Evidence map›Paper›PMID 42820461›Full record

ReviewBiochemical Society transactions2026

One adaptor, multiple outcomes: decoding TRIFosome heterogeneity.

Prasanna Suresh, Yu P Zhang, Clare Bryant, David Klenerman

Abstract readReview
In one paragraph

Review in Biochemical Society transactions, 2026. 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

4 authors.

Prasanna SureshYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, U.K.ORCID 0009-0001-5298-5994
Yu P ZhangYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, U.K.ORCID 0000-0001-5486-278X
Clare BryantDepartment of Veterinary Medicine, University of Cambridge, Cambridge, U.K.ORCID 0000-0002-2924-0038
David KlenermanYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, U.K.ORCID 0000-0001-7116-6954

Funding

Wellcome TrustWellcome Trust (WT) 321588/Z/24/Z
6 · The paper itself

Abstract

Innate immune signalling is uniquely driven through the formation of supramolecular organising centres (SMOCs), which couple receptor activation with downstream effector recruitment. The adaptor protein TRIF coordinates interferon, inflammatory, and cell death responses downstream of TLR3 and TLR4 activation, yet exactly how this protein drives such diverse outputs remains unresolved. Recent structural studies of recombinant TRIF, alongside single-molecule fluorescence imaging of endogenously expressed TRIF in live cells, reveal that TRIF assembles into complexes with heterogeneous size and morphology, with monomeric and low-order complexes associated with early-phase interferon signalling and mature, RIPK1-containing complexes associated with NF-κB activation. This review explores how differences in the structural architecture of the TRIFosome, from TIR-mediated oligomerisation through to RHIM-mediated cross-linking, may underlie this divergence in signalling outcome. Finally, this review discusses the translational opportunities that coordinating scaffold assembly with downstream function presents, including structure-selective therapeutics capable of shifting the balance between TRIF's signalling outputs and novel diagnostics that could be built on TRIFosome heterogeneity as a molecular fingerprint of disease.

Indexed as

Adaptor Proteins, Vesicular TransportAnimalsHumansImmunity, InnateSignal TransductionAdaptor Proteins, Vesicular TransportTICAM1 protein, humaninflammationinnate immunitySMOCtoll-like receptorsTRIFTRIFosome

Identifiers

PMID42820461
PMCPMC13642992

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.