The enzyme pseudooxynicotine amine oxidase from Pseudomonas putida S16 is not an oxidase, but a dehy
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Choudhary, Vishakha↗
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The Structures of SctK and SctD from Pseudomonas aeruginosa Reveal the Interface of the Type III Secretion System Basal Body and Sorting Platform
Abstract not provided
Muthuramalingam, Meenakumari↗
Leveraging host metabolism for bisdemethoxycurcumin production in Pseudomonas putida
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
Evaluation of chromosomal insertion loci in the Pseudomonas putida KT2440 genome for predictable biosystems design
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
T3SS and alginate biosynthesis of Pseudomonas aeruginosa impair healing of infected rabbit wounds
Not Available
Karna, S. L. Rajasekhar↗
A phage-encoded anti-activator inhibits quorum sensing in Pseudomonas aeruginosa
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Shah, Megha↗
Construction of a novel dual-inducible duet-expression system for gene (over)expression in Pseudomonas putida
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
Helix Cracking Regulates the Critical Interaction between RetS and GacS in Pseudomonas aeruginosa
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99 GENERAL AND MISCELLANEOUS↗
High titer methyl ketone production with tailored Pseudomonas taiwanensis VLB120
Not Available
Nies, Salome C.↗
Tandem chemical deconstruction and biological upcycling of poly(ethylene terephthalate) to β-ketoadipic acid by Pseudomonas putida KT2440
Not Available
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
The PqsE Active Site as a Target for Small Molecule Antimicrobial Agents against Pseudomonas aeruginosa
Not provided.
Biochemistry & Molecular Biology↗
Structure-Based Ligand Design Targeting Pseudomonas aeruginosa LpxA in Lipid A Biosynthesis
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Sacco, Michael D.↗
Structure Guided Development of Novel Thymidine Mimetics Targeting Pseudomonas aeruginosa Thymidylat
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Choi, Jun Yong↗
Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida
Abstract The genome-scale model of metabolism and gene expression (ME-model) forPseudomonas putidaKT2440,iPpu1676-ME, provides a comprehensive representation of biosynthetic costs and proteome allocation. Compared to a metabolic-only model,iPpu1676-ME significantly expands on gene expression, macromolecular assembly, and cofactor utilization, enabling accurate growth predictions without additional constraints. Multi-omics analysis using RNA sequencing and ribosomal profiling data revealed translational prioritization inP. putida, with core pathways, such as nicotinamide biosynthesis and queuosine metabolism, exhibiting higher translational efficiency, while secondary pathways displayed lower priority. Notably, the ME-model significantly outperformed the M-model in alignment with multi-omics data, thereby validating its predictive capacity. Thus,iPpu1676-ME offers valuable insights intoP. putida’s proteome allocation and presents a powerful tool for understanding resource allocation in this industrially relevant microorganism.
Mathematical & Computational Biology↗
Author Correction: Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida
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Zournas, Apostolos↗