Genome Sequence of the Bacterioplanktonic, Mixotrophic Vibrio campbellii Strain PEL22A, Isolated in the Abrolhos Bank

Vibrio campbellii PEL22A was isolated from open ocean water in the Abrolhos Bank. The genome of PEL22A consists of 6,788,038 bp (the GC content is 45%). The number of coding sequences (CDS) is 6,359, as determined according to the Rapid Annotation using Subsystem Technology (RAST) server. The number of ribosomal genes is 80, of which 68 are tRNAs and 12 are rRNAs. V. campbellii PEL22A contains genes related to virulence and fitness, including a complete proteorhodopsin cluster, complete type II and III secretion systems, incomplete type I, IV, and VI secretion systems, a hemolysin, and CTX Phi.

A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation

The Neotropical evaniid genus Evaniscus Szepligeti currently includes six species. Two new species are described, Evaniscus lansdownei Mullins, sp. n. from Colombia and Brazil and E. rafaeli Kawada, sp. n. from Brazil. Evaniscus sulcigenis Roman, syn. n., is synonymized under E. rufithorax Enderlein. An identification key to species of Evaniscus is provided. Thirty-five parsimony informative morphological characters are analyzed for six ingroup and four outgroup taxa. A topology resulting in a monophyletic Evaniscus is presented with E. tibialis and E. rafaeli as sister to the remaining Evaniscus species. The Hymenoptera Anatomy Ontology and other relevant biomedical ontologies are employed to create semantic phenotype statements in Entity-Quality (EQ) format for species descriptions. This approach is an early effort to formalize species descriptions and to make descriptive data available to other domains.

A hymenopterists' guide to the Hymenoptera Anatomy Ontology: utility, clarification, and future directions

Hymenoptera exhibit an incredible diversity of phenotypes, the result of similar to 240 million years of evolution and the primary subject of more than 250 years of research. Here we describe the history, development, and utility of the Hymenoptera Anatomy Ontology (HAO) and its associated applications. These resources are designed to facilitate accessible and extensible research on hymenopteran phenotypes. Outreach with the hymenopterist community is of utmost importance to the HAO project, and this paper is a direct response to questions that arose from project workshops. In a concerted attempt to surmount barriers of understanding, especially regarding the format, utility, and development of the HAO, we discuss the roles of homology, "preferred terms", and "structural equivalency". We also outline the use of Universal Resource Identifiers (URIs) and posit that they are a key element necessary for increasing the objectivity and repeatability of science that references hymenopteran anatomy. Pragmatically, we detail a mechanism (the "URI table") by which authors can use URIs to link their published text to the HAO, and we describe an associated tool (the "Analyzer") to derive these tables. These tools, and others, are available through the HAO Portal website (http://portal.hymao.org). We conclude by discussing the future of the HAO with respect to digital publication, cross-taxon ontology alignment, the advent of semantic phenotypes, and community-based curation.

Identification of intracellular peptides in rat adipose tissue: Insights into insulin resistance

Intracellular peptides generated by the proteasome and oligopeptidases have been suggested to function in signal transduction and to improve insulin resistance in mice fed a high-caloric diet. The aim of this study was to identify specific intracellular peptides in the adipose tissue of Wistar rats that could be associated with the physiological and therapeutic control of glucose uptake. Using semiquantitative mass spectrometry and LC/MS/MS analyses, we identified ten peptides in the epididymal adipose tissue of the Wistar rats; three of these peptides were present at increased levels in rats that were fed a high-caloric Western diet (WD) compared with rats fed a control diet (CD). The results of affinity chromatography suggested that in the cytoplasm of epididymal adipose tissue from either WD or CD rats, distinctive proteins bind to these peptides. However, despite the observed increase in the WD animals, the evaluated peptides increased insulin-stimulated glucose uptake in 3T3-L1 adipocytes treated with palmitate. Thus, intracellular peptides from the adipose tissue of Wistar rats can bind to specific proteins and facilitate insulin-induced glucose uptake in 3T3-L1 adipocytes.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.