Method Article

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

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DOI:

10.3791/51302

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June 10th, 2014

 ,  ,  , 
1Department of Physics, University of Massachusetts Boston

* These authors contributed equally

In This Article

Summary

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

Abstract

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*(ω). 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.

Introduction

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 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*(ω) 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 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 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 (see http://www.physics.emory.edu/~weeks/idl/).

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Protocol

1. Culturing Tumor Spheroids

  1. Mix 10 ml of cell culture grade water with 0.1 g of agarose to obtain a 1% agarose solution.
  2. Heat agarose solution to above 70 °C (roughly 14 sec in a standard microwave or by using a heating plate) before aliquoting 40 μl of agarose solution into a well on a 96-well plate.
  3. Incubate plate at 37 °C for at least 1 hr while harvesting cells using standard techniques.
  4. Use a hemacytometer to determine the concentration of cells in the suspension.
  5. Dilute cell suspension to 1,000 cells/ml and add 100 µl of this dilution to the well containing the cured agarose bed.
  6. Place the sample on a shaker overnight in an incubator set at 37 °C and 5% CO2.
  7. Remove sample from shaker and add 100 µl of cell culture media.
  8. Incubate spheroids until desired diameter is reached. For example, after 9 days, a spheroid will be approximately 450 µm 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.

2. Preparing 3D Tumor Spheroids Embedded in ECM

  1. Prepare a work station with needed materials inside a laminar flow hood.
  2. Prepare a diluted mixture of carboxylate-modified 1 μm diameter fluorescent tracer probes by adding 2 parts stock probes (2% solids) to 25 parts sterile water.
  3. Remove a bottle of 3.1 mg/ml bovine collagen from the refrigerator and place it on ice.
  4. Aliquot 125 μl of collagen into an empty 2 ml vial.
  5. Add 50 μl of diluted tracer probe solution to the vial containing the collagen and vortex briefly to distribute probes.
  6. Add 235 μl of appropriate cell culture media containing phenol red (which will turn yellow) for a total volume of 410 ml and vortex briefly before removing 205 ml (half the total volume) and placing it in a new 2 ml vial. Vial 1 will contain the tumor spheroid and Vial 2 will be a control mixture.
  7. Add ~2 μl 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.
  8. Using a wide-mouth pipette tip, gently remove 40 μl of media from the well containing the tumor spheroid. Retain this 40 μl while conducting the next step.
  9. Check the well to see if the spheroid was removed in the previous step. If it was, add the 40 μl containing the spheroid to Vial 1. If not, place the 40 μl back into the well and repeat the previous step.
  10. Gently stir Vial 1 (do not risk vortexing, it may damage the spheroid) before transferring the mixture in 60 μl 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.
  11. Add ~2 μl 1 M NaOH and 40 μl of cell culture media to Vial 2 and vortex before aliquotting 60 μl of this mixture to an empty well in the 96-well plate and labeling as a control.
  12. Place the plate in a 37 °C incubator to cure for at least 1 hr.

3. Construct Grid of Sample Points and Take a Video at Each Point

  1. Transfer the sample plate from the incubator to the microscope stage. Allow 10 min for the sample to equilibrate with the room temperature if a heated stage is not available.
  2. 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.
  3. 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.
  4. 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).
  5. 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.
  6. 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.
  7. 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.
  8. Obtain a video sequence at a frame rate of 20-30 msec per frame (approximately 800 frames or 16-24 sec 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.
  9. Repeat steps 3.6 to 3.9 for each sample point in the grid.
  10. Repeat steps 3.3 to 3.10 for each well in the experiment.

4. Analyze Video Data to Compute Rheological Properties at Each Sample Point

  1. Copy all video data to an analysis folder (possibly on a different computer).
  2. 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 http://people.umass.edu/kilfoil. The use of a custom calling function for automating processing of multiple files at different positions is recommended.
  3. 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.
  4. Use the software to automatically determine each probe position for all video frames and then link these positions into trajectories.
  5. 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 (μm per pixel) for the specific objective lens, any pixel binning, etc (typically carried in meta-data).
  6. 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.
  7. Repeat steps 4.2 through 4.6 for each fov in the experiment.
  8. 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.
  9. Use 3D interpolation functions to generate a spatial rheology map of the ECM.

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Results

To verify the validity of G*(ω) 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 the sam...

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Discussion

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...

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Disclosures

The authors declare that they have no competing financial interests.

Acknowledgements

We gratefully acknowledge the open-source sharing of MATLAB particle-tracking code provided by Maria Kilfoil (http://people.umass.edu/kilfoil/), 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).

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
Bovine type 1 collagenBD Biosciences, San Jose, CA354231
PANC-1American Type Cell Culture, Manassas, VACRL1469or other appropriate cell type
Fluorescent MicrospheresLife Technologies, Carlsbad, CA906906
MatrigelBD Biosciences, Bedford, MA354230
AgaroseFisher Bioreagents, Waltham, MAC12H18O9
NaOHFisher Bioreagents, Waltham, MANC0480985
96-well Imaging platesCorning Inc., Corning, NY3904
DMEMHyclone, Waltham, MASH30243.01or appropriate cell culture media
Zeiss AxioObsever MicroscopeZeiss, Oberkochen, Germanyincludes high-speed camera and imaging software
MATLAB softwareThe Mathworks, Natick, MA

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3D Tumor ModelsPancreatic CancerCollagen ScaffoldFluorescent Tracer ProbesGeneralized Stokes Einstein RelationViscoelastic Shear ModulusLongitudinal MonitoringMechanical Microenvironment

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