Pseudomonas aeruginosa Regulated Intramembrane Proteolysis: Protease MucP Can Overcome Mutations in the AlgO Periplasmic Protease To Restore Alginate Production in Nonmucoid Revertants.

The progression of cystic fibrosis (CF) from an acute to a chronic disease is often associated with the conversion of the opportunistic pathogen Pseudomonas aeruginosa from a nonmucoid form to a mucoid form in the lung. This conversion involves the constitutive synthesis of the exopolysaccharide alginate, whose production is under the control of the AlgT/U sigma factor. This factor is regulated posttranslationally by an extremely unstable process and has been commonly attributed to mutations in the algT (algU) gene. By exploiting this unstable phenotype, we isolated 34 spontaneous nonmucoid variants arising from the mucoid strain PDO300, a PAO1 derivative containing the mucA22 allele commonly found in mucoid CF isolates. Complementation analysis using a minimal tiling path cosmid library revealed that most of these mutants mapped to two protease-encoding genes, algO, also known as prc or PA3257, and mucP Interestingly, our algO mutations were complemented by both mucP and algO, leading us to delete, clone, and overexpress mucP, algO, mucE, and mucD in both wild-type PAO1 and PDO300 backgrounds to better understand the regulation of this complex regulatory mechanism. Our findings suggest that the regulatory proteases follow two pathways for regulated intramembrane proteolysis (RIP), where both the AlgO/MucP pathway and MucE/AlgW pathway are required in the wild-type strain but where the AlgO/MucP pathway can bypass the MucE/AlgW pathway in mucoid strains with membrane-associated forms of MucA with shortened C termini, such as the MucA22 variant. This work gives us a better understanding of how alginate production is regulated in the clinically important mucoid variants of Pseudomonas aeruginosaIMPORTANCE Infection by the opportunistic pathogen Pseudomonas aeruginosa is the leading cause of morbidity and mortality seen in CF patients. Poor patient prognosis correlates with the genotypic and phenotypic change of the bacteria from a typical nonmucoid to a mucoid form in the CF lung, characterized by the overproduction of alginate. The expression of this exopolysaccharide is under the control an alternate sigma factor, AlgT/U, that is regulated posttranslationally by a series of proteases. A better understanding of this regulatory phenomenon will help in the development of therapies targeting alginate production, ultimately leading to an increase in the length and quality of life for those suffering from CF.

Microbial metagenome profiling using amplicon length heterogeneity-polymerase chain reaction proves more effective than elemental analysis in discriminating soil specimens.

The combination of soil's ubiquity and its intrinsic abiotic and biotic information can contribute greatly to the forensic field. Although there are physical and chemical characterization methods of soil comparison for forensic purposes, these require a level of expertise not always encountered in crime laboratories. We hypothesized that soil microbial community profiling could be used to discriminate between soil types by providing biological fingerprints that confer uniqueness. Three of the six Miami-Dade soil types were randomly selected and sampled. We compared the microbial metagenome profiles generated using amplicon length heterogeneity-polymerase chain reaction analysis of the 16S rRNA genes with inductively coupled plasma optical emission spectroscopy analysis of 13 elements (Al, B, Ca, Cu, Fe, K, Mg, Mn, Na, P, S, Si, and Zn) that are commonly encountered in soils. Bray-Curtis similarity index and analysis of similarity were performed on all data to establish differences within sites, among sites, and across two seasons. These data matrices were used to group samples that shared similar community patterns using nonmetric multidimensional scaling analysis. We concluded that while chemical characterization could provide some differentiation between soils, microbial metagenome profiling was better able to discriminate between the soil types and had a high degree of reproducibility, therefore proving to be a potential tool for forensic soil comparisons.