TY - JOUR A1 - Fröhlich, Kathrin S. A1 - Haneke, Katharina A1 - Papenfort, Kai A1 - Vogel, Jörg T1 - The target spectrum of SdsR small RNA in Salmonella JF - Nucleic Acids Research N2 - Model enteric bacteria such as Escherichia coli and Salmonella enterica express hundreds of small non-coding RNAs (sRNAs), targets for most of which are yet unknown. Some sRNAs are remarkably well conserved, indicating that they serve cellular functions that go beyond the necessities of a single species. One of these ‘core sRNAs’ of largely unknown function is the abundant ∼100-nucleotide SdsR sRNA which is transcribed by the general stress σ-factor, σ\(^{S}\) and accumulates in stationary phase. In Salmonella, SdsR was known to inhibit the synthesis of the species-specific porin, OmpD. However, sdsR genes are present in almost all enterobacterial genomes, suggesting that additional, conserved targets of this sRNA must exist. Here, we have combined SdsR pulse-expression with whole genome transcriptomics to discover 20 previously unknown candidate targets of SdsR which include mRNAs coding for physiologically important regulators such as the carbon utilization regulator, CRP, the nucleoid-associated chaperone, StpA and the antibiotic resistance transporter, TolC. Processing of SdsR by RNase E results in two cellular SdsR variants with distinct target spectra. While the overall physiological role of this orphan core sRNA remains to be fully understood, the new SdsR targets present valuable leads to determine sRNA functions in resting bacteria. KW - sRNA KW - Salmonella enterica KW - SdsR Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-175365 VL - 44 IS - 21 ER - TY - JOUR A1 - Jiang, Yuxiang A1 - Oron, Tal Ronnen A1 - Clark, Wyatt T. A1 - Bankapur, Asma R. A1 - D'Andrea, Daniel A1 - Lepore, Rosalba A1 - Funk, Christopher S. A1 - Kahanda, Indika A1 - Verspoor, Karin M. A1 - Ben-Hur, Asa A1 - Koo, Da Chen Emily A1 - Penfold-Brown, Duncan A1 - Shasha, Dennis A1 - Youngs, Noah A1 - Bonneau, Richard A1 - Lin, Alexandra A1 - Sahraeian, Sayed M. E. A1 - Martelli, Pier Luigi A1 - Profiti, Giuseppe A1 - Casadio, Rita A1 - Cao, Renzhi A1 - Zhong, Zhaolong A1 - Cheng, Jianlin A1 - Altenhoff, Adrian A1 - Skunca, Nives A1 - Dessimoz, Christophe A1 - Dogan, Tunca A1 - Hakala, Kai A1 - Kaewphan, Suwisa A1 - Mehryary, Farrokh A1 - Salakoski, Tapio A1 - Ginter, Filip A1 - Fang, Hai A1 - Smithers, Ben A1 - Oates, Matt A1 - Gough, Julian A1 - Törönen, Petri A1 - Koskinen, Patrik A1 - Holm, Liisa A1 - Chen, Ching-Tai A1 - Hsu, Wen-Lian A1 - Bryson, Kevin A1 - Cozzetto, Domenico A1 - Minneci, Federico A1 - Jones, David T. A1 - Chapman, Samuel A1 - BKC, Dukka A1 - Khan, Ishita K. A1 - Kihara, Daisuke A1 - Ofer, Dan A1 - Rappoport, Nadav A1 - Stern, Amos A1 - Cibrian-Uhalte, Elena A1 - Denny, Paul A1 - Foulger, Rebecca E. A1 - Hieta, Reija A1 - Legge, Duncan A1 - Lovering, Ruth C. A1 - Magrane, Michele A1 - Melidoni, Anna N. A1 - Mutowo-Meullenet, Prudence A1 - Pichler, Klemens A1 - Shypitsyna, Aleksandra A1 - Li, Biao A1 - Zakeri, Pooya A1 - ElShal, Sarah A1 - Tranchevent, Léon-Charles A1 - Das, Sayoni A1 - Dawson, Natalie L. A1 - Lee, David A1 - Lees, Jonathan G. A1 - Sillitoe, Ian A1 - Bhat, Prajwal A1 - Nepusz, Tamás A1 - Romero, Alfonso E. A1 - Sasidharan, Rajkumar A1 - Yang, Haixuan A1 - Paccanaro, Alberto A1 - Gillis, Jesse A1 - Sedeño-Cortés, Adriana E. A1 - Pavlidis, Paul A1 - Feng, Shou A1 - Cejuela, Juan M. A1 - Goldberg, Tatyana A1 - Hamp, Tobias A1 - Richter, Lothar A1 - Salamov, Asaf A1 - Gabaldon, Toni A1 - Marcet-Houben, Marina A1 - Supek, Fran A1 - Gong, Qingtian A1 - Ning, Wei A1 - Zhou, Yuanpeng A1 - Tian, Weidong A1 - Falda, Marco A1 - Fontana, Paolo A1 - Lavezzo, Enrico A1 - Toppo, Stefano A1 - Ferrari, Carlo A1 - Giollo, Manuel A1 - Piovesan, Damiano A1 - Tosatto, Silvio C. E. A1 - del Pozo, Angela A1 - Fernández, José M. A1 - Maietta, Paolo A1 - Valencia, Alfonso A1 - Tress, Michael L. A1 - Benso, Alfredo A1 - Di Carlo, Stefano A1 - Politano, Gianfranco A1 - Savino, Alessandro A1 - Rehman, Hafeez Ur A1 - Re, Matteo A1 - Mesiti, Marco A1 - Valentini, Giorgio A1 - Bargsten, Joachim W. A1 - van Dijk, Aalt D. J. A1 - Gemovic, Branislava A1 - Glisic, Sanja A1 - Perovic, Vladmir A1 - Veljkovic, Veljko A1 - Almeida-e-Silva, Danillo C. A1 - Vencio, Ricardo Z. N. A1 - Sharan, Malvika A1 - Vogel, Jörg A1 - Kansakar, Lakesh A1 - Zhang, Shanshan A1 - Vucetic, Slobodan A1 - Wang, Zheng A1 - Sternberg, Michael J. E. A1 - Wass, Mark N. A1 - Huntley, Rachael P. A1 - Martin, Maria J. A1 - O'Donovan, Claire A1 - Robinson, Peter N. A1 - Moreau, Yves A1 - Tramontano, Anna A1 - Babbitt, Patricia C. A1 - Brenner, Steven E. A1 - Linial, Michal A1 - Orengo, Christine A. A1 - Rost, Burkhard A1 - Greene, Casey S. A1 - Mooney, Sean D. A1 - Friedberg, Iddo A1 - Radivojac, Predrag A1 - Veljkovic, Nevena T1 - An expanded evaluation of protein function prediction methods shows an improvement in accuracy JF - Genome Biology N2 - Background A 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. Results We 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. Conclusions The 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. KW - Protein function prediction KW - Disease gene prioritization Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-166293 VL - 17 IS - 184 ER - TY - JOUR A1 - Müller, Anna A. A1 - Dolowschiak, Tamas A1 - Sellin, Mikael E. A1 - Felmy, Boas A1 - Verbree, Carolin A1 - Gadient, Sandra A1 - Westermann, Alexander J. A1 - Vogel, Jörg A1 - LeibundGut-Landmann, Salome A1 - Hardt, Wolf-Dietrich T1 - An NK Cell Perforin Response Elicited via IL-18 Controls Mucosal Inflammation Kinetics during Salmonella Gut Infection JF - PLoS Pathogens N2 - Salmonella Typhimurium (S.Tm) is a common cause of self-limiting diarrhea. The mucosal inflammation is thought to arise from a standoff between the pathogen's virulence factors and the host's mucosal innate immune defenses, particularly the mucosal NAIP/NLRC4 inflammasome. However, it had remained unclear how this switches the gut from homeostasis to inflammation. This was studied using the streptomycin mouse model. S.Tm infections in knockout mice, cytokine inhibition and –injection experiments revealed that caspase-1 (not -11) dependent IL-18 is pivotal for inducing acute inflammation. IL-18 boosted NK cell chemoattractants and enhanced the NK cells' migratory capacity, thus promoting mucosal accumulation of mature, activated NK cells. NK cell depletion and Prf\(^{-/-}\) ablation (but not granulocyte-depletion or T-cell deficiency) delayed tissue inflammation. Our data suggest an NK cell perforin response as one limiting factor in mounting gut mucosal inflammation. Thus, IL-18-elicited NK cell perforin responses seem to be critical for coordinating mucosal inflammation during early infection, when S.Tm strongly relies on virulence factors detectable by the inflammasome. This may have broad relevance for mucosal defense against microbial pathogens. KW - NK cells KW - Salmonella Typhimurium KW - mucosal inflammation KW - diarrhea Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-167429 VL - 12 IS - 6 ER - TY - JOUR A1 - Hershko-Shalev, Tal A1 - Odenheimer-Bergman, Ahuva A1 - Elgrably-Weiss, Maya A1 - Ben-Zvi, Tamar A1 - Govindarajan, Sutharsan A1 - Seri, Hemda A1 - Papenfort, Kai A1 - Vogel, Jörg A1 - Altuvia, Shoshy T1 - Gifsy-1 Prophage IsrK with Dual Function as Small and Messenger RNA Modulates Vital Bacterial Machineries JF - PLoS Genetics N2 - While an increasing number of conserved small regulatory RNAs (sRNAs) are known to function in general bacterial physiology, the roles and modes of action of sRNAs from horizontally acquired genomic regions remain little understood. The IsrK sRNA of Gifsy-1 prophage of Salmonella belongs to the latter class. This regulatory RNA exists in two isoforms. The first forms, when a portion of transcripts originating from isrK promoter reads-through the IsrK transcription-terminator producing a translationally inactive mRNA target. Acting in trans, the second isoform, short IsrK RNA, binds the inactive transcript rendering it translationally active. By switching on translation of the first isoform, short IsrK indirectly activates the production of AntQ, an antiterminator protein located upstream of isrK. Expression of antQ globally interferes with transcription termination resulting in bacterial growth arrest and ultimately cell death. Escherichia coli and Salmonella cells expressing AntQ display condensed chromatin morphology and localization of UvrD to the nucleoid. The toxic phenotype of AntQ can be rescued by co-expression of the transcription termination factor, Rho, or RNase H, which protects genomic DNA from breaks by resolving R-loops. We propose that AntQ causes conflicts between transcription and replication machineries and thus promotes DNA damage. The isrK locus represents a unique example of an island-encoded sRNA that exerts a highly complex regulatory mechanism to tune the expression of a toxic protein. KW - prophage KW - Gifsy-1 KW - sRNA KW - IsrK Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-166717 VL - 12 IS - 4 ER - 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 - Fan, Ben A1 - Li, Lei A1 - Chao, Yanjie A1 - Förstner, Konrad A1 - Vogel, Jörg A1 - Borriss, Rainer A1 - Wu, Xiao-Qin T1 - dRNA-Seq Reveals Genomewide TSSs and Noncoding RNAs of Plant Beneficial Rhizobacterium Bacillus amyloliquefaciens FZB42 JF - PLoS One N2 - Bacillus amyloliquefaciens subsp. plantarum FZB42 is a representative of Gram-positive plant-growth-promoting rhizobacteria (PGPR) that inhabit plant root environments. In order to better understand the molecular mechanisms of bacteria-plant symbiosis, we have systematically analyzed the primary transcriptome of strain FZB42 grown under rhizospheremimicking conditions using differential RNA sequencing (dRNA-seq). Our analysis revealed 4,877 transcription start sites for protein-coding genes, identified genes differentially expressed under different growth conditions, and corrected many previously mis-annotated genes. We also identified a large number of riboswitches and cis-encoded antisense RNAs, as well as trans-encoded small noncoding RNAs that may play important roles in the gene regulation of Bacillus. Overall, our analyses provided a landscape of Bacillus primary transcriptome and improved the knowledge of rhizobacteria-host interactions. KW - gene expression KW - subtilis genome KW - enterica serovar thphimurium KW - small regulatory RNAs KW - binding protein HFQ KW - escherichia coli KW - messenger RNA KW - transcriptional landscape KW - mycobacterium tuberculosis KW - listeria monocytogenes Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-138369 VL - 10 IS - 11 ER - TY - JOUR A1 - Afonso-Grunz, Fabian A1 - Hoffmeier, Klaus A1 - Müller, Sören A1 - Westermann, Alexander J. A1 - Rotter, Björn A1 - Vogel, Jörg A1 - Winter, Peter A1 - Kahl, Günter T1 - Dual 3'Seq using deepSuperSAGE uncovers transcriptomes of interacting Salmonella enterica Typhimurium and human host cells JF - BMC Genomics N2 - Background: The interaction of eukaryotic host and prokaryotic pathogen cells is linked to specific changes in the cellular proteome, and consequently to infection-related gene expression patterns of the involved cells. To simultaneously assess the transcriptomes of both organisms during their interaction we developed dual 3'Seq, a tag-based sequencing protocol that allows for exact quantification of differentially expressed transcripts in interacting pro-and eukaryotic cells without prior fixation or physical disruption of the interaction. Results: Human epithelial cells were infected with Salmonella enterica Typhimurium as a model system for invasion of the intestinal epithelium, and the transcriptional response of the infected host cells together with the differential expression of invading and intracellular pathogen cells was determined by dual 3'Seq coupled with the next-generation sequencing-based transcriptome profiling technique deepSuperSAGE (deep Serial Analysis of Gene Expression). Annotation to reference transcriptomes comprising the operon structure of the employed S. enterica Typhimurium strain allowed for in silico separation of the interacting cells including quantification of polycistronic RNAs. Eighty-nine percent of the known loci are found to be transcribed in prokaryotic cells prior or subsequent to infection of the host, while 75% of all protein-coding loci are represented in the polyadenylated transcriptomes of human host cells. Conclusions: Dual 3'Seq was alternatively coupled to MACE (Massive Analysis of cDNA ends) to assess the advantages and drawbacks of a library preparation procedure that allows for sequencing of longer fragments. Additionally, the identified expression patterns of both organisms were validated by qRT-PCR using three independent biological replicates, which confirmed that RELB along with NFKB1 and NFKB2 are involved in the initial immune response of epithelial cells after infection with S. enterica Typhimurium. KW - complete genome sequence KW - secretion systems KW - RNA-Seq KW - deepSuperSAGE KW - transcriptome KW - gene expression KW - serovar Typhimurium KW - human macrophages KW - epithelial cells KW - infection KW - SuperSAGE KW - receptors KW - Dual 3'seq KW - MACE KW - tag based KW - simultaneous KW - genome wide KW - gene expression profiling KW - host pathogen interaction KW - Salmonella enterica Typhimurium strain SL1344 Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-143230 VL - 16 IS - 323 ER - TY - JOUR A1 - Papenfort, Kai A1 - Vogel, Jörg T1 - Small RNA functions in carbon metabolism and virulence of enteric pathogens JF - Frontiers in Cellular and Infection Microbiology N2 - Enteric pathogens often cycle between virulent and saprophytic lifestyles. To endure these frequent changes in nutrient availability and composition bacteria possess an arsenal of regulatory and metabolic genes allowing rapid adaptation and high flexibility. While numerous proteins have been characterized with regard to metabolic control in pathogenic bacteria, small non-coding RNAs have emerged as additional regulators of metabolism. Recent advances in sequencing technology have vastly increased the number of candidate regulatory RNAs and several of them have been found to act at the interface of bacterial metabolism and virulence factor expression. Importantly, studying these riboregulators has not only provided insight into their metabolic control functions but also revealed new mechanisms of post-transcriptional gene control. This review will focus on the recent advances in this area of host-microbe interaction and discuss how regulatory small RNAs may help coordinate metabolism and virulence of enteric pathogens. KW - sRNA KW - carbon metabolism KW - Hfq KW - CsrA KW - virulence Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-197520 SN - 2235-2988 VL - 4 IS - 91 ER - TY - JOUR A1 - Dimastrogiovanni, Daniela A1 - Fröhlich, Kathrin S. A1 - Bandyra, Katarzyna J. A1 - Bruce, Heather A. A1 - Hohensee, Susann A1 - Vogel, Jörg A1 - Luisi, Ben F. T1 - Recognition of the small regulatory RNA RydC by the bacterial Hfq protein JF - eLife N2 - Bacterial small RNAs (sRNAs) are key elements of regulatory networks that modulate gene expression. The sRNA RydC of Salmonella sp. and Escherichia coli is an example of this class of riboregulators. Like many other sRNAs, RydC bears a 'seed' region that recognises specific transcripts through base-pairing, and its activities are facilitated by the RNA chaperone Hfq. The crystal structure of RydC in complex with E. coli Hfq at 3.48 angstrom resolution illuminates how the protein interacts with and presents the sRNA for target recognition. Consolidating the protein-RNA complex is a host of distributed interactions mediated by the natively unstructured termini of Hfq. Based on the structure and other data, we propose a model for a dynamic effector complex comprising Hfq, small RNA, and the cognate mRNA target. KW - Hfq KW - small RNA KW - natively unstructured protein KW - protein-RNA recognition KW - gene regulation KW - Escherichia coli-Hfq KW - SM-like protein KW - messenger-RNA KW - chaperone Hfq KW - target recognition KW - noncoding RNAs KW - interaction surfaces KW - crystal-structures KW - soluble-RNAs KW - C-Terminus Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-114191 SN - 2050-084X VL - 3 IS - e05375 ER - TY - JOUR A1 - Gorski, Stanislaw A. A1 - Vogel, Jörg A1 - Saliba, Antoine-Emmanuel A1 - Westermann, Alexander J. T1 - Single-cell RNA-seq: advances and future challenges N2 - Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Singlecell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNAseq protocols have been introduced and are reviewed here – each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field. KW - RNS Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-110993 ER -