Advances in Komagataella phaffii Engineering for the Production of Renewable Chemicals and Proteins
Abstract
:1. Introduction
2. Komagataella Taxonomy and Diversity
3. Production of Renewable Chemicals from Glycerol by K. phaffii
3.1. Metabolism of Glycerol
3.2. K. phaffii Engineering for Renewable Chemicals from Glycerol
3.2.1. Lactic Acid Production from Glycerol by K. phaffii
3.2.2. 3-Hydroxy-Propionic Acid (3-HP) Production from Glycerol in K. phaffii
3.2.3. Isobutanol and Isobutyl Acetate Production from Glycerol in K. phaffii
3.2.4. Aromatic Secondary Metabolite Production from Glycerol in K. phaffii
3.3. Glycerol Co-Utilization by K. phaffii
4. Renewables from Sugars and Lignocellulosic Hydrolysates
4.1. Metabolic Engineering of K. phaffii to Produce Renewables Chemicals from Glucose
4.1.1. Isobutanol Production from Glucose in K. phaffii
4.1.2. 2,3-Butanediol Production from Glucose in K. phaffii
4.1.3. Inositol Production from Glucose in K. phaffii
4.1.4. Glucaric Acid Production from Glucose in K. phaffii
4.2. Metabolic Engineering of K. phaffii to Produce Renewables Chemicals from Xylose
4.2.1. Xylitol Production from Xylose in K. phaffii
4.2.2. Xylonic Acid Production from Xylose in K. phaffii
5. Renewables from Methanol and CO2
5.1. K. phaffii Engineering for CO2 Assimilation
5.2. Metabolic Engineering of K. phaffii for Production of Renewables from Methanol
5.2.1. β-Alanine Production from Methanol in K. phaffii
5.2.2. Organic Acids Production from Methanol in K. phaffii
5.2.3. Biopolymers Production from Methanol in K. phaffii
5.2.4. Polyketides Production from Methanol in K. phaffii
6. Komagataella phaffii Application in Protein Production
7. Strategies to Develop and Optimize Fermentative Processes
7.1. Fermentation Parameters
7.2. Operation Mode
7.3. Mathematical Models
8. Challenges for Industrial Processes with K. phaffii
9. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Type Species | Strain | Genome Size (Mb) | Isolation | Origin | Carbon Sources | Ref |
---|---|---|---|---|---|---|
K. pastoris | CBS 704 | 9.6 | Aesculus species | France | Glucose Glycerol Methanol Ethanol Xylose | ASM170810v1 A |
K. phaffii | CBS 7435 | 9.4 | Quercus velutina | California, USA | ASM170808v1 A | |
K. ulmi | CBS 12361 | 9.6 | Ulmus americana | Illinois, USA | [21] | |
K. kurtzmanii | CBS 12817 | 9.6 | Fir flux | Arizona, USA | ||
K. mondaviorum | CBS 15017 | 9.5 | Populus deltoides | California, USA | ||
K. pseudopastoris | CBS 9187 | 10.6 | Salix alba | Hungary | ||
K. populi | CBS 12362 | 9.3 | Populus deltoides | Illinois, USA |
Substrate | Product | Genetic modification | Process | Production (g·L−1) | Yield (g·g−1) | Productivity (g·L−1·h−1) | Reference |
---|---|---|---|---|---|---|---|
Glycerol | Lactic Acid | Expression of lactate dehydrogenase (LDH) | Batch and fed-batch fermentation | - | 0.70 | - | [36] |
Lactic Acid | Deletion of ArDH gene | Batch fermentation | 24 | 0.85 | - | [38] | |
3-hydroxy propionic acid (3-HP) | Expression of mcr | Fed-batch | 24.75 | 0.13 | 0.54 | [39] | |
Glycerol and glucose | Isobutanol | Over-expression of the keto acid degradation pathway and medium supplementation | Batch | 2.22 | - | - | [40] |
Isobutyl acetate ester | Expression of an alcohol-O-acyltransferase enzyme | Batch | 0.051 | - | - | [40] | |
Isopentyl acetate | Expression of an alcohol-O-acyltransferase enzyme | Batch | 0.024 | - | - | [40] | |
Glucose | Isobutanol | Expression of LlkivD, ScADH7, PpIlv2, PpIlv3, PpIlv5, PpIlv6 | Shake-flask | 2.22 | 0.22 | - | [40] |
2,3-butanediol | Expression of alsS and alsD | 2-L bioreactor, fed-batch | 74.5 | 0.30 | 0.81 | [41] | |
Glucaric acid | Expression of mMIOX and Udh | Shake flask; fed-batch | 6.61 | - | - | [42] | |
Inositol | Overexpression of native inositol pathway | Fed-batch fermentation | 30.7 | - | - | [43] | |
Xylose | Xylitol | Expression of PsXYL1 and gdh | - | 320 (mM) | 0.80 | 2.44 | [44] |
Xylonic acid | Expression of XDH | 1-L bioreactor; batch | 37 | 0.96 | 0.41 | [45] | |
Methanol | β-alanine | Overexpression of ADC and aspDH | 1-L bioreactor, fed-batch | 5.60 | - | - | [46] |
Lactic acid | Multicopy integration of Ldh | Batch | 3.48 | 0.22 | 0.036 | [47] | |
Malic acid | Overexpression of Mdh, Pyc and SpMae; Δgpi | Shake-flask; batch | 2.79 | - | - | [48] | |
Lovastatin | Expression of LovB, LovC, LovG, NpgA, LovA, CPR, LovD, LovF | 5-L bioreactor, fed-batch | 0.250 | - | - | [49] | |
Monacolin J | Expression of LovB, LovC, LovG, NpgA, LovA, CPR | 5-L bioreactor, fed-batch | 0.593 | - | - | [49] | |
6-Methylsalicylic acid | Overexpression of atX, npgA | 5-L bioreactor with 3-L operating volume, fed-batch | 2.2 | - | - | [50] | |
Chondroitin sulfate | Expression of kfoA, kfoC, tuaD, C4ST, PAS_chr1-4_0253, PAS_chr3_0667 | 3-L bioreactor, fed-batch | 2.1 | - | - | [51] | |
Heparin | Expression of tuaD, kfiC, kfiA, NDST, C5 epi, 2OST,3OST, 6OST | 3-L bioreactor, fed-bach | 2.08 | - | - | [52] | |
Methanol and Glucose | Hyaluronic acid | Overexpression of xhasA2, xhasB, hasC, hasD, hasE | 2.5-L bioreactor with 1-L operating volume, fed-batch | 0.8–1.7 | - | - | [53] |
Biomass | Solid Concentration | Biomass Composition (Dry Basis %) | Pretreatment | Hydrolysate Composition (g/L) | ||||
---|---|---|---|---|---|---|---|---|
Cellulose | Hemicellulose | Lignin | Acetic acid | Furans | Phenols | |||
Sugarcane bagasse | 10% | 43.1 | 31.1 | 11.4 | Hot water | 1.1–3.4 | 0.5–5.1 | 1.4–2.4 |
Corn stover | 10–20% | 37 | 22.7 | 18.6 | Hot water | 2.0–2.8 | 0.74–8.37 | 181–246 AU |
Wheat straw | 30% | 30.2 | 21 | 17 | Steam explosion | 0.04–1.01 | 0.16–2.14 | nd |
Maple | 23% | 41 | 15 | 29.1 | Hot water | 13.1 | 4.1 | 1.3 |
Olive tree pruning | 20% | 25 | 11.1 | 16.2 | Steam explosion | 0.4–4.2 | 0–3.2 | nd |
Protein | Expression Vector | Promoter | Production | Yield/Activity | Reference |
---|---|---|---|---|---|
Malaria vaccine candidate protein | pPICZαA | AOX | 3-L bioreactor, fed-batch | 62.2 g/L | [102] |
Dengue vaccine candidate protein | pPICZ-A | AOX | Shake-flask; fed-batch | 15 mg/L | [103] |
Chikungunya vaccine candidate protein | pPIC9K | AOX | Shake-flask; fed-batch | 60 mg/L | [104] |
Tuberculosis vaccine candidate protein | pPICZαA | AOX | Shake-flask; fed-batch | 5 µg/mL | [105] |
SARS-CoV-2 Spike RBD | pPICZαA | AOX | 7-L bioreactor, fed-batch | 45 mg/L | [106] |
Human proinsulin | pPICZα | AOX | Shake-flask; fed-batch | 5 mg/L | [107] |
Human epidermal growth | pPIC9K | AOX | Shake-flask; fed-batch | 2.27 µm/mL | [108] |
Interleukin-1beta | pPICZαA | AOX | Shake-flask; fed-batch | 250 mg/L | [109] |
Antimicrobial Hispidalin | pPICZαA | AOX | Shake-flask; fed-batch | 98.6 µg/mL | [110] |
Antimicrobial CecropinA-thanatin | pPICZαA | AOX | Shake-flask; fed-batch | 1.061 µmol/L | [111] |
Antimicrobial PAF102 peptide | pGAPZA | GAP | Shake-flask; batch | 180 mg/L | [112] |
Antimicrobial fowlicidins | pPICZαA | AOX | Shake-flask; fed-batch | 85.6 mg/L | [113] |
Human serum albumin | pPIC9K | AOX | Shake-flask; fed-batch | 8.86 g/L | [114] |
Endoglucanase | pPink-GAP | GAP | 15-L bioreactor, fed-batch | 3 to 5 g/L | [115] |
Cellobiohydrolase | pPpB1 | AOX | 1-L bioreactor, fed-batch | 6.55 g/L | [116] |
β-glucosidases | pPIC3.5K | AOX | 5-L bioreactor, fed-batch | 403 mg/L | [117] |
LPMO | pPICZαA | AOX | Shake-flask; fed-batch | - | [118] |
Expansin | pPICZαA | AOX | 5-L bioreactor, fed-batch | 4.3 mg/L | [119] |
Xylanase | pPICZαA | AOX | 7.5-L bioreactor, fed-batch | 2503 U/mL | [120] |
β-xilosidase | pPICZαA | AOX | Shake-flask; fed-batch | 0.22 mg/L | [121] |
Feruloyl esterase | pGAPZαA | GAP | Shake-flask; fed-batch | - | [122] |
Acetyl xylan esterase | pPICZαA | AOX | Shake-flask; fed-batch | 1.5 mg/L | [121] |
α-L-arabinofuranosidase | pPICZαA | AOX | 7.5-L bioreactor, fed-batch | 164 U/mL | [123] |
Mannase | pPIC9K | AOX | 10-L bioreactor, fed-batch | 10.47 g/L | [117] |
Lipase | pPICZαA | AOX | Shake-flask; fed-batch | 145.4 U/mg | [124] |
Heterologous Product | Optimization Strategy | Observed Improvement | Ref |
---|---|---|---|
Erythropoietin (biopharmaceutical product) | Dynamic flux balance analysis (elementary process function integrated with FBA) | The maximum productivity obtained in optimization is 66% higher than the benchmark experimental study | [146] |
Recombinant Human Growth Hormone (rhGH) | Study of sorbitol-methanol co-feeding strategy and results compared with the basic feeding protocol | Under optimal conditions, cell biomass, total protein, and rhGH concentration increased 15%, 99.5%, and 99.4% | [147] |
Sea raven antifreeze protein | A model-based approach to optimize qV in a glycerol/methanol mixed-feed continuous stirred-tank reactor | In the optimized conditions, qV was 2.2 mg/L.h, representing a tenfold increase compared with an initial strategy | [148] |
Growth and AOX-promoter based recombinant protein expression | Adaptive laboratory evolution to improve growth and recombinant protein production in methanol-based growth media | Evolved populations showed increased µ. A selected clone showed increased product titers ranging from a 2.5-fold increase in shake flask batch culture to a 1.8-fold increase in fed-batch cultivation | [149] |
Human 2F5 antigen-binding fragment (Fab) | Development of a novel operational strategy, with carbon-starving periods and elucidation of the µ effects on the protein secretion | Increments up to 50% of both yields and total production were observed. High µ presented an increment up to 8-fold on the production rates | [150] |
Human 2F5 antigen-binding fragment (Fab) | Evaluation of a wide range of oxygen-limiting conditions in chemostat cultivations | Specific conditions that lead to the maximum productivity of the process were determined and resulted in an increase of up to 3-fold in qV and YP/X | [151] |
Human recombinant alpha 1-antitrypsin (A1AT) | A new control system designed for maintaining the μopt during the induction phase. The neural network was applied to adjust and optimize the performance of the robust control system | The newly designed μ-stat control technique enhanced production by up to 1.5 and 2.1 folds in comparison with oxygen-limited fed-batch feeding and mixed feed methods, respectively | [152] |
Human Serum Albumin (HSA) | Dynamic genome-scale metabolic model for glucose-limited, aerobic cultivations for batch and fed-batch cultures | The model suggested that implementation of a decreasing µ during the feed phase of fed-batch culture results in a 25% increase in qV | [153] |
Fab fragment (anti-HIV antibody 2F5) | Model for product accumulation in fed-batch, based on iterative calculation, to optimize the time course of the media feed to maximize qV | Good correlation to the optimized model data, and a 2.2-fold improvement of the volumetric productivity in fed-batch optimal profile | [138] |
Cytochrome P450 enzymes (CYPs) | Rational optimization criteria to optimize production kinetics in bioreactors | Carbon-limiting strategy at the highest µ maximized qP. In the optimum condition, up to threefold increases in terms of qV and yield were achieved in comparison with initial tests | [154] |
Recombinant hepatitis B small surface antigen (rHBsAg) | Optimization of continuous process efficiency by evaluation of D, and comparison with well-established fed-batch mode | Continuous process reaches similar levels of product titer with qV and qP, respectively, about 1.5 and 1.3 times higher than in fed-batch mode | [155] |
Candida rugosa lipase | A combination of strain and bioprocess engineering: different gene dosages compared in chemostat cultures with different oxygen-limiting conditions and hypoxic conditions in carbon-limited fed-batch cultures | Increases of up to 9-fold in the production rates were reached when both strain and bioprocess engineering were improved | [156] |
Candida antartica lipase | Trade-off between fed-batch and continuous. The influence of the μ was examined on various key bioprocess parameters | In continuous mode, the overall production was 5.8 times greater than the fed-batch process | [155] |
Streptomyces ghanaenis L-glutamate oxidase | Study of the effect of feeding strategy on cell growth and enzyme production | The cell density and total enzyme activity were 210 g/L and 118 U/mL, respectively, which represent a 3-fold and 36-fold increase relative to shake flask experiments | [142] |
Trichoderma reesei xylanase | HCDF under optimal parameters | HCDF strategy boosts the amount of enzyme by 40.1-fold in comparison to the shake flask fermentation | [142] |
Rhizopus oryzae lipase | A numerical optimization of mathematical model which includes cell substrate and product kinetics | The optimal profiles were defined, and bioprocess efficiency improvement was confirmed in terms of a 2.2-fold higher final titer and 3.4-fold higher productivity | [157] |
Applicable to different products | Combination of three metabolic models optimized with constraint-based FBA | Simulated values were highly comparable with existing experimental results that outperformed each model. This similarity can be useful to reduce experimental work and costs in optimization process | [158] |
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Carneiro, C.V.G.C.; Serra, L.A.; Pacheco, T.F.; Ferreira, L.M.M.; Brandão, L.T.D.; Freitas, M.N.d.M.; Trichez, D.; Almeida, J.R.M.d. Advances in Komagataella phaffii Engineering for the Production of Renewable Chemicals and Proteins. Fermentation 2022, 8, 575. https://doi.org/10.3390/fermentation8110575
Carneiro CVGC, Serra LA, Pacheco TF, Ferreira LMM, Brandão LTD, Freitas MNdM, Trichez D, Almeida JRMd. Advances in Komagataella phaffii Engineering for the Production of Renewable Chemicals and Proteins. Fermentation. 2022; 8(11):575. https://doi.org/10.3390/fermentation8110575
Chicago/Turabian StyleCarneiro, Clara Vida Galrão Corrêa, Luana Assis Serra, Thályta Fraga Pacheco, Letícia Maria Mallmann Ferreira, Lívia Teixeira Duarte Brandão, Mariana Nogueira de Moura Freitas, Débora Trichez, and João Ricardo Moreira de Almeida. 2022. "Advances in Komagataella phaffii Engineering for the Production of Renewable Chemicals and Proteins" Fermentation 8, no. 11: 575. https://doi.org/10.3390/fermentation8110575
APA StyleCarneiro, C. V. G. C., Serra, L. A., Pacheco, T. F., Ferreira, L. M. M., Brandão, L. T. D., Freitas, M. N. d. M., Trichez, D., & Almeida, J. R. M. d. (2022). Advances in Komagataella phaffii Engineering for the Production of Renewable Chemicals and Proteins. Fermentation, 8(11), 575. https://doi.org/10.3390/fermentation8110575