Biochemical and Fatty Acids Composition of Water Buffalo (Bubalus Bubalis) Follicular Fluid

Aim of this study was to characterize the biochemical and fatty acids composition of follicular fluid collected from follicles of different sizes and in different phases of ovarian cycle in water buffalo farmed in Italy. Ovaries were collected at slaughterhouse during the breeding season; follicular fluid was aspirated dividing samples in small and large follicles (< 6 mm and > 6 mm respectively) and in luteal and follicular phase. Biochemical analysis and gas-chromatography were performed. Biochemical and fatty acids composition were greatly influenced by both follicular dimension and phase of ovarian cycle. Biochemical composition and its variations were in agreement with previously study conducted in buffalo and other species. This is the first report of the fatty acids composition of buffalo follicular fluid. Twenty-two fatty acids were identified in follicular fluid; nine were saturated fatty acids, six monounsatured fatty acids and seven polyunsatured fatty acids. The most dominant fatty acids were linoleic acid, oleic acid, palmitic acid, stearic acid and arachidonic acid. All the identified fatty acids concentrations vary at least because of follicle dimension or phase, with the exception of γ-linoleic acid and arachidonic acid which concentrations remain stable in all classes

The stealth episome: suppression of gene expression on the excised genomic island PPHGI-1 from Pseudomonas syringae pv. phaseolicola

Pseudomonas syringae pv. phaseolicola is the causative agent of halo blight in the common bean, Phaseolus vulgaris. P. syringae pv. phaseolicola race 4 strain 1302A contains the avirulence gene avrPphB (syn. hopAR1), which resides on PPHGI-1, a 106 kb genomic island. Loss of PPHGI-1 from P. syringae pv. phaseolicola 1302A following exposure to the hypersensitive resistance response (HR) leads to the evolution of strains with altered virulence. Here we have used fluorescent protein reporter systems to gain insight into the mobility of PPHGI-1. Confocal imaging of dual-labelled P. syringae pv. phaseolicola 1302A strain, F532 (dsRFP in chromosome and eGFP in PPHGI-1), revealed loss of PPHGI-1::eGFP encoded fluorescence during plant infection and when grown in vitro on extracted leaf apoplastic fluids. Fluorescence-activated cell sorting (FACS) of fluorescent and non-fluorescent PPHGI-1::eGFP F532 populations showed that cells lost fluorescence not only when the GI was deleted, but also when it had excised and was present as a circular episome. In addition to reduced expression of eGFP, quantitative PCR on sub-populations separated by FACS showed that transcription of other genes on PPHGI-1 (avrPphB and xerC) was also greatly reduced in F532 cells harbouring the excised PPHGI-1::eGFP episome. Our results show how virulence determinants located on mobile pathogenicity islands may be hidden from detection by host surveillance systems through the suppression of gene expression in the episomal state

Biological and structure-activity evaluation of chalcone derivatives against bacteria and fungi

The present work describes the antibacterial and antifungal activities of several chalcones obtained by a straight Claisen-Schmidt aldol condensation determined by the minimal inhibitory concentration against different microorganisms (Gram-positive and Gram-negative bacteria and fungi). Solid state crystal structures of seven chalcones were determined by X-ray diffraction (XRD) analysis. Chemometric studies were carried out in order to identify a potential structure-activity relationship.O presente trabalho descreve as atividades antibacterianas e antifúngicas de diversas chalconas obtidas diretamente através da condensação aldólica tipo Claisen-Schmidt das quais se determinou a concentração inibitória mínima frente a diferentes microrganismos (bactérias Gram-positivas e Gram-negativas e fungos). Estruturas no estado sólido cristalino de sete chalconas foram determinadas por análise de difração de raios X (XRD). Estudos quimiométricos foram realizados com intuito de identificar uma potencial relação entre estrutura e atividade

Genetic Analysis of the Individual Contribution to Virulence of the Type III Effector Inventory of Pseudomonas syringae pv. phaseolicola

Several reports have recently contributed to determine the effector inventory of the sequenced strain Pseudomonas syringae pv. phaseolicola (Pph) 1448a. However, the contribution to virulence of most of these effectors remains to be established. Genetic analysis of the contribution to virulence of individual P. syringae effectors has been traditionally hindered by the lack of phenotypes of the corresponding knockout mutants, largely attributed to a high degree of functional redundancy within their effector inventories. In support of this notion, effectors from Pseudomonas syringae pv. tomato (Pto) DC3000 have been classified into redundant effector groups (REGs), analysing virulence of polymutants in the model plant Nicotiana benthamiana. However, using competitive index (CI) as a virulence assay, we were able to establish the individual contribution of AvrPto1PtoDC3000 to Pto DC3000 virulence in tomato, its natural host, even though typically, contribution to virulence of AvrPto1 is only shown in strains also lacking AvrPtoB (also called HopAB2), a member of its REG. This report raised the possibility that even effectors targeting the same defence signalling pathway may have an individual contribution to virulence, and pointed out to CI assays as the means to establish such a contribution for individual effectors. In this work, we have analysed the individual contribution to virulence of the majority of previously uncharacterised Pph 1448a effectors, by monitoring the development of disease symptoms and determining the CI of single knockout mutants at different stages of growth within bean, its natural host. Despite their potential functional redundancy, we have found individual contributions to virulence for six out of the fifteen effectors analysed. In addition, we have analysed the functional relationships between effectors displaying individual contribution to virulence, highlighting the diversity that these relationships may present, and the interest of analysing their functions within the context of the infection

Sequence-Based Prediction of Type III Secreted Proteins

The type III secretion system (TTSS) is a key mechanism for host cell interaction used by a variety of bacterial pathogens and symbionts of plants and animals including humans. The TTSS represents a molecular syringe with which the bacteria deliver effector proteins directly into the host cell cytosol. Despite the importance of the TTSS for bacterial pathogenesis, recognition and targeting of type III secreted proteins has up until now been poorly understood. Several hypotheses are discussed, including an mRNA-based signal, a chaperon-mediated process, or an N-terminal signal peptide. In this study, we systematically analyzed the amino acid composition and secondary structure of N-termini of 100 experimentally verified effector proteins. Based on this, we developed a machine-learning approach for the prediction of TTSS effector proteins, taking into account N-terminal sequence features such as frequencies of amino acids, short peptides, or residues with certain physico-chemical properties. The resulting computational model revealed a strong type III secretion signal in the N-terminus that can be used to detect effectors with sensitivity of ∼71% and selectivity of ∼85%. This signal seems to be taxonomically universal and conserved among animal pathogens and plant symbionts, since we could successfully detect effector proteins if the respective group was excluded from training. The application of our prediction approach to 739 complete bacterial and archaeal genome sequences resulted in the identification of between 0% and 12% putative TTSS effector proteins. Comparison of effector proteins with orthologs that are not secreted by the TTSS showed no clear pattern of signal acquisition by fusion, suggesting convergent evolutionary processes shaping the type III secretion signal. The newly developed program EffectiveT3 (http://www.chlamydiaedb.org) is the first universal in silico prediction program for the identification of novel TTSS effectors. Our findings will facilitate further studies on and improve our understanding of type III secretion and its role in pathogen–host interactions

Accurate Prediction of Secreted Substrates and Identification of a Conserved Putative Secretion Signal for Type III Secretion Systems

The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates—effector proteins—are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal