Sorting large cells successfully is no mean feat. Because large cells are fragile, prone to aggregation, and sediment quickly, sorting them demands careful sample preparation and the right tools for the job. Here, we explore some of the large cell types being studied by researchers and share tips that can help to improve sorting outcomes.
‘Large’ is not just a matter of size
When discussing the process of sorting large cells, it is important to note that large does not always mean physically big—it can also refer to cells that are irregularly shaped and highly deformable. “Dendritic cells are a prime example,” says Rodrigo Pestana Lopes, Ph.D., Associate Director for Global Market Development at BD Biosciences. “Although not the largest by size, dendritic cells have a highly irregular shape due to their branching projections. Additionally, the adhesive properties of dendritic cells often lead to clumping and a higher frequency of aggregates such as doublets. These characteristics cause dendritic cells to occupy more space in the core stream and flow at varying speeds due to the parabolic flow pattern in a cuvette, presenting unique challenges for sorting.”
Large cell types that commonly require sorting
- Cardiomyocytes
- Adipocytes
- Neurons
- Megakaryocytes
- Multinucleated macrophages
- Osteoclasts
- 3D cell culture models (e.g., spheroids, organoids, tumoroids)
- Insect cells
- Nematodes
- Double-emulsion droplets (e.g., used to retain cells that produce a specific extracellular product)
- Hydrogel particles and similar carriers (e.g., used to establish 3D model systems)
Overcoming challenges for droplet-based sorting of large cells
Before considering some of the challenges for sorting large cells, it is worth recalling how droplet-based cell sorting works. “Essentially, cuvette-based cell sorters such as the BD FACSDiscover™ S8 Cell Sorter predict where a targeted cell will be at a given point in the future based on sheath pressure and sample flow rate,” explains Pestana Lopes. “When the stream is broken into droplets after the laser interrogation point, those droplets are evaluated for sorting based on these predictions. However, while this approach works well for uniform particles like beads or small, spherical cells like lymphocytes, which travel in a fairly consistent pattern and are relatively easy to centralize in the sample core, it becomes far more complex for large or irregular cell types. For instance, some large cells can span multiple droplets, but if the system assumes that the cell fits within a single droplet, this can lead to incomplete or inaccurate sorting.”
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According to Andrew Snyder, Product Manager, Cell Sorting Technologies at Thermo Fisher Scientific, the drop delay value (the length of time between the interrogation point and the droplet break-off point) is one of the most critical factors to consider when setting up a large particle sort. “While instruments such as the Invitrogen™ Bigfoot™ Cell Sorter automatically calculate the drop delay using beads, optimizing this value for your cells of interest is vital to maximize recovery,” he says. “Because large cells travel less consistently through the instrument than small particles, determining which droplet contains the target cell cannot rely on predictions alone, and instead requires some degree of user intervention.”
Table 1 summarizes some of the main issues faced by researchers when sorting large cells and suggests ways of addressing these problems.
| Challenge | Tips to improve sorting outcomes |
|---|
| Fragility. Large cells are often delicate and prone to damage. |
- Consider replacing trypsin with a gentler dissociation reagent (e.g., Accutase).
- Reduce the sheath pressure and use larger nozzle sizes (e.g., 130, 150 or 200 µm) to prevent shear stress.
- Sort cells into an appropriate buffer to safeguard their survival.
|
| Aggregation and clumping. Irregular shapes and adhesive properties increase the likelihood of doublets and aggregates. |
- Ensure the sample buffer composition minimizes the activation of adhesion molecules.
- Control the temperature in both the sample tube and collection units to reduce adhesion.
- Match sample buffer viscosity to sheath fluid to preserve stable hydrodynamics.
|
| Sedimentation. The greater mass of large cells makes them more likely to settle quickly in the sample tube. |
- Use proper tube materials (e.g., low-adhesion plastics) to reduce cell sticking.
- Maintain constant agitation of the sample tube during sorting to keep the cells in suspension.
|
| Drop delay accuracy. Large or deformable cells travel at different speeds, making it difficult for the instrument to predict which droplet contains the target cell. |
- Try using multiple-drop sorting (adding trailing drops to the sort envelope) for oversized cells, but be aware that this might impact purity.
- Perform test sorts with microscopy confirmation to validate accuracy.
|
| Instrument clogging. Clogs can negatively impact sorting accuracy and limit experimental efficiency. |
- Optimize the sample concentration, which should be reduced when using larger nozzle sizes.
- Decrease the sort rate.
|
Table 1. Key challenges and potential solutions for large cell sorting applications.
Technology advances for large cell sorting applications
To support growing demand for large cell sorting applications, instrument manufacturers continue to refine their sorting technology. “Thermo Fisher Scientific offers three large nozzle tips that cover most large particles any cell sorter could use,” reports Snyder. “The 120 µm nozzle tip operates at 20 psi and provides many of the perks from the 100 µm nozzle tip while being slightly larger. For much larger particles, the 150 and 200 µm nozzle tips operate at 8.75 psi and 6 psi, respectively. Both the 150 and 200 µm nozzle tips are the largest nozzle tips commercially available.”
Pestana Lopes notes that the BD FACSDiscover™ S8 Cell Sorter uniquely combines imaging parameters with spectral flow cytometry, adding morphological and spatial information not available on traditional sorters. “This enables verification of target cells based on numerous morphological parameters and signal localization and helps discriminate them from doublets or aggregates that are often mistaken for large cells when gating solely on traditional parameters such as light scatter and MFI,” he says. Additionally, qualifying cells through image-derived parameters may contribute to sort performance. “This has been hypothesized by a few users but not yet scientifically proven through a comparative study,” he adds. “However, those users report improved sorting performance when using imaging parameters and theorize that leveraging Center of Mass X and Y imaging parameters, for example, could help centralize cells inside droplets to promote more uniform charge distribution and, as a result, achieve more precise electromagnetic deflection.”
Whatever type of large cells you’re working with, adopting practices that ensure cell integrity and sorting accuracy is essential to generate reliable results. Stay tuned to Biocompare for more cell sorting tips from leading technology providers.