An Introduction to Pathway Informatics

1. An Introduction to Pathway Informatics Yuanhua Tom Tang, Ph.D. Bioinformatics R & D Hyseq Pharmaceuticals, Inc. Sunnyvale, CA, USA Singapore National University January 10, 2002

2. Outline of the Tutorial • Introduction • KEGG and GenMAPP Tutorial • Introduction to Pathmetrics Technology and Products • Data Representation and SLIPR Standard • Expression Analysis Tools • Pathway Comparison and Pathway Database Searches • Pathway Prediction and Beyond

3. I. Introduction to Pathway Informatics

4. Pathways • It can be defined ad a modular unit of interacting molecules to fulfill a cellular function. • It is usually represented by a 2-D diagram with characteristic symbols linking the protein and non-protein entities. A circle indicates a protein or a non-protein biomolecule. An symbol in between indicates the nature of molecule-molecule interaction.

5. A Pathway Example

6. Informatics Its carrier is a set of digital codes and a language. In its manifestation in the space-time continuum, it has utility (e.g. to decrease entropy of an open system). Bioinformatics The essence of life is information (i.e. from digital code to emerging properties of biosystems.) Bioinformatics is the study of information content of life A Broad Definition of Bioinformatics

7. Pathway Database --Increasing Level of Complexity • The genome • 4 bases • 3 billion bp total • 3 billion bp/cell, identical • The proteome • 20 amino acids • ~60K genes, ~200K proteins • ~10K proteins/cell; different cells/conditions, different expressions • The pathome • ~200K reactions • ~20K pathways • ~1K pathways/cell; different cells/conditions, different expressions

8. The Need for Pathway Informatics • Good angle for data integration and representation. • Research tool for scientists. Learning tool for students. • Pharmaceutical drug discovery efforts would benefit from comprehensive pathway databases and tools. • A challenge for post-genomic era: functional discovery of ~95% genes with unknown function

9. Evolutionary Theory of Pathways--A New Field of Theoretical Studies • The most important assumption for sequence informatics is evolution • Evolution principle also applies to pathway informatics • From simple to complex • Duplication, diversifying, and modular re-use • Will provide new view toward fundamental questions toward a unified informatics theory of life • What is life? • How does new function arise? • How does evolution work? (pathway is the bridge between digital signal and emerging properties) • When does life begin (what is the initial set of pathways)?

10. List of Pathway Databases/Tools Name: KEGG (Kyoto Encyclopedia of Genes and Genomes) Web: http://www.genome.ad.jp/kegg/ Owner: Institute for Chemical Research, Kyoto University Description: KEGG is an effort to computerize current knowledge of molecular and cellular biology in terms of the information pathways that consist of interacting molecules or genes and to provide links from the gene catalogs produced by genome sequencing projects. The KEGG project is undertaken in the Bioinformatics Center, Institute for Chemical Research, Kyoto Univ. Name: PathDB Web: http://www.ncgr.org/pathdb/index.html Owner: National Center for Genomic Resources Description: PathDB™ is a functional prototype research tool for biochemistry and functional genomics. One of the key underlying philosophies of their project is to capture discrete metabolic steps. This allows them to build tools to construct metabolic networks de novo from a set of defined steps. PathDB is not simply a data repository but a system around which tools can be created for building, visualizing, and comparing metabolic networks.

11. List of Pathway Database/Tools (cont.) Name: GenMAPP (Gene MicroArray Pathway Profiler) Gladstone Institute, UCSF. GenMAPP is a computer application designed to visualize gene expression data on maps representing biological pathways and groupings of genes. The first release of GenMAPP 1.0 beta is available with over 50 mouse and human pathways. They also provide hundreds of functional groupings of genes derived from the Gene Ontology Project for the human, mouse, Drosophila, C. elegans, and yeast genomes. GenMAPP seeks collaborators in the biological community to assist in the development of a library of pathways that will encompass all known genes in the major model organisms. Name: SPAD: Signaling PAthway Database Graduate School of Genetic Resources Technology. Kyushu University. There are multiple signal transduction pathways: cascade of information from plasma membrane to nucleus in response to an extracellular stimulus in living organisms. Extracellular signal molecule binds specific intracellular receptor, and initiates the signaling pathway. Now, there is a large amount of information about the signaling pathways which control the gene expression and cellular proliferation. They have developed an integrated database SPAD to understand the overview of signaling transduction. SPAD is divided to four categories based on extracellular signal molecules (Growth factor, Cytokine, and Hormone) that initiate the intracellular signaling pathway. SPAD is compiled in order to describe information on interaction between protein and protein, protein and DNA as well as information on sequences of DNA and proteins.

12. Specific Pathway Databases • Cytokine Signaling Pathway DB. Dept. of Biochemistry. Kumamoto Univ. • The Database contains information on signaling pathways of cytokines. It is designed for researchers who work with cytokines and their receptors, and provides biochemical data and references about signaling molecules as well as ligand-receptor relationships. • EcoCyc and MetaCyc Stanford Research Institute • EcoCyc database describes the genome and the biochemical machinery of E. coli. The database contains up-to-date annotations of all E. coli genes. EcoCyc describes all known pathways of E. coli small-molecule metabolism. Each pathway and its component reactions and enzymes are annotated in rich detail, with extensive references to the biomedical literature. The Pathway Tools software provides query and visualization services. BIND (Biomolecular Interaction Network Database) UBC, Univ. of Toronto -- BIND is a database designed to store full descriptions of interactions, molecular complexes and pathways, including interactions between any two molecules composed of proteins, nucleic acids and small molecules. Chemical reactions, photochemical activation and conformational changes can also be described. Abstraction is made in such a way that graph theory methods may be applied for data mining. The database can be used to study networks of interactions, to map pathways across taxonomic branches and to generate information for kinetic simulations.

13. Industrial Companies in Path Informatics • Protein Pathways, Los Angeles, USA • Genmetrics, Inc., Silicon Valley, USA • Biobase, Braunschweig, Germany • InforMax, Bethesda, MD and AxCell Bioscience, Newtown, PA • Myriad Proteomics, Salt Lake City, Utah • CuraGen Corporation, New Haven, CT, USA

14. II. KEGG and GenMAPP Tutorial

15. KEGG Tutorial From Pathway to Genes and Molecules

16. Objectives of the KEGG Project • Pathway Database: Computerize current knowledge of molecular and cellular biology in terms of the pathway of interacting molecules or genes. • Genes Database: Maintain gene catalogs of all sequenced organisms and link each gene product to a pathway component • Ligand Database: Organize a database of all chemical compounds in living cells and link each compound to a pathway component • Pathway Tools: Develop new bioinformatics technologies for functional genomics, such as pathway comparison, pathway reconstruction, and pathway design • Professor Minoru Kanehisa is the leading scientist on the project

17. Data Representation in KEGG • Entity: a molecule or a gene • Binary relation: a relation between two entities • Network: a graph formed from a set of related entities • Pathway: metabolic pathway or regulatory pathway

20. This is the expanded

23. Drosophila melanogaster Genes According to the KEGG metabolic and regulatory pathways Pathway Search by [ EC | Cpd | Gene | Seq ][ 1st Level | 2nd Level | 3rd Level | Text Search ] • Carbohydrate Metabolism • Energy Metabolism • 2.1 Oxidative phosphorylation [PATH:dme00190] • 2.2 ATP Synthesis [PATH:dme00193] • 2.4 Carbon fixation [PATH:dme00710] • 2.5 Reductive carboxylate cycle (CO2 fixation) [PATH:dme00720] • 2.6 Methane metabolism [PATH:dme00680] • 2.7 Nitrogen metabolism [PATH:dme00910] • 2.8 Sulfur metabolism [PATH:dme00920] • Lipid Metabolism • Nucleotide Metabolism • Amino Acid Metabolism • Metabolism of Other Amino Acids • Metabolism of Complex Carbohydrates • Metabolism of Complex Lipids • Metabolism of Cofactors and Vitamins

24. Introduction to GenMAPP • GeneMicroArray Pathway Profiler by Bruce Conklin at Gladstone Institute, UCSF. • GenMAPP is a free computer application designed to visualize gene expression data on maps representing biological pathways and groupings of genes. • The main features underlying GenMAPP version 1.0 are: • Draw pathways with easy to use graphics tools • Multiple species gene databases • Color genes on MAPP files based on user-imported gene expression data

36. III. Introduction to Pathmetrics---Technology and Products Overview

37. Two Main Challenges in Post-genomic Age • Data integration: integrate diverse biological information • Scientific literature, existing body of knowledge about cellular systems • Genomic sequences • Protein sequences, motifs, and structures • Expression data from microarray, dbEST, and RT-PCR • Protein-protein interaction data from large-scale screening • Functional discovery: assign functions to the 60K+ human genes • Only 5% of known genes have assigned function • We have no clue what the function for the majority of discovered genes • Without understanding function, no drug discovery can be done in either small molecule, or in biopharmaceuticals • Will be the focus of next 20-years of life-science research

38. Data integration Establish standard for pathway curation and pathway database designing Develop pathway databases using existing knowledge in scientific literature Utilizes dbEST, microarray, and other types of expression data Utilizes genomic data such as promoter-region similarities Functional studies Assign proteins with unknown function into functional pathways Determine which cells those pathways work at what level Be much more efficient then large-scale random screening Discover the majority of pathways and protein functions Deliver many tissue-specific pathways for pharmaceutical industry Pathmetrics provides solution on

39. Technology Overview • Method of developing and curating pathway databases • Pathway search engines • Expression analysis tools • Pathway prediction engines

40. Amgen and EPO (Erythropoietin) • Brought company from near bankruptcy to largest biotech in world • EPO sales >1.3 billion yearly since 1998

41. Amgen’s Billion Dollar Drug: EPOGEN The gene was cloned 1 agaaaggaac aattattgaa taaggaatct tttcccaacc aatgtgcaat atcatcttta taagtgctaa attcccatgt gcatttgggg ctatttctgg acgcttcatt ccgatggatt atatggatta tgccagtcct gtgccaggac aagcatgctt tgacttttat ttcctgtttt aatatttgat agggcaggtc cccctattac tcttctgttt cagaatgttc tggtttttct …. 658,843 The A.A. sequence of the protein was determined MGVHECPAWLWLLLSLLSLPLGLPVLGAPPRLICDSRVLERYLLEAKEAENITTGCAEHCSLNENITVPD TKVNFYAWKRMEVGQQAVEVWQGLALLSEAVLRGQALLVNSSQPWEPLQLHVDKAVSGLRSLTTLLRALP WQKEAISPPDAASAAPLRTITADTFRKLFRVYSNFLRGKLKLYTGEACRTGDR The structure provided clues about its function The pathway showed how it treats anemia

42. EPO (erythropoeitin) pathways

43. Topics to Cover • SLIPR standard for pathway database model • Gene, pathway, and tissue expression tools • Pathway search engine • Ortholog pathway prediction • Pathway prediction user interface

44. Curating Pathway Databases • SLIPR standard for linearly representing protein pathways • Relational database design including diverse information about genes, proteins, expression, and tissues • Input in graphical format, and graphical displaying

45. Expression Analysis Tools • Gene expression • Gene expression comparison involving multiple genes • Pathway expression • Pathway expression comparison, involving multiple pathways • Tissue expression, visualizing genes, pathways • Tissue expression comparison, involving multiple tissue types

46. Pathway Search Engines • Comparing two pathways in SLIPR standard using dynamic programming algorithm • Search a query pathway against a pathway database: advance BLAST-type of searches into pathway level • Find orthologous, paralogous, and homologous pathways with alignments • Like BLAST, there are different types of searches: • Node only search • Mode only search • Node and mode search • In node only searches, one can perform: • protein-node only • non-protein node only • Protein-node and non-protein node

47. Novel Pathway Prediction Engines • Predicting orthologous pathways across different organisms • A known query pathway from some organism as query • A protein database or genomic database for the organism of interest to search against • Output is the ortholog pathway in the organism of interest • Predicting homologous pathways for an organism of interest • A known query pathway from some organism as query • A protein database or genomic database for the organism • A protein-protein correlation matrix for protein expression • Output is a collection of homologous pathways

48. IV. SLIPR Standard and Data Representation

49. Basic Concepts • Node • Protein, peptide, or non-protein biomolecules. • Mode • The nature of interaction between two nodes. Qualitative data. • Pathway • A linked list of interconnected nodes and modes. Represented in either 2-D or 1-D format. • Pathway Network • A network of cellular function and regulation involving interconnected pathways.

50. SLIRPPstandard for pathway curation • SLIPR stands for Semi-LInear Pathway Representation. Like the FastA, it is pronounced as SlipR or Slipir. • For linear comparison (homology) and display the alignments, • 2-D diagrams of pathways 1-D format. • We call the 2-D diagrams graph pathways, and the corresponding 1-D representation semi-linear pathways. • One graph pathway may be transformed into multiple semi-linear pathways. But • we prefer one-to-one mapping between the 2-D graph or the SLIPR form. The generation of 2-D graph pathways and the corresponding 1-D SLIPR form from • scientific literature is called pathway curation. • Pathways are curated by trained scientists with expertise on the relevant pathways. In addition to generating the 2-D and 1-D formats, they also have to generate a pathway • description file for each pathway they curate (pathway annotation), and a protein file • that contains all the proteins in the pathway.