Carbon-negative production of acetone and isopropanol by gas fermentation at industrial pilot scale.
Journal
Nature biotechnology
ISSN: 1546-1696
Titre abrégé: Nat Biotechnol
Pays: United States
ID NLM: 9604648
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
06
10
2020
accepted:
09
12
2021
pubmed:
23
2
2022
medline:
20
4
2022
entrez:
22
2
2022
Statut:
ppublish
Résumé
Many industrial chemicals that are produced from fossil resources could be manufactured more sustainably through fermentation. Here we describe the development of a carbon-negative fermentation route to producing the industrially important chemicals acetone and isopropanol from abundant, low-cost waste gas feedstocks, such as industrial emissions and syngas. Using a combinatorial pathway library approach, we first mined a historical industrial strain collection for superior enzymes that we used to engineer the autotrophic acetogen Clostridium autoethanogenum. Next, we used omics analysis, kinetic modeling and cell-free prototyping to optimize flux. Finally, we scaled-up our optimized strains for continuous production at rates of up to ~3 g/L/h and ~90% selectivity. Life cycle analysis confirmed a negative carbon footprint for the products. Unlike traditional production processes, which result in release of greenhouse gases, our process fixes carbon. These results show that engineered acetogens enable sustainable, high-efficiency, high-selectivity chemicals production. We expect that our approach can be readily adapted to a wide range of commodity chemicals.
Identifiants
pubmed: 35190685
doi: 10.1038/s41587-021-01195-w
pii: 10.1038/s41587-021-01195-w
doi:
Substances chimiques
Acetone
1364PS73AF
Carbon
7440-44-0
2-Propanol
ND2M416302
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
335-344Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.
Références
Aguado-Deblas, L. et al. Acetone prospect as an additive to allow the use of castor and sunflower oils as drop-in biofuels in diesel/acetone/vegetable oil triple blends for application in diesel engines. Molecules 25, 2935 (2020).
pmcid: 7356534
doi: 10.3390/molecules25122935
Elfasakhany, A. Performance and emissions analysis on using acetone–gasoline fuel blends in spark-ignition engine. Eng. Sci. Technol. Int. J. 19, 1224–1232 (2016).
Anbarasan, P. et al. Integration of chemical catalysis with extractive fermentation to produce fuels. Nature 491, 235–239 (2012).
pubmed: 23135469
doi: 10.1038/nature11594
Ryan, C. F. et al. Synthesis of aviation fuel from bio-derived isophorone. Sustain. Energy Fuels 4, 1088–1092 (2020).
doi: 10.1039/C9SE01014A
Kratzel, A. et al. Inactivation of severe acute respiratory syndrome coronavirus 2 by WHO-recommended hand rub formulations and alcohols. Emerg. Infect. Dis. 26, 1592–1595 (2020).
pubmed: 32284092
pmcid: 7323537
doi: 10.3201/eid2607.200915
Wernet, G. et al. The ecoinvent database version 3 (part I): overview and methodology. Int. J. Life Cycle Assess. 21, 1218–1230 (2016).
doi: 10.1007/s11367-016-1087-8
Jones, D. T. & Woods, D. R. Acetone–butanol fermentation revisited. Microbiol. Rev. 50, 484–524 (1986).
pubmed: 3540574
pmcid: 373084
doi: 10.1128/mr.50.4.484-524.1986
Ismaiel, A. A., Zhu, C. X., Colby, G. D. & Chen, J. S. Purification and characterization of a primary–secondary alcohol dehydrogenase from two strains of Clostridium beijerinckii. J. Bacteriol. 175, 5097–5105 (1993).
pubmed: 8349550
pmcid: 204976
doi: 10.1128/jb.175.16.5097-5105.1993
Hanai, T., Atsumi, S. & Liao, J. C. Engineered synthetic pathway for isopropanol production in Escherichia coli. Appl. Environ. Microbiol. 73, 7814–7818 (2007).
pubmed: 17933911
pmcid: 2168132
doi: 10.1128/AEM.01140-07
May, A. et al. A modified pathway for the production of acetone in Escherichia coli. Metab. Eng. 15, 218–225 (2013).
pubmed: 22906955
doi: 10.1016/j.ymben.2012.08.001
Liang, L. et al. CRISPR EnAbled Trackable genome Engineering for isopropanol production in Escherichia coli. Metab. Eng. 41, 1–10 (2017).
pubmed: 28216108
doi: 10.1016/j.ymben.2017.02.009
Soma, Y., Yamaji, T., Matsuda, F. & Hanai, T. Synthetic metabolic bypass for a metabolic toggle switch enhances acetyl-CoA supply for isopropanol production by Escherichia coli. J. Biosci. Bioeng. 123, 625–633 (2017).
pubmed: 28214243
doi: 10.1016/j.jbiosc.2016.12.009
Jojima, T., Inui, M. & Yukawa, H. Production of isopropanol by metabolically engineered Escherichia coli. Appl. Microbiol. Biotechnol. 77, 1219–1224 (2008).
pubmed: 17987288
doi: 10.1007/s00253-007-1246-8
Jones, S. W. et al. CO
pubmed: 27687501
pmcid: 5056431
doi: 10.1038/ncomms12800
Simpson, S. D. & Köpke, M. Pollution to products: recycling of ‘above ground’ carbon by gas fermentation. Curr. Opin. Biotechnol. 65, 180–189 (2020).
pubmed: 32315931
doi: 10.1016/j.copbio.2020.02.017
Marcellin, E. et al. Low carbon fuels and commodity chemicals from waste gases—systematic approach to understand energy metabolism in a model acetogen. Green Chem. 18, 3020 (2016).
doi: 10.1039/C5GC02708J
Kato, J. et al. Metabolic engineering of Moorella thermoacetica for thermophilic bioconversion of gaseous substrates to a volatile chemical. AMB Express 11, 59 (2021).
pubmed: 33891189
pmcid: 8065083
doi: 10.1186/s13568-021-01220-w
Hoffmeister, S. et al. Acetone production with metabolically engineered strains of Acetobacterium woodii. Metab. Eng. 36, 37–47 (2016).
pubmed: 26971669
doi: 10.1016/j.ymben.2016.03.001
Banerjee, A., Leang, C., Ueki, T., Nevin, K. P. & Lovley, D. R. A lactose-inducible system for metabolic engineering of Clostridium ljungdahlii. Appl. Environ. Microbiol. 80, 2410–2416 (2014).
pubmed: 24509933
pmcid: 3993169
doi: 10.1128/AEM.03666-13
Garrigues, L., Maignien, L., Lombard, E., Singh, J. & Guillouet, S. E. Isopropanol production from carbon dioxide in Cupriavidus necator in a pressurized bioreactor. N. Biotechnol. 56, 16–20 (2020).
pubmed: 31731039
doi: 10.1016/j.nbt.2019.11.005
Lee, H. J., Son, J., Sim, S. J. & Woo, H. M. Metabolic rewiring of synthetic pyruvate dehydrogenase bypasses for acetone production in cyanobacteria. Plant Biotechnol. J. 18, 1860–1868 (2020).
pubmed: 31960579
pmcid: 7415776
doi: 10.1111/pbi.13342
Torella, J. P. et al. Efficient solar-to-fuels production from a hybrid microbial-water-splitting catalyst system. Proc. Natl Acad. Sci. USA 112, 2337–2342 (2015).
pubmed: 25675518
pmcid: 4345567
doi: 10.1073/pnas.1424872112
Hirokawa, Y., Dempo, Y., Fukusaki, E. & Hanai, T. Metabolic engineering for isopropanol production by an engineered cyanobacterium, Synechococcus elongatus PCC 7942, under photosynthetic conditions. J. Biosci. Bioeng. 123, 39–45 (2016).
pubmed: 27613406
doi: 10.1016/j.jbiosc.2016.07.005
Zhou, J., Zhang, H., Zhang, Y., Li, Y. & Ma, Y. Designing and creating a modularized synthetic pathway in cyanobacterium Synechocystis enables production of acetone from carbon dioxide. Metab. Eng. 14, 394–400 (2012).
pubmed: 22475865
doi: 10.1016/j.ymben.2012.03.005
Claassens, N. J., Cotton, C. A. R., Kopljar, D. & Bar-Even, A. Making quantitative sense of electromicrobial production. Nat. Catal. 2, 437–447 (2019).
doi: 10.1038/s41929-019-0272-0
Fast, A. G. & Papoutsakis, E. T. Stoichiometric and energetic analyses of non-photosynthetic CO
doi: 10.1016/j.coche.2012.07.005
Bar-Even, A., Noor, E. & Milo, R. A survey of carbon fixation pathways through a quantitative lens. J. Exp. Bot. 63, 2325–2342 (2012).
pubmed: 22200662
doi: 10.1093/jxb/err417
Köpke, M. et al. Clostridium ljungdahlii represents a microbial production platform based on syngas. Proc. Natl Acad. Sci. USA 107, 13087–13092 (2010).
pubmed: 20616070
pmcid: 2919952
doi: 10.1073/pnas.1004716107
Fackler, N. et al. Stepping on the gas to a circular economy: accelerating development of carbon-negative chemical production from gas fermentation. Ann. Rev. Chem. Biomol. Eng. 12, 439–470 (2021).
doi: 10.1146/annurev-chembioeng-120120-021122
Jin, S. et al. Synthetic biology on acetogenic bacteria for highly efficient conversion of C1 gases to biochemicals. Int. J. Mol. Sci. 21, 7639 (2020).
pmcid: 7589590
doi: 10.3390/ijms21207639
Takors, R. et al. Using gas mixtures of CO, CO
pubmed: 29761637
pmcid: 6011938
doi: 10.1111/1751-7915.13270
Jones, D. T. Applied acetone–butonal fermentation. In: Clostridia: Biotechnology and Medical Applications (eds Dürre, P. & Bahl, H.) 125–168 (Wiley, 2001).
Jones, D. T. & Keis, S. Origins and relationships of industrial solvent-producing clostridial strains. FEMS Microbiol. Rev. 17, 223–232 (1995).
doi: 10.1111/j.1574-6976.1995.tb00206.x
Karim, A. S. et al. In vitro prototyping and rapid optimization of biosynthetic enzymes for cellular design. Nat. Chem. Biol. 16, 912–919 (2020).
pubmed: 32541965
doi: 10.1038/s41589-020-0559-0
Krüger, A. et al. Development of a clostridia-based cell-free system for prototyping genetic parts and metabolic pathways. Metab. Eng. 62, 95–105 (2020).
pubmed: 32540392
doi: 10.1016/j.ymben.2020.06.004
Heap, J. T., Pennington, O. J., Cartman, S. T. & Minton, N. P. A modular system for Clostridium shuttle plasmids. J. Microbiol. Methods 78, 79–85 (2009).
pubmed: 19445976
doi: 10.1016/j.mimet.2009.05.004
Maddock, D. J., Patrick, W. M. & Gerth, M. L. Substitutions at the cofactor phosphate-binding site of a clostridial alcohol dehydrogenase lead to unexpected changes in substrate specificity. Protein Eng. Des. Sel. 28, 251–258 (2015).
pubmed: 26034298
pmcid: 4498498
doi: 10.1093/protein/gzv028
Köpke, M. et al. Reconstruction of an acetogenic 2,3-butanediol pathway involving a novel NADPH-dependent primary–secondary alcohol dehydrogenase. Appl. Environ. Microbiol. 80, 3394–3403 (2014).
pubmed: 24657865
pmcid: 4018851
doi: 10.1128/AEM.00301-14
Valgepea, K. et al. H
pubmed: 29507607
pmcid: 5831606
doi: 10.1186/s13068-018-1052-9
de Souza Pinto Lemgruber, R. et al. Systems-level engineering and characterisation of Clostridium autoethanogenum through heterologous production of poly-3-hydroxybutyrate (PHB). Metab. Eng. 53, 14–23 (2019).
pubmed: 30641139
doi: 10.1016/j.ymben.2019.01.003
Maia, P., Rocha, I. & Rocha, M. Identification of robust strain designs via tandem pFBA/LMOMA phenotype prediction. In: GECCO 2017: Proceedings of the Genetic and Evolutionary Computation Conference Companion 1661–1668 (Association for Computing Machinery, 2017).
Zitzler, E., Laumanns, M. & Thiele, L. SPEA2: improving the Strength Pareto Evolutionary Algorithm. In: Proceedings of the Fifth Conference on Evolutionary Methods for Design 95–100 (Association for Computing Machinery, 2001).
Takanashi, M. & Saito, T. Characterization of two 3-hydroxybutyrate dehydrogenases in poly(3-hydroxybutyrate)-degradable bacterium, Ralstonia pickettii T1. J. Biosci. Bioeng. 101, 501–507 (2006).
pubmed: 16935252
doi: 10.1263/jbb.101.501
Segawa, M., Wen, C., Orita, I., Nakamura, S. & Fukui, T. Two NADH-dependent (S)-3-hydroxyacyl-CoA dehydrogenases from polyhydroxyalkanoate-producing Ralstonia eutropha. J. Biosci. Bioeng. 127, 294–300 (2019).
pubmed: 30243533
doi: 10.1016/j.jbiosc.2018.08.009
Tan, Y., Liu, Z.-Y., Liu, Z. & Li, F.-L. Characterization of an acetoin reductase/2,3-butanediol dehydrogenase from Clostridium ljungdahlii DSM 13528. Enzyme Microb. Technol. 79–80, 1–7 (2015).
pubmed: 26320708
doi: 10.1016/j.enzmictec.2015.06.011
Kim, J., Chang, J. H., Kim, E. J. & Kim, K. J. Crystal structure of (R)-3-hydroxybutyryl-CoA dehydrogenase PhaB from Ralstonia eutropha. Biochem. Biophys. Res. Commun. 443, 783–788 (2014).
pubmed: 24211201
doi: 10.1016/j.bbrc.2013.10.150
Boynton, Z. L., Bennet, G. N. & Rudolph, F. B. Cloning, sequencing, and expression of clustered genes encoding beta-hydroxybutyryl-coenzyme A (CoA) dehydrogenase, crotonase, and butyryl-CoA dehydrogenase from Clostridium acetobutylicum ATCC 824. J. Bacteriol. 178, 3015–3024 (1996).
pubmed: 8655474
pmcid: 178046
doi: 10.1128/jb.178.11.3015-3024.1996
Vick, J. E. et al. Escherichia coli enoyl-acyl carrier protein reductase (FabI) supports efficient operation of a functional reversal of the β-oxidation cycle. Appl. Environ. Microbiol. 81, 1406–1416 (2015).
pubmed: 25527535
pmcid: 4309689
doi: 10.1128/AEM.03521-14
Liew, F. et al. Metabolic engineering of Clostridium autoethanogenum for selective alcohol production. Metab. Eng. 40, 104–114 (2017).
pubmed: 28111249
pmcid: 5367853
doi: 10.1016/j.ymben.2017.01.007
Mahamkali, V. et al. Redox controls metabolic robustness in the gas-fermenting acetogen Clostridium autoethanogenum. Proc. Natl Acad. Sci. USA 117, 13168–13175 (2020).
pubmed: 32471945
pmcid: 7293625
doi: 10.1073/pnas.1919531117
Greene, J., Daniell, J., Köpke, M., Broadbelt, L. & Tyo, K. E. J. Kinetic ensemble model of gas fermenting Clostridium autoethanogenum for improved ethanol production. Biochem. Eng. J. 148, 46–56 (2019).
doi: 10.1016/j.bej.2019.04.021
Wehrs, M. et al. Engineering robust production microbes for large-scale cultivation. Trends Microbiol. 27, 524–537 (2019).
pubmed: 30819548
doi: 10.1016/j.tim.2019.01.006
Hoff, B. et al. Unlocking nature’s biosynthetic power—metabolic engineering for the fermentative production of chemicals. Angew. Chem. Int. Ed. Engl. 60, 2258–2278 (2021).
pubmed: 33026132
doi: 10.1002/anie.202004248
Nielsen, J. & Keasling, J. D. Engineering cellular metabolism. Cell 164, 1185–1197 (2016).
pubmed: 26967285
doi: 10.1016/j.cell.2016.02.004
Crater, J. S. & Lievense, J. C. Scale-up of industrial microbial processes. FEMS Microbiol. Lett. 365, 138 (2018).
doi: 10.1093/femsle/fny138
Bertsch, J. & Müller, V. Bioenergetic constraints for conversion of syngas to biofuels in acetogenic bacteria. Biotechnol. Bioeng. 8, 210 (2015).
Schuchmann, K. & Müller, V. Autotrophy at the thermodynamic limit of life: a model for energy conservation in acetogenic bacteria. Nat. Rev. Microbiol. 12, 809–821 (2014).
pubmed: 25383604
doi: 10.1038/nrmicro3365
Erb, T. J. Back to the future: why we need enzymology to build a synthetic metabolism of the future. Beilstein J. Org. Chem. 15, 551–557 (2019).
pubmed: 30873239
pmcid: 6404388
doi: 10.3762/bjoc.15.49
Diether, M., Nikolaev, Y., Allain, F. H. & Sauer, U. Systematic mapping of protein-metabolite interactions in central metabolism of Escherichia coli. Mol. Syst. Biol. 15, e9008 (2019).
pubmed: 31464375
pmcid: 6706640
doi: 10.15252/msb.20199008
Kim, H. M., Chae, T. U., Choi, S. Y., Kim, W. J. & Lee, S. Y. Engineering of an oleaginous bacterium for the production of fatty acids and fuels. Nat. Chem. Biol. 15, 721–729 (2019).
pubmed: 31209347
doi: 10.1038/s41589-019-0295-5
Amin, S. A., Chavez, E., Porokhin, V., Nair, N. U. & Hassoun, S. Towards creating an extended metabolic model (EMM) for E. coli using enzyme promiscuity prediction and metabolomics data. Microb. Cell Fact. 18, 109 (2019).
pubmed: 31196115
pmcid: 6567437
doi: 10.1186/s12934-019-1156-3
Vögeli, B. et al. Archaeal acetoacetyl-CoA thiolase/HMG-CoA synthase complex channels the intermediate via a fused CoA-binding site. Proc. Natl Acad. Sci. USA 115, 3380–3385 (2018).
pubmed: 29531083
pmcid: 5879682
doi: 10.1073/pnas.1718649115
Chen, I. M. A. et al. The IMG/M data management and analysis system v.6.0: new tools and advanced capabilities. Nucleic Acids Res. 49, D751–D763 (2021).
pubmed: 33119741
doi: 10.1093/nar/gkaa939
Larkin, M. A. et al. Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947–2948 (2007).
doi: 10.1093/bioinformatics/btm404
pubmed: 17846036
Nguyen, L., Schmidt, H. A., Von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2014).
pubmed: 25371430
pmcid: 4271533
doi: 10.1093/molbev/msu300
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).
pubmed: 28481363
pmcid: 5453245
doi: 10.1038/nmeth.4285
Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 47, 256–259 (2019).
doi: 10.1093/nar/gkz239
Fero, M. J., Craft, J. K., Trang, V. & Hillson, N. J. Combinatorial-hierarchical DNA library design using the TeselaGen DESIGN Module with j5. Methods Mol. Biol. 2205, 19–47 (2020).
pubmed: 32809191
doi: 10.1007/978-1-0716-0908-8_2
Liew, F. M. et al. Gas fermentation—a flexible platform for commercial scale production of low-carbon-fuels and chemicals from waste and renewable feedstocks. Front. Microbiol. 7, 694 (2016).
pubmed: 27242719
pmcid: 4862988
doi: 10.3389/fmicb.2016.00694
Valgepea, K. et al. Arginine deiminase pathway provides ATP and boosts growth of the gas-fermenting acetogen Clostridium autoethanogenum. Metab. Eng. 41, 202–211 (2017).
pubmed: 28442386
doi: 10.1016/j.ymben.2017.04.007
Ebrahim, A., Lerman, J. A., Palsson, B. O. & Hyduke, D. R. COBRApy: COnstraints-Based Reconstruction and Analysis for Python. BMC Syst. Biol. 7, 74 (2013).
pubmed: 23927696
pmcid: 3751080
doi: 10.1186/1752-0509-7-74
Gonçalves, E., Pereira, R., Rocha, I. & Rocha, M. Optimization approaches for the in silico discovery of optimal targets for gene over/underexpression. J. Comput. Biol. 19, 102–114 (2012).
pubmed: 22300313
doi: 10.1089/cmb.2011.0265
Kwon, Y. C. & Jewett, M. C. High-throughput preparation methods of crude extract for robust cell-free protein synthesis. Sci. Rep. 5, 8663 (2015).
pubmed: 25727242
pmcid: 4345344
doi: 10.1038/srep08663
Jewett, M. C. & Swartz, J. R. Mimicking the Escherichia coli cytoplasmic environment activates long-lived and efficient cell-free protein synthesis. Biotechnol. Bioeng. 86, 19–26 (2004).
pubmed: 15007837
doi: 10.1002/bit.20026
Jewett, M. C., Calhoun, K. A., Voloshin, A., Wuu, J. J. & Swartz, J. R. An integrated cell-free metabolic platform for protein production and synthetic biology. Mol. Syst. Biol. 4, 220 (2008).
pubmed: 18854819
pmcid: 2583083
doi: 10.1038/msb.2008.57
Karim, A. S., Rasor, B. J. & Jewett, M. C. Enhancing control of cell-free metabolism through pH modulation. Synth. Biol. 5, ysz027 (2020).
doi: 10.1093/synbio/ysz027
Batth, T. S. et al. Protein aggregation capture on microparticles enables multipurpose proteomics sample preparation. Mol. Cell. Proteomics 18, 1027–1035 (2019).
pubmed: 30833379
pmcid: 6495262
doi: 10.1074/mcp.TIR118.001270
Walker, C., Ryu, S., Giannone, R. J., Garcia, S. & Trinh, C. T. Understanding and eliminating the detrimental effect of thiamine deficiency on the oleaginous yeast Yarrowia lipolytica. Appl. Environ. Microbiol 86, e02299–19 (2020).
pubmed: 31704686
pmcid: 6974654
doi: 10.1128/AEM.02299-19
Taverner, T. et al. DanteR: an extensible R-based tool for quantitative analysis of -omics data. Bioinformatics 28, 2404–2406 (2012).
pubmed: 22815360
pmcid: 3436848
doi: 10.1093/bioinformatics/bts449
Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).
pubmed: 27348712
doi: 10.1038/nmeth.3901