Evidence map›Paper›PMID 40126873›Full record

ArticleMicrobial biotechnology2025

Rational Design Assisted by Evolutionary Engineering Allows (De)Construction and Optimization of Complex Phenotypes in Pseudomonas putida KT2440.

Blas Blázquez, Juan Nogales

Abstract read
In one paragraph

Article in Microbial biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Blas BlázquezDepartment of Systems Biology, Centro Nacional de Biotecnología CSIC, Madrid, Spain.ORCID https://orcid.org/0000-0003-4099-6909
Juan NogalesDepartment of Systems Biology, Centro Nacional de Biotecnología CSIC, Madrid, Spain.ORCID https://orcid.org/0000-0002-4961-0833

Funding

European Union (Next Generation EU/PRTR) fundingHorizon 2020 Framework Programme 101000733Horizon 2020 Framework Programme 814650Horizon 2020 Framework Programme 870294MCIN/AEI/10.13039/501100011033 PID2022-139247OB-I00MCIN/AEI/10.13039/501100011033 TED2021-130689B-C33
6 · The paper itself

Abstract

Beyond the rational construction of genetic determinants to encode target functions, complex phenotype engineering requires the contextualisation of their expression within the metabolic and genetic background of the host strain. Furthermore, wherever metabolic complexity is involved, phenotype engineering demands standard, reliable, plug-and-play tools. We introduce GENIO (GENome Integration and fitness Optimization platform for Pseudomonas putida), a framework to optimise genetic circuit performance by means of (i) chromosome-location-based differential gene expression and (ii) subsequent fitness improvement through evolutionary engineering if needed. Using gene expression strength and cell-to-cell variation, we characterised 10 P. putida chromosomal loci (ppLPS) to show that genome context rather than distance to ORI is the main factor driving differential expression performance. We further contextualised ppLPS gene expression against well-known chromosomal integration sites and plasmids displaying different copy numbers. GENIO supports comprehensive exploration of the gene expression space across P. putida's genome while unlocking performance optimization of complex heterologous metabolic pathways through evolutionary engineering. To demonstrate the usability of GENIO, we restored P. putida's aromatic hydrocarbon metabolism by (de)constructing the toluene/m-xylene catabolic pathway coded in the pWW0 plasmid. We also showed that engineering complex phenotypes requires accurate contextualisation of the synthetic pathways involved, a process that benefits from biological robustness.

Indexed as

Metabolic EngineeringPseudomonas putidaHydrocarbons, AromaticMetabolic Networks and PathwaysPhenotypeTolueneXylenesHydrocarbons, AromaticTolueneXylenescomplex phenotypefitness landscapeGENIOgenome expansionmetabolic engineeringPseudomonas putida

Identifiers

PMID40126873
PMCPMC11932161

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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.