Origins and Evolution of the HET-s Prion-Forming Protein: Searching for Other Amyloid-Forming Solenoids

The HET-s prion-forming domain from the filamentous fungus Podospora anserina is gaining considerable interest since it yielded the first well-defined atomic structure of a functional amyloid fibril. This structure has been identified as a left-handed beta solenoid with a triangular hydrophobic core. To delineate the origins of the HET-s prion-forming protein and to discover other amyloid-forming proteins, we searched for all homologs of the HET-s protein in a database of protein domains and fungal genomes, using a combined application of HMM, psi-blast and pGenThreader techniques, and performed a comparative evolutionary analysis of the N-terminal alpha-helical domain and the C-terminal prion-forming domain of HET-s. By assessing the tandem evolution of both domains, we observed that the prion-forming domain is restricted to Sordariomycetes, with a marginal additional sequence homolog in Arthroderma otae as a likely case of horizontal transfer. This suggests innovation and rapid evolution of the solenoid fold in the Sordariomycetes clade. In contrast, the N-terminal domain evolves at a slower rate (in Sordariomycetes) and spans many diverse clades of fungi. We performed a full three-dimensional protein threading analysis on all identified HET-s homologs against the HET-s solenoid fold, and present detailed structural annotations for identified structural homologs to the prion-forming domain. An analysis of the physicochemical characteristics in our set of structural models indicates that the HET-s solenoid shape can be readily adopted in these homologs, but that they are all less optimized for fibril formation than the P. anserina HET-s sequence itself, due chiefly to the presence of fewer asparagine ladders and salt bridges. Our combined structural and evolutionary analysis suggests that the HET-s shape has “limited scope” for amyloidosis across the wider protein universe, compared to the ‘generic’ left-handed beta helix. We discuss the implications of our findings on future identification of amyloid-forming proteins sharing the solenoid fold

GeneViTo: Visualizing gene-product functional and structural features in genomic datasets

BACKGROUND: The availability of increasing amounts of sequence data from completely sequenced genomes boosts the development of new computational methods for automated genome annotation and comparative genomics. Therefore, there is a need for tools that facilitate the visualization of raw data and results produced by bioinformatics analysis, providing new means for interactive genome exploration. Visual inspection can be used as a basis to assess the quality of various analysis algorithms and to aid in-depth genomic studies. RESULTS: GeneViTo is a JAVA-based computer application that serves as a workbench for genome-wide analysis through visual interaction. The application deals with various experimental information concerning both DNA and protein sequences (derived from public sequence databases or proprietary data sources) and meta-data obtained by various prediction algorithms, classification schemes or user-defined features. Interaction with a Graphical User Interface (GUI) allows easy extraction of genomic and proteomic data referring to the sequence itself, sequence features, or general structural and functional features. Emphasis is laid on the potential comparison between annotation and prediction data in order to offer a supplement to the provided information, especially in cases of "poor" annotation, or an evaluation of available predictions. Moreover, desired information can be output in high quality JPEG image files for further elaboration and scientific use. A compilation of properly formatted GeneViTo input data for demonstration is available to interested readers for two completely sequenced prokaryotes, Chlamydia trachomatis and Methanococcus jannaschii. CONCLUSIONS: GeneViTo offers an inspectional view of genomic functional elements, concerning data stemming both from database annotation and analysis tools for an overall analysis of existing genomes. The application is compatible with Linux or Windows ME-2000-XP operating systems, provided that the appropriate Java Runtime Environment is already installed in the system

iLIR : a web resource for prediction of Atg8-family interacting proteins

Macroautophagy was initially considered to be a nonselective process for bulk breakdown of cytosolic material. However, recent evidence points toward a selective mode of autophagy mediated by the so-called selective autophagy receptors (SARs). SARs act by recognizing and sorting diverse cargo substrates (e.g., proteins, organelles, pathogens) to the autophagic machinery. Known SARs are characterized by a short linear sequence motif (LIR-, LRS-, or AIM-motif) responsible for the interaction between SARs and proteins of the Atg8 family. Interestingly, many LIR-containing proteins (LIRCPs) are also involved in autophagosome formation and maturation and a few of them in regulating signaling pathways. Despite recent research efforts to experimentally identify LIRCPs, only a few dozen of this class of—often unrelated—proteins have been characterized so far using tedious cell biological, biochemical, and crystallographic approaches. The availability of an ever-increasing number of complete eukaryotic genomes provides a grand challenge for characterizing novel LIRCPs throughout the eukaryotes. Along these lines, we developed iLIR, a freely available web resource, which provides in silico tools for assisting the identification of novel LIRCPs. Given an amino acid sequence as input, iLIR searches for instances of short sequences compliant with a refined sensitive regular expression pattern of the extended LIR motif (xLIR-motif) and retrieves characterized protein domains from the SMART database for the query. Additionally, iLIR scores xLIRs against a custom position-specific scoring matrix (PSSM) and identifies potentially disordered subsequences with protein interaction potential overlapping with detected xLIR-motifs. Here we demonstrate that proteins satisfying these criteria make good LIRCP candidates for further experimental verification. Domain architecture is displayed in an informative graphic, and detailed results are also available in tabular form. We anticipate that iLIR will assist with elucidating the full complement of LIRCPs in eukaryotes

VeSTIS: A Versatile Semi- Automatic Taxon Identification System from Digital Images

In this work we present a flexible Open Source software platform for training classifiers capable of identifying the taxonomy of a specimen from digital images. We demonstrate the performance of our system in a pilot study, building a feed-forward artificial neural network to effectively classify five different species of marine annelid worms of the class Polychaeta. We also discuss on the extensibility of the system, and its potential uses either as a research tool or in assisting routine taxon identification procedures

Establishment of computational biology in Greece and Cyprus: Past, present, and future.

We review the establishment of computational biology in Greece and Cyprus from its inception to date and issue recommendations for future development. We compare output to other countries of similar geography, economy, and size—based on publication counts recorded in the literature—and predict future growth based on those counts as well as national priority areas. Our analysis may be pertinent to wider national or regional communities with challenges and opportunities emerging from the rapid expansion of the field and related industries. Our recommendations suggest a 2-fold growth margin for the 2 countries, as a realistic expectation for further expansion of the field and the development of a credible roadmap of national priorities, both in terms of research and infrastructure funding

An intrinsically disordered proteins community for ELIXIR.

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are now recognised as major determinants in cellular regulation. This white paper presents a roadmap for future e-infrastructure developments in the field of IDP research within the ELIXIR framework. The goal of these developments is to drive the creation of high-quality tools and resources to support the identification, analysis and functional characterisation of IDPs. The roadmap is the result of a workshop titled "An intrinsically disordered protein user community proposal for ELIXIR" held at the University of Padua. The workshop, and further consultation with the members of the wider IDP community, identified the key priority areas for the roadmap including the development of standards for data annotation, storage and dissemination; integration of IDP data into the ELIXIR Core Data Resources; and the creation of benchmarking criteria for IDP-related software. Here, we discuss these areas of priority, how they can be implemented in cooperation with the ELIXIR platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for an IDP Community in ELIXIR and is an appeal to identify and involve new stakeholders

Contemporary Challenges and Solutions

CA18131 CP16/00163 NIS-3317 NIS-3318 decision 295741 C18/BM/12585940The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 “ML4Microbiome” that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.publishersversionpublishe

Membrane Topology and Predicted RNA-Binding Function of the ‘Early Responsive to Dehydration (ERD4)’ Plant Protein

Functional annotation of uncharacterized genes is the main focus of computational methods in the post genomic era. These tools search for similarity between proteins on the premise that those sharing sequence or structural motifs usually perform related functions, and are thus particularly useful for membrane proteins. Early responsive to dehydration (ERD) genes are rapidly induced in response to dehydration stress in a variety of plant species. In the present work we characterized function of Brassica juncea ERD4 gene using computational approaches. The ERD4 protein of unknown function possesses ubiquitous DUF221 domain (residues 312–634) and is conserved in all plant species. We suggest that the protein is localized in chloroplast membrane with at least nine transmembrane helices. We detected a globular domain of 165 amino acid residues (183–347) in plant ERD4 proteins and expect this to be posited inside the chloroplast. The structural-functional annotation of the globular domain was arrived at using fold recognition methods, which suggested in its sequence presence of two tandem RNA-recognition motif (RRM) domains each folded into βαββαβ topology. The structure based sequence alignment with the known RNA-binding proteins revealed conservation of two non-canonical ribonucleoprotein sub-motifs in both the putative RNA-recognition domains of the ERD4 protein. The function of highly conserved ERD4 protein may thus be associated with its RNA-binding ability during the stress response. This is the first functional annotation of ERD4 family of proteins that can be useful in designing experiments to unravel crucial aspects of stress tolerance mechanism

The Interaction Properties of the Human Rab GTPase Family – A Comparative Analysis Reveals Determinants of Molecular Binding Selectivity

Rab GTPases constitute the largest subfamily of the Ras protein superfamily. Rab proteins regulate organelle biogenesis and transport, and display distinct binding preferences for effector and activator proteins, many of which have not been elucidated yet. The underlying molecular recognition motifs, binding partner preferences and selectivities are not well understood.Comparative analysis of the amino acid sequences and the three-dimensional electrostatic and hydrophobic molecular interaction fields of 62 human Rab proteins revealed a wide range of binding properties with large differences between some Rab proteins. This analysis assists the functional annotation of Rab proteins 12, 14, 26, 37 and 41 and provided an explanation for the shared function of Rab3 and 27. Rab7a and 7b have very different electrostatic potentials, indicating that they may bind to different effector proteins and thus, exert different functions. The subfamily V Rab GTPases which are associated with endosome differ subtly in the interaction properties of their switch regions, and this may explain exchange factor specificity and exchange kinetics.We have analysed conservation of sequence and of molecular interaction fields to cluster and annotate the human Rab proteins. The analysis of three dimensional molecular interaction fields provides detailed insight that is not available from a sequence-based approach alone. Based on our results, we predict novel functions for some Rab proteins and provide insights into their divergent functions and the determinants of their binding partner selectivity

DisProt: intrinsic protein disorder annotation in 2020

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome