Identification of putative novel O-glycosylations in the NK killer receptor Ncr1 essential for its activity

Natural killer (NK) cells kill tumor and virus-infected cells using activating NK cell receptors. One of the major NK-activating receptors is NKp46 and its mouse ortholog Ncr1. NKp46/Ncr1 is expressed exclusively on NK cells and on a subset of innate lymphoid cells. NKp46/Ncr1 was shown to be involved in a myriad of pathologies and immunological settings. Specifically, NKp46/Ncr1 was shown to interact with the viral hemagglutinin (HA) protein and with an unknown tumor/cellular ligand. NKp46 and Ncr1 are structurally similar; however, they are substantially different in their glycosylation patterns. Although the human NKp46 carries both O- and N-glycosylations that are essential for its activity, the mouse Ncr1 was predicted to have N-linked glycosylations only. Here we discovered using prediction algorithms and high-performance liquid chromatography analysis that Ncr1 carries two putative novel O-glycosylations, one of which (Thr 225) is conserved in NKp46. We next used surface plasmon resonance, biochemical, mutational and functional in vitro and in vivo assays to demonstrate that the putative O-glycosylations of Ncr1 are critical for its function

A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

Background: Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of gene function promises to help focus limited experimental resources on the most likely hypotheses. Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated. Results: In this study, a standardized collection of mouse functional genomic data was assembled; nine bioinformatics teams used this data set to independently train classifiers and generate predictions of function, as defined by Gene Ontology (GO) terms, for 21,603 mouse genes; and the best performing submissions were combined in a single set of predictions. We identified strengths and weaknesses of current functional genomic data sets and compared the performance of function prediction algorithms. This analysis inferred functions for 76% of mouse genes, including 5,000 currently uncharacterized genes. At a recall rate of 20%, a unified set of predictions averaged 41% precision, with 26% of GO terms achieving a precision better than 90%. Conclusion: We performed a systematic evaluation of diverse, independently developed computational approaches for predicting gene function from heterogeneous data sources in mammals. The results show that currently available data for mammals allows predictions with both breadth and accuracy. Importantly, many highly novel predictions emerge for the 38% of mouse genes that remain uncharacterized

History Shaped the Geographic Distribution of Genomic Admixture on the Island of Puerto Rico

Contemporary genetic variation among Latin Americans human groups reflects population migrations shaped by complex historical, social and economic factors. Consequently, admixture patterns may vary by geographic regions ranging from countries to neighborhoods. We examined the geographic variation of admixture across the island of Puerto Rico and the degree to which it could be explained by historic and social events. We analyzed a census-based sample of 642 Puerto Rican individuals that were genotyped for 93 ancestry informative markers (AIMs) to estimate African, European and Native American ancestry. Socioeconomic status (SES) data and geographic location were obtained for each individual. There was significant geographic variation of ancestry across the island. In particular, African ancestry demonstrated a decreasing East to West gradient that was partially explained by historical factors linked to the colonial sugar plantation system. SES also demonstrated a parallel decreasing cline from East to West. However, at a local level, SES and African ancestry were negatively correlated. European ancestry was strongly negatively correlated with African ancestry and therefore showed patterns complementary to African ancestry. By contrast, Native American ancestry showed little variation across the island and across individuals and appears to have played little social role historically. The observed geographic distributions of SES and genetic variation relate to historical social events and mating patterns, and have substantial implications for the design of studies in the recently admixed Puerto Rican population. More generally, our results demonstrate the importance of incorporating social and geographic data with genetics when studying contemporary admixed populations

European Society of Cardiology: Cardiovascular Disease Statistics 2017

Background: The European Society of Cardiology (ESC) Atlas has been compiled by the European Heart Agency to document cardiovascular disease (CVD) statistics of the 56 ESC member countries. A major aim of this 2017 data presentation has been to compare high income and middle income ESC member countries, in order to identify inequalities in disease burden, outcomes and service provision. Methods: The Atlas utilizes a variety of data sources, including the World Health Organization, the Institute for Health Metrics and Evaluation, and the World Bank to document risk factors, prevalence and mortality of cardiovascular disease and national economic indicators. It also includes novel ESC sponsored survey data of health infrastructure and cardiovascular service provision provided by the national societies of the ESC member countries. Data presentation is descriptive with no attempt to attach statistical significance to differences observed in stratified analyses. Results: Important differences were identified between the high income and middle income member countries of the ESC with regard to CVD risk factors, disease incidence and mortality. For both women and men, the age-standardised prevalence of hypertension was lower in high income countries (18.3% and 27.3%) compared with middle income countries (23.5% and 30.3%). Smoking prevalence in men (not women) was also lower (26% vs 41.3%), and together these inequalities are likely to have contributed to the higher CVD mortality in middle income countries. Declines in CVD mortality have seen cancer becoming a more common cause of death in a number of high income member countries, but in middle income countries declines in CVD mortality have been less consistent where CVD remains the leading cause of death. Inequalities in CVD mortality are emphasised by the smaller contribution they make to potential years of life lost in high income compared with middle income countries both for women (13% vs. 23%) and men (20% vs. 27%). The downward mortality trends for CVD may, however, be threatened by the emerging obesity epidemic that is seeing rates of diabetes increasing across all ESC member countries. Survey data from the National Cardiac Societies (n=41) showed that rates of cardiac catheterization and coronary artery bypass surgery, as well as the number of specialist centres required to deliver them, were greatest in the high income member countries of the ESC. The Atlas confirmed that these ESC member countries, where the facilities for the contemporary treatment of coronary disease were best developed, were often those in which declines in coronary mortality have been most pronounced. Economic resources were not the only driver for delivery of equitable cardiovascular healthcare, as some middle income ESC member countries reported rates for interventional procedures and device implantations that matched or exceeded the rates in wealthier member countries. Conclusion: In documenting national CVD statistics, the Atlas provides valuable insights into the inequalities in risk factors, healthcare delivery and outcomes of CVD across ESC member countries. The availability of these data will underpin the ESC’s ambitious mission “to reduce the burden of cardiovascular disease” not only in its member countries, but also in nation states around the world

Syndromics: A Bioinformatics Approach for Neurotrauma Research

Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help restore function after injury. Despite these advances, bench-to-bedside translation has remained elusive. Translational testing of novel therapies requires standardized measures of function for comparison across different laboratories, paradigms, and species. Although numerous functional assessments have been developed in animal models, it remains unclear how to best integrate this information to describe the complete translational “syndrome” produced by neurotrauma. The present paper describes a multivariate statistical framework for integrating diverse neurotrauma data and reviews the few papers to date that have taken an information-intensive approach for basic neurotrauma research. We argue that these papers can be described as the seminal works of a new field that we call “syndromics”, which aim to apply informatics tools to disease models to characterize the full set of mechanistic inter-relationships from multi-scale data. In the future, centralized databases of raw neurotrauma data will enable better syndromic approaches and aid future translational research, leading to more efficient testing regimens and more clinically relevant findings

Biotic interactions as drivers of algal origin and evolution

Biotic interactions underlie life's diversity and are the lynchpin to understanding its complexity and resilience within an ecological niche. Algal biologists have embraced this paradigm, and studies building on the explosive growth in omics and cell biology methods have facilitated the in-depth analysis of nonmodel organisms and communities from a variety of ecosystems. In turn, these advances have enabled a major revision of our understanding of the origin and evolution of photosynthesis in eukaryotes, bacterial–algal interactions, control of massive algal blooms in the ocean, and the maintenance and degradation of coral reefs. Here, we review some of the most exciting developments in the field of algal biotic interactions and identify challenges for scientists in the coming years. We foresee the development of an algal knowledgebase that integrates ecosystem-wide omics data and the development of molecular tools/resources to perform functional analyses of individuals in isolation and in populations. These assets will allow us to move beyond mechanistic studies of a single species towards understanding the interactions amongst algae and other organisms in both the laboratory and the field