Evidence map›Paper›PMID 41278769›Full record

ArticlebioRxiv : the preprint server for biology2025

From spark to wildfire: illuminating single-cell origins of virus infection spread and diversification.

Rahul Ramachandran, Huicheng Shi, John Yin

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

3 authors.

Rahul RamachandranWisconsin Institute for Discovery, Chemical and Biological Engineering, University of Wisconsin-Madison, 330 N Orchard St, Madison, 53715, Wisconsin, USA.
Huicheng ShiWisconsin Institute for Discovery, Chemical and Biological Engineering, University of Wisconsin-Madison, 330 N Orchard St, Madison, 53715, Wisconsin, USA.
John YinWisconsin Institute for Discovery, Chemical and Biological Engineering, University of Wisconsin-Madison, 330 N Orchard St, Madison, 53715, Wisconsin, USA.ORCID 0000-0001-6146-0594

Funding

A new hybrid modeling framework combining biophysics and deep learning to predict and optimize peripheral neuromodulation outcomes in lower urinary tract diseaseR01DK133605 · NIDDK · FLORIDA INTERNATIONAL UNIVERSITY · PI Zachary C Danziger · 2022 to 2026
$3.1M
A New Paradigm for Systems Physiology Modeling: Biomechanistic Learning Augmentation with Deep Differential Equation Representations (BLADDER)OT2OD030524 · OD · FLORIDA INTERNATIONAL UNIVERSITY · PI DANZIGER, ZACHARY C · 2020 to 2021
$1.9M
NIDDK NIH HHS R01 DK133605NIH HHS OT2 OD030524
6 · The paper itself

Abstract

When a virus encounters a living cell it triggers infection, cell death, and the release of virus progeny. In lab cultures, such progeny spread to near and distant cells, creating a plaque, a visible record of virus growth and cell death. Plaque-based assays have long enabled amplification and quantification of virus particles, but the earliest infections of a plaque remain poorly characterized. Here, we used a recombinant rhinovirus expressing a fluorescent reporter protein to track the start and spread of infection across HeLa cell monolayers at single-cell resolution. We analyzed reporter expression profiles from eight plaques and over 150 cells, reviewing, testing and applying methods of time-series analysis, clustering, and dimensionality reduction. We identified primary infections based on early reporter expression in isolated cells and secondary infections among their neighbors. Primary infected cells exhibited tightly clustered gene expression profiles, while secondary infected cells showed broader heterogeneity in the timing, intensity, and duration of reporter expression, without correspondence to their associated primary cells. This heterogeneity likely reflects a combination of factors, including noisy gene expression, viral genetic changes, and variation in local cellular environments. The rapid diversification of gene expression highlights the power of single-cell imaging to shed light on infection spread.

Indexed as

clusteringdimensionality reductiongene expression profileplaque growthtime-series analysisViral infection

Identifiers

PMID41278769
PMCPMC12632452

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.