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Massively parallel and multiparameter titration of biochemical assays with droplet microfluidics

Nature Protocols volume 12, pages 1912–1932 (2017)Cite this article

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Abstract

Biochemical systems in which multiple components take part in a given reaction are of increasing interest. Because the interactions between these different components are complex and difficult to predict from basic reaction kinetics, it is important to test for the effect of variations in the concentration for each reagent in a combinatorial manner. For example, in PCR, an increase in the concentration of primers initially increases template amplification, but large amounts of primers result in primer–dimer by-products that inhibit the amplification of the template. Manual titration of biochemical mixtures rapidly becomes costly and laborious, forcing scientists to settle for suboptimal concentrations. Here we present a droplet-based microfluidics platform for mapping of the concentration space of up to three reaction components followed by detection with a fluorescent readout. The concentration of each reaction component is read through its internal standard (barcode), which is fluorescent but chemically orthogonal. We describe in detail the workflow, which comprises the following: (i) production of the microfluidics chips, (ii) preparation of the biochemical mixes, (iii) their mixing and compartmentalization into water-in-oil emulsion droplets via microfluidics, (iv) incubation and imaging of the fluorescent barcode and reporter signals by fluorescence microscopy and (v) image processing and data analysis. We also provide recommendations for choosing the appropriate fluorescent markers, programming the pressure profiles and analyzing the generated data. Overall, this platform allows a researcher with a few weeks of training to acquire ∼10,000 data points (in a 1D, 2D or 3D concentration space) over the course of a day from as little as 100–1,000 μl of reaction mix.

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Figure 1: A schematic of the droplet-based titration platform.
Figure 2: The layout of the microfluidic chip.
Figure 3: Scripting of the pressure profiles for a 2D experiment.
Figure 4: Fabrication outline for the droplet chamber.
Figure 5: Examples of artifacts encountered with the droplet chambers.
Figure 6: Various imaging and processing artifacts.

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Acknowledgements

We thank S. Nishikawa and K. Montagne for kindly proofreading the manuscript. Y.R. acknowledges support from the Japan Society for the Promotion of Science (JSPS) through a Grant-in-Aid for Scientific Research on Innovative Areas 'Synthetic Biology for Comprehension of Biomolecular Networks' (project number 23119001). A.J.G. acknowledges support from the ANR (ANR-13-PDOC-0001) and the JSPS (postdoctoral fellowship). J.-F.B. was supported by a PhD fellowship from Region Alsace. N.B. acknowledges support from the PHC Sakura program (project number 34171WG). A.B. and N.A.-K. were supported by the ELSI Origins Network (EON), which is supported by a grant from the John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation.

Author information

Author notes

  1. Alexandre Baccouche and Shu Okumura: These authors contributed equally to this work.

Authors and Affiliations

  1. LIMMS, CNRS–Institute of Industrial Science, UMI 2820, The University of Tokyo, Tokyo, Japan

    Alexandre Baccouche, Shu Okumura, Rémi Sieskind, Elia Henry, Yannick Rondelez, Teruo Fujii & Anthony J Genot

  2. Earth Life Science Institute, Tokyo Institute of Technology, Tokyo, Japan

    Alexandre Baccouche & Nathanaël Aubert-Kato

  3. CIBIS, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

    Shu Okumura & Teruo Fujii

  4. Laboratoire Gulliver, CNRS, ESPCI Paris, PSL Research University, Paris, France

    Rémi Sieskind, Elia Henry & Yannick Rondelez

  5. Department of Information Science, Ochanomizu University, Tokyo, Japan

    Nathanaël Aubert-Kato

  6. Sorbonne Universités, UPMC Univ. Paris 06, CNRS, Institute of Intelligent Systems and Robotics (ISIR), Paris, France

    Nathanaël Aubert-Kato & Nicolas Bredeche

  7. LCAMB, UMR 7199, CNRS/Université de Strasbourg, Illkirch, France

    Jean-François Bartolo

  8. INSERM UMR-S1147, CNRS SNC5014, Paris Descartes University, Equipe labellisée Ligue Nationale Contre le Cancer, Paris, France

    Valérie Taly

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Contributions

All authors contributed to the development of the method. A.B., S.O., R.S., E.H. and A.J.G. performed the experiments. N.B., N.A.-K., Y.R. and A.J.G. analyzed the data. J.-F.B. and V.T. synthesized the surfactant. T.F. and V.T. provided support with the microfluidic platform. All authors contributed to the writing of the manuscript.

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Correspondence to Anthony J Genot.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Data 1

An SU-8 master mold of the chip array (ZIP file). (ZIP 507 kb)

Supplementary Data 2

Pressure scripts (ZIP file). (ZIP 70 kb)

Supplementary Data 3

MATLAB script (TXT file). (TXT 4 kb)

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Baccouche, A., Okumura, S., Sieskind, R. et al. Massively parallel and multiparameter titration of biochemical assays with droplet microfluidics. Nat Protoc 12, 1912–1932 (2017). https://doi.org/10.1038/nprot.2017.092

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