Evidence map›Paper›PMID 38982158›Full record

ArticleNature biomedical engineering2024

Sensing and guiding cell-state transitions by using genetically encoded endoribonuclease-mediated microRNA sensors.

Lei Wang, Wenlong Xu, Shun Zhang, Gregory C Gundberg, Christine R Zheng, Zhengpeng Wan, Kamila Mustafina, Fabio Caliendo, Hayden Sandt, Roger Kamm and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature biomedical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Reversing transgene silencing via targeted chromatin editing.bioRxiv : the preprint server for biology · 2025
    Article
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  10. Article
  11. Article
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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

11 authors.

Lei WangDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. lei1.wang@northeastern.edu.ORCID http://orcid.org/0000-0001-5218-556X
Wenlong XuDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-2906-4724
Shun ZhangDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-5831-7148
Gregory C GundbergDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0009-0004-3257-7768
Christine R ZhengDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-7809-2932
Zhengpeng WanDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-5626-7722
Kamila MustafinaDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-3973-7208
Fabio CaliendoDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-5676-6000
Hayden SandtDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0009-0009-2195-232X
Roger KammDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-7232-304X
Ron WeissDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. rweiss@mit.edu.ORCID http://orcid.org/0000-0003-0396-2443

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precisely sensing and guiding cell-state transitions via the conditional genetic activation of appropriate differentiation factors is challenging. Here we show that desired cell-state transitions can be guided via genetically encoded sensors, whereby endogenous cell-state-specific miRNAs regulate the translation of a constitutively transcribed endoribonuclease, which, in turn, controls the translation of a gene of interest. We used this approach to monitor several cell-state transitions, to enrich specific cell types and to automatically guide the multistep differentiation of human induced pluripotent stem cells towards a haematopoietic lineage via endothelial cells as an intermediate state. Such conditional activation of gene expression is durable and resistant to epigenetic silencing and could facilitate the monitoring of cell-state transitions in physiological and pathological conditions and eventually the 'rewiring' of cell-state transitions for applications in organoid-based disease modelling, cellular therapies and regenerative medicine.

Indexed as

Cell DifferentiationEndoribonucleasesInduced Pluripotent Stem CellsMicroRNAsBiosensing TechniquesEndothelial CellsHumansEndoribonucleasesMicroRNAs

Identifiers

PMID38982158

What OpenQuestion holds

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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.