Download Systems Metabolic Engineering Systems Metabolic

Systems Metabolic
Engineering
Consultant
Director & CSO
Adriana Botes (PhD)
Contents
Introduction
10 Systems strategies for developing industrial microbial strains
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Project Design
Selection of host strain
Metabolic Pathway reconstruction
Increasing tolerance to product
Remove negative regulatory circuits limiting overproduction
Rerouting fluxes to optimise cofactor & precursor availability
Diagnose & optimise metabolic fluxes toward product
Diagnose & optimise culture conditions
System- wide manipulation of the metabolic network
Scale-up
up fermentation and diagnosis
Conclusions & Perspectives
Introduction
• Development of an industrial process to produc
uce bioproducts takes a great deal of time & effort
• 50-300 person years of work
• Several $100M investment
• Despite revolutionary technological developments, only a few bio-processes
bio
had been commercialised to date
•
Researchers fail to consider a fully integrated industrial bioprocess when developing new microbial cell factories
•
Companies lagged behind academia in adopting SOTA metabolic engineering techniques
•
Time/Cost is prohibitive for small companies – the few examples of technology translation to commercial processes
required early partnering with big players
•
Need for academia/industry to collaborate more effectively & transfer knowledge more quickly1
• 10 Stepwise strategies
• underpin successful development of industrial micr
icrobial strains through systems metabolic engineering (SME)
• Implementation of Systems Metabolic Engineering:
• E. coli production strains for L-valine & L-threonine
threonine developed in 10 person years
• Feasible for small companies to develop production strains for target products
Pronk J.T. et al. How to set up collaborations between academia and industrial biotech compan
Pronk,
Nat. Biotechnol. 33, 237–240 (2015).
Status of commercialization of microbial cell factories
Status
C
C
C
C
C
C
C
C
C ‘06
D
C
D
C
D
D
C
?
C
D
D
D-C
C
C-D
C
D
C
Product
Acetone
citric acid
lactic acid
succinic acid
MCF
Feedstock
Company
C. acetobutylicum
Corn sugar
Green Biologics
Aspergillus niger
sugar, molasses
Issatchenkia orientalis Corn sugars (dextrose) NatureWorks
E. coli
corn sugar
BioAmber
E. coli
sucrose
Myriant
S. cerevisiae
Starch sugars
Reverdia
B. succiniproducens
sugar, glycerol
Succinity
itaconic acid
Aspergillus terreus
sugar, molasses
Qingdao Kehai
1,3-propanediol
E. coli
sugar
DuPont Tate&Lyle Metabolic Ex
1,3-butanediol
E. coli
sugar
Genomatica & Versalis
1,4-butanediol
E. coli
sugar
Genomatica & DuPont Tate&Lyle
2,3-butanediol
C. autoethanogenum
syngas
LanzaTech
PHA
E. coli
sugar
Metabolix
Isoprene
S. cerevisiae (E.coli)
sugar, cellulose
Amyris, Braskem, Michelin
Isobutene
E. coli
Glucose, sucrose
Global Bioenergies
L-Lysine & L-Arginine C. glutanicum
sugar
SA Bioproducts
sugar
KAIST
L-valine L-threonine E. coli
1,5-pentanediamine C. glutanicum
sugar
Cathay Industrial Biotech
adipic acid
C. tropicalis
fatty acids (plant oil) Verdezyne
sebacic acid
C. tropicalis
fatty acids (plant oil)
Verdezyne
dodoecanedioic acid C. tropicalis
fatty acids (plant oil)
Verdezyne
artemisinic acid
S. cerevisiae
Sugar
Amyris
squalene
S. cerevisiae
Sugar
Amyris
farnesene
S. cerevisiae
Sugar
Amyris
valencene
S. cerevisiae
Sugar
Evolva
vanillic acid
S. cerevisiae
Sugar
Evolva
Introduction
• Development of an industrial process to produc
uce bioproducts takes a great deal of time & effort
• 50-300 person years of work
• Several $100M investment
• Despite revolutionary technological developments, only a few bio-processes
bio
had been commercialised to date
•
Researchers fail to consider a fully integrated industrial bioprocess when developing new microbial cell factories
•
Companies lagged behind academia in adopting SOTA metabolic engineering techniques
•
Time/Cost is prohibitive for small companies – the few examples of technology translation to commercial processes
required early partnering with big players
•
Need for academia/industry to collaborate more effectively & transfer knowledge more quickly1
• 10 Stepwise strategies
• underpin successful development of industrial micr
icrobial strains through systems metabolic engineering (SME)
• Implementation of Systems Metabolic Engineering:
• E. coli production strains for L-valine & L-threonine
threonine developed in 10 person years
• Feasible for small companies to develop production strains for target products
Pronk J.T. et al. How to set up collaborations between academia and industrial biotech compan
Pronk,
Nat. Biotechnol. 33, 237–240 (2015).
Systems Metabolic Engineering
SME integrates traditional metabolic engineering
approaches with other fields
• Systems biology
• -omics analysis and genome scale computational simulation
• Synthetic biology
• Genetic engineering approaches, tools and pathway modules
that allow fine control of gene expression levels and precise
genome editing
• Evolutionary engineering
• Evolution of strains in the lab for enhanced product tolerance
While taking into account
• Techno-economic factors
• Tolerance to product and inhibitors in the feedstock
• Genetic stability & strain robustness under actual
fermentation conditions
Design the cell factor
to fit the technoeconomics and proces
Do not design the
process around the
strain-
the techno-economics
will never work!
Cost
Performance
3 Bioprocess
stages
Selection of microbial host
Construction of biosynthetic
pathway
Improvement of tolerance against
target product and inhibitors in
feedstock
Removal of negative regulations
Flux rerouting for cofactor and
precursor optimisation
Optimisation of metabolic fluxes
through pathway(s)
Systems level metabolic analysis
Use of effective, low cost
easily available C-sources
C
&
chemically defined medium
Use of effective, low cost
easily available C-sources &
chemically defined medium
Optimisation of culture
conditions & feeding strategies
Minimisation of by-products
Performance of batch/fedbatch/fed
batch/semi-continuous
continuous cultures
High [product]
Evaluation of production
performance under scale-down
scale
conditions
Scale-up
up of bioreactors
Iterative design and construction of strains
Adapted from Lee & Kim, Nature Biotechnology, 2015, 33
10 Stepwise strateg
tegies for developing
industrial microbial strains
The Public Sector aspires to a Circular Bio-economy
Bio
to produce
chemicals and fuels from renewable non-food
non
biomass due to
concerns about climate change & depletion of fossil resources
The Private Sector (bulk chemicals/fuels) aspires to increase profits and
market share by reducing production costs using lower cost raw materials
with stable supply, fewer unit operations, decrease CAPEX and OPEX
while protecting their existin
ting investments in production plants
via controlled roll-out of disruptive technologies or new products
. Project Design
st
ume
pply chain
Commodity,
Speciality
Selection of
a Bio-Product
Bio
Technical, economical, legal &
regulatory factors
Final Product
Properties:
Volatile, Soluble (aq), Insoluble (oil/ppt
Physical properties
Purity required, ‘bad’ impurities
Selection of
a Feedstock
w value/Waste streams
ean’: glycerol
rty’ organic acids (paper & pulp)
ermediate’ fatty acids (tall oil, edible oil)
feedstocks
4; CH3OH; CO2/H2; CO/ CO2/H2
lulosic/starch sugars
nocellulosic Sugars
Downstream
Process
Fermentation Process
Unit operations
Equipment & Siz
Operating Conditions
Aerobic, Anaerobic, Microaerobic
pH, Temperature, Sterility
Fed Batch/Continuous
Titer (g/L), Yield (g/g) Productivity (g/L/h
Type of reactor (shear)
Estimate performance metrics of different
strains using genome scale metabolic simulat
Selection of
a host strain
Preliminary techno-economic
techno
analysis
Overview of the microbial cell fact
design process.
For successful commercial implementation
full picture should be considered
throughout the design process.
A. Considerations relating to the choice o
renewable feedstock, including the locatio
the production facility in close proximity
available feedstocks, as indicated by blue
(correct) and red (incorrect) concentric c
B. The metabolic engineering
process, start from selection of productio
organisms and iterating through design-b
test-learn cycles until the process
requirements are met.
C and D. Critical parameters for the
production process and downstream purif
to final products respectively.
Taken from Gustavvson & Lee, Microbial Biotechnology
9:610
2. Selection of host strain
Tractable to Genetic Manipulation
Quality metabolic models
E. coli
S. cerevisiae
•
•
Extensive genetic engineering to
obtain desired traits
Host may never produce product as
efficiently as a non-conventional host
Tools to manipulate non-conventional
hosts are becoming less of an issue
Systems biology advances
Synthetic biology tools CRIPR-Cas9
Innate characteristics of host
Native producer of product or precursor
• Amino acids: Corynebacterium glutanicum
• Succinic acid: Mannheimia succiniciproducens
• Fatty acids: Y. lipolytica vs Rhodosporidium toruloides
• Antibiotics: Streptomyces
Feedstock utilisation
• C1 feedstocks:
• Clostridium autoethanogenum
• Cupriavidus necator
• Synechosystis sp.
• Methylococcus capsulatus (Bath)
• Organic acids, fatty acids
• Cupriavidus necator, Candida tropicalis
Product tolerance
• Pseudomonas putida
•
•
Need to develop toolkit for genetic manipulation
Extensive data generation required to refine
metabolic model
Basic Toolkit, less
established than E. coli
Mature Molecular
biology toolkit
Flexible and extensive
Metabolic capabilities
Aerobic & anaearobic growth al
pathways with oxygen requiring
oxygen sensitive enzymes
sic model published, needs
to be curated with data
Genome scale
model available
Phenotype
characteristics that
can be exploited
Stringent response under limit
conditions allows continued upt
of C & generates an NADPH poo
reduction
Requires evaluation
Tolerance to
target product
Feedstock flexibility
Autotrophic growth on CO2/H
Glycerol, TAG’s, organic acids, Fa
acids, aromatics
Known degradation,
requires KO strategy
Degradation of
Product/Precurosrs
High growth rate on
low cost defined
media
Carbon source +
mineral salts
Requires evaluation for
active transported products
Respiratory metabolism
egates need to co-produce
y-products such as ethanol
Host
selection
Needs
analysis
Efflux of target
product
ACDP classification of
pathogenicity
By-product formation
Robustness at
industrial scale
Class 1
Large scale production of
PHBs to industrial scale
riteria defined for selecting a host organism suitable for the production of bulk chemicals from low cost feedstocks at indus
cale, and how Cupriavidus necator fit the criteria.
& criteria are essential, criteria are possible to address through strain evolution and genetic engineering, if identified early.
3. Metabolic Pathway reconstruction
Pathway Modeling Tools in SME:
dstock
take
Central
metabolism
Product
pathway
Biomass,
energy
Product non-natural or
inefficiently produced in
natural host
Gene Discovery: Enzymes required to
complete pathway from bacterial,
plant, fungal, mammalian origin?
Functional expression in
selected host?
Secreted
Product
•
Computational tools for rational enzyme
engineering
•
Chemo-bioinformatic tools for pathway
construction
•
Constraint-based reconstruction and
analysis (COBRA) of genome scale models
•
13C flux analysis
•
Elementary mode analysis
Identify optimal metabolic pathways to
drive fluxes from one metabolite to another
Enzyme engineering
Enzymes required to complete
pathway kinetic properties?
Enzyme selection &
screening
Semi-synthesis
synthesis of Artemesinin
Glucose
Squalene Synthase
Cu / Methionine
DXP Pathway
E. coli
Ergosterol
G3P
Pyruvate
IPP DMAPP
Acetyl-CoA
FPP
Amorphadiene
Synthase
Mevalonate Pathway
S. cerevisiae
CYP71AV1, CPR1, CYB5
ADH1, ALDH1
Chemical
conversion
Amorphadiene
25 g/L E. coli
40 g/L S. cerevisiae
Artemesinic acid
25 g/L S. cerevisiae
Artemesinin
4. Increasing tolerance to product
Test product toxicity and stability early on
product tolerance once the strain under
development produces close to
inhibitory [product]
Strain with tolerance at high [product]
does not necessarily correlate with productivity
Adaptive Evolution
• Serial subculturing with [product] or product analogs
with or w/o mutagen treatment
• Increase dilution rate during
continuous culture
• Identification of cells with
highest growth rate
Rational Engineering
• Efflux pump for biofuel in E. coli
• Manipulation of ionic membrane gradients
in S. cerevisiae for EtOH production
• Overexpression of L-valine exporter titer by 40% in E. coli
Engineering efflux pumps is a powerful
strategy to improve product tolerance
Bioprocess Design
• Couple in situ product removal
with fermentation if no better
ways of increasing product
tolerance can be found
Competition assay efficiently identifies ef
efflux pumps that provide biofuel tolerance.
©2011 by European Molecular Biology Organization
Mary J Dunlop et al. Mol Syst Biol 2011;7:48
5. Remove negative regulatory circuits
Transcriptional regulation
• Replace native promoters
• KO transcription factors
Metabolic engineering of a C. glutanicum
strain overproducing L-Arg
(9 person years)
Negative feedback regulation in the AR1
strain was removed by inactivating two
regulatory genes, argR and farR.
The resulting AR2 strain was able to
produce 61.9 g/L of L-arginine by fed-batch
culture compared to 34.2 g/L of the AR1
strain
5. Remove negative regulatory circuits
Allosteric regulation of enzymes
Feedback inhibition of enzyme by
product or pathway intermediate
Metabolic engineering of a C. glutanicum
strain overproducing L-Lysine & PMD
The LysC gene encoding aspartatokinase was
mutated to T311I to release feedback
inhibition by L-Lysine & L-Threonine (Lys-1)
6. Rerouting fluxes to optimise cofactor & precursor
availability
Co-factors & Precursors
Manipulation of co-factors & precursors
• NADH, NADPH, ATP, CoA are involved
in 100’s of reactions in the cell
• Remove competing pathways (gene KO)- time
consuming, only applicable to non-essential gene
• Acetyl-CoA, TCA cycle metabolites,
amino acids
• Gene attenuation (gene knock-down) if gene is
essential
• Rerouting of metabolic fluxes is
required to optimize the availability of
cofactors and metabolic precursors of
pathway
• Combinatorial knockdown targets (synthetic
biology tools & high-throughput screening of
strains with combinations of downregulated gen
Optimisation of cofactors and
precursors require systems-wide
approaches
Global mass, energy and redox balances
must be considered
• Manipulation of co-factor specificity (swop
NADPH-dependent enzymes and NADH depend
enzymes)
Metabolic engineering of a C. glutanicu
strain overproducing L-Lysine & PMD:
Co-factor & precursor availability
Fluxes to L-lysine were reinforced by
overexpressing ddh and removing competing
pathways (knockout of pck and downregulation
hom).
Flux rerouting to the pentose phosphate pathw
(PPP) was conducted for NADPH generation by
overexpressing the gluconeogenic gene fbp.
For PMD production, NCgl1469 encoding Nacetyltransferase and lysE encoding L-lysine
exporter were both removed as they divert Llysine away from 1,5-diaminopentane.
7. Diagnose & optimise meta
etabolic fluxes toward product
8. Diagnose & optimise culture conditions
Diagnosis of the metabolic state
• Experiments must be performed under
conditions as similar as possible to the
final industrial fermentation conditions
• Fed-batch or continuous fermentation
under scale-down conditions are
essential for the ‘test’ element
• Identify bottlenecks and by-products for
further metabolic engineering
Performance of intermediate strain
under scale-down conditions facilitates
evaluation & diagnosis of production
performance
Titer, Yield, Productivity
• Define new objectives for the next
round of metabolic engineering
Metabolic engineering of a C. glutanicu
strain overproducing L-Lysine & PMD:
Metabolic Flux Optimisation
Increase fluxes to L-Lys biosynthesis:
Overexpressing genes involved in the Llysine biosynthetic pathway (dapB, lysA an
the mutated lysC),
mutating a pycA gene and downregulating
the icd gene
Amplification of PPP operon was amplified in th
engineered C. glutamicum strain to enhance Llysine production.
For PMD production, amplification of its export
(cg2893) led to further improvement in the
production titer.
A complex medium based on molasses
was used for the fed-batch culture of
C. glutamicum LYS-12 in order to
evaluate its L-lysine production
performance in an industrial setting.
Industrial glucose medium was used fo
cultivating 1,5-diaminopentaneoverproducing C. glutamicum DAP-16
strain.
Strain
LYS 12 DAP-16
(L-Lys) (PMD)
Titer (g/L)
120
88
Yield (g/g)
0.55
0.29
Productivity
(g/L/h)
4.0
2.2
9. System- wide manipulation of the metabolic
network
Final rounds of engineering required to construct the
industrial strain
Synthetic Biology Approaches
Systems Biology Approaches
High-throughput genome scale engineering
Cultivation profile-based system-wide
analysis (‘fermentome’)
• Multiplex automated genome
engineering
• -omics- based approaches
• Trackable multiplex recombineering
• In silico metabolic simulations
• Synthetic small regulatory RNAs
• Auto-inducers for dynamic control of
fluxes
Current challenges
• Low transformation efficiency of host
strains
• Screening methods for mutants
overproducing a desired products
Identify optimal combinations of genetic
targets quickly
Isolation of mutants with desired
phenotpes
10. Scale-up
up fermentation and diagnosis
Pilot/Demo plant validation of industrial strain
• Aerobic fermentations are particularly
affected by scale-up issues
Fine
Fine-tune
fermentation conditions using
• Mixing & aeration differences between
lab and pilot scale
• industrial grade feedstocks and medium
components
• Mass transfer rates of nutrients &
oxygen
• Manipulate pH, temperature & oxygen
transfer
• Genetic instability (chromosomal
manipulation)
• Contamination control (phage infection)
Industrial Fermentation engineers
Conclusions & Perspectives
The process of bioengineering strains for commodity chemicals
als from initial concept (target molecule selection) to scale up
(process engineering and implementation)
Victor Chubukov et al. npj Systems Biology and Applications (2016) 2, 16
Acknowledgements
• Former colleagues
• Alex Conradie (),
• Changlin Chen & Ramdane Haddouche (),
• Unni Chokkathukalam & Satnam Surae ()
• CPI
• Frank Millar /Kris Wardrop
• Robin Mitra & Steve Pearson
Further Reading
• Sang Yup Lee & Hyun Uk Kim (2015). Systems strategies for developing industrial microbial
strains. Nature Biotechnology, 33 (10):1061. doi:10.1038/nbt.3365
• Martin Gustavsson & Sang Yup Lee (2016). Prospects of microbial cell factories developed
through systems metabolic engineering. Microbial Biotechnology 9 (5): 610. doi:10.1111/1751doi:10.1111/1751
7915.12385.
• Victor Chubukov et al. (2016). Synthetic and systems biology for microbial production of
commodity chemicals. npj Systems Biology and Applications 2, 16009.