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

S Stephen T. Moore X Xizhen Lian A Amogh Vaidya S Sumanta Chatterjee (Department of Biomedical Engineering, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center) J Julien Santelli Y Yehui Sun (Department of Biomedical Engineering, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center) L Lukas Farbiak H Hao Zhu D Daniel J. Siegwart (Department of Biomedical Engineering, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center)

Abstract

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.

Article Details

Volume / Issue Vol. 17, Issue 1
Published January 07, 2026
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (9)

S

Stephen T. Moore

X

Xizhen Lian

A

Amogh Vaidya

S

Sumanta Chatterjee

Department of Biomedical Engineering, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center

J

Julien Santelli

Y

Yehui Sun

Department of Biomedical Engineering, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center

L

Lukas Farbiak

H

Hao Zhu

D

Daniel J. Siegwart

Department of Biomedical Engineering, Simmons Comprehensive Cancer Center, Program in Genetic Drug Engineering, The University of Texas Southwestern Medical Center