Systems Metabolic Engineering (2) - University of...
Transcript of Systems Metabolic Engineering (2) - University of...
Systems Metabolic Engineering
Adriana Botes (PhDConsultant
Systems Metabolic Engineering
Adriana Botes (PhD) Director & CSO
Contents
Introduction10 Systems strategies for developing industrial microbial strains
1. Project Design2. Selection of host strain3. Metabolic Pathway reconstruction4. Increasing tolerance to product4. Increasing tolerance to product5. Remove negative regulatory circuits limiting overproduction6. Rerouting fluxes to optimise cofactor & precursor availability7. Diagnose & optimise metabolic fluxes toward product8. Diagnose & optimise culture conditions9. System- wide manipulation of the metabolic network10. Scale-up fermentation and diagnosis
Conclusions & Perspectives
10 Systems strategies for developing industrial microbial strains
Metabolic Pathway reconstruction
Remove negative regulatory circuits limiting overproductionRerouting fluxes to optimise cofactor & precursor availabilityDiagnose & optimise metabolic fluxes toward productDiagnose & optimise culture conditions
wide manipulation of the metabolic networkup fermentation and diagnosis
Introduction
• Development of an industrial process to produc
• 50-300 person years of work
• Several $100M investment
• Despite revolutionary technological developments, only a few bio
• 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 • 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 quickly
• 10 Stepwise strategies
• underpin successful development of industrial micr
• Implementation of Systems Metabolic Engineering:
• E. coli production strains for L-valine & L-threonine developed in 10 person years
• Feasible for small companies to develop production strains for target products
PronkNat.
uce bioproducts takes a great deal of time & effort:
Despite revolutionary technological developments, only a few bio-processes had been commercialised to date
fail to consider a fully integrated industrial bioprocess when developing new microbial cell factories
lagged behind academia in adopting SOTA metabolic engineering techniques
the few examples of technology translation to commercial processes the few examples of technology translation to commercial processes
collaborate more effectively & transfer knowledge more quickly1
icrobial strains through systems metabolic engineering (SME)
Implementation of Systems Metabolic Engineering:
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 companNat. Biotechnol. 33, 237–240 (2015).
Status Product MCFC Acetone C. acetobutylicumC citric acid Aspergillus nigerC lactic acid Issatchenkia orientalisC succinic acid E. coliC E. coliC S. cerevisiaeC B. succiniproducensC itaconic acid Aspergillus terreusC ‘06 1,3-propanediol E. coliD 1,3-butanediol E. coliC 1,4-butanediol E. coliD 2,3-butanediol C. autoethanogenum
Status of commercialization of microbial cell factories
D 2,3-butanediol C. autoethanogenumC PHA E. coliD Isoprene S. cerevisiae (E.coli)D Isobutene E. coliC L-Lysine & L-Arginine C. glutanicum? L-valine L-threonine E. coliC 1,5-pentanediamine C. glutanicumD adipic acid C. tropicalisD sebacic acid C. tropicalisD-C dodoecanedioic acid C. tropicalisC artemisinic acid S. cerevisiaeC-D squalene S. cerevisiaeC farnesene S. cerevisiaeD valencene S. cerevisiaeC vanillic acid S. cerevisiae
Feedstock CompanyCorn sugar Green Biologicssugar, molassesCorn sugars (dextrose) NatureWorkscorn sugar BioAmbersucrose MyriantStarch sugars Reverdiasugar, glycerol Succinitysugar, molasses Qingdao Kehaisugar DuPont Tate&Lyle Metabolic Ex sugar Genomatica & Versalissugar Genomatica & DuPont Tate&Lylesyngas LanzaTech
Status of commercialization of microbial cell factories
syngas LanzaTechsugar Metabolixsugar, cellulose Amyris, Braskem, MichelinGlucose, sucrose Global Bioenergiessugar SA Bioproductssugar KAISTsugar Cathay Industrial Biotechfatty acids (plant oil) Verdezynefatty acids (plant oil) Verdezynefatty acids (plant oil) VerdezyneSugar AmyrisSugar AmyrisSugar AmyrisSugar EvolvaSugar Evolva
Introduction
• Development of an industrial process to produc
• 50-300 person years of work
• Several $100M investment
• Despite revolutionary technological developments, only a few bio
• 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 • 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 quickly
• 10 Stepwise strategies
• underpin successful development of industrial micr
• Implementation of Systems Metabolic Engineering:
• E. coli production strains for L-valine & L-threonine developed in 10 person years
• Feasible for small companies to develop production strains for target products
PronkNat.
uce bioproducts takes a great deal of time & effort:
Despite revolutionary technological developments, only a few bio-processes had been commercialised to date
fail to consider a fully integrated industrial bioprocess when developing new microbial cell factories
lagged behind academia in adopting SOTA metabolic engineering techniques
the few examples of technology translation to commercial processes the few examples of technology translation to commercial processes
Need for academia/industry to collaborate more effectively & transfer knowledge more quickly1
icrobial strains through systems metabolic engineering (SME)
Implementation of Systems Metabolic Engineering:
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 companNat. Biotechnol. 33, 237–240 (2015).
Systems Metabolic EngineeringSME 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 editingthat 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
Systems Metabolic EngineeringSME integrates traditional metabolic engineering
analysis and genome scale computational simulation
Genetic engineering approaches, tools and pathway modules that allow fine control of gene expression levels and precise
Design the cell factorto fit the techno-
economics and process
Do not design the process around the
strain-that allow fine control of gene expression levels and precise
Evolution of strains in the lab for enhanced product tolerance
While taking into account
Tolerance to product and inhibitors in the feedstockGenetic stability & strain robustness under actual
strain-
the techno-economicswill never work!
3 Bioprocess stages
Selection of microbial host
Construction of biosynthetic
Use of effective, low cost easily available C
� Performance
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
easily available Cchemically defined medium
Optimisation of culture conditions & feeding strategies
Performance of batch/fedbatch/semi-continuous cultures
Evaluation of production performance under scale
conditions
Scale-up of bioreactors
Iterative design and construction of strains
Use of effective, low cost easily available C-sources &
Use of effective, low cost easily available C-sources &
� Cost
easily available C-sources & chemically defined medium
Optimisation of culture conditions & feeding strategies
Performance of batch/fed-continuous cultures
Evaluation of production performance under scale-down
conditions
up of bioreactors
easily available C-sources & chemically defined medium
Minimisation of by-products
High [product]
Iterative design and construction of strains
Adapted from Lee & Kim, Nature Biotechnology, 2015, 33
10 Stepwise strategindustrial microbial strainsThe Public Sector aspires to a Circular Biochemicals and fuels from renewable nonconcerns about climate change & depletion of fossil resourcesconcerns 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 existinvia controlled roll-out of disruptive
tegies for developing industrial microbial strains
aspires to a Circular Bio-economy to produce chemicals and fuels from renewable non-food biomass due to concerns about climate change & depletion of fossil resourcesconcerns about climate change & depletion of fossil resources
(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
ting investments in production plants disruptive technologies or new products
1. Project DesignSelection of a BioSelection of a Bio
Fermentation Process
CostVolumeSupply chain
Selection of a Feedstock
Commodity, Speciality
Technical, economical, legal & regulatory factors
Preliminary techno
Fermentation Process
Operating ConditionsAerobic, Anaerobic, MicroaerobicpH, Temperature, Sterility Fed Batch/ContinuousType of reactor (shear)
Low value/Waste streams‘clean’: glycerol‘dirty’ organic acids (paper & pulp)‘intermediate’ fatty acids (tall oil, edible oil)C1 feedstocks
4; CH3OH; CO2/H2; CO/ CO2/H2
Cellulosic/starch sugarsLignocellulosic Sugars
Selection of a host strain
Selection of a Bio-ProductSelection of a Bio-Product
Fermentation Process
Downstream Process
Properties:Volatile, Soluble (aq), Insoluble (oil/ppt)Physical propertiesPurity required, ‘bad’ impurities
Technical, economical, legal & regulatory factors
Final Product
Preliminary techno-economic analysis
Fermentation Process
Operating ConditionsAerobic, Anaerobic, MicroaerobicpH, Temperature, Sterility Fed Batch/ContinuousType of reactor (shear) Titer (g/L), Yield (g/g) Productivity (g/L/h
Estimate performance metrics of different strains using genome scale metabolic simulati
Unit operationsEquipment & Siz
Selection of a host strain
Overview of the microbial cell factodesign process.
For successful commercial implementationfull picture should be consideredthroughout the design process.
A. Considerations relating to the choice orenewable feedstock, including the locatiothe production facility in close proximity available feedstocks, as indicated by blue(correct) and red (incorrect) concentric c
B. The metabolic engineeringprocess, start from selection of productioprocess, start from selection of productioorganisms and iterating through design-butest-learn cycles until the process requirements are met.
C and D. Critical parameters for the production process and downstream purifito final products respectively.
Taken from Gustavvson & Lee, Microbial Biotechnology9:610
2. Selection of host strain
Tractable to Genetic Manipulation Quality metabolic models
E. coliS. cerevisiae
Native producer of product or precursor • Amino acids: • Succinic acid: • Fatty acids• Antibiotics: Feedstock utilisation• C1 feedstocks: • Extensive genetic engineering to • C1 feedstocks:
• Organic acids, fatty acids
Product tolerance
• Need to develop toolkit for genetic manipulation• Extensive data generation required to refine
metabolic model
• 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
2. Selection of host strainInnate characteristics of host
Native producer of product or precursor Amino acids: Corynebacterium glutanicumSuccinic acid: Mannheimia succiniciproducensFatty acids: Y. lipolytica vs Rhodosporidium toruloidesAntibiotics: Streptomyces
Feedstock utilisationC1 feedstocks: 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 manipulationExtensive data generation required to refine metabolic model
Host selection Needs analysis
Mature Molecular biology toolkit
Basic Toolkit, less established than E. coli
Genome scale model available
Basic model published, needs to be curated with data
Tolerance to target product
Requires evaluation
Degradation of Known degradation, analysisDegradation of Product/Precurosrs
Known degradation, requires KO strategy
Efflux of target product
Requires evaluation for active transported products
By-product formationRespiratory metabolism
negates need to co-produce by-products such as ethanol
Criteria defined for selecting a host organism suitable for the productionscale, and how Cupriavidus necator fit the criteria.� & � criteria are essential, � criteria are possible to address through
Host selection Needs analysis
Flexible and extensive Metabolic capabilities
Aerobic & anaearobic growth alpathways with oxygen requiring
oxygen sensitive enzymes
Phenotype characteristics that can be exploited
Stringent response under limitconditions allows continued uptof C & generates an NADPH poo
reduction
Feedstock flexibilityAutotrophic growth on CO2/H
Glycerol, TAG’s, organic acids, Faacids, aromatics
High growth rate on low cost defined
Carbon source + analysislow cost defined
media
Carbon source + mineral salts
ACDP classification of pathogenicity
Class 1
Robustness at industrial scale
Large scale production of PHBs to industrial scale
production of bulk chemicals from low cost feedstocks at indust
through strain evolution and genetic engineering, if identified early.
3. Metabolic Pathway reconstruction
Feedstock uptake
Central metabolism Product
pathway
Biomass, energy
Secreted Product
�
Product non-natural or inefficiently produced in
natural host
Gene Discovery: Enzymes required to complete pathway from bacterial, plant, fungal, mammalian origin?
Enzymes required to complete pathway kinetic properties?
Functional expression in selected host?
3. Metabolic Pathway reconstructionPathway Modeling Tools in SME:
• Computational tools for rational enzyme engineering
• Chemo-bioinformatic tools for pathway construction
• Constraint-based reconstruction and analysis (COBRA) of genome scale modelsanalysis (COBRA) of genome scale models
• 13C flux analysis
• Elementary mode analysis
Identify optimal metabolic pathways to drive fluxes from one metabolite to another
Enzymes required to complete pathway kinetic properties?
Enzyme selection & screening
Enzyme engineering
Semi-synthesis of
IPP ���� DMAPP
Glucose
G3P
Pyruvate
Acetyl-CoA
DXP Pathway
E. coli
DXP Pathway
E. coli
FPPFPPAmorphadiene
Synthase
Amorphadiene
SynthaseAcetyl-CoA
Mevalonate Pathway
S. cerevisiae
FPPFPP
AmorphadieneAmorphadiene
25 g/L E. coli25 g/L E. coli
40 g/L S. cerevisiae
SynthaseSynthase
Squalene Synthase
� Cu / Methionine
Squalene Synthase
� Cu / Methionine
ErgosterolErgosterol
synthesis of Artemesinin
Amorphadiene
Synthase
Amorphadiene
Synthase
Artemesinic acidArtemesinic acid
25 g/L S. cerevisiae
CYP71AV1, CPR1, CYB5
ADH1, ALDH1
CYP71AV1, CPR1, CYB5
ADH1, ALDH1
ArtemesininArtemesinin
Chemical
conversion
Chemical
conversion
S. cerevisiae
SynthaseSynthase
4. Increasing tolerance to productTest 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 analogswith or w/o mutagen treatment
• Increase dilution rate during continuous culture
• Identification of cells with highest growth rate
4. Increasing tolerance to product
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
©2011 by European Molecular Biology Organization
efflux pumps that provide biofuel tolerance.
Mary J Dunlop et al. Mol Syst Biol 2011;7:48
5. Remove negative regulatory circuits5. Remove negative regulatory circuitsTranscriptional regulation
• Replace native promoters
• KO transcription factors
Metabolic engineering of a C. glutanicumstrain overproducing L-Arg
(9 person years)(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 circuits5. Remove negative regulatory circuitsAllosteric regulation of enzymes
Feedback inhibition of enzyme by product or pathway intermediate
Metabolic engineering of a C. glutanicumstrain overproducing L-Lysine & PMD
The LysC gene encoding aspartatokinase was mutated to T311I to release feedback 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
• NADH, NADPH, ATP, CoA are involved in 100’s of reactions in the cell
• Acetyl-CoA, TCA cycle metabolites, amino acids
• Rerouting of metabolic fluxes is • Rerouting of metabolic fluxes is required to optimize the availability of cofactors and metabolic precursors of pathway
Optimisation of cofactors and precursors require systems-wide
approaches
Global mass, energy and redox balances must be considered
6. Rerouting fluxes to optimise cofactor & precursor
Manipulation of co-factors & precursors
• Remove competing pathways (gene KO)- time consuming, only applicable to non-essential gene
• Gene attenuation (gene knock-down) if gene is essential
• Combinatorial knockdown targets (synthetic • Combinatorial knockdown targets (synthetic biology tools & high-throughput screening of strains with combinations of downregulated gen
• Manipulation of co-factor specificity (swop NADPH-dependent enzymes and NADH dependenzymes)
Metabolic engineering of a C. glutanicustrain overproducing L-Lysine & PMD:
Co-factor & precursor availability
Flux rerouting to the pentose phosphate pathwa
Fluxes to L-lysine were reinforced by overexpressing ddh and removing competing pathways (knockout of pck and downregulation ohom).
Flux rerouting to the pentose phosphate pathwa(PPP) was conducted for NADPH generation by overexpressing the gluconeogenic gene fbp.
For PMD production, NCgl1469 encoding N-acetyltransferase and lysE encoding L-lysine exporter were both removed as they divert L-lysine away from 1,5-diaminopentane.
7. Diagnose & optimise meta8. 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
etabolic fluxes toward product8. Diagnose & optimise culture conditions
Performance of intermediate strain under scale-down conditions facilitates evaluation & diagnosis of production
performanceperformance
Titer, Yield, Productivity
• Define new objectives for the next round of metabolic engineering
Metabolic engineering of a C. glutanicustrain overproducing L-Lysine & PMD:
Metabolic Flux Optimisation
Increase fluxes to L-Lys biosynthesis:
Overexpressing genes involved in the L-lysine biosynthetic pathway (dapB, lysA anthe mutated lysC),
mutating a pycA gene and downregulating the icd gene
For PMD production, amplification of its export(cg2893) led to further improvement in the production titer.
Amplification of PPP operon was amplified in theengineered C. glutamicum strain to enhance L-lysine production.
mutating a pycA gene and downregulating the icd gene
A complex medium based on molasses was used for the fed-batch culture ofC. glutamicum LYS-12 in order to evaluate its L-lysine production performance in an industrial setting.
Industrial glucose medium was used focultivating 1,5-diaminopentane-overproducing C. glutamicum DAP-16 strain.
Strain LYS 12
(L-Lys)
DAP-16
(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
Systems Biology Approaches
Cultivation profile-based system-wide analysis (‘fermentome’)
• -omics- based approaches
Final rounds of engineering required to construct the industrial strain
• -omics- based approaches
• In silico metabolic simulations
Current challenges
• Low transformation efficiency of host strains
• Screening methods for mutants overproducing a desired products
wide manipulation of the metabolic
Synthetic Biology Approaches
High-throughput genome scale engineering
• Multiplex automated genome engineering
• Trackable multiplex recombineering
Final rounds of engineering required to construct the industrial strain
• Trackable multiplex recombineering
• Synthetic small regulatory RNAs
• Auto-inducers for dynamic control of fluxes
Identify optimal combinations of genetic targets quickly
Isolation of mutants with desired phenotpes
10. Scale-up fermentation and diagnosis
• Aerobic fermentations are particularly affected by scale-up issues
• Mixing & aeration differences between lab and pilot scale
Fine
•
Pilot/Demo plant validation of industrial strain
lab and pilot scale
• Mass transfer rates of nutrients & oxygen
• Genetic instability (chromosomal manipulation)
•
•
up fermentation and diagnosis
Industrial Fermentation engineers
Fine-tune fermentation conditions using
• industrial grade feedstocks and medium components
Pilot/Demo plant validation of industrial strain
components
• Manipulate pH, temperature & oxygen transfer
• Contamination control (phage infection)
Conclusions & Perspectives
The process of bioengineering strains for commodity chemicals(process engineering and implementation)
Conclusions & Perspectives
als from initial concept (target molecule selection) to scale up
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:10.1111/17517915.12385.
• Victor Chubukov et al. (2016). Synthetic and systems biology for microbial production of commodity chemicals. npj Systems Biology and Applications 2, 16009.
Kim (2015). Systems strategies for developing industrial microbial strains. Nature Biotechnology, 33 (10):1061. doi:10.1038/nbt.3365
& Sang Yup Lee (2016). Prospects of microbial cell factories developed through systems metabolic engineering. Microbial Biotechnology 9 (5): 610. doi:10.1111/1751-
et al. (2016). Synthetic and systems biology for microbial production of Systems Biology and Applications 2, 16009.