ELM—the database of eukaryotic linear motifs

Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instance

Ten Simple Rules for Organizing an Unconference

This is an open access article distributed under the terms of the Creative Commons Attribution License.Peer Reviewe

An Open Science Peer Review Oath

One of the foundations of the scientific method is to be able to reproduce experiments and corroborate the results of research that has been done before. However, with the increasing complexities of new technologies and techniques, coupled with the specialisation of experiments, reproducing research findings has become a growing challenge. Clearly, scientific methods must be conveyed succinctly, and with clarity and rigour, in order for research to be reproducible. Here, we propose steps to help increase the transparency of the scientific method and the reproducibility of research results: specifically, we introduce a peer-review oath and accompanying manifesto. These have been designed to offer guidelines to enable reviewers (with the minimum friction or bias) to follow and apply open science principles, and support the ideas of transparency, reproducibility and ultimately greater societal impact. Introducing the oath and manifesto at the stage of peer review will help to check that the research being published includes everything that other researchers would need to successfully repeat the work. Peer review is the lynchpin of the publishing system: encouraging the community to consciously (and conscientiously) uphold these principles should help to improve published papers, increase confidence in the reproducibility of the work and, ultimately, provide strategic benefits to authors and their institutions

Experimental detection of short regulatory motifs in eukaryotic proteins: tips for good practice as well as for bad

It has become clear in outline though not yet in detail how cellular regulatory and signalling systems are constructed. The essential machines are protein complexes that effect regulatory decisions by undergoing internal changes of state. Subcomponents of these cellular complexes are assembled into molecular switches. Many of these switches employ one or more short peptide motifs as toggles that can move between one or more sites within the switch system, the simplest being on-off switches. Paradoxically, these motif modules (termed short linear motifs or SLiMs) are both hugely abundant but difficult to research. So despite the many successes in identifying short regulatory protein motifs, it is thought that only the “tip of the iceberg” has been exposed. Experimental and bioinformatic motif discovery remain challenging and error prone. The advice presented in this article is aimed at helping researchers to uncover genuine protein motifs, whilst avoiding the pitfalls that lead to reports of false discovery. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12964-015-0121-y) contains supplementary material, which is available to authorized users

A computational strategy for the prediction of functional interaction motifs

Eine Vielzahl an wichtigen Protein:Protein-Interaktionen wird von relativ kleinen Adapterdomänen (z.B. SH2, SH3, PDZ, WW) vermittelt. Diese Domänen binden an kurze Peptide, die spezifische Sequenzmotive aufweisen. Das Charakteristische dieser Interaktionen ist, daß ein Partner (die Interaktionsdomäne) eine globuläre Struktur aufweist, während der zweite Interaktionspartner (das Interaktionsmotiv) einen linearen Sequenzabschnitt darstellt. Derartige Interaktionen sind überaus wichtig für die zelluläre Signaltransduktion via Rezeptoren, für das Sortieren von Proteinen in ihr jeweiliges Zielkompartiment sowie für die Mechanismen der post-translationalen Protein-Modifikation. Bislang lieferten Suchen nach solchen Motiven in Proteinsequenzen aufgrund ihrer geringen Länge und ihrer häufig unscharfen Notation eine Vielzahl an Treffern, von denen die überwiegende Mehrzahl ohne biologische Funktion sind. In der vorliegenden Arbeit wurde dieses Problem auf zwei verschiedene Arten angegangen: Zum Einen wurden verschiedene Sequenzfilter implementiert, evaluiert und optimiert mit dem Ziel, diejenigen Sequenzabschnitte zu maskieren, in denen wenige oder gar keine Interaktionsmotive zu finden sind. So wurden beispielsweise verschiedene Vorhersage-algorithmen implementiert, die globuläre Bereiche oder Transmembran-Helices erkennen. In diesen Regionen sollten keine funktionalen Interaktionsmotive zu finden sein und daher wurden diese Sequenzbereiche ausgefiltert. Besonderes Augenmerk wurde auf die methodische Weiterentwicklung und Verbesserung einzelner Filter gelegt und darüber hinaus wurden die Filter auch in verschiedenen Kombinationen getestet. Es konnte gezeigt werden, daß durch die Anwendung dieser Filter die Anzahl an falsch-positiven Treffern signifikant reduziert wird. Dies erleichtert die Planung von entsprechenden Experimenten und erlaubt die Konzentration auf Bereiche, in denen funktionale Motive angereichert sind. Zum Anderen wurde ein neuartiges Bewertungsschema entworfen um funktionale Motive zu identifizieren. Dieses Schema bewertet die Konserviertheit der Motive in homologen Sequenzen wobei explizit die Sequenzähnlichkeit zur Suchsequenz mit berücksichtigt wird. Eine besondere Eigenschaft dieses Bewertungsschemas ist, daß keine Unterteilung der homologen Sequenzen in Paraloge und Orthologe notwendig ist. Beide Ansätze, Bewertungsschema und Sequenzfilter, wurden in dieser Arbeit erstmals gemeinsam implementiert und ergänzen sich gegenseitig auf synergistische Art und Weise. Die Effizienz des gesamten Ansatzes wurde daran gemessen, wie gut es gelang, 576 experimentell bestätigte Motive in 415 Proteinsequenzen aus der Gesamtheit von 15563 Motiven zu identifizieren. Verglichen mit einer Zufallsauswahl bringt eine Kombination von Sequenzfiltern und dem neuartigen Bewertungsschema eine mehr als neunfach erhöhte Anreicherung von funktionalen Motiven auf dem ersten Rang. Des Weiteren müssen nur halb so viele Treffen analysiert werden, um 75% aller funktionalen Motive in diesem Datensatz abzudecken. Deshalb stellt dieser Ansatz eine wertvolle Hilfe dar um Experimente zu planen, denn er erlaubt eine Konzentration auf diejenigen linearen Motive welche die höchste Wahrscheinlichkeit besitzen, biologisch relevant zu sein. Weiterhin wurde diese Methode auch auf mehrere virale Proteine des humanen Immundefizienz-Virus und EBV angewandt. In jedem viralen Protein wurden Interaktionsmotive gemäß der beschriebenen Methode gesucht und bewertet. Anschließend wurde eine Literaturrecherche durchgeführt um zu sehen, welche der signifikanten Motive bereits als biologisch relevant beschrieben waren. Hier konnte gezeigt werden, daß mehrere entsprechende Motive bereits als funktional annotiert waren, was den Nutzen des Bewertungsschema unterstreicht und als Validierung der vorgestellten Strategie dient. Weitere Literatursuchen lieferten darüber hinaus Beispiele für beschriebene physiologische Proteinfunktionen, die durch die hier gefundenen Interaktionsmotive nun molekular erklärt werden können. Beide virale Beispiele unterstreichen den Nutzen dieser Methode für den Experimentator, denn sie reduziert die Anzahl an notwendigen Experimenten und ermöglicht es, sich auf biologisch relevante Interaktionsmotive zu konzentrieren.Many important protein:protein interactions are mediated by relatively small recognition domains (e.g. SH3, SH2, PDZ, WW) which bind to peptides exhibiting specific sequence motifs. In this type of interaction, one partner (the interaction domain) forms a globular three-dimensional structure, while the other one (the interaction motif) is mostly linear. These interactions are of crucial importance to signalling mechanisms such as receptor signalling, cell compartment targeting and post-translational modification. Up to now, searches for protein interaction motifs were hampered by the short length and fuzzy notation of these motifs, resulting in large amounts of false-positive motif instances without biological relevance. So the aim of this project was to improve the prediction of functional interaction motifs and the genome-wide identification of interaction motifs in viral proteins. In order to improve the search for functional interaction motifs in protein sequences, the work presented here employed two different strategies: Firstly, different sequence filters have been implemented, evaluated and optimized to mask those sequence regions containing little or no interaction motifs. For instance, different predictors of globularity, extracellular or transmembrane regions have been implemented which filter out regions which should be devoid of interaction motifs. Furthermore, single filters were improved and several filters were tested for a possible combined application. It could be shown that the joint employment of these filters minimizes the number of false positives and thus allows focussing on regions which are enriched in functional motifs. Secondly, a novel scoring scheme has been developed for the identification of functional motifs, which scores motif conservation in homologous sequences by taking explicitly into account the sequence similarity to a query sequence. A special feature of this scoring scheme is the fact that no a priori separation between paralogous and orthologous sequences is necessary. A synergistic effect could be demonstrated for both strategies, as the scoring scheme and the filtering approach mutually complement each other. Up to now, this unique combination of motif filtering and motif scoring has not yet been implemented elsewhere. The performance of the whole approach was verified by measuring its ability to identify 576 experimentally validated motifs among a total of 15563 instances in a set of 415 protein sequences. Compared to a random selection procedure, the joint application of sequence filters and the novel scoring scheme resulted in a nine fold enrichment of functional motifs on the first rank. In addition, only half as many hits need to be investigated to recover 75% of the functional instances in this dataset. Therefore, this motif detection approach should be helpful to guide experiments because it allows focussing on those interaction motifs which have a high probability to be functional. Finally this method has also been applied to various viral proteins from HIV and EBV. Each viral protein was searched for high-scoring motifs that have a high chance to be functional. As a validation of the strategy, the literature was searched, whether some of the highest-confidence hits were already experimentally confirmed interaction motifs. Further literature searches were conducted for the remaining high-scoring motifs, and several examples were found in which the motif-mediated interactions can explain the physiological data reported for the respective protein. Both viral examples demonstrated the usefulness of this approach for the experimentalist as it significantly reduces the amount of experiments to be conducted and helps focussing on biologically relevant interaction motifs. Consequently, this approach should be very helpful in annotating unknown proteins and in detecting novel protein:protein interactions mediated by interaction motifs

Intracellular Localization Map of Human Herpesvirus 8 Proteins▿

Human herpesvirus 8 (HHV-8) is the etiological agent of Kaposi's sarcoma. We present a localization map of 85 HHV-8-encoded proteins in mammalian cells. Viral open reading frames were cloned with a Myc tag in expression plasmids, confirmed by full-length sequencing, and expressed in HeLa cells. Protein localizations were analyzed by immunofluorescence microscopy. Fifty-one percent of all proteins were localized in the cytoplasm, 22% were in the nucleus, and 27% were found in both compartments. Surprisingly, we detected viral FLIP (v-FLIP) in the nucleus and in the cytoplasm, whereas cellular FLIPs are generally localized exclusively in the cytoplasm. This suggested that v-FLIP may exert additional or alternative functions compared to cellular FLIPs. In addition, it has been shown recently that the K10 protein can bind to at least 15 different HHV-8 proteins. We noticed that K10 and only five of its 15 putative binding factors were localized in the nucleus when the proteins were expressed in HeLa cells individually. Interestingly, in coexpression experiments K10 colocalized with 87% (13 of 15) of its putative binding partners. Colocalization was induced by translocation of either K10 alone or both proteins. These results indicate active intracellular translocation processes in virus-infected cells. Specifically in this framework, the localization map may provide a useful reference to further elucidate the function of HHV-8-encoded genes in human diseases

Soluble fms-Like Tyrosine Kinase-1-to-Placental Growth Factor Ratio and Time to Delivery in Women With Suspected Preeclampsia.

OBJECTIVE: To assess the association of a serum soluble fms-like tyrosine kinase 1-to-placental growth factor (sFlt-1-to-PlGF) ratio of greater than 38 with time to delivery and preterm birth. METHODS: Secondary analysis of an observational cohort study that included women 18 years of age or older from 24 to 36 6/7 weeks of gestation at their first study visit with suspected (not confirmed) preeclampsia. Participants were recruited from December 2010 to January 2014 at 30 sites in 14 countries. A total of 1,041 women were included in time-to-delivery analysis and 848 in preterm birth analysis. RESULTS: Women with an sFlt-1-to-PlGF ratio greater than 38 (n=250) had a 2.9-fold greater likelihood of imminent delivery (ie, delivery on the day of the test) (Cox regression hazard ratio 2.9; P<.001) and shorter remaining time to delivery (median 17 [interquartile range 10-26] compared with 51 [interquartile range 30-75] days, respectively; Weibull regression factor 0.62; P<.001) than women with an sFlt-1-to-PlGF ratio of 38 or less, whether or not they developed preeclampsia. For women who did not (n=842) and did develop preeclampsia (n=199), significant correlations were seen between an sFlt-1-to-PlGF ratio greater than 38 and preterm birth (r=0.44 and r=0.46; both P<.001). Among women who did not develop preeclampsia, those who underwent iatrogenic preterm delivery had higher median sFlt-1-to-PlGF ratios at their first visit (35.3, interquartile range 6.8-104.0) than those who did not (8.4, interquartile range 3.4-30.6) or who delivered at term (4.3, interquartile range 2.4-10.9). CONCLUSIONS: In women undergoing evaluation for suspected preeclampsia, a serum sFlt-1-to-PlGF ratio greater than 38 is associated with a shorter remaining pregnancy duration and a higher risk of preterm delivery