Evidence map›Paper›PMID 35074872›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs).

Justin L Madrigal, Nathan G Schoepp, Linfeng Xu, Codian S Powell, Cyrille L Delley, Christian A Siltanen, Jay Danao, Maithreyan Srinivasan, Russell H Cole, Adam R Abate

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.2field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 54 citations in OpenAlex.

  1. Review
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  11. Long and Accurate: How HiFi Sequencing is Transforming Genomics.Genomics, proteomics & bioinformatics · 2025
    Review
  12. Single Cell-Pair Proteomics for Decoding Immune-Cancer Cell Interactions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  13. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Justin L MadrigalScribe Biosciences, San Francisco, CA 94107.ORCID 0000-0003-2041-1192
Nathan G SchoeppScribe Biosciences, San Francisco, CA 94107.ORCID 0000-0002-2406-3693
Linfeng XuDepartment of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA 94158.ORCID 0000-0002-6386-1815
Codian S PowellScribe Biosciences, San Francisco, CA 94107.
Cyrille L DelleyDepartment of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA 94158.ORCID 0000-0002-3599-5701
Christian A SiltanenScribe Biosciences, San Francisco, CA 94107.
Jay DanaoChimera Bioengineering, South San Francisco, CA 94080.
Maithreyan SrinivasanScribe Biosciences, San Francisco, CA 94107.
Russell H ColeScribe Biosciences, San Francisco, CA 94107; russell.cole@scribebiosciences.com arabate@gmail.com.
Adam R AbateDepartment of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA 94158; russell.cole@scribebiosciences.com arabate@gmail.com.
Scribe Biosciences (United States) · USQB3 · US

Funding

A platform for integrating cell signaling and single cell transcriptomics.R43HG010592 · NHGRI · SCRIBE BIOSCIENCES, INC. · PI SRINIVASAN, MAITHREYAN · 2019 to 2019
$350k
A platform for coupling chromatin profiling with single cell transcriptomicsR43HG010128 · NHGRI · SCRIBE BIOSCIENCES, INC. · PI COLE, RUSSELL H · 2018 to 2018
$280k
NHGRI NIH HHS R43 HG010128NHGRI NIH HHS R43 HG010592
6 · The paper itself

Abstract

Cell-cell interactions are important to numerous biological systems, including tissue microenvironments, the immune system, and cancer. However, current methods for studying cell combinations and interactions are limited in scalability, allowing just hundreds to thousands of multicell assays per experiment; this limited throughput makes it difficult to characterize interactions at biologically relevant scales. Here, we describe a paradigm in cell interaction profiling that allows accurate grouping of cells and characterization of their interactions for tens to hundreds of thousands of combinations. Our approach leverages high-throughput droplet microfluidics to construct multicellular combinations in a deterministic process that allows inclusion of programmed reagent mixtures and beads. The combination droplets are compatible with common manipulation and measurement techniques, including imaging, barcode-based genomics, and sorting. We demonstrate the approach by using it to enrich for chimeric antigen receptor (CAR)-T cells that activate upon incubation with target cells, a bottleneck in the therapeutic T cell engineering pipeline. The speed and control of our approach should enable valuable cell interaction studies.

Indexed as

AnimalsBiological AssayCell CommunicationGenomicsHumansMicrofluidic Analytical TechniquesMicrofluidicscell–cell interactioncell therapydroplet microfluidicsfunctional sortingsingle-cell analysis

Identifiers

PMID35074872
PMCPMC8812558
OpenAlexW4206972328

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.