@article{SharanFoerstnerEulalioetal.2017, author = {Sharan, Malvika and F{\"o}rstner, Konrad U. and Eulalio, Ana and Vogel, J{\"o}rg}, title = {APRICOT: an integrated computational pipeline for the sequence-based identification and characterization of RNA-binding proteins}, series = {Nucleic Acids Research}, volume = {45}, journal = {Nucleic Acids Research}, number = {11}, doi = {10.1093/nar/gkx137}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157963}, pages = {e96}, year = {2017}, abstract = {RNA-binding proteins (RBPs) have been established as core components of several post-transcriptional gene regulation mechanisms. Experimental techniques such as cross-linking and co-immunoprecipitation have enabled the identification of RBPs, RNA-binding domains (RBDs) and their regulatory roles in the eukaryotic species such as human and yeast in large-scale. In contrast, our knowledge of the number and potential diversity of RBPs in bacteria is poorer due to the technical challenges associated with the existing global screening approaches. We introduce APRICOT, a computational pipeline for the sequence-based identification and characterization of proteins using RBDs known from experimental studies. The pipeline identifies functional motifs in protein sequences using position-specific scoring matrices and Hidden Markov Models of the functional domains and statistically scores them based on a series of sequence-based features. Subsequently, APRICOT identifies putative RBPs and characterizes them by several biological properties. Here we demonstrate the application and adaptability of the pipeline on large-scale protein sets, including the bacterial proteome of Escherichia coli. APRICOT showed better performance on various datasets compared to other existing tools for the sequence-based prediction of RBPs by achieving an average sensitivity and specificity of 0.90 and 0.91 respectively. The command-line tool and its documentation are available at https://pypi.python.org/pypi/bio-apricot.}, language = {en} } @article{SassVanAckerFoerstneretal.2015, author = {Sass, Andrea M. and Van Acker, Heleen and F{\"o}rstner, Konrad U. and Van Nieuwerburgh, Filip and Deforce, Dieter and Vogel, J{\"o}rg and Coenye, Tom}, title = {Genome-wide transcription start site profiling in biofilm-grown Burkholderia cenocepacia J2315}, series = {BMC Genomics}, volume = {16}, journal = {BMC Genomics}, number = {775}, doi = {10.1186/s12864-015-1993-3}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-139748}, year = {2015}, abstract = {Background: Burkholderia cenocepacia is a soil-dwelling Gram-negative Betaproteobacterium with an important role as opportunistic pathogen in humans. Infections with B. cenocepacia are very difficult to treat due to their high intrinsic resistance to most antibiotics. Biofilm formation further adds to their antibiotic resistance. B. cenocepacia harbours a large, multi-replicon genome with a high GC-content, the reference genome of strain J2315 includes 7374 annotated genes. This study aims to annotate transcription start sites and identify novel transcripts on a whole genome scale. Methods: RNA extracted from B. cenocepacia J2315 biofilms was analysed by differential RNA-sequencing and the resulting dataset compared to data derived from conventional, global RNA-sequencing. Transcription start sites were annotated and further analysed according to their position relative to annotated genes. Results: Four thousand ten transcription start sites were mapped over the whole B. cenocepacia genome and the primary transcription start site of 2089 genes expressed in B. cenocepacia biofilms were defined. For 64 genes a start codon alternative to the annotated one was proposed. Substantial antisense transcription for 105 genes and two novel protein coding sequences were identified. The distribution of internal transcription start sites can be used to identify genomic islands in B. cenocepacia. A potassium pump strongly induced only under biofilm conditions was found and 15 non-coding small RNAs highly expressed in biofilms were discovered. Conclusions: Mapping transcription start sites across the B. cenocepacia genome added relevant information to the J2315 annotation. Genes and novel regulatory RNAs putatively involved in B. cenocepacia biofilm formation were identified. These findings will help in understanding regulation of B. cenocepacia biofilm formation.}, language = {en} }