Introduction to the Plant Metabolic Network: 18 Databases and Omics-Level Tools for Analysis and Discovery kate dreher The Carnegie Institution for Science Stanford, CA (CIMMYT, Mexico)

Free access to high quality, curated data promotes beneficial research on plant metabolism  Plants provide crucial benefits to humanity and the ecosystem  A better understanding of plant metabolism may contribute to: More nutritious foods More pest-resistant plants More stress-tolerant crops Higher photosynthetic capacity and higher yield in agricultural and biofuel crops New pharmaceutical sources... many more applications  These efforts benefit from access to high quality plant metabolism data

Plant Metabolic Network goals  Transform published results into data-rich metabolic pathways  Create and deploy improved methods for predicting enzyme function and metabolic capacity using plant genome sequences  Facilitate data analysis  Support research, breeding, and education  Provide public resources : PlantCyc AraCyc 16 additional species-specific databases

Plant Metabolic Network collaborators  SRI International – BioCyc project Provide Pathway Tools Software Maintain and update MetaCyc  Other collaborators / contributors include: MaizeGDB GoFORSYS TAIR SoyBase Sol Genomics Network (SGN) / Boyce Thompson Institute Gramene MedicCyc / Nobel Foundation PlantMetabolomics group... and more SoyBase Editorial Board Community Submissions

17 PMN species are phylogenetically and "functionally" diverse Eudicots Cereals Basal land plants Basal land plants Green alga Major crops Model species Legume Woody and herbaceous species Annuals and perennials C3 and C4 species

PlantCyc provides access to important pathways not found in species-specific databases  PlantCyc contains over 1000 pathways and information from over 400 plant species 1050 pathways 1050 pathways 477 pathways (average) 477 pathways (average)

PlantCyc provides access to numerous specialized metabolic pathways  Many PlantCyc-specific metabolic pathways produce or break-down specialized ("secondary") metabolites  Many of the enzymes in these pathways have experimental evidence Caffeine biosynthesis I (Caffea arabica) Morphine biosynthesis (Papaver somniferum) Taxol biosynthesis (cancer drug) (Taxus brevifolia) Raspberry ketone biosynthesis (Rubus idaeus) Vicianin bioactivation (defense compound) (Vicia sativa) Alliin degradation (garlic odor) (Allium sativum)

Species-specific databases require predictions Annotated Genome e.g. Populus trichocarpa PathoLogic Software Reference Pathway Database (MetaCyc) Reactions Pathways compounds Gene products genes Pathway/Genome Database (PoplarCyc) E2P2

The PMN predicts enzyme functions from sequenced proteomes To improve enzyme functional predictions:  A high-confidence Reference Protein Sequence Database was built RPSD 2.0 contains 34,269 enzymes and 82,216 non-enzymes  The Ensemble Enzyme Prediction Pipeline (E2P2) uses the RPSD to predict functions based on protein sequence E2P2 can predict reactions that are not fully defined in the EC system by incorporating MetaCyc reaction IDs

Pathway predictions are refined through a SAVI pipeline Annotated Genome e.g. Populus trichocarpa PathoLogic Software Reference Pathway Database (MetaCyc) Reactions Pathways compounds Gene products genes Pathway/Genome Database (PoplarCyc) E2P2 SAVI Validated – Publicly Released Pathway/Genome Database (PoplarCyc)

SAVI pipeline  Decision rules and criteria for each pathway are generated by curators  The Semi-automated validation / incorporation pipeline uses the rules to: Identify pathways with curated experimental evidence* Bring in “Ubiquitous Plant Pathways” that were not predicted  Calvin cycle, glycolysis, etc. Remove predicted non-plant / non-PMN pathways  Glycogen biosynthesis (non-plant)  Proteolysis (not small molecule metabolism) Check key reactions and expected phylogenetic range to automatically assess many other predicted pathways Highlight pathways that require manual validation

Expert input welcome!!  To submit data, report an error, volunteer to validate, or ask a question Send an Use our feedback form: Meet with me at the end of the workshop Schedule an individual meeting with me at PAG

Community gratitude  We thank you publicly!  Together, we can make valuable, high quality databases

The PMN databases provide data and tools for analysis  Information, curated summaries, high quality predictions, and experimentally supported information about: Pathways Enzymes Reactions Compounds  Tools General and specific searches Comparative analysis tools BLAST against enzymes in the PMN or the RPSD

OMICs-level data analysis

Data analysis with the Metabolic Map / Omics Viewer  Display experimental data on a metabolic map Data types:  Genes - transcriptomics  Enzymes – proteomics  Reactions - fluxomics  Compounds – metabolomics Data inputs:  Single or multiple values for each object  Absolute or relative values gene IDs relative expression levels at different timepoints

Visualizing quantitative data

input file color gradient data columns type of data scale relative or absolute data display options

Easily identify altered pathways

Navigate to items of interest on the metabolic map

Working with Groups  Opportunities Create custom data sets Explore experimental results Perform enrichment analyses Share data  Requires free registration

Generate custom datasets

Create groups from searches

modify content paint on map compare to other groups export to Excel share with others

Plant metabolic NETWORKING  Please use our data  Please use our tools  Please come explore our new species databases coming in 2014  Please help us to improve our databases!  Please contact us if we can be of any help!

PMN Acknowledgements Curator: - kate dreher Post-docs: - Lee Chae - Ricardo Nilo Poyanco - Chuan Wang Interns - Ashley Joseph Tech Team Members: -Bob Muller - Garret Huntress Rhee Lab Members: - Flavia Bossi - Hye-in Nam - Taehyong Kim - Meng Xu - Jim Guo - Jue Fan - Caryn Johansen Peifen Zhang (Director and curator) Sue Rhee (PI) Collaborators: SRI - Peter Karp - Ron Caspi - Hartmut Foerster - Suzanne Paley - SRI Tech Team MaizeGDB - Mary Schaeffer - Lisa Harper - Jack Gardiner - Taner Sen ChlamyCyc - Patrick May - Dirk Walther - Lukas Mueller (SGN) - Rex Nelson (Soybase) - Gramene and MedicCyc PMN Alumni: - A. S. Karthikeyan (curator) - Christophe Tissier (curator) - Hartmut Foerster (curator) - Eva Huala (co-PI) - Tam Tran (intern) - Varun Dwaraka (intern) - Damian Priamurskiy (intern) - Ricardo Leitao (intern) - Michael Ahn (intern) - Purva Karia (intern) - Anuradha Pujar (SGN curator) Tech Team Alumni - Anjo Chi - Cynthia Lee - Tom Meyer - Larry Ploetz - Shanker Singh - Bill Nelson - Vanessa Kirkup - Chris Wilks - Raymond Chetty

 Please use our data  Please use our tools  Sue Rhee (PI) Peifen Zhang (Director) We're here to help...