Microbial communities in sediment from Zostera marina patches, but not the Z. marina leaf or root microbiomes, vary in relation to distance from patch edge

© 2017 Ettinger et al. Background. Zostera marina (also known as eelgrass) is a foundation species in coastal and marine ecosystems worldwide and is a model for studies of seagrasses (a paraphyletic group in the order Alismatales) that include all the known fully submerged marine angiosperms. In recent years, there has been a growing appreciation of the potential importance of the microbial communities (i.e., microbiomes) associated with various plant species. Here we report a study of variation in Z. marina microbiomes from a field site in Bodega Bay, CA. Methods. We characterized and then compared the microbial communities of root, leaf and sediment samples (using 16S ribosomal RNA gene PCR and sequencing) and associated environmental parameters from the inside, edge and outside of a single subtidal Z. marina patch. Multiple comparative approaches were used to examine associations between microbiome features (e.g., diversity, taxonomic composition) and environmental parameters and to compare sample types and sites. Results. Microbial communities differed significantly between sample types (root, leaf and sediment) and in sediments from different sites (inside, edge, outside). Carbon:Nitrogen ratio and eelgrass density were both significantly correlated to sediment community composition. Enrichment of certain taxonomic groups in each sample type was detected and analyzed in regard to possible functional implications (especially regarding sulfur metabolism). Discussion. Our results are mostly consistent with prior work on seagrass associated microbiomes with a few differences and additional findings. From a functional point of view, the most significant finding is that many of the taxa that differ significantly between sample types and sites are closely related to ones commonly associated with various aspects of sulfur and nitrogen metabolism. Though not a traditional model organism, we believe that Z. marina can become a model for studies of marine plantmicrobiome interactions

Transmission Shifts Underlie Variability in Population Responses to Yersinia pestis Infection

Host populations for the plague bacterium, Yersinia pestis, are highly variable in their response to plague ranging from near deterministic extinction (i.e., epizootic dynamics) to a low probability of extinction despite persistent infection (i.e., enzootic dynamics). Much of the work to understand this variability has focused on specific host characteristics, such as population size and resistance, and their role in determining plague dynamics. Here, however, we advance the idea that the relative importance of alternative transmission routes may vary causing shifts from epizootic to enzootic dynamics. We present a model that incorporates host and flea ecology with multiple transmission hypotheses to study how transmission shifts determine population responses to plague. Our results suggest enzootic persistence relies on infection of an off-host flea reservoir and epizootics rely on transiently maintained flea infection loads through repeated infectious feeds by fleas. In either case, early-phase transmission by fleas (i.e., transmission immediately following an infected blood meal) has been observed in laboratory studies, and we show that it is capable of driving plague dynamics at the population level. Sensitivity analysis of model parameters revealed that host characteristics (e.g., population size and resistance) vary in importance depending on transmission dynamics, suggesting that host ecology may scale differently through different transmission routes enabling prediction of population responses in a more robust way than using either host characteristics or transmission shifts alone

Variable strength of forest stand attributes and weather conditions on the questing activity of Ixodes ricinus ticks over years in managed forests

Given the ever-increasing human impact through land use and climate change on the environment, we crucially need to achieve a better understanding of those factors that influence the questing activity of ixodid ticks, a major disease-transmitting vector in temperate forests. We investigated variation in the relative questing nymph densities of Ixodes ricinus in differently managed forest types for three years (2008–2010) in SW Germany by drag sampling. We used a hierarchical Bayesian modeling approach to examine the relative effects of habitat and weather and to consider possible nested structures of habitat and climate forces. The questing activity of nymphs was considerably larger in young forest successional stages of thicket compared with pole wood and timber stages. Questing nymph density increased markedly with milder winter temperatures. Generally, the relative strength of the various environmental forces on questing nymph density differed across years. In particular, winter temperature had a negative effect on tick activity across sites in 2008 in contrast to the overall effect of temperature across years. Our results suggest that forest management practices have important impacts on questing nymph density. Variable weather conditions, however, might override the effects of forest management practices on the fluctuations and dynamics of tick populations and activity over years, in particular, the preceding winter temperatures. Therefore, robust predictions and the detection of possible interactions and nested structures of habitat and climate forces can only be quantified through the collection of long-term data. Such data are particularly important with regard to future scenarios of forest management and climate warming

The Implementation and Evaluation of a Media Literacy Intervention About PAES Use in Sport Science Students

With respect to both competitive and amateur/fitness sports, media may strongly influence young people’s opinions and behaviors concerning the use of PAES (Performance and Appearance Enhancing Substances). The present investigation addressed this topic by focusing on sport sciences students’ beliefs concerning the possible role of media related to the implementation and evaluation of a PAES-focus media literacy intervention conducted with sport science students. This study relied on a sample of 521 students (attrition rate 10.3%) (45.1% female, mean age = 22.6, SD = 2.20), which provided baseline data on students’ levels of media literacy concerning the use of PAES (i.e. “descriptive sample”), and a sample of 248 students, who participated in and provided data on the media literacy intervention. This latter sample included a group of 128 students (44.5% female, mean age = 23.03, SD = 3.76) who actively participated in the intervention (i.e. “intervention group”), and a group of 120 students who did not (i.e. “control group”, 53.3% female, mean age = 22.25, SD = 2.47). All students filled out media literacy questionnaires targeting students’ awareness of media influence, their views about the realism of media content, their sense of confidence in dealing with media messages, and their positive attitudes toward PAES use. Analyses of questionnaire data showed that students are relatively aware of media influence on people’s views and behaviors with respect to PAES use. At the same time, students also believed that young people do not consider media as “realistic sources” of information; nonetheless, they also did not consider themselves entirely capable of dealing effectively with media messages. With respect to the intervention, students overall appreciated and greatly welcomed the educational program on media literacy, and the analyses of intervention data across intervention and control groups showed that key media literacy variables changed over time, attesting to the overall effectiveness of the intervention.Ministry of Health, Italy CUPB86G17000660005 2017-

Networks link antigenic and receptor-binding sites of influenza hemagglutinin: Mechanistic insight into fitter strain propagation

Influenza viral passaging through pre-vaccinated mice shows that emergent antigenic site mutations on the viral hemagglutinin (HA) impact host receptor-binding affinity and, therefore, the evolution of fitter influenza strains. To understand this phenomenon, we computed the Significant Interactions Network (SIN) for each residue and mapped the networks of antigenic site residues on a representative H1N1 HA. Specific antigenic site residues are ‘linked’ to receptor-binding site (RBS) residues via their SIN and mutations within “RBS-linked” antigenic residues can significantly influence receptor-binding affinity by impacting the SIN of key RBS residues. In contrast, other antigenic site residues do not have such “RBS-links” and do not impact receptor-binding affinity upon mutation. Thus, a potential mechanism emerges for how immunologic pressure on RBS-linked antigenic residues can contribute to evolution of fitter influenza strains by modulating the host receptor-binding affinity

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

<p>Abstract</p> <p>Background</p> <p>The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions.</p> <p>Results</p> <p>In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification.</p> <p>Conclusion</p> <p>High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.</p

Multiple Oncogenic Pathway Signatures Show Coordinate Expression Patterns in Human Prostate Tumors

BACKGROUND: Gene transcription patterns associated with activation of oncogenes Myc, c-Src, beta-catenin, E2F3, H-Ras, HER2, EGFR, MEK, Raf, MAPK, Akt, and cyclin D1, as well as of the cell cycle and of androgen signaling have been generated in previous studies using experimental models. It was not clear whether genes in these "oncogenic signatures" would show coordinate expression patterns in human prostate tumors, particularly as most of the signatures were derived from cell types other than prostate. PRINCIPAL FINDINGS: The above oncogenic pathway signatures were examined in four different gene expression profile datasets of human prostate tumors (representing approximately 250 patients in all), using both Q1-Q2 and one-sided Fisher's exact enrichment analysis methods. A significant fraction (approximately 5%) of genes up-regulated experimentally by Myc, c-Src, HER2, Akt, or androgen were co-expressed in human tumors with the oncogene or biomarker corresponding to the pathway signature. Genes down-regulated experimentally, however, did not show anticipated patterns of anti-enrichment in the human tumors. CONCLUSIONS: Significant subsets of the genes in these experimentally-derived oncogenic signatures are relevant to the study of human prostate cancer. Both molecular biologists and clinical researchers could focus attention on the relatively small number of genes identified here as having coordinate patterns that arise from both the experimental system and the human disease system

Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data

<p>Abstract</p> <p>Background</p> <p>Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differentially expressed in time-course data, measured between different biological conditions. These differentially expressed genes can reveal the changes in biological process due to the change in condition which is essential to understand differences in dynamics.</p> <p>Results</p> <p>In this paper, we propose a novel method for finding differentially expressed genes in time-course data and across biological conditions (say <it>C</it>₁and <it>C</it>₂). We model the expression at <it>C</it>₁using Principal Component Analysis and represent the expression profile of each gene as a linear combination of the dominant Principal Components (PCs). Then the expression data from <it>C</it>₂is projected on the developed PCA model and scores are extracted. The difference between the scores is evaluated using a hypothesis test to quantify the significance of differential expression. We evaluate the proposed method to understand differences in two case studies (1) the heat shock response of wild-type and HSF1 knockout mice, and (2) cell-cycle between wild-type and Fkh1/Fkh2 knockout Yeast strains.</p> <p>Conclusion</p> <p>In both cases, the proposed method identified biologically significant genes.</p