CDD: a Conserved Domain Database for protein classification

The Conserved Domain Database (CDD) is the protein classification component of NCBI's Entrez query and retrieval system. CDD is linked to other Entrez databases such as Proteins, Taxonomy and PubMed®, and can be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=cdd. CD-Search, which is available at http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, is a fast, interactive tool to identify conserved domains in new protein sequences. CD-Search results for protein sequences in Entrez are pre-computed to provide links between proteins and domain models, and computational annotation visible upon request. Protein–protein queries submitted to NCBI's BLAST search service at http://www.ncbi.nlm.nih.gov/BLAST are scanned for the presence of conserved domains by default. While CDD started out as essentially a mirror of publicly available domain alignment collections, such as SMART, Pfam and COG, we have continued an effort to update, and in some cases replace these models with domain hierarchies curated at the NCBI. Here, we report on the progress of the curation effort and associated improvements in the functionality of the CDD information retrieval system

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Basking in the sun: how mosses photosynthesise and survive in Antarctica

The Antarctic environment is extremely cold, windy and dry. Ozone depletion has resulted in increasing ultraviolet-B radiation, and increasing greenhouse gases and decreasing stratospheric ozone have altered Antarctica’s climate. How do mosses thrive photosynthetically in this harsh environment? Antarctic mosses take advantage of microclimates where the combination of protection from wind, sufficient melt water, nutrients from seabirds and optimal sunlight provides both photosynthetic energy and sufficient warmth for efficient metabolism. The amount of sunlight presents a challenge: more light creates warmer canopies which are optimal for photosynthetic enzymes but can contain excess light energy that could damage the photochemical apparatus. Antarctic mosses thus exhibit strong photoprotective potential in the form of xanthophyll cycle pigments. Conversion to zeaxanthin is high when conditions are most extreme, especially when water content is low. Antarctic mosses also produce UV screening compounds which are maintained in cell walls in some species and appear to protect from DNA damage under elevated UV-B radiation. These plants thus survive in one of the harshest places on Earth by taking advantage of the best real estate to optimise their metabolism. But survival is precarious and it remains to be seen if these strategies will still work as the Antarctic climate changes

The COG database: an updated version includes eukaryotes

<p>Abstract</p> <p>Background</p> <p>The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies.</p> <p>Results</p> <p>We describe here a major update of the previously developed system for delineation of Clusters of Orthologous Groups of proteins (COGs) from the sequenced genomes of prokaryotes and unicellular eukaryotes and the construction of clusters of predicted orthologs for 7 eukaryotic genomes, which we named KOGs after eukaryotic orthologous groups. The COG collection currently consists of 138,458 proteins, which form 4873 COGs and comprise 75% of the 185,505 (predicted) proteins encoded in 66 genomes of unicellular organisms. The eukaryotic orthologous groups (KOGs) include proteins from 7 eukaryotic genomes: three animals (the nematode <it>Caenorhabditis elegans</it>, the fruit fly <it>Drosophila melanogaster </it>and <it>Homo sapiens</it>), one plant, <it>Arabidopsis thaliana</it>, two fungi (<it>Saccharomyces cerevisiae </it>and <it>Schizosaccharomyces pombe</it>), and the intracellular microsporidian parasite <it>Encephalitozoon cuniculi</it>. The current KOG set consists of 4852 clusters of orthologs, which include 59,838 proteins, or ~54% of the analyzed eukaryotic 110,655 gene products. Compared to the coverage of the prokaryotic genomes with COGs, a considerably smaller fraction of eukaryotic genes could be included into the KOGs; addition of new eukaryotic genomes is expected to result in substantial increase in the coverage of eukaryotic genomes with KOGs. Examination of the phyletic patterns of KOGs reveals a conserved core represented in all analyzed species and consisting of ~20% of the KOG set. This conserved portion of the KOG set is much greater than the ubiquitous portion of the COG set (~1% of the COGs). In part, this difference is probably due to the small number of included eukaryotic genomes, but it could also reflect the relative compactness of eukaryotes as a clade and the greater evolutionary stability of eukaryotic genomes.</p> <p>Conclusion</p> <p>The updated collection of orthologous protein sets for prokaryotes and eukaryotes is expected to be a useful platform for functional annotation of newly sequenced genomes, including those of complex eukaryotes, and genome-wide evolutionary studies.</p

Dragon Enhances BMP Signaling and Increases Transepithelial Resistance in Kidney Epithelial Cells

The neuronal adhesion protein Dragon acts as a bone morphogenetic protein (BMP) coreceptor that enhances BMP signaling. Given the importance of BMP signaling in nephrogenesis and its putative role in the response to injury in the adult kidney, we studied the localization and function of Dragon in the kidney. We observed that Dragon localized predominantly to the apical surfaces of tubular epithelial cells in the thick ascending limbs, distal convoluted tubules, and collecting ducts of mice. Dragon expression was weak in the proximal tubules and glomeruli. In mouse inner medullary collecting duct (mIMCD3) cells, Dragon generated BMP signals in a ligand-dependent manner, and BMP4 is the predominant endogenous ligand for the Dragon coreceptor. In mIMCD3 cells, BMP4 normally signaled through BMPRII, but Dragon enhanced its signaling through the BMP type II receptor ActRIIA. Dragon and BMP4 increased transepithelial resistance (TER) through the Smad1/5/8 pathway. In epithelial cells isolated from the proximal tubule and intercalated cells of collecting ducts, we observed coexpression of ActRIIA, Dragon, and BMP4 but not BMPRII. Taken together, these results suggest that Dragon may enhance BMP signaling in renal tubular epithelial cells and maintain normal renal physiology