The alternative sigma factor, sigmaS, affects polyhydroxyalkanoate metabolism in Pseudomonas putida

To determine whether the stationary sigma factor, sigma(S), influences polyhydroxyalkanoate metabolism in Pseudomonas putida KT2440, an rpoS-negative mutant was constructed to evaluate polyhydroxyalkanoate accumulation and expression of a translational fusion to the promoter region of the genes that code for polyhydroxyalkanoate synthase 1 (phaC1) and polyhydroxyalkanoate depolymerase (phaZ). By comparison with the wild-type, the rpoS mutant showed a higher polyhydroxyalkanoate degradation rate and increased expression of the translational fusion during the stationary growth phase. These results suggest that sigma(S) might control the genes involved in polyhydroxyalkanoate metabolism, possibly in an indirect manner. In addition, survival and oxidative stress assays performed under polyhydroxyalkanoate- and nonpolyhydroxyalkanoate- accumulating conditions demonstrated that the accumulated polyhydroxyalkanoate increased the survival and stress tolerance of the rpoS mutant. According to this, polyhydroxyalkanoate accumulation would help cells to overcome the adverse conditions encountered during the stationary phase in the strain that lacks RpoS.     

Analysis of the Pseudomonas aeruginosa regulon controlled by the sensor kinase KinB and sigma factor RpoN

Alginate overproduction by Pseudomonas aeruginosa, also known as mucoidy, is associated with chronic endobronchial infections in cystic fibrosis. Alginate biosynthesis is initiated by the extracytoplasmic function sigma factor (σ(22); AlgU/AlgT). In the wild-type (wt) nonmucoid strains, such as PAO1, AlgU is sequestered to the cytoplasmic membrane by the anti-sigma factor MucA that inhibits alginate production. One mechanism underlying the conversion to mucoidy is mutation of mucA. However, the mucoid conversion can occur in wt mucA strains via the degradation of MucA by activated intramembrane proteases AlgW and/or MucP. Previously, we reported that the deletion of the sensor kinase KinB in PAO1 induces an AlgW-dependent proteolysis of MucA, resulting in alginate overproduction. This type of mucoid induction requires the alternate sigma factor RpoN (σ(54)). To determine the RpoN-dependent KinB regulon, microarray and proteomic analyses were performed on a mucoid kinB mutant and an isogenic nonmucoid kinB rpoN double mutant. In the kinB mutant of PAO1, RpoN controlled the expression of approximately 20% of the genome. In addition to alginate biosynthetic and regulatory genes, KinB and RpoN also control a large number of genes including those involved in carbohydrate metabolism, quorum sensing, iron regulation, rhamnolipid production, and motility. In an acute pneumonia murine infection model, BALB/c mice exhibited increased survival when challenged with the kinB mutant relative to survival with PAO1 challenge. Together, these data strongly suggest that KinB regulates virulence factors important for the development of acute pneumonia and conversion to mucoidy.     

Plasmid Involvement in Acyclic Isoprenoid Metabolism by Pseudomonas putida

An organism identified as Pseudomonas putida was found to utilize citronellol or geraniol as the sole carbon and energy source. The ability to degrade these acyclic isoprenols was associated with pSRQ50, a 50-megadalton transmissible plasmid.     

Genetic evidence of distinct physiological regulation mechanisms in the sigma(54) Pu promoter of Pseudomonas putida

The activity of the toluene-responsive sigma(54) Pu promoter of the pWW0 TOL plasmid of Pseudomonas putida is down-regulated in vivo during exponential growth in rich medium and also by the presence of glucose in the culture. Although the Pu promoter already performs poorly during log growth in minimal medium when amended with casamino acids, the addition of glucose further decreased by two- to threefold the accumulation of beta-galactosidase in a Pu-lacZ reporter P. putida strain. Since Pu was still down-regulated during exponential growth regardless of glucose addition, it appeared that the carbohydrate separately influenced promoter activity. This notion was supported by the growth-dependent induction pattern of Pu in a ptsN mutant of P. putida, the loss of which makes Pu no longer responsive to repression by glucose. On the other hand, overexpression of the sigma factor sigma(54), known to partially alleviate the exponential silencing of the promoter, did not affect glucose inhibition of Pu. These data indicated that exponential silencing and carbon source-dependent repression are two overlapping but genetically distinguishable mechanisms that adapt Pu to the physiological status of the cells and nutrient availability.     

High-quality genome-scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities

Genome-scale reconstructions of metabolism are computational species-specific knowledge bases able to compute systemic metabolic properties. We present a comprehensive and validated reconstruction of the biotechnologically relevant bacterium Pseudomonas putida KT2440 that greatly expands computable predictions of its metabolic states. The reconstruction represents a significant reactome expansion over available reconstructed bacterial metabolic networks. Specifically, iJN1462 (i) incorporates several hundred additional genes and associated reactions resulting in new predictive capabilities, including new nutrients supporting growth; (ii) was validated by in vivo growth screens that included previously untested carbon (48) and nitrogen (41) sources; (iii) yielded gene essentiality predictions showing large accuracy when compared with a knock-out library and Bar-seq data; and (iv) allowed mapping of its network to 82 P. putida sequenced strains revealing functional core that reflect the large metabolic versatility of this species, including aromatic compounds derived from lignin. Thus, this study provides a thoroughly updated metabolic reconstruction and new computable phenotypes for P. putida, which can be leveraged as a first step toward understanding the pan metabolic capabilities of Pseudomonas.