Evidence map›Paper›PMID 38461201›Full record

ArticleScientific reports2024

Synthetic receptor scaffolds significantly affect the efficiency of cell fate signals.

Kirato Umene, Masahiro Kawahara

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 97% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Review
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

2 authors at 1 institution in 1 country.

Kirato UmeneDepartment of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8656, Japan.
Masahiro KawaharaDepartment of Chemistry and Biotechnology, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8656, Japan. m-kawahara@nibiohn.go.jp.
The University of Tokyo · JP

Funding

Japan Society for the Promotion of Science 21H01735, 23K17854
6 · The paper itself

Abstract

Mimicry of receptor functions by designing synthetic receptors would be one of the recently hot research trends in cell engineering. While several types of synthetic receptors have been designed to induce desired cell fates in response to external stimuli, little is known about which receptor type signals more efficiently for inducing a certain cell fate. In this study, we compared the performance of three types of synthetic receptor scaffolds, i.e. myristoylated, cytosolic, and transmembrane types that signal through JAK-dependent phosphorylation of tyrosine motifs to transduce growth signaling. As a result, the phosphorylation levels of JAK and subsequent downstream signaling molecules were significantly maintained in the cytosolic type receptors, leading to more efficient cell growth than the other types. In contrast, the phosphorylation levels of JAK decreased in a motif-dependent manner in the transmembrane type receptors. Although various studies on receptor engineering based on domain or motif engineering have been reported, to our knowledge this study is the first to demonstrate that synthetic receptor scaffolds significantly affect the efficiency of cell fate signals. These findings are important for both receptor biology and receptor engineering, providing guidelines for rationally designing synthetic receptors that can transduce as efficient signaling as possible.

Indexed as

Receptors, ArtificialCell DifferentiationPhosphorylationProtein-Tyrosine KinasesSignal TransductionProtein-Tyrosine KinasesReceptors, Artificial

Identifiers

PMID38461201
PMCPMC10925030
OpenAlexW4392625046

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.