Search

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.

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.

The UniProt Knowledgebase is a collection of sequences and annotations for over 120 million proteins across all branches of life. Detailed annotations extracted from the literature by expert curators have been collected for over half a million of these proteins. These annotations are supplemented by annotations provided by rule based automated systems, and those imported from other resources. In this article we describe significant updates that we have made over the last 2 years to the resource. We have greatly expanded the number of Reference Proteomes that we provide and in particular we have focussed on improving the number of viral Reference Proteomes. The UniProt website has been augmented with new data visualizations for the subcellular localization of proteins as well as their structure and interactions. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.

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.

The Proteins API provides searching and programmatic access to protein and associated genomics data such as curated protein sequence positional annotations from UniProtKB, as well as mapped variation and proteomics data from large scale data sources (LSS). Using the coordinates service, researchers are able to retrieve the genomic sequence coordinates for proteins in UniProtKB. This, the LSS genomics and proteomics data for UniProt proteins is programmatically only available through this service. A Swagger UI has been implemented to provide documentation, an interface for users, with little or no programming experience, to ‘talk’ to the services to quickly and easily formulate queries with the services and obtain dynamically generated source code for popular programming languages, such as Java, Perl, Python and Ruby. Search results are returned as standard JSON, XML or GFF data objects. The Proteins API is a scalable, reliable, fast, easy to use RESTful services that provides a broad protein information resource for users to ask questions based upon their field of expertise and allowing them to gain an integrated overview of protein annotations available to aid their knowledge gain on proteins in biological processes. The Proteins API is available at (http://www.ebi.ac.uk/proteins/api/doc).

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.

UniProt continues to support the ongoing process of making scientific data FAIR. Here we contribute to this process with a FAIRness assessment of our UniProtKB dataset followed by a critical reflection on the challenges and future directions of the adoption and validation of the FAIR principles and metrics.

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 backwards 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 athttp://www.psidev.info/peff.

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

Personalized genomic medicine depends on integrated analyses that combine genetic and phenotypic data from individual patients with reference knowledge of the functional and clinical significance of sequence variants. Sources of this reference knowledge include the ClinVar repository of human genetic variants, a community resource that accepts submissions from external groups, and UniProtKB/Swiss-Prot, an expert-curated resource of protein sequences and functional annotation. UniProtKB/Swiss-Prot provides knowledge on the functional impact and clinical significance of over 30 000 human protein-coding sequence variants, curated from peer-reviewed literature reports. Here we present a pilot study that lays the groundwork for the integration of curated knowledge of protein sequence variation from UniProtKB/Swiss-Prot with ClinVar. We show that existing interpretations of variant pathogenicity in UniProtKB/Swiss-Prot and ClinVar are highly concordant, with 88% of variants that are common to the two resources having interpretations of clinical significance that agree. Re-curation of a subset of UniProtKB/Swiss-Prot variants according to American College of Medical Genetics and Genomics (ACMG) guidelines using ClinGen tools further increases this level of agreement, mainly due to the reclassification of supposedly pathogenic variants as benign, based on newly available population frequency data. We have now incorporated ACMG guidelines and ClinGen tools into the UniProt Knowledgebase (UniProtKB) curation workflow and routinely submit variant data from UniProtKB/Swiss-Prot to ClinVar. These efforts will increase the usability and utilization of UniProtKB variant data and will facilitate the continuing (re-)evaluation of clinical variant interpretations as data sets and knowledge evolve.

The UniProt knowledgebase is a large resource of protein sequences and associated detailed annotation. The database contains over 60 million sequences, of which over half a million sequences have been curated by experts who critically review experimental and predicted data for each protein. The remainder are automatically annotated based on rule systems that rely on the expert curated knowledge. Since our last update in 2014, we have more than doubled the number of reference proteomes to 5631, giving a greater coverage of taxonomic diversity. We implemented a pipeline to remove redundant highly similar proteomes that were causing excessive redundancy in UniProt. The initial run of this pipeline reduced the number of sequences in UniProt by 47 million. For our users interested in the accessory proteomes, we have made available sets of pan proteome sequences that cover the diversity of sequences for each species that is found in its strains and sub-strains. To help interpretation of genomic variants, we provide tracks of detailed protein information for the major genome browsers. We provide a SPARQL endpoint that allows complex queries of the more than 22 billion triples of data in UniProt (http://sparql.uniprot.org/). UniProt resources can be accessed via the website at http://www.uniprot.org/.

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.

The mission of the Universal Protein Resource (UniProt) (http://www.uniprot.org) is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequences and functional annotation. It integrates, interprets and standardizes data from literature and numerous resources to achieve the most comprehensive catalog possible of protein information. The central activities are the biocuration of the UniProt Knowledgebase and the dissemination of these data through our Web site and web services. UniProt is produced by the UniProt Consortium, which consists of groups from the European Bioinformatics Institute (EBI), the SIB Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is updated and distributed every 4 weeks and can be accessed online for searches or downloads.

HAMAP (High-quality Automated and Manual Annotation of Proteins-available at http://hamap.expasy.org/) is a system for the classification and annotation of protein sequences. It consists of a collection of manually curated family profiles for protein classification, and associated annotation rules that specify annotations that apply to family members. HAMAP was originally developed to support the manual curation of UniProtKB/Swiss-Prot records describing microbial proteins. Here we describe new developments in HAMAP, including the extension of HAMAP to eukaryotic proteins, the use of HAMAP in the automated annotation of UniProtKB/TrEMBL, providing high-quality annotation for millions of protein sequences, and the future integration of HAMAP into a unified system for UniProtKB annotation, UniRule. HAMAP is continuously updated by expert curators with new family profiles and annotation rules as new protein families are characterized. The collection of HAMAP family classification profiles and annotation rules can be browsed and viewed on the HAMAP website, which also provides an interface to scan user sequences against HAMAP profiles.

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

Advances in high-throughput and advanced technologies allow researchers to routinely perform whole genome and proteome analysis. For this purpose, they need high-quality resources providing comprehensive gene and protein sets for their organisms of interest. Using the example of the human proteome, we will describe the content of a complete proteome in the UniProt Knowledgebase (UniProtKB). We will show how manual expert curation of UniProtKB/Swiss-Prot is complemented by expert-driven automatic annotation to build a comprehensive, high-quality and traceable resource. We will also illustrate how the complexity of the human proteome is captured and structured in UniProtKB. Database URL: www.uniprot.org.

The PRoteomics IDEntifications (PRIDE, http://www.ebi.ac.uk/pride) database at the European Bioinformatics Institute is one of the most prominent data repositories of mass spectrometry (MS)-based proteomics data. Here, we summarize recent developments in the PRIDE database and related tools. First, we provide up-to-date statistics in data content, splitting the figures by groups of organisms and species, including peptide and protein identifications, and post-translational modifications. We then describe the tools that are part of the PRIDE submission pipeline, especially the recently developed PRIDE Converter 2 (new submission tool) and PRIDE Inspector (visualization and analysis tool). We also give an update about the integration of PRIDE with other MS proteomics resources in the context of the ProteomeXchange consortium. Finally, we briefly review the quality control efforts that are ongoing at present and outline our future plans.

The mission of the Universal Protein Resource (UniProt) (http://www.uniprot.org) is to support biological research by providing a freely accessible, stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase. It integrates, interprets and standardizes data from numerous resources to achieve the most comprehensive catalogue of protein sequences and functional annotation. UniProt comprises four major components, each optimized for different uses, the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is produced by the UniProt Consortium, which consists of groups from the European Bioinformatics Institute (EBI), the SIB Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is updated and distributed every 4 weeks and can be accessed online for searches or downloads.

Public availability of biological sequences is essential for their widespread access and use by the research community. The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and functional data. While most protein sequences entering UniProt are imported from other source databases containing nucleotide or 3-D structure data, protein sequences determined at the protein level can be submitted directly to UniProt. To this end, UniProt provides a Web interface called SPIN. This service enables researchers to make their de novo-sequenced proteins available to the scientific community and acquire UniProt accession numbers for use in publications. This unit explains the process of submitting a protein sequence to UniProt using SPIN. The basic protocol describes all the necessary steps for a single sequence. A support protocol gives guidance on how best to deal with exceptionally large datasets. © 2018 by John Wiley & Sons, Inc.

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

UniProt is an important collection of protein sequences and their annotations, which has doubled in size to 80 million sequences during the past year. This growth in sequences has prompted an extension of UniProt accession number space from 6 to 10 characters. An increasing fraction of new sequences are identical to a sequence that already exists in the database with the majority of sequences coming from genome sequencing projects. We have created a new proteome identifier that uniquely identifies a particular assembly of a species and strain or subspecies to help users track the provenance of sequences. We present a new website that has been designed using a user-experience design process. We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein. These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis. All UniProt data is provided freely and is available on the web at http://www.uniprot.org/.

UniProtKB/Swiss-Prot provides expert curation with information extracted from literature and curator-evaluated computational analysis. As knowledgebases continue to play an increasingly important role in scientific research, a number of studies have evaluated their accuracy and revealed various errors. While some are curation errors, others are the result of incorrect information published in the scientific literature. By taking the example of sirtuin-5, a complex annotation case, we will describe the curation procedure of UniProtKB/Swiss-Prot and detail how we report conflicting information in the database. We will demonstrate the importance of collaboration between resources to ensure curation consistency and the value of contributions from the user community in helping maintain error-free resources. Database URL: www.uniprot.org

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.

The UniProt KnowledgeBase (UniProtKB) provides a single, centralized, authoritative resource for protein sequences and functional information. The majority of its records is based on automatic translation of coding sequences (CDS) provided by submitters at the time of initial deposition to the nucleotide sequence databases (INSDC). This article will give a general overview of the current situation, with some specific illustrations extracted from our annotation of Arabidopsis and rice proteomes. More and more frequently, only the raw sequence of a complete genome is deposited to the nucleotide sequence databases and the gene model predictions and annotations are kept in separate, specialized model organism databases (MODs). In order to be able to provide the complete proteome of model organisms, UniProtKB had to implement pipelines for import of protein sequences from Ensembl and EnsemblGenomes. A single genome can be the target of several unrelated sequencing projects and the final assembly and gene model predictions may diverge quite significantly. In addition, several cultivars of the same species are often sequenced - 1001 Arabidopsis cultivars are currently under way - and the resulting proteomes are far from being identical. Therefore, one challenge for UniProtKB is to store and organize these data in a convenient way and to clearly defined reference proteomes that should be made available to users. Manual annotation is one of the landmarks of the Swiss-Prot section of UniProtKB. Besides adding functional annotation, curators are checking, and often correcting, gene model predictions. For plants, this task is limited to Arabidopsis thaliana and Oryza sativa subsp. japonica. Proteomics data providing experimental evidences confirming the existence of proteins or identifying sequence features such as post-translational modifications are also imported into UniProtKB records and the knowledgebase is cross-referenced to numerous proteomics resource.

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.

Summary The integration of viral cDNA into the host genome is a critical step in the life cycle of HIV-1. This step is catalyzed by integrase (IN), a viral enzyme that is positively regulated by acetylation via the cellular histone acetyl transferase (HAT) p300. To investigate the relevance of IN acetylation, we searched for cellular proteins that selectively bind acetylated IN and identified KAP1, a protein belonging to the TRIM family of antiviral proteins. KAP1 binds acetylated IN and induces its deacetylation through the formation of a protein complex which includes the deacetylase HDAC1. Modulation of intracellular KAP1 levels in different cell types including T cells, the primary HIV-1 target, revealed that KAP1 curtails viral infectivity by selectively affecting HIV-1 integration. This study identifies KAP1 as a cellular factor restricting HIV-1 infection and underscores the relevance of IN acetylation as a crucial step in the viral infectious cycle.

Trideuterated tocopherols were needed to be used as internal standards for our study about simultaneous quantitative determination of tocopherols in foodstuffs by mass spectrometry. Whilst procedures for trideuterated α-tocopherol have been recently optimized, no method is reported as regards δ-tocopherol. Different synthetic approaches are discussed, as well as the first procedure for the synthesis of (8-2H3)-(all-rac)-δ-tocopherol. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2003)

The idea that stem cell therapies work only via cell replacement is challenged by the observation of consistent intercellular molecule exchange between the graft and the host. Here we defined a mechanism of cellular signaling by which neural stem/precursor cells (NPCs) communicate with the microenvironment via extracellular vesicles (EVs), and we elucidated its molecular signature and function. We observed cytokine-regulated pathways that sort proteins and mRNAs into EVs. We described induction of interferon gamma (IFN-γ) pathway in NPCs exposed to proinflammatory cytokines that is mirrored in EVs. We showed that IFN-γ bound to EVs through Ifngr1 activates Stat1 in target cells. Finally, we demonstrated that endogenous Stat1 and Ifngr1 in target cells are indispensable to sustain the activation of Stat1 signaling by EV-associated IFN-γ/Ifngr1 complexes. Our study identifies a mechanism of cellular signaling regulated by EV-associated IFN-γ/Ifngr1 complexes, which grafted stem cells may use to communicate with the host immune system.