Integrated Biology. A Pathway-centric Approach to Multiomics Research Powered by GeneSpring Analytics

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1 Integrated Biology A Pathway-centric Approach to Multiomics Research Powered by GeneSpring Analytics Sham Naal Market Manager, Academia and Research Europe March 13, 2013

2 Looking at results from individual disciplines describes only part of the picture. Interpretive value comes from integrating diverse measurements within their biological context 3

3 Agilent Overview Electronic LTM Measurement Revenue* $2.7B Chemical Analysis LTM Revenue* $1.1B Life Sciences LTM Revenue* $1.0B Diagnostics

4 Agilent Overview Electronic LTM Measurement Revenue* $2.7B Chemical Analysis LTM Revenue* $1.1B Life Sciences LTM Revenue* $1.0B Diagnostics

5 Life Life Sciences Products and Applications Liquid Chromatographs Liquid Chromatographs Mass Spectrometry Software and Lab Informatics Capillary Electrophoresis Micro-fluidics and bio-analyzers Robotics (sample prep automation) Bio-reagents PCR and QPC instruments Microarrays (DNA and R&A) Consumables Services and Support Sample collection Sample Prep Life Sciences Business Models Sample Intro Sample Labeling Separation Detection Detection Data to Report Conversion Products, Systems and Integrated Solutions Enabling Customer s Workflows

6 Omics DNA RNA Protein Metabolite What is the common coordinate that enables integrative analysis? 7

7 Common Reference: Pathway Representation Gene A R HO R Gene B Gene X 8

8 Omics DNA RNA Protein Metabolite 9

9 Omics DNA RNA Protein Metabolite 11

10 Omics Biology DNA RNA Protein Metabolite DNA RNA Protein Metabolite DNA RNA Protein Metabolite RNA Protein Metabolite Protein DNA RNA Protein Metabolite 12

11 Omics DNA RNA Protein Metabolite DNA RNA Protein Metabolite DNA RNA Protein Metabolite RNA Protein Metabolite Protein DNA RNA Protein Metabolite 13

12 Omics DNA RNA Protein Metabolite DNA RNA Protein Metabolite DNA RNA Protein Metabolite RNA Protein Metabolite Protein DNA RNA Protein Metabolite 14

13 The Challenge DNA RNA Protein Metabolite DNA RNA Protein Metabolite DNA RNA Protein Metabolite DNA RNA Protein Metabolite RNA Protein Metabolite RNA Protein Metabolite DNA DNA RNA Protein Metabolite RNA Protein Metabolite Protein Protein DNA RNA DNA RNA Protein Metabolite Protein Metabolite -Omics Biological Processes 15

14 Common Reference: Pathway Representation Gene A R HO R Gene B Sources WikiPathways BioCyc/MetaCyc Generalized BioPax KEGG Gene X Platforms GeneSpring IPA MetaCore others. 16

15 Gene A R Gene A HO R R HO Gene B Gene A R R Gene B Gene X HO R Gene B Gene X Gene X 17

16 Gene A R HO R Gene B Gene X Identifies why the pathway is active Suggests follow-on experiments 18

17 Agilent Integrated Biology Workflows: Practically any omics technology type imaginable LC/MS GC/MS MassHunter Qual/Quant ChemStation AMDIS Microarrays Feature Extraction GeneSpring Platform Biological Pathways NGS Alignment to Reference Genome 19

18 Case Studies Study I Infectious Disease Study II Cancer Kyu Rhee Tuberculosis (Treatment) Weil / Cornell Akhilesh Pandey Chemopreventives Johns Hopkins 20

19 Pathway-informed Drug Discovery for Tuberculosis (Dr. Kyu Rhee, Weill Cornell Medical College) TB can usually be cured with a combination of firstline drugs taken for several months. Shown here are the four drugs in the standard regimen of first-line drugs and their modes of action. Also shown are the dates these four drugs were discovered all more than 40 years ago. NIAID WhatIsTB/ScientificIllustrations/Pages/firstLineIllustration.aspx 21

20 Multi-omics Workflow: Transcriptomics + Metabolomics Drug X low, mid, high LC/MS (6520 ifunnel Q-TOF) Metabolome (Label-free) GeneSpring Drug Y low, mid, high GX Microarray (Custom) Transcriptome (2-color) Corroborate known mechanisms of action Discover unknown cellular responses Drug Z low, mid, high Suggest new druggable targets. 22

21 Fold Change Example Analysis Drug X All Genes (Note increased change with dose) Low Med High Dose 23

22 Fold Change Example Analysis Drug X Genes among top 5% up-regulated in all dosages Low Med High Dose Genes among bottom 5% downregulated in all dosages 24

23 Enrichment: Find interesting pathways Down- Regulated Genes Up-Regulated Genes Pathway Database GO Database Pathway Database GO Database Enriched Pathways Enriched GO terms Enriched Pathways Enriched GO terms Pathway source: WikiPathways Enrichment: HG via GeneSpring Identifier Mapping: GeneSpring + BridgeDB 25

24 BridgeDb: Mapping Entities Onto Pathways Resolves Mapping Problem Between Databases Identifiers in omics Data Identifiers in Pathway DBs BridgeDB Pathways DB Gene ID Protein ID Metabolite ID Map entities Interactive HomoloGene Metabolite Identifiers KEGG HMDB ChEBI CAS Protein Identifiers: Swiss-Prot UniProt UniProt/TrEMBL Gene Identifiers : Entrez Gene, GenBank, Ensembl EC Number, RefSeq, UniGene, HUGO HGNC, EMBL 26 LBMSDG September 2012

25 Enrichment: Find interesting pathways Down- Regulated Genes Up-Regulated Genes Pathway Database GO Database Pathway Database GO Database Enriched Pathways Enriched GO terms Enriched Pathways Enriched GO terms Pathway source: WikiPathways Enrichment: HG via GeneSpring Identifier Mapping: GeneSpring + BridgeDB 27

26 Pathway & GO Enrichment: Drug X MOA Suggestion of secondary mechanisms Direction for further exploration DOWNREGULATED Pathway p-value (Genes) GO Term P-value Mx_Oxidative_phosphorylation_WP1680_ E-04 phospholipase C activity 3.34E-04 Mx_Peptidoglycan_biosynthesis_WP1685_ lipase activity 2.01E-04 Mx_D-Glutamine_and_Dglutamate_metabolism_WP1643_ phospholipase activity Mx_Ether_lipid_metabolism_WP1645_ Mx_Inositol_phosphate_metabolism_WP1664_ Mx_Riboflavin_metabolism_WP1696_ UPREGULATED Pathway p-value (Genes) GO Term P-value Mx_Glyoxylate_and_dicarboxylate_metabolism_W P1661_ biological regulation 9.75E regulation of biological process 7.11E-06 response to chemical stimulus 3.50E-06 response to stimulus 1.42E-05 negative regulation of biological process regulation of growth negative regulation of growth propionate catabolic process, 2-methylcitrate cycle propionate metabolic process, methylcitrate cycle regulation of metabolic process 2.97E E E E E E-04 28

27 Multi-omics Analysis: Learning more about significant genes, metabolites, paths, etc. Peptidoglycan biosynthesis Question: How can I understand what is biologically relevant about this pathway? Answer: Pathway visualization to find enriched paths 29

28 Pathway: Peptidoglycan Biosynthesis Significantly downregulated in all dosages 30

29 Pathway: Peptidoglycan Biosynthesis Enriched Genes Significantly downregulated in all dosages 31

30 Pathway: Peptidoglycan Biosynthesis Metabolite Changes Control vs. Drug 32

31 Pathway: Peptidoglycan Biosynthesis All Measurements Candidates for re-mining or for targeted assay Candidates for targeted proteomics 33

32 Multi-omics Workflow: Transcriptomics + Metabolomics Drug X low, mid, high LC/MS (6520 ifunnel Q-TOF) Metabolome (Label-free) GeneSpring Drug Y low, mid, high GX Microarray (Custom) Transcriptome (2-color) Corroborate known mechanisms of action Discover unknown cellular responses Drug Z low, mid, high Suggest new druggable targets. 34

33 Multi-omics Workflow: Transcriptomics + Metabolomics Targeted Proteomics Drug X low, mid, high Drug Y low, mid, high LC/MS (6520 ifunnel Q-TOF) GX Microarray (Custom) Metabolome (Label-free) Proteome (Targeted) Transcriptome (2-color) GeneSpring Corroborate known mechanisms of action Discover unknown cellular responses Drug Z low, mid, high Suggests next experiments Suggest new druggable targets. 35

34 Case Study: Looking for Evidence of Pathway Intervention to Advance the Search for New Breast Cancer Chemopreventives sirna Suhr Y-J. Nat. Rev. Cancer, 2003,

35 The Workflow: Manual GeneSpring 11.5 SpectrumMill MS IPA IPA Joint Pathway Analysis (Manual) 37

36 Keap1- Nrf2 Pathway: Transcriptome in GeneSpring Integrated Biology Control Knockdown Control SFN treated

37 Keap1- Nrf2 Pathway: Proteome in GeneSpring Integrated Biology Control Knockdown Control SFN treated

38 VC SFN NTC KD VC SFN NTC KD Western blot validation of SILAC data MCF10A MCF12A Pharmacologic Genetic Pharmacologic Genetic KEAP1 NQO1 GCLC SQSTM1 AKR1B10 AKR1C1/2 AKR1C3 * ALDH3A1 GAPDH * Candidate markers IHC validation

39 AKR1C3 Validation by immunohistochemistry VC SFN NTC KEAP1 Knockdown

40 Insights from Integrated Analysis Big Picture view Pharmacodynamic profile Key Pathways from SFN Exploration Xenobiotic metabolism and antioxidants Glutathione metabolism Carbohydrate metabolism and NAD(P)H generation Identify activated pathways including known cytoprotective pathways Identify off-target behaviors, and theorize as to mechanism (or even toxicity) (e.g. SFN does more than inhibit KEAP1) 42

41 Integrated Biology: Enabling pathway-based multi-omic discovery-to-validation MULTI-OMIC PATHWAY-CENTRIC 43

42 Feedback Loop: Multi Omics Discovery Targeted proteomics Multi-omic Analysis in GeneSpring Spectrum Mill or Skyline for targeted proteomics 44

43 Pathway-directed re-mining of data or designing the next experiment Propose new experiments based on pathway analysis 1. Re-mine originally acquired (or legacy) untargeted metabolomics data based on pathway analysis create db 2. Design new experiments (metabolite, protein or genes) based on pathway results interpretation Build custom metabolite database PCDL Spectrum Mill Export protein IDs to Peptide Selector for targeted MS/MS earray Multi-Omic Analysis in GeneSpring Upload select pathway genes for custom microarray or NGS design

44 46 GeneSpring: Combining Modules for Multi-Omics Capabilities

45 Integrated Biology 48

46 Thank you! Acknowledgements Kyu Rhee Cornell Weil Medical College Akhilesh Pandey Johns Hopkins University Learn more! New Agilent IB Website: Agilent Technologies Steve Fischer, Metabolomics & Proteomics Theo Sana, Metabolomics/IB Chris Miller & Alex Apfel, Proteomics/IB Allan Kuchinsky, Agilent Labs Leo Bonilla, Life Sciences Marketing 49