Evidence map›Paper›PMID 41659460›Full record

ArticlebioRxiv : the preprint server for biology2026

Programmable artificial RNA condensates in mammalian cells.

Shiyi Li, Yuna Kim, Kevin Wang, Eric John Payson, Anli A Tang, Maria Villalba Nieto, Dino Osmanovic, Madison Yang, Diego Dilao, Alexandra Bermudez and 6 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for 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

5 · Who and what money

Authors and funding

16 authors.

Shiyi LiDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.ORCID 0000-0002-7831-7900
Yuna KimDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Kevin WangDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Eric John PaysonDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Anli A TangDepartment of Mechanical and Aerospace Engineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Maria Villalba NietoDepartment of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Dino OsmanovicDepartment of Mechanical and Aerospace Engineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Madison YangDepartment of Molecular, Cell and Developmental Biology, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Diego DilaoDepartment of Molecular, Cell and Developmental Biology, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Alexandra BermudezDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Wen XiaoDepartment of Molecular, Cell and Developmental Biology, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Melody M H LiDepartment of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Neil Y C LinDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.
Kathrin PlathDepartment of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles; Los Angeles, CA, 90024, USA.ORCID 0000-0001-7796-3372
Douglas L BlackDepartment of Molecular, Cell and Developmental Biology, University of California, Los Angeles; Los Angeles, CA, 90024, USA.ORCID 0000-0002-2705-8187
Elisa FrancoDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA, 90024, USA.ORCID 0000-0003-1103-2668

Funding

Developing synthetic RNA organelles for spatiotemporal separation, control, and monitoring in living cellsR35GM155833 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Elisa Franco · 2024 to 2026
$1.1M
NIGMS NIH HHS R35 GM155833
6 · The paper itself

Abstract

Artificial biomolecular condensates have emerged as powerful tools to control cellular behaviors. Here we introduce a method to build artificial condensates within living mammalian cells through the design of modular RNA motifs formed by a single, short strand of RNA. These condensates emerge spontaneously, creating RNA-rich compartments that remain separated from their surrounding environment. The RNA sequences include stem-loop domains that fold as the RNA is transcribed, and then condense in the nucleus and cytoplasm through loop-loop interactions. These sequences can be optimized and diversified, enabling the generation of distinct, non-mixing condensate populations and the programmable control of their subcellular localization. The RNA motifs can also be modified to recruit small molecules, proteins, and RNA molecules in a sequence-specific manner to the RNA-rich phase. By introducing additional RNAs that link two distinct types of condensates, we can create droplets with multiple subcompartments, whose organization can be controlled by tuning the stoichiometry of different RNA sequences. These artificial condensates provide a versatile platform for studying and manipulating molecular functions inside living cells.

Identifiers

PMID41659460
PMCPMC12873911

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.