Evidence map›Paper›PMID 41543892›Full record

ArticleACS synthetic biology2026

RNA-Based Communication in Heterogeneous Populations of Cell Mimics.

François-Xavier Lehr, Imre Banlaki, Eric Bumüller, Thibault Mercier, Henrike Niederholtmeyer

Abstract read
In one paragraph

Article in ACS synthetic biology, 2026. 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

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

5 authors.

François-Xavier LehrMax Planck Institute for Terrestrial Microbiology, 35043 Marburg, Germany.ORCID 0000-0003-3837-6882
Imre BanlakiMax Planck Institute for Terrestrial Microbiology, 35043 Marburg, Germany.ORCID 0009-0002-8192-846X
Eric BumüllerMax Planck Institute for Terrestrial Microbiology, 35043 Marburg, Germany.ORCID 0009-0006-3838-497X
Thibault MercierMax Planck Institute for Terrestrial Microbiology, 35043 Marburg, Germany.
Henrike NiederholtmeyerMax Planck Institute for Terrestrial Microbiology, 35043 Marburg, Germany.ORCID 0000-0002-1375-0287

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA regulators offer a promising path for building complex, orthogonal circuits due to their low resource demands and design flexibility. In this study, we explore their potential as signaling molecules in communication between synthetic cells. Specifically, we engineer populations of heterogenetic porous polymer cell mimics to produce, emit, and receive two types of small synthetic RNA regulators. These RNAs are required to activate reporter expression at both the levels of transcription and translation. We distribute this AND gate circuit in receiver and two types of sender cell mimics to compare the distributed logic computation to the behavior of the circuit in well-mixed, bulk cell-free expression reactions. Analyzing different densities and spatial arrangements of senders and receivers, we reveal spatiotemporal gradients in RNA signals and identify configurations that increase specific activation. With small regulatory RNAs, the engineering toolbox for communication between synthetic cells expands to include a programmable class of signaling molecules. The rapid turnover of RNA suggests applications in establishing dynamic signaling gradients in communities of synthetic cells.

Indexed as

Artificial CellsRNACell CommunicationProtein BiosynthesisSignal TransductionTranscription, GeneticRNAcell-free transcription and translationcommunicationlogic gateRNA regulatorssynthetic cells

Identifiers

PMID41543892
PMCPMC12930506

What OpenQuestion holds

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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.