Teaching strategies and gender in higher education instrumental studios

This study investigates instrumental music teaching strategies in higher education settings, in order to identify those employed and their frequency and context of use. An instrument- and gender-balanced sample of 24 lessons from five institutions was analysed using a researcher-designed observational instrument. The results reveal the predominance of teacher demonstration, general directives and praise as most frequent teaching strategies employed in lessons. Gender differences emerged in the teaching approaches: the male teachers gave more general directives and explanations and the female teachers offered more answers and practice discussions; the male students received the most specific teacher criticism despite uniform use of praise. The findings provide new evidence of teaching practices in advanced instrumental studios and raise questions regarding gender issues in music teaching

Viral population estimation using pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an EM algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.Comment: 23 pages, 13 figure

A Thermal Analysis of a Hot-Wire Probe for Icing Applications

This paper presents a steady-state thermal model of a hot-wire instrument applicable to atmospheric measurement of water content in clouds. In this application, the power required to maintain the wire at a given temperature is used to deduce the water content of the cloud. The model considers electrical resistive heating, axial conduction, convection to the flow, radiation to the surroundings, as well as energy loss due to the heating, melting, and evaporation of impinging liquid and or ice. All of these parameters can be varied axially along the wire. The model further introduces a parameter called the evaporation potential which locally gauges the maximum fraction of incoming water that evaporates. The primary outputs of the model are the steady-state power required to maintain a spatially-average constant temperature as well as the variation of that temperature and other parameters along the wire. The model is used to understand the sensitivity of the hot-wire performance to various flow and boundary conditions including a detailed comparison of dry air and wet (i.e. cloud-on) conditions. The steady-state power values are compared to experimental results from a Science Engineering Associates (SEA) Multi-Element probe, a commonly used water-content measurement instrument. The model results show good agreement with experiment for both dry and cloud-on conditions with liquid water content. For ice, the experimental measurements under read the actual water content due to incomplete evaporation and splashing. Model results, which account for incomplete evaporation, are still higher than experimental results where the discrepancy is attributed to splashing mass-loss which is not accounted in the model

Bacterial diversity and community composition from seasurface to subseafloor

© The International Society for Microbial Ecology, 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in ISME Journal 10 (2016): 979–989, doi:10.1038/ismej.2015.175.We investigated compositional relationships between bacterial communities in the water column and those in deep-sea sediment at three environmentally distinct Pacific sites (two in the Equatorial Pacific and one in the North Pacific Gyre). Through pyrosequencing of the v4–v6 hypervariable regions of the 16S ribosomal RNA gene, we characterized 450 104 pyrotags representing 29 814 operational taxonomic units (OTUs, 97% similarity). Hierarchical clustering and non-metric multidimensional scaling partition the samples into four broad groups, regardless of geographic location: a photic-zone community, a subphotic community, a shallow sedimentary community and a subseafloor sedimentary community (greater than or equal to1.5 meters below seafloor). Abundance-weighted community compositions of water-column samples exhibit a similar trend with depth at all sites, with successive epipelagic, mesopelagic, bathypelagic and abyssopelagic communities. Taxonomic richness is generally highest in the water-column O2 minimum zone and lowest in the subseafloor sediment. OTUs represented by abundant tags in the subseafloor sediment are often present but represented by few tags in the water column, and represented by moderately abundant tags in the shallow sediment. In contrast, OTUs represented by abundant tags in the water are generally absent from the subseafloor sediment. These results are consistent with (i) dispersal of marine sedimentary bacteria via the ocean, and (ii) selection of the subseafloor sedimentary community from within the community present in shallow sediment.This study was funded by the Biological Oceanography Program of the US National Science Foundation (grant OCE-0752336) and by the NSF-funded Center for Dark Energy Biosphere Investigations (grant NSF-OCE-0939564)

Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics

We introduce Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct ‘metacommunities’, and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the ‘evidence framework’ (http://code.google.com/p/microbedmm/). This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the ‘Anna Karenina principle (AKP)’ applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD) phenotypes, ileal Crohn's disease (ICD) is associated with a more variable community

Conservative Fragments in Bacterial 16S rRNA Genes and Primer Design for 16S Ribosomal DNA Amplicons in Metagenomic Studies

Bacterial 16S ribosomal DNA (rDNA) amplicons have been widely used in the classification of uncultured bacteria inhabiting environmental niches. Primers targeting conservative regions of the rDNAs are used to generate amplicons of variant regions that are informative in taxonomic assignment. One problem is that the percentage coverage and application scope of the primers used in previous studies are largely unknown. In this study, conservative fragments of available rDNA sequences were first mined and then used to search for candidate primers within the fragments by measuring the coverage rate defined as the percentage of bacterial sequences containing the target. Thirty predicted primers with a high coverage rate (>90%) were identified, which were basically located in the same conservative regions as known primers in previous reports, whereas 30% of the known primers were associated with a coverage rate of <90%. The application scope of the primers was also examined by calculating the percentages of failed detections in bacterial phyla. Primers A519–539, E969–983, E1063–1081, U515 and E517, are highly recommended because of their high coverage in almost all phyla. As expected, the three predominant phyla, Firmicutes, Gemmatimonadetes and Proteobacteria, are best covered by the predicted primers. The primers recommended in this report shall facilitate a comprehensive and reliable survey of bacterial diversity in metagenomic studies

Using the RDP Classifier to Predict Taxonomic Novelty and Reduce the Search Space for Finding Novel Organisms

BACKGROUND: Currently, the naïve Bayesian classifier provided by the Ribosomal Database Project (RDP) is one of the most widely used tools to classify 16S rRNA sequences, mainly collected from environmental samples. We show that RDP has 97+% assignment accuracy and is fast for 250 bp and longer reads when the read originates from a taxon known to the database. Because most environmental samples will contain organisms from taxa whose 16S rRNA genes have not been previously sequenced, we aim to benchmark how well the RDP classifier and other competing methods can discriminate these novel taxa from known taxa. PRINCIPAL FINDINGS: Because each fragment is assigned a score (containing likelihood or confidence information such as the boostrap score in the RDP classifier), we "train" a threshold to discriminate between novel and known organisms and observe its performance on a test set. The threshold that we determine tends to be conservative (low sensitivity but high specificity) for naïve Bayesian methods. Nonetheless, our method performs better with the RDP classifier than the other methods tested, measured by the f-measure and the area-under-the-curve on the receiver operating characteristic of the test set. By constraining the database to well-represented genera, sensitivity improves 3-15%. Finally, we show that the detector is a good predictor to determine novel abundant taxa (especially for finer levels of taxonomy where novelty is more likely to be present). CONCLUSIONS: We conclude that selecting a read-length appropriate RDP bootstrap score can significantly reduce the search space for identifying novel genera and higher levels in taxonomy. In addition, having a well-represented database significantly improves performance while having genera that are "highly" similar does not make a significant improvement. On a real dataset from an Amazon Terra Preta soil sample, we show that the detector can predict (or correlates to) whether novel sequences will be assigned to new taxa when the RDP database "doubles" in the future

The Kolumbo submarine volcano of Santorini island is a large pool of bacterial strains with antimicrobial activity

Microbes in hydrothermal vents with their unique secondary metabolism may represent an untapped potential source of new natural products. In this study, samples were collected from the hydrothermal field of Kolumbo submarine volcano in the Aegean Sea, in order to isolate bacteria with antimicrobial activity. Eight hundred and thirty-two aerobic heterotrophic bacteria were isolated and then differentiated through BOX-PCR analysis at the strain level into 230 genomic fingerprints, which were screened against 13 different type strains (pathogenic and nonpathogenic) of Gram-positive, Gram-negative bacteria and fungi. Forty-two out of 176 bioactive-producing genotypes (76 %) exhibited antimicrobial activity against at least four different type strains and were selected for 16S rDNA sequencing and screening for nonribosomal peptide (NRPS) and polyketide (PKS) synthases genes. The isolates were assigned to genus Bacillus and Proteobacteria, and 20 strains harbored either NRPS, PKS type I or both genes. This is the first report on the diversity of culturable mesophilic bacteria associated with antimicrobial activity from Kolumbo area; the extremely high proportion of antimicrobial-producing strains suggested that this unique environment may represent a potential reservoir of novel bioactive compounds

Effect of Cry1Ab Protein on Rhizobacterial Communities of Bt-Maize over a Four-Year Cultivation Period

Background: Bt-maize is a transgenic variety of maize expressing the Cry toxin from Bacillus turingiensis. The potential accumulation of the relative effect of the transgenic modification and the cry toxin on the rhizobacterial communities of Btmaize has been monitored over a period of four years. Methodology/Principal Findings: The accumulative effects of the cultivation of this transgenic plant have been monitored by means of high throughput DNA pyrosequencing of the bacterial DNA coding for the 16S rRNA hypervariable V6 region from rhizobacterial communities. The obtained sequences were subjected to taxonomic, phylogenetic and taxonomicindependent diversity studies. The results obtained were consistent, indicating that variations detected in the rhizobacterial community structure were possibly due to climatic factors rather than to the presence of the Bt-gene. No variations were observed in the diversity estimates between non-Bt and Bt-maize. Conclusions/Significance: The cultivation of Bt-maize during the four-year period did not change the maize rhizobacterial communities when compared to those of the non-Bt maize. This is the first study to be conducted with Bt-maize during such a long cultivation period and the first evaluation of rhizobacterial communities to be performed in this transgenic plant using Next Generation Sequencing