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Optimization of a Clinically Relevant Chemical-Mechanical Tissue Dissociation Workflow for Single-Cell Analysis

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Abstract

Introduction

While single-cell analysis technology has flourished, obtaining single cells from complex tissues continues to be a challenge. Current methods require multiple steps and several hours of processing. This study investigates chemical and mechanical methods for clinically relevant preparation of single-cell suspension from frozen biopsy cores of complex tissues. The developed protocol can be completed in 15 min.

Methods

Frozen bovine liver biopsy cores were normalized by weight, dimension, and calculated cellular composition. Various chemical reagents were tested for their capability to dissociate the tissue via confocal microscopy, hemocytometry and quantitative flow cytometry. Images were processed using ImageJ. Quantitative flow cytometry with gating analysis was also used for the analysis of dissociation. Physical modeling simulations were conducted in COMSOL Multiphysics.

Results

A rapid method for tissue dissociation was developed for single-cell analysis techniques. The results of this study show that a combination of 1% type-1 collagenase and pronase or hyaluronidase in 100 U/µL HBSS solution is the most effective at dissociating 2.5 mm thawed bovine liver biopsy cores in 15 min, with dissociation efficiency of 37-42% and viability >90% as verified using live MDA-MB-231 cancer cells. Cellular dissociation is significantly improved by adding a controlled mechanical force during the chemical process, to dissociate 93 ± 8% of the entire tissue into single cells.

Conclusions

Understanding cellular dissociation in ex vivo tissues is essential to the development of clinically relevant dissociation workflows. Controlled mechanical force in combination with chemical treatment produces high quality tissue dissociation. This research is relevant to the understanding and assessment of tissue dissociation and the establishment of an automated preparatory workflow for single cell diagnostics.

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References

  1. Alles, J., Karaiskos, N., Praktiknjo, S.D., Grosswendt, S., Wahle, P., Ruffault, P.L., Ayoub, S., Schreyer, L., Boltengagen, A., Birchmeier, C. and Zinzen, R. Cell fixation and preservation for droplet-based single-cell transcriptomics. BMC Biol. 15(1)44. 2017.

  2. Amsterdam, A., T. E. Solomon, and J. D. Jamieson. Sequential dissociation of the exocrine pancreas. Methods in cell biol. 20:361, 1978.

    Article  Google Scholar 

  3. Blow, N. Biobanking: freezer burn. Nat. Methods 6(2):173–178, 2009.

    Article  Google Scholar 

  4. Cunningham, R. E. Tissue Disaggregation. Immunocytochemical Methods and Protocols 327-330. New York: Humana Press, 2010.

    Google Scholar 

  5. Elattar, T. M., and A. S. Virji. The inhibitory effect of curcumin, genistein, quercetin and cisplatin on the growth of oral cancer cells in vitro. Anticancer Res. 20(3A):1733–1738, 2000.

    Google Scholar 

  6. Freyer, J. P., and R. M. Sutherland. Selective dissociation and characterization of cells from different regions of multicell tumor spheroids. Cancer Res. 40(11):3956–3965, 1980.

    Google Scholar 

  7. Heslin, M. J., J. J. Lewis, J. M. Woodruff, and M. F. Brennan. Core needle biopsy for diagnosis of extremity soft tissue sarcoma. Ann. Surg. Oncol. 4(5):425–431, 1997.

    Article  Google Scholar 

  8. Hwang, B., J. H. Lee, and D. Bang. Single-cell RNA sequencing technologies and bioinformatics pipelines. Exp. Mol. Med. 50(8):1–14, 2018.

    Article  Google Scholar 

  9. Jager, L. D., C. M. A. Canda, C. A. Hall, C. L. Heilingoetter, J. Huynh, S. S. Kwok, J. H. Kwon, J. R. Richie, and M. B. Jensen. Effect of enzymatic and mechanical methods of dissociation on neural progenitor cells derived from induced pluripotent stem cells. Adv. Med. Sci. 61(1):78–84, 2016.

    Article  Google Scholar 

  10. Jermyn, M., Mok, K., Mercier, J., Desroches, J., Pichette, J., Saint-Arnaud, K., Bernstein, L., Guiot, M.C., Petrecca, K. and Leblond, F., Intraoperative brain cancer detection with Raman spectroscopy in humans. Sci Transl Med, 7(274)274ra19-274ra19. 2015.

  11. Junatas, K. L., Z. Tonar, T. Kubíková, V. Liška, R. Pálek, P. Mik, M. Králíčková, and K. Witter. Stereological analysis of size and density of hepatocytes in the porcine liver. J. Anat. 230(4):575–588, 2017.

    Article  Google Scholar 

  12. Kasserra, H. P., and K. J. Laidler. Mechanisms of action of trypsin and chymotrypsin. Can. J. Chem. 47:4031–4039, 1969.

    Article  Google Scholar 

  13. Kaur, M., and L. Esau. Two-step protocol for preparing adherent cells for high-throughput flow cytometry. Biotechniques 59(3):119–126, 2015.

    Article  Google Scholar 

  14. Kim, J., S. Han, J. Yoon, E. Lee, D. W. Lim, J. Won, J. Y. Byun, and S. Chung. Nanointerstice-driven microflow patterns in physical interrupts. Microfluid Nanofluidics 18(5–6):1433–1438, 2015.

    Article  Google Scholar 

  15. Kim, Y. J., R. L. Sah, J. Y. H. Doong, and A. J. Grodzinsky. Fluorometric assay of DNA in cartilage explants using Hoechst 33258. Anal. Biochem. 174(1):168–176, 1988.

    Article  Google Scholar 

  16. Klein, A.B., Witonsky, S.G., Ansar Ahmed, S., Holladay, S.D., Gogal Jr, R.M., Link, L. and Reilly, C.M. Impact of different cell isolation techniques on lymphocyte viability and function. J Immunoassay Immunochem, 27(1)61-76. 2006.

  17. L. Nestler, E. Evege, J. Mclaughlin, D. Munroe, T. Tan, K. Wagner, and B. Stiles. TrypLE ™ express: a temperature stable replacement for animal trypsin in cell dissociation applications. Quest 1, 2004.

  18. Miller, T. E., Mack, S. C., & Rich, J. N. Mouse cell depletion. Miltenyi Biotec.

  19. Mino-Kenudson, M. Cons: Can liquid biopsy replace tissue biopsy?—the US experience. Transl Lung Cancer Res 5(4):424, 2016.

    Article  Google Scholar 

  20. Rafael, S. C., G. H. Diego, and C. H. F. Javier. Mechanism of action of collagenase clostridium histolyticum for clinical application. Eur. J. Clin. Pharmacol. 18:263–272, 2016.

    Google Scholar 

  21. Sambrook, J. and Russell, D.W. Estimation of cell number by hemocytometry counting. Cold Spring Harbor Protocols, 2006.

  22. Sen, A., M. S. Kallos, and L. A. Behie. New tissue dissociation protocol for scaled-up production of neural stem cells in suspension bioreactors. Tissue Eng. 10(5–6):904–913, 2004.

    Article  Google Scholar 

  23. Shapiro, E., T. Biezuner, and S. Linnarsson. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat. Rev. Genet. 14(9):618–630, 2013.

    Article  Google Scholar 

  24. Silvestri, G. A., A. V. Gonzalez, M. A. Jantz, M. L. Margolis, M. K. Gould, L. T. Tanoue, L. J. Harris, and F. C. Detterbeck. Methods for staging non-small cell lung cancer: diagnosis and management of lung cancer: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 143(5):e211S–e250S, 2013.

    Article  Google Scholar 

  25. Stenn, K. S., R. Link, G. Moellmann, J. Madri, and E. Kuklinska. Dispase, a neutral protease from Bacillus polymyxa, is a powerful fibronectinase and type IV collagenase. J Invest Dermatol 93(2):287–290, 1989.

    Article  Google Scholar 

  26. Stern, R., and M. J. Jedrzejas. Hyaluronidases: their genomics, structures, and mechanisms of action. Chem. Rev. 106(3):818–839, 2006.

    Article  Google Scholar 

  27. Tirosh, I., B. Izar, S. M. Prakadan, M. H. Wadsworth, D. Treacy, J. J. Trombetta, A. Rotem, C. Rodman, C. Lian, G. Murphy, and M. Fallahi-Sichani. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Sci 352(6282):189–196, 2016.

    Article  Google Scholar 

  28. van den Brink, S. C., F. Sage, Á. Vértesy, B. Spanjaard, J. Peterson-Maduro, C. S. Baron, C. Robin, and A. Van Oudenaarden. Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations. Nat .Methods 14(10):935, 2017.

    Article  Google Scholar 

  29. Vanharanta, S., and J. Massagué. Origins of metastatic traits. Cancer Cell 24(4):410–421, 2013.

    Article  Google Scholar 

  30. Vekemans, K., and F. Braet. Structural and functional aspects of the liver and liver sinusoidal cells in relation to colon carcinoma metastasis. World J Gastroenterol: WJG 11(33):5095, 2005.

    Article  Google Scholar 

  31. Vembadi, A., Menachery, A. and Qasaimeh, M.A. Cell cytometry: review and perspective on biotechnological advances. Front Bioeng Biotechnol, 7. 2019.

  32. Wang, Y., and N. E. Navin. Advances and applications of single-cell sequencing technologies. Mol. Cell 58(4):598–609, 2015.

    Article  Google Scholar 

  33. Waymouth, C. Tissue Dissociation Guide. Freehold, NJ: Worthington Biochemical, pp. 1–78, 1993.

    Google Scholar 

  34. Wilson, Z. E., A. Rostami-Hodjegan, J. L. Burn, A. Tooley, J. Boyle, S. W. Ellis, and G. T. Tucker. Inter-individual variability in levels of human microsomal protein and hepatocellularity per gram of liver. Br. J. Clin. Pharmacol. 56(4):433–440, 2003.

    Article  Google Scholar 

  35. Wlodkowic, D., and J. M. Cooper. Microfabricated analytical systems for integrated cancer cytomics. Anal. Bioanal. Chem. 398(1):193–209, 2010.

    Article  Google Scholar 

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Acknowledgments

We would like to acknowledge the Flow Cytometry Facility, Genomics Core Facility, and Leduc Bioimaging Facility of Brown University for providing the flow cytometer, automated hemocytometer, and confocal microscope used in the study. We would also like to thank the Laboratory of Ian Wong for supplying us with the cancer cells used in the viability assay. We would also like to gratefully acknowledge PerkinElmer for the financial support for this study. AT is a paid scientific advisor/consultant and lecturer for PerkinElmer.

No human studies were carried out by the authors for this article. No animal studies were carried out by the authors for this article.

Conflict of interest

The authors declare that they have no conflict of interest. AT is a paid scientific advisor/consultant and lecturer for PerkinElmer.

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Authors and Affiliations

  1. School of Engineering, Center for Biomedical Engineering, Brown University, Providence, RI, 02916, USA

    E. Celeste Welch, Harry Yu & Anubhav Tripathi

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  1. E. Celeste Welch
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Correspondence to Anubhav Tripathi.

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Welch, E.C., Yu, H. & Tripathi, A. Optimization of a Clinically Relevant Chemical-Mechanical Tissue Dissociation Workflow for Single-Cell Analysis. Cel. Mol. Bioeng. 14, 241–258 (2021). https://doi.org/10.1007/s12195-021-00667-y

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