spinDrop: a droplet microfluidic platform to maximise single-cell sequencing information content.
Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack of strategies to enrich for high-quality material or specific cell types at the moment of cell encapsulation and the absence of implementable multi-step enzymatic processes that increase capture. Here we alleviate both bottlenecks using fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei, fixed cells or target cell types and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half. We harness these properties to deliver a high-quality molecular atlas of mouse brain development, despite starting with highly damaged input material, and provide an atlas of nascent RNA transcription during mouse organogenesis. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.
Acknowledgements: J.D.J. received scholarship support from the BBSRC, T.S.K. was supported by EU H2020 Marie Skłodowska-Curie Individual Fellowship (MSCA-IF 750772), A.L.E. was supported by the Cambridge Trusts and the EU H2020 Marie Curie ITN MMBio and T.N.K. by an AstraZeneca studentship. M.T. was supported by the International Centre for Translational Eye Research (MAB/2019/12) project, which was carried out within the International Research Agendas programme of the Foundation for Polish Science, co-financed by the European Union under the European Regional Development Fund. This work was supported by the EU Horizon 2020 programme (ERC Advanced Investigator Awards to F.H., 69566 and M.Z.G., 669198), the Wellcome Trust (WT108438/C/15/Z to F.H. and 207415/Z/17/Z to M.Z.G.) and the NIH (Pioneer Award to M.Z.G., DP1 HD104575-01). The authors would like to thank the members of the Hollfelder laboratory for their feedback. We thank Dr. Anna Alemany for help and suggestions for the data analysis.
Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (750772)
Wellcome Trust (108438/C/15/Z)
Wellcome Trust (108438/E/15/Z)
European Research Council (669198)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (721613)
Wellcome Trust (207415/Z/17/Z)