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  - 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  - 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  - 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  -