Construction of a computable cell proliferation network focused on non-diseased lung cells

<p>Abstract</p> <p>Background</p> <p>Critical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work.</p> <p>Results</p> <p>To further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data.</p> <p>Conclusions</p> <p>To the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.</p

The Role of Hypoxia in 2-Butoxyethanol–Induced Hemangiosarcoma

To understand the molecular mechanisms underlying compound-induced hemangiosarcomas in mice, and therefore, their human relevance, a systems biology approach was undertaken using transcriptomics and Causal Network Modeling from mice treated with 2-butoxyethanol (2-BE). 2-BE is a hemolytic agent that induces hemangiosarcomas in mice. We hypothesized that the hemolysis induced by 2-BE would result in local tissue hypoxia, a well-documented trigger for endothelial cell proliferation leading to hemangiosarcoma. Gene expression data from bone marrow (BM), liver, and spleen of mice exposed to a single dose (4 h) or seven daily doses of 2-BE were used to develop a mechanistic model of hemangiosarcoma. The resulting mechanistic model confirms previous work proposing that 2-BE induces macrophage activation and inflammation in the liver. In addition, the model supports local tissue hypoxia in the liver and spleen, coupled with increased erythropoeitin signaling and erythropoiesis in the spleen and BM, and suppression of mechanisms that contribute to genomic stability, events that could be contributing factors to hemangiosarcoma formation. Finally, an immunohistochemistry method (Hypoxyprobe) demonstrated that tissue hypoxia was present in the spleen and BM. Together, the results of this study identify molecular mechanisms that initiate hemangiosarcoma, a key step in understanding safety concerns that can impact drug decision processes, and identified hypoxia as a possible contributing factor for 2-BE–induced hemangiosarcoma in mice

Phase 1 Safety and Immunogenicity Evaluation of ADMVA, a Multigenic, Modified Vaccinia Ankara-HIV-1 B'/C Candidate Vaccine

in a modified vaccinia Ankara viral vector. Sequences were derived from a prevalent circulating HIV-1 recombinant form in Yunnan, China, an area of high HIV incidence. The objective was to evaluate the safety and immunogenicity of ADMVA in human volunteers.. Two volunteers mounted antibodies that were able to neutralize clade-matched viruses.ADMVA was well-tolerated and elicited durable humoral and cellular immune responses

Crop Updates 2005 - Cereals

This session covers thirty six papers from different authors: WHEAT AGRONOMY 1. Optimum sowing time of new wheat varieties in Western Australia, Darshan Sharma, Brenda Shackley, Mohammad Amjad, Christine M. Zaicou-Kunesch and Wal Anderson, Department of Agriculture 2. Wheat varieties updated in ‘Flowering Calculator’: A model predicting flowering time, B. Shackley, D. Tennant, D. Sharma and C.M. Zaicou-Kunesch, Department of Agriculture 3. Plant populations for wheat varieties, Christine M. Zaicou-Kunesch, Wal Anderson, Darshan Sharma, Brenda Shackley and Mohammad Amjad, Department of Agriculture 4. New wheat cultivars response to fertiliser nitrogen in four major agricultural regions of Western Australia, Mohammad Amjad, Wal Anderson, Brenda Shackley, Darshan Sharma and Christine Zaicou-Kunesch, Department of Agriculture 5. Agronomic package for EGA Eagle Rock, Steve Penny, Department of Agriculture 6. Field evaluation of eastern and western wheats in large-scale farmer’s trials, Mohammad Amjad, Ben Curtis and Veronika Reck, Department of Agriculture 7. New wheat varieties for a changing environment, Richard Richards, CSIRO Plant Industry; Canberra 8. Farmers can profitably minimise exposure to frost! Garren Knell, Steve Curtin and David Sermon, ConsultAg 9. National Variety Trials, Alan Bedggood, Australian Crops Accreditation System; Horsham 10. Preharvest-sprouting tolerance of wheat in the field, T.B. Biddulph1, T.L. Setter2, J.A. Plummer1 and D.J. Mares3; 1Plant Biology; FNAS, University of Western Australia; 2Department of Agriculture, 3School of Agriculture and Wine, University of Adelaide 11. Waterlogging induces high concentration of Mn and Al in wheat genotypes in acidic soils, H. Khabaz-Saberi, T. Setter, I. Waters and G. McDonald, Department of Agriculture 12. Agronomic responses of new wheat varieties in the Northern Agricultural Region, Christine M. Zaicou-Kunesch and Wal Anderson, Department of Agriculture 13. Agronomic responses of new wheat varieties in the Central Agricultural Region of WA, Darshan Sharma, Steve Penny and Wal Anderson, Department of Agriculture 14. EGA Eagle Rock tolerance to metribuzin and its mixtures, Harmohinder Dhammu, David Nicholson and Chris Roberts, Department of Agriculture 15. Herbicide tolerance of new bread wheats, Harmohinder Dhammu1 and David Nicholson2, Department of Agriculture NUTRITION 16. The impact of fertiliser placement, timing and rates on nitrogen-use efficiency, Stephen Loss, CSBP Ltd 17. Cereals deficient in potassium are most susceptible to some leaf diseases, Ross Brennan and Kith Jayasena, Department of Agriculture 18. Responses of cereal yields to potassium fertiliser type, placement and timing, Eddy Pol, CSBP Limited 19. Sulphate of Potash, the potash of choice at seeding, Simon Teakle, United Farmers Co-operative 20. Essential disease management for successful barley production, K. Jayasena, R. Loughman, C. Beard, B. Paynter, K. Tanaka, G. Poulish and A. Smith, Department of Agriculture 21. Genotypic differences in potassium efficiency of wheat, Paul Damon and Zed Rengel, Faculty of Natural and Agricultural Sciences, University of Western Australia 22. Genotypic differences in potassium efficiency of barley, Paul Damon and Zed Rengel, Faculty of Natural and Agricultural Sciences, University of Western Australia 23. Investigating timing of nitrogen application in wheat, Darshan Sharma and Lionel Martin, Department of Agriculture, and Muresk Institute of Agriculture, Curtin University of Technology 24. Nutrient timing requirements for increased crop yields in the high rainfall cropping zone, Narelle Hill, Ron McTaggart, Dr Wal Anderson and Ray Tugwell, Department of Agriculture DISEASES 25. Integrate strategies to manage stripe rust risk, Geoff Thomas, Robert Loughman, Ciara Beard, Kith Jayasena and Manisha Shankar, Department of Agriculture 26. Effect of primary inoculum level of stripe rust on variety response in wheat, Manisha Shankar, John Majewski and Robert Loughman, Department of Agriculture 27. Disease resistance update for wheat varieties in WA, M. Shankar, J.M. Majewski, D. Foster, H. Golzar, J. Piotrowski and R. Loughman, Department of Agriculture 28. Big droplets for wheat fungicides, Rob Grima, Agronomist, Elders 29. On farm research to investigate fungicide applications to minimise leaf disease impacts in wheat, Jeff Russell and Angie Roe, Department of Agriculture, and Farm Focus Consultants PESTS 30. Rotations for nematode management, Vivien A. Vanstone, Sean J. Kelly, Helen F. Hunter and Mena C. Gilchrist, Department of Agriculture 31. Investigation into the adaqyacy of sealed farm silos in Western Australia to control phosphine-resistant Rhyzopertha dominica, C.R. Newman, Department of Agriculture 32.Insect contamination of cereal grain at harvest, Svetlana Micic and Phil Michael, Department of Agriculture 33. Phosure – Extending the life of phosphine, Gabrielle Coupland and Ern Kostas, Co-operative Bulk Handling SOIL 34. Optimum combinations of ripping depth and tine spacing for increasing wheat yield, Mohammed Hamza and Wal Anderson, Department of Agriculture 35. Hardpan penetration ability of wheat roots, Tina Botwright Acuña and Len Wade, School of Plant Biology, University of Western Australia MARKETS 36. Latin America: An emerging agricultural powerhouse, Ingrid Richardson, Food and Agribusiness Research, Rabobank; Sydne

Probabilistic Phylogenetic Inference with Insertions and Deletions

A fundamental task in sequence analysis is to calculate the probability of a multiple alignment given a phylogenetic tree relating the sequences and an evolutionary model describing how sequences change over time. However, the most widely used phylogenetic models only account for residue substitution events. We describe a probabilistic model of a multiple sequence alignment that accounts for insertion and deletion events in addition to substitutions, given a phylogenetic tree, using a rate matrix augmented by the gap character. Starting from a continuous Markov process, we construct a non-reversible generative (birth–death) evolutionary model for insertions and deletions. The model assumes that insertion and deletion events occur one residue at a time. We apply this model to phylogenetic tree inference by extending the program dnaml in phylip. Using standard benchmarking methods on simulated data and a new “concordance test” benchmark on real ribosomal RNA alignments, we show that the extended program dnamlε improves accuracy relative to the usual approach of ignoring gaps, while retaining the computational efficiency of the Felsenstein peeling algorithm

Comparative Genomic Analysis of Human Fungal Pathogens Causing Paracoccidioidomycosis

Paracoccidioides is a fungal pathogen and the cause of paracoccidioidomycosis, a health-threatening human systemic mycosis endemic to Latin America. Infection by Paracoccidioides, a dimorphic fungus in the order Onygenales, is coupled with a thermally regulated transition from a soil-dwelling filamentous form to a yeast-like pathogenic form. To better understand the genetic basis of growth and pathogenicity in Paracoccidioides, we sequenced the genomes of two strains of Paracoccidioides brasiliensis (Pb03 and Pb18) and one strain of Paracoccidioides lutzii (Pb01). These genomes range in size from 29.1 Mb to 32.9 Mb and encode 7,610 to 8,130 genes. To enable genetic studies, we mapped 94% of the P. brasiliensis Pb18 assembly onto five chromosomes. We characterized gene family content across Onygenales and related fungi, and within Paracoccidioides we found expansions of the fungal-specific kinase family FunK1. Additionally, the Onygenales have lost many genes involved in carbohydrate metabolism and fewer genes involved in protein metabolism, resulting in a higher ratio of proteases to carbohydrate active enzymes in the Onygenales than their relatives. To determine if gene content correlated with growth on different substrates, we screened the non-pathogenic onygenale Uncinocarpus reesii, which has orthologs for 91% of Paracoccidioides metabolic genes, for growth on 190 carbon sources. U. reesii showed growth on a limited range of carbohydrates, primarily basic plant sugars and cell wall components; this suggests that Onygenales, including dimorphic fungi, can degrade cellulosic plant material in the soil. In addition, U. reesii grew on gelatin and a wide range of dipeptides and amino acids, indicating a preference for proteinaceous growth substrates over carbohydrates, which may enable these fungi to also degrade animal biomass. These capabilities for degrading plant and animal substrates suggest a duality in lifestyle that could enable pathogenic species of Onygenales to transfer from soil to animal hosts.National Institute of Allergy and Infectious Diseases (U.S.)National Institutes of Health. Department of Health and Human Services (contract HHSN266200400001C)National Institutes of Health. Department of Health and Human Services(contract HHSN2722009000018C)Brazil. National Council for Scientific and Technological Developmen

Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio