Selective Enrichment Media Bias the Types of Salmonella enterica Strains Isolated from Mixed Strain Cultures and Complex Enrichment Broths

For foodborne outbreak investigations it can be difficult to isolate the relevant strain from food and/or environmental sources. If the sample is contaminated by more than one strain of the pathogen the relevant strain might be missed. In this study mixed cultures of Salmonella enterica were grown in one set of standard enrichment media to see if culture bias patterns emerged. Nineteen strains representing four serogroups and ten serotypes were compared in four-strain mixtures in Salmonella-only and in cattle fecal culture enrichment backgrounds using Salmonella enrichment media. One or more strain(s) emerged as dominant in each mixture. No serotype was most fit, but strains of serogroups C2 and E were more likely to dominate enrichment culture mixtures than strains of serogroups B or C1. Different versions of Rappaport-Vassiliadis (RV) medium gave different patterns of strain dominance in both Salmonella-only and fecal enrichment culture backgrounds. The fittest strains belonged to serogroups C1, C2, and E, and included strains of S. Infantis, S. Thompson S. Newport, S. 6,8:d:-, and S. Give. Strains of serogroup B, which included serotypes often seen in outbreaks such as S. Typhimurium, S. Saintpaul, and S. Schwarzengrund were less likely to emerge as dominant strains in the mixtures when using standard RV as part of the enrichment. Using a more nutrient-rich version of RV as part of the protocol led to a different pattern of strains emerging, however some were still present in very low numbers in the resulting population. These results indicate that outbreak investigations of food and/or other environmental samples should include multiple enrichment protocols to ensure isolation of target strains of Salmonella

Mining Virulence Genes Using Metagenomics

When a bacterial genome is compared to the metagenome of an environment it inhabits, most genes recruit at high sequence identity. In free-living bacteria (for instance marine bacteria compared against the ocean metagenome) certain genomic regions are totally absent in recruitment plots, representing therefore genes unique to individual bacterial isolates. We show that these Metagenomic Islands (MIs) are also visible in bacteria living in human hosts when their genomes are compared to sequences from the human microbiome, despite the compartmentalized structure of human-related environments such as the gut. From an applied point of view, MIs of human pathogens (e.g. those identified in enterohaemorragic Escherichia coli against the gut metagenome or in pathogenic Neisseria meningitidis against the oral metagenome) include virulence genes that appear to be absent in related strains or species present in the microbiome of healthy individuals. We propose that this strategy (i.e. recruitment analysis of pathogenic bacteria against the metagenome of healthy subjects) can be used to detect pathogenicity regions in species where the genes involved in virulence are poorly characterized. Using this approach, we detect well-known pathogenicity islands and identify new potential virulence genes in several human pathogens

Dichotomous factor analysis of symptoms reported by UK and US veterans of the 1991 Gulf War

BACKGROUND: Factor analysis is one of the most used statistical techniques to analyze the inter-relationships among symptoms reported by Gulf War veterans. The objective of this study was to apply factor analyses to binary symptom data from the UK study of Gulf War illness and the US Air Force study of Gulf War veterans, and to compare the symptom domains derived from the distinct samples. METHODS: UK veterans of the 1991 Gulf War (n = 3,454), individuals deployed to Bosnia on U.N. peacekeeping operations (n = 1,979) and Gulf War-era servicemen (n = 2,577) who were not deployed to the Gulf were surveyed in 1997–1998, and US 1991 Gulf War veterans from four Air Force units (n = 1,163) were surveyed in 1995 to collect health characteristics including symptoms. Each sample was randomly split in half for exploratory and confirmatory dichotomous factor analyses with promax oblique rotation. RESULTS: Four correlated factors were identified in each of the samples. Three factors (Respiratory, Mood-Cognition, Peripheral Nervous) overlapped considerably across the UK cohorts. The Gastrointestinal/Urogenital factor in the UK Gulf cohort was noticeably different from the Gastrointestinal factor identified from the Bosnia and Era cohorts. Symptoms from Gulf War UK and U.S cohorts yielded similar Gastrointestinal, Respiratory and Mood-Cognition factors, despite differences in symptom inventories between the two surveys. A Musculoskeletal factor was only elicited from the US Gulf sample. CONCLUSION: Findings of this report are consistent with those from other factor analysis studies that identified similar symptom dimensions between Gulf and non-Gulf War veterans, except that the Gastrointestinal factor in Gulf veterans included other symptom types. Correlations among factors raise the question as to whether there is a general illness, even if not unique to Gulf veterans, representing the common pathway underlying the identified factors. Hierarchical factor analysis models may be useful to address this issue

A gene frequency model for QTL mapping using Bayesian inference

<p>Abstract</p> <p>Background</p> <p>Information for mapping of quantitative trait loci (QTL) comes from two sources: linkage disequilibrium (non-random association of allele states) and cosegregation (non-random association of allele origin). Information from LD can be captured by modeling conditional means and variances at the QTL given marker information. Similarly, information from cosegregation can be captured by modeling conditional covariances. Here, we consider a Bayesian model based on gene frequency (BGF) where both conditional means and variances are modeled as a function of the conditional gene frequencies at the QTL. The parameters in this model include these gene frequencies, additive effect of the QTL, its location, and the residual variance. Bayesian methodology was used to estimate these parameters. The priors used were: logit-normal for gene frequencies, normal for the additive effect, uniform for location, and inverse chi-square for the residual variance. Computer simulation was used to compare the power to detect and accuracy to map QTL by this method with those from least squares analysis using a regression model (LSR).</p> <p>Results</p> <p>To simplify the analysis, data from unrelated individuals in a purebred population were simulated, where only LD information contributes to map the QTL. LD was simulated in a chromosomal segment of 1 cM with one QTL by random mating in a population of size 500 for 1000 generations and in a population of size 100 for 50 generations. The comparison was studied under a range of conditions, which included SNP density of 0.1, 0.05 or 0.02 cM, sample size of 500 or 1000, and phenotypic variance explained by QTL of 2 or 5%. Both 1 and 2-SNP models were considered. Power to detect the QTL for the BGF, ranged from 0.4 to 0.99, and close or equal to the power of the regression using least squares (LSR). Precision to map QTL position of BGF, quantified by the mean absolute error, ranged from 0.11 to 0.21 cM for BGF, and was better than the precision of LSR, which ranged from 0.12 to 0.25 cM.</p> <p>Conclusions</p> <p>In conclusion given a high SNP density, the gene frequency model can be used to map QTL with considerable accuracy even within a 1 cM region.</p

Different Human Copper-Zinc Superoxide Dismutase Mutants, SOD1G93A and SOD1H46R, Exert Distinct Harmful Effects on Gross Phenotype in Mice

Amyotrophic lateral sclerosis (ALS) is a heterogeneous group of fatal neurodegenerative diseases characterized by a selective loss of motor neurons in the brain and spinal cord. Creation of transgenic mice expressing mutant Cu/Zn superoxide dismutase (SOD1), as ALS models, has made an enormous impact on progress of the ALS studies. Recently, it has been recognized that genetic background and gender affect many physiological and pathological phenotypes. However, no systematic studies focusing on such effects using ALS models other than SOD1G93A mice have been conducted. To clarify the effects of genetic background and gender on gross phenotypes among different ALS models, we here conducted a comparative analysis of growth curves and lifespans using congenic lines of SOD1G93A and SOD1H46R mice on two different genetic backgrounds; C57BL/6N (B6) and FVB/N (FVB). Copy number of the transgene and their expression between SOD1G93A and SOD1H46R lines were comparable. B6 congenic mutant SOD1 transgenic lines irrespective of their mutation and gender differences lived longer than corresponding FVB lines. Notably, the G93A mutation caused severer disease phenotypes than did the H46R mutation, where SOD1G93A mice, particularly on a FVB background, showed more extensive body weight loss and earlier death. Gender effect on survival also solely emerged in FVB congenic SOD1G93A mice. Conversely, consistent with our previous study using B6 lines, lack of Als2, a murine homolog for the recessive juvenile ALS causative gene, in FVB congenic SOD1H46R, but not SOD1G93A, mice resulted in an earlier death, implying a genetic background-independent but mutation-dependent phenotypic modification. These results indicate that SOD1G93A- and SOD1H46R-mediated toxicity and their associated pathogenic pathways are not identical. Further, distinctive injurious effects resulted from different SOD1 mutations, which are associated with genetic background and/or gender, suggests the presence of several genetic modifiers of disease expression in the mouse genome

How does one become spiritual? The Spiritual Modeling Inventory of Life Environments (SMILE)

We report psychometric properties, correlates and underlying theory of the Spiritual Modeling Index of Life Environments (SMILE), a measure of perceptions of spiritual models, defined as everyday and prominent people who have functioned for respondents as exemplars of spiritual qualities, such as compassion, self-control, or faith. Demographic, spiritual, and personality correlates were examined in an ethnically diverse sample of college students from California, Connecticut, and Tennessee (N=1010). A summary measure of model influence was constructed from perceived models within family, school, religious organization, and among prominent individuals from both tradition and media. The SMILE, based on concepts from Bandura\u27s (1986) Social Cognitive Theory, was well-received by respondents. The summary measure demonstrated good 7-week test/retest reliability (r=.83); patterns of correlation supporting convergent, divergent, and criterion-related validity; demographic differences in expected directions; and substantial individual heterogeneity. Implications are discussed for further research and for pastoral, educational, and health-focused interventions

Genome-wide mapping of Quantitative Trait Loci for fatness, fat cell characteristics and fat metabolism in three porcine F2 crosses

<p>Abstract</p> <p>Background</p> <p>QTL affecting fat deposition related performance traits have been considered in several studies and mapped on numerous porcine chromosomes. However, activity of specific enzymes, protein content and cell structure in fat tissue probably depend on a smaller number of genes than traits related to fat content in carcass. Thus, in this work traits related to metabolic and cytological features of back fat tissue and fat related performance traits were investigated in a genome-wide QTL analysis. QTL similarities and differences were examined between three F₂crosses, and between male and female animals.</p> <p>Methods</p> <p>A total of 966 F₂animals originating from crosses between Meishan (M), Pietrain (P) and European wild boar (W) were analysed for traits related to fat performance (11), enzymatic activity (9) and number and volume of fat cells (20). Per cross, 216 (M × P), 169 (W × P) and 195 (W × M) genome-wide distributed marker loci were genotyped. QTL mapping was performed separately for each cross in steps of 1 cM and steps were reduced when the distance between loci was shorter. The additive and dominant components of QTL positions were detected stepwise by using a multiple position model.</p> <p>Results</p> <p>A total of 147 genome-wide significant QTL (76 at P < 0.05 and 71 at P < 0.01) were detected for the three crosses. Most of the QTL were identified on SSC1 (between 76-78 and 87-90 cM), SSC7 (predominantly in the MHC region) and SSCX (in the vicinity of the gene <it>CAPN6</it>). Additional genome-wide significant QTL were found on SSC8, 12, 13, 14, 16, and 18. In many cases, the QTL are mainly additive and differ between F₂crosses. Many of the QTL profiles possess multiple peaks especially in regions with a high marker density. Sex specific analyses, performed for example on SSC6, SSC7 and SSCX, show that for some traits the positions differ between male and female animals. For the selected traits, the additive and dominant components that were analysed for QTL positions on different chromosomes, explain in combination up to 23% of the total trait variance.</p> <p>Conclusions</p> <p>Our results reveal specific and partly new QTL positions across genetically diverse pig crosses. For some of the traits associated with specific enzymes, protein content and cell structure in fat tissue, it is the first time that they are included in a QTL analysis. They provide large-scale information to analyse causative genes and useful data for the pig industry.</p

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente