Transcript CellFactoryChemE355 - University of Washington

Bacteria
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Single cells
Small size (1-5 mm)
Rapid reproduction
Genomic and genetic
capabilities
Bacterial Diversity
• 4 billion years of
evolution
• Ability to thrive in
extreme
environments
• Use nutrients
unavailable to other
organisms
• Tremendous catalytic
potential
Problem to be Solved: Waste
Minimization in the Chemical Industry
•Most of our manufactured goods
involve chemicals
•Chemical industry currently
based on chemicals derived from
petroleum
Not renewable resource
Many produce hazardous wastes
Use bacteria as the factories of the future
Bacteria as Factories
Starting materials
Harnessing Catalytic Potential of
Bacteria
Value-added products
Starting materials
• Use bacteria as self-replicating multistage
catalysts for chemical production
• Environmentally benign
• Renewable starting materials (feedstocks)
Potential Feedstocks
Characteristics: Inexpensive
Abundant
Renewable
Candidates
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Glucose C6H12O6
Methane CH4
Methanol CH3OH
Carbon dioxide/water CO2/H2O
Source
agricultural wastes
natural gas, sewage
methane
atmosphere/photosynthesis
Potential Products
• Fuels
• H2 hydrogen
• CH4 methane
• CH3CH2OH ethanol
Potential Products
• Natural products (complex synthesis)
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Vitamins
Therapeutic agents
Pigments
Amino acids
Viscosifiers
Industrial enzymes
PHAs (biodegradable plastics)
Potential Products
• Engineered products
• Starting materials for polymers (such as
rubber, plastics, fabrics)
• Specialty chemicals (chiral)
• Bulk chemicals (C4 acids)
Problem to Solve
• If bacteria are such wonderful alternatives, why
are our chemicals still made from
environmentally hazardous feedstocks?
Bacterial processes are too expensive
Nature’s Design Solutions
• Competitive advantage in natural niches
• Optimized parameters
• Low nutrients
• Defense systems
Opportunity
Redesign bacteria with industrially-valuable
parameters optimized
• Redirect metabolism to
specific products
• Increase metabolic efficiency
• Increase process efficiency
This idea has been around for 30 years, why has
the problem not been solved?
Metabolism as a Network
• Metabolism: the
complex network of
chemical reactions in
the cell
• Must redesign the
network
• Understand the
connections to achieve
end result
What’s New?
• Genomics
• Bacterial genomes small (1000 = human)
• Hundreds of bacterial genome sequences
available
• Provides the blueprint for the organism (the parts
list)
New platform for redesign
What’s New?
• Increased understanding of how new kinds
of metabolism arose
New strategies for redesign
How Build Novel Metabolic
Pathways?
• Whole metabolic pathways: no single gene or
small number of genes confer selective
advantage
• Cannot build a step at a time
Dilemma: how were entire pathways constructed
during evolution?
Modular Aspect of Metabolism
• Metabolic capabilities were built in blocks,
like puzzle pieces
Strategy:
Understand the modules and their connections
Redesign in blocks
Methanol as an Alternative
Biofeedstock
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Soluble in water
Inexpensive
Pure substrate
Bacteria that use it
well-studied
CH3OH
chemicals
Methylotrophic Bacteria
CH3OH (methanol)
O2
CO2, H2O, cells
Specified product
Approach
• Define functional
modules by
experimental and
evolutionary analysis
methanol
MEDH
MADH
CH OH
HCHO
3CH2 NH
3
cytcL
amicyanin
H4F
H4MPT
Assimilation
Dissimilation
MethyleneHCHO
H4F
Methylene H
4MPT
NADH
CO2
NADPH Methenyl NADPH
H4F
Methenyl
H4MPT
Serine
N10-Formyl H4F
cycle
N5-Formyl H4MPT
ATP
Formate
BIOMASS
C3 Compounds
Formyl MFR
Purines
NADH
fMet-tRNA
2H
x
CO2
•Manipulate modules
to optimize product
•Optimize process parameters
CO2
product
CO2
Methylobacterium extorquens AM1
•Grows on one-carbon compounds
(reducing power limited)
•Also grows on multi-carbon
compounds (ATP-limited)
•Natural habitat: leaf surfaces
•Substantial toolkit for genetic analyses
•Genome sequence available
•Whole genome microarrays available
Clover leaf print showing pink
Methylobacterium strains
Target Product: Biodegradable
Plastics
CH3OH
Biosynthesis
(assimilation)
C3
CO2
Energy metabolism
(dissimilation)
Biomass
PHA (biodegradable
plastic)
Methylotrophic Metabolic Modules
Methanol
Methanol
Oxidation
PHA
PHA
cycle
Glyoxylate
Regeneration
cycle
Formaldehyde
Serine
cycle
TCA
cycle
Methylene H4F
H4MPT-linked
C1 transfer
H4F-linked
C1 transfer
Formate
CELLS
FDH2
FDH1
CO2
FDH3
Constraints
• Understanding how the system is
integrated in time and space
• Changing how it works
Work in Progress
• Use genome-wide
techniques to assess
expression of genes
within each module
• Use metabolic modeling
to make predictions about
flow through each module
• Use labeling techniques
to measure flow through
each module
BIOMASS
CO2
Results: redesign the metabolic network to overproduce a
biodegradable plastic
Multi-tiered datasets
Metabolite pools
Xiaofeng Guo
Abundance
Average spectra for serine peak
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400
360
228
320
microarrays: mRNA
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240
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160
120
114
80
Yoko Okubo, Betsy Skovran
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174
128
40
101
184
220
242
0
100
120
140
160
180
m/z
200
220
240
256
260
Enzyme activities
Xiaofeng Guo
CH3OH
MDH
H2O, 2eH4MPT
H4 F
HCHO
Fae
spont.
H2 O
Methylene
H2 O
Methylene
CH2=H4MPT
H4F CH2=H4F
H4MPT
Serine
NAD(P)H
MtdA,
MtdB
MtdA
NADPH
CH=H4MPT
CH=H4F
H2 O
H2 O
Mch
Fch
CHO-H4MPT
CHO-H
F
H
O
4
2
H2 O
FtfL H4MPT
Fhc
H4F, ATP
HCOOH
FDHs
NADH CO2
Fluxes
Chris Marx
Steve Van Dien
Greg Crowther
2 NADPH
G6P
0.29
R5P
0
Biomass yield: 4.98
PP Pathway
0.01
NADH
F6P
E4P
-KG
0.09
0.03
Triose-P
0.04
Citrate
0.35
0
Ac-CoA
CO2
2.27
Propionyl-CoA
Butyryl-CoA
Glyoxylate Ac-CoA
3.27
Serine
Acetyl-CoA
Conversion
Pathway
1.00
FADH2
3.27
Serine Cycle
NADPH
Glycine
1.00
NADPH
0.62
2.92
Methylene-H4MPT
CO2
NADH
2 e-
Malyl-CoA
3.27
OAA
2.56
PEP
3.17
CO2
NADPH
2 e-
1.00
1.00
Malate
0
0.21
2.83
Succinate
2 NADH
Pyruvate
2-PG
TCA
Cycle
0.09
3-PG
0.35
Succ-CoA
0
0.30
Hydroxybutyryl-CoA
3.21
0.46
6.17
5.55
HCHO
3.84
Methylene-H4F
0.62
NADPH
ATP
Formate
Cell membrane
10.00
CH3OH
NADH
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4 H+ext
0.56
HCHO
2e-
PHB
CO2
NADH
2 H+ext
19.3
ATP
proteomics: proteins
Julia Vorholt group
Murray Hackett group
Global Analysis
Global analysis provides indepth information
•Transcription of all detectable genes
•Production of all detectable proteins
•Measurement of all major fluxes
•Measurement of 100s of metabolites
Involves a basic assumption, that all cells are roughly in the
same physiological state
Growing body of literature shows this is not correct
Final Phase: Study Metabolism in
Single Cells
• Metabolic studies in averaged
populations do not capture the
range of metabolic events or
heterogeneity in subpopulations
• Difficult to study multiple metabolic
parameters in single cells
Need: new technologies to study
living individual cells in real time
Single Cell Challenges
• Volume of a bacterial cell ~ fl (10-15)
• Number of DNA molecules ~2-3
• Number of mRNA molecules for a specific
gene ~10-10,000
• Total protein amount ~amoles (10-18)
• Total moles of specific metabolites ~ amoles
(10-18)
• Respiration rates ~fmol/min/cell (10-15 )
New Interdisciplinary
Approaches
• Combine
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Genomics
Computational biology
MEMS (microelectromechanical systems)
Systems integration
Nanotechnology
Microscale Life Sciences Center
University of Washington
• Center of Excellence of Genomic Sciences funded by NIH
NHGRI
• Co-directed by Mary Lidstrom and Deirdre Meldrum (EE)
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Started August 2001
Goal:
Study complex processes in individual
living cells
Chemists, biologists, engineers working
together
Microsystem-Based Devices for
Studying Single Cells
•Move, trap, image single cells (9 cell sets x 11)
•Control environment, make additions
•Measure 4 fluorescent protein fusions
•Single-cell proteomics
•Measure substrate-dependent O2 uptake (phosphorescence
sensor)
Multi-parameter high throughput
analysis at the single-cell level,
leading to understanding of
metabolic networks
N. Dovichi group (Chemistry); L. Burgess group (Chemistry); D. Meldrum group (Elec Engr); A. Jen group (Mat Sci Engr)
Evidence for Heterogeneity
• Single-cell cell cycle analysis: growth
Single Cell Division Times During MeOH Growth
Range:
2.5-4.3 hr
5
4.5
4
Time (hrs)
3.5
3
2.5
2
1.5
1
0.5
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1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63
Single Cell Division Times
12
10
# cells
8
6
Tim Strovas,
Linda Sauter
4
2
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2.5 2.6 2.7 2.8 2.9 3 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3
Time , Hr
Summary
• Breadth of bacterial diversity provides
opportunity
• Environmentally benign aspects provide
impetus
• New approaches provide strategies
• Result: increasing number of microbiallybased products over the next several years