Paul Denny

UniProt is a comprehensive, expert-led, publicly available database of protein sequence, function, and variation information. This webinar will give a brief introduction to the UniProt website and then highlight resources which should be of interest to people beginning work on antimicrobial resistance (AMR), including students, early-stage researchers, and clinicians. AMR constitutes one of the world’s most urgent public health problems. We have been improving the annotation of various protein classes with a known role in AMR, including beta-lactamases, efflux pumps and ABC transporters, and other proteins indirectly involved in the survival of resistant bacteria, such as those playing a role in quorum sensing and biofilm formation. Using these as examples, we will introduce some of the UniProt resources. UniProt annotations are widely disseminated to other databases, including Rhea, EnsemblBacteria, PATRIC (Bacterial & Viral Bioinformatics Resource Center), BioCyc/EcoCyc and KEGG.

UniProt provides the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequence and functional information. This webinar will guide you through ways in which students and researchers at all career stages may take a structured approach to access the data in the UniProtKB and Proteomes sections of the UniProt protein function database. The webinar will discuss the types of data that can be accessed, and using sequence analysis tools, how this data can be analysed to answer biological questions. We will demonstrate how to find the function of a protein, how the protein components of a pathway may be identified, features of proteins of interest can be compared, similar sections of sequence can be sought in other species and how whole data sets containing all the proteins expressed in an organism can be obtained. By accessing sequence, structural and functional data through UniProt, we want researchers to be part of data’s biological journey and support further work and adventures along the way!

UniProt provides the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequence and functional information. This webinar will guide you through ways in which students and researchers at all career stages may take a structured approach to access the data in the UniProtKB and Proteomes sections of the UniProt protein function database.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO—a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations—evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)—mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Standardized gene naming is crucial for effective communication about genes, and as genomics becomes increasingly important in health care, the need for a consistent language to refer to human genes becomes ever more essential. Here, we present the current HUGO Gene Nomenclature Committee (HGNC) guidelines for naming not only protein-coding genes but also RNA genes and pseudogenes, and we outline the changes in approach and ethos that have resulted from the discoveries of the past few decades.

Streptococcus pneumoniae is a major human pathogen, causing pneumonia and sepsis. Genetic components strongly influence host responses to pneumococcal infections, but the responsible loci are unknown. We have previously identified a locus on mouse chromosome 7 from a susceptible mouse strain, CBA/Ca, to be crucial for pneumococcal infection. Here we identify a responsible gene, Cd22, which carries a point mutation in the CBA/Ca strain, leading to loss of CD22 on B cells. CBA/Ca mice and gene-targeted CD22-deficient mice on a C57BL/6 background are both similarly susceptible to pneumococcal infection, as shown by bacterial replication in the lungs, high bacteremia and early death. After bacterial infections, CD22-deficient mice had strongly reduced B cell populations in the lung, including GM-CSF producing, IgM secreting innate response activator B cells, which are crucial for protection. This study provides striking evidence that CD22 is crucial for protection during invasive pneumococcal disease. Streptococcus pneumoniae (known as the pneumococcus) is a human bacterial pathogen responsible for diseases such as pneumonia and sepsis, that cause illness and death in millions of individuals. Susceptibility to pneumococcal infections is associated with genetic components that strongly influence how infected individuals respond to infection, but little is known about the causal gene(s) and the mechanisms of control of the infection. In previous studies we have found strong differences in susceptibility and resistance to pneumococcal infections between mouse strains. In this study we identified a gene, the Cd22 gene, that controls resistance to pneumococcal infection. Mice without the B-cell specific CD22 protein were much more susceptible to infection with S. pneumoniae. We could show that a protective population of B cells that migrates to the lung during pneumococcal infection is missing in Cd22-deficient mice. The study shows to a new role for CD22 and indicates a new potential target for treatment of pneumococcal infections.

The HUGO Gene Nomenclature Committee (HGNC) based at EMBL’s European Bioinformatics Institute (EMBL-EBI) assigns unique symbols and names to human genes. There are over 40 000 approved gene symbols in our current database of which over 19 000 are for protein-coding genes. The Vertebrate Gene Nomenclature Committee (VGNC) was established in 2016 to assign standardized nomenclature in line with human for vertebrate species that lack their own nomenclature committees. The VGNC initially assigned nomenclature for over 15000 protein-coding genes in chimpanzee. We have extended this process to other vertebrate species, naming over 14000 protein-coding genes in cow and dog and over 13 000 in horse to date. Our HGNC website https://www.genenames.org has undergone a major design update, simplifying the homepage to provide easy access to our search tools and making the site more mobile friendly. Our gene families pages are now known as ‘gene groups’ and have increased in number to over 1200, with nearly half of all named genes currently assigned to at least one gene group. This article provides an overview of our online data and resources, focusing on our work over the last two years.

Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular stresses and ridding cells of foreign material. Perturbations in autophagy have been implicated in a number of pathological conditions such as neurodegeneration, cardiac disease and cancer. The growing knowledge about autophagic mechanisms needs to be collected in a computable and shareable format to allow its use in data representation and interpretation. The Gene Ontology (GO) is a freely available resource that describes how and where gene products function in biological systems. It consists of 3 interrelated structured vocabularies that outline what gene products do at the biochemical level, where they act in a cell and the overall biological objectives to which their actions contribute. It also consists of ‘annotations’ that associate gene products with the terms. Here we describe how we represent autophagy in GO, how we create and define terms relevant to autophagy researchers and how we interrelate those terms to generate a coherent view of the process, therefore allowing an interoperable description of its biological aspects. We also describe how annotation of gene products with GO terms improves data analysis and interpretation, hence bringing a significant benefit to this field of study.

Building effective and supportive communities of practice in an asynchronous environment can enable students to learn from each other at their own convenient times without the need to meeting for discussing concepts. In an undergraduate course with a large amount of content to learn, working collaboratively to answer practice exam questions can help encourage deeper learning and understanding. This project examined whether exam performance can be positively influenced by online collaboration during revision and suggests that the quality of an individual’s contribution has a direct effect on his/her subsequent exam performance. We compared two student cohorts’ exam marks from their previous 3 years of exams with how they performed in Year 4 after using PeerWise (an online repository of multiple-choice questions that are created, answered, rated and discussed by students). In addition, we looked at the quantity and quality of their contribution in PeerWise to evaluate how this affected their fourth year exam performance. We confirmed that exam performance is improved by authoring questions in PeerWise, but found it is further enhanced by replying to, and commenting on, others’ posts as well. Published: 3 January 2018 Citation: Research in Learning Technology 2017, 25: 1979 - http://dx.doi.org/10.25304/rlt.v25.1979