Evidence map›Paper›PMID 42239288›Full record

ArticlebioRxiv : the preprint server for biology2026

Protein•DNA mesh assembly drives dsDNA-specific and duplex length-dependent activation of cGAS.

Shuai Wu, Christina M Stallings, Stephanie M Torres, Brendan Antiochos, Jungsan Sohn

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In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

5 authors.

Shuai WuDepartment of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205.
Christina M StallingsDepartment of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205.
Stephanie M TorresDepartment of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205.
Brendan AntiochosDivision of Rheumatology, Johns Hopkins University School of Medicine, Baltimore, MD 21205.
Jungsan SohnDepartment of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205.

Funding

Mechanistic Studies of cytosolic double-stranded DNA sensing pathways.R35GM145363 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI JUNGSAN SOHN · 2022 to 2026
$2.3M
Delineating the interplay between nucleic-acid-dependent phase separation and immune responses against cGAS in SLER21AR085266 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI ANTIOCHOS, BRENDAN, SOHN, JUNGSAN · 2024 to 2024
$375k
NIAMS NIH HHS R21 AR085266NIGMS NIH HHS R35 GM145363
6 · The paper itself

Abstract

Cyclic G/AMP synthase (cGAS) forms condensates on dysregulated double-stranded (ds) DNA to trigger inflammatory responses. Currently, how it specifically recognizes dsDNA and why activation depends on duplex length remain poorly understood. Using cryo-electron microscopy, biochemical assays, and single-molecule methods, we show that full-length cGAS assembles a protein•dsDNA mesh by reiteratively propagating dimers-of-dimers, driving an associative phase transition. Previously uncharacterized N- and C-terminal interactions, together with inter-dimer junction-loops, track the B-form groove and bend dsDNA to build an extensive mesh network spanning multiple duplexes. These interactions are critical for cross-stabilizing active cGAS, revealing why higher-order assembly on long duplexes maximizes signaling activity. Remarkably, cGAS can build the protein•dsDNA mesh on a single contiguous duplex by entangling its oligomerization platform, resulting in a mechanically resilient and kinetically stable signaling platform. Together, our findings establish higher-order mesh assembly of cGAS as the foundation for dsDNA selectivity, duplex-length-dependent activation, and condensate formation.

Identifiers

PMID42239288
PMCPMC13228216

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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.