Evidence map›Paper›PMID 33145367›Full record

ArticleMolecular therapy. Methods & clinical development2020

Development of a Novel Competitive qRT-PCR Assay to Measure Relative Lentiviral Packaging Efficiency.

Eirini Vamva, Andrew M L Lever, Conrad A Vink, Julia C Kenyon

Abstract read
In one paragraph

Article in Molecular therapy. Methods & clinical development, 2020. 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. 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

4 authors.

Eirini VamvaUniversity of Cambridge Department of Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.
Andrew M L LeverUniversity of Cambridge Department of Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.
Conrad A VinkGlaxoSmithKline, Gunnels Wood Road, Stevenage SG1 2NY, UK.
Julia C KenyonUniversity of Cambridge Department of Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Third-generation HIV-1-derived lentiviral vectors are successfully used as therapeutic agents in various clinical applications. To further promote their use, we attempted to enhance vector infectivity by targeting the dimerization and packaging properties of the RNA transfer vector based on the premise that these two processes are tightly linked. We rationally designed mutant vectors to favor the dimeric conformation, potentially enhancing genome packaging. Initial assessments using standard assays generated outputs of variable reproducibility, sometimes with conflicting results. Therefore, we developed a novel competitive qRT-PCR assay in a co-transfection setting to measure the relative packaging efficiencies of wild-type and mutant transfer vectors. Here we report the effect of the dimerization-stabilizing mutations on infectious and physical titers of lentiviral vectors together with their packaging efficiency, measured using our novel assay. Enhancing dimerization did not automatically lead to better vector RNA packaging, suggesting that, for vector functionality, sufficient flexibility of the RNA to adopt different conformations is more important than the dimerization capacity. Our novel competitive qPCR assay enables a more stringent analysis of RNA packaging efficiency, allowing a much more precise understanding of the links between RNA structure, packaging, and infectious titers that will be invaluable for future vector development.

Identifiers

PMID33145367
PMCPMC7581820

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.