Project description:Specific Lactobacillus strains are marketed as probiotics i.e. health promoting organisms. As previously shown in vivo, L. plantarum WCFS1 modulates immune responses via nuclear factor (NF)kB in a growth phase dependent manner, likely caused by changed microbial cell surface characteristics. Here, we identified the differential cell-surface proteome composition of L. plantarum WCFS1 cells derived from the mid-logarithmic and late stationary growth phase by surface trypsination of intact bacterial cells, followed by a combined 1D- and 2D-LC-MS shotgun proteomics strategy, and growth phase dependent transcriptome analysis. Overall, these analyses led to the identification of 31 surface proteins differentially present in the logarithmic and stationary phase, whereas additional 17 and 33 proteins appeared solely present in stationary and logarithmic phase of growth, respectively. From 75% of predicted surface related genes displaying relatively high expression levels, the corresponding proteins were detected, demonstrating a high correlation between transcriptome and proteome profiles. The impact of cell-surface peptide fractions on cellular host responses was evaluated using NFkB promoter activation assays in intestinal epithelial cells, revealing that only late stationary phase derived peptides are capable of attenuating flagellin and cell envelope induced NFkB activation. Overall our data mechanistically expand earlier observations that revealed growth-phase dependent immunomodulation by L. plantarum WCFS1, leading to a typical adjuvant- or tolerance-like response after exposure to stationary phase harvested bacterial cells. Sub-fractionation of the late stationary phase peptide fraction revealed a sub-set of strong attenuator peptides able to manipulate NFkB related pathways to hereby attenuate pro-inflammatory signaling. Samples were hybridizedin a loop design linking each timepoint to the next as well as the previous timepoint. Additional hybridizations were introduced linking each sample three timepoints forward and three timepoints back. All samples were hybridized unsing at least each of the two dyes once.

Project description:The genome sequence is the “blue-print of life”, but proteomics is required to relate this blue-print of life to the actual physiology of living cells. Because of their low complexity – only about 2.000 proteins make a Staphylococcus aureus cell viable – bacteria are excellent model systems to identify the entire protein assembly of a living organism. Many of the studies on physiological proteomics of bacteria, however, still rely on 2D gel-based technologies that visualize only a minor part of the proteome. In this study it will be shown that the majority of proteins expressed in the Gram-positive human pathogen S. aureus can be identified and even quantified by a combination of gel-based and gel-free approaches, the latter having undergone formidable improvements over the last 10 years. S. aureus has been the model of choice for our proteomic studies, because it combines high pathogenicity with increasing antibiotic resistance, which calls for new leads in the development of anti-staphylococcal therapy. On the way towards the entire proteome of S. aureus, we analysed four subproteomic fractions: cytosolic proteins, membrane-bound proteins, cell-surface associated and extracellular proteins, the two latter fractions containing most of the virulence factors. To obtain quantitative results, we compared growing cells and non-growing/stationary phase cells using the 15N metabolic labelling approach. With almost 2.000 proteins, 80 % of the expressed proteome was identified and even quantified in growing and non-growing cells. A comprehensive inventory of the entire protein assembly during the two physiologically distinct states is presented, which integrates data ranging from gene expression to subcellular localization. Three major protein classes were distinguished: (i) Proteins induced in the stationary phase only (ii) Vegetative proteins, no longer synthesized but stable in the stationary phase (iii) Vegetative proteins, no longer required in non-growing cells and finally degraded. This quantitative proteomics approach for growing/non-growing cells, which represents a proof-of-principle for whole-cell physiological proteomics, can now be extended to address particular infection-relevant physiological states. Importantly, the present model study represents the highest coverage of a bacterial proteome so far (except low complexity bacteria). It thus paves the way towards a new understanding of cell physiology and pathophysiology of S. aureus and related pathogenic bacteria, opening a new era in infection-related research on this crucial pathogen. For the DNA-microarray experiment RNA was extracted from two independently grown cultures. One was grown in 14N labelled BioExpress medium and the other in 15N labelled BioExpress medium. Samples of exponentially growing cells (OD600=0.5) and of cell at 5h after entry into stationary phase were harvested from every culture. Equal amounts of all four RNAs were pooled and the pool was used as common reference (Cy3-labeld) for the four sample RNAs (Cy3). Thus, in total four hybridizations, one for each sample versus the common reference, were performed.

Project description:The genome sequence is the “blue-print of life”, but proteomics is required to relate this blue-print of life to the actual physiology of living cells. Because of their low complexity – only about 2.000 proteins make a Staphylococcus aureus cell viable – bacteria are excellent model systems to identify the entire protein assembly of a living organism. Many of the studies on physiological proteomics of bacteria, however, still rely on 2D gel-based technologies that visualize only a minor part of the proteome. In this study it will be shown that the majority of proteins expressed in the Gram-positive human pathogen S. aureus can be identified and even quantified by a combination of gel-based and gel-free approaches, the latter having undergone formidable improvements over the last 10 years. S. aureus has been the model of choice for our proteomic studies, because it combines high pathogenicity with increasing antibiotic resistance, which calls for new leads in the development of anti-staphylococcal therapy. On the way towards the entire proteome of S. aureus, we analysed four subproteomic fractions: cytosolic proteins, membrane-bound proteins, cell-surface associated and extracellular proteins, the two latter fractions containing most of the virulence factors. To obtain quantitative results, we compared growing cells and non-growing/stationary phase cells using the 15N metabolic labelling approach. With almost 2.000 proteins, 80 % of the expressed proteome was identified and even quantified in growing and non-growing cells. A comprehensive inventory of the entire protein assembly during the two physiologically distinct states is presented, which integrates data ranging from gene expression to subcellular localization. Three major protein classes were distinguished: (i) Proteins induced in the stationary phase only (ii) Vegetative proteins, no longer synthesized but stable in the stationary phase (iii) Vegetative proteins, no longer required in non-growing cells and finally degraded. This quantitative proteomics approach for growing/non-growing cells, which represents a proof-of-principle for whole-cell physiological proteomics, can now be extended to address particular infection-relevant physiological states. Importantly, the present model study represents the highest coverage of a bacterial proteome so far (except low complexity bacteria). It thus paves the way towards a new understanding of cell physiology and pathophysiology of S. aureus and related pathogenic bacteria, opening a new era in infection-related research on this crucial pathogen.

Project description:<p>The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens.</p> <p>We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.</p>

Project description:Background Small colony variants (SCVs) are slow-growing bacteria, which often show increased resistance to antibiotics and cause latent or recurrent infections. It is therefore important to understand the mechanisms at the basis of this phenotypic switch. Methodology/Principal findings One SCV (termed PAO-SCV) was isolated, showing high resistance to gentamicin and to the cephalosporine cefotaxime. PAO-SCV was prone to reversion as evidenced by emergence of large colonies with a frequency of 10-5 on media without antibiotics while it was stably maintained in presence of gentamicin. PAO-SCV showed a delayed growth, defective motility, and strongly reduced levels of the quorum sensing Pseudomonas quinolone signal (PQS). Whole genome expression analysis further suggested a multi-layered antibiotic resistance mechanism, including simultaneous over-expression of two drug efflux pumps (MexAB-OprM, MexXY-OprM), the LPS modification operon arnBCADTEF, and the PhoP-PhoQ two-component system. Conversely, the genes for the synthesis of PQS were strongly down-regulated in PAOSCV. Finally, genomic analysis revealed the presence of mutations in phoP and phoQ genes as well as in the mexZ gene encoding a repressor of the mexXY and mexABoprM genes. Only one mutation occurred only in REV, at nucleotide 1020 of the tufA gene, a paralog of tufB, both encoding the elongation factor Tu, causing a change of the rarely used aspartic acid codon GAU to the more common GAC, possibly causing an increase of tufA mRNA translation. High expression of phoP and phoQ was confirmed for the SCV variant while the revertant showed expression levels reduced to wild-type levels. Conclusions By combining data coming from phenotypic, gene expression and proteome analysis, we could demonstrate that resistance to aminoglycosides in one SCV mutant is multifactorial including overexpression of efflux mechanisms, LPS modification and is accompanied by a drastic down-regulation of the Pseudomonas quinolone signal quorum sensing system. We used microarrays to study changes in gene expression during early and late stationary phase of SCV and WT strains. SCV and WT cultures were grown in triplicate until early (24h) and late (48h) stationary phase. RNA was extracted, labelled and hybridised on Affymetrix P. aeruginosa expression microarrays.

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Identification of molecular markers involved in glycopeptide resistance of S. aureus

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