Pseudomonas aeruginosa (Pa) is the most common virulent pathogen contributing to the pathogenesis of cystic fibrosis (CF). During bacterial lung colonization, the products of its metabolism are released in the extracellular space contributing to the pathogenic events associated with its presence. To gain insights on the mechanisms involved in the Pa pathogenesis we focused our attention on proteins released by Pa using a MudPIT approach combined with cell biology assays. Conditioned medium (CM) collected under aerobic and microaerobic conditions from Pa clinical strains (in early and late colonization), unlike the laboratory strain, induced expression of IL-8 mRNA in CF airway epithelial cells. We have identified proteins released by clinically relevant Pa strains, focusing on the pro-inflammatory effects as metalloproteases (MMPs). In fact, their expression pattern was associated with the highest pro-inflammatory activity measured in the early clinically isolated strain. The relation was further supported by the result of the analysis of a larger and independent set of Pa isolates derived from sporadically and chronically infected CF patients: 76% of sporadic samples expressed protease activity (n = 44), while only 27% scored positive in the chronically infected individuals (n = 38, p < 0.0001, Fisher's exact test). Finally, looking for a possible mechanism of action of bacterial MMPs, we found that CM from early clinical isolates can cleave CXCR1 on the surface of human neutrophils, suggesting a potential role for the bacterially released MMPs in the protection of the pathogen from the host's response.
"Further, where P. aeruginosa dominates the infection microbiota, its growth is likely to further affect the composition of airway environment. This impact of colonisation could occur both directly through the metabolomic (Kozlowska et al., 2013) and secretomic (Bergamini et al., 2012) footprint of P. aeruginosa, and, in turn, indirectly by stimulating changes in the host immune response (Bergamini et al., 2012) and the activity of other co-colonising species (Bakkal et al., 2010; Tashiro et al., 2013). Whereas the causality in these interactions is difficult to demonstrate, were such relationships to exist, they would result in both an association between P. aeruginosa infection and measures of airway disease, and an association between P. aeruginosa infection and microbiota composition. "
[Show abstract][Hide abstract] ABSTRACT: Chronic bacterial lung infections associated with non-cystic fibrosis bronchiectasis represent a substantial and growing health-care burden. Where Pseudomonas aeruginosa is the numerically dominant species within these infections, prognosis is significantly worse. However, in many individuals, Haemophilus influenzae predominates, a scenario associated with less severe disease. The mechanisms that determine which pathogen is most abundant are not known. We hypothesised that the distribution of H. influenzae and P. aeruginosa would be consistent with strong interspecific competition effects. Further, we hypothesised that where P. aeruginosa is predominant, it is associated with a distinct 'accessory microbiota' that reflects a significant interaction between this pathogen and the wider bacterial community. To test these hypotheses, we analysed 16S rRNA gene pyrosequencing data generated previously from 60 adult bronchiectasis patients, whose airway microbiota was dominated by either P. aeruginosa or H. influenzae. The relative abundances of the two dominant species in their respective groups were not significantly different, and when present in the opposite pathogen group the two species were found to be in very low abundance, if at all. These findings are consistent with strong competition effects, moving towards competitive exclusion. Ordination analysis indicated that the distribution of the core microbiota associated with each pathogen, readjusted after removal of the dominant species, was significantly divergent (analysis of similarity (ANOSIM), R=0.07, P=0.019). Taken together, these findings suggest that both interspecific competition and also direct and/or indirect interactions between the predominant species and the wider bacterial community may contribute to the predominance of P. aeruginosa in a subset of bronchiectasis lung infections.The ISME Journal advance online publication, 18 July 2014; doi:10.1038/ismej.2014.124.
The ISME Journal 07/2014; 9(1). DOI:10.1038/ismej.2014.124 · 9.30 Impact Factor
"It allows to automatically obtain thousands of features comprising spectra, peptide sequences and related proteins
[24,25]. In addition, label-free quantification approaches based on spectral count (SpC) or SEQUEST-based SCORE evaluation permit an high-throughput discovering of multiple biomarkers
[26-28], which could contain a higher level of discriminatory information. "
[Show abstract][Hide abstract] ABSTRACT: Background
Mass spectrometry is an important analytical tool for clinical proteomics. Primarily employed for biomarker discovery, it is increasingly used for developing methods which may help to provide unambiguous diagnosis of biological samples. In this context, we investigated the classification of phenotypes by applying support vector machine (SVM) on experimental data obtained by MudPIT approach. In particular, we compared the performance capabilities of SVM by using two independent collection of complex samples and different data-types, such as mass spectra (m/z), peptides and proteins.
Globally, protein and peptide data allowed a better discriminant informative content than experimental mass spectra (overall accuracy higher than 87% in both collection 1 and 2). These results indicate that sequencing of peptides and proteins reduces the experimental noise affecting the raw mass spectra, and allows the extraction of more informative features available for the effective classification of samples. In addition, proteins and peptides features selected by SVM matched for 80% with the differentially expressed proteins identified by the MAProMa software.
These findings confirm the availability of the most label-free quantitative methods based on processing of spectral count and SEQUEST-based SCORE values. On the other hand, it stresses the usefulness of MudPIT data for a correct grouping of sample phenotypes, by applying both supervised and unsupervised learning algorithms. This capacity permit the evaluation of actual samples and it is a good starting point to translate proteomic methodology to clinical application.
Journal of Clinical Bioinformatics 01/2013; 3(1):1. DOI:10.1186/2043-9113-3-1
[Show abstract][Hide abstract] ABSTRACT: The halophyte Mesembryanthemum crystallinum adapts to salt stress by salt uptake and switching from C3 photosynthesis to Crassulacean Acid Metabolism (CAM). An important role in this process is played by transport proteins in the tonoplast of the central vacuole. Here we examine dynamic changes in protein composition during salt-stress adaptation in microsomes from M. crystallinum leaves. Plants challenged with 400 mM NaCl accumulate salt already at day 4 of treatment and malic acid only at day 12; a switching to CAM hence follows any initial steps of salt adaptation with a delay. With a label-free and semi-quantitative approach, we identified here the most dramatic changes between the proteome of control plants and plants harvested at 12 days of the treatment; the abundance of 14 proteins was significantly affected. The proteome data reveal the majority of subunits of the vacuolar H+-ATPase holoenzyme (V-ATPase). The salt treatment somewhat decreases the abundance of all subunits in the short-term (4 days). Long-term adaptation, including the switching to CAM, goes together with a strong increase in the representation of all detectable subunits. Because this increase is subunit-specific, with the highest rise occurring for subunits E and c, the data suggests that long-term adaptation to salt stress correlates with a change in V-ATPase subunit stoichiometry and point out the structural plasticity of this holoenzyme.
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