{"title":"Single-Cell Reporter Dynamics During the First Two Rounds of Rhinovirus Plaque Growth.","authors":"Rahul Ramachandran, Huicheng Shi, John Yin","doi":"10.1002/cyto.a.70069","DOIUrl":null,"url":null,"abstract":"<p><p>When infection spreads from an initially infected cell through a cell monolayer, the resulting plaque records successive rounds of virus-cell interaction. Fluorescent reporter viruses permit this process to be followed at single-cell resolution, but whether secondary infected cells retain detectable signatures associated with their plaque of origin remains unclear. Here, we tracked enhanced green fluorescent protein expression in 154 cells from eight rhinovirus plaques and systematically compared feature-based, clustering, dimensionality-reduction, and sequence-alignment methods. Primary and secondary infected cells were distinguished mainly by the time of first detectable fluorescence; no consistent differences were detected in reporter-trajectory kinetics or amplitude. Among secondary cells, most methods detected no plaque-associated structure beyond chance. Affinity propagation detected a small plaque-label association that persisted after removal of the first detection time, although its biological interpretation was limited by session-associated intensity differences. Thus, by the secondary round, cell-to-cell heterogeneity largely exceeded any plaque-associated signature detectable under the present conditions. This work provides a framework for comparing single-cell trajectories across early rounds of plaque growth and for designing studies to resolve subtle lineage-associated effects.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cytometry Part A","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/cyto.a.70069","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
When infection spreads from an initially infected cell through a cell monolayer, the resulting plaque records successive rounds of virus-cell interaction. Fluorescent reporter viruses permit this process to be followed at single-cell resolution, but whether secondary infected cells retain detectable signatures associated with their plaque of origin remains unclear. Here, we tracked enhanced green fluorescent protein expression in 154 cells from eight rhinovirus plaques and systematically compared feature-based, clustering, dimensionality-reduction, and sequence-alignment methods. Primary and secondary infected cells were distinguished mainly by the time of first detectable fluorescence; no consistent differences were detected in reporter-trajectory kinetics or amplitude. Among secondary cells, most methods detected no plaque-associated structure beyond chance. Affinity propagation detected a small plaque-label association that persisted after removal of the first detection time, although its biological interpretation was limited by session-associated intensity differences. Thus, by the secondary round, cell-to-cell heterogeneity largely exceeded any plaque-associated signature detectable under the present conditions. This work provides a framework for comparing single-cell trajectories across early rounds of plaque growth and for designing studies to resolve subtle lineage-associated effects.
期刊介绍:
Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques.
The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome:
Biomedical Instrumentation Engineering
Biophotonics
Bioinformatics
Cell Biology
Computational Biology
Data Science
Immunology
Parasitology
Microbiology
Neuroscience
Cancer
Stem Cells
Tissue Regeneration.