The retina of honeybee drone is a nervous tissue with a crystal-like structure in which glial cells and photoreceptor neurons constitute two distinct metabolic compartments. The phosphorylation of glucose and its subsequent incorporation into glycogen occur in glia, whereas O2 consumption (QO2) occurs in the photoreceptors. Experimental evidence showed that glia phosphorylate glucose and supply the photoreceptors with metabolic substrates. We aimed to identify these transferred substrates. Using ion-exchange and reversed-phase HPLC and gas chromatography-mass spectrometry, we demonstrated that more than 50% of 14C(U)-glucose entering the glia is transformed to alanine by transamination of pyruvate with glutamate. In the absence of extracellular glucose, glycogen is used to make alanine; thus, its pool size in isolated retinas is maintained stable or even increased. Our model proposes that the formation of alanine occurs in the glia, thereby maintaining the redox potential of this cell and contributing to NH3 homeostasis. Alanine is released into the extracellular space and is then transported into photoreceptors using an Na(+)-dependent transport system. Purified suspensions of photoreceptors have similar alanine aminotransferase activity as glial cells and transform 14C- alanine to glutamate, aspartate, and CO2. Therefore, the alanine entering photoreceptors is transaminated to pyruvate, which in turn enters the Krebs cycle. Proline also supplies the Krebs cycle by making glutamate and, in turn, the intermediate alpha-ketoglutarate. Light stimulation caused a 200% increase of QO2 and a 50% decrease of proline and of glutamate. Also, the production of 14CO2 from 14C-proline was increased. The use of these amino acids would sustain about half of the light-induced delta QO2, the other half being sustained by glycogen via alanine formation. The use of proline meets a necessary anaplerotic function in the Krebs cycle, but implies high NH3 production. The results showed that alanine formation fixes NH3 at a rate exceeding glutamine formation. This is consistent with the rise of a glial pool of alanine upon photostimulation. In conclusion, the results strongly support a nutritive function for glia.

Phylogenetic and epidemiological analyses underline the impact of PHI in the spread of HIV. Moreover, this study indicates that drug resistance transmission may have decreased recently in Switzerland through the increased frequency of infection with HIV non-B subtypes and the steady increase of patients with undetectable viraemia.

N-terminal myristoylation is a post-translational modification that causes the addition of a myristate to a glycine in the N-terminal end of the amino acid chain. This work presents neural network (NN) models that learn to discriminate myristoylated and nonmyristoylated proteins. Ensembles of 25 NNs and decision trees were trained on 390 positive sequences and 327 negative sequences. Experiments showed that NN ensembles were more accurate than decision tree ensembles. Our NN predictor evaluated by the leave-one-out procedure, obtained a false positive error rate equal to 2.1%. That was better than the PROSITE pattern for myristoylation for which the false positive error rate was 22.3%. On a recent version of Swiss-Prot (41.2), the NN ensemble predicted 876 myristoylated proteins, while 1150 proteins were predicted by the PROSITE pattern for myristoylation. Finally, compared to the well-known NMT predictor, the NN predictor gave similar results. Our tool is available under http://www.expasy.org/tools/myristoylator/myristoylator.html.

Summary: The SwissVar portal provides access to a comprehensive collection of single amino acid polymorphisms and diseases in the UniProtKB/Swiss-Prot database via a unique search engine. In particular, it gives direct access to the newly improved Swiss-Prot variant pages. The key strength of this portal is that it provides a possibility to query for similar diseases, as well as the underlying protein products and the molecular details of each variant. In the context of the recently proposed molecular view on diseases, the SwissVar portal should be in a unique position to provide valuable information for researchers and to advance research in this area.Availability: The SwissVar portal is available at www.expasy.org/swissvarContact: anais.mottaz@isb-sib.ch; lina.yip@isb-sib.chSupplementary information: Supplementary data are available at Bioinformatics online.

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on ‘Text Mining for the BioCuration Workflow’ at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community.