figshare
Browse
1/1
3 files

MetaDeformability Dataset

Version 2 2020-06-15, 09:01
Version 1 2020-01-24, 14:58
dataset
posted on 2020-06-15, 09:01 authored by Marta UrbanskaMarta Urbanska, Hector E. Muñoz, Josephine Shaw Bagnall, Oliver Otto, Scott R. Manalis, Dino Di Carlo, Jochen Guck

This datasets contains results presented in the following manuscript:

Urbanska, M., Muñoz, H.E. et al., Nat Methods 17, 587–593 (2020)

A comparison of microfluidic methods for high-throughput cell deformability measurements

https://doi.org/10.1038/s41592-020-0818-8


Abstract

The mechanical phenotype of a cell is an inherent biophysical marker of its state and function, with potential value in clinical diagnostics. Several microfluidic-based methods developed in recent years have enabled single-cell mechanophenotyping at throughputs comparable to flow cytometery. Here we present a highly standardized cross-laboratory study comparing three leading microfluidic-based approaches to measure cell mechanical phenotype: constriction-based deformability cytometry (cDC), shear flow deformability cytometry (sDC), and extensional flow deformability cytometry (xDC). We show that all three methods detect cell deformability changes induced by exposure to altered osmolarity. However, a dose-dependent deformability increase upon latrunculin B-induced actin disassembly was detected only with cDC and sDC, which suggests that when exposing cells to the higher strain rate imposed by xDC, other cell components dominate the response. The direct comparison presented here serves to unify deformability cytometry methods and provides context for the interpretation of deformability measurements performed using different platforms.


Further information

The cross-laboratory study presented here focuses on comparing representatives of the three deformability cytometry methods:

(i) an SMR-based cDC variant [1],

(ii) RT-DC [2] as an example of sDC,

(iii) DC [3] as an example of xDC.


References

[1] Byun et al., 2013. Characterizing deformability and surface friction of cancer cells. PNAS 110(19): 7580-7585, https://doi.org/10.1073/pnas.1218806110

[2] Otto et al., 2015. Real-time deformability cytometry: on-the-fly cell mechanical phenotyping. Nature Methods 12(3): 199-202, https://doi.org/10.1038/nmeth.3281

[3] Gossett et al., 2012. Hydrodynamic stretching of single cells for large population mechanical phenotyping. PNAS 109(20): 7630-7635, https://doi.org/10.1073/pnas.1200107109


Analysis codes

The accompanying analysis scripts necessary to generate the results presented in the manuscript from the dataset uploaded here are available on GitHub:

https://github.com/dicarlo-lab/metadeformability


Funding

Alexander von Humboldt Professorship to J.G.

Ludwig Center for Molecular Oncology (S.R.M.)

Cancer Systems Biology Consortium U54 CA217377 from the NCI (S.R.M.)

ZIK grant to O.O. under grant agreement 03Z22CN11

Presidential Early Career Award for Scientists and Engineers to D.D. (N00014-16-1-2997)

History