BackgroundThe Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.ResultsHere, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.ConclusionWe conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

Brown adipose tissue (BAT) and beige adipose tissue combust fuels for heat production in adult humans, and so constitute an appealing target for the treatment of metabolic disorders such as obesity, diabetes and hyperlipidemia1,2. Cold exposure can enhance energy expenditure by activating BAT, and it has been shown to improve nutrient metabolism3–5. These therapies, however, are time consuming and uncomfortable, demonstrating the need for pharmacological interventions. Recently, lipids have been identified that are released from tissues and act locally or systemically to promote insulin sensitivity and glucose tolerance; as a class, these lipids are referred to as ‘lipokines’6–8. Because BAT is a specialized metabolic tissue that takes up and burns lipids and is linked to systemic metabolic homeostasis, we hypothesized that there might be thermogenic lipokines that activate BAT in response to cold. Here we show that the lipid 12,13-dihydroxy-9Z-octadecenoic acid (12,13-diHOME) is a stimulator of BAT activity, and that its levels are negatively correlated with body-mass index and insulin resistance. Using a global lipidomic analysis, we found that 12,13-diHOME was increased in the circulation of humans and mice exposed to cold. Furthermore, we found that the enzymes that produce 12,13-diHOME were uniquely induced in BAT by cold stimulation. The injection of 12,13-diHOME acutely activated BAT fuel uptake and enhanced cold tolerance, which resulted in decreased levels of serum triglycerides. Mechanistically, 12,13-diHOME increased fatty acid (FA) uptake into brown adipocytes by promoting the translocation of the FA transporters FATP1 and CD36 to the cell membrane. These data suggest that 12,13-diHOME, or a functional analog, could be developed as a treatment for metabolic disorders.

The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics and therapeutics against influenza virus by providing a comprehensive collection of influenza-related data integrated from various sources, a growing suite of analysis and visualization tools for data mining and hypothesis generation, personal workbench spaces for data storage and sharing, and active user community support. Here, we describe the recent improvements in IRD including the use of cloud and high performance computing resources, analysis and visualization of user-provided sequence data with associated metadata, predictions of novel variant proteins, annotations of phenotype-associated sequence markers and their predicted phenotypic effects, hemagglutinin (HA) clade classifications, an automated tool for HA subtype numbering conversion, linkouts to disease event data and the addition of host factor and antiviral drug components. All data and tools are freely available without restriction from the IRD website at https://www.fludb.org.

Peri-operative SARS-CoV-2 infection increases postoperative mortality. The aim of this study was to determine the optimal duration of planned delay before surgery in patients who have had SARS-CoV-2 infection. This international, multicentre, prospective cohort study included patients undergoing elective or emergency surgery during October 2020. Surgical patients with pre-operative SARS-CoV-2 infection were compared with those without previous SARS-CoV-2 infection. The primary outcome measure was 30-day postoperative mortality. Logistic regression models were used to calculate adjusted 30-day mortality rates stratified by time from diagnosis of SARS-CoV-2 infection to surgery. Among 140,231 patients (116 countries), 3127 patients (2.2%) had a pre-operative SARS-CoV-2 diagnosis. Adjusted 30-day mortality in patients without SARS-CoV-2 infection was 1.5% (95%CI 1.4-1.5). In patients with a pre-operative SARS-CoV-2 diagnosis, mortality was increased in patients having surgery within 0-2 weeks, 3-4 weeks and 5-6 weeks of the diagnosis (odds ratio (95%CI) 4.1 (3.3-4.8), 3.9 (2.6-5.1) and 3.6 (2.0-5.2), respectively). Surgery performed ≥ 7 weeks after SARS-CoV-2 diagnosis was associated with a similar mortality risk to baseline (odds ratio (95%CI) 1.5 (0.9-2.1)). After a ≥ 7 week delay in undertaking surgery following SARS-CoV-2 infection, patients with ongoing symptoms had a higher mortality than patients whose symptoms had resolved or who had been asymptomatic (6.0% (95%CI 3.2-8.7) vs. 2.4% (95%CI 1.4-3.4) vs. 1.3% (95%CI 0.6-2.0), respectively). Where possible, surgery should be delayed for at least 7 weeks following SARS-CoV-2 infection. Patients with ongoing symptoms ≥ 7 weeks from diagnosis may benefit from further delay.

The objective of this study was to characterize the diagnostic timelines and their predictors in people with amyotrophic lateral sclerosis (ALS). Patients were identified through ALS billing codes. Time from presenting symptom to first doctor visit, first doctor visit to suspected ALS diagnosis, suspected to confirmed ALS diagnosis, and presenting symptom to confirmed ALS diagnosis (total diagnostic time) were collected. Regression models were used to analyze the predictors of diagnostic delay. Three hundred and four ALS patients were included in the analysis. Median total diagnostic time was 11.5 months. Diagnostic timelines were longer in patients with age > 60 years (p < 0.001), sporadic ALS (p = 0.043), and limb onset (p = 0.010). The presence of fasciculations, slurred speech, and lower extremity weakness when symptoms were first noted were independent predictors of shorter time to ALS diagnosis (p = 0.04, p = 0.02, and p = 0.04, respectively). About half of the patients (52%) received an alternative diagnosis and each patient saw an average of three different physicians before ALS diagnosis was confirmed. In conclusion, diagnostic timelines in ALS are long, and patients see many physicians and receive multiple alternative diagnoses before the diagnosis of ALS is confirmed. Older age, sporadic disease, and limb onset can delay ALS diagnosis.

The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Here we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility (P. aureginosa only). We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. We conclude that, while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. We finally report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bioontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. 157 project. Predicting GO terms for a protein (protein-centric) and predicting which proteins are associated 158 with a given function (term-centric) are related but different computational problems: the former is a 159 multi-label classification problem with a structured output, while the latter is a binary classification task. 160Predicting the results of a genome-wide screen for a single or a small number of functions fits the term-centric 161 formulation. To see how well all participating CAFA methods perform term-centric predictions, we mapped 162 results from the protein-centric CAFA3 methods onto these terms. In addition we held a separate CAFA 163 challenge, CAFA-π whose purpose was to attract additional submissions from algorithms that specialize in 164 term-centric tasks. 165 We performed screens for three functions in three species, which we then used to assess protein function 166 prediction. In the bacterium Pseudomonas aeruginosa and the fungus Candida albicans we performed 167 genome-wide screens capable of uncovering genes with two functions, biofilm formation (GO:0042710) and 168 motility (for P. aeruginosa only) (GO:0001539), as described in Methods. In Drosophila melanogaster we 169 performed targeted assays, guided by previous CAFA submissions, of a ...

The lipid chaperone aP2/FABP4 has been implicated in the pathology of many immunometabolic diseases, including diabetes in humans, but aP2 has not yet been targeted for therapeutic applications. aP2 is not only an intracellular protein but also an active adipokine that contributes to hyperglycemia by promoting hepatic gluconeogenesis and interfering with peripheral insulin action. Serum aP2 levels are markedly elevated in mouse and human obesity and strongly correlate with metabolic complications. These observations raise the possibility of a new strategy to treat metabolic disease by targeting serum aP2 with a monoclonal antibody (mAb) to aP2. We evaluated mAbs to aP2 and identified one, CA33, that lowered fasting blood glucose, improved systemic glucose metabolism, increased systemic insulin sensitivity, and reduced fat mass and liver steatosis in obese mouse models. We examined the structure of the aP2-CA33 complex and resolved the target epitope by crystallographic studies in comparison to another mAb that lacked efficacy in vivo. In hyperinsulinemic-euglycemic clamp studies, we found that the antidiabetic effect of CA33 was predominantly linked to the regulation of hepatic glucose output and peripheral glucose utilization. The antibody had no effect in aP2-deficient mice, demonstrating its target specificity. We conclude that an aP2 mAb-mediated therapeutic constitutes a feasible approach for the treatment of diabetes.

Enterovirus D68 (EV-D68) caused a severe respiratory illness outbreak in the United States in 2014. Reports of acute flaccid myelitis (AFM)/paralysis (AFP) in several independent epidemiological clusters of children with detectable EV-D68 have raised concerns that genetic changes in EV-D68 could be causing increased disease severity and neurological symptoms. To explore the potential link between EV-D68 genetic variations and symptom changes, we performed a series of comparative genomic analyses of EV-D68 2014 outbreak isolate sequences using data and analytical tools in the Virus Pathogen Resource (ViPR; www.viprbrc.org). Our results suggest that (1) three distinct lineages of EV-D68 were co-circulating in 2013 and 2014; (2) isolates associated with AFM/AFP belong to a single phylogenetic subclade – B1; (3) the majority of isolates from the B1 subclade have 21 unique substitutions that distinguish them from other isolates, including amino acid substitutions in the VP1, VP2, and VP3 capsid proteins and the 3D RNA-dependent RNA polymerase, and nucleotide substitutions in the internal ribosome entry sequence (IRES); (4) at 12 of these positions, B1 isolates carry the same residues observed at equivalent positions in paralysis-causing enteroviruses, including poliovirus, EV-D70 and EV-A71. Based on these results, we hypothesize that unique B1 substitutions may be responsible for the apparent increased incidence of neuropathology associated with the 2014 outbreak.