Entomopathogen ID: a curated sequence resource for entomopathogenic fungi

We report the development of a publicly accessible, curated nucleotide sequence database of hypocrealean entomopathogenic fungi. The goal is to provide a platform for users to easily access sequence data from taxonomic reference strains. The database can be used to accurately identify unknown entomopathogenic fungi based on sequence data for a variety of phylogenetically informative loci. The database provides full multi-locus sequence alignment capabilities. The initial release contains data compiled for 525 strains covering the phylogenetic diversity of three important entomopathogenic families: Clavicipitaceae, Cordycipitaceae, and Ophiocordycipitaceae. Furthermore, Entomopathogen ID can be expanded to other fungal clades of insect pathogens, as sequence data becomes available. The database will allow isolate characterisation and evolutionary analyses. We contend that this freely available, web-accessible database will facilitate the broader community to accurately identify fungal entomopathogens, which will allow users to communicate research results more effectively.     

From annotated genomes to metabolic flux models and kinetic parameter fitting

Significant advances in system-level modeling of cellular behavior can be achieved based on constraints derived from genomic information and on optimality hypotheses. For steady-state models of metabolic networks, mass conservation and reaction stoichiometry impose linear constraints on metabolic fluxes. Different objectives, such as maximization of growth rate or minimization of flux distance from a reference state, can be tested in different organisms and conditions. In particular, we have suggested that the metabolic properties of mutant bacterial strains are best described by an algorithm that performs a minimization of metabolic adjustment (MOMA) upon gene deletion. The increasing availability of many annotated genomes paves the way for a systematic application of these flux balance methods to a large variety of organisms. However, such a high throughput goal crucially depends on our capacity to build metabolic flux models in a fully automated fashion. Here we describe a pipeline for generating models from annotated genomes and discuss the current obstacles to full automation. In addition, we propose a framework for the integration of flux modeling results and high throughput proteomic data, which can potentially help in the inference of whole-cell kinetic parameters.     

The BioGRID database: A comprehensive biomedical resource of curated protein,genetic, and chemical interactions

The BioGRID (Biological General Repository for Interaction Datasets, thebiogrid.org ) is an open‐access database resource that houses manually curated protein and genetic interactions from multiple species including yeast, worm, fly, mouse, and human. The ~1.93 million curated interactions in BioGRID can be used to build complex networks to facilitate biomedical discoveries, particularly as related to human health and disease. All BioGRID content is curated from primary experimental evidence in the biomedical literature, and includes both focused low‐throughput studies and large high‐throughput datasets. BioGRID also captures protein post‐translational modifications and protein or gene interactions with bioactive small molecules including many known drugs. A built‐in network visualization tool combines all annotations and allows users to generate network graphs of protein, genetic and chemical interactions. In addition to general curation across species, BioGRID undertakes themed curation projects in specific aspects of cellular regulation, for example the ubiquitin‐proteasome system, as well as specific disease areas, such as for the SARS‐CoV‐2 virus that causes COVID‐19 severe acute respiratory syndrome. A recent extension of BioGRID, named the Open Repository of CRISPR Screens (ORCS, orcs.thebiogrid.org ), captures single mutant phenotypes and genetic interactions from published high throughput genome‐wide CRISPR/Cas9‐based genetic screens. BioGRID‐ORCS contains datasets for over 1,042 CRISPR screens carried out to date in human, mouse and fly cell lines. The biomedical research community can freely access all BioGRID data through the web interface, standardized file downloads, or via model organism databases and partner meta‐databases.     

The Yeast Protein Database (YPD): a curated proteome database for Saccharomyces cerevisiae.

The Yeast Protein Database (YPD) is a curated database for the proteome of Saccharomyces cerevisiae . It consists of approximately 6000 Yeast Protein Reports, one for each of the known or predicted yeast proteins. Each Yeast Protein Report is a one-page presentation of protein properties, annotation lines that summarize findings from the literature, and references. In the past year, the number of annotation lines has grown from 25 000 to approximately 35 000, and the number of articles curated has grown from approximately 3500 to >5000. Recently, new data types have been included in YPD: protein-protein interactions, genetic interactions, and regulators of gene expression. Finally, a new layer of information, the YPD Protein Minireviews, has recently been introduced. The Yeast Protein Database can be found on the Web at http://www.proteome.com/YPDhome. html     

Mathematical tools for molecular genetics data: An annotated bibliography

An annotated bibliography of mathematical and computer analyses of protein and nucleic acid sequences is presented. The major subject areas represented are the determination of sequences, restriction mapping, similarity searching, sequence alignment, codon utilization, statistical analysis, information theoretic analysis, the construction of secondary and tertiary structure and DNA topology.     

Reaction sequences for (Na+ + K+)-dependent ATPase hydrolytic activities: new quantitative kinetic models

To delineate better the reaction sequence of the (Na+ + K+)-ATPase and illuminate properties of the active site, kinetic data were fitted to specific quantitative models. For the (Na+ + K+)-ATPase reaction, double-reciprocal plots of velocity against ATP (in the millimolar range), with a series of fixed KCl concentrations, are nearly parallel, in accord with the ping pong kinetics of ATP binding at the low-affinity sites only after Pi release. However, contrary to requirements of usual formulations, Pi is not a competitor toward ATP. A new steady-state kinetic model accommodates these data quantitatively, requiring that under usual assay conditions most of the enzyme activity follows a sequence in which ATP adds after Pi release, but also requiring a minor alternative pathway with ATP adding after K+ binds but before Pi release. The fit to the data also reveals that Pi binds nearly as rapidly to E2 X K X ATP as to E2 X K, whereas ATP binds quite slowly to E2 X P X K: the site resembles a cul-de-sac with distal ATP and proximal Pi sites. For the K+-nitrophenyl phosphatase reaction also catalyzed by this enzyme, the apparent affinities for both substrate and Pi (as inhibitor) decrease with higher KCl concentrations, and both Pi and TNP-ATP appear to be competitive inhibitors toward substrate with 10 mM KCl but noncompetitive inhibitors with 1 mM KCl. These data are accommodated quantitatively by a steady-state model allowing cyclic hydrolytic activity without obligatory release of K+, and with exclusive binding of substrate vs. either Pi or TNP-ATP. The greater sensitivity of the phosphatase reaction to both Pi and arsenate is attributable to the weaker binding by the occluded-K+ enzyme form occurring in the (Na+ + K+)-ATPase reaction sequence. The steady-state models are consistent with cyclical interconversion of high- and low-affinity substrate sites accompanying E1/E2 transitions, with distortion to low-affinity sites altering not only affinity and route of access but also separating the adenine- and phosphate-binding regions, the latter serving in the E2 conformation as the active site for the phosphatase reaction.     

PFR2: a curated database of planktonic foraminifera 18S ribosomal DNA as a resource for studies of plankton ecology,biogeography and evolution

Planktonic foraminifera (Rhizaria) are ubiquitous marine pelagic protists producing calcareous shells with conspicuous morphology. They play an important role in the marine carbon cycle, and their exceptional fossil record serves as the basis for biochronostratigraphy and past climate reconstructions. A major worldwide sampling effort over the last two decades has resulted in the establishment of multiple large collections of cryopreserved individual planktonic foraminifera samples. Thousands of 18S rDNA partial sequences have been generated, representing all major known morphological taxa across their worldwide oceanic range. This comprehensive data coverage provides an opportunity to assess patterns of molecular ecology and evolution in a holistic way for an entire group of planktonic protists. We combined all available published and unpublished genetic data to build PFR², the Planktonic foraminifera Ribosomal Reference database. The first version of the database includes 3322 reference 18S rDNA sequences belonging to 32 of the 47 known morphospecies of extant planktonic foraminifera, collected from 460 oceanic stations. All sequences have been rigorously taxonomically curated using a six‐rank annotation system fully resolved to the morphological species level and linked to a series of metadata. The PFR² website, available at http://pfr2.sb-roscoff.fr , allows downloading the entire database or specific sections, as well as the identification of new planktonic foraminiferal sequences. Its novel, fully documented curation process integrates advances in morphological and molecular taxonomy. It allows for an increase in its taxonomic resolution and assures that integrity is maintained by including a complete contingency tracking of annotations and assuring that the annotations remain internally consistent.     

The Histone Database: a comprehensive resource for histones and histone fold-containing proteins

The Histone Database is a curated and searchable collection of full-length sequences and structures of histones and nonhistone proteins containing histone-like folds, compiled from major public databases. Several new histone fold-containing proteins have been identified, including the huntingtin-interacting protein HYPM. Additionally, based on the recent crystal structure of the Son of Sevenless protein, an interpretation of the sequence analysis of the histone fold domain is presented. The database contains an updated collection of multiple sequence alignments for the four core histones (H2A, H2B, H3, and H4) and the linker histones (H1/H5) from a total of 975 organisms. The database also contains information on the human histone gene complement and provides links to three-dimensional structures of histone and histone fold-containing proteins. The Histone Database is a comprehensive bioinformatics resource for the study of structure and function of histones and histone fold-containing proteins. The database is available at http://research.nhgri.nih.gov/histones/.     

Web-based applications for building, managing and analysing kinetic models of biological systems

Mathematical modelling and computational analysis play an essentialrole in improving our capability to elucidate the functionsand characteristics of complex biological systems such as metabolic,regulatory and cell signalling pathways. The modelling and concomitantsimulation render it possible to predict the cellular behaviourof systems under various genetically and/or environmentallyperturbed conditions. This motivates systems biologists/bioengineers/bioinformaticiansto develop new tools and applications, allowing non-expertsto easily conduct such modelling and analysis. However, amonga multitude of systems biology tools developed to date, onlya handful of projects have adopted a web-based approach to kineticmodelling. In this report, we evaluate the capabilities andcharacteristics of current web-based tools in systems biologyand identify desirable features, limitations and bottlenecksfor further improvements in terms of usability and functionality.A short discussion on software architecture issues involvedin web-based applications and the approaches taken by existingtools is included for those interested in developing their ownsimulation applications.      

The Hawaiian Algal Database: a laboratory LIMS and online resource for biodiversity data

Background  

Organization and presentation of biodiversity data is greatly facilitated by databases that are specially designed to allow easy data entry and organized data display. Such databases also have the capacity to serve as Laboratory Information Management Systems (LIMS). The Hawaiian Algal Database was designed to showcase specimens collected from the Hawaiian Archipelago, enabling users around the world to compare their specimens with our photographs and DNA sequence data, and to provide lab personnel with an organizational tool for storing various biodiversity data types.     

AntiJen: a quantitative immunology database integrating functional, thermodynamic, kinetic, biophysical, and cellular data

AntiJen is a database system focused on the integration of kinetic, thermodynamic, functional, and cellular data within the context of immunology and vaccinology. Compared to its progenitor JenPep, the interface has been completely rewritten and redesigned and now offers a wider variety of search methods, including a nucleotide and a peptide BLAST search. In terms of data archived, AntiJen has a richer and more complete breadth, depth, and scope, and this has seen the database increase to over 31,000 entries. AntiJen provides the most complete and up-to-date dataset of its kind. While AntiJen v2.0 retains a focus on both T cell and B cell epitopes, its greatest novelty is the archiving of continuous quantitative data on a variety of immunological molecular interactions. This includes thermodynamic and kinetic measures of peptide binding to TAP and the Major Histocompatibility Complex (MHC), peptide-MHC complexes binding to T cell receptors, antibodies binding to protein antigens and general immunological protein-protein interactions. The database also contains quantitative specificity data from position-specific peptide libraries and biophysical data, in the form of diffusion co-efficients and cell surface copy numbers, on MHCs and other immunological molecules. The uses of AntiJen include the design of vaccines and diagnostics, such as tetramers, and other laboratory reagents, as well as helping parameterize the bioinformatic or mathematical in silico modeling of the immune system. The database is accessible from the URL: http://www.jenner.ac.uk/antijen.     

EffectorK,a comprehensive resource to mine for Ralstonia,Xanthomonas, and other published effector interactors in the Arabidopsis proteome

Pathogens deploy effector proteins that interact with host proteins to manipulate the host physiology to the pathogen's own benefit. However, effectors can also be recognized by host immune proteins, leading to the activation of defence responses. Effectors are thus essential components in determining the outcome of plant–pathogen interactions. Despite major efforts to decipher effector functions, our current knowledge on effector biology is scattered and often limited. In this study, we conducted two systematic large-scale yeast two-hybrid screenings to detect interactions between Arabidopsis thaliana proteins and effectors from two vascular bacterial pathogens: Ralstonia pseudosolanacearum and Xanthomonas campestris. We then constructed an interactomic network focused on Arabidopsis and effector proteins from a wide variety of bacterial, oomycete, fungal, and invertebrate pathogens. This network contains our experimental data and protein–protein interactions from 2,035 peer-reviewed publications (48,200 Arabidopsis–Arabidopsis and 1,300 Arabidopsis–effector protein interactions). Our results show that effectors from different species interact with both common and specific Arabidopsis interactors, suggesting dual roles as modulators of generic and adaptive host processes. Network analyses revealed that effector interactors, particularly “effector hubs” and bacterial core effector interactors, occupy important positions for network organization, as shown by their larger number of protein interactions and centrality. These interactomic data were incorporated in EffectorK, a new graph-oriented knowledge database that allows users to navigate the network, search for homology, or find possible paths between host and/or effector proteins. EffectorK is available at www.effectork.org and allows users to submit their own interactomic data.     

MIRACH: efficient model checker for quantitative biological pathway models

Model checking is playing an increasingly important role in systems biology as larger and more complex biological pathways are being modeled. In this article we report the release of an efficient model checker MIRACH 1.0, which supports any model written in popular formats such as CSML and SBML. MIRACH is integrated with a Petri-net-based simulation engine, enabling efficient online (on-the-fly) checking. In our experiment, by using Levchenko et al. model, we reveal that timesaving gains by using MIRACH easily surpass 400% compared with its offline-based counterpart. AVAILABILITY AND IMPLEMENTATION: MIRACH 1.0 was developed using Java and thus executable on any platform installed with JDK 6.0 (not JRE 6.0) or later. MIRACH 1.0, along with its source codes, documentation and examples are available at http://sourceforge.net/projects/mirach/ under the LGPLv3 license.