Community outbreaks of group A Streptococcus revealed by genome sequencing

The frequent occurrence of disease outbreaks in humans caused by group A Streptococcus (GAS) is an on-going public health threat. Conventional bacterial typing methods lack the discriminatory power to confidently confirm or refute outbreaks in hospital and community settings. Microbial whole genome sequencing (WGS) provides a potential solution to this, but, there has been limited population-based surveillance with accompanying sequence data. We performed retrospective genomic surveillance of 93 clinical GAS isolates from individuals in a defined geographic region. Detailed clinical information was obtained for closely related clusters of isolates. Genomic sequence data was contextualised through comparison with international data. We identified 18 different emm genotypes within our bacterial population, and revealed both highly diverse and closely related isolates. This high level of diversity was maintained even in the context of international sequence data. We also identified two emm1 clusters, and one emm3 cluster, of closely-related isolates that differed only by 1 to 4 single nucleotide polymorphisms. Analysis of clinical information identified no healthcare associated contact between patients, indicating cryptic community transmission. Our findings suggest that genomic surveillance of GAS would increase detection of transmission and highlight opportunities for intervention

Comparison of long-term outcome between patients aged < 65 years vs. ≥ 65 years after atrial fibrillation ablation

Background Atrial fibrillation (AF) is the most frequent arrhythmia, and its prevalence is increasing with aging. We aimed to compare the long-term outcome data of patients < 65 years vs. ≥ 65 years who underwent ca

Homologous Flares and Magnetic Field Topology in Active Region NOAA 10501 on 20 November 2003

We present and interpret observations of two morphologically homologous flares that occurred in active region (AR) NOAA 10501 on 20 November 2003. Both flares displayed four homologous H-alpha ribbons and were both accompanied by coronal mass ejections (CMEs). The central flare ribbons were located at the site of an emerging bipole in the center of the active region. The negative polarity of this bipole fragmented in two main pieces, one rotating around the positive polarity by ~ 110 deg within 32 hours. We model the coronal magnetic field and compute its topology, using as boundary condition the magnetogram closest in time to each flare. In particular, we calculate the location of quasiseparatrix layers (QSLs) in order to understand the connectivity between the flare ribbons. Though several polarities were present in AR 10501, the global magnetic field topology corresponds to a quadrupolar magnetic field distribution without magnetic null points. For both flares, the photospheric traces of QSLs are similar and match well the locations of the four H-alpha ribbons. This globally unchanged topology and the continuous shearing by the rotating bipole are two key factors responsible for the flare homology. However, our analyses also indicate that different magnetic connectivity domains of the quadrupolar configuration become unstable during each flare, so that magnetic reconnection proceeds differently in both events.Comment: 24 pages, 10 figures, Solar Physics (accepted

Evolutionary signals of selection on cognition from the great tit genome and methylome

For over 50 years, the great tit (Parus major) has been a model species for research in evolutionary, ecological and behavioural research; in particular, learning and cognition have been intensively studied. Here, to provide further insight into the molecular mechanisms behind these important traits, we de novo assemble a great tit reference genome and whole-genome re-sequence another 29 individuals from across Europe. We show an overrepresentation of genes related to neuronal functions, learning and cognition in regions under positive selection, as well as increased CpG methylation in these regions. In addition, great tit neuronal non-CpG methylation patterns are very similar to those observed in mammals, suggesting a universal role in neuronal epigenetic regulation which can affect learning-, memory- and experience-induced plasticity. The high-quality great tit genome assembly will play an instrumental role in furthering the integration of ecological, evolutionary, behavioural and genomic approaches in this model species.</p

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives