Evidence map›Paper›PMID 11992006›Full record

ArticleJournal of virology2002

Evolution of bacteriophage in continuous culture: a model system to test antiviral gene therapies for the emergence of phage escape mutants.

Björn F Lindemann, Christian Klug, Andreas Schwienhorst

Open access · greenAbstract read
In one paragraph

Article in Journal of virology, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 35% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Quantitative analysis of a parasitic antiviral strategy.Antimicrobial agents and chemotherapy · 2004
    Article
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

3 authors at 1 institution in 1 country.

Björn F LindemannDepartment of Biochemical Kinetics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany.
Christian Klug
Andreas Schwienhorst
Max Planck Institute for Biophysical Chemistry · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of viral escape mutants is usually a highly undesirable phenomenon. This phenomenon is frequently observed in antiviral drug applications for the treatment of viral infections and can undermine long-term therapeutic success. Here, we propose a strategy for evaluating a given antiviral approach in terms of its potential to provoke the appearance of resistant virus mutants. By use of Q beta RNA phage as a model system, the effect of an antiviral gene therapy, i.e., a virus-specific repressor protein expressed by a recombinant Escherichia coli host, was studied over the course of more than 100 generations. In 13 experiments carried out in parallel, 12 phage populations became resistant and 1 became extinct. Sequence analysis revealed that only two distinct phage mutants emerged in the 12 surviving phage populations. For both escape mutants, sequence variations located in the repressor binding site of the viral genomic RNA, which decrease affinity for the repressor protein, conferred resistance to translational repression. The results clearly suggest the feasibility of the proposed strategy for the evaluation of antiviral approaches in terms of their potential to allow resistant mutants to appear. In addition, the strategy proved to be a valuable tool for observing virus-specific molecular targets under the impact of antiviral drugs.

Indexed as

Evolution, MolecularAllolevivirusCapsidGene ExpressionGenetic TherapyGenetic VectorsMutagenesisPlasmidsRNA, ViralSequence Analysis, RNARNA, Viral

Identifiers

PMID11992006
PMCPMC137063
OpenAlexW2149573581

What OpenQuestion holds

Textmetadata
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.