Evidence map›Paper›PMID 39484498›Full record

ArticlebioRxiv : the preprint server for biology2024

Correlating Disordered Activation Domain Ensembles with Gene Expression Levels.

Eduardo Flores, Aleah R Camacho, Estefania Cuevas-Zepeda, Mary B McCoy, Feng Yu, Max V Staller, Shahar Sukenik

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

5 · Who and what money

Authors and funding

7 authors.

Eduardo FloresDepartment of Chemistry and Biochemistry, University of California Merced, Merced, 95343.
Aleah R CamachoDepartment of Chemistry and Biochemistry, University of California Merced, Merced, 95343.
Estefania Cuevas-ZepedaDepartment of Chemistry and Biochemistry, University of California Merced, Merced, 95343.
Mary B McCoyDepartment of Chemistry and Biochemistry, University of California Merced, Merced, 95343.
Feng YuDepartment of Chemistry and Biochemistry, University of California Merced, Merced, 95343.ORCID 0000-0003-1755-5515
Max V StallerDepartment of Molecular and Cell Biology, University of California Berkeley, Berkeley, 94720.
Shahar SukenikDepartment of Chemistry and Biochemistry, University of California Merced, Merced, 95343.ORCID 0000-0003-3855-9574

Funding

Uncovering the structural underpinnings of function in disordered transcription factor regionsR35GM137926 · NIGMS · UNIVERSITY OF CALIFORNIA, MERCED · PI Shahar Sukenik · 2020 to 2026
$2.5M
Defining the protein sequence features that control transcriptional activation domain functionR35GM150813 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI Max Valentin Staller · 2023 to 2026
$1.5M
NIGMS NIH HHS R35 GM137926NIGMS NIH HHS R35 GM150813
6 · The paper itself

Abstract

Transcription factor proteins bind to specific DNA promoter sequences and initiate gene transcription. In eukaryotes, most transcription factors contain intrinsically disordered activation domains (ADs) that regulate their transcriptional activity. Like other disordered protein regions, ADs do not have a fixed three-dimensional structure and instead exist in an ensemble of conformations. Disordered ensembles contain sequence-encoded structural preferences which are often linked to their function. We hypothesize this link exists between the structural preferences of disordered AD ensembles and their ability to induce gene expression. To test this, we used FRET microscopy to measure the ensemble dimensions of two activation domains, HIF-1α and CITED2, in live cells, and correlate this structural information with transcriptional activity. We find that point mutations that expanded the HIF-1α ensemble increased transcriptional activity, while those that compacted it reduced activity. Conversely, CITED2 showed no correlation between ensemble dimensions and activity. Our results reveal a sequence-dependent relationship between AD ensemble dimensions and their transcriptional activity.

Identifiers

PMID39484498
PMCPMC11527027

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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.