The Eli and Edythe L. Broad Institute A Collaboration of Massachusetts Institute of Technology, Harvard University and affiliated Hospitals, and Whitehead.

Slides:



Advertisements
Similar presentations
SRI International Bioinformatics 1 A BRG Biofuels Metabolic Engineering Project Bioinformatics Research Group SRI International
Advertisements

Introduction to Steady State Metabolic Modeling Concepts Flux Balance Analysis Applications Predicting knockout phenotypes Quantitative Flux Prediction.
Instantiation of Generic Reactions by Markus Krummenacker Q
Metabolism Collection of biochemical rxns within a cell Metabolic pathways –Sequence of rxns –Each step catalyzed by a different enzyme Enzymes of a pathway.
Metabolic Pathways Several steps Oxidations paired with reductions Specific enzymes for each step Multiple ways to “enter” or “exit” pathway Allows links.
ATP (adenosine triphosphate) is a nucleoside triphosphate used in cells as a coenzyme. It is often called the "molecular unit of currency" of intracellular.
CELL RESPIRATION.
Darwinian Genomics Csaba Pal Biological Research Center Szeged, Hungary.
CHAPTER 14 Glucose Utilization and Biosynthesis –Harnessing energy from glucose via glycolysis –Fermentation under anaerobic conditions –Synthesis of glucose.
Prediction of Therapeutic microRNA based on the Human Metabolic Network Ming Wu, Christina Chan Bioinformatics Advance Access Published January 7, 2014.
Mona Yousofshahi, Prof. Soha Hassoun Department of Computer Science Prof. Kyongbum Lee Chemical & Biological Engineering Tufts University 1.
Using Pathway-tools for phenotype- directed curation Jeremy Zucker Broad Institute of MIT and Harvard Boston University.
The Eli and Edythe L. Broad Institute A Collaboration of Massachusetts Institute of Technology, Harvard University and affiliated Hospitals, and Whitehead.
Cellular Pathways that Harvest Chemical Energy
Systems Biology Existing and future genome sequencing projects and the follow-on structural and functional analysis of complete genomes will produce an.
Experimental and computational assessment of conditionally essential genes in E. coli Chao WANG, Oct
Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae Speaker: Zhu YANG 6 th step, 2006.
陳虹瑋 國立陽明大學 生物資訊學程 Genome Engineering Lab. Genome Engineering Lab The Newest.
Prentice Hall c2002Chapter 101 Metabolism Is the Sum of Cellular Reactions Metabolism - the entire network of chemical reactions carried out by living.
Welcome to Biochemistry 432/832 Instructors: Vadim Gladyshev Lori Allison Teaching Assistant: Yun Jeong Kim Class web page :
Introduction to molecular networks Sushmita Roy BMI/CS 576 Nov 6 th, 2014.
Metabolic/Subsystem Reconstruction And Modeling. Given a “complete” set of genes… Assemble a “complete” picture of the biology of an organism? Gene products.
From Databases to Dynamics Dr. Raquell M Holmes Center for Computational Science Boston University.
Cellular Respiration continued. Review Purpose of cellular respiration is to convert ________ into _____ energy. Aerobic conditions: the pathway is glucoseATP.
1 SRI International Bioinformatics BioCyc Tutorial Peter D. Karp, Ph.D. Bioinformatics Research Group SRI International BioCyc.org EcoCyc.org,
Metabolic Model Describing Growth of Substrate Uptake By Idelfonso Arrieta Anant Kumar Upadhyayula.
Data Content of the BioCyc Databases. BioCyc Tier 1 Databases.
Lecture #23 Varying Parameters. Outline Varying a single parameter – Robustness analysis – Old core E. coli model – New core E. coli model – Literature.
Cellular Respiration AP Biology Photosynthesis….then Photosynthesis captures the sun’s energy and converts it to glucose Cellular respiration is the.
(c) The McGraw-Hill Companies, Inc.
The BioCyc Collection of Pathway/Genome Databases Alexander Shearer Bioinformatics Research Group SRI International BioCyc.org EcoCyc.org.
SRI International Bioinformatics 1 Recent Developments in Pathway Tools GMOD Workshop November ‘07 Suzanne Paley Bioinformatics Research Group SRI International.
From genomes to Pathway tools and from Pathway Tools to Metabolic Models Jeremy Zucker Broad Institute of MIT and Harvard.
Section 3: Cellular Respiration
AP Biology Ch. 9 – Cellular Respiration. Catabolic pathway Fermentation Aerobic respiration Anaerobic respiration Cellular respiration Redox reaction.
MetaCyc and AraCyc: Plant Metabolic Databases Hartmut Foerster Carnegie Institution.
Ch. 9 Cellular Respiration and Fermentation. Catabolic pathways yield energy by oxidizing organic fuels Cells break down glucose and other organic fuels.
1 SRI International Bioinformatics GO Term Integration and Curation in Pathway Tools and EcoCyc Ingrid M. Keseler Bioinformatics Research Group SRI International.
Top Four Essential TAIR Resources Debbie Alexander Metabolic Pathway Databases for Arabidopsis and Other Plants Peifen Zhang.
1 Departament of Bioengineering, University of California 2 Harvard Medical School Department of Genetics Metabolic Flux Balance Analysis and the in Silico.
SRI International Bioinformatics 1 Submitting pathway to MetaCyc Ron Caspi.
Metabolism Collection of biochemical rxns within a cell Metabolic pathways –Sequence of rxns –Each step catalyzed by a different enzyme Enzymes of a pathway.
Metabolism Is the Sum of Cellular Reactions Metabolism - the entire network of chemical reactions carried out by living cells Metabolites - small molecule.
Introduction: Acknowledgments Thanks to Department of Biotechnology (DBT), the Indo-US Science and Technology Forum (IUSSTF), University of Wisconsin-Madison.
Metabolism Enzymes Metabolism and Metabolic Pathways.
Genome Biology and Biotechnology The next frontier: Systems biology Prof. M. Zabeau Department of Plant Systems Biology Flanders Interuniversity Institute.
Introduction to biological molecular networks
Metabolic pathway alteration, regulation and control (3) Xi Wang 01/29/2013 Spring 2013 BsysE 595 Biosystems Engineering for Fuels and Chemicals.
Flexibility in energy metabolism supports hypoxia tolerance in Drosophila flight muscle: metabolomic and computational systems analysis Jacob Feala 1,2.
Cellular Respiration. What is Cellular Respiration? Cellular respiration is a catabolic pathway in which oxygen is consumed along with organic fuel. In.
1 AraCyc Metabolic Pathway Annotation. 2 AraCyc – An overview  AraCyc is a metabolic pathway database for Arabidopsis thaliana;  Computational prediction.
Lecture #19 Growth states of cells. Outline Objective functions The BOF The core E. coli model The genome-scale E. coli model Using BOF.
Reconstructing the metabolic network of a bacterium from its genome: the construction of LacplantCyc Christof Francke In silico reconstruction of the metabolic.
Catabolism – Electron Transport. Catabolism -- Overview.
National Center for Agricultural Utilization Research, USDA-ARS
SRI International Bioinformatics 1 Pathway Tools Features Available Only in the Desktop Version PathoLogic.
SRI International Bioinformatics Selected PathoLogic Refining Tasks Creation of Protein Complexes Assignment of Modified Proteins Operon Prediction.
Cellular Respiration. Metabolism The sum of all the chemical processes occurring in an organism at one time Concerned with the management of material.
Recent Developments and Future Directions in Pathway Tools Peter D. Karp SRI International.
Pathways that Harvest and Store Chemical Energy
Compiling Information and Inferring Useful Knowledge for Systems Biology by Text Mining the Literature Anália Lourenço IBB – Institute for Biotechnology.
BT8118 – Adv. Topics in Systems Biology
The Pathway Tools FBA Module
Building Metabolic Models
A Community Effort to Model the Human Microbiome
The Omics Dashboard Suzanne Paley Pathway Tools Workshop 2018
Section 3: Cellular Respiration
Overview of Microbial Pathway and Genome Databases
Overview of the Pathway Tools FBA Module
Learning Outcomes By the end of this lesson: Define respiration
Presentation transcript:

The Eli and Edythe L. Broad Institute A Collaboration of Massachusetts Institute of Technology, Harvard University and affiliated Hospitals, and Whitehead Institute for Biomedical Research Lessons learned from the Genome- scale metabolic reconstruction and curation of Neurospora crassa Jeremy Zucker Jonathan Dreyfuss Heather Hood James Galagan

Capture Metabolic Knowledge Pathway-tools/BioCyc KEGG Reactions Interactions Literature

Visualizing ‘omics Data Provide a visually intuitive, metabolic framework for interpreting large ‘omics datasets

in silico Predictions Algorithmically Interpret Expression Data in a Metabolic Context?

Example: Plasmodium Validation KO Phenotype Predictions – 90% Accuracy External Metabolite Changes – 70% Accuracy New Predictions 40 Enzymatic drug targets Experimental validation of novel target Eflux* *Colijn, C., A. Brandes, J. Zucker, et al. (2009). PLoS Comput Biol

Modeling in the Neurospora PO1 ClockVisualization and Analysis Profiling RNA-Seq ChIP-Seq Interpretation of Expression Profiling and Regulatory Network Data in a Metabolic Context – Inform Experiments

BUILDING THE MODEL

Manual reconstruction protocol Nature Protocols, Vol. 5, No. 1. (07 January 2010), pp

Automated Model SEED reconstruction pipeline Nature biotechnology, Vol. 28, No. 9. (29 September 2010), pp

Genome sequence to metabolic model PathwaysLiterature Nutrient media (Vogels) NeurosporaCyc ElementsMetadata Complexes Reactions Transporters Biomass composition

EFICAz2 predicts enzymes … Decision tree Databases HMMs FDR SVM 9934 protein sequences 1993 enzymes 1770 reactions BMC Bioinformatics 2009, 10:107

Protein Complex editor 182 reactions with isozymes or complexes 31 complexes experimentally validated through literature search 2-oxoisovalerate alpha subunit 2-oxoisovalerate beta subunit … fatty acid synthase beta subunit dehydratase fatty acid synthase alpha subunit reductase Identify multiple genes of reaction Allow curator to validate potential complexes 2-oxoisovalerate complex Present all possible combinations of complexes Fatty acid synthase complex …

Transport inference parser (TIP) 9934 free-text Protein annotations 176 transporters assigned to 97 transport reactions MFS glucose transporter ATP synthase … sucrose transporter Filter proteins for transporters Infer multimeric complex Infer substrate Infer energy-coupling mechanism … Bioinformatics (2008) 24 (13): i259-i267.

Pathologic predicts pathways 1770 enzyme- catalyzed reactions 265 Pathways … … X = #rxns in metacyc pwy Y = #rxns with enzyme evidence Z = #unique rxns in pwy P(X|Y|Z) = prob of pwy in Neurospora Science 293:2040-4, 2001.

Literature curation validates predictions … 1212 citations associated with 307 pathways 31 complexes 168 genes …

Neurospora Cellular overview

NEUROSPORACYC

New feature on Broad website

NeurosporaCyc Cellular overview

NeurosporaCyc cellular overview

Googlemaps-like zoomable interface

Highlight genes on overview

NeurosporaCyc Omics Viewer

Omics data mapped onto metabolism

Omics data mapped onto Genome

DEBUGGING THE BUG

The problem with EC numbers Reaction classNumber of reactions neurospora (metacyc) Balanced normal reactions993 (4585) Generic reactions198 (688) Protein modification reactions:82 (469) Reactions with instanceless classes:80 (228) Generic redox reactions36 (212) Polymeric reactions24 (91) Polymerization pathway reactions11 (17)

Generic Reactions

instance of ?

Protein Modification reactions

Reactions with instanceless classes

Solution: Instantiate classes

Generic Redox reactions

Polymeric reactions

Polymerization Pathway reactions

Solution: Instantiate polymerization steps POLYMER-INST-Fatty-Acids-C16 + coenzyme A + ATP -> POLYMER-INST-Saturated-Fatty-Acyl-CoA- C16 + diphosphate + AMP + H+ POLYMER-INST-Fatty-Acids-C14 + coenzyme A + ATP -> POLYMER-INST-Saturated-Fatty-Acyl-CoA- C14 + diphosphate + AMP + H+ … POLYMER-INST-Fatty-Acids-C0 + coenzyme A + ATP -> POLYMER-INST-Saturated-Fatty-Acyl-CoA- C0 + diphosphate + AMP + H+

What happens when the metabolic network is infeasible? Add a “reaction” with the smallest number of reactants and products that results in a feasible model minimize card(r) subject to Sv + r = 0 l ≤ v ≤ u

Fast Automated Reconstruction of Metabolism Input: – EFICAz probabilities for each reaction – Biomass components – Experimental growth / no growth phenotypes in different nutrient conditions – Gene essentiality – Manual curation of pathways Output: – Metabolic network of MetaCyc reactions maximally consistent with input

VALIDATING THE MODEL WITH IN SILICO KNOCKOUT PREDICTIONS

Neurospora phenotypes for validation Neurospora e-Compendium – 29 Mutants essential on minimal media – Non-essential on supplemental media PO1 Phenotype Collection – 79 non-essential KOs under minimal media – Additional phenotypes are observed. Used FBA with Neurospora model to simulate gene knockouts in minimal medium

Neurospora phenotype prediction results Predicted EssentialNon-Essential ObservedEssential22 (TN)7 (FP) Non-Essential14 (FN)65 (TP) PrecisionTP/ (TP+FP) 90% RecallTP/ (TP+FN) 82% SpecificityTN/ (TP+FP) 76% Accuracy(TP+TN)/ (TP+TN+FP+FN) 81%

Comparison of model organisms under minimal media Yeast (iND750) 1 E.Coli (iAF1260) 2 Neurospora Viable Predicted/ Observed 439/455=96%993/1022=97%65/79=82% Essential Predicted/ Observed 35/109=32%159/238=67%22/29=76% Overall accuracy84%91%81% [1] Genome Res : [2] Molecular Systems Biology :121

MODELING THE EFFECT OF OXYGEN LIMITATION ON XYLOSE FERMENTATION

Biofuels from Neurospora? Growing interest for obtaining biofuels from fungi Neurospora crassa has more cellulytic enzymes than Trichoderma reesei N. crassa can degrade cellulose and hemicellulose to ethanol [Rao83] Simultaneous saccharification and fermentation means that N. crassa is a possible candidate for consolidated bioprocessing Xylose Ethanol

Effects of Oxygen limitation on Xylose fermentation in Neurospora crassa Zhang, Z., Qu, Y., Zhang, X., Lin, J., March Effects of oxygen limitation on xylose fermentation, intracellular metabolites, and key enzymes of Neurospora crassa as Applied biochemistry and biotechnology 145 (1-3), Xylose Pyruvate TCAEthanol RespirationFermentation Glycolysis Oxygen level (mmol/L*g) Ethanol conversion (%) Low O 2 Intermediate O 2 High O 2

Pentose phosphate Aerobic respiration Fermentation TCA Cycle Model of Xylose Fermentation Xylose Oxygen Ethanol ATP Two paths from xylose to xylitol

Pentose phosphate Aerobic respiration Fermentation TCA Cycle Oxygen=5 ATP=16.3 NADPH Regeneration NADPH & NAD + Utilization High Oxygen NAD + Regeneration

Pentose phosphate Aerobic respiration Fermentation TCA Cycle Ethanol Low Oxygen Oxygen=0

Pentose phosphate Aerobic respiration Fermentation TCA Cycle Ethanol Intermediate Oxygen Optimal Ethanol NADPH & NAD Utilization Oxygen=0.5 ATP=2.8 NAD Regeneration NADPH Regeneration All O 2 used to regenerate NAD used in first step

Pentose phosphate Aerobic respiration Fermentation TCA Cycle Ethanol Intermediate Oxygen Optimal Ethanol NADPH & NAD Utilization Oxygen=0.5 ATP=2.8 NAD Regeneration NADPH Regeneration All O 2 used to regenerate NAD used in first step Bottleneck Pyruvate decarboxylase Improve NADH enzyme

USING E-FLUX TO PREDICT DRUG TARGETS BY INTEGRATING EXPRESSION DATA WITH FBA

E-Flux explanation

Application of E-flux to TB

Next Steps Annotation: use phenotype predictions to improve model NeurosporaCyc: Use E-flux to interpret the effect of clock genetic regulatory program on metabolism. Validation: add additional phenotypes

Acknowledgements Neurospora P01 Project Heather Hood Jonathan Dreyfuss James Galagan SRI Peter Karp Mario Latendresse Markus Krumenacker Ingrid Kesseler Tomer Altman Suzanne Paley Ron Caspi Mike Travers

Fast Automated Reconstruction of Metabolism (FARM) Gene Calls (Broad) Protein Complex prediction Transport predictor (TIP) Pathway prediction (Pathologic) Enzyme prediction (EFICAz) Literature curation (CAP) Nutrient media (Vogels) NeurosporaCyc

C C Fast Automated Reconstruction of Metabolism (FARM) 846 Reactions 640 Metabolites 564 Genes EFICAz predictions Pathway predictions Nutrient conditions Biomass composition Protein complexes Transport