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Updated: Sep 2, 2025
Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells
Published on: January 7, 2020
Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in
L Mathur1,2, B Szalai3,4,5, N H Du6
1Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
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.
Insights
This study introduces Combi-Seq, a microfluidic method for screening numerous anti-cancer drug combinations using single-cell transcriptomics. It efficiently identifies effective drug pairings and pathway activities from minimal patient samples.
Area of Science:
- Oncology
- Genomics
- Bioengineering
Background:
- Anti-cancer therapies often have limited efficacy due to acquired drug resistance, leading to tumor relapse.
- Drug combinations offer a promising strategy to overcome resistance, but identifying optimal combinations is complex.
- Current high-throughput screening methods require substantial biological material, often unavailable from patient biopsies.
Purpose of the Study:
- To develop a scalable microfluidic workflow, Combi-Seq, for high-throughput screening of drug combinations.
- To utilize single-cell transcriptome changes as a readout for drug effects.
- To enable drug combination screening using limited patient-derived samples.
Main Methods:
- A microfluidic system was designed to screen hundreds of drug combinations in picoliter droplets.
- A deterministic combinatorial DNA barcoding method was developed to encode treatment conditions.
- Single-cell RNA sequencing was employed to analyze transcriptome-wide gene expression changes.
Main Results:
- Combi-Seq successfully screened 420 drug combinations using approximately 250 single-cell droplets per condition.
- The workflow accurately predicted synergistic and antagonistic drug pairs.
- Pathway activities influenced by drug combinations were identified.
Conclusions:
- Combi-Seq provides a scalable and material-efficient approach for drug combination screening.
- This method enables gene expression-based analysis of drug effects in a highly multiplexed manner.
- Combi-Seq has the potential to accelerate the discovery of effective combination therapies for cancer treatment.
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