Transcript Effects of oxygen limitation on E-flux model of xylose fermentation is

Lessons learned from the Genomescale metabolic reconstruction and
curation of
Neurospora crassa
Jeremy Zucker
Jonathan Dreyfuss
Heather Hood
James Galagan
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
Capture Metabolic Knowledge
Pathway-tools/BioCyc
• Reactions
• Interactions
• Literature
KEGG
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
Eflux*
Validation
• KO Phenotype Predictions – 90% Accuracy
• External Metabolite Changes – 70% Accuracy
New Predictions
• 40 Enzymatic drug targets
• Experimental validation of novel targe
*Colijn, C., A. Brandes, J. Zucker, et al. (2009). PLoS Comput Biol
Modeling in the Neurospora PO1
Clock
Profiling
RNA-Seq
Visualization
and Analysis
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. 93-121.
Automated Model SEED
reconstruction pipeline
Nature biotechnology, Vol. 28, No. 9. (29 September 2010), pp. 977-982
Genome sequence to metabolic model
Elements
Pathways
Literature
Metadata
Nutrient
media
(Vogels)
Reactions
Complexes
NeurosporaCyc
Transporters
Biomass
composition
EFICAz2 predicts enzymes
Databases
1993 enzymes
1770 reactions
HMMs
FDR
SVM
BMC Bioinformatics 2009, 10:107
Decision tree
9934 protein
sequences
…
Protein Complex editor
182 reactions with
isozymes or complexes
• 2-oxoisovalerate alpha subunit
• 2-oxoisovalerate beta subunit
Identify multiple genes
of reaction
Present all possible
combinations of
complexes
31 complexes
experimentally
validated through
literature search
2-oxoisovalerate
complex
…
• fatty acid synthase beta
subunit dehydratase
• fatty acid synthase alpha
subunit reductase
Allow curator to validate
potential complexes
…
Fatty acid synthase
complex
Transport inference parser (TIP)
9934 free-text
Protein annotations
Filter proteins for
transporters
176 transporters assigned
to
97 transport reactions
Infer multimeric complex
• MFS glucose transporter
• ATP synthase
…
• sucrose transporter
Infer substrate
…
Infer energy-coupling
mechanism
Bioinformatics (2008) 24 (13): i259-i267.
Pathologic predicts pathways
1770 enzymecatalyzed
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
Highlight genes on overview
Highlight genes on overview
NeurosporaCyc Omics Viewer
Omics data mapped onto metabolism
Omics data mapped onto metabolism
Omics data mapped onto metabolism
Omics data mapped onto Genome
Omics data mapped onto Genome
Omics data mapped onto Genome
DEBUGGING THE BUG
The problem with EC numbers
Reaction class
Number of reactions
neurospora (metacyc)
Balanced normal reactions
993 (4585)
Generic reactions
198 (688)
Protein modification reactions:
82 (469)
Reactions with instanceless classes:
80 (228)
Generic redox reactions
36 (212)
Polymeric reactions
24 (91)
Polymerization pathway reactions
11 (17)
Generic Reactions
3.6.1.42 instance of 3.6.1.6?
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-CoAC16 + diphosphate + AMP + H+
• POLYMER-INST-Fatty-Acids-C14 + coenzyme A +
ATP -> POLYMER-INST-Saturated-Fatty-Acyl-CoAC14 + diphosphate + AMP + H+
• …
• POLYMER-INST-Fatty-Acids-C0 + coenzyme A +
ATP -> POLYMER-INST-Saturated-Fatty-Acyl-CoAC0 + 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
Observed
Essential
Non-Essential
Essential
22 (TN)
7 (FP)
Non-Essential
14 (FN)
65 (TP)
Precision
TP/
(TP+FP)
90%
Recall
TP/
(TP+FN)
82%
Specificity
TN/
(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 accuracy
84%
91%
81%
[1] Genome Res. 2004. 14: 1298-1309
[2] Molecular Systems Biology 2007 3:121
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
Ethanol production vs Oxygen level
Xylose
Glycolysis
Pyruvate
Respiration
TCA
Fermentation
Ethanol conversion (%)
70
Intermediate O2
60
50
40
30
20
Low O2
10
Ethanol
High O2
0
0
2
4
6
8
10
12
14
Oxygen level (mmol/L*g)
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.
Pentose phosphate
Xylose
Two paths from
xylose to xylitol
Model of Xylose
Fermentation
Aerobic respiration
Fermentation
Oxygen
Ethanol
TCA Cycle
ATP
Pentose phosphate
High
Oxygen
NADPH
Regeneration
NADPH &
NAD+
Utilization
Aerobic respiration
Fermentation
TCA Cycle
Oxygen=5
NAD+
Regeneration
ATP=16.3
Pentose phosphate
Low
Oxygen
Aerobic respiration
Fermentation
Ethanol
TCA Cycle
Oxygen=0
Pentose phosphate
Intermediate
Oxygen
NADPH
Regeneration
Optimal
Ethanol
NADPH &
NAD
Utilization
Aerobic respiration
Fermentation
Oxygen=0.5
Ethanol
TCA Cycle
NAD
Regeneration
ATP=2.8
All O2 used to
regenerate
NAD used in
first step
Pentose phosphate
NADPH
Regeneration
Improve NADH
enzyme
Intermediate
Oxygen
Optimal
Ethanol
NADPH &
NAD
Utilization
Bottleneck
Pyruvate
decarboxylase
Aerobic respiration
Fermentation
Oxygen=0.5
Ethanol
TCA Cycle
NAD
Regeneration
ATP=2.8
All O2 used to
regenerate
NAD used in
first step
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
SRI
Peter Karp
Mario Latendresse
Markus Krumenacker
Ingrid Kesseler
Tomer Altman
Suzanne Paley
Ron Caspi
Mike Travers
Neurospora P01 Project
Heather Hood
Jonathan Dreyfuss
James Galagan
Fast Automated Reconstruction of Metabolism
(FARM)
Gene
Calls
(Broad)
Protein
Complex
prediction
Enzyme
prediction
(EFICAz)
Pathway
prediction
(Pathologic)
Nutrient
media
(Vogels)
Literature
curation
(CAP)
NeurosporaCyc
Transport
predictor
(TIP)
Fast Automated Reconstruction of Metabolism (FARM)
• EFICAz predictions
• Pathway predictions
• Nutrient conditions
• Biomass composition
• Protein complexes
• Transport
C
846 Reactions
640 Metabolites
564 Genes