* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Systems Metabolic Engineering Systems Metabolic
Survey
Document related concepts
Biochemical cascade wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Fatty acid metabolism wikipedia , lookup
Biosynthesis wikipedia , lookup
Fatty acid synthesis wikipedia , lookup
Community fingerprinting wikipedia , lookup
Gene regulatory network wikipedia , lookup
Biochemistry wikipedia , lookup
Metabolomics wikipedia , lookup
Genetic engineering wikipedia , lookup
Amino acid synthesis wikipedia , lookup
Pharmacometabolomics wikipedia , lookup
Transcript
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.