40 &#956;l&#160;while conducting the next step.</li>
	<li>Check the well to see if the spheroid was removed in the previous step. If it was, add the 40 &#956;l&#160;containing the spheroid to Vial 1. If not, place the 40 &#956;l&#160;back into the well and repeat the previous step.</li>
	<li>Gently stir Vial 1 (do not risk vortexing, it may damage the spheroid) before transferring the mixture in 60 &#956;l&#160;portions into three separate wells of a 96-well plate. Inspect each well with a microscope after adding mixture to determine which well contains the spheroid.</li>
	<li>Add ~2 &#956;l&#160;1 M NaOH and 40 &#956;l&#160;of cell culture media to Vial 2 and vortex before aliquotting 60 &#956;l&#160;of this mixture to an empty well in the 96-well plate and labeling as a control.</li>
	<li>Place the plate in a 37 &#176;C incubator to cure for at least 1 hr.</li>
</ol>
3. Construct Grid of Sample Points and Take a Video at Each Point
<ol>
	<li>Transfer the sample plate from the incubator to the microscope stage. Allow 10 min&#160;for the sample to equilibrate with the room temperature if a heated stage is not available.</li>
	<li>Observe the sample with low powered objective lenses to make sure it is intact and ready for imaging. Determine the tumor position within the well.</li>
	<li>Decide how many sample points to take. Typically, 20 sample points in each well, distributed in concentric rings around the spheroid will produce adequately detailed results.</li>
	<li>Move the stage to each desired position and use microscope interfacing software to record the x and y coordinates (or record coordinates manually if interfacing software is unavailable).</li>
	<li>Switch the microscope to a high powered objective lens (typically 100X), and select the appropriate filter cube for the excitation wavelength of the tracer probes. Use the list of points created in step 3.4 to move to the first point in the grid.</li>
	<li>Adjust the focus to find the bottom of the well, then move up to find a field of view (fov) containing several in-focus tracer probes.</li>
	<li>Observe the intensity histogram and adjust the exposure intensity and time to give the greatest dynamic range possible while ensuring that the image does not become saturated.</li>
	<li>Obtain a video sequence at a frame rate of 20-30 msec per frame (approximately 800 frames or 16-24 sec&#160;in length is recommended to provide sufficient statistics for robust MSD calculation balanced with the need for minimizing acquisition time at each spatial grid point) and save with an appropriate convention. During the recording, do not touch the microscope or table.</li>
	<li>Repeat steps 3.6 to 3.9 for each sample point in the grid.</li>
	<li>Repeat steps 3.3 to 3.10 for each well in the experiment.</li>
</ol>
4. Analyze Video Data to Compute Rheological Properties at Each Sample Point
<ol>
	<li>Copy all video data to an analysis folder (possibly on a different computer).</li>
	<li>Import image data into MATLAB or other analysis software. 
	NOTE: Extensive documentation regarding the set of MATLAB particle tracking routines adopted here is available at <a href="http://people.umass.edu/kilfoil/">http://people.umass.edu/kilfoil</a>. The use of a custom calling function for automating processing of multiple files at different positions is recommended.</li>
	<li>Calibrate the software by analyzing several frames of the video to appropriately determine selection and rejection parameters (size, bandpass, etc) for identifying probe center positions. Extensive background for these crucial steps is described by Crocker and Grier.</li>
	<li>Use the software to automatically determine each probe position for all video frames and then link these positions into trajectories.</li>
	<li>Use the trajectory data to compute the mean squared displacement (MSD) as a function of lag time, being sure to apply the appropriate spatial calibration factor (&#956;m per pixel) for the specific objective lens, any pixel binning, etc (typically carried in meta-data).</li>
	<li>Calculate G*(using the generalized Stokes-Einstein relation taken into consideration the limits of applicability of GSER for a particular sample24,28,43. Alternatively, users may wish to interpret ECM properties directly from MSD by simply comparing power law scaling, plateau values, indices of heterogeneity or other parameters.</li>
	<li>Repeat steps 4.2 through 4.6 for each fov in the experiment.</li>
	<li>Co-register position data from step 3.4 with viscoelastic modulii at a particular frequency of interest. Depending on the manufacturer of the microscope used, this step can be facilitated by a custom routine which reads microscope metadata or position data can be tabulated manually.</li>
	<li>Use 3D interpolation functions to generate a spatial rheology map of the ECM.</li>
</ol>

The authors declare that they have no competing financial interests.

In this protocol we introduce a robust and widely applicable strategy for longitudinally tracking local changes in ECM rigidity in 3D tumor models. We envision that this methodology could be adopted by cancer biologists and biophysicists interested in mechanosensitive behavior implicated in matrix remodeling during tumor growth and invasion processes. Precise quantification of matrix degradation kinetics could be particularly valuable to those studying the activity of matrix metalloproteases, lysyl oxidase or other relev...

It is clear from a growing body of evidence in the literature that cancer cells, as with non-malignant mammalian epithelial cells, are highly sensitive to the mechanical&#160;and biophysical properties of the surrounding extracellular matrix (ECM) and other microenvironment components1-9. Elegant mechanistic studies have provided insights into the role of extracellular rigidity as a complex mechanosensitive signaling partner that regulates malignant growth behavior and morphogenesis2,3,10,11. This work has been facilitated in particular by the development of 3D in vitro tumor models that restore biologically relevant tissue architecture and can be grown in scaffold materials with tunable mechanics and imaged by optical microscopy12-19. However, the other side of this mechanoregulatory dialog between tumor and microenvironment, through which cancer cells in turn modify the rheology of their surroundings, remains somewhat more difficult to study. For example, during invasion processes, cells at the periphery of a tumor may undergo epithelial to mesenchymal transition (EMT) and increase expression of matrix metalloproteases (MMPs) that cause local degradation of ECM20-22, which in turn influences mechanosensitive growth behavior of other proximal tumor cells. Through a variety of biochemical processes, cancer cells continually dial the local rigidity of their environment up and down to suit different processes at different times. The methodology described here is motivated by the need for analytical tools that report local changes in the rigidity and compliance of the ECM during growth, that can be integrated with 3D tumor models and correlated longitudinally with biochemical and phenotypic changes without terminating the culture.
In search of an appropriate technique to implement in this context, particle-tracking microrheology (PTM) emerges as a strong candidate. This method, pioneered originally by Mason and Weitz23,24, uses the motion of tracer probes embedded in a complex fluid to report the frequency-dependent complex viscoelastic shear modulus, G*(&#969;) at micron length scales. This general approach has been developed with multiple variations suited for different applications in soft-condensed matter, colloids, biophysics and polymer physics25-31. PTM has certain advantages relative to other methods, since readouts of local viscoelasticity are provided by non-destructive video imaging of biochemically inactive tracer probes that are incorporated at the time of culture preparation and remain in place over extended periods of growth. This is in contrast to gold standard measurements with an oscillatory shear bulk rheometer, which necessarily requires termination of the culture and reports the bulk macroscopic rheology of the sample rather than point measurements within the complex 3D tumor microenvironment. Indeed a number of studies have illustrated the utility of interpreting measurements of tracer probe movements in or around cancer or non-cancer cells to measure deformations associated with cell migration32, mechanical stress induced by an expanding spheroid33, intracellular rheology34,35, and to map mechanical stresses and strains in engineered tissues36, and relation between pore size and invasion speed37. Other techniques suitable for microrheology, such as atomic force microscopy (AFM) can be implemented, but primarily for probing points at the sample surface and also may pose culture sterility issues that complicate longitudinal measurements38.
Here, we describe a comprehensive protocol encompassing methods for growth of 3D tumor spheroids suitable for transfer into ECM with embedded fluorescent probes for video particle-tracking and analysis methods for reliably mapping spatial changes in microrheology over time in culture. In the present implementation, 3D tumor models are grown in multiwell format with a view towards incorporation of microrheology measurements with other traditional assays (e.g., cytotoxicity) which this format is conducive to. In this representative illustration of this methodology we culture in vitro 3D spheroids using PANC-1 cells, an established pancreatic cancer cell line known to form spheroids39, but all measurements described herein are broadly applicable to study of solid tumors using a variety of cell lines suitable for 3D culture. Because this method is inherently imaging-based it is ideally suited for co-registration of high-resolution microrheology data with large transmitted-light fields of view that report changes in cell growth, migration and phenotype. The implementation of PTM integrated with transmitted light microscopy in this manner assumes reproducible positioning of the microscope stage which is typically available on motorized commercial widefield epifluorescence biological microscopes. The protocol developed below can be implemented with any reasonably equipped automated fluorescence biological microscope. This is an inherently data-intensive method, which requires acquisition of gigabytes of digital video microscopy data for offline processing.
In the following protocol, Protocol&#160;1 pertains to the initial preparation of tumor spheroids which is described here using overlay on agarose but could be substituted with a variety of other methods such as hanging drop40, or rotary culture41 techniques. Protocol&#160;2 describes the process of embedding spheroids in a collagen scaffold though alternatively, in vitro 3D tumors could be grown by encapsulation or embedding of resuspended cells in ECM12,15, rather than single pre-formed non-adherent spheroids. Subsequent protocols describe procedures for obtaining time-resolved microrheology measurements by acquiring and processing video microscopy data, respectively. Data processing is described using MATLAB, making use of open source routines for PTM built on algorithms originally described by Crocker and Grier42, which have also been extensively developed for different software platforms&#160;(see&#160;http://www.physics.emory.edu/~weeks/idl/).

<table border="0" cellpadding="0" cellspacing="0" width="779">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:177px;">Bovine type 1 collagen</td>
			<td style="width:235px;">BD Biosciences, San Jose, California</td>
			<td style="width:100px;">354231</td>
			<td style="width:268px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">PANC-1</td>
			<td>American Type Cell Culture, Manassas, VA</td>
			<td>CRL1469</td>
			<td>or other appropriate cell type</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Fluorescent Microspheres</td>
			<td>Life Technologies, Carlsbad, California</td>
			<td>906906</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Matrigel</td>
			<td>BD Biosciences, Bedford MA</td>
			<td>354230</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Agarose</td>
			<td>Fisher Bioreagents, Waltham, MA</td>
			<td>C12H18O9</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">NaOH</td>
			<td>Fisher Bioreagents, Waltham, MA</td>
			<td>NC0480985</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">96-well Imaging plates</td>
			<td>Corning Inc., Corning, NY</td>
			<td>3904</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DMEM</td>
			<td>Hyclone, Waltham, MA</td>
			<td>SH30243.01</td>
			<td>or appropriate&#160; cell culture media</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:23px;">Zeiss AxioObsever Microscope</td>
			<td>Zeiss, Oberkochen, Germany</td>
			<td></td>
			<td>includes high-speed camera and imaging software</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MATLAB software</td>
			<td>The Mathworks, Natick, MA</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

longitudinal measurement of extracellular matrix rigidity in 3d tumor models using particle-tracking microrheology

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(&#969;). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.

To verify the validity of G*(&#969;) measurements at localized positions within a complex model tumor microenvironment, two initial validation experiments were conducted. First, we sought to validate our measurements against the "gold standard" of bulk oscillatory shear rheometry. We prepared identical samples of collagen matrix (without cells) at a concentration of 1.0 mg/ml collagen. These samples were probed with a bulk rheometer (TA Instruments AR-G2, using 40 mm parallel plate geometry) and by PTM (using th...

Watch this Scientific Journal Video about Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology at JoVE.com

Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology

Particle-tracking microrheology can be used to non-destructively quantify and spatially map changes in extracellular matrix mechanical properties in 3D tumor models.

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and ...

longitudinal-measurement-extracellular-matrix-rigidity-3d-tumor

Research

JoVE Journal

Bioengineering

11.4K Views.  University of Massachusetts Boston. Particle-tracking microrheology can be used to non-destructively quantify and spatially map changes in extracellular matrix mechanical properties in 3D tumor models.

Video: Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology

Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy

Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, currently available routine methods require processing steps and alter sample integrity. Raman spectroscopy is a fast method that enables the measurement of biological samples without the need for further processing steps. This laser-based technology detects the inelastic scattering of monochromatic light.6 As every chemical vibration is assigned to a specific Raman band (wavenumber in cm-1), each biological sample features a typical spectral pattern due to their inherent biochemical composition.7-9 Within Raman spectra, the peak intensities correlate with the amount of the present molecular bonds.1 Similarities and differences of the spectral data sets can be detected by employing a multivariate analysis (e.g. principal component analysis (PCA)).10
Here, we perform Raman spectroscopy of living cells and native tissues. Cells are either seeded on glass bottom dishes or kept in suspension under normal cell culture conditions (37 &deg;C, 5% CO2) before measurement. Native tissues are dissected and stored in phosphate buffered saline (PBS) at 4 &deg;C prior measurements. Depending on our experimental set up, we then either focused on the cell nucleus or extracellular matrix (ECM) proteins such as elastin and collagen. For all studies, a minimum of 30 cells or 30 random points of interest within the ECM are measured. Data processing steps included background subtraction and normalization.

Raman spectroscopy is a suitable technique for the non-contact, label-free analysis of living cells, tissue-engineered constructs and native tissues. Source-specific spectral fingerprints can be generated and analyzed using multivariate analysis.

Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, ...

Flexural Rigidity Measurements of Biopolymers Using Gliding Assays

Microtubules are cytoskeletal polymers which play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires microtubules that are stiff and straight enough to span a significant fraction of the cell diameter. As a result, the microtubule persistence length, a measure of stiffness, has been actively studied for the past two decades1. Nonetheless, open questions remain: short microtubules are 10-50 times less stiff than long microtubules2-4, and even long microtubules have measured persistence lengths which vary by an order of magnitude5-9.
	Here, we present a method to measure microtubule persistence length. The method is based on a kinesin-driven microtubule gliding assay10. By combining sparse fluorescent labeling of individual microtubules with single particle tracking of individual fluorophores attached to the microtubule, the gliding trajectories of single microtubules are tracked with nanometer-level precision. The persistence length of the trajectories is the same as the persistence length of the microtubule under the conditions used11. An automated tracking routine is used to create microtubule trajectories from fluorophores attached to individual microtubules, and the persistence length of this trajectory is calculated using routines written in IDL.
	This technique is rapidly implementable, and capable of measuring the persistence length of 100 microtubules in one day of experimentation. The method can be extended to measure persistence length under a variety of conditions, including persistence length as a function of length along microtubules. Moreover, the analysis routines used can be extended to myosin-based acting gliding assays, to measure the persistence length of actin filaments as well.

A method to measure the persistence length or flexural rigidity of biopolymers is described. The method uses a kinesin-driven microtubule gliding assay to experimentally determine the persistence length of individual microtubules and is adaptable to actin-based gliding assays.

Microtubules are cytoskeletal polymers which  play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires ...

In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology

Bacterial cells are able to form surface-attached biofilm communities known as biofilms by encasing themselves in extracellular polymeric substances (EPS). The EPS serves as a physical and protective scaffold that houses the bacterial cells and consists of a variety of materials that includes proteins, exopolysaccharides and DNA. The composition of the EPS may change, which remodels the mechanic properties of the biofilm to further develop or support alternative biofilm structures, such as streamers, as a response to environmental cues. Despite this, there are little quantitative descriptions on how EPS components contribute to the mechanical properties and function of biofilms. Rheology, the study of the flow of matter, is of particular relevance to biofilms as many biofilms grow in flow conditions and are constantly exposed to shear stress. It also provides measurement and insight on the spreading of the biofilm on a surface. Here, particle-tracking microrheology is used to examine the viscoelasticity and effective crosslinking roles of different matrix components in various parts of the biofilm during development. This approach allows researchers to measure mechanic properties of biofilms at the micro-scale, which might provide useful information for controlling and engineering biofilms.

In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology

Particle-tracking microrheology investigates the viscoelasticity of materials. Here, the technique is used to determine the viscoelasticity, creep compliance and effective crosslinking roles of different matrix components of a bacterial biofilm. The matrix consists of polymeric substances secreted by the bacteria and its components determine biofilm structure and mechanical properties.

Bacterial cells are able to form surface-attached biofilm communities known as biofilms by encasing themselves in extracellular polymeric substances ...

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

The glycoprotein family of collagens represents the main structural proteins in the human body, and are key components of biomaterials used in modern tissue engineering. A technical bottleneck is the deposition of collagen in vitro, as it is notoriously slow, resulting in sub-optimal formation of connective tissue and subsequent tissue cohesion, particularly in skin models. Here, we describe a method which involves the addition of differentially-sized sucrose co-polymers to skin cultures to generate macromolecular crowding (MMC), which results in a dramatic enhancement of collagen deposition. Particularly, dermal fibroblasts deposited a significant amount of collagen I/IV/VII and fibronectin under MMC in comparison to controls.
The protocol also describes a method to decellularize crowded cell layers, exposing significant amounts of extracellular matrix (ECM) which were retained on the culture surface as evidenced by immunocytochemistry. Total matrix mass and distribution pattern was studied using interference reflection microscopy. Interestingly, fibroblasts, keratinocytes and co-cultures produced cell-derived matrices (CDM) of varying composition and morphology. CDM could be used as &#34;bio-scaffolds&#34; for secondary cell seeding, where the current use of coatings or scaffolds, typically from xenogenic animal sources, can be avoided, thus moving towards more clinically relevant applications.
In addition, this protocol describes the application of MMC during the submerged phase of a 3D-organotypic skin co-culture model which was sufficient to enhance ECM deposition in the dermo-epidermal junction (DEJ), in particular, collagen VII, the major component of anchoring fibrils. Electron microscopy confirmed the presence of anchoring fibrils in cultures developed with MMC, as compared to controls. This is significant as anchoring fibrils tether the dermis to the epidermis, hence, having a pre-formed mature DEJ may benefit skin graft recipients in terms of graft stability and overall wound healing. Furthermore, culture time was condensed from 5 weeks to 3 weeks to obtain a mature construct, when using MMC, reducing costs.

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

We present a protocol to obtain cell-derived matrices rich in extracellular matrix proteins, using macromolecular crowders (MMC). In addition, we present a protocol which incorporates MMC in 3D organotypic skin co-culture generation, which reduces culture time while maintaining maturity of construct.

The glycoprotein family of collagens represents the main structural proteins in the human body, and are key components of biomaterials used in modern ...

Tunable Hydrogels from Pulmonary Extracellular Matrix for 3D Cell Culture

Here we present a method for establishing multiple component cell culture hydrogels for in vitro lung cell culture. Beginning with healthy en bloc lung tissue from porcine, rat, or mouse, the tissue is perfused and submerged in subsequent chemical detergents to remove the cellular debris. Histological comparison of the tissue before and after processing confirms removal of over 95% of double stranded DNA and alpha galactosidase staining suggests the majority of cellular debris is removed. After decellularization, the tissue is lyophilized and then cryomilled into a powder. The matrix powder is digested for 48 hr in an acidic pepsin digestion solution and then neutralized to form the pregel solution. Gelation of the pregel solution can be induced by incubation at 37 &#176;C and can be used immediately following neutralization or stored at 4 &#176;C for up to two weeks. Coatings can be formed using the pregel solution on a non-treated plate for cell attachment. Cells can be suspended in the pregel prior to self-assembly to achieve a 3D culture, plated on the surface of a formed gel from which the cells can migrate through the scaffold, or plated on the coatings. Alterations to the strategy presented can impact gelation temperature, strength, or protein fragment sizes. Beyond hydrogel formation, the hydrogel stiffness may be increased using genipin.

This is a method to create a 3-dimensional cell culture scaffold from pulmonary extracellular matrix. Intact lung is processed into hydrogels that can support the growth of cells in three-dimensions.

Here we present a method for establishing multiple component cell culture hydrogels for in vitro lung cell culture. Beginning with healthy en bloc lung ...

A Protocol for Real-time 3D Single Particle Tracking

Real-time three-dimensional single particle tracking (RT-3D-SPT) has the potential to shed light on fast, 3D processes in cellular systems. Although various RT-3D-SPT methods have been put forward in recent years, tracking high speed 3D diffusing particles at low photon count rates remains a challenge. Moreover, RT-3D-SPT setups are generally complex and difficult to implement, limiting their widespread application to biological problems. This protocol presents a RT-3D-SPT system named 3D Dynamic Photon Localization Tracking (3D-DyPLoT), which can track particles with high diffusive speed (up to 20 &#181;m2/s) at low photon count rates (down to 10 kHz). 3D-DyPLoT employs a 2D electro-optic deflector (2D-EOD) and a tunable acoustic gradient (TAG) lens to drive a single focused laser spot dynamically in 3D. Combined with an optimized position estimation algorithm, 3D-DyPLoT can lock onto single particles with high tracking speed and high localization precision. Owing to the single excitation and single detection path layout, 3D-DyPLoT is robust and easy to set up. This protocol discusses how to build 3D-DyPLoT step by step. First, the optical layout is described. Next, the system is calibrated and optimized by raster scanning a 190 nm fluorescent bead with the piezoelectric nanopositioner. Finally, to demonstrate real-time 3D tracking ability, 110 nm fluorescent beads are tracked in water.

This protocol details the construction and operation of a real-time 3D single particle tracking microscope capable of tracking nanoscale fluorescent probes at high diffusive speeds and low photon count rates.

Real-time three-dimensional single particle tracking (RT-3D-SPT) has the potential to shed light on fast, 3D processes in cellular systems. Although ...

Fabricating a Kidney Cortex Extracellular Matrix-Derived Hydrogel

Extracellular matrix (ECM) provides important biophysical and biochemical cues to maintain tissue homeostasis. Current synthetic hydrogels offer robust mechanical support for in vitro cell culture but lack the necessary protein and ligand composition to elicit physiological behavior from cells. This manuscript describes a fabrication method for a kidney cortex ECM-derived hydrogel with proper mechanical robustness and supportive biochemical composition. The hydrogel is fabricated by mechanically homogenizing and solubilizing decellularized human kidney cortex ECM. The matrix preserves native kidney cortex ECM protein ratios while also enabling gelation to physiological mechanical stiffnesses. The hydrogel serves as a substrate upon which kidney cortex-derived cells can be maintained under physiological conditions. Furthermore, the hydrogel composition can be manipulated to model a diseased environment which enables the future study of kidney diseases.

Here we present a protocol to fabricate a kidney cortex extracellular matrix-derived hydrogel to retain the native kidney extracellular matrix (ECM) structural and biochemical composition. The fabrication process and its applications are described. Finally, a perspective on using this hydrogel to support kidney-specific cellular and tissue regeneration and bioengineering is discussed.

Extracellular matrix (ECM) provides important biophysical and biochemical cues to maintain tissue homeostasis. Current synthetic hydrogels offer robust ...

Pancreatic Tissue-Derived Extracellular Matrix Bioink for Printing 3D Cell-Laden Pancreatic Tissue Constructs

The transplantation of pancreatic islets is a promising treatment for patients who suffer from type 1 diabetes accompanied by hypoglycemia and secondary complications. However, islet transplantation still has several limitations such as the low viability of transplanted islets due to poor islet engraftment and hostile environments. In addition, the insulin-producing cells differentiated from human pluripotent stem cells have limited ability to secrete sufficient hormones that can regulate the blood glucose level; therefore, improving the maturation by culturing cells with proper microenvironmental cues is strongly required. In this article, we elucidate protocols for preparing a pancreatic tissue-derived decellularized extracellular matrix (pdECM) bioink to provide a beneficial microenvironment that can increase glucose sensitivity of pancreatic islets, followed by describing the processes for generating 3D pancreatic tissue constructs using a microextrusion-based bioprinting technique.

Decellularized extracellular matrix (dECM) can provide suitable microenvironmental cues to recapitulate the inherent functions of target tissues in an engineered construct. This article elucidates the protocols for the decellularization of pancreatic tissue, evaluation of pancreatic tissue-derived dECM bioink, and generation of 3D pancreatic tissue constructs using a bioprinting technique.

The transplantation of pancreatic islets is a promising treatment for patients who suffer from type 1 diabetes accompanied by hypoglycemia and secondary ...

A Human 3D Extracellular Matrix-Adipocyte Culture Model for Studying Matrix-Cell Metabolic Crosstalk

The extracellular matrix (ECM) plays a central role in regulating tissue homeostasis, engaging in crosstalk with cells and regulating multiple aspects of cellular function. The ECM plays a particularly important role in adipose tissue function in obesity, and alterations in adipose tissue ECM deposition and composition are associated with metabolic disease in mice and humans. Tractable in vitro models that permit dissection of the roles of the ECM and cells in contributing to global tissue phenotype are sparse. We describe a novel 3D in vitro model of human ECM-adipocyte culture that permits study of the specific roles of the ECM and adipocytes in regulating adipose tissue metabolic phenotype. Human adipose tissue is decellularized to isolate ECM, which is subsequently repopulated with preadipocytes that are then differentiated within the ECM into mature adipocytes. This method creates ECM-adipocyte constructs that are metabolically active and retain characteristics of the tissues and patients from which they are derived. We have used this system to demonstrate disease-specific ECM-adipocyte crosstalk in human adipose tissue. This culture model provides a tool for dissecting the roles of the ECM and adipocytes in contributing to global adipose tissue metabolic phenotype and permits study of the role of the ECM in regulating adipose tissue homeostasis.

We describe a 3D human extracellular matrix-adipocyte in vitro culture system that permits dissection of the roles of the matrix and adipocytes in contributing to adipose tissue metabolic phenotype.

The extracellular matrix (ECM) plays a central role in regulating tissue homeostasis, engaging in crosstalk with cells and regulating multiple aspects of ...

Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models

Cell-matrix interactions mediate complex physiological processes through biochemical, mechanical, and geometrical cues, influencing pathological changes and therapeutic responses. Accounting for matrix effects earlier in the drug development pipeline is expected to increase the likelihood of clinical success of novel therapeutics. Biomaterial-based strategies recapitulating specific tissue microenvironments in 3D cell culture exist but integrating these with the 2D culture methods primarily used for drug screening has been challenging. Thus, the protocol presented here details the development of methods for 3D culture within miniaturized biomaterial matrices in a multi-well plate format to facilitate integration with existing drug screening pipelines and conventional assays for cell viability. Since the matrix features critical for preserving clinically relevant phenotypes in cultured cells are expected to be highly tissue- and disease-specific, combinatorial screening of matrix parameters will be necessary to identify appropriate conditions for specific applications. The methods described here use a miniaturized culture format to assess cancer cell responses to orthogonal variation of matrix mechanics and ligand presentation. Specifically, this study demonstrates the use of this platform to investigate the effects of matrix parameters on the responses of patient-derived glioblastoma (GBM) cells to chemotherapy.

The present protocol describes an experimental platform to assess the effects of mechanical and biochemical cues on chemotherapeutic responses of patient-derived glioblastoma cells in 3D matrix-mimetic cultures using a custom-made UV illumination device facilitating high-throughput photocrosslinking of hydrogels with tunable mechanical features.

Cell-matrix interactions mediate complex physiological processes through biochemical, mechanical, and geometrical cues, influencing pathological changes ...