Evidence map›Paper›PMID 36151112›Full record

ArticleNature communications2022

Payload distribution and capacity of mRNA lipid nanoparticles.

Sixuan Li, Yizong Hu, Andrew Li, Jinghan Lin, Kuangwen Hsieh, Zachary Schneiderman, Pengfei Zhang, Yining Zhu, Chenhu Qiu, Efrosini Kokkoli and 2 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 148 papers.

0numbers the graph read from it
0cells of the map it votes in
148citing papers in PubMed
21.4field-weighted citation impact, top 1% of its field
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

148 citing papers in PubMed, 264 citations in OpenAlex.

  1. Review
  2. Cas12a chRDNA-mediatedMolecular therapy. Nucleic acids · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Towards mRNA therapeutics 2.0.Nature reviews. Drug discovery · 2026
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. NNature · 2026
    Article
  16. Review
  17. Review
  18. Article
  19. Messenger RNA and guide RNA distributions in lipid nanoparticles impact gene-editing efficiency in vivo.Molecular therapy : the journal of the American Society of Gene Therapy · 2026
    Article
  20. Review

88 more citing papers are in PubMed but not listed here.

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

12 authors at 1 institution in 1 country.

Sixuan Li *Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-0116-8812
Yizong Hu *Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA. yhu38@jhmi.edu.ORCID 0000-0003-3983-5104
Andrew LiDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jinghan LinInstitute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
Kuangwen HsiehDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0003-3730-4406
Zachary SchneidermanInstitute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
Pengfei ZhangDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID 0000-0002-8578-8305
Yining ZhuInstitute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
Chenhu QiuInstitute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
Efrosini KokkoliInstitute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0001-7783-0158
Tza-Huei WangDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA. thwang@jhu.edu.ORCID 0000-0002-3540-9354
Hai-Quan MaoInstitute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA. hmao@jhu.edu.ORCID 0000-0002-4262-9988
Johns Hopkins University · US

Funding

Development of an oral liver-targeted prime-and-trap malaria vaccineU01AI155313 · NIAID · UNIVERSITY OF WASHINGTON · PI MURPHY, SEAN C · 2021 to 2025
$4.1M
A "Culture" Shift: Integrated Bacterial Screening and Antibacterial Susceptibility Test on Microfluidic Digital Array for Bloodstream InfectionsR01AI137272 · NIAID · JOHNS HOPKINS UNIVERSITY · PI WANG, TZA-HUEI JEFF, YANG, SAMUEL · 2018 to 2022
$3.6M
NIAID NIH HHS R01 AI137272NIAID NIH HHS U01 AI155313
6 · The paper itself

Abstract

Lipid nanoparticles (LNPs) are effective vehicles to deliver mRNA vaccines and therapeutics. It has been challenging to assess mRNA packaging characteristics in LNPs, including payload distribution and capacity, which are critical to understanding structure-property-function relationships for further carrier development. Here, we report a method based on the multi-laser cylindrical illumination confocal spectroscopy (CICS) technique to examine mRNA and lipid contents in LNP formulations at the single-nanoparticle level. By differentiating unencapsulated mRNAs, empty LNPs and mRNA-loaded LNPs via coincidence analysis of fluorescent tags on different LNP components, and quantitatively resolving single-mRNA fluorescence, we reveal that a commonly referenced benchmark formulation using DLin-MC3 as the ionizable lipid contains mostly 2 mRNAs per loaded LNP with a presence of 40%-80% empty LNPs depending on the assembly conditions. Systematic analysis of different formulations with control variables reveals a kinetically controlled assembly mechanism that governs the payload distribution and capacity in LNPs. These results form the foundation for a holistic understanding of the molecular assembly of mRNA LNPs.

Indexed as

LipidsNanoparticlesLiposomesRNA, MessengerRNA, Small InterferingLipid NanoparticlesLipidsLiposomesRNA, MessengerRNA, Small Interfering

Identifiers

PMID36151112
PMCPMC9508184
OpenAlexW4296833728

What OpenQuestion holds

Textmetadata
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.