Evidence map›Paper›PMID 40307426›Full record

ArticleNature biomedical engineering2025

A live bacteria enzyme assay for identification of human disease mutations and drug screening.

Donghui Choe, Bernhard O Palsson

Abstract read
In one paragraph

Article in Nature biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Evidence forbioRxiv : the preprint server for biology · 2025
    Article
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

2 authors.

Donghui ChoeShu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0003-1107-7380
Bernhard O PalssonShu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA. bpalsson@ucsd.edu.ORCID http://orcid.org/0000-0003-2357-6785

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in high-throughput sequencing have enabled the identification of genetic variations associated with human disease. However, deciphering the functional significance of these variations remains challenging. Here we propose an alternative approach that uses humanized Escherichia coli to study human genetic enzymopathies and to screen candidate drug effects on metabolic targets. By replacing selected E. coli metabolic enzymes with their human orthologues and their sequence variants, we demonstrate that the growth rate of E. coli reflects the in vivo activity of heterologously expressed human enzymes. This approach accurately reflected enzyme activities of known sequence variants, enabling rapid screening of causal sequence variations associated with human diseases. This approach bridges the gap between in vitro assays and cell-based assays. Our findings suggest that the proposed approach using a humanized E. coli strain holds promise for drug discovery, offering a high-throughput and cost-effective platform for identifying new compounds targeting human enzymes. Continued research and innovation in this field have the potential to impact the development and practice of precision medicine.

Indexed as

Enzyme AssaysEscherichia coliMutationDrug DiscoveryDrug Evaluation, PreclinicalHigh-Throughput Screening AssaysHumans

Identifiers

PMID40307426
PMCPMC12443593

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.