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Motivation The number of protein records in the UniProt Knowledgebase (UniProtKB: https://www.uniprot.org) continues to grow rapidly as a result of genome sequencing and the prediction of protein-coding genes. Providing functional annotation for these proteins presents a significant and continuing challenge. Results In response to this challenge, UniProt has developed a method of annotation, known as UniRule, based on expertly curated rules, which integrates related systems (RuleBase, HAMAP, PIRSR, PIRNR) developed by the members of the UniProt consortium. UniRule uses protein family signatures from InterPro, combined with taxonomic and other constraints, to select sets of reviewed proteins which have common functional properties supported by experimental evidence. This annotation is propagated to unreviewed records in UniProtKB that meet the same selection criteria, most of which do not have (and are never likely to have) experimentally verified functional annotation. Release 2020_01 of UniProtKB contains 6496 UniRule rules which provide annotation for 53 million proteins, accounting for 30% of the 178 million records in UniProtKB. UniRule provides scalable enrichment of annotation in UniProtKB. Availability and implementation UniRule rules are integrated into UniProtKB and can be viewed at https://www.uniprot.org/unirule/. UniRule rules and the code required to run the rules, are publicly available for researchers who wish to annotate their own sequences. The implementation used to run the rules is known as UniFIRE and is available at https://gitlab.ebi.ac.uk/uniprot-public/unifire.

Motivation Biological knowledgebases, such as UniProtKB/Swiss-Prot, constitute an essential component of daily scientific research by offering distilled, summarized and computable knowledge extracted from the literature by expert curators. While knowledgebases play an increasingly important role in the scientific community, their ability to keep up with the growth of biomedical literature is under scrutiny. Using UniProtKB/Swiss-Prot as a case study, we address this concern via multiple literature triage approaches. Results With the assistance of the PubTator text-mining tool, we tagged more than 10 000 articles to assess the ratio of papers relevant for curation. We first show that curators read and evaluate many more papers than they curate, and that measuring the number of curated publications is insufficient to provide a complete picture as demonstrated by the fact that 8000–10 000 papers are curated in UniProt each year while curators evaluate 50 000–70 000 papers per year. We show that 90% of the papers in PubMed are out of the scope of UniProt, that a maximum of 2–3% of the papers indexed in PubMed each year are relevant for UniProt curation, and that, despite appearances, expert curation in UniProt is scalable. Availability and implementation UniProt is freely available at http://www.uniprot.org/. Supplementary information Supplementary data are available at Bioinformatics online.

Phosphatases play an essential role in the regulation of protein phosphorylation. Less abundant than kinases, many phosphatases are components of one or more macromolecular complexes with different substrate specificities and specific functionalities. The expert scientific curation of phosphatase complexes for the UniProt and Complex Portal databases supports the whole scientific community by collating and organising small- and large-scale experimental data from the scientific literature into context-specific central resources, where the data can be freely accessed and used to further academic and translational research. In this review, we discuss how the diverse biological functions of phosphatase complexes are presented in UniProt and the Complex Portal, and how understanding the biological significance of phosphatase complexes in Caenorhabditis elegans offers insight into the mechanisms of substrate diversity in a variety of cellular and molecular processes.

Mass-spectrometry-based proteomics enables the high-throughput identification and quantification of proteins, including sequence variants and post-translational modifications (PTMs) in biological samples. However, most workflows require that such variations be included in the search space used to analyze the data, and doing so remains challenging with most analysis tools. In order to facilitate the search for known sequence variants and PTMs, the Proteomics Standards Initiative (PSI) has designed and implemented the PSI extended FASTA format (PEFF). PEFF is based on the very popular FASTA format but adds a uniform mechanism for encoding substantially more metadata about the sequence collection as well as individual entries, including support for encoding known sequence variants, PTMs, and proteoforms. The format is very nearly backward compatible, and as such, existing FASTA parsers will require little or no changes to be able to read PEFF files as FASTA files, although without supporting any of the extra capabilities of PEFF. PEFF is defined by a full specification document, controlled vocabulary terms, a set of example files, software libraries, and a file validator. Popular software and resources are starting to support PEFF, including the sequence search engine Comet and the knowledge bases neXtProt and UniProtKB. Widespread implementation of PEFF is expected to further enable proteogenomics and top-down proteomics applications by providing a standardized mechanism for encoding protein sequences and their known variations. All the related documentation, including the detailed file format specification and example files, are available at http://www.psidev.info/peff. acceptedVersion

International audience; The Consortium for Top-Down Proteomics (CTDP) proposes a standardized notation, ProForma, for writing the sequence of fully characterized proteoforms. ProForma provides a means to communicate any proteoform by writing the amino acid sequence using standard one-letter notation and specifying modifications or unidentified mass shifts within brackets following certain amino acids. The notation is unambiguous, human-readable, and can easily be parsed and written by bioinformatic tools. This system uses seven rules and supports a wide range of possible use cases, ensuring compatibility and reproducibility of proteoform annotations. Standardizing proteoform sequences will simplify storage, comparison, and reanalysis of proteomic studies, and the Consortium welcomes input and contributions from the research community on the continued design and maintenance of this standard.

Candida infection has emerged as a critical health care burden worldwide, owing to the formation of robust biofilms against common antifungals. Recent evidence shows that multidrug-tolerant persisters critically account for biofilm recalcitrance, but their underlying biological mechanisms are poorly understood. Here, we first investigated the phenotypic characteristics of Candida biofilm persisters under consecutive harsh treatments of amphotericin B. The prolonged treatments effectively killed the majority of the cells of biofilms derived from representative strains of Candida albicans , Candida glabrata , and Candida tropicalis but failed to eradicate a small fraction of persisters. Next, we explored the tolerance mechanisms of the persisters through an investigation of the proteomic profiles of C. albicans biofilm persister fractions by liquid chromatography-tandem mass spectrometry. The C. albicans biofilm persisters displayed a specific proteomic signature, with an array of 205 differentially expressed proteins. The crucial enzymes involved in glycolysis, the tricarboxylic acid cycle, and protein synthesis were markedly downregulated, indicating that major metabolic activities are subdued in the persisters. It is noteworthy that certain metabolic pathways, such as the glyoxylate cycle, were able to be activated with significantly increased levels of isocitrate lyase and malate synthase. Moreover, a number of important proteins responsible for Candida growth, virulence, and the stress response were greatly upregulated. Interestingly, the persisters were tolerant to oxidative stress, despite highly induced intracellular superoxide. The current findings suggest that delicate metabolic control and a coordinated stress response may play a crucial role in mediating the survival and antifungal tolerance of Candida biofilm persisters.

Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data.

In this article, we provide a comprehensive study of the content of the Universal Protein Resource (UniProt) protein data sets for human and mouse. The tryptic search spaces of the UniProtKB (UniProt knowledgebase) complete proteome sets were compared with other data sets from UniProtKB and with the corresponding International Protein Index, reference sequence, Ensembl, and UniRef100 (where UniRef is UniProt reference clusters) organism-specific data sets. All protein forms annotated in UniProtKB (both the canonical sequences and isoforms) were evaluated in this study. In addition, natural and disease-associated amino acid variants annotated in UniProtKB were included in the evaluation. The peptide unicity was also evaluated for each data set. Furthermore, the peptide information in the UniProtKB data sets was also compared against the available peptide-level identifications in the main MS-based proteomics repositories. Identifying the peptides observed in these repositories is an important resource of information for protein databases as they provide supporting evidence for the existence of otherwise predicted proteins. Likewise, the repositories could use the information available in UniProtKB to direct reprocessing efforts on specific sets of peptides/proteins of interest. In summary, we provide comprehensive information about the different organism-specific sequence data sets available from UniProt, together with the pros and cons for each, in terms of search space for MS-based bottom-up proteomics workflows. The aim of the analysis is to provide a clear view of the tryptic search space of UniProt and other protein databases to enable scientists to select those most appropriate for their purposes.

Summary ProtVista is a comprehensive visualization tool for the graphical representation of protein sequence features in the UniProt Knowledgebase, experimental proteomics and variation public datasets. The complexity and relationships in this wealth of data pose a challenge in interpretation. Integrative visualization approaches such as provided by ProtVista are thus essential for researchers to understand the data and, for instance, discover patterns affecting function and disease associations. Availability and Implementation ProtVista is a JavaScript component released as an open source project under the Apache 2 License. Documentation and source code are available at http://ebi-uniprot.github.io/ProtVista/. Supplementary information Supplementary data are available at Bioinformatics online.

The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data (UniProt Consortium, 2015). The UniProt Web site receives ∼400,000 unique visitors per month and is the primary means to access UniProt. Along with various datasets that you can search, UniProt provides three main tools. These are the ‘BLAST’ tool for sequence similarity searching, the ‘Align’ tool for multiple sequence alignment, and the ‘Retrieve/ID Mapping’ tool for using a list of identifiers to retrieve UniProtKB proteins and to convert database identifiers from UniProt to external databases or vice versa. This unit provides three basic protocols, three alternate protocols, and two support protocols for using UniProt tools. © 2016 by John Wiley & Sons, Inc. Keywords: UniProt; search; navigation; tutorial

Neuronal CIPP (channel-interacting PDZ protein) is a multivalent PDZ protein that interacts with specific channels and receptors highly expressed in the brain. It is composed of four PDZ domains that behave as a scaffold to clusterize functionally connected proteins. In the present study, we selected a set of potential CIPP interactors that are involved directly or indirectly in mechanisms of cytoskeletal remodelling and membrane protrusion formation. For some of these, we first proved the direct binding to specific CIPP PDZ domains considered as autonomous elements, and then confirmed the interaction with the whole protein. In particular, the small G-protein effector IRSp53 (insulin receptor tyrosine kinase substrate protein p53) specifically interacts with the second PDZ domain of CIPP and, when co-transfected in cultured mammalian cells with a tagged full-length CIPP, it induces a marked reorganization of CIPP cytoplasmic localization. Large punctate structures are generated as a consequence of CIPP binding to the IRSp53 C-terminus. Analysis of the puncta nature, using various endocytic markers, revealed that they are not related to cytoplasmic vesicles, but rather represent multi-protein assemblies, where CIPP can tether other potential interactors.

The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt Web site receives ∼400,000 unique visitors per month and is the primary means to access UniProt. It provides ten searchable datasets and three main tools. The key UniProt datasets are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), the UniProt Archive (UniParc), and protein sets for completely sequenced genomes (Proteomes). Other supporting datasets include information about proteins that is present in UniProtKB protein entries such as literature citations, taxonomy, and subcellular locations, among others. This paper focuses on how to use UniProt datasets. The basic protocol describes navigation and searching mechanisms for the UniProt datasets, while two alternative protocols build on the basic protocol to describe advanced search and query building.

0000-0002-1521-4306 WOS: 000352268900017 PubMed ID: 25398609 Motivation: UniRef databases provide full-scale clustering of UniProtKB sequences and are utilized for a broad range of applications, particularly similarity-based functional annotation. Non-redundancy and intra-cluster homogeneity in UniRef were recently improved by adding a sequence length overlap threshold. Our hypothesis is that these improvements would enhance the speed and sensitivity of similarity searches and improve the consistency of annotation within clusters. Results: Intra-cluster molecular function consistency was examined by analysis of Gene Ontology terms. Results show that UniRef clusters bring together proteins of identical molecular function in more than 97% of the clusters, implying that clusters are useful for annotation and can also be used to detect annotation inconsistencies. To examine coverage in similarity results, BLASTP searches against UniRef50 followed by expansion of the hit lists with cluster members demonstrated advantages compared with searches against UniProtKB sequences; the searches are concise (similar to 7 times shorter hit list before expansion), faster (similar to 6 times) and more sensitive in detection of remote similarities (>96% recall at e-value

Summary: We have developed a new web application for peptide matching using Apache Lucene-based search engine. The Peptide Match service is designed to quickly retrieve all occurrences of a given query peptide from UniProt Knowledgebase (UniProtKB) with isoforms. The matched proteins are shown in summary tables with rich annotations, including matched sequence region(s) and links to corresponding proteins in a number of proteomic/peptide spectral databases. The results are grouped by taxonomy and can be browsed by organism, taxonomic group or taxonomy tree. The service supports queries where isobaric leucine and isoleucine are treated equivalent, and an option for searching UniRef100 representative sequences, as well as dynamic queries to major proteomic databases. In addition to the web interface, we also provide RESTful web services. The underlying data are updated every 4 weeks in accordance with the UniProt releases. Availability: http://proteininformationresource.org/peptide.shtml Contact: ude.ledu@cnehc Supplementary information: Supplementary data are available at Bioinformatics online.

Background A number of Tuber species are ecologically important. The fruiting bodies of some of these also have value as a cooking ingredient due to the fact that they possess exceptional flavor and aromatic properties. In particular, T. magnatum fruiting bodies (commonly known as truffles), are greatly appreciated by consumers. These grow naturally in some parts of Italy. However, the quality of these fruiting bodies varies significantly depending on the area of origin due to differences in environmental growth conditions. It is therefore useful to be able to characterize them. A suitable method to reach this goal is to identify proteins which occur in the fruiting bodies that are specific to each area of origin. In this work protein profiles are described for samples coming from different areas and collected in two successive years. To our knowledge this is the first time that proteins of T. magnatum have been thoroughly examined. Results Using two dimensional electrophoresis, reproducible quantitative differences in the protein patterns (total 600 spots) of samples from different parts of Italy (accession areas) were revealed by bioinformatic analysis. 60 spots were chosen for further analysis, out of which 17 could probably be used to distinguish a sample grown in one area from a sample grown in another area. Mass spectrometry (MS) protein analysis of these seventeen spots allowed the identification of 17 proteins of T. magnatum. Conclusions The results indicate that proteomic analysis is a suitable method for characterizing those differences occurring in samples and induced by the different environmental conditions present in the various Italian areas where T. magnatum can grow. The positive protein identification by MS analysis has proved that this method can be applied with success even in a species whose genome, at the moment, has not been sequenced.

Vascular smooth-muscle cells (VSMCs) are the main components of the artery medial layer and if activated by growth factors (such as PDGF-BB) as a consequence of vessel injuries, acquire the ability to proliferate and migrate contributing to the formation of neointima. In the early times of VSMC stimulation a cascade of kinases and phosphatases initiates phospho-events that are decisive for VSMC activation, which terminates with a reorganization of the cell structure. In this work, a shotgun proteomics approach aimed at disclosing factors involved in these phenotypically imperceptible, but significant events has been applied. A SILAC approach in a multi-strategy combined method for phosphopeptides enrichment was used, in order to gain insights into the phosphomodulation of VSMC proteome stimulated by PDGF-BB. We performed a quantitative SILAC phosphoproteome analysis on primary VSMC cells which allowed the identification of 1300 phosphopeptides among which 47 resulted novel phosphosites. Moreover, in VSMC signaling events, some important factors involved in cytoskeleton remodeling, focal adhesions, gap junction assembly and cell activation have been found differentially phosphorylated, highlighting their pivotal role in early VSMC reorganization and suggesting a novel starting point to assess the precise actors of VSMC activation and their roles.

This study used 2DE to investigate how Arabidopsis thaliana modulates protein levels in response to freezing stress after sub-lethal exposure at − 10 °C, both in cold-acclimated and in non-acclimated plants. A map was implemented in which 62 spots, corresponding to 44 proteins, were identified. Twenty-two spots were modulated upon treatments, and the corresponding proteins proved to be related to photosynthesis, energy metabolism, and stress response. Proteins demonstrated differences between control and acclimation conditions. Most of the acclimation-responsive proteins were either not further modulated or they were down-modulated by freezing treatment, indicating that the levels reached during acclimation were sufficient to deal with freezing. Anabolic metabolism appeared to be down-regulated in favor of catabolic metabolism. Acclimated plants and plants submitted to freezing after acclimation showed greater reciprocal similarity in protein profiles than either showed when compared both to control plants and to plants frozen without acclimation. The response of non-acclimated plants was aimed at re-modulating photosynthetic apparatus activity, and at increasing the levels of proteins with antioxidant-, molecular chaperone-, or post-transcriptional regulative functions. These changes, even less effective than the acclimation strategy, might allow the injured plastids to minimize the production of non-useful metabolites and might counteract photosynthetic apparatus injuries.