Evidence map›Paper›PMID 39974952›Full record

ArticlebioRxiv : the preprint server for biology2025

ZUGC-RNA degradation generates immunosuppressor to evade immune responses in eukaryotes.

Shuliang Gao, Mengting Chen, Douglas Wich, Hanan Bloomer, Zhiyuan Qu, Huiwen Guan, Qiaobing Xu

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

7 authors.

Shuliang GaoDepartment of Biomedical Engineering, Tufts University, Medford, MA, USA.
Mengting ChenDepartment of Biomedical Engineering, Tufts University, Medford, MA, USA.
Douglas WichDepartment of Biomedical Engineering, Tufts University, Medford, MA, USA.
Hanan BloomerDepartment of Biomedical Engineering, Tufts University, Medford, MA, USA.
Zhiyuan QuDepartment of Biomedical Engineering, Tufts University, Medford, MA, USA.
Huiwen GuanDepartment of Biomedical Engineering, Tufts University, Medford, MA, USA.
Qiaobing XuDepartment of Biomedical Engineering, Tufts University, Medford, MA, USA.

Funding

Develop lung-targeted synthetic lipid nanoparticles for mRNA medicine treating pulmonary lymphangioleiomyomatosisR01HL171728 · NHLBI · TUFTS UNIVERSITY MEDFORD · PI Yan Tang, Qiaobing Xu · 2024 to 2026
$1.9M
NHLBI NIH HHS R01 HL171728
6 · The paper itself

Abstract

Among the hundreds of modified nucleosides identified in terrestrial life, 2-amino-6-aminopurine (Z) is widely recognized as a prominent modified purine. Recently, RNA written with the ZUGC alphabet shows significant potential in RNA therapeutics as a synthetic biosystem. Here, we demonstrate that ZUGC-RNA can evade immune recognition in eukaryotes, independent of factors such as RNA length, sequence, 5'-triphosphate, modified uridine, and secondary structure. Notably, we discovered that both the degradation of ZUGC-RNA and metabolites of Z-nucleotides can function as immunosuppressors, silencing TLR7 sensing to block immune responses. This mechanism differs from that of pseudo-uridine (Ψ) modified RNA currently in use. ZUGC-RNAs also demonstrate broad applicability across multiple neural cell types. Our findings provide valuable insights for developing more tolerable RNA-based drugs and designing immunomodulators targeting TLR7. In addition to the potential prebiotic relevance of Z, our finding not only contributes to understanding the RNA world hypothesis but also provides new insights into the exploration of the origin of life.

Identifiers

PMID39974952
PMCPMC11838226

What OpenQuestion holds

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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.