AcetoBase: a functional gene repository and database for formyltetrahydrofolate synthetase sequences

Acetogenic bacteria are imperative to environmental carbon cycling and diverse biotechnological applications, but their extensive physiological and taxonomical diversity is an impediment to systematic taxonomic studies. Acetogens are chemolithoautotrophic bacteria that perform reductive carbon fixation under anaerobic conditions through the Wood–Ljungdahl pathway (WLP)/acetyl-coenzyme A pathway. The gene-encoding formyltetrahydrofolate synthetase (FTHFS), a key enzyme of this pathway, is highly conserved and can be used as a molecular marker to probe acetogenic communities. However, there is a lack of systematic collection of FTHFS sequence data at nucleotide and protein levels. In an attempt to streamline investigations on acetogens, we developed AcetoBase - a repository and database for systematically collecting and organizing information related to FTHFS sequences. AcetoBase also provides an opportunity to submit data and obtain accession numbers, perform homology searches for sequence identification and access a customized blast database of submitted sequences. AcetoBase provides the prospect to identify potential acetogenic bacteria, based on metadata information related to genome content and the WLP, supplemented with FTHFS sequence accessions, and can be an important tool in the study of acetogenic communities. AcetoBase can be publicly accessed at https://acetobase.molbio.slu.se

Biopython Project Update 2017

The Biopython Project is a long-running distributed collaborative effort, supported by the Open Bioinformatics Foundation, which develops a freely available Python library for biological computation [1]. We present here details of the Biopython releases since BOSC 2016, namely Biopython 1.68, 1.69 and 1.70. Together these had 82 named contributors including 51 newcomers which reflects our policy of trying to encourage even small contributions.Biopython 1.68 (August 2016) was a relatively small release, with the main new feature being support for RSSB’s new binary Macromolecular Transmission Format (MMTF) for structural data.Biopython 1.69 (April 2017) represents the start of our re-licensing plan, to transition away from our liberal but unique Biopython License Agreement to the similar but very widely used 3-Clause BSD License. We are reviewing the code base authorship file-by-file, in order to gradually dual license the entire project. Major new features include: a new parser for the ExPASy Cellosaurus cell line database, catalogue and ontology; support for the UCSC Multiple Alignment Format (MAF), FSA sequencing files, version 4 of the Affymetrix CEL format; updates to the REBASE February 2017 restriction enzyme list; Bio.PDB.PDBList now can download more formats including MMTF; enhanced PyPy support by taking advantage of NumPy and compiling most of the Biopython C code modules.Biopython 1.70 (July 2017) has internal changes to better support the now standard pip tool for Python package installation. Major new features include: support for Mauve’s eXtended Multi-FastA (XMFA) file format, updates to our BLAST XML and MEME parsers, ExPASy support, and phylogenetic distance matrices. This release is noteworthy for our new logo, contributed by Patrick Kunzmann. This draws on our original double helix logo, and the blue and yellow colors of the current Python logo.All releases fixed miscellaneous bugs, enhanced the test suite, and continued efforts to follow the PEP8 and PEP257 coding style guidelines which is now checked automatically with GitHub-integrated continuous integration testing using TravisCI. We now also use AppVeyor for continuous integration testing under Windows. Current efforts include improving the unit test coverage, which is easily viewed online at CodeCov.io

BIOINFORMATICSAPPLICATIONSNOTE GenomeDiagram: A Python Package for the Visualisation of Large-Scale Genomic Data

Summary: We present GenomeDiagram, a flexible, open-source Python module for the visualisation of large-scale genomic, comparative genomic and other data with reference to a single chromosome or other biological sequence. GenomeDiagram may be used to generate publication-quality vector graphics, rastered images, and in-line streamed graphics for webpages. The package integrates with datatypes from the BioPython project, and is available for Windows, Linux and Mac OS X systems. Availability: GenomeDiagram is freely available as source cod