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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

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↗
DOE OSTI2021

Development of dual‐inducible duet‐expression vectors for tunable gene expression control and CRISPR interference‐based gene repression in Pseudomonas putida KT2440

Summary The development of P. putida as an industrial host requires a sophisticated molecular toolbox for strain improvement, including vectors for gene expression and repression. To augment existing expression plasmids for metabolic engineering, we developed a series of dual‐inducible duet‐expression vectors for P. putida KT2440. A number of inducible promoters (P lac , P tac , P tetR/tetA and P bad ) were used in different combinations to differentially regulate the expression of individual genes. Protein expression was evaluated by measuring the fluorescence of reporter proteins (GFP and RFP). Our experiments demonstrated the use of compatible plasmids, a useful approach to coexpress multiple genes in P. putida KT2440. These duet vectors were modified to generate a fully inducible CRISPR interference system using two catalytically inactive Cas9 variants from S. pasteurianus (dCas9) and S. pyogenes (spdCas9). The utility of developed CRISPRi system(s) was demonstrated by repressing the expression of nine conditionally essential genes, resulting in growth impairment and prolonged lag phase for P. putida KT2440 growth on glucose. Furthermore, the system was shown to be tightly regulated, tunable and to provide a simple way to identify essential genes with an observable phenotype.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Correction for Thompson et al., “Fatty Acid and Alcohol Metabolism in Pseudomonas putida : Functional Analysis Using Random Barcode Transposon Sequencing”

Volume 86, no. 21, 2020, e01665-20, https://doi.org/10.1128/AEM.01665-20. Readers should note that when the authors created the deletion mutant of PP_2675, they deleted the entire region between the gene’s start and stop codons. However, this also deleted the DNA that codes for the first 14 amino acids of the overlapping ORF PP_2676. Additionally, the originally published URL for the JBEI public strain repository was incorrect. The correct link to all strains and plasmids in this study is https://public-registry.jbei .org/folders/641.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Engineered Membrane Vesicle Production via oprF or oprI Deletion Has Distinct Phenotypic Effects in Pseudomonas putida -putative knockouts table

Table S1, putative gene knockout targets in P. putida KT2440 to enhance vesiculation; Table S2, protein sequence identity of OmpA from E. coli K12 to P. putida KT2440 genes; Table S3, strains utilized in this study and corresponding construction details; Table S4, oligonucleotides utilized in this study; Table S5, plasmids utilized in this study; Table S6, sequences for mNeonGreen, tags, and codon-optimized genes; Figure S1, particle count per gCDW for KT2440 and knockout strains corresponding to data presented in Figure 1B; Figure S2, OD600 measurements of extracted MVs from KT2440 and knockout strains; Figure S3, particle count per gCDW for WT, ΔPP_4669, and ΔPP_1502; Figure S4, particle count per gCDW for KT2440 and knockout strains corresponding to data presented in Figure 3C; Figure S5, sizes of MVs corresponding to particle counts in Figure S4; Figure S6, particle count per gCDW for KT2440 grown on 20 mM glucose alone or 20 mM glucose plus 12.5 mM p-coumarate and 12.5 mM ferulate; Figure S7 and Figure S8, principal component analysis of the cellular fractions; Figure S9, heatmap of outer membrane proteins with differential abundance; and Figure S10, mNeonGreen (mNG) fluorescence signal for the cellular fraction and the extracellular fraction

hypervesiculation↗
DOE OSTI2026

Evolution_and_engineering_of_pathways_for_aromatic_O-demethylation_in_Pseudomonas_putida_KT2440

Biological conversion of lignin from biomass offers a promising strategy for sustainable production of fuels and chemicals. However,aromatic compoundsderived from lignin commonly contain methoxy groups, andO-demethylation of these substrates is often a rate-limiting reaction that influences catabolic efficiency. Severalenzymefamilies catalyze aromaticO-demethylation, but they are rarely comparedin vivoto determine an optimal biocatalytic strategy. Here, two pathways for aromaticO-demethylation were compared inPseudomonas putidaKT2440. The native Rieske non-heme ironmonooxygenase(VanAB) and, separately, a heterologous tetrahydrofolate-dependentdemethylase(LigM) were constitutively expressed inP. putida, and the strains were optimized via adaptive laboratory evolution (ALE) withvanillateas a model substrate. All evolved strains displayed improved growth phenotypes, with the evolved strains harboring the native VanAB pathway exhibiting growth rates ∼1.8x faster than those harboring the heterologous LigM pathway.Enzyme kineticsandtranscriptomicsstudies investigated the contribution of selected mutations toward enhanced utilization of vanillate. The VanAB-overexpressing strains contained the most impactful mutations, including those in VanB, thereductasefor vanillateO-demethylase, PP_3494, a global regulator of vanillate catabolism, andfghA, involved in formaldehydedetoxification. These three mutations were combined into a single strain, which exhibited approximately 5x faster vanillate consumption than the wild-type strain in the first 8 h of cultivation. Overall, this study illuminates the details of vanillate catabolism in the context of two distinct enzymatic mechanisms,yielding a platform strain for efficientO-demethylation of lignin-related aromatic compounds to value-added products. This DOI contains supplementary material associated with the published manuscript.

CBI↗