@article{SunkavalliAguilarSilvaetal.2017, author = {Sunkavalli, Ushasree and Aguilar, Carmen and Silva, Ricardo Jorge and Sharan, Malvika and Cruz, Ana Rita and Tawk, Caroline and Maudet, Claire and Mano, Miguel and Eulalio, Ana}, title = {Analysis of host microRNA function uncovers a role for miR-29b-2-5p in Shigella capture by filopodia}, series = {PLoS Pathogens}, volume = {13}, journal = {PLoS Pathogens}, number = {4}, doi = {10.1371/journal.ppat.1006327}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-158204}, pages = {e1006327}, year = {2017}, abstract = {MicroRNAs play an important role in the interplay between bacterial pathogens and host cells, participating as host defense mechanisms, as well as exploited by bacteria to subvert host cellular functions. Here, we show that microRNAs modulate infection by Shigella flexneri, a major causative agent of bacillary dysentery in humans. Specifically, we characterize the dual regulatory role of miR-29b-2-5p during infection, showing that this microRNA strongly favors Shigella infection by promoting both bacterial binding to host cells and intracellular replication. Using a combination of transcriptome analysis and targeted high-content RNAi screening, we identify UNC5C as a direct target of miR-29b-2-5p and show its pivotal role in the modulation of Shigella binding to host cells. MiR-29b-2-5p, through repression of UNC5C, strongly enhances filopodia formation thus increasing Shigella capture and promoting bacterial invasion. The increase of filopodia formation mediated by miR-29b-2-5p is dependent on RhoF and Cdc42 Rho-GTPases. Interestingly, the levels of miR-29b-2-5p, but not of other mature microRNAs from the same precursor, are decreased upon Shigella replication at late times post-infection, through degradation of the mature microRNA by the exonuclease PNPT1. While the relatively high basal levels of miR-29b-2-5p at the start of infection ensure efficient Shigella capture by host cell filopodia, dampening of miR-29b-2-5p levels later during infection may constitute a bacterial strategy to favor a balanced intracellular replication to avoid premature cell death and favor dissemination to neighboring cells, or alternatively, part of the host response to counteract Shigella infection. Overall, these findings reveal a previously unappreciated role of microRNAs, and in particular miR-29b-2-5p, in the interaction of Shigella with host cells.}, language = {en} } @phdthesis{Sharan2017, author = {Sharan, Malvika}, title = {Bio-computational identification and characterization of RNA-binding proteins in bacteria}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-153573}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2017}, abstract = {RNA-binding proteins (RBPs) have been extensively studied in eukaryotes, where they post-transcriptionally regulate many cellular events including RNA transport, translation, and stability. Experimental techniques, such as cross-linking and co-purification followed by either mass spectrometry or RNA sequencing has enabled the identification and characterization of RBPs, their conserved RNA-binding domains (RBDs), and the regulatory roles of these proteins on a genome-wide scale. These developments in quantitative, high-resolution, and high-throughput screening techniques have greatly expanded our understanding of RBPs in human and yeast cells. In contrast, our knowledge of number and potential diversity of RBPs in bacteria is comparatively poor, in part due to the technical challenges associated with existing global screening approaches developed in eukaryotes. Genome- and proteome-wide screening approaches performed in silico may circumvent these technical issues to obtain a broad picture of the RNA interactome of bacteria and identify strong RBP candidates for more detailed experimental study. Here, I report APRICOT ("Analyzing Protein RNA Interaction by Combined Output Technique"), a computational pipeline for the sequence-based identification and characterization of candidate RNA-binding proteins encoded in the genomes of all domains of life using RBDs known from experimental studies. The pipeline identifies functional motifs in protein sequences of an input proteome using position-specific scoring matrices and hidden Markov models of all conserved domains available in the databases and then statistically score them based on a series of sequence-based features. Subsequently, APRICOT identifies putative RBPs and characterizes them according to functionally relevant structural properties. APRICOT performed better than other existing tools for the sequence-based prediction on the known RBP data sets. The applications and adaptability of the software was demonstrated on several large bacterial RBP data sets including the complete proteome of Salmonella Typhimurium strain SL1344. APRICOT reported 1068 Salmonella proteins as RBP candidates, which were subsequently categorized using the RBDs that have been reported in both eukaryotic and bacterial proteins. A set of 131 strong RBP candidates was selected for experimental confirmation and characterization of RNA-binding activity using RNA co-immunoprecipitation followed by high-throughput sequencing (RIP-Seq) experiments. Based on the relative abundance of transcripts across the RIP-Seq libraries, a catalogue of enriched genes was established for each candidate, which shows the RNA-binding potential of 90\% of these proteins. Furthermore, the direct targets of few of these putative RBPs were validated by means of cross-linking and co-immunoprecipitation (CLIP) experiments. This thesis presents the computational pipeline APRICOT for the global screening of protein primary sequences for potential RBPs in bacteria using RBD information from all kingdoms of life. Furthermore, it provides the first bio-computational resource of putative RBPs in Salmonella, which could now be further studied for their biological and regulatory roles. The command line tool and its documentation are available at https://malvikasharan.github.io/APRICOT/.}, language = {en} } @article{GarciaBetancurGoniMorenoHorgeretal.2017, author = {Garc{\´i}a-Betancur, Juan-Carlos and Go{\~n}i-Moreno, Angel and Horger, Thomas and Schott, Melanie and Sharan, Malvika and Eikmeier, Julian and Wohlmuth, Barbara and Zernecke, Alma and Ohlsen, Knut and Kuttler, Christina and Lopez, Daniel}, title = {Cell differentiation defines acute and chronic infection cell types in Staphylococcus aureus}, series = {eLife}, volume = {6}, journal = {eLife}, number = {e28023}, doi = {10.7554/eLife.28023}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-170346}, year = {2017}, abstract = {A central question to biology is how pathogenic bacteria initiate acute or chronic infections. Here we describe a genetic program for cell-fate decision in the opportunistic human pathogen Staphylococcus aureus, which generates the phenotypic bifurcation of the cells into two genetically identical but different cell types during the course of an infection. Whereas one cell type promotes the formation of biofilms that contribute to chronic infections, the second type is planktonic and produces the toxins that contribute to acute bacteremia. We identified a bimodal switch in the agr quorum sensing system that antagonistically regulates the differentiation of these two physiologically distinct cell types. We found that extracellular signals affect the behavior of the agr bimodal switch and modify the size of the specialized subpopulations in specific colonization niches. For instance, magnesium-enriched colonization niches causes magnesium binding to S. aureusteichoic acids and increases bacterial cell wall rigidity. This signal triggers a genetic program that ultimately downregulates the agr bimodal switch. Colonization niches with different magnesium concentrations influence the bimodal system activity, which defines a distinct ratio between these subpopulations; this in turn leads to distinct infection outcomes in vitro and in an in vivo murine infection model. Cell differentiation generates physiological heterogeneity in clonal bacterial infections and helps to determine the distinct infection types.}, language = {en} } @article{TawkSharanEulalioetal.2017, author = {Tawk, Caroline and Sharan, Malvika and Eulalio, Ana and Vogel, J{\"o}rg}, title = {A systematic analysis of the RNA-targeting potential of secreted bacterial effector proteins}, series = {Scientific Reports}, volume = {7}, journal = {Scientific Reports}, doi = {10.1038/s41598-017-09527-0}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-158815}, pages = {9328}, year = {2017}, abstract = {Many pathogenic bacteria utilize specialized secretion systems to deliver proteins called effectors into eukaryotic cells for manipulation of host pathways. The vast majority of known effector targets are host proteins, whereas a potential targeting of host nucleic acids remains little explored. There is only one family of effectors known to target DNA directly, and effectors binding host RNA are unknown. Here, we take a two-pronged approach to search for RNA-binding effectors, combining biocomputational prediction of RNA-binding domains (RBDs) in a newly assembled comprehensive dataset of bacterial secreted proteins, and experimental screening for RNA binding in mammalian cells. Only a small subset of effectors were predicted to carry an RBD, indicating that if RNA targeting was common, it would likely involve new types of RBDs. Our experimental evaluation of effectors with predicted RBDs further argues for a general paucity of RNA binding activities amongst bacterial effectors. We obtained evidence that PipB2 and Lpg2844, effector proteins of Salmonella and Legionella species, respectively, may harbor novel biochemical activities. Our study presenting the first systematic evaluation of the RNA-targeting potential of bacterial effectors offers a basis for discussion of whether or not host RNA is a prominent target of secreted bacterial proteins.}, language = {en} } @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} }