High Sensitivity TSS Prediction: Estimates of Locations Where TSS Cannot Occur

Although transcription in mammalian genomes can initiate from various genomic positions (e.g., 3′UTR, coding exons, etc.), most locations on genomes are not prone to transcription initiation. It is of practical and theoretical interest to be able to estimate such collections of non-TSS locations (NTLs). The identification of large portions of NTLs can contribute to better focusing the search for TSS locations and thus contribute to promoter and gene finding. It can help in the assessment of 5′ completeness of expressed sequences, contribute to more successful experimental designs, as well as more accurate gene annotation.Using comprehensive collections of Cap Analysis of Gene Expression (CAGE) and other transcript data from mouse and human genomes, we developed a methodology that allows us, by performing computational TSS prediction with very high sensitivity, to annotate, with a high accuracy in a strand specific manner, locations of mammalian genomes that are highly unlikely to harbor transcription start sites (TSSs). The properties of the immediate genomic neighborhood of 98,682 accurately determined mouse and 113,814 human TSSs are used to determine features that distinguish genomic transcription initiation locations from those that are not likely to initiate transcription. In our algorithm we utilize various constraining properties of features identified in the upstream and downstream regions around TSSs, as well as statistical analyses of these surrounding regions.

PLAN2L: a web tool for integrated text mining and literature-based bioentity relation extraction

There is an increasing interest in using literature mining techniques to complement information extracted from annotation databases or generated by bioinformatics applications. Here we present PLAN2L, a web-based online search system that integrates text mining and information extraction techniques to access systematically information useful for analyzing genetic, cellular and molecular aspects of the plant model organism Arabidopsis thaliana. Our system facilitates a more efficient retrieval of information relevant to heterogeneous biological topics, from implications in biological relationships at the level of protein interactions and gene regulation, to sub-cellular locations of gene products and associations to cellular and developmental processes, i.e. cell cycle, flowering, root, leaf and seed development. Beyond single entities, also predefined pairs of entities can be provided as queries for which literature-derived relations together with textual evidences are returned. PLAN2L does not require registration and is freely accessible at http://zope.bioinfo.cnio.es/plan2l

Rhubarb extract partially improves mucosal integrity in chemotherapy-induced intestinal mucositis

AIM: To investigate the effects of orally gavaged aqueous rhubarb extract (RE) on 5-fluorouracil (5-FU)-induced intestinal mucositis in rats. METHODS: Female Dark Agouti rats (n = 8/group) were gavaged daily (1 mL) with water, high-dose RE (HDR; 200 mg/kg) or low-dose RE (LDR; 20mg/kg) for eight days. Intestinal mucositis was induced (day 5) with 5-FU (150 mg/kg) via intraperitoneal injection. Intestinal tissue samples were collected for myeloperoxidase (MPO) activity and histological examination. Xenopus oocytes expressing aquaporin 4 water channels were prepared to examine the effect of aqueous RE on cell volume, indicating a potential mechanism responsible for modulating net fluid absorption and secretion in the gastrointestinal tract. Statistical significance was assumed at P < 0.05 by one-way ANOVA. RESULTS: Bodyweight was significantly reduced in rats administered 5-FU compared to healthy controls (P < 0.01). Rats administered 5-FU significantly increased intestinal MPO levels (≥ 307%; P < 0.001), compared to healthy controls. However, LDR attenuated this effect in 5-FU treated rats, significantly decreasing ileal MPO activity (by 45%; P < 0.05), as compared to 5-FU controls. 5-FU significantly reduced intestinal mucosal thickness (by ≥ 29% P < 0.001) as compared to healthy controls. LDR significantly increased ileal mucosal thickness in 5-FU treated rats (19%; P < 0.05) relative to 5-FU controls. In xenopus oocytes expressing AQP4 water channels, RE selectively blocked water influx into the cell, induced by a decrease in external osmotic pressure. As water efflux was unaltered by the presence of extracellular RE, the directional flow of water across the epithelial barrier, in the presence of extracellular RE, indicated that RE may alleviate water loss across the epithelial barrier and promote intestinal health in chemotherapy-induced intestinal mucositis. CONCLUSION: In summary, low dose RE improves selected parameters of mucosal integrity and reduces ileal inflammation, manifesting from 5-FU-induced intestinal mucositis.Juliana E Bajic, Georgina L Eden, Lorrinne S Lampton, Ker Y Cheah, Kerry A Lymn, Jinxin V Pei, Andrea J Yool, Gordon S Howart

Mutations and Binding Sites of Human Transcription Factors

Mutations in any genome may lead to phenotype characteristics that determine ability of an individual to cope with adaptation to environmental challenges. In studies of human biology, among the most interesting ones are phenotype characteristics that determine responses to drug treatments, response to infections, or predisposition to specific inherited diseases. Most of the research in this field has been focused on the studies of mutation effects on the final gene products, peptides, and their alterations. Considerably less attention was given to the mutations that may affect regulatory mechanism(s) of gene expression, although these may also affect the phenotype characteristics. In this study we make a pilot analysis of mutations observed in the regulatory regions of 24,667 human RefSeq genes. Our study reveals that out of eight studied mutation types, “insertions” are the only one that in a statistically significant manner alters predicted transcription factor binding sites (TFBSs). We also find that 25 families of TFBSs have been altered by mutations in a statistically significant manner in the promoter regions we considered. Moreover, we find that the related transcription factors are, for example, prominent in processes related to intracellular signaling; cell fate; morphogenesis of organs and epithelium; development of urogenital system, epithelium, and tube; neuron fate commitment. Our study highlights the significance of studying mutations within the genes regulatory regions and opens way for further detailed investigations on this topic, particularly on the downstream affected pathways

DTi2Vec: Drug-target interaction prediction using network embedding and ensemble learning.

Drug-target interaction (DTI) prediction is a crucial step in drug discovery and repositioning as it reduces experimental validation costs if done right. Thus, developing in-silico methods to predict potential DTI has become a competitive research niche, with one of its main focuses being improving the prediction accuracy. Using machine learning (ML) models for this task, specifically network-based approaches, is effective and has shown great advantages over the other computational methods. However, ML model development involves upstream hand-crafted feature extraction and other processes that impact prediction accuracy. Thus, network-based representation learning techniques that provide automated feature extraction combined with traditional ML classifiers dealing with downstream link prediction tasks may be better-suited paradigms. Here, we present such a method, DTi2Vec, which identifies DTIs using network representation learning and ensemble learning techniques. DTi2Vec constructs the heterogeneous network, and then it automatically generates features for each drug and target using the nodes embedding technique. DTi2Vec demonstrated its ability in drug-target link prediction compared to several state-of-the-art network-based methods, using four benchmark datasets and large-scale data compiled from DrugBank. DTi2Vec showed a statistically significant increase in the prediction performances in terms of AUPR. We verified the novel predicted DTIs using several databases and scientific literature. DTi2Vec is a simple yet effective method that provides high DTI prediction performance while being scalable and efficient in computation, translating into a powerful drug repositioning tool

Database for exploration of functional context of genes implicated in ovarian cancer

Ovarian cancer (OC) is becoming the most common gynecological cancer in developed countries and the most lethal gynecological malignancy. It is also the fifth leading cause of all cancer-related deaths in women. The identification of diagnostic biomarkers and development of early detection techniques for OC largely depends on the understanding of the complex functionality and regulation of genes involved in this disease. Unfortunately, information about these OC genes is scattered throughout the literature and various databases making extraction of relevant functional information a complex task. To reduce this problem, we have developed a database dedicated to OC genes to support exploration of functional characterization and analysis of biological processes related to OC. The database contains general information about OC genes, enriched with the results of transcription regulation sequence analysis and with relevant text mining to provide insights into associations of the OC genes with other genes, metabolites, pathways and nuclear proteins. Overall, it enables exploration of relevant information for OC genes from multiple angles, making it a unique resource for OC and will serve as a useful complement to the existing public resources for those interested in OC genetics. Access is free for academic and non-profit users and database can be accessed at http://apps.sanbi.ac.za/ddoc/

Prioritizing genes of potential relevance to diseases affected by sex hormones: an example of Myasthenia Gravis

<p>Abstract</p> <p>Background</p> <p>About 5% of western populations are afflicted by autoimmune diseases many of which are affected by sex hormones. Autoimmune diseases are complex and involve many genes. Identifying these disease-associated genes contributes to development of more effective therapies. Also, association studies frequently imply genomic regions that contain disease-associated genes but fall short of pinpointing these genes. The identification of disease-associated genes has always been challenging and to date there is no universal and effective method developed.</p> <p>Results</p> <p>We have developed a method to prioritize disease-associated genes for diseases affected strongly by sex hormones. Our method uses various types of information available for the genes, but no information that directly links genes with the disease. It generates a score for each of the considered genes and ranks genes based on that score. We illustrate our method on early-onset myasthenia gravis (MG) using genes potentially controlled by estrogen and localized in a genomic segment (which contains the MHC and surrounding region) strongly associated with MG. Based on the considered genomic segment 283 genes are ranked for their relevance to MG and responsiveness to estrogen. The top three ranked genes, HLA-G, TAP2 and HLA-DRB1, are implicated in autoimmune diseases, while TAP2 is associated with SNPs characteristic for MG. Within the top 35 prioritized genes our method identifies 90% of the 10 already known MG-associated genes from the considered region without using any information that directly links genes to MG. Among the top eight genes we identified HLA-G and TUBB as new candidates. We show that our <it>ab-initio </it>approach outperforms the other methods for prioritizing disease-associated genes.</p> <p>Conclusion</p> <p>We have developed a method to prioritize disease-associated genes under the potential control of sex hormones. We demonstrate the success of this method by prioritizing the genes localized in the MHC and surrounding region and evaluating the role of these genes as potential candidates for estrogen control as well as MG. We show that our method outperforms the other methods. The method has a potential to be adapted to prioritize genes relevant to other diseases.</p

Structure-Guided Molecular Grafting Of A Complex Broadly Neutralizing Viral Epitope

Antigenic variation and viral evolution have thwarted traditional influenza vaccination strategies. The broad protection afforded by a “universal” influenza vaccine may come from immunogens that elicit humoral immune responses targeting conserved epitopes on the viral hemagglutinin (HA), such as the receptor-binding site (RBS). Here, we engineered candidate immunogens that use noncirculating, avian influenza HAs as molecular scaffolds to present the broadly neutralizing RBS epitope from historical, circulating H1 influenzas. These “resurfaced” HAs (rsHAs) remove epitopes potentially targeted by strain-specific responses in immune-experienced individuals. Through structure-guided optimization, we improved two antigenically different scaffolds to bind a diverse panel of pan-H1 and H1/H3 cross-reactive bnAbs with high affinity. Subsequent serological and single germinal center B cell analyses from murine prime-boost immunizations show that the rsHAs are both immunogenic and can augment the quality of elicited RBS-directed antibodies. Our structure-guided, RBS grafting approach provides candidate immunogens for selectively presenting a conserved viral epitope

Evidence for the progression through S-phase in the ectopic cell cycle re-entry of neurons in Alzheimer disease

Aberrant neuronal re-entry into the cell cycle is emerging as a potential pathological mechanism in Alzheimer disease (AD). However, while cyclins, cyclin dependent kinases (CDKs), and other mitotic factors are ectopically expressed in neurons, many of these proteins are also involved in other pathological and physiological processes, generating continued debate on whether such markers are truly indicative of a bona fide cell cycle process. To address this issue, here we analyzed one of the minichromosome maintenance (Mcm) proteins that plays a role in DNA replication and becomes phosphorylated by the S-phase promoting CDKs and Cdc7 during DNA synthesis. We found phosphorylated Mcm2 (pMcm2) markedly associated with neurofibrillary tangles, neuropil threads, and dystrophic neurites in AD but not in aged-matched controls. These data not only provide further evidence for cell cycle aberrations in AD, but the cytoplasmic, rather than nuclear, localization of pMcm2 suggests an abnormal cellular distribution of this important replication factor in AD that may explain resultant cell cycle stasis and consequent neuronal degeneration