Sorting the impossible: CytoRecovery’s technology and applications

By now, we have all become acquainted with the need for cell sorting in biomedical research, but what happens if you have a sample that can’t be sorted using conventional label-based methods? Perhaps you have a sample that is overridden with debris and dead cells, and you need to isolate the few remaining viable cells. Or maybe you have stem and stem-like cells that don’t have a readily available marker for which you would like to sort. Or maybe, you are hoping to recover rare cells from a heterogeneous mixture and need a gentle method of sorting with a sufficient detection limit. Well, you’ve come to the right place.

CytoRecovery technology offers a solution to these difficult sorts while maintaining sample sterility and viability. The CytoR1 Platform can sort your cells without a label for a variety of applications. CytoRecovery’s CytoR1TM Platform is a chip-based platform that uses dielectrophoresis (DEP) to sort cells, enrich for live and rare cell types, and remove debris from biological samples. By implementing electric fields across the intelligently designed microfluidic CytoChipTM, cells of interest become “trapped” within the microchannel based on their electrical properties. Other cells, with differing bioelectric signatures (e.g., phenotype, morphology, membrane capacitance, stemness, size, etc.) will not be affected by the electric field and proceed out of the outlet. At the user’s discretion, the electric field can be turned off and the desired cells can be released from the microchannel and proceed to the outlet for collection. 

CytoRecovery’s technology is revolutionizing the way your samples are prepared, purified, and enriched – and it does it all without a label. The applications of our technology as it relates to mammalian cell sorting are vast and more than one can fit in a single blog post. With that said, here’s just a few exciting applications for CytoRecovery’s technology:

  1. Viable Cells: The CytoR1 platform can enrich viable cells to enhance your downstream applications. Dead cells and debris can lead to inaccurate cytometry results and sample contamination. By implementing the CytoR1 platform before performing sensitive processes, such as genomics, your sample can be improved by removing impurities such as cellular debris and low/non-viable cells. Additionally, enriching live cells in a label-free and gentle manner is becoming more and more desirable for cellular engineering applications such as the development of immunotherapies like CAR-T cell manufacturing. CytoRecovery offers an innovative approach to enrich cells that survive transfection to improve efficiencies across the board.A graph of a cell AI-generated content may be incorrect.

  2. Stem Cells: Stem cells pose a unique problem to the biomedical community – their status as progenitor cells with an unknown differentiation potential makes developing a marker for sorting these cells difficult. Still, stem cells must be gently handled to avoid unwanted differentiation upon processing. Stem cells, though difficult to mark, have unique properties nonetheless. These unique properties are reflected in their bioelectric signature and are detectable using CytoRecovery technologies. In fact, the laboratory of Dr. Lisa Flanagan at University of California at Irvine shows dielectrophoresis is capable of sorting neuronal stem cells based on their differentiation bias prior to differentiation.1-2 Likewise, Dr. Tayloria Adams from the University of California at Irvine is capitalizing on these capabilities to investigate the role of heterogeneity and fate-bias of mesenchymal stem cells for regenerative medicine applications.2-3 The CytoR1 platform provides a basis for the user to investigate their cell populations of interest uniquely, even in the absence of a marker. A collage of different colors of different shapes AI-generated content may be incorrect.
  3. Circulating Tumor Cells: Circulating tumor cells (CTCs) cancer cells that have spread into the blood stream from a primary or satellite tumor, potentially indicating metastasis or at the very least being a marker for early diagnosis. The difficulty with identifying CTCs is their rarity. There may be only ~200-3000 CTCs in a mL of blood amongst the 4-6 million blood cells – talk about a needle in a haystack! DEP, however, has a lower limit of detection on the order of 1 CTC/mL,4-5 a value low enough to detect these rare cells in healthy patients.4 This capability extends to several other rare cell types, as well. By harnessing the power of DEP and designing a platform that prioritizes cell health to subsequently perform downstream studies to facilitate precision medicine, the CytoR1 is positioned well to meet your CTC isolation needs. A graph of a number of cells AI-generated content may be incorrect.

    Of course, the applications don’t end there. The CytoR1 Platform is an advantageous tool to have in the laboratory for exploratory research, purifying and preparing samples, characterizing sample homogeneity, identifying subpopulations, and isolating rare cells. CytoRecovery’s technology stands in the gap left by conventional cell sorting technologies by offering a new way to sort cells without sacrificing your sample.

References

  1. Flanagan, L. A., Lu, J., Wang, L., Marchenko, S. A., Jeon, N. L., Lee, A. P., & Monuki, E. S. (2008). Unique Dielectric Properties Distinguish Stem Cells and Their Differentiated Progeny. Stem Cells, 26(3), 656–665. https://doi.org/10.1634/stemcells.2007-0810

  2. Adams, T. N. G., Jiang, A. Y. L., Mendoza, N. S., Ro, C. C., Lee, D.-H., Lee, A. P., & Flanagan, L. A. (2020). Label-free enrichment of fate-biased human neural stem and progenitor cells. Biosensors and Bioelectronics, 152, 111982. https://doi.org/10.1016/j.bios.2019.111982

  3. Adams, T. N. G., Turner, P. A., Janorkar, A. v., Zhao, F., & Minerick, A. R. (2014). Characterizing the dielectric properties of human mesenchymal stem cells and the effects of charged elastin-like polypeptide copolymer treatment. Biomicrofluidics, 8(5). https://doi.org/10.1063/1.4895756

  4. Habli, Z., AlChamaa, W., Saab, R., Kadara, H., & Khraiche, M. L. (2020). Circulating Tumor Cell Detection Technologies and Clinical Utility: Challenges and Opportunities. Cancers, 12(7), 1930. https://doi.org/10.3390/cancers12071930

  5. He, W., Kularatne, S. A., Kalli, K. R., Prendergast, F. G., Amato, R. J., Klee, G. G., Hartmann, L. C., & Low, P. S. (2008). Quantitation of circulating tumor cells in blood samples from ovarian and prostate cancer patients using tumor‐specific fluorescent ligands. International Journal of Cancer, 123(8), 1968–1973. https://doi.org/10.1002/ijc.23717