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Record W4391513486 · doi:10.1101/2024.02.02.578543

Temperature-induced changes in protein interactions control RNA recruitment to G3BP1 condensates

2024· preprint· en· W4391513486 on OpenAlexaff
Charlotte M. Fischer, Hannes Ausserwӧger, Tomas Šneideris, Daoyuan Qian, Rob Scrutton, Seema Qamar, Peter St George‐Hyslop, Tuomas P. J. Knowles

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersEuropean Commission
KeywordsStress granuleRNARNA-binding proteinBiophysicsPhase diagramChemical physicsChemistryProtein–protein interactionPhase (matter)BiologyMessenger RNABiochemistryTranslation (biology)

Abstract

fetched live from OpenAlex

Abstract Biomolecular condensates have emerged as prominent regulators of dynamic subcellular organisation and essential biological processes. Temperature, in particular, exerts a significant influence on the formation and behaviour of biomolecular condensation. For example, during cellular heat stress, stress granules (SGs) are formed from RNA-binding proteins (RBPs) and RNA, forming liquid condensates to protect the RNA from damage. However, the molecular mechanisms leading to changes in protein phase behaviour are not well understood. To answer how temperature modulates protein interactions and phase behaviour, we developed a high-throughput microfluidic platform, capable of mapping the phase space and quantifying protein interactions in a temperature-dependent manner. Specifically, our approach measures high-resolution protein phase diagrams as a function of temperature, while accurately quantifying changes in the binodal, condensate stoichiometry and free energy contribution of a solute, hence, providing information about the underlying mechanistic driving forces. We employ this approach to investigate the effect of temperature changes on the phase separation of the stress granule scaffold protein Ras GTPase-activating protein-binding protein 1 (G3BP1) with PolyA-RNA. Surprisingly, we find that the G3BP1/RNA phase boundary remains unaffected by the increasing temperature but the underlying stoichiometry and energetics shift, which can only be revealed with high-resolution phase diagrams. This indicates that temperature-induced dissolution is counteracted by entropic processes driving phase separation. With increasing temperature, the G3BP1 content in condensates decreases alongside with a reduction of the free energy of protein interactions, while the RNA content increases driven by entropically favoured hydrophobic interactions. In the context of cellular heat SG formation, these findings could indicate that during heat shock, elevated temperatures directly induce RNA recruitment to stress granules as a cytoprotective mechanism by finetuning the strength of protein and RNA interactions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.286
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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