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WP6.2 Genomics and microbiology

WP6.2 Genomics and microbiology. Overall Objective: To demonstrate how the integration of pathway biology and host/ pathogen genomics can contribute to clinical diagnosis and treatment of infected patients. 4th Consortium Meeting, Madrid, 21 st -22 nd Feb, 2005.

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WP6.2 Genomics and microbiology

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  1. WP6.2 Genomics and microbiology Overall Objective: To demonstrate how the integration of pathway biology and host/ pathogen genomics can contribute to clinical diagnosis and treatment of infected patients 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  2. WP6.2 Genomics and microbiology Framework for project Interferon Pathway(s) • A family of related proteins (, , , & ) whose binding to specific receptors • leads to the activation of signal transduction pathways. • Activation of these pathways results in a defined gene expression and: • An anti-infective state state, • Increased antigen presentation, • Development of a TH1 response, • Inhibition of cellular proliferation Interferon is a key Inflammatory mediator with a number of notable therapeutic applications 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  3. WP6.2 Genomics and microbiology Medical Informatics Bioinformatics Viral Immunomodulatory Interactions SNPs / Phenotype DB Anthony Brooks Ifna Ifnb GTI/ A Angulo/ M Alba Omim Protein Interaction Network GTI/ All M Alba/ B Oliva P Microarray/ Proteomic patient profiling Micro RNA M Reczko GTI P Clinical / pathway database Secretome M Zazzi/ Informa/ ARCA GTI T Imaging Erik Meijering/ Wiro Niessen Regulatory Network A Sousa Pereira 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  4. WP6.2 Genomics and microbiology Year 1: Parallel activities Year 2: Target ID and validation 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  5. WP6.2 Genomics and microbiology Efforts towards characterisation of IFN signalling pathway and identification of potential/ novel genes/ proteins of (clinical) interest 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  6. WP6.2 Genomics and microbiology Objective 1: Identification of a core set of interferon Gamma-related genes/ proteins around which initial studies of WP6.2 will focus UEDIN ‘novel’ Genes (300 – 400) 263 Core interferon gamma response genes identified Human/Mouse, Variety of cell types Literature Review Ingenuity Pathway Assist Core Literature ‘novel’ genes 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  7. WP6.2 Genomics and microbiology Literature Review (PubMed) Several Hundred gene/ gene products Subjective/ Objective Reduction and assortment Antigen Presentation Jak/ STAT IRF(s) Apoptosis Ingenuity Pathway Assist Further novel signalling interactions identified Core genes for analysis Annotation (inc hand-curated protein-protein interaction data) 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  8. WP6.2 Genomics and microbiology Literature ‘novel’ Genes (100 – 1000?) UEDIN ‘novel’ Genes (300 – 400) Core Actual number of genes involved in interferon response likely to be >1000 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  9. WP6.2 Genomics and microbiology • Primary aim of database: • Web accessible repository of interferon signalling-related information • Incorporate data generated in course of InfoBiomed project • Future aims (Year 2): • Incorporate further signalling pathway information (type 1 interferon, TLR • TNF-alpha) selected via objective criteria. • To integrate database with GPX database and allow • rapid focussed analyses of microarray/ proteomic data • 2) Output signalling pathway information from database in XML • (SBML-like) allowing modelling/ simulation 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  10. WP6.2 Genomics and microbiology How is the core gene information to be used? 3. Protein Interaction Network Analysis Objective: To characterise protein-protein interactions: 1. Within host interferon signalling pathway and 2. Between virus and host proteins 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  11. WP6.2 Genomics and microbiology How is the core gene information to be used? 3. Protein Interaction Network Analysis Methods/ approaches: Algorithm development: Prediction of protein interactions whose homologs defined as interacting in DIP/ BIND etc Construction of a protein interaction network for each of proteins from virus and host Host-Virus Network development Description of the relationships between host and viral proteins A matrix of protein-protein similarities will be produced Root protein identification and functional analysis Potential targets for in vitro and in vivo validation will be obtained 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  12. WP6.2 Genomics and microbiology How is the core gene information to be used? 3. Protein Interaction Network Analysis From host perspective • 71 identifiers from the IRF ‘module’ of the interferon pathway (~1/4 of known UEDIN curated pathways) inputted into Protein interaction databases (DIP, STRING, BIND and GRIB) • Result: • > 5000 interactions across human, mouse and rat identified and annotated 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  13. WP6.2 Genomics and microbiology 3. Protein Interaction Network Analysis cont. From Virus/ Host perspective (M. Alba, B. Oliva) Application of PIANA to identification of virus/ host protein interaction COG/ KOG STRING • - Further classification of novel proteins into • existing clusters • New cluster assignment following further • sequence alignment • Clusters of orthologous groups of proteins • Clustering by protein seq comparison • ‘Hand’curation into clusters • Annotation by Genbank/ sequence (PSI Blast) Microarray data/ BLAST comparisons PIANA Species X (Yeast) interacting pairs Gene COG code x x 1 2 3 x y z Human orthologs found x x Human CMV Based on theory of interologs: Walhout, A. J. et al. Protein interaction mapping in C. elegans using proteins involved in vulval development. Science 287, 116-22 (2000). 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  14. WP6.2 Genomics and microbiology 3. Protein Interaction Network Analysis cont. From Virus/ Host perspective (M. Alba, B. Oliva) HCMV protein Human Proteins Cyclin-dependent kinases regulatory subunit 1 (CKS-1) Cyclin-dependent kinases regulatory subunit 2 (CKS-2) Nucleoprotein interactor 1; NPI-1 [Homo sapiens] Deoxyuridine 5'-triphosphate nucleotidohydrolase (dUTPase) (dUTP pyrophosphatase) Importin alpha-2 subunit (KPNA2) (SRP1-alpha) (RAG cohort protein 1) Ingenuity Importin alpha-4 subunit (KPNA4) (Qip1 protein) Importin alpha-7 subunit (Karyopherin alpha-6) Sperm associated antigen 6 (SPAG6) [Homo sapiens] 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  15. WP6.2 Genomics and microbiology 3. Protein Interaction Network Analysis cont. Kumar KP, McBride KM, Weaver BK, Dingwall C, Reich NC.Regulated nuclear-cytoplasmic localization of interferon regulatory factor 3, a subunit of double-stranded RNA-activated factor 1 Mol Cell Biol 2000 Jun 1;20(11):4159-68. 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  16. WP6.2 Genomics and microbiology How is the core gene information to be used? 4. MicroRNA control of interferon gene expression Abundant class of tiny regulatory RNAs Function via: mRNA cleavage (‘High’ complementarity) &/or Translational repression (‘Low’ complementarity) Control and influence: Cell proliferation, Cell Death, differentiation etc etc. Objectives 1. Prediction of novel precursor miRNAs from genomic (Virus and Host) sequences Prediction of novel mature miRNAs from precursors 2. Prediction of novel miRNA targets 3. Experimental verification of miRNA expression/ target gene control 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  17. WP6.2 Genomics and microbiology 5. Host immunity and antiviral success prediction Incorporation of host information into Anti-Retroviral Cohort Analysis (ARCA) database • ARCA db stores clinical and HIV genome data (>3000 patients) from a large multicentric • observational cohort in Italy • Aim: to exploit data and derive models which predict response to treatment • Can information relating to host (immune response) be incorporated into DB and models? 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  18. WP6.2 Genomics and microbiology 5. Host immunity and antiviral success prediction Potential result (post InfoBiomed) Improved clinical outcome with therapeutic regimes based on knowledge of viral and human genotype Tasks HLA typing Chemokine/ KIR Incorporation of Data into DB and analysis General Schedule: Genotyping Year 1 DB and analysis Year 2 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  19. WP6.2 Genomics and microbiology 5. Host immunity and antiviral success prediction Objective 1: Sample selection 230 patients identified from a single clinical centre: - Multiple samples available - Full treatment history and clinical follow-up available (mean 5.7 years) - HIV genotypic data available at multiple time points 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  20. WP6.2 Genomics and microbiology 5. Host immunity and antiviral success prediction Objective 1: Sample selection Aim: To reduce number of patients to a manageable cohort of 100 Options for final selection: - Those 100 with lowest nadir CD4 counts Most challenging subset for antiretroviral treatment (most interesting to know if host factors play a role in response to treatment in this context) - Those 50 with lowest vs. those 50 with highest nadir CD4 counts Host factors (e. g. HLA) may have contributed to different course of infection • Those 50 with best vs. those 50 with worst outcome Definition of ‘outcome’ not straightforward (e. g. adjusting for treatment, duration of infection often unknown) • Virus Infection Status e.g. ICMV: Prevalence High in cohort (>90%), may measure replicating vs latent, CMV disease v.low due to HAART. e.g. II Hepatitis G virus: Potential role in protecting against HIV progression 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  21. WP6.2 Genomics and microbiology 6. HIV clinical data storage and phenotype database model • Phenotype data handling is poorly developed • Increasingly major hurdle for post-genomics analysis • Standards desperately needed • Teams/components now in place to create a solution 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  22. WP6.2 Genomics and microbiology 6. HIV clinical data storage and phenotype database model Objective 1: Data source identification and acquisition - Gender - Age - MHC haplotype - Other host genotype data (e. g. MDR) - CD4 T cell count (multiple data) - HIV RNA load (multiple data) - Treatment regimen (multiple data) - HIV genotype (multiple data) - Viral coinfections • CMV? (but prevalence very high in adults and CMV disease quite rare in the HAART era) • GBV-C / hepatitis G virus? (claimed to protect from HIV disease but possibly a consequence of larger availability of CD4 T cells where it can replicate) 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  23. WP6.2 Genomics and microbiology Milestones and Objectives Year 1 Year 2 Interpretation and target ID Data acquisition, compilation and curation Protein to protein Interactions miRNA Gene Expression Genotyping/ Infection status Target Validation 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  24. WP6.2 Genomics and microbiology 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

  25. WP6.2 Genomics and microbiology Ingenuity Pathway Analysis Ingenuity ‘Knowledge Base’: >1m curated direct physical and functional interactions (from published peer-reviewed papers) Input genes ‘Relevant’ sub-networks of interactions formed (enriched for focus genes) • Networks ranked according to a score based on • number of focus genes and • size of network 4th Consortium Meeting, Madrid, 21st-22nd Feb, 2005

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