Ana Carolina Fierro

Obg and Membrane Depolarization Are Part of a Microbial Bet-Hedging Strategy that Leads to Antibiotic Tolerance

Within bacterial populations, a small fraction of persister cells is transiently capable of surviving exposure to lethal doses of antibiotics. As a bet-hedging strategy, persistence levels are determined both by stochastic induction and by environmental stimuli called responsive diversification. Little is known about the mechanisms that link the low frequency of persisters to environmental signals. Our results support a central role for the conserved GTPase Obg in determining persistence in Escherichia coli in response to nutrient starvation. Obg-mediated persistence requires the stringent response alarmone (p)ppGpp and proceeds through transcriptional control of the hokB-sokB type I toxin-antitoxin module. In individual cells, increased Obg levels induce HokB expression, which in turn results in a collapse of the membrane potential, leading to dormancy. Obg also controls persistence in Pseudomonas aeruginosa and thus constitutes a conserved regulator of antibiotic tolerance. Combined, our findings signify an important step toward unraveling shared genetic mechanisms underlying persistence.

Evolutionary conservation of plant gibberellin signalling pathway components

Background:Gibberellins (GA) are plant hormones that can regulate germination, elongation growth, and sex determination. They ubiquitously occur in seed plants. The discovery of gibberellin receptors, together with advances in understanding the function of key components of GA signalling in Arabidopsis and rice, reveal a fairly short GA signal transduction route. The pathway essentially consists of GID1 gibberellin receptors that interact with F-box proteins, which in turn regulate degradation of downstream DELLA proteins, suppressors of GA-controlled responses.Results:Arabidopsis sequences of the gibberellin signalling compounds were used to screen databases from a variety of plants, including protists, for homologues, providing indications for the degree of conservation of the pathway. The pathway as such appears completely absent in protists, the moss Physcomitrella patens shares only a limited homology with the Arabidopsis proteins, thus lacking essential characteristics of the classical GA signalling pathway, while the lycophyte Selaginella moellendorffii contains a possible ortholog for each component. The occurrence of classical GA responses can as yet not be linked with the presence of homologues of the signalling pathway. Alignments and display in neighbour joining trees of the GA signalling components confirm the close relationship of gymnosperms, monocotyledonous and dicotyledonous plants, as suggested from previous studies.Conclusion:Homologues of the GA-signalling pathway were mainly found in vascular plants. The GA signalling system may have its evolutionary molecular onset in Physcomitrella patens, where GAs at higher concentrations affect gravitropism and elongation growth.

Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection

Computationally retrieving biologically relevant cis-regulatory modules (CRMs) is not straightforward. Because of the large number of candidates and the imperfection of the screening methods, many spurious CRMs are detected that are as high scoring as the biologically true ones. Using ChIP-information allows not only to reduce the regions in which the binding sites of the assayed transcription factor (TF) should be located, but also allows restricting the valid CRMs to those that contain the assayed TF (here referred to as applying CRM detection in a query-based mode). In this study, we show that exploiting ChIP-information in a query-based way makes in silico CRM detection a much more feasible endeavor. To be able to handle the large datasets, the query-based setting and other specificities proper to CRM detection on ChIP-Seq based data, we developed a novel powerful CRM detection method ‘CPModule’. By applying it on a well-studied ChIP-Seq data set involved in self-renewal of mouse embryonic stem cells, we demonstrate how our tool can recover combinatorial regulation of five known TFs that are key in the self-renewal of mouse embryonic stem cells. Additionally, we make a number of new predictions on combinatorial regulation of these five key TFs with other TFs documented in TRANSFAC.

Photoreceptor-Mediated Bending towards UV-B in Arabidopsis

Plants reorient their growth towards light to optimize photosynthetic light capture--a process known as phototropism. Phototropins are the photoreceptors essential for phototropic growth towards blue and ultraviolet-A (UV-A) light. Here we detail a phototropic response towards UV-B in etiolated Arabidopsis seedlings. We report that early differential growth is mediated by phototropins but clear phototropic bending to UV-B is maintained in phot1 phot2 double mutants. We further show that this phototropin-independent phototropic response to UV-B requires the UV-B photoreceptor UVR8. Broad UV-B-mediated repression of auxin-responsive genes suggests that UVR8 regulates directional bending by affecting auxin signaling. Kinetic analysis shows that UVR8-dependent directional bending occurs later than the phototropin response. We conclude that plants may use the full short-wavelength spectrum of sunlight to efficiently reorient photosynthetic tissue with incoming light.

Inferring the transcriptional network of Bacillus subtilis

The adaptation of bacteria to the vigorous environmental changes they undergo is crucial to their survival. They achieve this adaptation partly via intricate regulation of the transcription of their genes. In this study, we infer the transcriptional network of the Gram-positive model organism, Bacillus subtilis. We use a data integration workflow, exploiting both motif and expression data, towards the generation of condition-dependent transcriptional modules. In building the motif data, we rely on both known and predicted information. Known motifs were derived from DBTBS, while predicted motifs were generated by a de novo motif detection method that utilizes comparative genomics. The expression data consists of a compendium of microarrays across different platforms. Our results indicate that a considerable part of the B. subtilis network is yet undiscovered; we could predict 417 new regulatory interactions for known regulators and 453 interactions for yet uncharacterized regulators. The regulators in our network showed a preference for regulating modules in certain environmental conditions. Also, substantial condition-dependent intra-operonic regulation seems to take place. Global regulators seem to require functional flexibility to attain their roles by acting as both activators and repressors.

COLOMBOS: Access Port for Cross-Platform Bacterial Expression Compendia

Background Microarrays are the main technology for large-scale transcriptional gene expression profiling, but the large bodies of data available in public databases are not useful due to the large heterogeneity. There are several initiatives that attempt to bundle these data into expression compendia, but such resources for bacterial organisms are scarce and limited to integration of experiments from the same platform or to indirect integration of per experiment analysis results. Methodology/Principal Findings We have constructed comprehensive organism-specific cross-platform expression compendia for three bacterial model organisms (Escherichia coli, Bacillus subtilis, and Salmonella enterica serovar Typhimurium) together with an access portal, dubbed COLOMBOS, that not only provides easy access to the compendia, but also includes a suite of tools for exploring, analyzing, and visualizing the data within these compendia. It is freely available at http://bioi.biw.kuleuven.be/colombos. The compendia are unique in directly combining expression information from different microarray platforms and experiments, and we illustrate the potential benefits of this direct integration with a case study: extending the known regulon of the Fur transcription factor of E. coli. The compendia also incorporate extensive annotations for both genes and experimental conditions; these heterogeneous data are functionally integrated in the COLOMBOS analysis tools to interactively browse and query the compendia not only for specific genes or experiments, but also metabolic pathways, transcriptional regulation mechanisms, experimental conditions, biological processes, etc. Conclusions/Significance We have created cross-platform expression compendia for several bacterial organisms and developed a complementary access port COLOMBOS, that also serves as a convenient expression analysis tool to extract useful biological information. This work is relevant to a large community of microbiologists by facilitating the use of publicly available microarray experiments to support their research.

COMODO: an adaptive coclustering strategy to identify conserved coexpression modules between organisms

Increasingly large-scale expression compendia for different species are becoming available. By exploiting the modularity of the coexpression network, these compendia can be used to identify biological processes for which the expression behavior is conserved over different species. However, comparing module networks across species is not trivial. The definition of a biologically meaningful module is not a fixed one and changing the distance threshold that defines the degree of coexpression gives rise to different modules. As a result when comparing modules across species, many different partially overlapping conserved module pairs across species exist and deciding which pair is most relevant is hard. Therefore, we developed a method referred to as conserved modules across organisms (COMODO) that uses an objective selection criterium to identify conserved expression modules between two species. The method uses as input microarray data and a gene homology map and provides as output pairs of conserved modules and searches for the pair of modules for which the number of sharing homologs is statistically most significant relative to the size of the linked modules. To demonstrate its principle, we applied COMODO to study coexpression conservation between the two well-studied bacteria Escherichia coli and Bacillus subtilis. COMODO is available at: http://homes.esat.kuleuven.be/∼kmarchal/Supplementary_Information_Zarrineh_2010/comodo/index.html.

Exploring nervous system transcriptomes during embryogenesis and metamorphosis in Xenopus tropicalis using EST analysis

BackgroundThe western African clawed frog Xenopus tropicalis is an anuran amphibian species now used as model in vertebrate comparative genomics. It provides the same advantages as Xenopus laevis but is diploid and has a smaller genome of 1.7 Gbp. Therefore X. tropicalis is more amenable to systematic transcriptome surveys. We initiated a large-scale partial cDNA sequencing project to provide a functional genomics resource on genes expressed in the nervous system during early embryogenesis and metamorphosis in X. tropicalis.ResultsA gene index was defined and analysed after the collection of over 48,785 high quality sequences. These partial cDNA sequences were obtained from an embryonic head and retina library (30,272 sequences) and from a metamorphic brain and spinal cord library (27,602 sequences). These ESTs are estimated to represent 9,693 transcripts derived from an estimated 6,000 genes. Comparison of these cDNA sequences with protein databases indicates that 46% contain their start codon. Further annotation included Gene Ontology functional classification, InterPro domain analysis, alternative splicing and non-coding RNA identification. Gene expression profiles were derived from EST counts and used to define transcripts specific to metamorphic stages of development. Moreover, these ESTs allowed identification of a set of 225 polymorphic microsatellites that can be used as genetic markers.ConclusionThese cDNA sequences permit in silico cloning of numerous genes and will facilitate studies aimed at deciphering the roles of cognate genes expressed in the nervous system during neural development and metamorphosis. The genomic resources developed to study X. tropicalis biology will accelerate exploration of amphibian physiology and genetics. In particular, the model will facilitate analysis of key questions related to anuran embryogenesis and metamorphosis and its associated regulatory processes.

Elucidation of the Mode of Action of a New Antibacterial Compound Active against Staphylococcus aureus and Pseudomonas aeruginosa

Nosocomial and community-acquired infections caused by multidrug resistant bacteria represent a major human health problem. Thus, there is an urgent need for the development of antibiotics with new modes of action. In this study, we investigated the antibacterial characteristics and mode of action of a new antimicrobial compound, SPI031 (N-alkylated 3, 6-dihalogenocarbazol 1-(sec-butylamino)-3-(3,6-dichloro-9H-carbazol-9-yl)propan-2-ol), which was previously identified in our group. This compound exhibits broad-spectrum antibacterial activity, including activity against the human pathogens Staphylococcus aureus and Pseudomonas aeruginosa. We found that SPI031 has rapid bactericidal activity (7-log reduction within 30 min at 4x MIC) and that the frequency of resistance development against SPI031 is low. To elucidate the mode of action of SPI031, we performed a macromolecular synthesis assay, which showed that SPI031 causes non-specific inhibition of macromolecular biosynthesis pathways. Liposome leakage and membrane permeability studies revealed that SPI031 rapidly exerts membrane damage, which is likely the primary cause of its antibacterial activity. These findings were supported by a mutational analysis of SPI031-resistant mutants, a transcriptome analysis and the identification of transposon mutants with altered sensitivity to the compound. In conclusion, our results show that SPI031 exerts its antimicrobial activity by causing membrane damage, making it an interesting starting point for the development of new antibacterial therapies.

Ranked tiling

Tiling is a well-known pattern mining technique. Traditionally, it discovers large areas of ones in binary databases or matrices, where an area is defined by a set of rows and a set of columns. In this paper, we introduce the novel problem of ranked tiling, which is concerned with finding interesting areas in ranked data. In this data, each transaction defines a complete ranking of the columns. Ranked data occurs naturally in applications like sports or other competitions. It is also a useful abstraction when dealing with numeric data in which the rows are incomparable. We introduce a scoring function for ranked tiling, as well as an algorithm using constraint programming and optimization principles. We empirically evaluate the approach on both synthetic and real-life datasets, and demonstrate the applicability of the framework in several case studies. One case study involves a heterogeneous dataset concerning the discovery of biomarkers for different subtypes of breast cancer patients. An analysis of the tiles by a domain expert shows that our approach can lead to the discovery of novel insights.