Bacillus thuringiensis ssp. galleriae simultaneously produces two δ-endotoxins differing strongly in primary structure and entomocidal activity

AbstractStrain 11–67 of B. thuringiensis ssp. galleriae produces two entomocidal proteins of molecular mass 130 kDa. Limited proteolysis of these proteins — protoxins — yields the ‘true’ toxins of molecular mass 65 kDa which are drastically different with respect to their charges at pH 8.6, immunological properties and toxicity (host range). One of the proteins — the ‘negative’ component — is toxic for Lymantria dispar larvae and shows 65% homology when compared with B. thuringiensis ssp. kurstaki δ-endotoxins. The other — the ‘positive’ component — is toxic for Galleria mellonella larvae. Its N-terminal sequence of 11 amino acid residues is homologous with the B. thuringiensis ssp. israelensis and san diego endotoxins known to be toxic for Coleoptera and Diptera but not for Lepidoptera. Hence, B. thuringiensis subspecies may produce simultaneously δ-endotoxins differing substantially in structural features and host range

MinION Analysis and Reference Consortium: Phase 1 data release and analysis

The advent of a miniaturized DNA sequencing device with a high-throughput contextual sequencing capability embodies the next generation of large scale sequencing tools. The MinION™ Access Programme (MAP) was initiated by Oxford Nanopore Technologies™ in April 2014, giving public access to their USB-attached miniature sequencing device. The MinION Analysis and Reference Consortium (MARC) was formed by a subset of MAP participants, with the aim of evaluating and providing standard protocols and reference data to the community. Envisaged as a multi-phased project, this study provides the global community with the Phase 1 data from MARC, where the reproducibility of the performance of the MinION was evaluated at multiple sites. Five laboratories on two continents generated data using a control strain of Escherichia coli K-12, preparing and sequencing samples according to a revised ONT protocol. Here, we provide the details of the protocol used, along with a preliminary analysis of the characteristics of typical runs including the consistency, rate, volume and quality of data produced. Further analysis of the Phase 1 data presented here, and additional experiments in Phase 2 of E. coli from MARC are already underway to identify ways to improve and enhance MinION performance

Petabyte-scale innovations at the European Nucleotide Archive

Dramatic increases in the throughput of nucleotide sequencing machines, and the promise of ever greater performance, have thrust bioinformatics into the era of petabyte-scale data sets. Sequence repositories, which provide the feed for these data sets into the worldwide computational infrastructure, are challenged by the impact of these data volumes. The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/embl), comprising the EMBL Nucleotide Sequence Database and the Ensembl Trace Archive, has identified challenges in the storage, movement, analysis, interpretation and visualization of petabyte-scale data sets. We present here our new repository for next generation sequence data, a brief summary of contents of the ENA and provide details of major developments to submission pipelines, high-throughput rule-based validation infrastructure and data integration approaches

The European Nucleotide Archive

The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) is Europe’s primary nucleotide-sequence repository. The ENA consists of three main databases: the Sequence Read Archive (SRA), the Trace Archive and EMBL-Bank. The objective of ENA is to support and promote the use of nucleotide sequencing as an experimental research platform by providing data submission, archive, search and download services. In this article, we outline these services and describe major changes and improvements introduced during 2010. These include extended EMBL-Bank and SRA-data submission services, extended ENA Browser functionality, support for submitting data to the European Genome-phenome Archive (EGA) through SRA, and the launch of a new sequence similarity search service

Specificity determinants for Cry insecticidal proteins: insights from their mode of action

Insecticidal proteins from the bacterium Bacillus thuringiensis (Bt) are used as active components of biopesticides and as plant incorporated protectants in transgenic crops. One of the most relevant attributes of these Bt protein-based insecticidal technologies is their high specificity, which assures lack of detrimental effects on non-target insects, vertebrates and the environment. The identification of specificity determinants in Bt insecticidal proteins could guide risk assessment for novel insecticidal proteins currently considered for commercialization. In this work we review the available data on specificity determinants of crystal (Cry) insecticidal proteins as the Bt toxins most well characterized and used in transgenic crops. The multi step mode of action of the Cry insecticidal proteins allows various factors to potentially affect specificity determination and here we define seven levels that could influence specificity. The relative relevance of each of these determinants on efficacy of transgenic crops producing Cry insecticidal proteins is also discussed

Major submissions tool developments at the European nucleotide archive

The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena), Europe's primary nucleotide sequence resource, captures and presents globally comprehensive nucleic acid sequence and associated information. Covering the spectrum from raw data to assembled and functionally annotated genomes, the ENA has witnessed a dramatic growth resulting from advances in sequencing technology and ever broadening application of the methodology. During 2011, we have continued to operate and extend the broad range of ENA services. In particular, we have released major new functionality in our interactive web submission system, Webin, through developments in template-based submissions for annotated sequences and support for raw next-generation sequence read submissions

Improvements to services at the European Nucleotide Archive

The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) is Europe’s primary nucleotide sequence archival resource, safeguarding open nucleotide data access, engaging in worldwide collaborative data exchange and integrating with the scientific publication process. ENA has made significant contributions to the collaborative nucleotide archival arena as an active proponent of extending the traditional collaboration to cover capillary and next-generation sequencing information. We have continued to co-develop data and metadata representation formats with our collaborators for both data exchange and public data dissemination. In addition to the DDBJ/EMBL/GenBank feature table format, we share metadata formats for capillary and next-generation sequencing traces and are using and contributing to the NCBI SRA Toolkit for the long-term storage of the next-generation sequence traces. During the course of 2009, ENA has significantly improved sequence submission, search and access functionalities provided at EMBL–EBI. In this article, we briefly describe the content and scope of our archive and introduce major improvements to our services

NCBI’s virus discovery codeathon: building “FIVE” —the Federated Index of Viral Experiments API index

Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus–host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE

NCBI's Virus Discovery Hackathon:Engaging Research Communities to Identify Cloud Infrastructure Requirements

A wealth of viral data sits untapped in publicly available metagenomic data sets when it might be extracted to create a usable index for the virological research community. We hypothesized that work of this complexity and scale could be done in a hackathon setting. Ten teams comprised of over 40 participants from six countries, assembled to create a crowd-sourced set of analysis and processing pipelines for a complex biological data set in a three-day event on the San Diego State University campus starting 9 January 2019. Prior to the hackathon, 141,676 metagenomic data sets from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) were pre-assembled into contiguous assemblies (contigs) by NCBI staff. During the hackathon, a subset consisting of 2953 SRA data sets (approximately 55 million contigs) was selected, which were further filtered for a minimal length of 1 kb. This resulted in 4.2 million (Mio) contigs, which were aligned using BLAST against all known virus genomes, phylogenetically clustered and assigned metadata. Out of the 4.2 Mio contigs, 360,000 contigs were labeled with domains and an additional subset containing 4400 contigs was screened for virus or virus-like genes. The work yielded valuable insights into both SRA data and the cloud infrastructure required to support such efforts, revealing analysis bottlenecks and possible workarounds thereof. Mainly: (i) Conservative assemblies of SRA data improves initial analysis steps; (ii) existing bioinformatic software with weak multithreading/multicore support can be elevated by wrapper scripts to use all cores within a computing node; (iii) redesigning existing bioinformatic algorithms for a cloud infrastructure to facilitate its use for a wider audience; and (iv) a cloud infrastructure allows a diverse group of researchers to collaborate effectively. The scientific findings will be extended during a follow-up event. Here, we present the applied workflows, initial results, and lessons learned from the hackathon