Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Design and construction of a microfluidics workstation for high-throughput multi-wavelength fluorescence and transmittance activated droplet analysis and sorting

Abstract

Droplet microfluidics has revolutionized quantitative high-throughput bioassays and screening, especially in the field of single-cell analysis where applications include cell characterization, antibody discovery and directed evolution. However, droplet microfluidic platforms capable of phenotypic, fluorescence-based readouts and sorting are still mostly found in specialized labs, because their setup is complex. Complementary to conventional FACS, microfluidic droplet sorters allow the screening of cell libraries for secreted factors, or even for the effects of secreted or surface-displayed factors on a second cell type. Furthermore, they also enable PCR-activated droplet sorting for the isolation of genetic material harboring specific markers. In this protocol, we provide a detailed step-by-step guide for the construction of a high-throughput droplet analyzer and sorter, which can be accomplished in ~45 working hours by nonspecialists. The resulting instrument is equipped with three lasers to excite the fluorophores in droplets and photosensors that acquire fluorescence signals in the blue (425–465 nm), green (505–545 nm) and red (580–630 nm) spectrum. This instrument also allows transmittance-activated droplet sorting by analyzing the brightfield light intensity transmitting through the droplets. The setup is validated by sorting droplets containing fluorescent beads at 200 Hz with 99.4% accuracy. We show results from an experiment where droplets hosting single cells were sorted on the basis of increased matrix metalloprotease activity as an application of our workstation in single-cell molecular biology, e.g., to analyze molecular determinants of cancer metastasis.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Workstation overview.
Fig. 2: Ray diagram.
Fig. 3: Droplet lensing.
Fig. 4: Droplet sorting chip.
Fig. 5: Breadboard layout.
Fig. 6: Filter holder assembly.
Fig. 7: Dichroic mirror assembly.
Fig. 8: PMT mount assembly.
Fig. 9: Electrical and data connections for the PMTs.
Fig. 10: FPGA connections.
Fig. 11: High-voltage amplifier connections and grounding.
Fig. 12: Emission light alignment.
Fig. 13: Laser alignment.
Fig. 14: Workstation setup validation.
Fig. 15: Droplet sorting initialization.
Fig. 16: Transmittance and fluorescence signals.
Fig. 17: Fluorescent beads sorting experiment.
Fig. 18: Single-cell enzymatic droplet assay and sorting experiment.

Similar content being viewed by others

Data availability

The custom-made software for droplet analysis and sorting is provided in Supplementary Software 1 and 2 and can also be checked for updates at www.epfl.ch/labs/lbmm/downloads/ or at https://doi.org/10.5281/zenodo.6399980. The design files for all the machined parts, 3D printed parts and microfluidic chips are provided in Supplementary Data 110 or at https://doi.org/10.5281/zenodo.6399971. Numeric data for all the experiments are in Source Data Figs. 1618 and Supplementary Data 11. Raw data can be found at https://doi.org/10.5281/zenodo.6392149. Source data are provided with this paper.

References

  1. Papalexi, E. & Satija, R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat. Rev. Immunol. 18, 35–45 (2018).

    Article  CAS  PubMed  Google Scholar 

  2. Zhang, X. et al. Comparative analysis of droplet-based ultra-high-throughput single-cell RNA-seq systems. Mol. Cell 73, 130–142.e5 (2019).

    Article  PubMed  Google Scholar 

  3. Matuła, K., Rivello, F. & Huck, W. T. S. Single-cell analysis using droplet microfluidics. Adv. Biosyst. 4, 1900188 (2020).

  4. Leman, M., Abouakil, F., Griffiths, A. D. & Tabeling, P. Droplet-based microfluidics at the femtolitre scale. Lab Chip 15, 753–765 (2015).

    Article  CAS  PubMed  Google Scholar 

  5. Collins, D. J., Neild, A., deMello, A., Liu, A. Q. & Ai, Y. The Poisson distribution and beyond: methods for microfluidic droplet production and single cell encapsulation. Lab Chip 15, 3439–3459 (2015).

    Article  CAS  PubMed  Google Scholar 

  6. Shembekar, N., Chaipan, C., Utharala, R. & Merten, C. A. Droplet-based microfluidics in drug discovery, transcriptomics and high-throughput molecular genetics. Lab Chip 16, 1314–1331 (2016).

    Article  CAS  PubMed  Google Scholar 

  7. Seah, Y. F. S., Hu, H. & Merten, C. A. Microfluidic single-cell technology in immunology and antibody screening. Mol. Asp. Med. 59, 47–61 (2018).

    Article  CAS  Google Scholar 

  8. El Debs, B., Utharala, R., Balyasnikova, I. V., Griffiths, A. D. & Merten, C. A. Functional single-cell hybridoma screening using droplet-based microfluidics. Proc. Natl Acad. Sci. USA 109, 11570–11575 (2012).

    Article  CAS  PubMed  Google Scholar 

  9. Hu, H., Eustace, D. & Merten, C. A. Efficient cell pairing in droplets using dual-color sorting. Lab Chip 15, 3989–3993 (2015).

    Article  CAS  PubMed  Google Scholar 

  10. Shembekar, N., Hu, H., Eustace, D. & Merten, C. A. Single-cell droplet microfluidic screening for antibodies specifically binding to target cells. Cell Rep. 22, 2206–2215 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Gérard, A. et al. High-throughput single-cell activity-based screening and sequencing of antibodies using droplet microfluidics. Nat. Biotechnol. 38, 715–721 (2020).

    Article  PubMed  Google Scholar 

  12. Wang, Y. et al. High-throughput functional screening for next-generation cancer immunotherapy using droplet-based microfluidics. Sci. Adv. 7, eabe3839 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Chokkalingam, V. et al. Probing cellular heterogeneity in cytokine-secreting immune cells using droplet-based microfluidics. Lab Chip 13, 4740–4744 (2013).

    Article  CAS  PubMed  Google Scholar 

  14. Obexer, R. et al. Emergence of a catalytic tetrad during evolution of a highly active artificial aldolase. Nat. Chem. 9, 50–56 (2017).

    Article  CAS  PubMed  Google Scholar 

  15. Autour, A. et al. Fluorogenic RNA Mango aptamers for imaging small non-coding RNAs in mammalian cells. Nat. Commun. 9, 656 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Bouhedda, F. et al. A dimerization-based fluorogenic dye-aptamer module for RNA imaging in live cells. Nat. Chem. Biol. 16, 69–76 (2020).

    Article  CAS  PubMed  Google Scholar 

  17. Lim, S. W., Tran, T. M. & Abate, A. R. PCR-activated cell sorting for cultivation-free enrichment and sequencing of rare microbes. PLoS ONE 10, 1–16 (2015).

    Google Scholar 

  18. Pryszlak, A. et al. Enrichment of gut microbiome strains for cultivation-free genome sequencing using droplet microfluidics. Cell Rep. Methods 2, 100137 (2022).

    Article  CAS  PubMed  Google Scholar 

  19. Colin, P. Y. et al. Ultrahigh-throughput discovery of promiscuous enzymes by picodroplet functional metagenomics. Nat. Commun. 6, 10008 (2015).

  20. Zhu, Y. & Fang, Q. Analytical detection techniques for droplet microfluidics—a review. Anal. Chim. Acta 787, 24–35 (2013).

    Article  CAS  PubMed  Google Scholar 

  21. Xi, H. D. et al. Active droplet sorting in microfluidics: a review. Lab Chip 17, 751–771 (2017).

    Article  CAS  PubMed  Google Scholar 

  22. Mazutis, L. et al. Single-cell analysis and sorting using droplet-based microfluidics. Nat. Protoc. 8, 870–891 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Ryckelynck, M. et al. Using droplet-based microfluidics to improve the catalytic properties of RNA under multiple-turnover conditions. RNA 21, 458–469 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gielen, F. et al. Ultrahigh-throughput-directed enzyme evolution by absorbance-activated droplet sorting (AADS). Proc. Natl Acad. Sci. USA 113, E7383–E7389 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Siltanen, C. A. et al. An oil-free picodrop bioassay platform for synthetic biology. Sci. Rep. 8, 1–7 (2018).

    Article  CAS  Google Scholar 

  26. Herzenberg, L. A., Sweet, R. G. & Herzenberg, L. A. Fluorescence-activated cell sorting. Sci. Am. 234, 108–117 (1976).

    Article  CAS  PubMed  Google Scholar 

  27. Piyasena, M. E. & Graves, S. W. The intersection of flow cytometry with microfluidics and microfabrication. Lab Chip 14, 1044–1059 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Zinchenko, A. et al. One in a million: flow cytometric sorting of single cell-lysate assays in monodisperse picolitre double emulsion droplets for directed evolution. Anal. Chem. 86, 2526–2533 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zhu, Z. & Yang, C. J. Hydrogel droplet microfluidics for high-throughput single molecule/cell analysis. Acc. Chem. Res. 50, 22–31 (2017).

    Article  CAS  PubMed  Google Scholar 

  30. Fischlechner, M. et al. Evolution of enzyme catalysts caged in biomimetic gel-shell beads. Nat. Chem. 6, 791–796 (2014).

    Article  CAS  PubMed  Google Scholar 

  31. Lim, S. W. & Abate, A. R. Ultrahigh-throughput sorting of microfluidic drops with flow cytometry. Lab Chip 13, 4563–4572 (2013).

    Article  CAS  PubMed  Google Scholar 

  32. Akbari, S. & Pirbodaghi, T. A droplet-based heterogeneous immunoassay for screening single cells secreting antigen-specific antibodies. Lab Chip 14, 3275–3280 (2014).

    Article  CAS  PubMed  Google Scholar 

  33. Josephides, D. et al. Cyto-Mine: an integrated, picodroplet system for high-throughput single-cell analysis, sorting, dispensing, and monoclonality assurance. SLAS Technol. 25, 177–189 (2020).

    Article  PubMed  Google Scholar 

  34. Yang, T., Stavrakis, S. & DeMello, A. A high-sensitivity, integrated absorbance and fluorescence detection scheme for probing picoliter-volume droplets in segmented flows. Anal. Chem. 89, 12880–12887 (2017).

    Article  CAS  PubMed  Google Scholar 

  35. Baret, J.-C. et al. Fluorescence-activated droplet sorting (FADS): efficient microfluidic cell sorting based on enzymatic activity. Lab Chip 9, 1850–1858 (2009).

    Article  CAS  PubMed  Google Scholar 

  36. Gruner, P. et al. Controlling molecular transport in minimal emulsions. Nat. Commun. 7, 10392 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Vermeir, L. et al. Effect of molecular exchange on water droplet size analysis as determined by diffusion NMR: the W/O/W double emulsion case. J. Colloid Interface Sci. 475, 57–65 (2016).

    Article  CAS  PubMed  Google Scholar 

  38. Skhiri, Y. et al. Dynamics of molecular transport by surfactants in emulsions. Soft Matter 8, 10618–10627 (2012).

    Article  CAS  Google Scholar 

  39. Baret, J.-C. C. Surfactants in droplet-based microfluidics. Lab Chip 12, 422–433 (2012).

    Article  CAS  PubMed  Google Scholar 

  40. Arppe, R., Carro-Temboury, M. R., Hempel, C., Vosch, T. & Sørensen, T. J. Investigating dye performance and crosstalk in fluorescence enabled bioimaging using a model system. PLoS ONE 12, 1–17 (2017).

    Article  Google Scholar 

  41. Waters, J. C. Accuracy and precision in quantitative fluorescence microscopy. J. Cell Biol. 185, 1135–1148 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Schütz, S. S., Beneyton, T., Baret, J. C. & Schneider, T. M. Rational design of a high-throughput droplet sorter. Lab Chip 19, 2220–2232 (2019).

    Article  PubMed  Google Scholar 

  43. Kim, M.-S. et al. Refraction limit of miniaturized optical systems: a ball-lens example. Opt. Express 24, 6996–7005 (2016).

    Article  CAS  PubMed  Google Scholar 

  44. Sciambi, A. & Abate, A. R. Accurate microfluidic sorting of droplets at 30 kHz. Lab Chip 15, 47–51 (2014).

    Article  Google Scholar 

  45. Clark, I. C., Thakur, R. & Abate, A. R. Concentric electrodes improve microfluidic droplet sorting. Lab Chip 18, 710–713 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Pohl, H. A. Some effects of nonuniform fields on dielectrics. J. Appl. Phys. 29, 1182–1188 (1958).

    Article  Google Scholar 

  47. Srisa-Art, M., deMello, A. J. & Edel, J. B. High-throughput DNA droplet assays using picoliter reactor volumes. Anal. Chem. 79, 6682–6689 (2007).

    Article  CAS  PubMed  Google Scholar 

  48. Li, Z., Yi Mak, S., Sauret, A. & Cheung Shum, H. Syringe-pump-induced fluctuation in all-aqueous microfluidic system implications for flow rate accuracy. Lab Chip 14, 744–749 (2014).

    Article  CAS  PubMed  Google Scholar 

  49. Dressaire, E. & Sauret, A. Clogging of microfluidic systems. Soft Matter 13, 37–48 (2017).

    Article  CAS  Google Scholar 

  50. Birkedal-Hansen, H. et al. Matrix metalloproteinases: a review. Crit. Rev. Oral. Biol. Med. 4, 197–250 (1993).

    Article  CAS  PubMed  Google Scholar 

  51. Bourboulia, D. & Stetler-Stevenson, W. G. Matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs): positive and negative regulators in tumor cell adhesion. Semin. Cancer Biol. 20, 161–168 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Stanton, H. et al. The activation of ProMMP-2 (gelatinase A) by HT1080 fibrosarcoma cells is promoted by culture on a fibronectin substrate and is concomitant with an increase in processing of MT1-MMP (MMP-14) to a 45 kDa form. J. Cell Sci. 111, 2789–2798 (1998).

    Article  CAS  PubMed  Google Scholar 

  53. Schröpfer, A. et al. Expression pattern of matrix metalloproteinases in human gynecological cancer cell lines. BMC Cancer 10, 553 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Singh, P. & Aubry, N. Transport and deformation of droplets in a microdevice using dielectrophoresis. Electrophoresis 28, 644–657 (2007).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Parts of this work were supported by DFG-Grant ME 3536/9-1 and the DFG-funded part of the transnational JPIAMR Grant 01KI1822 (‘DISRUPT’).

Author information

Authors and Affiliations

Authors

Contributions

C.A.M. conceived the project and supervised the experimental work. J.P. and A.A. introduced the transmittance-based sorting mode. J.P. wrote the LabVIEW code for droplet sorting software. A.A. performed all cell-based assays. All authors contributed to the writing of the manuscript.

Corresponding author

Correspondence to Christoph A. Merten.

Ethics declarations

Competing interests

C.A.M. is a cofounder of Veraxa Biotech and head of the TheraMe! consortium, both exploiting droplet microfluidic technology. However, the instrument described in this protocol is not offered commercially by any of these two entities.

Peer review

Peer review information

Nature Protocols thanks Han Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key references using this protocol

El Debs, B. et al. Proc. Natl Acad. Sci. USA 109, 11570–11575 (2012): https://doi.org/10.1073/pnas.1204514109

Shembekar, N. et al. Cell Rep. 22, 2206–2215 (2018): https://doi.org/10.1016/j.celrep.2018.01.071

Hu, H. et al. Lab Chip 15, 3989–3993 (2015): https://doi.org/10.1039/C5LC00686D

Extended data

Extended Data Fig. 1 Support blocks for breadboard mounting.

Silicone stoppers (red circle) placed on the host bench to provide support and passive vibration isolation to the breadboard. The relative distance between the silicone stoppers ensure their alignment to the four corners of the breadboard.

Extended Data Fig. 2 Map with screw coordinates.

Map depicting the coordinates for the screw positions to be marked before the breadboard assembly as per Fig. 5. The coordinate system has the origin at the left bottom side of the breadboard with a distance of 1 hole from the left edge. The screw positions follow the coordinates described in Table 2. As example, some screw coordinated are labelled.

Extended Data Fig. 3 Rail mounting on rail support blocks.

a) Essential pieces to assemble a small rail (e.g. rail A to E) on a rail support block. The black arrows point to the corresponding holes for the two M6 screws. Note that prior to mounting rails on the blocks, the block should already be screwed on the breadboard at its position as per Fig. 5.) through the depicted holes for breadboard b) Top view of the assembly. c) Side view of the assembly. The two screws allow to attach the rail to the block.

Extended Data Fig. 4 Wire crimping.

a) Power cable for PMT power supply with its rear end cut and stripped along with crimp ferrules and pliers for wire crimping. *The wall socket plug is country specific. b) Pliers crimping the wire with a crimp ferrule on its stripped end. c) Crimped wires of the power supply depicting neutral, live and ground wires (note that the color convention is country specific). d) Crimped end of the high-voltage amplifier’s trigger cable. The crimped wires will be connected to FPGA in later steps (57-59).

Extended Data Fig. 5 PMT wires.

The wires coming out of the PMT are assigned their function and pin number (in brackets) of the eight-pin connector. The cladding and core wire of the thick black cable are shown in zoom.

Extended Data Fig. 6 Projection from microscope’s side port.

Projection of the microfluidic chip’s image on a white sheet of paper, held close to the focal plane of the objective lens near the (left) side port of the microscope.

Extended Data Fig. 7 Alignment line.

The alignment line centred on the camera window using gridlines. The alignment line here is made by flowing molten Indium alloy into a straight (100 micron wide) microfluidic channel to achieve a good contrast between the line and the background. The projection of this alignment line is used for emission light alignment. The essential buttons in “MotionBLITZdirector2” software are highlighted in the picture.

Extended Data Fig. 8 Microscope fixing on the breadboard.

Microscope fixed at its position on the breadboard using clamping forks after the emission light alignment process.

Extended Data Fig. 9 Camera software controls.

Camera settings for the MotionBLITZdirector2 software to change the frame rate and for inserting a mark for alignment process on the camera window.

Extended Data Fig. 10 Brightfield filter positioning.

a) The full microscope is shown with the condenser for the brightfield lamp, located above of the microscope stage (orange box). b) A 561 nm longpass filter on a 25mm filter holder is placed over the condenser. This filter only allows the wavelengths that are not detected by any PMT to pass, enabling imaging by camera while simultaneously measuring fluorescence signals.

Supplementary information

Supplementary Information

Supplementary Figs. 1–9.

Reporting Summary

Supplementary Video 1

Animated video demonstrating breadboard assembly (Steps 1–68 of protocol).

Supplementary Video 2

Animated video demonstrating emission light alignment process (Steps 69–89 of protocol).

Supplementary Video 3

Animated video demonstrating laser alignment process (Steps 90–131 of protocol).

Supplementary Video 4

Video demonstrating how to operate TFADS software for droplet sorting.

Supplementary Video 5

Video showing all the droplets in the microfluidic channel are going to the waste channel. This is expected to be the state of the system before starting the sorting operation.

Supplementary Video 6

Video showing effect of high-voltage amplitude on droplets during a sorting operation. The effects of 0.2 kV, 0.6 kV, 0.9 kV and 1.2 kV are shown.

Supplementary Video 7

Every third droplet going to collection channel when test ratio is 1 in 3. This shows that the high-voltage parameters are optimum and the system is ready for droplet sorting.

Supplementary Video 8

Sorting of a droplet that contains a blue fluorescent bead as discussed in Fig. 17.

Supplementary Video 9

Encapsulation of HeLa cells and HT-1080 cells in droplets using the microfluidic chip for droplet generating.

Supplementary Video 10

Reinjection of droplets into the droplet sorting chip after the off-chip incubation.

Supplementary Video 11

Sorting of a droplet with green fluorescence containing HT-1080 cells as discussed in Fig. 18.

Supplementary Software 1

LabVIEW software for Transmittance and Fluorescence Activated Droplet Sorting (TFADS).

Supplementary Software 2

LabVIEW software for Transmittance and Fluorescence Activated Droplet Sorting (TFADS) with additional four PMT channels.

Supplementary Data 1

Design files for rail clamp modification.

Supplementary Data 2

Design files for filter holder modification.

Supplementary Data 3

CAD for rail support block.

Supplementary Data 4

CAD files for laser support block (M and FN series).

Supplementary Data 5

CAD files for PMT mount.

Supplementary Data 6

CAD files for black box parts.

Supplementary Data 7

STL files for 3D printing of target disk.

Supplementary Data 8

STL files for 3D printing of aperture disk.

Supplementary Data 9

STL files for 3D printing of filter rim.

Supplementary Data 10

CAD files for microfluidic chip fabrication (alignment line, droplet sorting chip and droplet generation chip).

Supplementary Data 11

Numeric data for Supplementary Fig. 6.

Source data

Source Data Fig. 16

Numeric data for comparison of transmittance and fluorescence signals and for transmittance signals gathered at different concentrations of trypan blue.

Source Data Fig. 17

Numeric data for fluorescent bead sorting experiment.

Source Data Fig. 18

Numeric data for single-cell enzymatic droplet assay and sorting experiment.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Panwar, J., Autour, A. & Merten, C.A. Design and construction of a microfluidics workstation for high-throughput multi-wavelength fluorescence and transmittance activated droplet analysis and sorting. Nat Protoc 18, 1090–1136 (2023). https://doi.org/10.1038/s41596-022-00796-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41596-022-00796-2

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer