Evidence map›Paper›PMID 40990513›Full record

ArticleJournal of virology2025

A novel ZIKV-targeted scRNA-seq method for precise quantification of ZIKV RNA.

Yang Zhou, Libo Liu, Wei Yang, Yanhua Wu, Chongyao Zhong, Yuxuan Liu, Kunqi Lin, Dongying Fan, Yisong Wang, Peigang Wang and 1 more

Abstract read
In one paragraph

Article in Journal of virology, 2025. 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. 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

11 authors.

Yang ZhouDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.ORCID 0009-0004-9566-4324
Libo LiuDepartment of Parasitology, School of Basic Medical Sciences, Guizhou Medical University, Guiyang, Guizhou, China.
Wei YangNational Center of Technology Innovation for Animal Model, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), Ministry of Education, NHC Key Laboratory of Comparative Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yanhua WuDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.
Chongyao ZhongDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.
Yuxuan LiuDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.
Kunqi LinDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.
Dongying FanDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.
Yisong WangDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.ORCID 0000-0002-1609-2523
Peigang WangDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.ORCID 0000-0001-6045-2007
Jing AnDepartment of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China.ORCID 0000-0002-2567-0380

Funding

Beijing Natural Science Foundation Undergraduate "Research Initiation (Qiyan)" QY24340National Key Research and Development Program of China 2021YFC2300202National Natural Science Foundation of China
6 · The paper itself

Abstract

Zika virus (ZIKV), transmitted by mosquitoes, poses a serious public health threat. Currently, precise quantitative diagnostic methods are lacking. Existing single-cell RNA-sequencing (scRNA-seq) techniques are challenged to detect ZIKV RNA due to its absence of a poly(A) tail, hindering the identification of infected cells. In this study, we developed a novel ZIKV-targeted scRNA-seq method that enables precise quantification of ZIKV RNA in individual cells. Immunocompetent suckling mice were intracerebrally infected with ZIKV to establish persistent infection in the brain. Samples were collected at 10-day post infection for ZIKV-targeted and 10× Genomics scRNA-seq analysis. Comparative analysis identified 17 distinct cell types in both ZIKV-infected and control suckling mouse brains, with significant changes in cell type distribution and proportion post-infection. The ZIKV-targeted scRNA-seq method suggested higher efficiency in capturing exogenous cells compared to the 10× Genomics scRNA-seq method. Both methods identified multiple endogenous and exogenous cell types susceptible to ZIKV, with peripheral blood-derived monocytes/macrophages (PBDMMs), neurons, and T cells as primary cell types expressing ZIKV RNA. IFA validated scRNA-seq findings, revealing that neurons and microglia could be infected by ZIKV, with significant reductions in their numbers post-infection. This study presents a novel ZIKV-targeted scRNA-seq that enables accurate quantification of ZIKV RNA within individual cells, identifies key susceptible cell types, and offers advantages in detecting exogenous cells, making it a scalable solution for providing valuable insights into therapeutic and vaccine development. IMPORTANCE: This study marks the first use of a scRNA-seq method tailored for ZIKV, allowing accurate measurement of ZIKV RNA in individual cells and identification of critical susceptible cell types. A comparative analysis with the 10× Genomics scRNA-seq method highlighted the advantages of ZIKV-targeted scRNA-seq in terms of accuracy and practicality, particularly its superior ability to capture exogenous cells. Beyond ZIKV, this method also helps establish precise quantification of viral RNA at the single-cell level for other viruses by designing target-specific beads based on conserved regions of the viral genome. This advancement is set to greatly enhance studying pathogenesis of ZIKV infection and then significantly contribute to improve prevention and research in therapeutics and vaccines.

Indexed as

RNA-SeqRNA, ViralSequence Analysis, RNASingle-Cell AnalysisZika VirusZika Virus InfectionAnimalsBrainMacrophagesMiceNeuronsSingle-Cell Gene Expression AnalysisRNA, Viral10× Genomics scRNA-seqprecise quantificationtargeted cellstargeted single-cell RNA sequencingZika virus

Identifiers

PMID40990513
PMCPMC12548417

What OpenQuestion holds

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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.