A Method to sort heterogenous cell populations based on migration in 2D and 3D environments

Aditya Arora, Jorge Luis Galeano Niño, Myint Zu Myaing, Bakya Arasi, Ruby Yun-Ju Huang, Ramanuj Dasgupta, Maté Biro, Virgile Viasnoff

Preprint posted on 7 May 2020 https://www.biorxiv.org/content/10.1101/2020.05.06.080234v1

Sorting by movement!

Selected by Mariana De Niz

Categories: biophysics, cell biology

Background

Cell migration plays a pivotal role in all stages of the life of a multicellular organism. Important homeostatic processes requiring cell migration include tissue morphogenesis, wound healing and immune responses. Conversely, aberrant migration of diseased cells, such as that displayed by cancer cells, can result in metastasis. Phenotypic assays, including Boyden chambers and wound healing assays, have been developed to study the migratory potential of cells at the population level. Equally, quantitative high-resolution imaging has allowed the study of the molecular basis of collective cell migration. Approaches to study cell migration in 3D are less popular due to the technical challenges of imaging. Despite their utility, although various of these 2D and 3D assays reveal heterogeneity of migratory behavior within a cell population, the quantitative analysis usually provides only a migration index averaged over the entire cell population, and many of them do not provide easy means to sort and retrieve cells from within the population. Altogether, very few methods exist that can sort subpopulations of cells based on their migratory behaviour from an initial heterogeneous pool. In their work, Arora et al present a new approach to sort migratory cancer and immune cells, based on their spontaneous migration in 2D and 3D microenvironments (1).

Figure 1. 2D and 3D setups for cell sorting based on migration (From Ref. 1)

Key findings and developments

In their work, Arora et al propose readily implementable methods to separate a faster migrating sub-population of cells from a heterogeneous population based on migration in 2D or 3D environments. Initially unsorted groups of cells are locally confined in a series of scattered predefined regions. They are then left to migrate spontaneously away from the original confinement zone to another substrate (for 2D or 3D as described below).

2D sorting device and proof of concept

The 2D migration sorting assay (2D-MSA) relies on a multi-layered PDMS micro-well device, in which arrays of holes are perforated, using a layer cutter. Cells are seeded at 70-80% confluency, and some of these cells will fall into the perforated cavities, and will adhere within a short time. Cells are then allowed to migrate up the cavity walls, to reach the top collection layer initially devoid of any cells. The authors optimized the diameter and height of the cavities, as well as the spacing between cavities, to accurately study cell migration. Ultimately, the collection layer will be enriched with fast migrating cells, while the base layer will be enriched in slow migrating cells. The authors validated the method using a 1:1 mixture of cell lines MCF7 and MD MB 231. Both are breast cancer derived cell lines, however, they have different motility characteristics: while MCF7 maintains an epithelial state and lacks the ability to metastasize, the latter is mesenchymal, with extensive migratory capacity. Both were differentially labeled for recognition. Quantification of both cell lines using image analysis revealed a significant enrichment of MDA MB 231 cells on the top layer of the device, as expected. This demonstrated the 2D-MSA to be useful for separating a heterogeneous cancer cell population into a more homogeneous population based on migration. The authors went on to further test the method with patient samples, and performed downstream analyses on the different sorted cell populations.

3D sorting device and proof of concept

The 3D sorting uses hierarchical hydrogel systems consisting of collagen micro-gels suspended in degradable bulk hydrogel. The surrounding matrix is rapidly cross-linked while mixing to minimize the sedimentation of the collagen beads. The way this method can be used to separate cancer cells in 3D, is that cells are left to migrate for several days from the collagen microbeads into the cleavable matrix. The cleavable matrix can then be selectively digested to release all the migrated cells, and a strainer can be used to separate the collagen beads from the less mobile cells. Each fraction can then be cultured separately. As for the 2D device testing, the authors used a 1:1 mixture of cell lines MCF7 and MD MB 231 as proof of concept, and again demonstrated that this method allows separation of both populations. They went on to test their method on cell types for which 2D migration assays are challenging, such as primary leukocytes, in this case, T cells. Using 3D sorting, they achieved a substantial enrichment of fast migrating cytotoxic T lymphocytes. Downstream analyses showed that these faster migrating T cells had significantly higher killing efficiency as compared to slow migrating, and unsorted cells. This further supports the potential of the method, for functional sorting of CTLs in the context of immunotherapeutic applications.

The authors further emphasize the easy implementation of this method, its high throughput, and the fact that it allows downstream genomic, molecular, phenotypic and functional tests.

What I like about this preprint

I like the out-of-the-box approach for solving a methodological problem that has existed for a long time. It’s ingenious, uses the cell’s own biophysical properties, and allows downstream analyses in the sorted cells. It overcomes many of the limitations of other existing assays, and is in many cases complementary. I like the proofs of concept, and the fact that the authors included a very detailed materials and methods section which allows reproducibility of the devices.

References

Arora A., et al A method to sort heterogeneous cells populations based on migration in 2D and 3D environments, bioRxiv, 2020.

Posted on: 2 July 2020

doi: https://doi.org/10.1242/prelights.22587

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Author's response

Aditya Arora and Virgile Viasnoff shared

Open questions

1.What are possible limitations you envisage in the use of either the 2D or 3D setups?

Since the overall goal of our work was to develop a method to be able to sort a larger heterogenous populations into more homogenous subpopulations in terms of their migratory capability, our focus has been on scalability and ease of execution, therefore there is some compromise on the resolution, thus unlike some microfluidics based methods we cannot resolve migratory differences at single cell level but more at a larger population level in both 2D and 3D setups. Also we feel in the 3D setup there is higher chance of a collective migration of chains of cells where a leader cell might create a track for other cells that may not show sufficient migration on their own, especially in cases of a highly heterogenous populations such as one derived from a tumor.

2.For the 3D setup, does digestion of the cleavable matrix affect the biology of the cells for downstream analyses? This is often a concern for other assays.

The matrix that we used in the current study is a hyaluronic acid hydrogel, the enzyme hyaluronidase which specifically degrades hyaluronic acid was used to cleave off the hydrogel. This in principal may cause some degradation of HA in the cellular glycocalyx, however, this should be limited by the short duration of the treatment. More importantly, this is much milder than the regular proteases-based dissociation methods as many of these enzymes have a rather broad specificity range thus causing proteolysis of large number of membrane exposed proteins. Further, if use of enzymatic methods is undesirable for a certain downstream application, the HA gel may be replaced with thermo-reversible or photo-cleavable hydrogels thus completely avoiding any influence on cell surface.

3.You mention in your discussion, the possibility to explore chemokine gradients and growth factors in the context of cell migration. Have you attempted this? Do you envisage any difficulties in the setup to explore chemotaxis?

This would be an interesting and important extension of this work that we would like to explore it future. There are several approaches available to immobilize growth factors and chemokines in hydrogels. We are currently exploring one such approach in the lab to engineer bio-instructive niches for cells by immobilizing growth factors. It should be in principle possible to extend the same to this system and use for sorting cells under growth factor gradients.

When using growth factors in the outer matrix, one of the confounding factor in downstream analysis would be the fact that there might be growth factor induced changes in cells that reach the outer gel. So differential behavior of cells that migrate out may be difficult to co-relate with just their motility alone, as it may also be a result of altered signaling as a result of the growth factor activity.

4.Are both setups compatible with live imaging, so that it would be possible to track important parameters of the migration of different cells (eg speed, directionality, etc), and cell-specific parameters (eg. morphology, actin cytoskeleton changes, membrane changes, etc.) during migration itself?

The 2D system is not well suited for imaging. You can use 20X objective and look at the rough morphologies of the cells at the top of the device, but in the bottom you have a lot of interference rings due to the edge. Cells migrating upwards cannot be imaged. Confocal microscope won t work.

In 3D the situation is different. Confocal microcopy can be used. This is how we measured the migration speed og the T-cell. Of couse you only detet the first few hundred microns.

5.At present, the 3D model as described in your work, allows separating migrating from non-migrating cells. This is perhaps very complex, but in your 3D model, is it possible to ‘reproduce’ the characteristics of typical destination sites for eg. cancer cells, immune cells, etc. to study not only migration from a site, but migration to specific locations?

Yes, indeed the approach is tailorable and in principle can be extended to make the outer cleavable hydrogel as a mimic of a distinct target tissue. So for example if we want to sort cancer cells that preferably metastasize into bone, certain features that mimic the bone tissue such as higher stiffness, collagen type I or other bone matrix proteins, and hydroxyapatite mineral particles can be incorporated into the matrix . In addition, as we pointed above, growth factors or chemokines can also be immobilized in the outer bulk gel to reproduce characteristics of a typical destination tissue.

6.How can you separate intermediate populations in your 2D setup? How do you define the best timing to perform downstream analyses?

We feel one of the most interesting aspect about 2D sorting is that multiple waves of migratory cells can be isolated by using multilayered PDMS microwells. For example, for an initial optimization for a cell type, two spacer layers can be included between the bottom and the collecting layer. After initial layer of migratory cells reach the collecting layer, it can be peeled off and now the top spacer layer can act as a collecting layer for the next wave of migratory cells and so forth. Essentially this allows to sort and compare multiple waves of migratory cells.

The best timing in our experience would vary significantly for the cells in question and must be estimated based on some initial optimization experiments.

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A Method to sort heterogenous cell populations based on migration in 2D and 3D environments

Background

Key findings and developments

What I like about this preprint

References

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