Comparative Exoproteome Analysis of Streptococcus suis Human Isolates

The swine pathogen Streptococcus suis is a Gram-positive bacterium which causes infections in pigs, with an impact in animal health and in the livestock industry, and it is also an important zoonotic agent. During the infection process, surface and secreted proteins are essential in the interaction between microorganisms and their hosts. Here, we report a comparative proteomic analysis of the proteins released to the extracellular milieu in six human clinical isolates belonging to the highly prevalent and virulent serotype 2. The total secreted content was precipitated and analyzed by GeLC-MS/MS. In the six strains, 144 proteins assigned to each of the categories of extracellular or surface proteins were identified, as well as 680 predicted cytoplasmic proteins, many of which are putative moonlighting proteins. Of the nine predicted signal peptide-I secreted proteins, seven had relevant antigenic potential when they were analyzed through bioinformatic analysis. This is the first work comparing the exoproteome fraction of several human isolates of this important pathogen

Sesión de Proteómica microbiana y de parásitos S.O.S., ¿nos podéis ayudar?

Comunicaciones a congreso

Métodos de enriquecimiento de glicoproteínas bacterianas para su posterior análisis y caracterización mediante espectrometría de masas

Comunicaciones a congreso

Approaching In Vivo Models of Pneumococcus–Host Interaction: Insights into Surface Proteins, Capsule Production, and Extracellular Vesicles

Infections caused by the Gram-positive bacterium Streptococcus pneumoniae have become a major health problem worldwide because of their high morbidity and mortality rates, especially in developing countries. This microorganism colonizes the human upper respiratory tract and becomes pathogenic under certain circumstances, which are not well known. In the interaction with the host, bacterial surface structures and proteins play major roles. To gain knowledge into gradual changes and adaptive mechanisms that this pathogen undergoes from when it enters the host, we mimicked several in vivo situations representing interaction with epithelial and macrophage cells, as well as a condition of presence in blood. Then, we analyzed, in four pneumococcal strains, two major surface structures, the capsule and extracellular vesicles produced by the pneumococci, as well as surface proteins by proteomics, using the “shaving” approach, followed by LC-MS/MS. We found important differences in both surface ultrastructures and proteins among the culture conditions and strains used. Thus, this work provides insights into physiological adaptations of the pneumococcus when it interacts with the host, which may be useful for the design of strategies to combat infections caused by this pathogen

Overcoming function annotation errors in the Gram-positive pathogen Streptococcus suis by a proteomics-driven approach

Background: Annotation of protein-coding genes is a key step in sequencing projects. Protein functions are mainly assigned on the basis of the amino acid sequence alone by searching of homologous proteins. However, fully automated annotation processes often lead to wrong prediction of protein functions, and therefore time-intensive manual curation is often essential. Here we describe a fast and reliable way to correct function annotation in sequencing projects, focusing on surface proteomes. We use a proteomics approach, previously proven to be very powerful for identifying new vaccine candidates against Gram-positive pathogens. It consists of shaving the surface of intact cells with two proteases, the specific cleavage-site trypsin and the unspecific proteinase K, followed by LC/MS/MS analysis of the resulting peptides. The identified proteins are contrasted by computational analysis and their sequences are inspected to correct possible errors in function prediction. Results: When applied to the zoonotic pathogen Streptococcus suis, of which two strains have been recently sequenced and annotated, we identified a set of surface proteins without cytoplasmic contamination: all the proteins identified had exporting or retention signals towards the outside and/or the cell surface, and viability of protease-treated cells was not affected. The combination of both experimental evidences and computational methods allowed us to determine that two of these proteins are putative extracellular new adhesins that had been previously attributed a wrong cytoplasmic function. One of them is a putative component of the pilus of this bacterium. Conclusion: We illustrate the complementary nature of laboratory-based and computational methods to examine in concert the localization of a set of proteins in the cell, and demonstrate the utility of this proteomics-based strategy to experimentally correct function annotation errors in sequencing projects. This approach also contributes to provide strong experimental evidences that can be used to annotate those proteins for which a Gene Ontology (GO) term has not been assigned so far. Function annotation correction would then improve the identification of surfaceassociated proteins in bacterial pathogens, thus accelerating the discovery of new vaccines in infectious disease research

Calibración de sensores de humedad capacitivos usando redes neuronales

X Jornadas de Investigación de la Zona no Saturada del Suelo, Salamanca (España), 2011El estudio de la variabilidad espacial de la humedad del suelo a escala de parcela o cuenca agrícola requiere el uso de redes de sensores de humedad de bajo coste, que suelen mostrar una fiabilidad limitada y requieren de calibraciones específicas, especialmente en suelos con elevados contenidos en arcilla. El presente trabajo pretende plantear una calibración más fiable de sondas de humedad mediante un análisis mixto campo-laboratorio. Para la calibración de campo se dispone de datos gravimétricos; para la calibración en laboratorio se han usado columnas de suelo inalterado que tras ser saturadas fueron desecadas en un entorno controlado mientras se monitorizaba la evolución de su peso y la de su humedad volumétrica, medida con diferentes sondas capacitivas Decagon. Tras obtener curvas de secado y la relación entre la humedad gravimétrica y la volumétrica es posible realizar una calibración mejorada específica para cada tipo de suelo. Las redes neuronales son particularmente útiles para el modelado de procesos físicos y el ajuste de modelos. En este trabajo se propone el empleo de dichas herramientas para obtener calibraciones para las sondas analizadas en el tipo de suelo objeto de estudio. Los resultados muestran que dichas calibraciones permiten mejorar la precisión de las mediciones de humedad realizadas.The study of the spatial variability of soil water content at agricultural plot or catchment scales requires the use of low-cost soil water content sensor networks, which usually show a limited reliability and require specific calibrations, specially for soils with a high clay content. This work proposes a more reliable calibration of soil water content probes with a laboratory analysis. Minimally disturbed soil columns were saturated with water and dried in a controlled environment while monitorizing the evolution of their volumetric soil water content (with different capacitive Decagon Probes) and weights. After obtaining the drying curves and the relation between the volumetric and the measured gravimetric soil water contents it is possible to achieve an improved calibration specific for different kinds of soil. Neural networks are especially interesting for the modeling of physical processes and model adjustment. In this work, these tools were used in order to obtain improved calibrations for the analyzed probes in the studied soil type. Results show that this calibration improves the accuracy and pMinisterio de Ciencia e Innovación AGL2009 C03-03Junta de Andalucía AGR-478

Optimization of digestion of living cells of streptococcus pneumoniae for searching protein vaccine candidates

Comunicaciones a congreso

Identification of Potential New Protein Vaccine Candidates through Pan-Surfomic Analysis of Pneumococcal Clinical Isolates from Adults

Purified polysaccharide and conjugate vaccines are widely used for preventing infections in adults and in children against the Gram-positive bacterium Streptococcus pneumoniae, a pathogen responsible for high morbidity and mortality rates, especially in developing countries. However, these polysaccharide-based vaccines have some important limitations, such as being serotype-dependent, being subjected to losing efficacy because of serotype replacement and high manufacturing complexity and cost. It is expected that protein-based vaccines will overcome these issues by conferring a broad coverage independent of serotype and lowering production costs. In this study, we have applied the ‘‘shaving’’ proteomic approach, consisting of the LC/MS/MS analysis of peptides generated by protease treatment of live cells, to a collection of 16 pneumococcal clinical isolates from adults, representing the most prevalent strains circulating in Spain during the last years. The set of unique proteins identified in all the isolates, called ‘‘pan-surfome’’, consisted of 254 proteins, which included most of the protective protein antigens reported so far. In search of new candidates with vaccine potential, we identified 32 that were present in at least 50% of the clinical isolates analyzed. We selected four of them (Spr0012, Spr0328, Spr0561 and SP670_2141), whose protection capacity has not yet been tested, for assaying immunogenicity in human sera. All of them induced the production of IgM antibodies in infected patients, thus indicating that they could enter the pipeline for vaccine studies. The pan-surfomic approach shows its utility in the discovery of new proteins that can elicit protection against infectious microorganisms

Characterization of the Burkholderia cenocepacia J2315 Surface-Exposed Immunoproteome

Infections by the Burkholderia cepacia complex (Bcc) remain seriously life threatening to cystic fibrosis (CF) patients, and no effective eradication is available. A vaccine to protect patients against Bcc infections is a highly attractive therapeutic option, but none is available. A strategy combining the bioinformatics identification of putative surface-exposed proteins with an experimental approach encompassing the “shaving” of surface-exposed proteins with trypsin followed by peptide identification by liquid chromatography and mass spectrometry is here reported. The methodology allowed the bioinformatics identification of 263 potentially surface-exposed proteins, 16 of them also experimentally identified by the “shaving” approach. Of the proteins identified, 143 have a high probability of containing B-cell epitopes that are surface-exposed. The immunogenicity of three of these proteins was demonstrated using serum samples from Bcc-infected CF patients and Western blotting, validating the usefulness of this methodology in identifying potentially immunogenic surface-exposed proteins that might be used for the development of Bcc-protective vaccines