Evidence map›Paper›PMID 40894656›Full record

ArticlebioRxiv : the preprint server for biology2025

A Super-Resolution Spatial Atlas of SARS-CoV-2 Infection in Human Cells.

Leonid Andronov, Mengting Han, Ashwin Balaji, Yanyu Zhu, Lei S Qi, W E Moerner

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

5 · Who and what money

Authors and funding

6 authors.

Leonid AndronovDepartment of Chemistry; Stanford University, Stanford, CA 94305 U.S.A.ORCID 0000-0002-4213-5363
Mengting HanDepartment of Bioengineering; Stanford University, Stanford, CA 94305 U.S.A.
Ashwin BalajiDepartment of Chemistry; Stanford University, Stanford, CA 94305 U.S.A.
Yanyu ZhuDepartment of Bioengineering; Stanford University, Stanford, CA 94305 U.S.A.
Lei S QiDepartment of Bioengineering; Stanford University, Stanford, CA 94305 U.S.A.ORCID 0000-0002-3965-3223
W E MoernerDepartment of Chemistry; Stanford University, Stanford, CA 94305 U.S.A.ORCID 0000-0002-2830-209X

Funding

Single-Molecule Imaging for Cell Biology and Super-Resolution MicroscopyR35GM118067 · NIGMS · STANFORD UNIVERSITY · PI MOERNER, WILLIAM E · 2016 to 2025
$6.2M
Engineering and Imaging 3D genome structure-function dynamics across time scalesU01DK127405 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI BLOBEL, GERD A, PHILLIPS-CREMINS, JENNIFER ELIZABETH · 2020 to 2024
$5.7M
NIDDK NIH HHS U01 DK127405NIGMS NIH HHS R35 GM118067
6 · The paper itself

Abstract

The spatial organization of viral and host components dictates the course of infection, yet the nanoscale architecture of the SARS-CoV-2 life cycle remains largely uncharted. Here, we present a comprehensive super-resolution Atlas of SARS-CoV-2 infection, systematically mapping the localization of nearly all viral proteins and RNAs in human cells. This resource reveals that the viral main protease, nsp5, localizes to the interior of double-membrane vesicles (DMVs), challenging existing models and suggesting that polyprotein processing is a terminal step in replication organelle maturation. We identify previously undescribed features of the infection landscape, including thin dsRNA "connectors" that physically link DMVs, and large, membrane-less dsRNA granules decorated with replicase components, reminiscent of viroplasms. Finally, we show that the antiviral drug nirmatrelvir induces the formation of persistent, multi-layered bodies of uncleaved polyproteins. This spatial Atlas provides a foundational resource for understanding coronavirus biology and offers crucial insights into viral replication, assembly, and antiviral mechanisms.

Identifiers

PMID40894656
PMCPMC12393340

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.