TY - JOUR A1 - Sass, Andrea M. A1 - Van Acker, Heleen A1 - Förstner, Konrad U. A1 - Van Nieuwerburgh, Filip A1 - Deforce, Dieter A1 - Vogel, Jörg A1 - Coenye, Tom T1 - Genome-wide transcription start site profiling in biofilm-grown Burkholderia cenocepacia J2315 JF - BMC Genomics N2 - 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. KW - persistence KW - genomic islands KW - pathogen KW - identification KW - bacteria KW - small RNAs KW - translation initiation KW - cepedia complex KW - global gene expression KW - SEQ KW - resistance KW - burkholderia cenocepacia KW - biofilms KW - dRNA-Seq KW - transcription start site KW - antisense RNA Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-139748 VL - 16 IS - 775 ER - TY - JOUR A1 - Yu, Sung-Huan A1 - Vogel, Jörg A1 - Förstner, Konrad U. T1 - ANNOgesic: a Swiss army knife for the RNA-seq based annotation of bacterial/archaeal genomes JF - GigaScience N2 - To understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or noncoding RNAs, are harder to detect. RNA sequencing (RNA-seq) has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-seq data in order to generate high-resolution annotations is challenging, time consuming, and requires numerous steps. We have constructed a powerful and modular tool called ANNOgesic that provides the required analyses and simplifies RNA-seq-based bacterial and archaeal genome annotation. It can integrate data from conventional RNA-seq and differential RNA-seq and predicts and annotates numerous features, including small noncoding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pypi.org/project/ANNOgesic/. KW - genome annotation KW - RNA-seq KW - transcriptomics Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-178942 VL - 7 ER - TY - JOUR A1 - Westermann, Alexander J. A1 - Venturini, Elisa A1 - Sellin, Mikael E. A1 - Förstner, Konrad U. A1 - Hardt, Wolf-Dietrich A1 - Vogel, Jörg T1 - The major RNA-binding protein ProQ impacts virulence gene expression in Salmonella enterica serovar Typhimurium JF - mBio N2 - FinO domain proteins such as ProQ of the model pathogen Salmonella enterica have emerged as a new class of major RNA-binding proteins in bacteria. ProQ has been shown to target hundreds of transcripts, including mRNAs from many virulence regions, but its role, if any, in bacterial pathogenesis has not been studied. Here, using a Dual RNA-seq approach to profile ProQ-dependent gene expression changes as Salmonella infects human cells, we reveal dysregulation of bacterial motility, chemotaxis, and virulence genes which is accompanied by altered MAPK (mitogen-activated protein kinase) signaling in the host. Comparison with the other major RNA chaperone in Salmonella, Hfq, reinforces the notion that these two global RNA-binding proteins work in parallel to ensure full virulence. Of newly discovered infection-associated ProQ-bound small noncoding RNAs (sRNAs), we show that the 3′UTR-derived sRNA STnc540 is capable of repressing an infection-induced magnesium transporter mRNA in a ProQ-dependent manner. Together, this comprehensive study uncovers the relevance of ProQ for Salmonella pathogenesis and highlights the importance of RNA-binding proteins in regulating bacterial virulence programs. IMPORTANCE The protein ProQ has recently been discovered as the centerpiece of a previously overlooked “third domain” of small RNA-mediated control of gene expression in bacteria. As in vitro work continues to reveal molecular mechanisms, it is also important to understand how ProQ affects the life cycle of bacterial pathogens as these pathogens infect eukaryotic cells. Here, we have determined how ProQ shapes Salmonella virulence and how the activities of this RNA-binding protein compare with those of Hfq, another central protein in RNA-based gene regulation in this and other bacteria. To this end, we apply global transcriptomics of pathogen and host cells during infection. In doing so, we reveal ProQ-dependent transcript changes in key virulence and host immune pathways. Moreover, we differentiate the roles of ProQ from those of Hfq during infection, for both coding and noncoding transcripts, and provide an important resource for those interested in ProQ-dependent small RNAs in enteric bacteria. KW - Hfq KW - noncoding RNA KW - ProQ KW - RNA-seq KW - bacterial pathogen KW - posttranscriptional control Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-177722 VL - 10 IS - 1 ER - TY - JOUR A1 - Sharan, Malvika A1 - Förstner, Konrad U. A1 - Eulalio, Ana A1 - Vogel, Jörg T1 - APRICOT: an integrated computational pipeline for the sequence-based identification and characterization of RNA-binding proteins JF - Nucleic Acids Research N2 - 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. KW - RNA-binding proteins KW - identification KW - characterization Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-157963 VL - 45 IS - 11 ER -