Evidence map›Paper›PMID 37606964›Full record

ReviewBioscience reports2023

Sensing nucleotide composition in virus RNA.

Raymon Lo, Daniel Gonçalves-Carneiro

Open access · goldAbstract readReview
In one paragraph

Review in Bioscience reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

6 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Immunology of RNA-based vaccines: The critical interplay between inflammation and expression.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. 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

2 authors at 1 institution in 1 country.

Raymon LoImperial College London, Department of Infectious Disease, Imperial College London, London, U.K.
Daniel Gonçalves-CarneiroImperial College London, Department of Infectious Disease, Imperial College London, London, U.K.ORCID 0000-0002-9333-1540
NIHR Imperial Biomedical Research Centre · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nucleotide composition plays a crucial role in the structure, function and recognition of RNA molecules. During infection, virus RNA is exposed to multiple endogenous proteins that detect local or global compositional biases and interfere with virus replication. Recent advancements in RNA:protein mapping technologies have enabled the identification of general RNA-binding preferences in the human proteome at basal level and in the context of virus infection. In this review, we explore how cellular proteins recognise nucleotide composition in virus RNA and the impact these interactions have on virus replication. Protein-binding G-rich and C-rich sequences are common examples of how host factors detect and limit infection, and, in contrast, viruses may have evolved to purge their genomes from such motifs. We also give examples of how human RNA-binding proteins inhibit virus replication, not only by destabilising virus RNA, but also by interfering with viral protein translation and genome encapsidation. Understanding the interplay between cellular proteins and virus RNA composition can provide insights into host-virus interactions and uncover potential targets for antiviral strategies.

Indexed as

Antiviral AgentsRNA, ViralCastor OilHumansNucleotidesProteomeAntiviral AgentsCastor OilNucleotidesProteomeRNA, ViralantiviralCoding Biashost-virus interactionNucleotideVirus

Identifiers

PMID37606964
PMCPMC10500230
OpenAlexW4386046400

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.