Enhancement of COPD biological networks using a web-based collaboration interface

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks.

[1]  Ashraf Elamin,et al.  A 7-month cigarette smoke inhalation study in C57BL/6 mice demonstrates reduced lung inflammation and emphysema following smoking cessation or aerosol exposure from a prototypic modified risk tobacco product. , 2015, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[2]  Diana Boraschi,et al.  MafB is a downstream target of the IL-10/STAT3 signaling pathway, involved in the regulation of macrophage de-activation. , 2014, Biochimica et biophysica acta.

[3]  P. Krammer,et al.  IFN-gamma represses IL-4 expression via IRF-1 and IRF-2. , 2002, Immunity.

[4]  Julio Saez-Rodriguez,et al.  Crowdsourcing Network Inference: The DREAM Predictive Signaling Network Challenge , 2011, Science Signaling.

[5]  Russell P Bowler,et al.  Cigarette smoke impairs clearance of apoptotic cells through oxidant-dependent activation of RhoA. , 2009, American journal of respiratory and critical care medicine.

[6]  Jennifer Park,et al.  A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue , 2011, BMC Systems Biology.

[7]  Ki Moon Bang,et al.  Airflow obstruction attributable to work in industry and occupation among U.S. race/ethnic groups: a study of NHANES III data. , 2004, American journal of industrial medicine.

[8]  Gert Folkerts,et al.  Effect of Cigarette Smoke Extract on Dendritic Cells and Their Impact on T-Cell Proliferation , 2009, PloS one.

[9]  Manuel C. Peitsch,et al.  In vitro systems toxicology approach to investigate the effects of repeated cigarette smoke exposure on human buccal and gingival organotypic epithelial tissue cultures , 2014, Toxicology mechanisms and methods.

[10]  A. Bierhaus,et al.  Modulation of Macrophage Efferocytosis in Inflammation , 2011, Front. Immun..

[11]  Yang Xiang,et al.  Quantification of biological network perturbations for mechanistic insight and diagnostics using two-layer causal models , 2014, BMC Bioinformatics.

[12]  David Galas,et al.  Gene expression networks in COPD: microRNA and mRNA regulation , 2011, Thorax.

[13]  Peter A. Ward,et al.  Neutrophil Chemotactic Activity and C5a Following Systemic Activation of Complement in Rats , 1997, Inflammation.

[14]  Ajay K. Royyuru,et al.  Industrial methodology for process verification in research (IMPROVER): toward systems biology verification , 2012, Bioinform..

[15]  Yi Zheng,et al.  Cdc42 regulates neutrophil migration via crosstalk between WASp, CD11b, and microtubules. , 2012, Blood.

[16]  Manuel C. Peitsch,et al.  Construction of a Computable Network Model of Tissue Repair and Angiogenesis in the Lung , 2013 .

[17]  J. W. Winchester,et al.  Regional anomalies in chronic obstructive pulmonary disease; comparison with acid air pollution particulate characteristics , 1989, Archives of environmental contamination and toxicology.

[18]  Manuel C. Peitsch,et al.  Systematic Verification of Upstream Regulators of a Computable Cellular Proliferation Network Model on Non-Diseased Lung Cells Using a Dedicated Dataset , 2013, Bioinformatics and biology insights.

[19]  C. Funk,et al.  Prostaglandins and leukotrienes: advances in eicosanoid biology. , 2001, Science.

[20]  R. Crystal,et al.  Cigarette smoking reprograms apical junctional complex molecular architecture in the human airway epithelium in vivo , 2011, Cellular and Molecular Life Sciences.

[21]  Francesco Ferrari,et al.  The Vitamin D3/Hox-A10 Pathway Supports MafB Function during the Monocyte Differentiation of Human CD34+ Hemopoietic Progenitors1 , 2008, The Journal of Immunology.

[22]  Julia Hoeng,et al.  A network-based approach to quantifying the impact of biologically active substances. , 2012, Drug discovery today.

[23]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[24]  D. Mosher,et al.  IL-5 induces suspended eosinophils to undergo unique global reorganization associated with priming. , 2014, American journal of respiratory cell and molecular biology.

[25]  Jennifer Park,et al.  Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems , 2015, Database J. Biol. Databases Curation.

[26]  R. Crystal,et al.  Variability in small airway epithelial gene expression among normal smokers. , 2008, Chest.

[27]  N. Kohno,et al.  Levels of Surfactant Proteins A and D and KL-6 Are Elevated in the Induced Sputum of Chronic Obstructive Pulmonary Disease Patients: A Sequential Sputum Analysis , 2011, Respiration.

[28]  S. Venkatesan,et al.  Cholesterol is obligatory for polarization and chemotaxis but not for endocytosis and associated signaling from chemoattractant receptors in human neutrophils. , 2008, Journal of biomedical science.

[29]  Manuel C. Peitsch,et al.  A Modular Cell-Type Focused Inflammatory Process Network Model for Non-Diseased Pulmonary Tissue , 2013, Bioinformatics and biology insights.

[30]  Julia Hoeng,et al.  A 28-day rat inhalation study with an integrated molecular toxicology endpoint demonstrates reduced exposure effects for a prototypic modified risk tobacco product compared with conventional cigarettes. , 2014, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[31]  G. Joos,et al.  Chronic Obstructive Pulmonary Disease 1 New insights into the immunology of chronic obstructive pulmonary disease , 2011 .

[32]  Charles N. Serhan,et al.  Resolvin E1 and protectin D1 activate inflammation-resolution programmes , 2007, Nature.

[33]  Alvar Agusti,et al.  Immunologic aspects of chronic obstructive pulmonary disease. , 2009, The New England journal of medicine.

[34]  Marcel Geertz,et al.  The Response of Human Nasal and Bronchial Organotypic Tissue Cultures to Repeated Whole Cigarette Smoke Exposure , 2014, International journal of toxicology.

[35]  B. Fischer,et al.  Pathogenic triad in COPD: oxidative stress, protease–antiprotease imbalance, and inflammation , 2011, International journal of chronic obstructive pulmonary disease.

[36]  Myriam Gorospe,et al.  Calorie Restriction Promotes Mammalian Cell Survival by Inducing the SIRT1 Deacetylase , 2004, Science.

[37]  Tohru Sakamoto,et al.  The search for common pathways underlying asthma and COPD , 2013, International journal of chronic obstructive pulmonary disease.

[38]  Ahmet Akin,et al.  Obstructive airway diseases in women exposed to biomass smoke. , 2005, Environmental research.

[39]  M. Peitsch,et al.  Verification of systems biology research in the age of collaborative competition , 2011, Nature Biotechnology.

[40]  B. Ma,et al.  Role of CCR5 in IFN-gamma-induced and cigarette smoke-induced emphysema. , 2005, The Journal of clinical investigation.

[41]  J. Barendregt,et al.  Global burden of disease , 1997, The Lancet.

[42]  Josep Roca,et al.  A Systems Biology Approach Identifies Molecular Networks Defining Skeletal Muscle Abnormalities in Chronic Obstructive Pulmonary Disease , 2011, PLoS Comput. Biol..

[43]  Hugh R. Brady,et al.  Cutting Edge: Lipoxins Rapidly Stimulate Nonphlogistic Phagocytosis of Apoptotic Neutrophils by Monocyte-Derived Macrophages1 , 2000, The Journal of Immunology.

[44]  Qing Lan,et al.  Improvement in household stoves and risk of chronic obstructive pulmonary disease in Xuanwei, China: retrospective cohort study , 2005, BMJ : British Medical Journal.

[45]  D. Postma,et al.  Chronic obstructive pulmonary disease. , 2002, Clinical evidence.

[46]  P. Roe,et al.  Pulmonary disease , 1991 .

[47]  Charles N. Serhan,et al.  Resolvin E1 Selectively Interacts with Leukotriene B4 Receptor BLT1 and ChemR23 to Regulate Inflammation1 , 2007, The Journal of Immunology.

[48]  Zhanxiang Zhou,et al.  MFG-E8 and HMGB1 Are Involved in the Mechanism Underlying Alcohol-Induced Impairment of Macrophage Efferocytosis , 2013, Molecular Medicine.

[49]  Delin Chen,et al.  Mammalian SIRT1 Represses Forkhead Transcription Factors , 2004, Cell.

[50]  J. Curtis,et al.  CC chemokine receptor 5 and CXC chemokine receptor 6 expression by lung CD8+ cells correlates with chronic obstructive pulmonary disease severity. , 2007, The American journal of pathology.

[51]  Ronald G. Crystal,et al.  Smoking-Dependent Reprogramming of Alveolar Macrophage Polarization: Implication for Pathogenesis of Chronic Obstructive Pulmonary Disease1 , 2009, The Journal of Immunology.

[52]  Jeanne Kowalski,et al.  Egr-2 and Egr-3 are negative regulators of T cell activation , 2005, Nature Immunology.

[53]  Alan D. Lopez.  THE GLOBAL BURDEN OF DISEASE 1990-2020 , 2001 .

[54]  Manuel C. Peitsch,et al.  Construction of a computable cell proliferation network focused on non-diseased lung cells , 2011, BMC Systems Biology.

[55]  S. Shapiro,et al.  The macrophage in chronic obstructive pulmonary disease. , 1999, American journal of respiratory and critical care medicine.

[56]  Jennifer Park,et al.  Reputation-Based Collaborative Network Biology , 2015, Pacific Symposium on Biocomputing.

[57]  Susumu Goto,et al.  Data, information, knowledge and principle: back to metabolism in KEGG , 2013, Nucleic Acids Res..

[58]  Takao Shimizu,et al.  The Lipoxin Receptor ALX: Potent Ligand-Specific and Stereoselective Actions in Vivo , 2006, Pharmacological Reviews.

[59]  Hidde Ploegh,et al.  Acetylation of the C terminus of Ku70 by CBP and PCAF controls Bax-mediated apoptosis. , 2004, Molecular cell.

[60]  P. Barnes,et al.  Chronic obstructive pulmonary disease • 12: New treatments for COPD , 2003, Thorax.

[61]  David A. Drubin,et al.  Toxicopanomics: Applications of Genomics, Transcriptomics, Proteomics, and Lipidomics in Predictive Mechanistic Toxicology , 2014 .

[62]  Fabrizio Montecucco,et al.  CCL3 (MIP-1alpha) induces in vitro migration of GM-CSF-primed human neutrophils via CCR5-dependent activation of ERK 1/2. , 2005, Cellular signalling.

[63]  S. Hodge,et al.  Smoking alters alveolar macrophage recognition and phagocytic ability: implications in chronic obstructive pulmonary disease. , 2007, American journal of respiratory cell and molecular biology.

[64]  Manuel C. Peitsch,et al.  Construction of a Computable Network Model for DNA Damage, Autophagy, Cell Death, and Senescence , 2013, Bioinformatics and biology insights.

[65]  Jordi Villà-Freixa,et al.  Knowledge management for systems biology a general and visually driven framework applied to translational medicine , 2011, BMC Systems Biology.

[66]  Oluwaseun Ojo,et al.  Pathological changes in the COPD lung mesenchyme--novel lessons learned from in vitro and in vivo studies. , 2014, Pulmonary pharmacology & therapeutics.

[67]  Mario Lauria,et al.  Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge , 2013, Bioinform..

[68]  K. Mayer,et al.  Acute Lung Injury: How Macrophages Orchestrate Resolution of Inflammation and Tissue Repair , 2011, Front. Immun..

[69]  Raquel Norel,et al.  On Crowd-verification of Biological Networks , 2013, Bioinformatics and biology insights.

[70]  Hongwei Yao,et al.  SIRT1 protects against emphysema via FOXO3-mediated reduction of premature senescence in mice. , 2012, The Journal of clinical investigation.

[71]  Yan Li,et al.  A cigarette component acrolein induces accelerated senescence in human diploid fibroblast IMR-90 cells , 2013, Biogerontology.

[72]  Julia Hoeng,et al.  Quantitative assessment of biological impact using transcriptomic data and mechanistic network models. , 2013, Toxicology and applied pharmacology.

[73]  Natalie L. Catlett,et al.  Reverse causal reasoning: applying qualitative causal knowledge to the interpretation of high-throughput data , 2013, BMC Bioinformatics.