Evidence map›Paper›PMID 38652106›Full record

ArticleeLife2024

Endogenous tagging using split mNeonGreen in human iPSCs for live imaging studies.

Mathieu C Husser, Nhat P Pham, Chris Law, Flavia R B Araujo, Vincent J J Martin, Alisa Piekny

Open access · goldAbstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. CRISPR Gene Tagging for Illuminating Endogenous Protein Dynamics.International journal of molecular sciences · 2026
    Review
  2. 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

6 authors at 1 institution in 2 countries.

Mathieu C HusserBiology Department, Concordia University, Montreal, Canada.ORCID https://orcid.org/0000-0001-6925-6440
Nhat P PhamBiology Department, Concordia University, Montreal, Canada.
Chris LawBiology Department, Concordia University, Montreal, Canada.
Flavia R B AraujoCenter for Applied Synthetic Biology, Concordia University, Montreal, Canada.
Vincent J J MartinBiology Department, Concordia University, Montreal, Canada.ORCID https://orcid.org/0000-0001-7511-115X
Alisa PieknyBiology Department, Concordia University, Montreal, Canada.ORCID https://orcid.org/0000-0002-4264-6980
Concordia University · US

Funding

Concordia University SynBioApps scholarshipFonds de recherche du Québec - Nature et technologies Doctoral Training Scholarship B2XNational Research Council Canada Disruptive Technology Solutions for Cell and Gene Therapy ChallengeNatural Sciences and Engineering Research Council of Canada Discovery GrantNatural Sciences and Engineering Research Council of Canada RGPIN-2023-04805
6 · The paper itself

Abstract

Endogenous tags have become invaluable tools to visualize and study native proteins in live cells. However, generating human cell lines carrying endogenous tags is difficult due to the low efficiency of homology-directed repair. Recently, an engineered split mNeonGreen protein was used to generate a large-scale endogenous tag library in HEK293 cells. Using split mNeonGreen for large-scale endogenous tagging in human iPSCs would open the door to studying protein function in healthy cells and across differentiated cell types. We engineered an iPS cell line to express the large fragment of the split mNeonGreen protein (mNG2

Indexed as

Induced Pluripotent Stem CellsCell LineHEK293 CellsHumanscell biologycrisprcytokinesisendogenous tagginggene editinghumanipsclive imaging

Identifiers

PMID38652106
PMCPMC11037917
OpenAlexW4388125678

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.