Evidence map›Paper›PMID 35919947›Full record

ArticleThe EMBO journal2022

Gruffi: an algorithm for computational removal of stressed cells from brain organoid transcriptomic datasets.

Ábel Vértesy, Oliver L Eichmüller, Julia Naas, Maria Novatchkova, Christopher Esk, Meritxell Balmaña, Sabrina Ladstaetter, Christoph Bock, Arndt von Haeseler, Juergen A Knoblich

Abstract read
In one paragraph

Article in The EMBO journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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.

Ábel Vértesy *Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna Biocenter, Vienna, Austria.ORCID 0000-0001-6075-5702
Oliver L Eichmüller *Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna Biocenter, Vienna, Austria.ORCID 0000-0002-1077-403X
Julia NaasMax Perutz Labs, Center for Integrative Bioinformatics Vienna (CIBIV), University of Vienna, Vienna, Austria.ORCID 0000-0003-3766-0945
Maria NovatchkovaInstitute of Molecular Pathology (IMP), Vienna, Austria.
Christopher EskInstitute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna Biocenter, Vienna, Austria.
Meritxell BalmañaInstitute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna Biocenter, Vienna, Austria.
Sabrina LadstaetterCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
Christoph BockCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
Arndt von HaeselerMax Perutz Labs, Center for Integrative Bioinformatics Vienna (CIBIV), University of Vienna, Vienna, Austria.ORCID 0000-0002-3366-4458
Juergen A KnoblichInstitute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna Biocenter, Vienna, Austria.ORCID 0000-0002-6751-3404

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organoids enable in vitro modeling of complex developmental processes and disease pathologies. Like most 3D cultures, organoids lack sufficient oxygen supply and therefore experience cellular stress. These negative effects are particularly prominent in complex models, such as brain organoids, and can affect lineage commitment. Here, we analyze brain organoid and fetal single-cell RNA sequencing (scRNAseq) data from published and new datasets, totaling about 190,000 cells. We identify a unique stress signature in the data from all organoid samples, but not in fetal samples. We demonstrate that cell stress is limited to a defined subpopulation of cells that is unique to organoids and does not affect neuronal specification or maturation. We have developed a computational algorithm, Gruffi, which uses granular functional filtering to identify and remove stressed cells from any organoid scRNAseq dataset in an unbiased manner. We validated our method using six additional datasets from different organoid protocols and early brains, and show its usefulness to other organoid systems including retinal organoids. Our data show that the adverse effects of cell stress can be corrected by bioinformatic analysis for improved delineation of developmental trajectories and resemblance to in vivo data.

Indexed as

OrganoidsTranscriptomeAlgorithmsBrainComputational BiologybioinformaticsER-stresshypoxianeural developmentorganoids

Identifiers

PMID35919947
PMCPMC9433936

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.