Topological Small-World Organization of the Fibroblastic Reticular Cell Network Determines Lymph Node Functionality.

PLoS Biol. 2016 Jul;14(7):e1002515

Authors: Novkovic M, Onder L, Cupovic J, Abe J, Bomze D, Cremasco V, Scandella E, Stein JV, Bocharov G, Turley SJ, Ludewig B

Abstract
Fibroblastic reticular cells (FRCs) form the cellular scaffold of lymph nodes (LNs) and establish distinct microenvironmental niches to provide key molecules that drive innate and adaptive immune responses and control immune regulatory processes. Here, we have used a graph theory-based systems biology approach to determine topological properties and robustness of the LN FRC network in mice. We found that the FRC network exhibits an imprinted small-world topology that is fully regenerated within 4 wk after complete FRC ablation. Moreover, in silico perturbation analysis and in vivo validation revealed that LNs can tolerate a loss of approximately 50% of their FRCs without substantial impairment of immune cell recruitment, intranodal T cell migration, and dendritic cell-mediated activation of antiviral CD8+ T cells. Overall, our study reveals the high topological robustness of the FRC network and the critical role of the network integrity for the activation of adaptive immune responses.

PMID: 27415420 [PubMed - as supplied by publisher]

Network analysis and juvenile idiopathic arthritis (JIA): a new horizon for the understanding of disease pathogenesis and therapeutic target identification.

Pediatr Rheumatol Online J. 2016;14(1):40

Authors: Donn R, De Leonibus C, Meyer S, Stevens A

Abstract
Juvenile idiopathic arthritis (JIA) is a clinically diverse and genetically complex autoimmune disease. Currently, there is very limited understanding of the potential underlying mechanisms that result in the range of phenotypes which constitute JIA.The elucidation of the functional relevance of genetic associations with phenotypic traits is a fundamental problem that hampers the translation of genetic observations to plausible medical interventions. Genome wide association studies, and subsequent fine-mapping studies in JIA patients, have identified many genetic variants associated with disease. Such approaches rely on 'tag' single nucleotide polymorphisms (SNPs). The associated SNPs are rarely functional variants, so the extrapolation of genetic association data to the identification of biologically meaningful findings can be a protracted undertaking. Integrative genomics aims to bridge the gap between genotype and phenotype.Systems biology, principally through network analysis, is emerging as a valuable way to identify biological pathways of relevance to complex genetic diseases. This review aims to highlight recent findings in systems biology related to JIA in an attempt to assist in the understanding of JIA pathogenesis and therapeutic target identification.

PMID: 27411317 [PubMed - in process]

Overview of major molecular alterations during progression from Barrett's esophagus to esophageal adenocarcinoma.

Ann N Y Acad Sci. 2016 Jul 14;

Authors: Kalatskaya I

Abstract
Esophageal adenocarcinoma (EAC) develops in the sequential transformation of normal epithelium into metaplastic epithelium, called Barrett's esophagus (BE), then to dysplasia, and finally cancer. BE is a common condition in which normal stratified squamous epithelium of the esophagus is replaced with an intestine-like columnar epithelium, and it is the most prominent risk factor for EAC. This review aims to impartially systemize the knowledge from a large number of publications that describe the molecular and biochemical alterations occurring over this progression sequence. In order to provide an unbiased extraction of the knowledge from the literature, a text-mining methodology was used to select genes that are involved in the BE progression, with the top candidate genes found to be TP53, CDKN2A, CTNNB1, CDH1, GPX3, and NOX5. In addition, sample frequencies across analyzed patient cohorts at each stage of disease progression are summarized. All six genes are altered in the majority of EAC patients, and accumulation of alterations correlates well with the sequential progression of BE to cancer, indicating that the text-mining method is a valid approach for gene prioritization. This review discusses how, besides being cancer drivers, these genes are functionally interconnected and might collectively be considered a central hub of BE progression.

PMID: 27415609 [PubMed - as supplied by publisher]

Muscle Logic: New Knowledge Resource for Anatomy Enables Comprehensive Searches of the Literature on the Feeding Muscles of Mammals.

PLoS One. 2016;11(2):e0149102

Authors: Druzinsky RE, Balhoff JP, Crompton AW, Done J, German RZ, Haendel MA, Herrel A, Herring SW, Lapp H, Mabee PM, Muller HM, Mungall CJ, Sternberg PW, Van Auken K, Vinyard CJ, Williams SH, Wall CE

Abstract
BACKGROUND: In recent years large bibliographic databases have made much of the published literature of biology available for searches. However, the capabilities of the search engines integrated into these databases for text-based bibliographic searches are limited. To enable searches that deliver the results expected by comparative anatomists, an underlying logical structure known as an ontology is required.
DEVELOPMENT AND TESTING OF THE ONTOLOGY: Here we present the Mammalian Feeding Muscle Ontology (MFMO), a multi-species ontology focused on anatomical structures that participate in feeding and other oral/pharyngeal behaviors. A unique feature of the MFMO is that a simple, computable, definition of each muscle, which includes its attachments and innervation, is true across mammals. This construction mirrors the logical foundation of comparative anatomy and permits searches using language familiar to biologists. Further, it provides a template for muscles that will be useful in extending any anatomy ontology. The MFMO is developed to support the Feeding Experiments End-User Database Project (FEED, https://feedexp.org/), a publicly-available, online repository for physiological data collected from in vivo studies of feeding (e.g., mastication, biting, swallowing) in mammals. Currently the MFMO is integrated into FEED and also into two literature-specific implementations of Textpresso, a text-mining system that facilitates powerful searches of a corpus of scientific publications. We evaluate the MFMO by asking questions that test the ability of the ontology to return appropriate answers (competency questions). We compare the results of queries of the MFMO to results from similar searches in PubMed and Google Scholar.
RESULTS AND SIGNIFICANCE: Our tests demonstrate that the MFMO is competent to answer queries formed in the common language of comparative anatomy, but PubMed and Google Scholar are not. Overall, our results show that by incorporating anatomical ontologies into searches, an expanded and anatomically comprehensive set of results can be obtained. The broader scientific and publishing communities should consider taking up the challenge of semantically enabled search capabilities.

PMID: 26870952 [PubMed - indexed for MEDLINE]

13 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/07/14

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

8 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/07/14

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Assessment of pharmacogenomic agreement.

F1000Res. 2016;5:825

Authors: Safikhani Z, El-Hachem N, Quevedo R, Smirnov P, Goldenberg A, Juul Birkbak N, Mason C, Hatzis C, Shi L, Aerts HJ, Quackenbush J, Haibe-Kains B

Abstract
In 2013 we published an analysis demonstrating that drug response data and gene-drug associations reported in two independent large-scale pharmacogenomic screens, Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE), were inconsistent. The GDSC and CCLE investigators recently reported that their respective studies exhibit reasonable agreement and yield similar molecular predictors of drug response, seemingly contradicting our previous findings. Reanalyzing the authors' published methods and results, we found that their analysis failed to account for variability in the genomic data and more importantly compared different drug sensitivity measures from each study, which substantially deviate from our more stringent consistency assessment. Our comparison of the most updated genomic and pharmacological data from the GDSC and CCLE confirms our published findings that the measures of drug response reported by these two groups are not consistent. We believe that a principled approach to assess the reproducibility of drug sensitivity predictors is necessary before envisioning their translation into clinical settings.

PMID: 27408686 [PubMed]

Effects of SLC22A1 Polymorphisms on Metformin-Induced Reductions in Adiposity and Metformin Pharmacokinetics in Obese Children with Insulin Resistance.

J Clin Pharmacol. 2016 Jul 13;

Authors: Sam WJ, Roza O, Hon YY, Alfaro RM, Calis KA, Reynolds JC, Yanovski JA

Abstract
Steady state population pharmacokinetics of a non-commercial immediate release metformin (hydrochloride) drug product were characterized in 28 severely obese children with insulin resistance. The concentration-time profiles with double peaks were well described by a one-compartment model with two absorption sites. Mean population apparent clearance (CL/F) was 68.1 L/hr and mean apparent volume of distribution (V/F) was 28.8 L. Body weight was a covariate of CL/F and V/F. Estimated glomerular filtration rate was a significant covariate of CL/F (p<0.001). SLC22A1genotype did not significantly affect metformin pharmacokinetics. The response to 6 months of metformin treatment (HbA1c, HOMA IR, fasting insulin, and glucose changes) was not different between SLC22A1 wild type subjects and carriers of presumably low activity SLC22A1 alleles. However, SLC22A1 variant carriers had smaller reductions in percentage of total trunk fat after metformin therapy, although the percentage reduction in trunk fat was small. The median % change in trunk fat was -2.20 % (-9.00 % - 0.900 %) and -1.20 % (-2.40 % - 7.30 %) for the SLC22A1 wild-type subjects and variant carriers, respectively. Future study is needed to evaluate the effects of SLC22A1 polymorphisms on metformin-mediated weight reduction in obese children. This article is protected by copyright. All rights reserved.

PMID: 27407018 [PubMed - as supplied by publisher]

A Global Health Diagnostic for Personalized Medicine in Resource-Constrained World Settings: A Simple PCR-RFLP Method for Genotyping CYP2B6 g.15582C>T and Science and Policy Relevance for Optimal Use of Antiretroviral Drug Efavirenz.

OMICS. 2015 Jun;19(6):332-8

Authors: Evans J, Swart M, Soko N, Wonkam A, Huzair F, Dandara C

Abstract
The use of pharmacogenomics (PGx) knowledge in treatment of individual patients is becoming a common phenomenon in the developed world. However, poorly resourced countries have thus far been constrained for three main reasons. First, the cost of whole genome sequencing is still considerably high in comparison to other (non-genomics) diagnostics in the developing world where both science and social dynamics create a dynamic and fragile healthcare ecosystem. Second, studies correlating genomic differences with drug pharmacokinetics and pharmacodynamics have not been consistent, and more importantly, often not indexed to impact on societal end-points, beyond clinical practice. Third, ethics regulatory frames over PGx testing require improvements based on nested accountability systems and in ways that address the user community needs. Thus, CYP2B6 is a crucial enzyme in the metabolism of antiretroviral drugs, efavirenz and nevirapine. More than 40 genetic variants have been reported, but only a few contribute to differences in plasma EFV and NVP concentrations. The most widely reported CYP2B6 variants affecting plasma drug levels include c.516G>T, c.983T>C, and to a lesser extent, g.15582C>T, which should be considered in future PGx tests. While the first two variants are easily characterized, the g.15582C>T detection has been performed primarily by sequencing, which is costly, labor intensive, and requires access to barely available expertise in the developing world. We report here on a simple, practical PCR-RFLP method with vast potentials for use in resource-constrained world regions to detect the g.15582C>T variation among South African and Cameroonian persons. The effects of CYP2B6 g.15582C>T on plasma EFV concentration were further evaluated among HIV/AIDS patients. We report no differences in the frequency of the g.15582T variant between the South African (0.08) and Cameroonian (0.06) groups, which are significantly lower than reported in Asians (0.39) and Caucasians (0.31). The g.15582C/T and T/T genotypes were associated with significantly reduced EFV levels (p=0.006). This article additionally presents the policy relevance of the PGX global health diagnostics and therefore, collectively makes an original interdisciplinary contribution to the field of integrative biology and personalized medicine in developing world. Such studies are, in fact, broadly important because resource-constrained regions exist not only in developing world but also in major geographical parts of the G20 nations and the developed countries.

PMID: 26415139 [PubMed - indexed for MEDLINE]

DBDiaSNP: An Open-Source Knowledgebase of Genetic Polymorphisms and Resistance Genes Related to Diarrheal Pathogens.

OMICS. 2015 Jun;19(6):354-60

Authors: Mehla K, Ramana J

Abstract
Diarrhea is a highly common infection among children, responsible for significant morbidity and mortality rate worldwide. After pneumonia, diarrhea remains the second leading cause of neonatal deaths. Numerous viral, bacterial, and parasitic enteric pathogens are associated with diarrhea. With increasing antibiotic resistance among enteric pathogens, there is an urgent need for global surveillance of the mutations and resistance genes primarily responsible for resistance to antibiotic treatment. Single Nucleotide Polymorphisms are important in this regard as they have a vast potential to be utilized as molecular diagnostics for gene-disease or pharmacogenomics association studies linking genotype to phenotype. DBDiaSNP is a comprehensive repository of mutations and resistance genes among various diarrheal pathogens and hosts to advance breakthroughs that will find applications from development of sequence-based diagnostic tools to drug discovery. It contains information about 946 mutations and 326 resistance genes compiled from literature and various web resources. As of March 2015, it houses various pathogen genes and the mutations responsible for antibiotic resistance. The pathogens include, for example, DEC (Diarrheagenic E.coli), Salmonella spp., Campylobacter spp., Shigella spp., Clostridium difficile, Aeromonas spp., Helicobacter pylori, Entamoeba histolytica, Vibrio cholera, and viruses. It also includes mutations from hosts (e.g., humans, pigs, others) that render them either susceptible or resistant to a certain type of diarrhea. DBDiaSNP is therefore intended as an integrated open access database for researchers and clinicians working on diarrheal diseases. Additionally, we note that the DBDiaSNP is one of the first antibiotic resistance databases for the diarrheal pathogens covering mutations and resistance genes that have clinical relevance from a broad range of pathogens and hosts. For future translational research involving integrative biology and global health, the database offers veritable potentials, particularly for developing countries and worldwide monitoring and personalized effective treatment of pathogens associated with diarrhea. The database is accessible on the public domain at http://www.juit.ac.in/attachments/dbdiasnp/ .

PMID: 25978092 [PubMed - indexed for MEDLINE]

MicroRNA gene expression signatures in long-surviving malignant pleural mesothelioma patients.

Genom Data. 2016 Sep;9:44-9

Authors: Lin RC, Kirschner MB, Cheng YY, van Zandwijk N, Reid G

Abstract
Malignant pleural mesothelioma (MPM) is a tumor originating in the mesothelium, the membrane lining the thoracic cavities, and is induced by exposure to asbestos. Australia suffers one of the world's highest rates of MPM and the incidence is yet to peak. The prognosis for patients with MPM is poor and median survival following diagnosis is 4-18 months. Currently, no or few effective therapies exist for MPM. Trials of targeted agents such as antiangiogenic agents (VEGF, EGFR) or ribonuclease inhibitors (ranpirnase) largely failed to show efficacy in MPM Tsao et al. (2009) [1]. A recent study, however, showed that cisplatin/pemetrexed + bevacizumab (a recombinant humanized monoclonal antibody that inhibit VEGF) treatment has a survival benefit of 2.7 months Zalcman et al. (2016) [2]. It remains to be seen if this targeted therapy will be accepted as a new standard for MPM. Thus the unmet needs of MPM patients remain very pronounced and almost every patient will be confronted with drug resistance and recurrence of disease. We have identified unique gene signatures associated with prolonged survival in mesothelioma patients undergoing radical surgery (EPP, extrapleural pneumonectomy), as well as patients who underwent palliative surgery (pleurectomy/decortication). In addition to data published in Molecular Oncology, 2015;9:715-26 (GSE59180) Kirschner et al. (2015) , we describe here additional data using a system-based approach that support our previous observations. This data provides a resource to further explore microRNA dynamics in MPM.

PMID: 27408810 [PubMed]

A Systems-Level Analysis of the Peripheral Nerve Intrinsic Axonal Growth Program.

Neuron. 2016 Mar 2;89(5):956-70

Authors: Chandran V, Coppola G, Nawabi H, Omura T, Versano R, Huebner EA, Zhang A, Costigan M, Yekkirala A, Barrett L, Blesch A, Michaelevski I, Davis-Turak J, Gao F, Langfelder P, Horvath S, He Z, Benowitz L, Fainzilber M, Tuszynski M, Woolf CJ, Geschwind DH

Abstract
The regenerative capacity of the injured CNS in adult mammals is severely limited, yet axons in the peripheral nervous system (PNS) regrow, albeit to a limited extent, after injury. We reasoned that coordinate regulation of gene expression in injured neurons involving multiple pathways was central to PNS regenerative capacity. To provide a framework for revealing pathways involved in PNS axon regrowth after injury, we applied a comprehensive systems biology approach, starting with gene expression profiling of dorsal root ganglia (DRGs) combined with multi-level bioinformatic analyses and experimental validation of network predictions. We used this rubric to identify a drug that accelerates DRG neurite outgrowth in vitro and optic nerve outgrowth in vivo by inducing elements of the identified network. The work provides a functional genomics foundation for understanding neural repair and proof of the power of such approaches in tackling complex problems in nervous system biology.

PMID: 26898779 [PubMed - indexed for MEDLINE]

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.

Nucleic Acids Res. 2016 Jan 4;44(D1):D515-22

Authors: King ZA, Lu J, Dräger A, Miller P, Federowicz S, Lerman JA, Ebrahim A, Palsson BO, Lewis NE

Abstract
Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.

PMID: 26476456 [PubMed - indexed for MEDLINE]

Renal systems biology of patients with systemic inflammatory response syndrome.

Kidney Int. 2015 Oct;88(4):804-14

Authors: Tsalik EL, Willig LK, Rice BJ, van Velkinburgh JC, Mohney RP, McDunn JE, Dinwiddie DL, Miller NA, Mayer ES, Glickman SW, Jaehne AK, Glew RH, Sopori ML, Otero RM, Harrod KS, Cairns CB, Fowler VG, Rivers EP, Woods CW, Kingsmore SF, Langley RJ

Abstract
A systems biology approach was used to comprehensively examine the impact of renal disease and hemodialysis (HD) on patient response during critical illness. To achieve this, we examined the metabolome, proteome, and transcriptome of 150 patients with critical illness, stratified by renal function. Quantification of plasma metabolites indicated greater change as renal function declined, with the greatest derangements in patients receiving chronic HD. Specifically, 6 uremic retention molecules, 17 other protein catabolites, 7 modified nucleosides, and 7 pentose phosphate sugars increased as renal function declined, consistent with decreased excretion or increased catabolism of amino acids and ribonucleotides. Similarly, the proteome showed increased levels of low-molecular-weight proteins and acute-phase reactants. The transcriptome revealed a broad-based decrease in mRNA levels among patients on HD. Systems integration revealed an unrecognized association between plasma RNASE1 and several RNA catabolites and modified nucleosides. Further, allantoin, N1-methyl-4-pyridone-3-carboxamide, and N-acetylaspartate were inversely correlated with the majority of significantly downregulated genes. Thus, renal function broadly affected the plasma metabolome, proteome, and peripheral blood transcriptome during critical illness; changes were not effectively mitigated by hemodialysis. These studies allude to several novel mechanisms whereby renal dysfunction contributes to critical illness.

PMID: 25993322 [PubMed - indexed for MEDLINE]

dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins.

Nucleic Acids Res. 2016 Jan 4;44(D1):D435-46

Authors: Huang KY, Su MG, Kao HJ, Hsieh YC, Jhong JH, Cheng KH, Huang HD, Lee TY

Abstract
Owing to the importance of the post-translational modifications (PTMs) of proteins in regulating biological processes, the dbPTM (http://dbPTM.mbc.nctu.edu.tw/) was developed as a comprehensive database of experimentally verified PTMs from several databases with annotations of potential PTMs for all UniProtKB protein entries. For this 10th anniversary of dbPTM, the updated resource provides not only a comprehensive dataset of experimentally verified PTMs, supported by the literature, but also an integrative interface for accessing all available databases and tools that are associated with PTM analysis. As well as collecting experimental PTM data from 14 public databases, this update manually curates over 12 000 modified peptides, including the emerging S-nitrosylation, S-glutathionylation and succinylation, from approximately 500 research articles, which were retrieved by text mining. As the number of available PTM prediction methods increases, this work compiles a non-homologous benchmark dataset to evaluate the predictive power of online PTM prediction tools. An increasing interest in the structural investigation of PTM substrate sites motivated the mapping of all experimental PTM peptides to protein entries of Protein Data Bank (PDB) based on database identifier and sequence identity, which enables users to examine spatially neighboring amino acids, solvent-accessible surface area and side-chain orientations for PTM substrate sites on tertiary structures. Since drug binding in PDB is annotated, this update identified over 1100 PTM sites that are associated with drug binding. The update also integrates metabolic pathways and protein-protein interactions to support the PTM network analysis for a group of proteins. Finally, the web interface is redesigned and enhanced to facilitate access to this resource.

PMID: 26578568 [PubMed - indexed for MEDLINE]

14 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/07/13

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

7 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/07/13

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Comparing Drug Images and Repurposing Drugs with BioGPS and FLAPdock: The Thymidylate Synthase Case.

ChemMedChem. 2016 Jul 12;

Authors: Siragusa L, Luciani R, Borsari C, Ferrari S, Costi MP, Cruciani G, Spyrakis F

Abstract
Repurposing and repositioning drugs has become a frequently pursued and successful strategy in the current era, as new chemical entities are increasingly difficult to find and get approved. Herein we report an integrated BioGPS/FLAPdock pipeline for rapid and effective off-target identification and drug repurposing. Our method is based on the structural and chemical properties of protein binding sites, that is, the ligand image, encoded in the GRID molecular interaction fields (MIFs). Protein similarity is disclosed through the BioGPS algorithm by measuring the pockets' overlap according to which pockets are clustered. Co-crystallized and known ligands can be cross-docked among similar targets, selected for subsequent in vitro binding experiments, and possibly improved for inhibitory potency. We used human thymidylate synthase (TS) as a test case and searched the entire RCSB Protein Data Bank (PDB) for similar target pockets. We chose casein kinase IIα as a control and tested a series of its inhibitors against the TS template. Ellagic acid and apigenin were identified as TS inhibitors, and various flavonoids were selected and synthesized in a second-round selection. The compounds were demonstrated to be active in the low-micromolar range.

PMID: 27404817 [PubMed - as supplied by publisher]

Screening a Commercial Library of Pharmacologically Active Small Molecules Against Staphylococcus aureus Biofilms.

Antimicrob Agents Chemother. 2016 Jul 11;

Authors: Torres NS, Abercrombie JJ, Srinivasan A, Lopez-Ribot JL, Ramasubramanian AK, Leung KP

Abstract
It is now well established that bacterial infections are often associated with biofilm phenotypes that demonstrate increased resistance to common antimicrobials. Further, due to the collective attrition of new-antibiotic development programs by the pharmaceutical industries, drug repurposing is an attractive alternative. In this work, we have screened 1,280 existing commercially available drugs in the Prestwick Chemical Library, some with previously unknown antimicrobial activity, against Staphylococcus aureus, one of the commonly encountered causative pathogen of burn and wound infections. From the primary screen of the entire Prestwick Chemical Library at a fixed concentration of 10μM, 104 drugs were found to be effective against planktonic S. aureus, and not surprisingly, these were mostly antimicrobials and antiseptics. The activity of 18 selected repurposing candidates, that is, drugs that show antimicrobial activity that are not already considered antimicrobials, observed in the primary screen was confirmed in dose response experiments. Finally, a subset of nine of these drug candidates was tested against pre-formed biofilms of S. aureus We found that three of these drugs, Niclosamide, Carmofur, and Auranofin, possessed antimicrobial activity against pre-formed biofilms, making them attractive candidates for repurposing as novel anti-biofilm therapies.

PMID: 27401577 [PubMed - as supplied by publisher]

FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki.

Database (Oxford). 2016;2016

Authors: Abugessaisa I, Shimoji H, Sahin S, Kondo A, Harshbarger J, Lizio M, Hayashizaki Y, Carninci P, FANTOM consortium, Forrest A, Kasukawa T, Kawaji H

Abstract
The Functional Annotation of the Mammalian Genome project (FANTOM5) mapped transcription start sites (TSSs) and measured their activities in a diverse range of biological samples. The FANTOM5 project generated a large data set; including detailed information about the profiled samples, the uncovered TSSs at high base-pair resolution on the genome, their transcriptional initiation activities, and further information of transcriptional regulation. Data sets to explore transcriptome in individual cellular states encoded in the mammalian genomes have been enriched by a series of additional analysis, based on the raw experimental data, along with the progress of the research activities. To make the heterogeneous data set accessible and useful for investigators, we developed a web-based database called Semantic catalog of Samples, Transcription initiation And Regulators (SSTAR). SSTAR utilizes the open source wiki software MediaWiki along with the Semantic MediaWiki (SMW) extension, which provides flexibility to model, store, and display a series of data sets produced during the course of the FANTOM5 project. Our use of SMW demonstrates the utility of the framework for dissemination of large-scale analysis results. SSTAR is a case study in handling biological data generated from a large-scale research project in terms of maintenance and growth alongside research activities.Database URL: http://fantom.gsc.riken.jp/5/sstar/.

PMID: 27402679 [PubMed - in process]