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

Nature Methods volume 17, pages 587–593 (2020)Cite this article

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Abstract

The mechanical phenotype of a cell is an inherent biophysical marker of its state and function, with many applications in basic and applied biological research. Microfluidics-based methods have enabled single-cell mechanophenotyping at throughputs comparable to those of flow cytometry. Here, we present a standardized cross-laboratory study comparing three microfluidics-based approaches for measuring cell mechanical phenotype: constriction-based deformability cytometry (cDC), shear flow deformability cytometry (sDC) and extensional flow deformability cytometry (xDC). 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, cellular components other than the actin cytoskeleton dominate the response. The direct comparison presented here furthers our understanding of the applicability of the different deformability cytometry methods and provides context for the interpretation of deformability measurements performed using different platforms.

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Fig. 1: Comparison of the microfluidics-based approaches for the determination of cell deformability used in this study.
Fig. 2: Effects of osmolarity changes on cell deformability.
Fig. 3: Effects of LatB-induced actin disassembly on cell deformability.

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Data availability

Source data for Figs. 1–3 are provided alongside the manuscript. The dataset containing numerical values from all deformability measurements supporting findings of this study is available on figshare60.

Code availability

MATLAB and R codes used to perform statistical analysis and generate data representations shown in this manuscript are available on GitHub at https://github.com/dicarlo-lab/metadeformability.

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Acknowledgements

We thank P. Janmey for helpful discussions, J. H. Kang and D. Soteriou for useful comments on the manuscript, A. Mietke (Massachusetts Institute of Technology) and C. Herold (Zellmechanik Dresden) for sharing parts of analysis codes, A.L. and D.E. Olins (University of New England) for providing the HL60/S4 cell line and the Microstructure Facility at the Center for Molecular and Cellular Bioengineering at Technische Universität Dresden (in part funded by the State of Saxony and the European Regional Development Fund) for help with the production of sDC chips. We acknowledge funding from the Alexander von Humboldt-Stiftung (Alexander von Humboldt Professorship to J.G.), the Ludwig Center for Molecular Oncology (S.R.M.), the Cancer Systems Biology Consortium U54 CA217377 and the Koch Institute Support Grant P30 CA14051 from the NCI (S.R.M.), the German Federal Ministry of Research and Education (ZIK grant to O.O. under grant agreement 03Z22CN11), and a Presidential Early Career Award for Scientists and Engineers (N00014-16-1-2997, to D.D.).

Author information

Author notes

  1. These authors contributed equally: Marta Urbanska, Hector E. Muñoz.

Authors and Affiliations

  1. Biotechnology Center, Center for Molecular and Cellular Bioengineering, Technische Universität Dresden, Dresden, Germany

    Marta Urbanska, Oliver Otto & Jochen Guck

  2. Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA

    Hector E. Muñoz & Dino Di Carlo

  3. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Josephine Shaw Bagnall & Scott R. Manalis

  4. Zentrum für Innovationskompetenz: Humorale Immunreaktionen in kardiovaskulären Erkrankungen, Universität Greifswald, Greifswald, Germany

    Oliver Otto

  5. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Scott R. Manalis

  6. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA

    Scott R. Manalis

  7. California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA, USA

    Dino Di Carlo

  8. Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA

    Dino Di Carlo

  9. Max Planck Institute for the Science of Light and Max-Planck-Zentrum für Physik und Medizin, Erlangen, Germany

    Jochen Guck

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Contributions

J.G., D.D. and S.R.M. conceptualized the project. M.U., H.E.M. and J.S.B. performed the experiments and analyzed the data. O.O. provided methodological support with sDC data acquisition and analysis. M.U. and H.E.M. visualized the data and prepared the original manuscript draft. All authors revised and edited the manuscript. J.G., D.D., S.R.M. and O.O. acquired funding.

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Correspondence to Scott R. Manalis, Dino Di Carlo or Jochen Guck.

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Competing interests

M.U., H.E.M., J.S.B. and J.G. declare no competing interests. O.O. is a shareholder of Zellmechanik Dresden GmbH distributing real-time deformability cytometry; Zellmechanik Dresden GmbH owns a patent for Real-Time Deformability Cytometry (RT-DC): EU patent under the number EP 30 036 520 B1. S.R.M. is a founder of Travera and Affinity Biosensors. D.D. has financial interests in Cytovale Inc., which is commercializing deformability cytometry technology.

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Integrated supplementary information

Supplementary Fig. 1 Distribution of passage times measured with cDC for untreated HL60 cells.

Bars represent binned data of control HL60 cells pulled from 10 experiments (total cell number, n = 9,734). Dashed curve represents Kernel density estimation (KDE) of probability distribution with vertical line at the most represented value equal to 23 ms.

Supplementary Fig. 2 Cell diameter of HL60 cells exposed to different osmotic shock conditions.

(a–c) Violin plots of cell diameter in a single experiment as measured by cDC (a), sDC (b) and xDC (c). Black boxes extend from 25th to 75th percentiles, with a dot at the median, whiskers indicate 1.5× IQR (interquartile range). (d–f) Summary of median cell diameter values obtained in all experiment series with cDC (d), sDC (e) and xDC (f). Data points correspond to medians of individual experiments (n = 3, 4 and 4, for cDC, sDC and xDC, respectively). Conditions measured in the same experimental series are color-coded. Boxes span 2× standard deviation with a line at the mean of all medians. In (d–f) statistical significance of overall differences among mean cell sizes at different osmolarities was tested using analysis of variance (ANOVA) and its result is shown on top of the horizontal line overarching all conditions. The P values reported above each box come from comparison of the given treatment to the control condition (300 mOsm) obtained through post-hoc analysis using two-sided pairwise t-tests for multiple comparison with Benjamin-Hochberg P-value adjustment.

Supplementary Fig. 3 Visualization of bin selection and data processing for osmolarity experiments.

(a–c) 50%-density contour plots of deformability vs cell diameter for an exemplary experiment on HL60 cells subjected to different osmolarity conditions. The contour plots are accompanied by deformability and cell diameter histograms for cDC (a), sDC (b), and xDC (c). The most represented 1-μm wide diameter bins used for relative deformability, RD, calculations and and the corresponding deformability histograms are outlined in grey. (d–f) Jitter plots showing distribution of RD from cDC (d), sDC (e), and xDC (f) measurements for a single experiment. Boxes extend from 25th to 75th percentiles, with a dot at the median, whiskers indicate 1.5× IQR (interquartile range) and each data point corresponds to an individual cell. (g–i) Summary of RD values obtained in all experimental series with cDC (g), sDC (h) and xDC (i). Data points correspond to medians of every experiment and conditions measured in same experimental series are color-coded. Boxes span 2× standard deviation with a line at the mean of all medians. (j) Number of events in the selected 1-μm wide diameter bin for each condition and method. (k) Events selected within the 1-μm wide diameter bin as a percentage of all events measured. In j and k, the boxes span 2× standard deviation with a line at the mean. In g-k, the statistics have been calculated for n = 3, 4 and 4 independent measurement replicates, for cDC, sDC and xDC, respectively.

Supplementary Fig. 4 Time-resolved effect of osmotic shock on HL60 deformability and size as measured by sDC.

(a–c) The changes in HL60 relative deformability, RD (a), and cell diameter (b) over time after exposure to medium with altered osmolarity as measured by sDC. The experiments were performed in 30 × 30-μm channels at a flowrate of 0.16 μl s−1. Data points represent medians of consecutive measurements taken at different times after the exposure to altered osmolarity medium. On average 3,000 events (and not less than 1,800) were analyzed for each data point.

Supplementary Fig. 5 Fitting of the relation between osmolarity and relative deformability for hyperosmotic shock data.

(a-c) Exponential (red), power law (green) and linear (blue) fits to relative deformability, RD, vs osmolarity data obtained with cDC (a), sDC (b) and xDC (c). Data points in a-c represent means of medians of multiple experimental replicates (n = 3, 4, and 4, for cDC, sDC, and xDC, respectively), error bars represent standard deviation. (d-e) Bar graphs of mean absolute residuals (d) and Bayesian information criterion (BIC) (e), that assess the quality of different fits. Values estimated for each method, as well as mean of values for all methods (n = 3) for given fit function, are presented. The error bars on the mean plots represent standard deviation. Mean absolute residuals give an information on how much the values predicted by the fitted function deviate from the experimental data. Lower values of residuals indicate better agreement of experimental data with proposed function. In case of BIC, lower values indicate a better fit.

Supplementary Fig. 6 Visualization of bin selection and data processing for LatB treatment experiments.

(a–c) 50%-density contour plots of deformability vs cell diameter for an exemplary experiment on HL60 cells treated with increasing concentration of LatB. The contour plots are accompanied by deformability and cell diameter histograms for cDC (a), sDC (b), and xDC (c). The most represented 1-μm wide diameter bins used for relative deformability, RD, calculations and the corresponding deformability histograms are outlined in grey. (d–f), Jitter plots showing distribution of RD from cDC (d), sDC (e), and xDC (f) measurements for a single experiment. Boxes extend from 25th to 75th percentiles, with a dot at the median, whiskers indicate 1.5 × IQR (interquartile range) and each data point corresponds to an individual cell. (g–i), Summary of RD values obtained in all experimental series with cDC (g), sDC (h) and xDC (i). Data points correspond to medians of every experiment and conditions measured in the same experimental series are color-coded. Boxes span 2× standard deviation with a line at the mean of all medians. (j) Number of events in the selected 1-μm wide diameter bin for each condition and method. (k) Events selected within the 1-μm wide diameter bin as a percentage of all events measured. In (j) and (k) the boxes span 2× standard deviation with a line at the mean. In g, k, the statistics have been calculated for n = 3, 5 and 4 independent measurement replicates, for cDC, sDC and xDC, respectively.

Supplementary Fig. 7 Dose-response to LatB treatment measured with sDC at three different flow rates.

Deformability, D (a), and relative deformability, RD (b), as a function of LatB concentration at three different flowrates (fr1 = 2.4 µl min-1, fr2 = 4.8 µl min-1, and fr3 = 7.2 µl min-1). The different flowrates are color-coded as indicated in the figure legend (fr1 – gray, fr2 – blue, fr3 – green). Open circles indicate medians of individual measurements, lines connect means of measurement replicates for each flowrate (n = 5), error bars correspond to standard deviation of the mean distributions. Bin-selected data was used.

Supplementary Fig. 8 Response to high LatB concentrations measured with cDC and sDC.

The graph shows relative deformability, RD, as a function of LatB concentration. Dots represent medians of individual measurements. Error bars represent median absolute deviation. Bin-selected data was used. One measurement series was performed using cDC (purple, from left to right n = 296 and 271 analyzed cells in the selected size bin per data point) and two measurement series were performed using sDC (bright and dark green, from left to right n = 656, 537, 420, 550, and n = 734, 615, 336, 541 analyzed cells in the selected size bin, for bright and dark green data points, respectively). The concentration range used for main analysis is shaded in gray.

Supplementary Fig. 9 Cell diameter of HL60 cells treated with different concentrations of LatB.

(a–c) Violin plots of cell diameter in a single experiment as measured by cDC (a), sDC (b) and xDC (c). Black boxes extend from 25th to 75th percentiles, with a dot at the median, whiskers indicate 1.5× IQR (interquartile range). (d–f) Summary of median cell diameter values obtained in all experiment series with cDC (d), sDC (e) and xDC (f). Data points correspond to medians of individual experiments (n = 3, 5 and 4, for cDC, sDC and xDC, respectively). Conditions measured in same experimental series are color-coded. Boxes span 2 × standard deviation with a line at the mean of all medians. In (d–f) statistical significance of overall differences among mean cell sizes at different concentrations was tested using analysis of variance (ANOVA) and its result is shown on top of the horizontal line overarching all conditions. The P values reported above each box come from comparison of the given treatment to the control condition obtained through post-hoc analysis using pairwise two-sided t-tests for multiple comparisons with Benjamin-Hochberg P-value adjustment.

Supplementary Fig. 10 The influence of size bin selection on relative deformability response to osmotic shock.

For all three methods RD was calculated for either all data, 3-μm wide cell diameter bin or 1-μm wide cell diameter bin. For the ease of comparison, the data is grouped based on binning strategy and all three methods are plotted together (a), or the data is grouped by method and all binning strategies are compared (b). The lines connect the data points representing means of medians from measurement replicates (n = 3, 4, and 4, for cDC, sDC, and xDC, respectively). Error bars present the standard deviation of the medians.

Supplementary Fig. 11 The influence of size bin selection on relative deformability response to LatB treatment.

For all three methods RD was calculated for either all data, 3-μm wide cell diameter bin or 1-μm wide cell diameter bin. For the ease of comparison, the data is grouped based on binning strategy and all three methods are plotted together (a), or the data is grouped by method and all binning strategies are compared (b). The lines connect the data points representing means of medians from measurement replicates (n = 3, 5, and 4, for cDC, sDC, and xDC, respectively). Error bars present the standard deviation of the medians.

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Urbanska, M., Muñoz, H.E., Shaw Bagnall, J. et al. A comparison of microfluidic methods for high-throughput cell deformability measurements. Nat Methods 17, 587–593 (2020). https://doi.org/10.1038/s41592-020-0818-8

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