Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Rescuing yeast from cell death enables overproduction of fatty acids from sole methanol

Nature Metabolism volume 4, pages 932–943 (2022)Cite this article

Subjects

Abstract

Methanol is an ideal feedstock for biomanufacturing that can be beneficial for global carbon neutrality; however, the toxicity of methanol limits the efficiency of methanol metabolism toward biochemical production. We here show that engineering production of free fatty acids from sole methanol results in cell death with decreased cellular levels of phospholipids in the methylotrophic yeast Ogataea polymorpha, and cell growth is restored by adaptive laboratory evolution. Whole-genome sequencing of the adapted strains reveals that inactivation of LPL1 (encoding a putative lipase) and IZH3 (encoding a membrane protein related to zinc metabolism) preserve cell survival by restoring phospholipid metabolism. Engineering the pentose phosphate pathway and gluconeogenesis enables high-level production of free fatty acid (15.9 g l−1) from sole methanol. Preventing methanol-associated toxicity underscores the link between lipid metabolism and methanol tolerance, which should contribute to enhancing methanol-based biomanufacturing.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Engineering fatty acid production from methanol resulted in cell death.
Fig. 2: Genome sequencing of evolved strains revealed two key mutations that restored cell growth of faa1Δ strain and enhanced tolerance of wild-type strain in methanol medium.
Fig. 3: Decreased phospholipids levels caused cell death via necrosis during fatty acid accumulation of faa1Δ strain in methanol.
Fig. 4: DEGs related to central metabolism and their effect on methanol utilization.
Fig. 5: Engineering O. polymorpha to improve FFA production from methanol.
Fig. 6: Fed-batch fermentation of strain HpFAM16u in bioreactor.

Data availability

The data that support the findings of this study are available within the article, Supplementary Information files and source data files linked to each figure. Source data are provided with this paper.

Code availability

No custom code was used in this paper. GC–MS and LC–MS data analysis were performed using published software, as indicated in Methods.

References

  1. Saha, D., Grappe, H. A., Chakraborty, A. & Orkoulas, G. Postextraction separation, on-board storage and catalytic conversion of methane in natural gas: a review. Chem. Rev. 116, 11436–11499 (2016).

    Article  CAS  PubMed  Google Scholar 

  2. Olah, G. A. Towards oil independence through renewable methanol chemistry. Angew. Chem. Int. Ed. 52, 104–107 (2013).

    Article  CAS  Google Scholar 

  3. Li, H. et al. Na+-gated water-conducting nanochannels for boosting CO2 conversion to liquid fuels. Science 367, 667–671 (2020).

    Article  CAS  PubMed  Google Scholar 

  4. Kattel, S., Ramírez, P. J., Chen, J. G., Rodriguez, J. A. & Liu, P. Active sites for CO2 hydrogenation to methanol on Cu/ZnO catalysts. Science 355, 1296–1299 (2017).

    Article  CAS  PubMed  Google Scholar 

  5. Graciani, J. et al. Highly active copper-ceria and copper-ceria-titania catalysts for methanol synthesis from CO2. Science 345, 546–550 (2014).

    Article  CAS  PubMed  Google Scholar 

  6. Tian, P., Wei, Y., Ye, M. & Liu, Z. Methanol to olefins (MTO): from fundamentals to commercialization. ACS Catal. 5, 1922–1938 (2015).

    Article  CAS  Google Scholar 

  7. Cotton, C. A., Claassens, N. J., Benito-Vaquerizo, S. & Bar-Even, A. Renewable methanol and formate as microbial feedstocks. Curr. Opin. Biotechnol. 62, 168–180 (2020).

    Article  CAS  PubMed  Google Scholar 

  8. Zhou, Y. J., Kerkhoven, E. J. & Nielsen, J. Barriers and opportunities in bio-based production of hydrocarbons. Nat. Energy 3, 925–935 (2018).

    Article  CAS  Google Scholar 

  9. Clomburg, J. M., Crumbley, A. M. & Gonzalez, R. Industrial biomanufacturing: The future of chemical production. Science 355, aag0804 (2017).

    Article  PubMed  CAS  Google Scholar 

  10. Moore, R. H. et al. Biofuel blending reduces particle emissions from aircraft engines at cruise conditions. Nature 543, 411–415 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Liu, Y. et al. Biofuels for a sustainable future. Cell 184, 1636–1647 (2021).

    Article  CAS  PubMed  Google Scholar 

  12. Haber, C. L., Allen, L. N., Zhao, S. & Hanson, R. S. Methylotrophic bacteria: biochemical diversity and genetics. Science 221, 1147–1153 (1983).

    Article  CAS  PubMed  Google Scholar 

  13. Jiang, W. et al. Metabolic engineering strategies to enable microbial utilization of C1 feedstocks. Nat. Chem. Biol. 17, 845–855 (2021).

    Article  CAS  PubMed  Google Scholar 

  14. Yuan, X. J. et al. Rewiring the native methanol assimilation metabolism by incorporating the heterologous ribulose monophosphate cycle into Methylorubrum extorquens. Metab. Eng. 64, 95–110 (2021).

    Article  CAS  PubMed  Google Scholar 

  15. Chen, Y. H., Jung, H. W., Tsuei, C. Y. & Liao, J. C. Converting Escherichia coli to a synthetic methylotroph growing solely on methanol. Cell 182, 933–946 (2020).

    Article  CAS  PubMed  Google Scholar 

  16. Keller, P. et al. Methanol-dependent Escherichia coli strains with a complete ribulose monophosphate cycle. Nat. Commun. 11, 5403 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Tuyishime, P. et al. Engineering Corynebacterium glutamicum for methanol-dependent growth and glutamate production. Metab. Eng. 49, 220–231 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. Dai, Z. et al. Metabolic construction strategies for direct methanol utilization in Saccharomyces cerevisiae. Bioresour. Technol. 245, 1407–1412 (2017).

    Article  CAS  PubMed  Google Scholar 

  19. Meadows, A. L. et al. Rewriting yeast central carbon metabolism for industrial isoprenoid production. Nature 537, 694–697 (2016).

    Article  CAS  PubMed  Google Scholar 

  20. Yu, T. et al. Reprogramming yeast metabolism from alcoholic fermentation to lipogenesis. Cell 174, 1549–1558 (2018).

    Article  CAS  PubMed  Google Scholar 

  21. Yamada, R., Ogura, K., Kimoto, Y. & Ogino, H. Toward the construction of a technology platform for chemicals production from methanol: D-lactic acid production from methanol by an engineered yeast Pichia pastoris. World J. Microbiol. Biotechnol. 35, 37 (2019).

    Article  PubMed  CAS  Google Scholar 

  22. Guo, F., Dai, Z., Peng, W., Zhang, S. & Jiang, M. Metabolic engineering of Pichia pastoris for malic acid production from methanol. Biotechnol. Bioeng. 118, 357–371 (2020).

    Article  PubMed  CAS  Google Scholar 

  23. Rebello, S. et al. Non-conventional yeast cell factories for sustainable bioprocesses. FEMS Microbiol. Lett. 365, fny222 (2018).

    CAS  Google Scholar 

  24. Gao, J., Gao, N., Zhai, X. & Zhou, Y. J. Recombination machinery engineering for precise genome editing in methylotrophic yeast Ogataea polymorpha. iScience 24, 102168 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Li, X. et al. Metabolic network remodelling enhances yeast’s fitness on xylose using aerobic glycolysis. Nat. Catal. 4, 783–796 (2021).

    Article  CAS  Google Scholar 

  26. Selvaraju, K., Rajakumar, S. & Nachiappan, V. Identification of a phospholipase B encoded by the LPL1 gene in Saccharomyces cerevisiae. Biochim. Biophys. Acta Mol. Cell Biol. Lipids 1841, 1383–1392 (2014).

    Article  CAS  Google Scholar 

  27. Morton, C. O., Dos Santos, S. C. & Coote, P. An amphibian-derived, cationic, α-helical antimicrobial peptide kills yeast by caspase-independent but AIF-dependent programmed cell death. Mol. Microbiol. 65, 494–507 (2007).

    Article  CAS  PubMed  Google Scholar 

  28. Eisenberg, T., Carmona-Gutierrez, D., Büttner, S., Tavernarakis, N. & Madeo, F. Necrosis in yeast. Apoptosis 15, 257–268 (2010).

    Article  PubMed  Google Scholar 

  29. Mirisola, M. G., Braun, R. J. & Petranovic, D. Approaches to study yeast cell aging and death. FEMS Yeast Res. 14, 109–118 (2014).

    Article  CAS  PubMed  Google Scholar 

  30. Davis, D. A. How human pathogenic fungi sense and adapt to pH: the link to virulence. Curr. Opin. Microbiol. 12, 365–370 (2009).

    Article  CAS  PubMed  Google Scholar 

  31. Rockenfeller, P. & Gourlay, C. W. Lipotoxicty in yeast: a focus on plasma membrane signalling and membrane contact sites. FEMS Yeast Res. 18, foy034 (2018).

    Article  PubMed Central  CAS  Google Scholar 

  32. Flis, V. V. et al. Phosphatidylcholine supply to peroxisomes of the yeast Saccharomyces cerevisiae. PLoS ONE 10, e0135084 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Færgeman, N. J., Black, P. N., Zhao, X. D., Knudsen, J. & DiRusso, C. C. The acyl-CoA synthetases encoded within FAA1 and FAA4 in Saccharomyces cerevisiae function as components of the fatty acid transport system linking import, activation, and intracellular utilization. J. Biol. Chem. 276, 37051–37059 (2001).

    Article  PubMed  Google Scholar 

  34. Ploier, B., Daum, G. & Petrovič, U. Molecular mechanisms in yeast carbon metabolism: lipid metabolism and lipidomics. in Molecular Mechanisms in Yeast Carbon Metabolism (eds Piškur, J. & Compagno, C.) 169–215. https://link.springer.com/chapter/10.1007/978-3-642-55013-3_8 (Springer, 2014).

  35. Xue, Z. et al. Production of omega-3 eicosapentaenoic acid by metabolic engineering of Yarrowia lipolytica. Nat. Biotechnol. 31, 734–740 (2013).

    Article  CAS  PubMed  Google Scholar 

  36. Zhou, Y. J. et al. Production of fatty acid-derived oleochemicals and biofuels by synthetic yeast cell factories. Nat. Commun. 7, 1–9 (2016).

    Google Scholar 

  37. Bocanegra, J. A., Scrutton, N. S. & Perham, R. N. Creation of an NADP-dependent pyruvate dehydrogenase multienzyme complex by protein engineering. Biochemistry 32, 2737–2740 (1993).

    Article  CAS  PubMed  Google Scholar 

  38. Partow, S., Hyland, P. B. & Mahadevan, R. Synthetic rescue couples NADPH generation to metabolite overproduction in Saccharomyces cerevisiae. Metab. Eng. 43, 64–70 (2017).

    Article  CAS  PubMed  Google Scholar 

  39. Qiao, K., Wasylenko, T. M., Zhou, K., Xu, P. & Stephanopoulos, G. Lipid production in Yarrowia lipolytica is maximized by engineering cytosolic redox metabolism. Nat. Biotechnol. 35, 173–177 (2017).

    Article  CAS  PubMed  Google Scholar 

  40. Nielsen, J. & Keasling, J. D. Engineering cellular metabolism. Cell 164, 1185–1197 (2016).

    Article  CAS  PubMed  Google Scholar 

  41. Gleizer, S. et al. Conversion of Escherichia coli to generate all biomass carbon from CO2. Cell 179, 1255–1263 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Gassler, T. et al. The industrial yeast Pichia pastoris is converted from a heterotroph into an autotroph capable of growth on CO2. Nat. Biotechnol. 38, 210–216 (2020).

    Article  CAS  PubMed  Google Scholar 

  43. Bang, J., Hwang, C. H., Ahn, J. H., Lee, J. A. & Lee, S. Y. Escherichia coli is engineered to grow on CO2 and formic acid. Nat. Microbiol. 5, 1459–1463 (2020).

    Article  CAS  PubMed  Google Scholar 

  44. Chou, A., Lee, S. H., Zhu, F., Clomburg, J. M. & Gonzalez, R. An orthogonal metabolic framework for one-carbon utilization. Nat. Metab. 3, 1385–1399 (2021).

    Article  CAS  PubMed  Google Scholar 

  45. Yu, W., Gao, J., Zhai, X. & Zhou, Y. J. Screening neutral sites for metabolic engineering of methylotrophic yeast Ogataea polymorpha. Synth. Syst. Biotechnol. 6, 63–68 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Krüsemann, J. L. et al. Artificial pathway emergence in central metabolism from three recursive phosphoketolase reactions. FEBS J. 285, 4367–4377 (2018).

    Article  PubMed  CAS  Google Scholar 

  47. Xuan, Q. et al. Development of a high coverage pseudotargeted lipidomics method based on ultra-high performance liquid chromatography–mass spectrometry. Anal. Chem. 90, 7608–7616 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. San, K. Y. et al. Metabolic Engineering through cofactor manipulation and its effects on metabolic flux redistribution in Escherichia coli. Metab. Eng. 4, 182–192 (2002).

    Article  CAS  PubMed  Google Scholar 

  49. Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25, 402–408 (2001).

    Article  CAS  PubMed  Google Scholar 

  50. Haushalter, R. W. et al. Production of anteiso-branched fatty acids in Escherichia coli; next generation biofuels with improved cold-flow properties. Metab. Eng. 26, 111–118 (2014).

    Article  CAS  PubMed  Google Scholar 

  51. Guo, F. et al. Metabolic engineering of Pichia pastoris for malic acid production from methanol. Biotechnol. Bioeng. 118, 357–371 (2021).

    Article  CAS  PubMed  Google Scholar 

  52. de Lima, P. B. et al. Novel homologous lactate transporter improves L-lactic acid production from glycerol in recombinant strains of Pichia pastoris. Microb. Cell Fact. 15, 158 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Liang, W. F. et al. Biosensor-assisted transcriptional regulator engineering for Methylobacterium extorquens AM1 to improve mevalonate synthesis by increasing the acetyl-CoA supply. Metab. Eng. 39, 159–168 (2017).

    Article  CAS  PubMed  Google Scholar 

  54. Satowa, D. et al. Metabolic engineering of E. coli for improving mevalonate production to promote NADPH regeneration and enhance acetyl-CoA supply. Biotechnol. Bioeng. 117, 2153–2164 (2020).

    Article  CAS  PubMed  Google Scholar 

  55. Cai, P. et al. Recombination machinery engineering facilitates metabolic engineering of the industrial yeast Pichia pastoris. Nucleic Acids Res. 49, 7791–7805 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank R. Chen from Naval Medical University in China for providing the method for extracting the total FFAs and the Energy Biotechnology Platform of Dalian Institute of Chemical Physics (DICP) for providing facility assistance. The authors thank AiMi Academic Services (www.aimieditor.com) for the English language editing. This study was financially supported by National Key Research and Development Program of China (2021YFC2100500 and 2021YFC2104200), the National Natural Science Foundation of China (21922812 and 21808216), DMTO research grant (DICP DMTO201701) and DICP innovation grant (DICP I202021 and DICP BioChE-X201801) from Dalian Institute of Chemical Physics, CAS.

Author information

Authors and Affiliations

  1. Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, PR China

    Jiaoqi Gao, Yunxia Li, Wei Yu & Yongjin J. Zhou

  2. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, PR China

    Jiaoqi Gao & Yongjin J. Zhou

  3. Dalian Key Laboratory of Energy Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, PR China

    Jiaoqi Gao, Yunxia Li, Wei Yu & Yongjin J. Zhou

  4. University of Chinese Academy of Sciences, Beijing, PR China

    Wei Yu

Authors
  1. Jiaoqi Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yunxia Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yongjin J. Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.G. and Y.J.Z. conceived the study. J.G. and Y.L. designed and performed most of the experiments. Y.L. performed ALE experiments. W.Y. assisted with experimental performance. J.G. and Y.J.Z. wrote the manuscript.

Corresponding author

Correspondence to Yongjin J. Zhou.

Ethics declarations

Competing interests

J.G., Y.L. and Y.J.Z. applied for a patent for protecting fatty acid production from methanol. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Metabolism thanks Rodrigo Ledesma-Amaro, Eun Yeol Lee and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary handling editor: Alfredo Giménez-Cassina in collaboration with the Nature Metabolism team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Effects of extra nutrition, glucose and xylose on cell growth of faa1Δ strain in methanol medium.

a, Fermentations were conducted in complex medium (YPM) containing 20 g/L peptone, 10 g/L yeast extract and 10 g/L methanol. b-d, faa1Δ cells were cultivated in Delft minimal medium containing various ratios of glucose and methanol that were equal to the molar amount of 10 g/L methanol. e-i, Xylose promoted cell growth and methanol assimilation of faa1Δ strain due to enhanced Xu5P supply. faa1Δ cells were cultivated in minimal medium containing substrates that were equal amount of carbon atoms to 10 g/L methanol (M), including sole xylose (Xyl) and different ratios of mixed methanol and xylose of 7:3 (7 M:3X), 8:2 (8 M:2X), 9:1 (9 M:1X). In particular, the sole xylose of 3X, 2X and 1X were used as controls to illustrate the utilization of methanol for cell growth and FFA production in the presence of xylose. Cells cultivated in sole methanol (YPM) and mixed methanol and xylose, were collected to extract intracellular metabolites and Xu5P was determined by LC–MS/MS. Data are presented as mean ± s.e.m. (n = 3 biologically independent samples).

Source data

Extended Data Fig. 2 Enhancing the supply of xylulose 5-phosphate and NADPH in faa1Δ strain.

a, Scheme of the rational design for the enhancement of Xu5P and NADPH, by enhancing gluconeogenesis, the pentose phosphate pathway and IDP2. b, Cell growth of strains with engineered NADPH related genes. Data are presented as mean ± s.e.m. (2 biologically independent samples were adopted).c, Overexpressing the Xu5P supply related genes TKL1, TALs, RPE, RKIs slightly increased the final amount of cell biomass but failed to fully restore growth in methanol medium. Data are presented as mean ± s.e.m. (3 biologically independent samples were adopted). For all experiments, strains were pre-cultured in YPD for 16~18 h and then washed twice with Delft medium and subsequently transferred into Delft medium with the initial OD600 of 0.2. Strains were cultivated at 37oC, 220 rpm for biomass analysis.

Source data

Extended Data Fig. 3 Adaptive laboratory evolution (ALE) of faa1Δ strain enabled cell growth and FFA production in sole methanol.

a, Procedure of ALE. Three independent colonies of HpFA01 were cultivated in minimal medium with a gradually reduced ratio of glucose and methanol. If the OD600 achieved up to 5~6 within 48 h, the evolved strains were transferred to a new medium, until the strains were able to grow normally in medium containing 10 g/L methanol as the sole carbon source. Final evolved strains were spotted on YPD plate for further characterization. b, Procedure of ALE that was illustrated by cell growth. Final OD600 before every transfer was measured and although distinguished processes had been gone through, all three groups finally achieved both cell growth and FFA production in minimal medium containing methanol as the sole carbon source. Five, or six colonies of each group were picked up for FFA production in minimal medium with 10 g/L methanol. Strains were pre-cultured in YPD for 16~18 h and then washed twice with minimal medium, which was subsequently transferred into fermentative media with the initial OD600 of 0.2. Strains were cultivated at 37oC, 220 rpm for analysis of growth curve (c-e), fatty acid titers (f-h) and fatty acid compositions (i). Data are presented as mean ± s.e.m. (n = 3 biologically independent samples).

Source data

Extended Data Fig. 4 13C labelling analysis shows that FFA were derived from the sole methanol.

Pre-cultured strain HpFAM01 was inoculated in minimal media containing 5 g/L 13C labelled methanol and 12C methanol, respectively. After 72 h of cultivation, the FFA products were analyzed by GC-MS. Total 5 types of FFAs were mainly detected, among which the mass spectrum of C16 and C1:-1 were displayed. The distinguished molecular and fragment ion peaks demonstrate that FFAs were derived from methanol.

Extended Data Fig. 5 Proportion of unsaturated fatty acids was increased in glucose medium because of enhanced expression of fatty acid desaturases.

a, FFA composition in Delft minimal medium containing methanol (Delft-MeOH) and glucose (Delft-Glc) as the sole carbon source. Cells were cultured at 37oC, 220 rpm for 96 h to measure FFA production for calculating saturated FFAs (C16 and C18), Δ9 single unsaturated FFAs (C16:1 and C18:1) and Δ9, Δ12 polyunsaturated FFAs (C18:2 and C18:3). b, Relative expression of gene OLE1, which encodes Δ9 desaturase. c, Relative expression of gene FAD2, which encodes Δ12 desaturase. At 48 h (methanol) or 24 h (glucose), cells were harvested to perform qPCR experiments to determine the relative expression levels of gene OLE1 and FAD2. Actin was selected as the reference and the 2-∆∆CT method was used to normalize the data. Data are presented as mean ± s.e.m. (n = 2 of a, 3 of b-c biologically independent samples).

Source data

Extended Data Fig. 6 FFA overproduction from methanol resulted in formaldehyde accumulation.

Cell growth (a) and methanol consumption (b) of wild-type, faa1Δ and evolved strains were detected in YPM medium and the corresponding formaldehyde accumulation was illustrated in Fig. 1g. c-d, Enhancing formaldehyde assimilation by overexpressed gene DASs improved cell growth and FFA production of faa1Δ strain in YPM medium. e-h, Lethal dose of formaldehyde in wild-type and FFA producing strains. e, cell growth (OD600) of wild-type under different formaldehyde concentrations at 24 h and 48 h; f, PI positive cells (%) of wild-type under different formaldehyde concentrations at 24 h and 48 h; g, cell growth (OD600) of evolved strain under different formaldehyde concentrations at 24 h and 48 h; h, PI positive cells (%) of evolved strain under different formaldehyde concentrations at 24 h and 48 h. Strains were pre-cultured in YPD for 16 - 18 h and then transferred into minimal medium containing 0.0, 1.0, 5.0, 10, 30, and 50 mM formaldehyde with an initial OD600 of 0.2. Strains were cultivated at 37 oC, 220 rpm, and OD600 and PI positive cells were detected at 24 h and 48 h, respectively. Data are presented as mean ± s.e.m. (n = 3 of a-d, or 2 of e-h biologically independent samples).

Source data

Extended Data Fig. 7 Lipidomics analysis of wild-type, faa1Δ and evolved strains.

a, Relative contents of lipids per gram dry cell weight (gDCW), including phospholipids, sphingolipids, neutral lipids, and other lipids. LPC, Lysophosphatidylcholine; PC, Phosphatidylcholine; PE, Phosphatidylethanolamine; PG, Phosphatidylglycerol; PI, Phosphatidylinositol; PS, Phosphatidylserine; CL, Cardiolipin; LPE, Lysophosphatidylethanolamine; Cer, Ceramides; Hex1Cer, Simple Glc series; SPH, Sphingosine; DG, Diglyceride; TG, Triglyceride; AcCa, Acyl carnitine; AEA, N-Acylethanolamine; OAHFA, OAcyl-(gamma-hydroxy) fatty acid; Co, Coenzyme. b, Composition of phosphatidylcholine (PC) with different chain lengths and saturation. Data are presented as mean ± s.e.m. (n = 3 biologically independent samples).

Source data

Extended Data Fig. 8 Transcriptome sequencing analysis of differentially expressed genes.

a, Venn diagram displaying numbers of upregulated (red) and downregulated (green) genes among the three groups; most genes were downregulated. b, Box plot displaying the average expression levels (RPKM values) between the reference strain HpFA01 and the three groups of evolved strains. The expression of evolved strains was significantly lower than expression in the reference strain (p < 0.001). Box boundaries are the 25th and 75th percentiles, the horizontal line across the box is the median, and the whiskers indicate the minimum and maximum values. c, Differentially expressed genes (DEGs) were annotated by Gene Ontology (GO), demonstrating a similar expression pattern among three groups. d, Differentially expressed genes (DEGs) were annotated by KEGG pathways, and Group II and III were distinguished with Group I, especially on pathways related to carbohydrate metabolism and lipid metabolism (Statistics analysis was conducted by two-paired t-test, *p < 0.05, **p < 0.01). Data are presented as mean ± s.e.m. (n = 3 biologically independent samples).

Source data

Extended Data Fig. 9 Effects of gene FBP1, RPE, and TAL1 on cell growth and FFA production in faa1Δ strain in methanol medium.

a, Genotype of engineered strains. According to transcriptional analysis, most genes were downregulated except for genes such as FBP1, RPE, and TAL1. For these three genes, coupled with disrupted lpl1 and izh3, were tested in faa1Δ strain. Engineered strains was cultivated in minimal methanol medium to detect the cell growth curve (b) and FFA production (c). Genes FBP1, RPE, and TAL1 failed to restore cell growth and FFA production without the double deletion of genes LPL1 and IZH3. Data are presented as mean ± s.e.m. (n = 3 biologically independent samples).

Source data

Extended Data Fig. 10 Engineering evolved strain to improve FFA production from methanol by manipulating genes related to supply of acetyl-CoA and NADPH.

a, The final biomass (OD600) of engineered strains. b, The final FFA titer of engineered strains. Evolved strain HpFAM02 (HpFAM01, ura3Δ, leu1.1:: HpLEU2) was used as the control strain. To increase the acetyl-CoA supply, a modified β-oxidation (pex10Δ), citrate lysis (MmACL), and PDH complex mutant from Escherichia coli were introduced. To increase the supply of NADPH, an enhanced gluconeogenesis (FBP1) and oxidative stage of PPP (ZWF1) was achieved. The introduction of PDHm did not cause any significant difference in growth and FFA production. Overexpression of MmACL and FBP1-ZWF1 increased the fatty acid titers by 10% and 30%, respectively. Data are presented as mean ± s.e.m. (n = 3 biologically independent samples). c, Proportion of unsaturated FFAs increased in a ScIDP2-expressing strain. d, Intracellular NADPH/NADP+ in strains with, without ScIDP2 overexpression. e, The expression level of genes that encode fatty acid desaturase (Δ9, Δ12, Δ15) in strains with, without ScIDP2 overexpression. Data are presented as mean ± s.e.m. (n = 3 biologically independent samples). f, Electron transfer in the process of desaturation of FFAs.

Source data

Supplementary information

Source data

Source Data Fig. 1

Statistical Source Data.

Source Data Fig. 2

Statistical Source Data.

Source Data Fig. 3

Statistical Source Data.

Source Data Fig. 4

Statistical Source Data.

Source Data Fig. 5

Statistical Source Data.

Source Data Fig. 6

Statistical Source Data.

Source Data Extended Data Fig. 1

Statistical Source Data.

Source Data Extended Data Fig. 2

Statistical Source Data.

Source Data Extended Data Fig. 3

Statistical Source Data.

Source Data Extended Data Fig. 5

Statistical Source Data.

Source Data Extended Data Fig. 6

Statistical Source Data.

Source Data Extended Data Fig. 7

Statistical Source Data.

Source Data Extended Data Fig. 8

Statistical Source Data.

Source Data Extended Data Fig. 9

Statistical Source Data.

Source Data Extended Data Fig. 10

Statistical Source Data.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, J., Li, Y., Yu, W. et al. Rescuing yeast from cell death enables overproduction of fatty acids from sole methanol. Nat Metab 4, 932–943 (2022). https://doi.org/10.1038/s42255-022-00601-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s42255-022-00601-0

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research