Evidence map›Paper›PMID 41469390›Full record

ArticleScientific reports2025

Competitive Viral Interference Controls Arbovirus Co-Transmission in Aedes aegypti.

Brinda Balakrishnan, Siva Santhiya Arul, Aarti Ravindran, Sangita Venkataraman

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Brinda BalakrishnanDepartment of Biotechnology, Anna University, Chennai, 600025, India.
Siva Santhiya ArulDepartment of Biotechnology, Anna University, Chennai, 600025, India.
Aarti RavindranDepartment of Biotechnology, Anna University, Chennai, 600025, India.
Sangita VenkataramanDepartment of Biotechnology, Anna University, Chennai, 600025, India. sangita.venkataraman@gmail.com.ORCID 0000-0003-0679-4529

Funding

University Grants Commission F.4-5(164-FRP)/2015
6 · The paper itself

Abstract

Viruses are the primary etiological agents responsible for numerous mosquito-borne diseases, which pose a global threat to humans and their carriers. In this study, we conducted a comprehensive analysis of the simultaneous presence of different viruses in a total of 237 transcriptomic datasets derived from Aedes aegypti (AA), obtained from the SRA and ENA databases to understand its impact on transmission of arboviruses such as Dengue, Zika, and Chikungunya to humans. We investigated the co-occurrence patterns of 21 distinct viruses, encompassing 52 isolates, which are known to be transmitted by mosquitoes. In addition, we used heatmaps, correlation coefficients, estimated count values, and differential gene expression to examine the viral abundance and the significant genes involved in viral co-transmission. We provide novel evidence of a robust antagonistic relationship between the Chikungunya virus and flaviviruses during their co-transmission in AA. Our study confirms that the genes involved in RNAi, ATP-binding, and venom allergen pathways are the pivotal vector interaction hubs in response to viral co-transmission in AA. For the first time, we highlight the critical role of the DDX5 gene in modulating responses to the relative loads of flaviviruses and togaviruses, which could determine the transmission dominance of one over the other.

Indexed as

AedesArbovirusesArbovirus InfectionsMosquito VectorsViral InterferenceAnimalsChikungunya virusHumansTranscriptomeZika VirusCo-occurrenceInteractionsMosquitoTranscriptomeVirus

Identifiers

PMID41469390
PMCPMC12753823

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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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.