Evidence map›Paper›PMID 38853934›Full record

ArticlebioRxiv : the preprint server for biology2024

Large-scale control over collective cell migration using light-controlled epidermal growth factor receptors.

Kevin Suh, Richard Thornton, Payam E Farahani, Daniel Cohen, Jared Toettcher

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Kevin SuhDepartment of Chemical and Biological Engineering, Princeton University, Princeton 08544.ORCID 0000-0001-7712-0279
Richard ThorntonOmenn-Darling Bioengineering Institutes, Princeton University, Princeton 08544.ORCID 0000-0002-9707-6110
Payam E FarahaniDepartment of Chemical and Biological Engineering, Princeton University, Princeton 08544.ORCID 0000-0003-2912-0519
Daniel CohenOmenn-Darling Bioengineering Institutes, Princeton University, Princeton 08544.ORCID 0000-0001-5819-1135
Jared ToettcherOmenn-Darling Bioengineering Institutes, Princeton University, Princeton 08544.ORCID 0000-0002-1546-4030

Funding

PREDOCTORAL TRAINING PROGRAM IN GENETICST32GM007388 · NIGMS · PRINCETON UNIVERSITY · PI CRISTEA, ILEANA M. · 1985 to 2022
$27.4M
A new class of biosensors for detecting signaling dynamics without live-cell microscopyR01GM144362 · NIGMS · PRINCETON UNIVERSITY · PI TOETTCHER, JARED E · 2022 to 2025
$1.3M
NIGMS NIH HHS R01 GM144362NIGMS NIH HHS T32 GM007388
6 · The paper itself

Abstract

Receptor tyrosine kinases (RTKs) are thought to play key roles in coordinating cell movement at single-cell and tissue scales. The recent development of optogenetic tools for controlling RTKs and their downstream signaling pathways suggested these responses may be amenable to engineering-based control for sculpting tissue shape and function. Here, we report that a light-controlled EGF receptor (OptoEGFR) can be deployed in epithelial cell lines for precise, programmable control of long-range tissue movements. We show that in OptoEGFR-expressing tissues, light can drive millimeter-scale cell rearrangements to densify interior regions or produce rapid outgrowth at tissue edges. Light-controlled tissue movements are driven primarily by PI 3-kinase signaling, rather than diffusible signals, tissue contractility, or ERK kinase signaling as seen in other RTK-driven migration contexts. Our study suggests that synthetic, light-controlled RTKs could serve as a powerful platform for controlling cell positions and densities for diverse applications including wound healing and tissue morphogenesis.

Identifiers

PMID38853934
PMCPMC11160748

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.