Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets

L. Mathur, B. Szalai, N. H. Du, R. Utharala, M. Ballinger, J. J. M. Landry, M. Ryckelynck, V. Benes, J. Saez-Rodriguez () and C. A. Merten ()
Additional contact information
L. Mathur: European Molecular Biology Laboratory (EMBL)
B. Szalai: Semmelweis University
N. H. Du: École Polytechnique Fédérale de Lausanne (EPFL)
R. Utharala: European Molecular Biology Laboratory (EMBL)
M. Ballinger: European Molecular Biology Laboratory (EMBL)
J. J. M. Landry: European Molecular Biology Laboratory (EMBL)
M. Ryckelynck: Université de Strasbourg, CNRS, Architecture et Réactivité de l’ARN, UPR
V. Benes: European Molecular Biology Laboratory (EMBL)
J. Saez-Rodriguez: Faculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Heidelberg University
C. A. Merten: European Molecular Biology Laboratory (EMBL)

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract Anti-cancer therapies often exhibit only short-term effects. Tumors typically develop drug resistance causing relapses that might be tackled with drug combinations. Identification of the right combination is challenging and would benefit from high-content, high-throughput combinatorial screens directly on patient biopsies. However, such screens require a large amount of material, normally not available from patients. To address these challenges, we present a scalable microfluidic workflow, called Combi-Seq, to screen hundreds of drug combinations in picoliter-size droplets using transcriptome changes as a readout for drug effects. We devise a deterministic combinatorial DNA barcoding approach to encode treatment conditions, enabling the gene expression-based readout of drug effects in a highly multiplexed fashion. We apply Combi-Seq to screen the effect of 420 drug combinations on the transcriptome of K562 cells using only ~250 single cell droplets per condition, to successfully predict synergistic and antagonistic drug pairs, as well as their pathway activities.

Date: 2022
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DOI: 10.1038/s41467-022-32197-0

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