Self-organizing ontology of biochemically relevant small molecules

Background  

The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest.     

MetaboLights: towards a new COSMOS of metabolomics data management

Exciting funding initiatives are emerging in Europe and the US for metabolomics data production, storage, dissemination and analysis. This is based on a rich ecosystem of resources around the world, which has been build during the past ten years, including but not limited to resources such as MassBank in Japan and the Human Metabolome Database in Canada. Now, the European Bioinformatics Institute has launched MetaboLights, a database for metabolomics experiments and the associated metadata (http://www.ebi.ac.uk/metabolights). It is the first comprehensive, cross-species, cross-platform metabolomics database maintained by one of the major open access data providers in molecular biology. In October, the European COSMOS consortium will start its work on Metabolomics data standardization, publication and dissemination workflows. The NIH in the US is establishing 6?C8 metabolomics services cores as well as a national metabolomics repository. This communication reports about MetaboLights as a new resource for Metabolomics research, summarises the related developments and outlines how they may consolidate the knowledge management in this third large omics field next to proteomics and genomics.     

An information-carrying and knowledge-producing molecular machine. A Monte-Carlo simulation

The concept called Knowledge is a measure of the quality of genetically transferred information. Its usefulness is demonstrated quantitatively in a Monte-Carlo simulation on critical steps in a origin of life model. The model describes the origin of a bio-like genetic apparatus by a long sequence of physical-chemical steps: it starts with the presence of a self-replicating oligomer and a specifically structured environment in time and space that allow for the formation of aggregates such as assembler-hairpins-devices and, at a later stage, an assembler-hairpins-enzyme device—a first translation machine.     

Remote sensing to map influence of light pollution on Cory’s shearwater in São Miguel Island,Azores Archipelago

Global economic and population growth increase the extent and intensity of artificial night lighting. From an ecological perspective, this is light pollution, which causes changes in reproductive physiology, migration and foraging of many species and ultimately leads to loss of biodiversity. Some seabirds are intimately linked with the light features of their environments because they are nocturnally active. We report light-induced groundings of Cory’s shearwater (Calonectris diomedea) during a 2-year study (2008 and 2009) in São Miguel Island, in the Azores archipelago, and investigate the spatial correlation of locations of grounded birds with an annual composite of remotely sensed stable lights. Results indicate that 16.7% of fledglings are attracted to lights. The exposure of shearwater colonies in the study area to artificial night lighting is low overall. Four colonies account for 87% of the grounded birds. The distance each bird was found from the closest colony was best explained by the ratio of the satellite-measured light levels at the grounding spot to the light levels at the assigned colony of origin. These results demonstrate that satellite-observed nighttime lights are sufficient to assess risk to marine birds at the scale of oceanic islands and indicate their utility for monitoring the effectiveness of programs to manage lighting to reduce risk for these species and conducting global assessments of species vulnerability. To minimize the impact on Cory’s shearwater and other marine birds, we recommend measures such as reduction and control of lighting intensity near colony locations, while continuing and re-enforcing rescue campaigns.     

A new species of <Emphasis Type="Italic">Pustula</Emphasis> (Oomycetes,Albuginales) is the causal agent of sunflower white rust

White blister rust of sunflower is an emerging disease that is among the most important diseases in this crop in South Africa and has recently spread to Europe. For the genus Albugo, it has been demonstrated that species are mostly at least host genus specific and that several previously overlooked species are present on Brassicaceae. It thus seems likely that previously unrecognised species are also present in the genus Pustula. Based on previous phylogenetic reconstruction in combination with differences in oospore ornamentation, it is revealed that Pustula on sunflower, previously attributed to Pustula tragopogonis (syn. Albugo tragopogonis), is distinct from Pustula on Tragopogon. Therefore, this pathogen is described as a new species, Pustula helianthicola. In addition, taxonomic observations revealed that Pustula tragopogonis is an incorrect name and is replaced by the new combination, Pustula obtusata.     

How subunits cooperate in cAMP-induced activation of homotetrameric HCN2 channels

Hyperpolarization-activated cyclic nucleotide-modulated (HCN) channels are tetrameric membrane proteins that generate electrical rhythmicity in specialized neurons and cardiomyocytes. The channels are primarily activated by voltage but are receptors as well, binding the intracellular ligand cyclic AMP. The molecular mechanism of channel activation is still unknown. Here we analyze the complex activation mechanism of homotetrameric HCN2 channels by confocal patch-clamp fluorometry and kinetically quantify all ligand binding steps and closed-open isomerizations of the intermediate states. For the binding affinity of the second, third and fourth ligand, our results suggest pronounced cooperativity in the sequence positive, negative and positive, respectively. This complex interaction of the subunits leads to a preferential stabilization of states with zero, two or four ligands and suggests a dimeric organization of the activation process: within the dimers the cooperativity is positive, whereas it is negative between the dimers.     

Lipidic phase membrane protein serial femtosecond crystallography

X-ray free electron laser (X-FEL)-based serial femtosecond crystallography is an emerging method with potential to rapidly advance the challenging field of membrane protein structural biology. Here we recorded interpretable diffraction data from micrometer-sized lipidic sponge phase crystals of the Blastochloris viridis photosynthetic reaction center delivered into an X-FEL beam using a sponge phase micro-jet.     

Confidence-based Somatic Mutation Evaluation and Prioritization

Next generation sequencing (NGS) has enabled high throughput discovery of somatic mutations. Detection depends on experimental design, lab platforms, parameters and analysis algorithms. However, NGS-based somatic mutation detection is prone to erroneous calls, with reported validation rates near 54% and congruence between algorithms less than 50%. Here, we developed an algorithm to assign a single statistic, a false discovery rate (FDR), to each somatic mutation identified by NGS. This FDR confidence value accurately discriminates true mutations from erroneous calls. Using sequencing data generated from triplicate exome profiling of C57BL/6 mice and B16-F10 melanoma cells, we used the existing algorithms GATK, SAMtools and SomaticSNiPer to identify somatic mutations. For each identified mutation, our algorithm assigned an FDR. We selected 139 mutations for validation, including 50 somatic mutations assigned a low FDR (high confidence) and 44 mutations assigned a high FDR (low confidence). All of the high confidence somatic mutations validated (50 of 50), none of the 44 low confidence somatic mutations validated, and 15 of 45 mutations with an intermediate FDR validated. Furthermore, the assignment of a single FDR to individual mutations enables statistical comparisons of lab and computation methodologies, including ROC curves and AUC metrics. Using the HiSeq 2000, single end 50 nt reads from replicates generate the highest confidence somatic mutation call set.