RNIE: genome-wide prediction of bacterial intrinsic terminators

Bacterial Rho-independent terminators (RITs) are important genomic landmarks involved in gene regulation and terminating gene expression. In this investigation we present RNIE, a probabilistic approach for predicting RITs. The method is based upon covariance models which have been known for many years to be the most accurate computational tools for predicting homology in structural non-coding RNAs. We show that RNIE has superior performance in model species from a spectrum of bacterial phyla. Further analysis of species where a low number of RITs were predicted revealed a highly conserved structural sequence motif enriched near the genic termini of the pathogenic Actinobacteria, Mycobacterium tuberculosis. This motif, together with classical RITs, account for up to 90% of all the significantly structured regions from the termini of M. tuberculosis genic elements. The software, predictions and alignments described below are available from http://github.com/ppgardne/RNIE

Reflecting back and forwards: The ebb and flow of peer-reviewed reflective practice research in sport

Researchers in sport have claimed that reflective practice is important for competent practice. Evidence supporting this claim is sparse, highly theoretical and located within a variety of domains. The aim of this study was to assimilate and analyse the last 12 years of reflective practice literature within the sport domain in order to identify new areas of inquiry, emerging trends with regard to findings or methodology, and to identify implications for future research and practice. A sample of 68 papers published between 2001 and 2012 was examined, and investigated for the research locations, data collection methods utilised, and the professions and communities involved. The paper concludes with some suggestions for future research

Maximum expected accuracy structural neighbors of an RNA secondary structure

International audienceBACKGROUND: Since RNA molecules regulate genes and control alternative splicing by allostery, it is important to develop algorithms to predict RNA conformational switches. Some tools, such as paRNAss, RNAshapes and RNAbor, can be used to predict potential conformational switches; nevertheless, no existent tool can detect general (i.e., not family specific) entire riboswitches (both aptamer and expression platform) with accuracy. Thus, the development of additional algorithms to detect conformational switches seems important, especially since the difference in free energy between the two metastable secondary structures may be as large as 15-20 kcal/mol. It has recently emerged that RNA secondary structure can be more accurately predicted by computing the maximum expected accuracy (MEA) structure, rather than the minimum free energy (MFE) structure. RESULTS: Given an arbitrary RNA secondary structure S₀ for an RNA nucleotide sequence a = a₁,..., a(n), we say that another secondary structure S of a is a k-neighbor of S₀, if the base pair distance between S₀ and S is k. In this paper, we prove that the Boltzmann probability of all k-neighbors of the minimum free energy structure S₀ can be approximated with accuracy ε and confidence 1 - p, simultaneously for all 0 ≤ k N(ε,p,K)=Φ⁻¹(p/2K)²/4ε², where Φ(z) is the cumulative distribution function (CDF) for the standard normal distribution. We go on to describe the algorithm RNAborMEA, which for an arbitrary initial structure S₀ and for all values 0 ≤ k < K, computes the secondary structure MEA(k), having maximum expected accuracy over all k-neighbors of S₀. Computation time is O(n³ * K²), and memory requirements are O(n² * K). We analyze a sample TPP riboswitch, and apply our algorithm to the class of purine riboswitches. CONCLUSIONS: The approximation of RNAbor by sampling, with rigorous bound on accuracy, together with the computation of maximum expected accuracy k-neighbors by RNAborMEA, provide additional tools toward conformational switch detection. Results from RNAborMEA are quite distinct from other tools, such as RNAbor, RNAshapes and paRNAss, hence may provide orthogonal information when looking for suboptimal structures or conformational switches. Source code for RNAborMEA can be downloaded from http://sourceforge.net/projects/rnabormea/ or http://bioinformatics.bc.edu/clotelab/RNAborMEA/

Transcriptional responses of ecologically diverse drosophila species to larval diets differing in relative sugar and protein ratios

We utilized three ecologically diverse Drosophila species to explore the influence of ecological adaptation on transcriptomic responses to isocaloric diets differing in their relative proportions of protein to sugar. Drosophila melanogaster, a cosmopolitan species that breeds in decaying fruit, exemplifies individuals long exposed to a Western diet higher in sugar, while the natural diet of the cactophilic D. mojavensis, is much lower in carbohydrates. Drosophila arizonae, the sister species of D. mojavensis, is largely cactophilic, but also utilizes rotting fruits that are higher in sugars than cacti. We exposed third instar larvae for 24 hours to diets either (1) high in protein relative to sugar, (2) diets with equal amounts of protein and sugar, and (3) diets low in protein but high in sugar. As we predicted, based upon earlier interspecific studies of development and metabolism, the most extreme differences in gene expression under different dietary conditions were found in D. mojavensis followed by D. arizonae. No differential expression among diets was observed for D. melanogaster, a species that survives well under all three conditions, with little impact on its metabolism. We suggest that these three species together provide a model to examine individual and population differences in vulnerability to lifestyle-associated health problems such as metabolic syndrome and diabetes

Single-nucleotide resolution analysis of the transcriptome structure of Clostridium beijerinckii NCIMB 8052 using RNA-Seq

<p>Abstract</p> <p>Background</p> <p><it>Clostridium beijerinckii </it>is an important solvent producing microorganism. The genome of <it>C. beijerinckii </it>NCIMB 8052 has recently been sequenced. Although transcriptome structure is important in order to reveal the functional and regulatory architecture of the genome, the physical structure of transcriptome for this strain, such as the operon linkages and transcript boundaries are not well understood.</p> <p>Results</p> <p>In this study, we conducted a single-nucleotide resolution analysis of the <it>C. beijerinckii </it>NCIMB 8052 transcriptome using high-throughput RNA-Seq technology. We identified the transcription start sites and operon structure throughout the genome. We confirmed the structure of important gene operons involved in metabolic pathways for acid and solvent production in <it>C. beijerinckii </it>8052, including <it>pta</it>-<it>ack</it>, <it>ptb</it>-<it>buk</it>, <it>hbd</it>-<it>etfA</it>-<it>etfB</it>-<it>crt </it>(<it>bcs</it>) and <it>ald</it>-<it>ctfA</it>-<it>ctfB</it>-<it>adc </it>(<it>sol</it>) operons; we also defined important operons related to chemotaxis/motility, transcriptional regulation, stress response and fatty acids biosynthesis along with others. We discovered 20 previously non-annotated regions with significant transcriptional activities and 15 genes whose translation start codons were likely mis-annotated. As a consequence, the accuracy of existing genome annotation was significantly enhanced. Furthermore, we identified 78 putative silent genes and 177 putative housekeeping genes based on normalized transcription measurement with the sequence data. We also observed that more than 30% of pseudogenes had significant transcriptional activities during the fermentation process. Strong correlations exist between the expression values derived from RNA-Seq analysis and microarray data or qRT-PCR results.</p> <p>Conclusions</p> <p>Transcriptome structural profiling in this research provided important supplemental information on the accuracy of genome annotation, and revealed additional gene functions and regulation in <it>C. beijerinckii</it>.</p

Regulation of Amyloid Precursor Protein Processing by the Beclin 1 Complex

Autophagy is an intracellular degradation pathway that functions in protein and organelle turnover in response to starvation and cellular stress. Autophagy is initiated by the formation of a complex containing Beclin 1 (BECN1) and its binding partner Phosphoinositide-3-kinase, class 3 (PIK3C3). Recently, BECN1 deficiency was shown to enhance the pathology of a mouse model of Alzheimer Disease (AD). However, the mechanism by which BECN1 or autophagy mediate these effects are unknown. Here, we report that the levels of Amyloid precursor protein (APP) and its metabolites can be reduced through autophagy activation, indicating that they are a substrate for autophagy. Furthermore, we find that knockdown of Becn1 in cell culture increases the levels of APP and its metabolites. Accumulation of APP and APP C-terminal fragments (APP-CTF) are accompanied by impaired autophagosomal clearance. Pharmacological inhibition of autophagosomal-lysosomal degradation causes a comparable accumulation of APP and APP-metabolites in autophagosomes. Becn1 reduction in cell culture leads to lower levels of its binding partner Pik3c3 and increased presence of Microtubule-associated protein 1, light chain 3 (LC3). Overexpression of Becn1, on the other hand, reduces cellular APP levels. In line with these observations, we detected less BECN1 and PIK3C3 but more LC3 protein in brains of AD patients. We conclude that BECN1 regulates APP processing and turnover. BECN1 is involved in autophagy initiation and autophagosome clearance. Accordingly, BECN1 deficiency disrupts cellular autophagy and autophagosomal-lysosomal degradation and alters APP metabolism. Together, our findings suggest that autophagy and the BECN1-PIK3C3 complex regulate APP processing and play an important role in AD pathology

High-throughput profiling of caenorhabditis elegans starvation-responsive microRNAs

MicroRNAs (miRNAs) are non-coding RNAs of ~22 nucleotides in length that regulate gene expression by interfering with the stability and translation of mRNAs. Their expression is regulated during development, under a wide variety of stress conditions and in several pathological processes. In nature, animals often face feast or famine conditions. We observed that subjecting early L4 larvae from Caenorhabditis elegans to a 12-hr starvation period produced worms that are thinner and shorter than well-fed animals, with a decreased lipid accumulation, diminished progeny, reduced gonad size, and an increased lifespan. Our objective was to identify which of the 302 known miRNAs of C. elegans changed their expression under starvation conditions as compared to well-fed worms by means of deep sequencing in early L4 larvae. Our results indicate that 13 miRNAs (miR-34-3p, the family of miR-35-3p to miR-41-3p, miR-39-5p, miR-41-5p, miR-240-5p, miR-246-3p and miR-4813-5p) were upregulated, while 2 miRNAs (let-7-3p and miR-85-5p) were downregulated in 12-hr starved vs. well-fed early L4 larvae. Some of the predicted targets of the miRNAs that changed their expression in starvation conditions are involved in metabolic or developmental process. In particular, miRNAs of the miR-35 family were upregulated 6-20 fold upon starvation. Additionally, we showed that the expression of gld-1, important in oogenesis, a validated target of miR-35-3p, was downregulated when the expression of miR-35-3p was upregulated. The expression of another reported target, the cell cycle regulator lin-23, was unchanged during starvation. This study represents a starting point for a more comprehensive understanding of the role of miRNAs during starvation in C. elegans

The role of tenascin-C in tissue injury and tumorigenesis

The extracellular matrix molecule tenascin-C is highly expressed during embryonic development, tissue repair and in pathological situations such as chronic inflammation and cancer. Tenascin-C interacts with several other extracellular matrix molecules and cell-surface receptors, thus affecting tissue architecture, tissue resilience and cell responses. Tenascin-C modulates cell migration, proliferation and cellular signaling through induction of pro-inflammatory cytokines and oncogenic signaling molecules amongst other mechanisms. Given the causal role of inflammation in cancer progression, common mechanisms might be controlled by tenascin-C during both events. Drugs targeting the expression or function of tenascin-C or the tenascin-C protein itself are currently being developed and some drugs have already reached advanced clinical trials. This generates hope that increased knowledge about tenascin-C will further improve management of diseases with high tenascin-C expression such as chronic inflammation, heart failure, artheriosclerosis and cancer

Comparative genomics of metabolic capacities of regulons controlled by cis-regulatory RNA motifs in bacteria

BACKGROUND: In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels. An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis. RESULTS: A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations. CONCLUSIONS: The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome-wide collection of reference RNA motif regulons is available in the RegPrecise database (http://regprecise.lbl.gov/)