The ARB (from Latin arbor, tree) project was initiated almost 10 years ago. The ARB program package comprises a variety of directly interacting software tools for sequence database maintenance and analysis which are controlled by a common graphical user interface. Although it was initially designed for ribosomal RNA data, it can be used for any nucleic and amino acid sequence data as well. A central database contains processed (aligned) primary structure data. Any additional descriptive data can be stored in database fields assigned to the individual sequences or linked via local or worldwide networks. A phylogenetic tree visualized in the main window can be used for data access and visualization. The package comprises additional tools for data import and export, sequence alignment, primary and secondary structure editing, profile and filter calculation, phylogenetic analyses, specific hybridization probe design and evaluation and other components for data analysis. Currently, the package is used by numerous working groups worldwide.

BackgroundA major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.ResultsWe conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.ConclusionsThe top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1037-6) contains supplementary material, which is available to authorized users.

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org.

A green phototrophic bacterium was enriched with ferrous iron as sole electron donor and was isolated in defined coculture with a spirilloid chemoheterotrophic bacterium. The coculture oxidized ferrous iron to ferric iron with stoichiometric formation of cell mass from carbon dioxide. Sulfide, thiosulfate, or elemental sulfur was not used as electron donor in the light. Hydrogen or acetate in the presence of ferrous iron increased the cell yield of the phototrophic partner, and hydrogen could also be used as sole electron source. Complexed ferric iron was slowly reduced to ferrous iron in the dark, with hydrogen as electron source. Similar to Chlorobium limicola, the phototrophic bacterium contained bacteriochlorophyll c and chlorobactene as photosynthetic pigments, and also resembled representatives of this species morphologically. On the basis of 16S rRNA sequence comparisons, this organism clusters with Chlorobium, Prosthecochloris, and Pelodictyon species within the green sulfur bacteria phylum. Since the phototrophic partner in the coculture KoFox is only moderately related to the other members of the cluster, it is proposed as a new species, Chlorobium ferrooxidans. The chemoheterotrophic partner bacterium, strain KoFum, was isolated in pure culture with fumarate as sole substrate. The strain was identified as a member of the epsilon-subclass of the Proteobacteria closely related to "Geospirillum arsenophilum" on the basis of physiological properties and 16S rRNA sequence comparison. The "Geospirillum" strain was present in the coculture only in low numbers. It fermented fumarate, aspartate, malate, or pyruvate to acetate, succinate, and carbon dioxide, and could reduce nitrate to dinitrogen gas. It was not involved in ferrous iron oxidation but possibly provided a thus far unidentified growth factor to the phototrophic partner.

Tubulins are still considered as typical proteins of Eukaryotes. However, more recently they have been found in the unusual bacteria Prosthecobacter (btubAB). In this study, the genomic organization of the btub-genes and their genomic environment were characterized by using the newly developed Two-Step Gene Walking method. In all investigated Prosthecobacters, btubAB are organized in a typical bacterial operon. Strikingly, all btub-operons comprise a third gene with similarities to kinesin light chain sequences. The genomic environments of the characterized btub-operons are always different. This supports the hypothesis that this group of genes represents an independent functional unit, which was acquired by Prosthecobacter via horizontal gene transfer. The newly developed Two-Step Gene Walking method is based on randomly primed polymerase chain reaction (PCR). It presents a simple workflow, which comprises only two major steps—a Walking-PCR with a single specific outward pointing primer (step 1) and the direct sequencing of its product using a nested specific primer (step 2). Two-Step Gene Walking proved to be highly efficient and was successfully used to characterize over 20 kb of sequence not only in pure culture but even in complex non-pure culture samples.