Evidence map›Paper›PMID 41501049›Full record

ArticleNature communications2026

Multiplexed lipid nanoparticle barcoding reveals tissue-dynamic kinetic insights and enriched cellular tropism in hepatic zones.

Stephen T Moore, Xizhen Lian, Amogh Vaidya, Sumanta Chatterjee, Julien Santelli, Yehui Sun, Lukas Farbiak, Hao Zhu, Daniel J Siegwart

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Collecting Duct-Targeted Lipid Nanoparticles DeliverbioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. 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

9 authors.

Stephen T MooreDepartment of Biomedical Engineering, Department of Biochemistry, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, USA.
Xizhen LianDepartment of Biomedical Engineering, Department of Biochemistry, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, USA.
Amogh VaidyaDepartment of Biomedical Engineering, Department of Biochemistry, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, USA.ORCID http://orcid.org/0000-0003-0712-659X
Sumanta ChatterjeeDepartment of Biomedical Engineering, Department of Biochemistry, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, USA.
Julien SantelliDepartment of Biomedical Engineering, Department of Biochemistry, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, USA.
Yehui SunDepartment of Biomedical Engineering, Department of Biochemistry, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, USA.ORCID http://orcid.org/0000-0003-0215-6095
Lukas FarbiakDepartment of Biomedical Engineering, Department of Biochemistry, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, USA.ORCID http://orcid.org/0000-0003-4107-1676
Hao ZhuChildren's Research Institute, Departments of Pediatrics and Internal Medicine, Center for Regenerative Science and Medicine, Children's Research Institute Mouse Genome Engineering Core, University of Texas Southwestern Medical Center, Dallas, TX, USA. Hao.Zhu@UTSouthwestern.edu.ORCID http://orcid.org/0000-0002-8417-9698
Daniel J SiegwartDepartment of Biomedical Engineering, Department of Biochemistry, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, USA. Daniel.Siegwart@UTSouthwestern.edu.ORCID http://orcid.org/0000-0003-3823-1931

Funding

UT Southwestern Medical Center Simmons Comprehensive Cancer CenterP30CA142543 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI MELANIE H. COBB · 2010 to 2026
$53.7M
UT Southwestern NORCP30DK127984 · NIDDK · UT SOUTHWESTERN MEDICAL CENTER · PI Jeff G McDonald · 2022 to 2026
$7.4M
Defining the molecular interactions within nanoparticles that enable delivery of long nucleic acidsR01EB025192 · NIBIB · UT SOUTHWESTERN MEDICAL CENTER · PI SIEGWART, DANIEL JOHN · 2018 to 2025
$3.1M
NCI NIH HHS P30 CA142543NIBIB NIH HHS R01 EB025192NIDDK NIH HHS P30 DK127984U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) P30CA142543U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB) 5R01EB025192-06
6 · The paper itself

Abstract

Lipid nanoparticles (LNPs) efficiently deliver nucleic acids to cells in vivo and facilitate clinical applications including RNA-based vaccines and therapies. Discovery and optimization of LNPs remain challenging due to the complexity of input variables and low throughput workflows. To accelerate these processes, we report a broadly compatible barcoded Cre recombinase mRNA barcode platform that enables multiplexed LNP tracking in vivo in tdTomato reporter mice. We evaluate accumulation and degradation kinetics of mRNA encapsulated in Selective Organ Targeting (SORT) LNPs in the liver, lung, and spleen, and show that functional protein activity is associated with rapid organ enrichment. We further demonstrate how barcode multiplexing can streamline systematic kinetic studies, distinguish nanoparticles with distinct biological outcomes, and differentiate subtle, yet important, variations within a series of similar formulations. Finally, we use barcoding to identify and characterize nanoparticles with hepatic zonal bias and previously overlooked extrahepatic tropism. This approach could accelerate high resolution characterization of nanoparticles with desirable properties, enable large-scale systematic studies of diverse LNPs, and provide insights into optimizable parameters of LNP-mRNA delivery.

Indexed as

LipidsLiverNanoparticlesAnimalsFemaleIntegrasesKineticsLiposomesLungMiceMice, Inbred C57BLRNA, MessengerSpleenCre recombinaseIntegrasesLipid NanoparticlesLipidsLiposomesRNA, Messenger

Identifiers

PMID41501049
PMCPMC12873177

What OpenQuestion holds

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LicenceCC BY
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.