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Improved polyketide production in C. glutamicum by preventing propionate-induced growth inhibition

Nature Metabolism volume 5, pages 1127–1140 (2023)Cite this article

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Abstract

Corynebacterium glutamicum is a promising host for production of valuable polyketides. Propionate addition, a strategy known to increase polyketide production by increasing intracellular methylmalonyl-CoA availability, causes growth inhibition in C. glutamicum. The mechanism of this inhibition was unclear before our work. Here we provide evidence that accumulation of propionyl-CoA and methylmalonyl-CoA induces growth inhibition in C. glutamicum. We then show that growth inhibition can be relieved by introducing methylmalonyl-CoA-dependent polyketide synthases. With germicidin as an example, we used adaptive laboratory evolution to leverage the fitness advantage of polyketide production in the presence of propionate to evolve improved germicidin production. Whole-genome sequencing revealed mutations in germicidin synthase, which improved germicidin titer, as well as mutations in citrate synthase, which effectively evolved the native glyoxylate pathway to a new methylcitrate pathway. Together, our results show that C. glutamicum is a capable host for polyketide production and we can take advantage of propionate growth inhibition to drive titers higher using laboratory evolution or to screen for production of polyketides.

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Fig. 1: Propionate metabolism in C. glutamicum.
Fig. 2: Propionate derivatives induce growth inhibition.
Fig. 3: Accumulation of propionyl-CoA and methylmalonyl-CoA induces growth inhibition in propionate-containing medium.
Fig. 4: Methylmalonyl-CoA-dependent production of germicidin and 3-hydroxyacids rescue cell growth in propionate-containing medium.
Fig. 5: Evolved germicidin production strains show increased titer and improved growth.
Fig. 6: Propionyl-CoA conversion to germicidin by GltA2-based methylcitrate pathway.

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Data availability

The accession codes (SRR22028101, SRR22028102, SRR22028103, SRR22028104, SRR22028105, SRR22028106, SRR22028107, SRR22028108, SRR22028109, SRR22028110, SRR22028111, SRR22028112, SRR22028113, SRR22028114, SRR22028115, SRR22028116, SRR22028117, SRR22028118, SRR22028119, SRR22028120, SRR22028121, SRR22028122 and SRR22028123) for the genome sequence data of evolved strains reported in this paper are available at the Sequence Read Archive at PRJNA893829. All RNA-seq data are provided in the supplementary files. Source data are provided with this paper.

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Acknowledgements

This work was part of the US Department of Energy (DoE) Joint BioEnergy Institute (jbei.org) supported by the US DoE Office of Science, Office of Biological and Environmental Research, through contract DE-AC02-05CH11231 between Lawrence Berkeley National Laboratory and the US DoE and by a DoE Office of Science Distinguished Scientist Award to J.D.K. The views and opinions of the authors expressed herein do not necessarily state or reflect those of the US Government or any agency thereof. Neither the US Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied or assumes any legal liability or responsibility or the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed or represents that its use would not infringe privately owned rights. The DoE will provide public access to the results of federally sponsored research in accordance with the DoE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Funding for the open access charge is provided by the US DoE.

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Authors and Affiliations

  1. Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, USA

    Chunjun Zhan, Namil Lee, Guangxu Lan, Qingyun Dan, Aidan Cowan, Zilong Wang, Edward E. K. Baidoo, Ramu Kakumanu, Bridget Luckie, Rita C. Kuo, Joshua McCauley, Yuzhong Liu, Luis Valencia, Robert W. Haushalter & Jay D. Keasling

  2. Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Chunjun Zhan, Namil Lee, Guangxu Lan, Qingyun Dan, Edward E. K. Baidoo, Ramu Kakumanu, Rita C. Kuo, Joshua McCauley, Robert W. Haushalter & Jay D. Keasling

  3. Departments of Chemical & Biomolecular Engineering and of Bioengineering, University of California, Berkeley, CA, USA

    Chunjun Zhan, Namil Lee, Zilong Wang & Jay D. Keasling

  4. California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, CA, USA

    Qingyun Dan & Zilong Wang

  5. Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA

    Aidan Cowan, Bridget Luckie, Yuzhong Liu & Luis Valencia

  6. Center for Biosustainability, Danish Technical University, Lyngby, Denmark

    Jay D. Keasling

  7. Center for Synthetic Biochemistry, Shenzhen Institutes for Advanced Technologies, Shenzhen, China

    Jay D. Keasling

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  1. Chunjun Zhan
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Contributions

The study was conceived by C.Z. and R.W.H. C.Z. designed the study, conducted experiments, processed and analyzed the data. N.L. analyzed transcription data, genome sequencing data and modifed figures, while G.L. conducted the ALE experiments. Q.D. performed protein simulation and E.E.K.B. and R.K. analyzed the data from the 13C labeled experiments. B.L. and Z.W. contributed to the construction of engineered strains. R.C.K. and J.M. performed genome sequencing and Y.L. reviewed and edited the manuscript. L.V. conducted fatty acid measurement. J.D.K. supervised the project, reviewed and edited the manuscript and approved the final version.

Corresponding authors

Correspondence to Robert W. Haushalter or Jay D. Keasling.

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Competing interests

J.D.K. has financial interests in Amyris, Ansa Biotechnologies, Apertor Pharma, Berkeley Yeast, Cyklos Materials, Demetrix, Lygos, Napigen, ResVita Bio and Zero Acre Farms. All other authors declare no competing interests.

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Nature Metabolism thanks Yongjin Zhou and the other, anonymous, reviewers for their contribution to the peer review of this work. Primary Handling Editor: Alfredo Giménez-Cassina in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 Genealogy of strains created in this manuscript and the changes that were made to create those strains.

This paper can be divided into two parts. In the first part, we demonstrated that the propionyl-CoA/methylmalonyl-CoA accumulation is the reason to cause growth inhibition in C. glutamicum (propionate uptake and propionate metabolism). Based on that, we demonstrated that introducing methylmalonyl-CoA dependent polyketide synthase can relieve this inhibition (PKS-based detoxification). The second part is focused on evolving polyketide synthase based on propionate inhibition (ALE and reverse engineering). To strengthen the selection pressure, we knocked out the 2-methylcitrate pathway and mutase AB (based on our [13C] labeling results showing that more than 99% propionate will goes into 2-methylcitrate pathway rather than into the methylmalonyl-CoA, which will significantly weaken the selection stress.

Extended Data Fig. 2 Carbon utilization efficiency comparison among glucose, branched-chain amino acids and propionate.

Glucose is one of the most common carbon sources. 2 mol CO2 are generated (during TCA cycle) when 1 mol glucose is converted to succinyl-CoA. Then, succinyl-CoA is converted into methylmalonyl-CoA, which is subsequently decarboxylated when it is loaded onto the PKS by AT domains. Hence, 3 mol CO2 will be lost when 1 mol glucose is used for polyketide production. The carbon utilization efficiency is approximately 50%. For branched chain amino acids like valine, approximately 40% carbon will be lost when it is utilized by PKSs. However, compared with the above two carbon sources, there is no carbon lost when propionate is utilized by PKSs because 1 CO2 will be fixed at the beginning, even though this carbon will be lost when methylmalonyl-CoA is loaded by PKSs. The above information indicates that compared with other carbon sources, propionate is better because the carbon utilization efficiency is much higher. Glu, Glucose; G6P, Glucose 6-phosphate; F6P, Fructose 6-phosphate; Pyr, Pyruvate; Suc-CoA, Succinyl-CoA; MM-CoA, Methylmalonyl-CoA.

Extended Data Fig. 3 CgI2569 is involved in propionate utilization.

a: SDS-PAGE of CgI2569, ?marked bands represent purified CgI2569 protein. 1-4 represents four different tubes during elution. b: LC-MS analysis of the reaction between propionate and succinyl-CoA, indicating that purified CgI2569 catalyzed the reaction between propionate and succinyl-CoA. c: LC-MS analysis of the reaction between propionate and free CoA, indicating that purified CgI2569 did not catalyze the reaction between propionate and free CoA. d: LC-MS analysis of the reaction between propionate and acetyl-CoA, showing that purified CgI2569 catalyzed the reaction between propionate and acetyl-CoA. e: LC-MS analysis of the reaction between propionate and methylmalonyl-CoA, showing that purified CgI2569 did not catalyze the reaction between propionate and methylmalonyl-CoA. f: Growth curves of wild-type in GXII minimal medium with different concentrations of propionate (0, 0.2, 0.6 and 1 g/L), showing that cell growth is inhibited when propionate concentration is increased. g: Growth curves of different strains in CGXII minimal medium, which show that knockout pta-ack or cgl2569 did not affect cell growth in glucose medium. Cz01 (?pta-ack), Cz02 (?cgl2569), Cz03 (?cgl2569?pta-ack). All data represent the mean ± SD and error bars indicate the standard error (n = 3, biologically independent samples).

Source data

Extended Data Fig. 4 Knocking out cgI2537 (acdh) further inhibits cell growth in propionate medium.

a: Alternate metabolic pathways for propionate consumption in wild type cells with percentage of propionyl-CoA funneled through the 2-methylcitrate and methylmalonyl-CoA pathways indicated. b: Acyl-CoA dehydrogenase-based propionyl-CoA utilization pathway. Transcriptomic data indicate that acdh was significantly upregulated in propionate medium (log2 (Fold change) = 4.5), indicating that acdh may be involved in propionate inhibition. c: Growth curves of different strains (WT, Cz05, Cz06, Cz23, Cz24, Cz25) in CGXII minimal medium. d: Growth curves of strains encoding acdh mutations in CGXII minimal medium with 0.5 g/L propionate. Cz05 (?prpDBC1/2). Cz06 (?prpDBC1/2, ?mcmAB). Cz23 (?acdh). Cz24 (?acdh, ?prpDBC1/2). Cz25 (?acdh, ?prpDBC1/2, ?mcmAB). Growth results indicate that deleting acdh in Cz05 or Cz06 further inhibits cell growth. All data represent the mean ± SD and error bars indicate the standard error (n = 3, biologically independent samples). Based on the results shown in (a), we surmise that most of the propionate is funneled through the 2-methylcitrate pathway with little flowing through the methylmalonyl-CoA pathway, indicating that the 2-methylcitrate pathway is the main pathway to utilize propionate, consistent with Fig. 3a.

Source data

Extended Data Fig. 5 Free CoA and acetyl-CoA in WT, Cz05 and, Cz06 strains.

a: Free CoA and acetyl-CoA measurement in wild type, Cz05 and Cz06 cultures grown in CGXII minimal medium with 1 g/L propionate. b: Free CoA measurement in Cz05 and Cz06 cultures grown in CGXII minimal medium with 1 g/L propionate and 10 μM vitamin B12. Cz05 (?prpDBC1/2). Cz06 (?prpDBC1/2, ?mcmAB). Compared with wild-type, free CoA and acetyl-CoA were both depleted in Cz05 and Cz06 strains when cells were inoculated into propionate-containing medium. Moreover, compared to Cz06, the free CoA concentration increased in Cz05 when cells were inoculated into propionate-containing medium with 10 μM vitamin B12. This is consistent with our hypothesis that accumulation of methylmalonyl-CoA is causing slower growth by depleting acetyl-CoA and free CoA-SH. This result is consistent with previous results2,3, in which propionate or its derivatives were shown to inhibit acetyl-CoA production. All cells were inoculated in BHI medium (30 °C, 200 rpm for 16 h), then transferred into CGXII minimal medium (30 °C, 200 rpm for 16 h) and finally inoculated into CGXII minimal medium with 1 g/L propionate. Samples were collected during early exponential phase (OD600 is around 0.5). All data represent the mean ± SD and error bars indicate the standard error (n = 3, biologically independent samples). Statistical analysis was performed using two-tailed Student’s t test.

Source data

Extended Data Fig. 6 Free CoA and vitamin B12 rescue cell growth in propionate.

a: Growth curves of different strains in CGXII minimal medium with 1 g/L propionate and 10 µM sodium pantothenate. b: Growth curves of Cz05 in CGXII minimal medium with 0.6 g/L propionate with 10 µM vitamin B12 or 10/100 µM sodium pantothenate. c: Growth curve of Cz05 in CGXII minimal medium with 1 g/L propionate with 10 µM vitamin B12 or 10/100 µM sodium pantothenate. d: Growth curve of Cz05 in CGXII minimal medium with 1.6 g/L propionate with 10 µM vitamin B12 or 10/100 µM sodium pantothenate. e: Transcriptomic analysis of genes in the CoA biosynthesis pathway in wild type strain. Samples 1 and 2 were inoculated in CGXII minimal medium with 1 g/L propionate and control samples were inoculated into CGXII minimal medium. Samples were collected during the early exponential phase at an OD600 of approximately 0.5. Cz04 (?mcmAB). Cz05 (?prpDBC1/2). Cz06 (?prpDBC1/2, ?mcmAB). All data represent the mean ± SD and error bars indicate the standard error (n = 3, biologically independent samples).

Source data

Extended Data Fig. 7 Propionate tolerance assay and ALE strategy to evolve germicidin initial production strain (Cz12).

a: Growth curve of Cz34 (?prpDBC1, prpDBC2::sfp, ?mcmAB) in CGXII minimal medium with various concentrations of propionate. b: Lag phase of Cz34 in CGXII minimal medium with various concentrations of propionate. All strains were pre-cultivated in BHI overnight (16 h), inoculated into CGII minimal medium and grown for 16 h. Then cells were inoculated into CGXII minimal medium with various concentrations of propionate. All data represent the mean ± SD and error bars indicate the standard error (n = 3, biologically independent samples). c: ALE workflow, cells were cultivated in BHI medium overnight (30 °C, 16 h), then inoculated into CGXII minimal medium and finally transferred into fresh CGXII medium with increasing concentration of propionate. Cells were passaged 10 times. d: OD600 measurement during ALE process. Three colonies (colony-1, colony-2 and colony-3) were chosen to perform ALE. The duration and propionate concentration of each passage is indicated above.

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Extended Data Fig. 8 Evaluate cell growth after ALE.

a: Biomass production of different strains after 7 h. b: Biomass production of different strains after 12 h. c: Biomass production of different strains after 17 h. d: Biomass production of different strains after 21 h. e: Growth curves of Cz34, initial strain (Cz12) and various evolved strains. f: Growth rate of initial strain and various evolved strains. All data represent the mean ± SD and error bars indicate the standard error (n = 3, biologically independent samples). Statistical analysis was performed using two-tailed Student’s t test (**P < 0.01, ***P < 0.001).

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Extended Data Fig. 9 Reverse Engineering to evaluate beneficial mutation.

a: Modeled surface structure of GltA2 (Citrate Synthase) based on module 4TVM (PDB)4. Residues that were mutated in evolved strains are labeled. Green represents mutations E239G, R310C and S60F. Active site catalytic triad residues are shown in pink. b: SDS-PAGE gel results of purified GltA2. Lanes 1-3 are three fractions of purified GltA2; we moved forward with the fraction in lane 2 for subsequent experiments. GltA2 molecular weight is approximately 47.98 KD. c: Growth of different strains in CGXII minimal medium. d: In vitro citrate synthase assay using purified GltA2 proteins. Acetyl-CoA and/or propionyl-CoA are consumed in the reaction, releasing free CoA-SH which is measured colorimetrically. CzEv208, single colony from evolved strain Cz13 (population). Cz34 (?prpDBC2, ?mcmAB, prpDBC1::sfp). Cz12 (entire germicidin production pathway integrated into Cz34). Cz16 (GltA2 Glu239Gly in Cz12), Cz17 (GltA2 Arg310Cyc in Cz12), Cz18 (GltA2 Ser60Phe in Cz12). All data represent the mean ± SD and error bars indicate the standard error (n = 3, biologically independent samples).

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Extended Data Fig. 10 LC-MS results to detect 13C labeled intermediates for germicidin product.

a: Measure the level of 13C-labeled different intermediates among Cz12 and Cz15. b: Measure the level of 13C-labeled 2-methylcitrate and germicidin in CzEv208. To further confirm that evolved GltA2 can catalyze the reaction between propionyl-CoA and oxaloacetate and the generated pyruvate can be used to produce acetyl-CoA and malonyl-CoA, Cz12 and Cz15 (native GltA2 in Cz12 replaced with evolved GltA2) were pre-cultivated in BHI liquid medium (30 °C, 200 rpm for 16 h). Then, the cells were transferred into CGXII minimal medium (30 °C, 200 rpm for 16 h). Finally, Cz12 and Cz15 were inoculated into CGXII minimal medium with 1 g/L [13C3] propionate. Samples were collected during exponential phase (OD600 around 0.5). Compared to Cz12, the concentrations of [13C] 2-methylcitrate, [13C] acetyl-CoA and [13C] malonyl-CoA were significantly increased, indicating that evolved GltA2 can catalyze the reaction between propionyl-CoA and oxalacetate to produce 2-methylcitrate. All data represent the mean ± SD, and error bars indicate the standard error (n = 3, biologically independent samples). Statistical analysis was performed using two-tailed Student’s t test (**P < 0.05, ***P < 0.001).

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Zhan, C., Lee, N., Lan, G. et al. Improved polyketide production in C. glutamicum by preventing propionate-induced growth inhibition. Nat Metab 5, 1127–1140 (2023). https://doi.org/10.1038/s42255-023-00830-x

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