Evidence map›Paper›PMID 40654819›Full record

ArticlebioRxiv : the preprint server for biology2025

High-throughput discovery of transmembrane helix dimers from human single-pass membrane proteins with TOXGREEN sort-seq.

Samantha M Anderson, Joshua Choi, Emma M Cushman, Megan Leander, Srivatsan Raman, Alessandro Senes

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

5 · Who and what money

Authors and funding

6 authors.

Samantha M AndersonDepartment of Biochemistry.ORCID 0000-0001-6114-0427
Joshua ChoiDepartment of Biochemistry.ORCID 0009-0002-3095-9987
Emma M CushmanDepartment of Biochemistry.ORCID 0009-0003-9415-4608
Megan LeanderDepartment of Biochemistry.ORCID 0000-0001-5257-2498
Srivatsan RamanDepartment of Biochemistry.ORCID 0000-0002-5673-6944
Alessandro SenesDepartment of Biochemistry.ORCID 0000-0002-3807-2275

Funding

Research Training for Computation and Informatics in Biology and MedicineT15LM007359 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI Mark W. Craven, Colin Noel Dewey · 2002 to 2026
$22.6M
PREDOCTORAL TRAINING IN MOLECULAR BIOPHYSICST32GM008293 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI JACKSON, MEYER B. · 1989 to 2016
$4.6M
Understanding the molecular basis of transmembrane protein associationR35GM130339 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI SENES, ALESSANDRO · 2019 to 2023
$1.8M
NIGMS NIH HHS R35 GM130339NIGMS NIH HHS T32 GM008293NLM NIH HHS T15 LM007359
6 · The paper itself

Abstract

The oligomerization of the transmembrane helices of single-pass membrane proteins is crucial to biological function and its misregulation can lead to many diseases. The study of transmembrane helix oligomerization is facilitated by the availability of genetic reporter assays, which are essential tools for understanding the organization and biology of single-pass systems. In particular, reporter assays are crucial for mapping the oligomerization interfaces of transmembrane helices through scanning mutagenesis but their application is limited by the need to clone and measure each construct individually. Here, we present "TOXGREEN sort-seq", a high-throughput version of the TOXGREEN assay that enables the direct measurement of transmembrane helix oligomerization in large libraries using fluorescence-activated cell sorting and next-generation sequencing. We show that TOXGREEN sort-seq is robust and reproduce the direct measurements of individual constructs with good accuracy and sensitivity. The method produced high-quality mutational profiles from a library of 17,400 constructs designed to probe the interface of 100 potential GAS

Identifiers

PMID40654819
PMCPMC12248156

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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.