45 research outputs found
Comparison of methods for the detection of biofilm production in coagulase-negative staphylococci
<p>Abstract</p> <p>Background</p> <p>The ability of biofilm formation seems to play an essential role in the virulence of coagulase-negative staphylococci (CNS). The most clearly characterized component of staphylococcal biofilms is the polysaccharide intercellular adhesin (PIA) encoded by the <it>icaADBC </it>operon. Biofilm production was studied in 80 coagulase-negative staphylococci (CNS) strains isolated from clinical specimens of newborns with infection hospitalized at the Neonatal Unit of the University Hospital, Faculty of Medicine of Botucatu, and in 20 isolates obtained from the nares of healthy individuals without signs of infection. The objective was to compare three phenotypic methods with the detection of the <it>icaA</it>, <it>icaD </it>and <it>icaC </it>genes by PCR.</p> <p>Findings</p> <p>Among the 100 CNS isolates studied, 82% tested positive by PCR, 82% by the tube test, 81% by the TCP assay, and 73% by the CRA method. Using PCR as a reference, the tube test showed the best correlation with detection of the <it>ica </it>genes, presenting high sensitivity and specificity.</p> <p>Conclusions</p> <p>The tube adherence test can be indicated for the routine detection of biofilm production in CNS because of its easy application and low cost and because it guarantees reliable results with excellent sensitivity and specificity.</p
Association and interaction of PPAR-complex gene variants with latent traits of left ventricular diastolic function
<p>Abstract</p> <p>Background</p> <p>Abnormalities in myocardial metabolism and/or regulatory genes have been implicated in left ventricular systolic dysfunction. However, the extent to which these modulate left ventricular diastolic function (LVDF) is uncertain.</p> <p>Methods</p> <p>Independent component analysis was applied to extract latent LVDF traits from 14 measured echocardiography-derived endophenotypes of LVDF in 403 Caucasians. Genetic association was assessed between measured and latent LVDF traits and 64 single nucleotide polymorphisms (SNPs) in three peroxisome proliferator-activated receptor <it>(PPAR)</it>-complex genes involved in the transcriptional regulation of fatty acid metabolism.</p> <p>Results</p> <p>By linear regression analysis, 7 SNPs (4 in <it>PPARA</it>, 2 in <it>PPARGC1A</it>, 1 in <it>PPARG</it>) were significantly associated with the latent LVDF trait, whereas a range of 0-4 SNPs were associated with each of the 14 measured echocardiography-derived endophenotypes. Frequency distribution of <it>P </it>values showed a greater proportion of significant associations with the latent LVDF trait than for the measured endophenotypes, suggesting that analyses of the latent trait improved detection of the genetic underpinnings of LVDF. Ridge regression was applied to investigate within-gene and gene-gene interactions. In the within-gene analysis, there were five significant pair-wise interactions in <it>PPARGC1A </it>and none in <it>PPARA </it>or <it>PPARG</it>. In the gene-gene analysis, significant interactions were found between rs4253655 in <it>PPARA </it>and rs1873532 (p = 0.02) and rs7672915 (p = 0.02), both in <it>PPARGC1A</it>, and between rs1151996 in <it>PPARG </it>and rs4697046 in <it>PPARGC1A </it>(p = 0.01).</p> <p>Conclusions</p> <p>Myocardial metabolism <it>PPAR</it>-complex genes, including within and between genes interactions, may play an important role modulating left ventricular diastolic function.</p
Expression variability of co-regulated genes differentiates Saccharomyces cerevisiae strains
Background: Saccharomyces cerevisiae (Baker’s yeast) is found in diverse ecological niches and is characterized by
high adaptive potential under challenging environments. In spite of recent advances on the study of yeast
genome diversity, little is known about the underlying gene expression plasticity. In order to shed new light onto
this biological question, we have compared transcriptome profiles of five environmental isolates, clinical and
laboratorial strains at different time points of fermentation in synthetic must medium, during exponential and
stationary growth phases.
Results: Our data unveiled diversity in both intensity and timing of gene expression. Genes involved in glucose
metabolism and in the stress response elicited during fermentation were among the most variable. This gene
expression diversity increased at the onset of stationary phase (diauxic shift). Environmental isolates showed lower
average transcript abundance of genes involved in the stress response, assimilation of nitrogen and vitamins, and
sulphur metabolism, than other strains. Nitrogen metabolism genes showed significant variation in expression
among the environmental isolates.
Conclusions: Wild type yeast strains respond differentially to the stress imposed by nutrient depletion, ethanol
accumulation and cell density increase, during fermentation of glucose in synthetic must medium. Our results
support previous data showing that gene expression variability is a source of phenotypic diversity among closely
related organisms.Fundação para a Ciência e TecnologiaThe authors wish to thank Adega Cooperativa da Bairrada, Cantanhede,
Portugal, for providing the commercial strains
Functional traits driving species role in the structure of terrestrial vertebrate scavenger networks
Species assemblages often have a non-random nested organization, which in vertebrate scavenger (carrion-consuming) assemblages is thought to be driven by facilitation in competitive environments. However, not all scavenger species play the same role in maintaining assemblage structure, as some species are obligate scavengers (i.e., vultures) and others are facultative, scavenging opportunistically. We used a database with 177 vertebrate scavenger species from 53 assemblages in 22 countries across five continents to identify which functional traits of scavenger species are key to maintaining the scavenging network structure. We used network analyses to relate ten traits hypothesized to affect assemblage structure with the role of each species in the scavenging assemblage in which it appeared. We characterized the role of a species in terms of both the proportion of monitored carcasses on which that species scavenged, or scavenging breadth (i.e., the species normalized degree), and the role of that species in the nested structure of the assemblage (i.e., the species paired nested degree), therefore identifying possible facilitative interactions among species. We found that species with high olfactory acuity, social foragers, and obligate scavengers had the widest scavenging breadth. We also found that social foragers had a large paired nested degree in scavenger assemblages, probably because their presence is easier to detect by other species to signal carcass occurrence. Our study highlights differences in the functional roles of scavenger species and can be used to identify key species for targeted conservation to maintain the ecological function of scavenger assemblages
Integrated Genome-Scale Prediction of Detrimental Mutations in Transcription Networks
A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or “edge”) rather than a gene (or “node”) in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy) associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism