Evidence map›Paper›PMID 38141039›Full record

ArticleACS synthetic biology2024

Coupling High-Throughput and Targeted Screening for Identification of Nonobvious Metabolic Engineering Targets.

Mahsa Babaei, Philip Tinggaard Thomsen, Marc Cernuda Pastor, Michael Krogh Jensen, Irina Borodina

Open access · hybridAbstract read
In one paragraph

Article in ACS synthetic biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 20% of its field
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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. High-throughput metabolic engineering ofProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. Review
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 at 1 institution in 1 country.

Mahsa BabaeiNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.ORCID 0000-0002-7862-0811
Philip Tinggaard ThomsenNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.ORCID 0000-0003-4498-4550
Marc Cernuda PastorNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
Michael Krogh JensenNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.ORCID 0000-0001-7574-4707
Irina BorodinaNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
Novo Nordisk Foundation · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of metabolic engineering targets is a fundamental challenge in strain development programs. While high-throughput (HTP) genetic engineering methodologies capable of generating vast diversity are being developed at a rapid rate, a majority of industrially interesting molecules cannot be screened at sufficient throughput to leverage these techniques. We propose a workflow that couples HTP screening of common precursors (e.g., amino acids) that can be screened either directly or by artificial biosensors, with low-throughput targeted validation of the molecule of interest to uncover nonintuitive beneficial metabolic engineering targets and combinations hereof. Using this workflow, we identified several nonobvious novel targets for improving

Indexed as

Metabolic EngineeringSaccharomyces cerevisiaeLevodopaRNA, Guide, CRISPR-Cas SystemsTyrosineLevodopaRNA, Guide, CRISPR-Cas SystemsTyrosinebetaxanthindCas9gRNA libraryL-DOPAp-coumaric acidSaccharomyces cerevisiae

Identifiers

PMID38141039
PMCPMC10804409
OpenAlexW4390142539

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.