Evidence map›Paper›PMID 41057294›Full record

ArticleNature communications2025

Sensitive, high-throughput, metabolic analysis by molecular sensors on the membrane surface of mother yeast cells.

Wenxin Jiang, Huanmin Du, Xingjie Huang, Luke P Lee, Chia-Hung Chen

Abstract read
In one paragraph

Article in Nature communications, 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

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

5 authors.

Wenxin Jiang *Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China.
Huanmin Du *Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China.
Xingjie HuangDepartment of Biomedical Engineering, City University of Hong Kong, Hong Kong, China.
Luke P LeeHarvard Medical School, Harvard University; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. lplee@bwh.harvard.edu.ORCID http://orcid.org/0000-0002-1436-4054
Chia-Hung ChenDepartment of Biomedical Engineering, City University of Hong Kong, Hong Kong, China. chiachen@cityu.edu.hk.ORCID http://orcid.org/0000-0001-5097-3968

Funding

City University of Hong Kong (CityU) 7005639City University of Hong Kong (CityU) 7020030City University of Hong Kong (CityU) 9229502City University of Hong Kong (CityU) 9610467City University of Hong Kong (CityU) 9667239Innovation and Technology Commission (ITF) PRP/011/24TiInnovation and Technology Commission (ITF) PRP/037/22FXResearch Grants Council, University Grants Committee (RGC, UGC) RIF R1007-24FUniversity Grants Committee (UGC) GRF CityU11201624University Grants Committee (UGC) GRF CityU11204923University Grants Committee (UGC) GRF CityU11212822University Grants Committee (UGC) RIF R4020-22
6 · The paper itself

Abstract

Due to its genetic similarity to humans, yeast serves as a vital model organism in life sciences and medicine, allowing for the study of crucial biological processes such as cell division and metabolism for drug development. However, current tools for measuring yeast extracellular secretion lack the sensitivity, throughput, and speed required for large-scale metabolic analysis. Here, we present an ultrasensitive, large-scale analysis of yeast extracellular secretion using molecular sensors on the membrane surface of mother yeast cells. These sensors remain selectively confined to mother yeast cells during cell division, enabling high-sensitivity detection, high-throughput screening and rapid single-yeast assays. Their detection limit is 100 nM, and they can screen over 10

Indexed as

Biosensing TechniquesCell MembraneHigh-Throughput Screening AssaysSaccharomyces cerevisiae

Identifiers

PMID41057294
PMCPMC12504667

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.