Boosting succinic acid production of Yarrowia lipolytica at low pH through enhancing product tolerance and glucose metabolism.


Journal

Microbial cell factories
ISSN: 1475-2859
Titre abrégé: Microb Cell Fact
Pays: England
ID NLM: 101139812

Informations de publication

Date de publication:
24 Oct 2024
Historique:
received: 13 07 2024
accepted: 11 10 2024
medline: 24 10 2024
pubmed: 24 10 2024
entrez: 24 10 2024
Statut: epublish

Résumé

Succinic acid (SA) is an important bio-based C4 platform chemical with versatile applications, including the production of 1,4-butanediol, tetrahydrofuran, and γ-butyrolactone. The non-conventional yeast Yarrowia lipolytica has garnered substantial interest as a robust cell factory for SA production at low pH. However, the high concentrations of SA, especially under acidic conditions, can impose significant stress on microbial cells, leading to reduced glucose metabolism viability and compromised production performance. Therefore, it is important to develop Y. lipolytica strains with enhanced SA tolerance for industrial-scale SA production. An SA-tolerant Y. lipolytica strain E501 with improved SA production was obtained through adaptive laboratory evolution (ALE). In a 5-L bioreactor, the evolved strain E501 produced 89.62 g/L SA, representing a 7.2% increase over the starting strain Hi-SA2. Genome resequencing and transcriptome analysis identified a mutation in the 26S proteasome regulatory subunit Rpn1, as well as genes involved in transmembrane transport, which may be associated with enhanced SA tolerance. By further fine-tuning the glycolytic pathway flux, the highest SA titer of 112.54 g/L to date at low pH was achieved, with a yield of 0.67 g/g glucose and a productivity of 2.08 g/L/h. This study provided a robust engineered Y. lipolytica strain capable of efficiently producing SA at low pH, thereby reducing the cost of industrial SA fermentation.

Sections du résumé

BACKGROUND BACKGROUND
Succinic acid (SA) is an important bio-based C4 platform chemical with versatile applications, including the production of 1,4-butanediol, tetrahydrofuran, and γ-butyrolactone. The non-conventional yeast Yarrowia lipolytica has garnered substantial interest as a robust cell factory for SA production at low pH. However, the high concentrations of SA, especially under acidic conditions, can impose significant stress on microbial cells, leading to reduced glucose metabolism viability and compromised production performance. Therefore, it is important to develop Y. lipolytica strains with enhanced SA tolerance for industrial-scale SA production.
RESULTS RESULTS
An SA-tolerant Y. lipolytica strain E501 with improved SA production was obtained through adaptive laboratory evolution (ALE). In a 5-L bioreactor, the evolved strain E501 produced 89.62 g/L SA, representing a 7.2% increase over the starting strain Hi-SA2. Genome resequencing and transcriptome analysis identified a mutation in the 26S proteasome regulatory subunit Rpn1, as well as genes involved in transmembrane transport, which may be associated with enhanced SA tolerance. By further fine-tuning the glycolytic pathway flux, the highest SA titer of 112.54 g/L to date at low pH was achieved, with a yield of 0.67 g/g glucose and a productivity of 2.08 g/L/h.
CONCLUSION CONCLUSIONS
This study provided a robust engineered Y. lipolytica strain capable of efficiently producing SA at low pH, thereby reducing the cost of industrial SA fermentation.

Identifiants

pubmed: 39443950
doi: 10.1186/s12934-024-02565-0
pii: 10.1186/s12934-024-02565-0
doi:

Substances chimiques

Glucose IY9XDZ35W2
Succinic Acid AB6MNQ6J6L

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

291

Subventions

Organisme : National Natural Science Foundation of Shandong Province
ID : ZR2022ZD24
Organisme : National Natural Science Foundation of China
ID : 22208192
Organisme : Major Scientific and Technological Innovation Project of Shandong Province
ID : 2022CXGC020712-4

Informations de copyright

© 2024. The Author(s).

Références

Jiang M, Ma J, Wu M, Liu R, Liang L, Xin F, Zhang W, Jia H, Dong W. Progress of succinic acid production from renewable resources: metabolic and fermentative strategies. Bioresour Technol. 2017;245(Pt B):1710–7. https://doi.org/10.1016/j.biortech.2017.05.209
doi: 10.1016/j.biortech.2017.05.209 pubmed: 28622981
Delhomme C, Weuster-Botz D, Kühn FE. Succinic acid from renewable resources as a C4 building-block chemical-a review of the catalytic possibilities in aqueous media. Green Chem 2009, 11(1):13–26. https://doi.org/10.1039/b810684c
Dai ZX, Guo F, Zhang SJ, Zhang WM, Yang Q, Dong WL, Jiang M, Ma JF, Xin FX. Bio-based succinic acid: an overview of strain development, substrate utilization, and downstream purification. Biofuel Bioprod Bior. 2020;14(5):965–85. https://doi.org/10.1002/bbb.2063
doi: 10.1002/bbb.2063
Dusselier M, Mascal M, Sels BF. Top chemical opportunities from carbohydrate biomass: a chemist’s view of the Biorefinery. Top Curr Chem. 2014;353:1–40. https://doi.org/10.1007/128_2014_544
doi: 10.1007/128_2014_544 pubmed: 24842622
McKinlay JB, Vieille C, Zeikus JG. Prospects for a bio-based succinate industry. Appl Microbiol Biotechnol. 2007;76(4):727–40. https://doi.org/10.1007/s00253-007-1057-y
doi: 10.1007/s00253-007-1057-y pubmed: 17609945
Choi S, Song CW, Shin JH, Lee SY. Biorefineries for the production of top building block chemicals and their derivatives. Metab Eng. 2015;28:223–39. https://doi.org/10.1016/j.ymben.2014.12.007
doi: 10.1016/j.ymben.2014.12.007 pubmed: 25576747
Pinazo JM, Domine ME, Parvulescu V, Petru F. Sustainability metrics for succinic acid production: a comparison between biomass-based and petrochemical routes. Catal Today. 2015;239:17–24. https://doi.org/10.1016/j.cattod.2014.05.035
doi: 10.1016/j.cattod.2014.05.035
Ahn JH, Jang YS, Lee SY. Production of succinic acid by metabolically engineered microorganisms. Curr Opin Biotechnol. 2016;42:54–66. https://doi.org/10.1016/j.copbio.2016.02.034
doi: 10.1016/j.copbio.2016.02.034 pubmed: 26990278
Muscat A, de Olde EM, Ripoll-Bosch R, Van Zanten HHE, Metze TAP, Termeer C, van Ittersum MK, de Boer IJM. Principles, drivers and opportunities of a circular bioeconomy. Nat Food 2021, 2(8):561–6. https://doi.org/10.1038/s43016-021-00340-7
Raj T, Chandrasekhar K, Kumar AN, Kim SH. Lignocellulosic biomass as renewable feedstock for biodegradable and recyclable plastics production: a sustainable approach. Renew Sust Energ Rev 2022, 158. https://doi.org/10.1016/j.rser.2022.112130
Jansen ML, van Gulik WM. Towards large scale fermentative production of succinic acid. Curr Opin Biotechnol. 2014;30:190–7. https://doi.org/10.1016/j.copbio.2014.07.003
doi: 10.1016/j.copbio.2014.07.003 pubmed: 25118136
Yin X, Li J, Shin HD, Du G, Liu L, Chen J. Metabolic engineering in the biotechnological production of organic acids in the tricarboxylic acid cycle of microorganisms: advances and prospects. Biotechnol Adv 2015, 33(6 Pt 1):830–41. https://doi.org/10.1016/j.biotechadv.2015.04.006
Kumar R, Basak B, Jeon BH. Sustainable production and purification of succinic acid: a review of membrane-integrated green approach. J Clean Prod. 2020;277. https://doi.org/10.1016/j.jclepro.2020.123954
Lund PA, De Biase D, Liran O, Scheler O, Mira NP, Cetecioglu Z, Fernández EN, Bover-Cid S, Hall R, Sauer M, et al. Understanding how microorganisms respond to Acid pH is Central to their control and successful Exploitation. Front Microbiol. 2020;11. https://doi.org/10.3389/fmicb.2020.556140
Liu HH, Ji XJ, Huang H. Biotechnological applications of Yarrowia lipolytica: past, present and future. Biotechnol Adv 2015, 33(8):1522–46. https://doi.org/10.1016/j.biotechadv.2015.07.010
Abdel-Mawgoud AM, Markham KA, Palmer CM, Liu N, Stephanopoulos G, Alper HS. Metabolic engineering in the host Yarrowia lipolytica. Metab Eng. 2018;50:192–208. https://doi.org/10.1016/j.ymben.2018.07.016
doi: 10.1016/j.ymben.2018.07.016 pubmed: 30056205
Gonçalves FAG, Colen G, Takahashi JA. Yarrowia lipolytica and its multiple applications in the biotechnological industry. Sci World J 2014. https://doi.org/10.1155/2014/476207
Cui Z, Zhong Y, Sun Z, Jiang Z, Deng J, Wang Q, Nielsen J, Hou J, Qi Q. Reconfiguration of the reductive TCA cycle enables high-level succinic acid production by Yarrowia lipolytica. Nat Commun 2023, 14(1):8480. https://doi.org/10.1038/s41467-023-44245-4
Yuzbashev TV, Bondarenko PY, Sobolevskaya TI, Yuzbasheva EY, Laptev IA, Kachala VV, Fedorov AS, Vybornaya TV, Larina AS, Sineoky SP. Metabolic evolution and
doi: 10.1002/bit.26007 pubmed: 27182846
Li C, Gao S, Li X, Yang X, Lin CSK. Efficient metabolic evolution of engineered Yarrowia lipolytica for succinic acid production using a glucose-based medium in an in situ fibrous bioreactor under low-pH condition. Biotechnol Biofuels 2018, 11:236. https://doi.org/10.1186/s13068-018-1233-6
Cui Z, Gao C, Li J, Hou J, Lin CSK, Qi Q. Engineering of unconventional yeast Yarrowia lipolytica for efficient succinic acid production from glycerol at low pH. Metab Eng 2017, 42:126–33. https://doi.org/10.1016/j.ymben.2017.06.007
Yu QL, Cui ZY, Zheng YQ, Huo HL, Meng LL, Xu JJ, Gao CJ. Exploring succinic acid production by engineered Yarrowia lipolytica strains using glucose at low pH. Biochem Eng J 2018, 139:51–6. https://doi.org/10.1016/j.bej.2018.08.001
Tran VG, Zhao H. Engineering robust microorganisms for organic acid production. J Ind Microbiol Biotechnol. 2022;49(2). https://doi.org/10.1093/jimb/kuab067
Sandberg TE, Salazar MJ, Weng LL, Palsson BO, Feist AM. The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology. Metab Eng. 2019;56:1–16. https://doi.org/10.1016/j.ymben.2019.08.004
doi: 10.1016/j.ymben.2019.08.004 pubmed: 31401242 pmcid: 6944292
Wang G, Li Q, Zhang Z, Yin X, Wang B, Yang X. Recent progress in adaptive laboratory evolution of industrial microorganisms. J Ind Microbiol Biotechnol. 2023;50(1). https://doi.org/10.1093/jimb/kuac023
Qi X, Wang Z, Lin Y, Guo Y, Dai Z, Wang Q. Elucidation and engineering mitochondrial respiratory-related genes for improving bioethanol production at high temperature in Saccharomyces cerevisiae. Eng Microbiol 2024, 4(2). https://doi.org/10.1016/j.engmic.2023.100108
Chen C, Li Y-W, Chen X-Y, Wang Y-T, Ye C, Shi T-Q. Application of adaptive laboratory evolution for Yarrowia lipolytica: a comprehensive review. Bioresour Technol. 2024;391. https://doi.org/10.1016/j.biortech.2023.129893
Zhu P, Luo R, Li Y, Chen X. Metabolic Engineering and adaptive evolution for efficient production of L-lactic acid in Saccharomyces cerevisiae. Microbiol Spectr. 2022;10(6):e0227722. https://doi.org/10.1128/spectrum.02277-22
doi: 10.1128/spectrum.02277-22 pubmed: 36354322
Zhang WM, Tao YX, Wu M, Xin FX, Dong WL, Zhou J, Gu JC, Ma JF, Jiang M. Adaptive evolution improves acid tolerance and succinic acid production in Actinobacillus succinogenes. Process Biochem 2020, 98:76–82. https://doi.org/10.1016/j.procbio.2020.08.003
Kim D, Song JY, Hahn JS. Improvement of glucose uptake rate and production of target chemicals by overexpressing hexose transporters and transcriptional activator Gcr1 in Saccharomyces cerevisiae. Appl Environ Microbiol 2015, 81(24):8392–401. https://doi.org/10.1128/AEM.02056-15
Yamada R, Wakita K, Ogino H. Global Metabolic engineering of glycolytic pathway via multicopy integration in Saccharomyces cerevisiae. ACS Synth Biol. 2017;6(4):659–66. https://doi.org/10.1021/acssynbio.6b00281
doi: 10.1021/acssynbio.6b00281 pubmed: 28080037
Tan SZ, Manchester S, Prather KL. Controlling central carbon metabolism for improved pathway yields in Saccharomyces cerevisiae. ACS Synth Biol. 2016;5(2):116–24. https://doi.org/10.1021/acssynbio.5b00164
doi: 10.1021/acssynbio.5b00164 pubmed: 26544022
Zhang L, Li YL, Hu JH, Liu ZY. Overexpression of enzymes in glycolysis and energy metabolic pathways to enhance coenzyme Q10 production in Rhodobacter sphaeroides VK-2-3. Front Microbiol 2022, 13:931470. https://doi.org/10.3389/fmicb.2022.931470
Lim JH, Jung GY. A simple method to control glycolytic flux for the design of an optimal cell factory. Biotechnol Biofuels. 2017;10. https://doi.org/10.1186/s13068-017-0847-4
Xu Y, Zhou Y, Cao W, Liu H. Improved production of malic acid in Aspergillus niger by abolishing citric acid accumulation and enhancing glycolytic flux. ACS Synth Biol. 2020;9(6):1418–25. https://doi.org/10.1021/acssynbio.0c00096
doi: 10.1021/acssynbio.0c00096 pubmed: 32379964
Cui Z, Jiang X, Zheng H, Qi Q, Hou J. Homology-independent genome integration enables rapid library construction for enzyme expression and pathway optimization in Yarrowia lipolytica. Biotechnol Bioeng. 2019;116(2):354–63.
doi: 10.1002/bit.26863 pubmed: 30418662
Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12(4):357–60. https://doi.org/10.1038/nmeth.3317
doi: 10.1038/nmeth.3317 pubmed: 25751142 pmcid: 4655817
Anders S, Pyl PT, Huber W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31(2):166–9. https://doi.org/10.1093/bioinformatics/btu638
doi: 10.1093/bioinformatics/btu638 pubmed: 25260700
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. https://doi.org/10.1186/s13059-014-0550-8
doi: 10.1186/s13059-014-0550-8 pubmed: 25516281 pmcid: 4302049
Boughton AJ, Zhang D, Singh RK, Fushman D. Polyubiquitin and ubiquitin-like signals share common recognition sites on proteasomal subunit Rpn1. J Biol Chem 2021, 296:100450. https://doi.org/10.1016/j.jbc.2021.100450
Boughton AJ, Liu L, Lavy T, Kleifeld O, Fushman D. A novel recognition site for polyubiquitin and ubiquitin-like signals in an unexpected region of proteasomal subunit Rpn1. J Biol Chem. 2021;297(3):101052. https://doi.org/10.1016/j.jbc.2021.101052
doi: 10.1016/j.jbc.2021.101052 pubmed: 34364874 pmcid: 8405992
Goldberg AL. Protein degradation and protection against misfolded or damaged proteins. Nature. 2003;426(6968):895–9. https://doi.org/10.1038/nature02263
doi: 10.1038/nature02263 pubmed: 14685250
Wang X, Xu H, Ha SW, Ju D, Xie Y. Proteasomal degradation of Rpn4 in Saccharomyces cerevisiae is critical for cell viability under stressed conditions. Genetics. 2010;184(2):335–42. https://doi.org/10.1534/genetics.109.112227
doi: 10.1534/genetics.109.112227 pubmed: 19933873 pmcid: 2828715
Wang X, Xu H, Ju D, Xie Y. Disruption of Rpn4-induced proteasome expression in Saccharomyces cerevisiae reduces cell viability under stressed conditions. Genetics. 2008;180(4):1945–53. https://doi.org/10.1534/genetics.108.094524
doi: 10.1534/genetics.108.094524 pubmed: 18832351 pmcid: 2600933
Xi Y, Zhan T, Xu H, Chen J, Bi C, Fan F, Zhang X. Characterization of JEN family carboxylate transporters from the acid-tolerant yeast Pichia kudriavzevii and their applications in succinic acid production. Microb Biotechnol. 2021;14(3):1130–47. https://doi.org/10.1111/1751-7915.13781
doi: 10.1111/1751-7915.13781 pubmed: 33629807 pmcid: 8085920
Dulermo R, Gamboa-Melendez H, Michely S, Thevenieau F, Neuveglise C, Nicaud JM. The evolution of Jen3 proteins and their role in dicarboxylic acid transport in Yarrowia. Volume 4. Microbiologyopen; 2015. pp. 100–20. 1 https://doi.org/10.1002/mbo3.225
Lv X, Xue H, Qin L, Li C. Transporter engineering in microbial cell factory boosts biomanufacturing capacity. Biodes Res 2022, 2022:9871087. https://doi.org/10.34133/2022/9871087
Madshus IH. Regulation of intracellular pH in eukaryotic cells. Biochem J. 1988;250(1):1–8. https://doi.org/10.1042/bj2500001
doi: 10.1042/bj2500001 pubmed: 2965576 pmcid: 1148806
Sekova VY, Dergacheva DI, Isakova EP, Gessler NN, Tereshina VM, Deryabina YI. Soluble sugar and lipid readjustments in the Yarrowia lipolytica yeast at various temperatures and pH. Metabolites. 2019;9(12). https://doi.org/10.3390/metabo9120307
Sassi H, Delvigne F, Kallel H, Fickers P. pH and not cell morphology modulate pLIP2 induction in the dimorphic yeast Yarrowia lipolytica. Curr Microbiol 2017, 74(3):413–7. https://doi.org/10.1007/s00284-017-1207-0
Gong Z, Nielsen J, Zhou YJ. Engineering robustness of microbial cell factories. Biotechnol J 2017, 12(10). https://doi.org/10.1002/biot.201700014
Wang S, Sun X, Yuan Q. Strategies for enhancing microbial tolerance to inhibitors for biofuel production: a review. Bioresour Technol. 2018;258:302–9. https://doi.org/10.1016/j.biortech.2018.03.064
doi: 10.1016/j.biortech.2018.03.064 pubmed: 29567023
Hasegawa S, Tanaka Y, Suda M, Jojima T, Inui M. Enhanced glucose consumption and organic acid production by engineered Corynebacterium glutamicum based on analysis of a pfkB1 deletion mutant. Appl Environ Microbiol. 2017;83(3). https://doi.org/10.1128/AEM.02638-16

Auteurs

Yutao Zhong (Y)

State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, P. R. China.

Changyu Shang (C)

State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, P. R. China.

Huilin Tao (H)

State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, P. R. China.

Jin Hou (J)

State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, P. R. China.

Zhiyong Cui (Z)

State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, P. R. China. cuizhiyong@sdu.edu.cn.

Qingsheng Qi (Q)

State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, P. R. China. qiqingsheng@sdu.edu.cn.

Articles similaires

Aspergillus Hydrogen-Ion Concentration Coculture Techniques Secondary Metabolism Streptomyces rimosus
Saccharomyces cerevisiae Aldehydes Biotransformation Flavoring Agents Lipoxygenase
Animals Rumen Methane Fermentation Cannabis

Metabolic engineering of

Jae Sung Cho, Zi Wei Luo, Cheon Woo Moon et al.
1.00
Corynebacterium glutamicum Metabolic Engineering Dicarboxylic Acids Pyridines Pyrones

Classifications MeSH