The freshwater Sponge Ephydatia Fluviatilis harbours diverse pseudomonas species (Gammaproteobacteria, Pseudomonadales) with broad-spectrum antimicrobial activity

Bacteria are believed to play an important role in the fitness and biochemistry of sponges (Porifera). Pseudomonas species (Gammaproteobacteria, Pseudomonadales) are capable of colonizing a broad range of eukaryotic hosts, but knowledge of their diversity and function in freshwater invertebrates is rudimentary. We assessed the diversity, structure and antimicrobial activities of Pseudomonas spp. in the freshwater sponge Ephydatia fluviatilis. Polymerase Chain Reaction - Denaturing Gradient Gel Electrophoresis (PCR-DGGE) fingerprints of the global regulator gene gacA revealed distinct structures between sponge-associated and free-living Pseudomonas communities, unveiling previously unsuspected diversity of these assemblages in freshwater. Community structures varied across E. fluviatilis specimens, yet specific gacA phylotypes could be detected by PCR-DGGE in almost all sponge individuals sampled over two consecutive years. By means of whole-genome fingerprinting, 39 distinct genotypes were found within 90 fluorescent Pseudomonas isolates retrieved from E. fluviatilis. High frequency of in vitro antibacterial (49%), antiprotozoan (35%) and anti-oomycetal (32%) activities was found among these isolates, contrasting less-pronounced basidiomycetal (17%) and ascomycetal (8%) antagonism. Culture extracts of highly predation-resistant isolates rapidly caused complete immobility or lysis of cells of the protozoan Colpoda steinii. Isolates tentatively identified as P. jessenii, P. protegens and P. oryzihabitans showed conspicuous inhibitory traits and correspondence with dominant sponge-associated phylotypes registered by cultivation-independent analysis. Our findings suggest that E. fluviatilis hosts both transient and persistent Pseudomonas symbionts displaying antimicrobial activities of potential ecological and biotechnological value.European Regional Development Fund (ERDF) through the COMPETE (Operational Competitiveness Programme); national funds through FCT (Foundation for Science and Technology) [PEst-C/MAR/LA0015/2011]; FCT-funded project [PTDC/BIA-MIC/3865/2012]; Federation of European Microbiological Societies (FEMS)info:eu-repo/semantics/publishedVersio

Fusogenic Variants of a Noncytopathic Paramyxovirus

SER virus is a type 5 parainfluenza virus that does not exhibit syncytium formation, in contrast to most other paramyxoviruses. This property has been attributed, at least in part, to the presence of an extension of the cytoplasmic tail (CT) of the SER F protein, as truncations or mutations of this region resulted in enhanced fusion. In this study we used repeated passage to select for mutant SER viruses, which were found to be fusogenic. The mutant viruses replicated at levels comparable to or higher than the wild-type SER virus and caused plaque formation, in contrast to the wild-type virus which does not form plaques. The mutants differed strikingly in their plaque sizes. The F genes of mutant viruses were cloned and sequenced and shared some mutations, including a proline-to-leucine change at position 22 and an isoleucine-to-leucine substitution at position 191; other changes that were specific to each mutant were also found. The HN proteins of mutant viruses also showed mutations spanning the length of the protein whereas the M protein showed a consistent mutation, threonine to isoleucine, at position 129. The structure of the F protein was used to identify residues involved in the mutant phenotypes in terms of their location and proximity to heptad repeat domains

xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data

<p>Abstract</p> <p>Background</p> <p>Detection of low abundance metabolites is important for de novo mapping of metabolic pathways related to diet, microbiome or environmental exposures. Multiple algorithms are available to extract <it>m/z</it> features from liquid chromatography-mass spectral data in a conservative manner, which tends to preclude detection of low abundance chemicals and chemicals found in small subsets of samples. The present study provides software to enhance such algorithms for feature detection, quality assessment, and annotation.</p> <p>Results</p> <p>xMSanalyzer is a set of utilities for automated processing of metabolomics data. The utilites can be classified into four main modules to: 1) improve feature detection for replicate analyses by systematic re-extraction with multiple parameter settings and data merger to optimize the balance between sensitivity and reliability, 2) evaluate sample quality and feature consistency, 3) detect feature overlap between datasets, and 4) characterize high-resolution <it>m/z</it> matches to small molecule metabolites and biological pathways using multiple chemical databases. The package was tested with plasma samples and shown to more than double the number of features extracted while improving quantitative reliability of detection. MS/MS analysis of a random subset of peaks that were exclusively detected using xMSanalyzer confirmed that the optimization scheme improves detection of real metabolites.</p> <p>Conclusions</p> <p>xMSanalyzer is a package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. The program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.</p