Evidence map›Paper›PMID 27281338›Full record

ArticlePLoS pathogens2016

Receptor-Targeted Nipah Virus Glycoproteins Improve Cell-Type Selective Gene Delivery and Reveal a Preference for Membrane-Proximal Cell Attachment.

Ruben R Bender, Anke Muth, Irene C Schneider, Thorsten Friedel, Jessica Hartmann, Andreas Plückthun, Andrea Maisner, Christian J Buchholz

Open access · goldAbstract read
In one paragraph

Article in PLoS pathogens, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed
6.3field-weighted citation impact, top 4% 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

74 citing papers in PubMed, 92 citations in OpenAlex.

  1. Article
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  3. Nanomaterials Drive In Vivo CAR Immune Cells Engineering.Advanced materials (Deerfield Beach, Fla.) · 2026
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  10. Article
  11. In Vivo CAR-T Therapies-A New Era of Programmable Immunity.International journal of molecular sciences · 2026
    Review
  12. In vivo chimeric antigen receptor (CAR)-T cell therapy.Nature reviews. Drug discovery · 2026
    Review
  13. FromImmune network · 2026
    Review
  14. Delivery platforms forFrontiers in immunology · 2026
    Review
  15. Article
  16. Article
  17. Article
  18. In vivo CAR cell therapy: from bench to bedside.Journal of hematology & oncology · 2025
    Review
  19. Efficient in vivo generation of CAR T cells using a retargeted fourth-generation lentiviral vector.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Article
  20. Article

14 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

8 authors at 3 institutions in 2 countries.

Ruben R BenderMolecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, Langen, Germany.
Anke MuthMolecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, Langen, Germany.
Irene C SchneiderMolecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, Langen, Germany.
Thorsten FriedelMolecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, Langen, Germany.
Jessica HartmannMolecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, Langen, Germany.
Andreas PlückthunDepartment of Biochemistry, University of Zurich, Zurich, Switzerland.
Andrea MaisnerInstitute for Virology (BMFZ), Philipps-University Marburg, Marburg, Germany.
Christian J BuchholzMolecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, Langen, Germany.
Paul Ehrlich Institut · DEPhilipps University of Marburg · DEUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Receptor-targeted lentiviral vectors (LVs) can be an effective tool for selective transfer of genes into distinct cell types of choice. Moreover, they can be used to determine the molecular properties that cell surface proteins must fulfill to act as receptors for viral glycoproteins. Here we show that LVs pseudotyped with receptor-targeted Nipah virus (NiV) glycoproteins effectively enter into cells when they use cell surface proteins as receptors that bring them closely enough to the cell membrane (less than 100 Å distance). Then, they were flexible in receptor usage as demonstrated by successful targeting of EpCAM, CD20, and CD8, and as selective as LVs pseudotyped with receptor-targeted measles virus (MV) glycoproteins, the current standard for cell-type specific gene delivery. Remarkably, NiV-LVs could be produced at up to two orders of magnitude higher titers compared to their MV-based counterparts and were at least 10,000-fold less effectively neutralized than MV glycoprotein pseudotyped LVs by pooled human intravenous immunoglobulin. An important finding for NiV-LVs targeted to Her2/neu was an about 100-fold higher gene transfer activity when particles were targeted to membrane-proximal regions as compared to particles binding to a more membrane-distal epitope. Likewise, the low gene transfer activity mediated by NiV-LV particles bound to the membrane distal domains of CD117 or the glutamate receptor subunit 4 (GluA4) was substantially enhanced by reducing receptor size to below 100 Å. Overall, the data suggest that the NiV glycoproteins are optimally suited for cell-type specific gene delivery with LVs and, in addition, for the first time define which parts of a cell surface protein should be targeted to achieve optimal gene transfer rates with receptor-targeted LVs.

Indexed as

Genetic VectorsGene Transfer TechniquesVirus InternalizationAnimalsBlotting, WesternCell LineFlow CytometryGlycoproteinsHumansLentivirusMicroscopy, ElectronNipah VirusTransduction, GeneticViral Envelope ProteinsGlycoproteinsViral Envelope Proteins

Identifiers

PMID27281338
PMCPMC4900575
OpenAlexW2414040529

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.