DroID: the Drosophila Interactions Database, a comprehensive resource for annotated gene and protein interactions

<p>Abstract</p> <p>Background</p> <p>Charting the interactions among genes and among their protein products is essential for understanding biological systems. A flood of interaction data is emerging from high throughput technologies, computational approaches, and literature mining methods. Quick and efficient access to this data has become a critical issue for biologists. Several excellent multi-organism databases for gene and protein interactions are available, yet most of these have understandable difficulty maintaining comprehensive information for any one organism. No single database, for example, includes all available interactions, integrated gene expression data, and comprehensive and searchable gene information for the important model organism, <it>Drosophila melanogaster</it>.</p> <p>Description</p> <p>DroID, the <it>Drosophila </it>Interactions Database, is a comprehensive interactions database designed specifically for <it>Drosophila</it>. DroID houses published physical protein interactions, genetic interactions, and computationally predicted interactions, including interologs based on data for other model organisms and humans. All interactions are annotated with original experimental data and source information. DroID can be searched and filtered based on interaction information or a comprehensive set of gene attributes from Flybase. DroID also contains gene expression and expression correlation data that can be searched and used to filter datasets, for example, to focus a study on sub-networks of co-expressed genes. To address the inherent noise in interaction data, DroID employs an updatable confidence scoring system that assigns a score to each physical interaction based on the likelihood that it represents a biologically significant link.</p> <p>Conclusion</p> <p>DroID is the most comprehensive interactions database available for <it>Drosophila</it>. To facilitate downstream analyses, interactions are annotated with original experimental information, gene expression data, and confidence scores. All data in DroID are freely available and can be searched, explored, and downloaded through three different interfaces, including a text based web site, a Java applet with dynamic graphing capabilities (IM Browser), and a Cytoscape plug-in. DroID is available at <url>http://www.droidb.org</url>.</p

Constructing non-stationary Dynamic Bayesian Networks with a flexible lag choosing mechanism

<p>Abstract</p> <p>Background</p> <p>Dynamic Bayesian Networks (DBNs) are widely used in regulatory network structure inference with gene expression data. Current methods assumed that the underlying stochastic processes that generate the gene expression data are stationary. The assumption is not realistic in certain applications where the intrinsic regulatory networks are subject to changes for adapting to internal or external stimuli.</p> <p>Results</p> <p>In this paper we investigate a novel non-stationary DBNs method with a potential regulator detection technique and a flexible lag choosing mechanism. We apply the approach for the gene regulatory network inference on three non-stationary time series data. For the Macrophages and Arabidopsis data sets with the reference networks, our method shows better network structure prediction accuracy. For the Drosophila data set, our approach converges faster and shows a better prediction accuracy on transition times. In addition, our reconstructed regulatory networks on the Drosophila data not only share a lot of similarities with the predictions of the work of other researchers but also provide many new structural information for further investigation.</p> <p>Conclusions</p> <p>Compared with recent proposed non-stationary DBNs methods, our approach has better structure prediction accuracy By detecting potential regulators, our method reduces the size of the search space, hence may speed up the convergence of MCMC sampling.</p

Evaluation of vardenafil for the treatment of subjective tinnitus: a controlled pilot study

<p>Abstract</p> <p>Background</p> <p>Vardenafil (Levitra^®) represents a potent and highly selective phosphodiesterase type 5 (PDE5) inhibitor, which is established for treatment of various diseases. There are several unpublished reports from patients stating that vardenafil has a considerable therapeutic effect on their concomitant tinnitus. This pilot study was conducted to specifically assess the effect of vardenafil in patients with chronic tinnitus.</p> <p>Methods</p> <p>This trial was based on a prospective, randomized, double-blind, placebo-controlled, parallel group design. Fourty-two consecutive subjects with mon- or binaural chronic tinnitus received 10 mg vardenafil (N = 21) or matching placebo tablets (N = 21) administered orally twice a day over a period of 12 weeks. Clinical examination and data acquisition took place at each visit: at baseline, after 4 weeks, after 12 weeks (end of treatment with study medication), and at non-medicated follow-up after 16 weeks. Assessment of clinical effectiveness was based on a standardized tinnitus questionnaire (TQ), the Short Form 36 health survey (SF-36), audiometric measurements (mode, pitch and loudness of tinnitus; auditory thresholds) and biomarkers of oxidative stress in patients' blood (malondialdehyde, protein carbonyl, homocysteine and total antioxidative status). Therapeutic efficacy was evaluated by comparison of subjective and objective parameters with baseline data between both treatment groups (ANCOVA).</p> <p>Results</p> <p>Vardenafil had no superior efficacy over placebo in the treatment of chronic tinnitus during this study. The primary efficacy criterion 'TQ total score' failed to demonstrate significant improvement compared to placebo. Subjective reports of TQ subscales and general quality of life areas (SF-36), objective audiometric examinations as well as investigated biomarkers for oxidative stress did not reveal any significant treatment effects. The safety profile was favorable and consistent with that in other vardenafil studies.</p> <p>Conclusion</p> <p>Although hypoxia and ischemia play a special role in the pathogenesis of tinnitus, the PDE5-inhibitor-induced increase of nitric oxide-mediated vasodilatation exerted no specific influence on tinnitus symptomatology. Considering the unclear risk of rarely associated hearing impairment, systemic application of vardenafil or other PDE5 inhibitors prove to be not appropriate for therapy of chronic tinnitus.</p

A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns

Metabolic Versatility and Antibacterial Metabolite Biosynthesis Are Distinguishing Genomic Features of the Fire Blight Antagonist Pantoea vagans C9-1

Smits THM, Rezzonico F, Kamber T, et al. Metabolic Versatility and Antibacterial Metabolite Biosynthesis Are Distinguishing Genomic Features of the Fire Blight Antagonist Pantoea vagans C9-1. PLoS ONE. 2011;6(7): e22247.Background: Pantoea vagans is a commercialized biological control agent used against the pome fruit bacterial disease fire blight, caused by Erwinia amylovora. Compared to other biocontrol agents, relatively little is currently known regarding Pantoea genetics. Better understanding of antagonist mechanisms of action and ecological fitness is critical to improving efficacy. Principal Findings: Genome analysis indicated two major factors contribute to biocontrol activity: competition for limiting substrates and antibacterial metabolite production. Pathways for utilization of a broad diversity of sugars and acquisition of iron were identified. Metabolism of sorbitol by P. vagans C9-1 may be a major metabolic feature in biocontrol of fire blight. Biosynthetic genes for the antibacterial peptide pantocin A were found on a chromosomal 28-kb genomic island, and for dapdiamide E on the plasmid pPag2. There was no evidence of potential virulence factors that could enable an animal or phytopathogenic lifestyle and no indication of any genetic-based biosafety risk in the antagonist. Conclusions: Identifying key determinants contributing to disease suppression allows the development of procedures to follow their expression in planta and the genome sequence contributes to rationale risk assessment regarding the use of the biocontrol strain in agricultural systems

Light regulation of metabolic pathways in fungi

Light represents a major carrier of information in nature. The molecular machineries translating its electromagnetic energy (photons) into the chemical language of cells transmit vital signals for adjustment of virtually every living organism to its habitat. Fungi react to illumination in various ways, and we found that they initiate considerable adaptations in their metabolic pathways upon growth in light or after perception of a light pulse. Alterations in response to light have predominantly been observed in carotenoid metabolism, polysaccharide and carbohydrate metabolism, fatty acid metabolism, nucleotide and nucleoside metabolism, and in regulation of production of secondary metabolites. Transcription of genes is initiated within minutes, abundance and activity of metabolic enzymes are adjusted, and subsequently, levels of metabolites are altered to cope with the harmful effects of light or to prepare for reproduction, which is dependent on light in many cases. This review aims to give an overview on metabolic pathways impacted by light and to illustrate the physiological significance of light for fungi. We provide a basis for assessment whether a given metabolic pathway might be subject to regulation by light and how these properties can be exploited for improvement of biotechnological processes

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.

Background: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.</p