the eli and edythe l. broad institute
DESCRIPTION
Project 2: Bioinformatics and Systems Modeling. Jeremy Zucker. 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. Specific Aims of Project 2. - PowerPoint PPT PresentationTRANSCRIPT
The Eli and Edythe L. Broad InstituteA Collaboration of Massachusetts Institute of Technology, Harvard University and affiliated Hospitals, and Whitehead Institute for Biomedical Research
Project 2: Bioinformatics and Systems Modeling
Jeremy Zucker
Specific Aims of Project 2
• Finish the Neurospora assembly • Continue to improve the structural
annotation.• Curate the functional annotation, with
particular emphasis on metabolic enzymes• Develop scientific insights by using system
models to integrate data from Projects 1 and 3
New Assembly/Annotation
• NC7 =>NC10• Contigs: 251 =>20• Genes: 9826=>9734• Transcripts: 9846=>9908• Exons: 27208=>26625
• New genes: 530• Removed genes: 631 • Merged genes: 24• Split genes: 86
• 3869 UTR changes
This is the final assembly!
Heather Hood, Zehua Chen
But the annotation continues…
• RNAseq!– New genes– UTR’s– Alternative
splicing– Noncoding
RNAs
Matt Sachs, Brian Haas
From genome annotation to functional annotation
Pathway predictor
Enzyme predictor
• 267 Pathways• 1701 enzymatic reactions• 1455 compounds• 4000+ community annotations (thanks Heather and CAP participants!)• 853 literature citations
fungicyc.broadinstitute.org:1555
Summary of BioCyc Capabilities• Knowledge Management System for Neurospora
Community– Literature citations– Evidence codes
• Metabolic Pathways and gene regulation• Omics viewer
– RNA expression data– Flux predictions– Metabolite measurements– Protein expression
• Enables system modeling
From functional annotation to system modeling
Pathway predictor
Enzyme predictor
Model
Predictions
Omics data
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 2008. Effects of oxygen limitation on xylose fermentation, intracellular metabolites, and key enzymes of Neurospora crassa as3.1602. Applied biochemistry and biotechnology 145 (1-3), 39-51.
Xylose
Pyruvate
TCA Ethanol
Respiration Fermentation
Glycolysis
0 2 4 6 8 10 12 140
10
20
30
40
50
60
70
Ethanol production vs Oxygen level
Oxygen level (mmol/L*g)
Etha
nol c
onve
rsio
n (%
)Low O2
Intermediate O2
High O2
Glycolysis
Xylose degradationPentose phosphate
Aerobic respirationFermentation
TCA Cycle
Model of Xylose Fermentation
Xylose
Oxygen
Ethanol
ATP
Two paths from xylose to xylitol
Glycolysis
Xylose degradationPentose phosphate
Aerobic respirationFermentation
TCA Cycle
Oxygen=5
ATP=16.3
NADPHRegeneration
NADPH &NAD+
Utilization
HighOxygen
NAD+ Regeneration
Glycolysis
Xylose degradationPentose phosphate
Aerobic respirationFermentation
TCA CycleEthanol
LowOxygen
Oxygen=0
Glycolysis
Xylose degradationPentose phosphate
Aerobic respirationFermentation
TCA CycleEthanol
IntermediateOxygen
OptimalEthanol
NADPH &NAD
Utilization
Oxygen=0.5
ATP=2.8
NAD Regeneration
NADPHRegeneration
All O2 used to regenerate
NAD used in first step
Glycolysis
Xylose degradationPentose phosphate
Aerobic respirationFermentation
TCA CycleEthanol
IntermediateOxygen
OptimalEthanol
NADPH &NAD
Utilization
Oxygen=0.5
ATP=2.8
NAD Regeneration
NADPHRegeneration
All O2 used to regenerate
NAD used in first step
BottleneckPyruvate
decarboxylase
Improve NADHenzyme
Future Goals
• Proceed pathway by pathway with the genome-scale metabolic reconstruction
• Apply gene expression and gene regulation data under a variety of different conditions
• Focus on a short list of high confidence predictions that can be experimentally validated.
AcknowledgementsBroad InstituteJames GalaganBruce Birren
Brian HaasAaron BrandesMatt HennLi Jun MaChristina Cuomo
Carsten Russ
Broad Genome Sequencing Platform
Program ProjectHeather HoodJay DunlapKathy BorkovichLouise GlassMary-Anne NelsonMatt SachsGloria TurnerDick Weiss
Mark Farman
Many others…
Finishing TeamMargaret PriestHarindra ArachchiLynne AftuckMike Fitzgerald
Genome AssemblySarah YoungSean Sykes
Annotation TeamBrian HaasMike KoehrsenQian ZengTom Walk