Evidence map›Paper›PMID 35165449›Full record

ArticleNature methods2022

Deterministic scRNA-seq captures variation in intestinal crypt and organoid composition.

Johannes Bues, Marjan Biočanin, Joern Pezoldt, Riccardo Dainese, Antonius Chrisnandy, Saba Rezakhani, Wouter Saelens, Vincent Gardeux, Revant Gupta, Rita Sarkis and 6 more

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
5.6field-weighted citation impact, top 3% 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

30 citing papers in PubMed, 70 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 3 countries.

Johannes Bues *Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Marjan Biočanin *Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Joern Pezoldt *Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0001-7143-5691
Riccardo DaineseLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Antonius ChrisnandyLaboratory for Stem Cell Bioengineering, Institute of Bioengineering, School of Life Sciences École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-3851-4870
Saba RezakhaniLaboratory for Stem Cell Bioengineering, Institute of Bioengineering, School of Life Sciences École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Wouter SaelensLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Vincent GardeuxLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0001-8954-2161
Revant GuptaInternal Medicine I, University Hospital Tübingen, Faculty of Medicine, University of Tübingen, Tübingen, Germany.ORCID http://orcid.org/0000-0002-0881-5074
Rita SarkisLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0003-4874-9937
Julie RusseilLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-0880-9483
Yvan SaeysData Mining and Modelling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium.
Esther AmstadSoft Materials Laboratory, Institute of Materials, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Manfred ClaassenInternal Medicine I, University Hospital Tübingen, Faculty of Medicine, University of Tübingen, Tübingen, Germany.
Matthias P LutolfLaboratory for Stem Cell Bioengineering, Institute of Bioengineering, School of Life Sciences École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-5898-305X
Bart DeplanckeLaboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. bart.deplancke@epfl.ch.ORCID http://orcid.org/0000-0001-9935-843X
SIB Swiss Institute of Bioinformatics · CHÉcole Polytechnique Fédérale de Lausanne · CHUniversity Children's Hospital Tübingen · DEGhent University · BERoche (Switzerland) · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) approaches have transformed our ability to resolve cellular properties across systems, but are currently tailored toward large cell inputs (>1,000 cells). This renders them inefficient and costly when processing small, individual tissue samples, a problem that tends to be resolved by loading bulk samples, yielding confounded mosaic cell population read-outs. Here, we developed a deterministic, mRNA-capture bead and cell co-encapsulation dropleting system, DisCo, aimed at processing low-input samples (<500 cells). We demonstrate that DisCo enables precise particle and cell positioning and droplet sorting control through combined machine-vision and multilayer microfluidics, enabling continuous processing of low-input single-cell suspensions at high capture efficiency (>70%) and at speeds up to 350 cells per hour. To underscore DisCo's unique capabilities, we analyzed 31 individual intestinal organoids at varying developmental stages. This revealed extensive organoid heterogeneity, identifying distinct subtypes including a regenerative fetal-like Ly6a

Indexed as

OrganoidsSingle-Cell AnalysisAnimalsCell DifferentiationIntestinal MucosaMiceStem Cells

Identifiers

PMID35165449
OpenAlexW4212799764

What OpenQuestion holds

Textmetadata
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.