Evidence map›Paper›PMID 40236220›Full record

ArticlebioRxiv : the preprint server for biology2025

Rapid optimization of protein function in mammalian cells via microbe-independent deep assembly and screening.

Yan Wu, Pengli Wang, Lan Xiang Liu, Chao Gao, Qin Qin, Matt Hageman, Thomas A Kirkland, Yichi Su, Michael Z Lin

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

9 authors.

Pengli Wang
Lan Xiang Liu
Qin Qin
Matt Hageman
Thomas A KirklandORCID 0000-0003-0859-5785

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Random mutagenesis and deep mutational scanning (DMS) are widely used to optimize proteins by oversampling large libraries in microbial cells, selecting cells expressing favorable variants, and sequencing to identify enriched variants. However, these methods are slow and costly, require effort to establish selection methods for a given protein function, and do not yield data on lower-performing variants. Here, we describe Microbe-Independent Deep Assembly and Screening (MIDAS), a rapid, high-throughput method for optimizing protein function directly in mammalian cells. As a demonstration, we applied MIDAS to improve a newly designed neurotransmitter bioluminescent indicator (NeuBI) for acetylcholine (ACh). MIDAS systematically optimized interdomain linkers, identified mutational hotspots, and exhaustively scanned amino acid combinations, in each case relating specific sequences to protein performance. MIDAS-optimized variants exhibited improved performance in vivo, highlighting the potential of MIDAS for improving protein function in mammalian systems.

Identifiers

PMID40236220
PMCPMC11996373

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LicenceCC BY-NC-ND
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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.