Flow Cytometry Protocols pp 347-369 | Cite as
Real-Time Deformability Cytometry: Label-Free Functional Characterization of Cells
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Abstract
Real-time deformability cytometry (RT-DC) is a microfluidic technique that allows to capture and evaluate morphology and rheology of up to 1000 cells/s in a constricted channel. The cells are deformed without mechanical contact by hydrodynamic forces and are quantified in real-time without the need of additional handling or staining procedures. Segmented pictures of the cells are stored and can be used for further analysis. RT-DC is sensitive to alterations of the cytoskeleton, which allows, e.g., to show differences in cell cycle phases, identify different subpopulations in whole blood and to study mechanical stiffening of cells entering a dormant state. The abundance of the obtainable parameters and the interpretation as mechanical readout is an analytical challenge that needs standardization. Here, we will provide guidelines for measuring and post-processing of RT-DC data.
Key words
Label-free cytometry Microfluidics Image analysis Automated segmentation Morphometry Rheology Cell mechanics Cytoskeleton Linear mixed modelsNotes
Acknowledgments
We thank the BIOTEC/CRTD Microstructure Facility (partly funded by the State of Saxony and the European Fund for Regional Development—EFRE) and Dr. Salvatore Girardo for the development and production of the master templates. We acknowledge financial support from the Alexander von Humboldt Foundation (Alexander von Humboldt Professorship to J.G.), the Sächsisches Ministerium für Wissenschaft und Kunst (TG70 grant to O.O. and J.G.), the Bundesministerium für Bildung und Forschung (ZIK grant to O.O. under no. 03Z22CN11), and the European Union’s Seventh Framework Programme under grant agreement no. 632222 (Proof-Of-Concept Grant FastTouch to J.G.).
Conflict of Interest Statement
O.O. is co-founder and CEO of Zellmechanik Dresden distributing the technology.
References
- 1.Shapiro HM (2003) Practical flow cytometry. Wiley, Hoboken. doi: 10.1002/0471722731 CrossRefGoogle Scholar
- 2.Green RE, Sosik HM, Olson RJ, DuRand MD (2003) Flow cytometric determination of size and complex refractive index for marine particles: comparison with independent and bulk estimates. Appl Opt 42:526. doi: 10.1364/AO.42.000526 CrossRefGoogle Scholar
- 3.Lautenschlager F, Paschke S, Schinkinger S et al (2009) The regulatory role of cell mechanics for migration of differentiating myeloid cells. Proc Natl Acad Sci 106:15696–15701. doi: 10.1073/pnas.0811261106 CrossRefGoogle Scholar
- 4.Tse JM, Cheng G, Tyrrell JA et al (2012) Mechanical compression drives cancer cells toward invasive phenotype. Proc Natl Acad Sci U S A 109:911–916. doi: 10.1073/pnas.1118910109 CrossRefGoogle Scholar
- 5.Darling EM, Zauscher S, Block JA, Guilak F (2007) A thin-layer model for viscoelastic, stress-relaxation testing of cells using atomic force microscopy: do cell properties reflect metastatic potential? Biophys J 92:1784–1791. doi: 10.1529/biophysj.106.083097 CrossRefGoogle Scholar
- 6.Guck J, Schinkinger S, Lincoln B et al (2005) Optical deformability as an inherent cell marker for testing malignant transformation and metastatic competence. Biophys J 88:3689–3698. doi: 10.1529/biophysj.104.045476 CrossRefGoogle Scholar
- 7.Lekka M, Laidler P, Gil D et al (1999) Elasticity of normal and cancerous human bladder cells studied by scanning force microscopy. Eur Biophys J 28:312–316. doi: 10.1007/s002490050213 CrossRefGoogle Scholar
- 8.Ekpenyong AE, Whyte G, Chalut K et al (2012) Viscoelastic properties of differentiating blood cells are fate- and function-dependent. PLoS One 7:e45237. doi: 10.1371/journal.pone.0045237 CrossRefGoogle Scholar
- 9.Darling EM, Topel M, Zauscher S et al (2008) Viscoelastic properties of human mesenchymally-derived stem cells and primary osteoblasts, chondrocytes, and adipocytes. J Biomech 41:454–464. doi: 10.1016/j.jbiomech.2007.06.019 CrossRefGoogle Scholar
- 10.Lange JR, Steinwachs J, Kolb T et al (2015) Microconstriction arrays for high-throughput quantitative measurements of cell mechanical properties. Biophys J 109:26–34. doi: 10.1016/j.bpj.2015.05.029 CrossRefGoogle Scholar
- 11.Hosseini SM, Feng JJ (2012) How malaria parasites reduce the deformability of infected red blood cells. Biophys J 103:1–10. doi: 10.1016/j.bpj.2012.05.026 CrossRefGoogle Scholar
- 12.Tabeling P (2005) Introduction to microfluidics. Oxford University Press, New YorkGoogle Scholar
- 13.Rosenbluth MJ, Lam WA, Fletcher DA (2008) Analyzing cell mechanics in hematologic diseases with microfluidic biophysical flow cytometry. Lab Chip 8:1062–1070. doi: 10.1039/b802931h CrossRefGoogle Scholar
- 14.Lange JR, Goldmann WH, Alonso JL (2016) Influence of αvβ3 integrin on the mechanical properties and the morphology of M21 and K562 cells. Biochem Biophys Res Commun 478:1280–1285. doi: 10.1016/j.bbrc.2016.08.111 CrossRefGoogle Scholar
- 15.Byun S, Son S, Amodei D et al (2013) Characterizing deformability and surface friction of cancer cells. Proc Natl Acad Sci 110:7580–7585. doi: 10.1073/pnas.1218806110 CrossRefGoogle Scholar
- 16.Dudani JS, Gossett DR, Tse HTK, Di Carlo D (2013) Pinched-flow hydrodynamic stretching of single-cells. Lab Chip 13:3728. doi: 10.1039/c3lc50649e CrossRefGoogle Scholar
- 17.Gossett DR, Tse HTK, Lee SA et al (2012) Hydrodynamic stretching of single cells for large population mechanical phenotyping. Proc Natl Acad Sci 109:7630–7635. doi: 10.1073/pnas.1200107109 CrossRefGoogle Scholar
- 18.Otto O, Rosendahl P, Mietke A et al (2015) Real-time deformability cytometry: on-the-fly cell mechanical phenotyping. Nat Methods 12:199–202. doi: 10.1038/nmeth.3281 CrossRefGoogle Scholar
- 19.Mietke A, Otto O, Girardo S et al (2015) Extracting cell stiffness from real-time deformability cytometry: theory and experiment. Biophys J 109:2023–2036. doi: 10.1016/j.bpj.2015.09.006 CrossRefGoogle Scholar
- 20.Suzuki S, Be K (1985) Topological structural analysis of digitized binary images by border following. Comput Vis Graph Image Process 30:32–46. doi: 10.1016/0734-189X(85)90016-7 CrossRefGoogle Scholar
- 21.Bradski G (2000) The OpenCV library. Dr Dobbs J Softw Tools 25:120–126Google Scholar
- 22.Mietke A (2014) Theoretical and experimental analysis of cell deformations by hydrodynamic forces in microfluidic channels. Technische Universität DresdenGoogle Scholar
- 23.Herold C (2017) Mapping of deformation to apparent young’s modulus in real-time deformability cytometry. arXiv:1704.00572Google Scholar
- 24.Müller P, et al. (2015) ShapeOut: analysis software for real-time deformability cytometry [Software]. Available at https://github.com/ZELLMECHANIK-DRESDEN/ShapeOut
- 25.Beer FP, Johnston ER Jr, Mazurek D, Cornwell P (2012) Vector mechanics for engineers: statics and dynamics, 10th edn. McGraw-Hill International, New YorkGoogle Scholar
- 26.Geoff Olynyk (2012) File Exchange - MATLAB Central – Mathworks. http://de.mathworks.com/matlabcentral/fileexchange/36525-volrevolve/content/volRevolve.m. Accessed 1 Jan 2017
- 27.Mokbel M, Mokbel D, Mietke A et al (2017) Numerical simulation of real-time deformability cytometry to extract cell mechanical properties. ACS Biomater Sci Eng. doi: 10.1021/acsbiomaterials.6b00558
- 28.R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
- 29.R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
- 30.Mood AM, Graybill FA, Boes DC (1974) Introduction to the theory of statistics. McGraw-Hill International, New YorkGoogle Scholar
- 31.Wilks SS (1938) The large-sample distribution of the likelihood ratio for testing composite hypotheses. Ann Math Stat 9:60–62. doi: 10.1214/aoms/1177732360 CrossRefGoogle Scholar