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Spatial–temporal regulation of fatty alcohol biosynthesis in yeast
Biotechnology for Biofuels and Bioproducts volume 15, Article number: 141 (2022)
Abstract
Background
Construction of efficient microbial cell factories is one of the core steps for establishing green bio-manufacturing processes. However, the complex metabolic regulation makes it challenging in driving the metabolic flux toward the product biosynthesis. Dynamically coupling the biosynthetic pathways with the cellular metabolism at spatial–temporal manner should be helpful for improving the production with alleviating the cellular stresses.
Results
In this study, we observed the mismatch between fatty alcohol biosynthesis and cellular metabolism, which compromised the fatty alcohol production in Saccharomyces cerevisiae. To enhance the fatty alcohol production, we spatial-temporally regulated fatty alcohol biosynthetic pathway by peroxisomal compartmentalization (spatial) and dynamic regulation of gene expression (temporal). In particular, fatty acid/acyl-CoA responsive promoters were identified by comparative transcriptional analysis, which helped to dynamically regulate the expression of acyl-CoA reductase gene MaFAR1 and improved fatty alcohol biosynthesis by 1.62-fold. Furthermore, enhancing the peroxisomal supply of acyl-CoA and NADPH further improved fatty alcohol production to 282 mg/L, 2.52 times higher than the starting strain.
Conclusions
This spatial–temporal regulation strategy partially coordinated fatty alcohol biosynthesis with cellular metabolism including peroxisome biogenesis and precursor supply, which should be applied for production of other products in microbes.
Introduction
Construction of cell factories is considered as a feasible approach for sustainable supply of a variety of products of interests [1]. However, the complex and tight metabolic regulation makes it challenging in driving the metabolic flux toward product biosynthesis [2]. In particular, eukaryotic cells have compartmentalized metabolism in different sub-organelles, which brings some barriers for substrate channeling in supplying precursors and cofactors [3]. Furthermore, the cellular metabolism is dynamically controlled in response to cell state and extracellular signal [4]. Thus, coupling the spatial–temporal metabolism with the biosynthesis pathways should be helpful for improving the chemical production.
As an example, we here tried to couple the spatial–temporal fatty acid metabolism of Saccharomyces cerevisiae for producing fatty alcohol, an important oleo-chemical that can be used in detergents and personal care products with a global market of 6.8 billion USD [5]. Fatty alcohol can be bio-synthesized from free fatty acids (FFA) or activated fatty acids (fatty acyl-CoA and -ACP) through various reductase [6]. In S. cerevisiae, fatty acids are mainly de novo synthesized by cytosolic type I fatty acid synthase (FAS) as fatty acyl-CoAs, which can be transformed to functional or storage lipids. Under carbon-rich conditions or cell growth phase, fatty acid biosynthesis is very active and results in relatively high fatty acyl-CoA formation in cytosol. In the absence of the sufficient carbon sources, the storage lipids, such as triacylglycerols, will be broken down for energy supply through β-oxidation in peroxisomes [7]. This spatial–temporal regulation of fatty acid metabolism has been largely ignored for production of fatty acid derived chemicals, though pathway optimization and enhancing the supply of precursors and cofactors have been extensively explored [8, 9].
We here designed a spatial–temporal regulation strategy to couple fatty alcohol biosynthesis with the fatty acid metabolism through pathway compartmentalization and dynamic regulation by screening fatty acid/acyl-CoA responsive promoters (Fig. 1). A coordination of cytoplasmic and peroxisomal biosynthetic pathways was proved to be beneficial for improving fatty alcohol production by 2.52-fold (Additional file 1: Figure S1), which could be applied for production of other target products.
Results
Coordination of fatty alcohol biosynthesis
We previously constructed a chimeric fatty alcohol pathway by expressing a carboxylic acid reductase gene MmCAR and a fatty acyl-CoA reductase gene FaCoAR, which used both FFAs and fatty acyl-CoA as substrates [10]. We targeted this chimeric pathway to cytosol and peroxisomes, respectively (Fig. 2A). We observed that the peroxisomal pathway had much lower fatty alcohol production compared with the cytosolic pathway when using constitutive promoters for gene expression (Fig. 2B). It has been reported that constitutive promoters (PTEF1 for expressing FaCoAR and PTDH3 for expressing MmCAR) reached the highest strength in log-phase, and are relatively weak in stationary phase using glucose as the carbon source [11], while the number of peroxisomes shows the opposite pattern during cell growth [12]. This mismatch between fatty alcohol biosynthesis and peroxisome biogenesis might compromise fatty alcohol production. Consistently, using GAL promoters of galactose catabolism (with deletion of GAL80) to drive the peroxisomal biosynthetic pathway (strain YJ-FOH4) significantly improved fatty alcohol production by 3.25-fold (82.3 mg/L), which was also much higher than that of cytosolic pathway (strain YJ-FOH3). PGAL promoters were shown to be activated at glucose exhaustion (Additional file 1: Figure S2), and their expression was supposed to be partially coordinated with peroxisome biogenesis [13]. This result suggested that spatial-temporally balancing the metabolic pathways was beneficial for improving the product biosynthesis.
The enhanced expression levels of peroxin genes PEX7 and PEX28 have been reported to increase the transport of peroxisomal matrix proteins [14] and peroxisome numbers [15] in S. cerevisiae, respectively, which was supposed to enhance fatty alcohol production in peroxisomes. Indeed, we found that overexpressing PEX7 or PEX28 promoted fatty alcohol production, and PEX28 overexpression resulted in a 2.6-fold higher fatty alcohol titer (Fig. 2C). However, a large proportion of residual fatty acids was observed in fatty alcohol producing strains, and only up to 28% of fatty acids were utilized for fatty alcohol production (Fig. 2D), which might be attributed to the secreted fatty acids barely being re-utilized [16]. We thus tried to optimize and balance the fatty acyl-CoA derived pathway, which could avoid the accumulation of FFAs. Gene evaluation showed that MaFAR1 from Marinobacter sp. ES-1 (Accession No. WP_022988858.1) achieved the highest fatty alcohol titer (Additional file 1: Figure S3), which was 7.7-fold higher than that from CAR pathway (Fig. 2E).
Screening fatty acid/acyl-CoA responsive promoters
Screening endogenous fatty acid/acyl-CoA responsive promoters might be helpful for further improving fatty alcohol production by precisely balancing cellular fatty acid/acyl-CoA levels. We conducted comparative transcriptional analysis of wild-type, fatty acid producing strain YJZ121, and strain JV03 that was engineered for acyl-CoA accumulation [17] (Fig. 3A). The potential fatty acid/acyl-CoA responsive promoters were identified based on differentially expressed genes (DEGs) according to the following rules: RPKM (Reads Per Kilobase Million) value > 1500, fold change > 5, common genes among different conditions and sampling points, and non-metabolic genes. Under this criteria, 20 candidate promoters were supposed to be fatty acids (Additional file 1: Table S1) and/or fatty acyl-CoA responsive (Additional file 1: Table S2).
These promoters were further characterized using an eGFP in wild-type, strain YJZ121, and strain JV03 (Fig. 3B). Six promoters (PADH6, PARI1, POYE3, PRDR5, PHSP31, and PAAD6) showed strong responsive activities to exogenous fatty acids (Fig. 3C), though most promoters demonstrated weak activities in wild-type cultivated in media with 0.5% (v/v) oleic acid (Additional file 1: Figure S4A). In particular, the activity of PAAD6 (promoter of a putative aryl-alcohol dehydrogenase) was 2.7-fold higher than that of the common strong constitutive promoter PeTDH3 in medium with 0.5% (v/v) oleic acid. Furthermore, promoters PADH6 and PAAD6 were significantly induced by endogenous FFAs (wild-type strain CEN.PK 113-11C vs FFA overproducing strain YJZ121, Additional file 1: Figure S5) with considerable strength.
Two acyl-CoA responsive promoters, PBDH2 (promoter of a putative 3-hydroxybutyrate dehydrogenase 2) and PSTE3 (promoter of receptor for a factor pheromone), were also characterized in both wild-type and JV03 (Fig. 3D and Additional file 1: Figure S4B). Promoter PBDH2 possessed relatively high activity in JV03, especially at the later stage of fermentation. Promoter PSTE3 possessed a favorable response to acyl-CoA, in spite of a relatively low activity, which might be also useful for dynamically regulating fatty alcohol biosynthesis.
Enhancing fatty alcohol production by dynamically regulating MaFAR1 expression
We then tried to enhance fatty alcohol production by dynamically regulating MaFAR1 expression with the identified fatty acid/acyl-CoA responsive promoters. To avoid unstable expression of biosynthetic pathways on plasmids [18], the fatty alcohol biosynthetic genes were integrated into genome. To enable sufficient supply of precursor fatty acyl-CoA and cofactor NADPH, we constructed the fatty alcohol biosynthetic pathway in the FFA overproduction strain Y&Z036 [19] by a metabolic transforming strategy via knocking out gene tesA and restoring FAA1/4 genes [20]. Furthermore, the peroxisome biogenesis was enhanced by over-expressing PEX28, which resulted in the chassis strain GN33 (Additional file 1: Figure S1). Expressing MaFAR1 with PADH6 and PBDH2 had higher fatty alcohol production than that of PAAD6, and PSTE3, which, however, was only 50% of that with PGAL1,10. As expected, fatty alcohol titers were positively correlated with the promoter strengths (Fig. 4).
We further combined PADH6 or PBDH2 with PGAL1,10 for expressing MaFAR1, which significantly improved fatty alcohol production compared with one-copy of PGAL1, 10 and also slightly higher than that with two copies of PGAL1,10 (Fig. 4A). These results suggested that fatty acid/acyl-CoA responsive promoters helped to synergistically promote fatty alcohol biosynthesis, especially the strength of PGAL1,10 was relatively low at the early stage of the cultivation, while PBDH2 was relatively higher (Fig. 4B). The strength compensation might be helpful for MaFAR1 expression. Finally, expressing three copies of MaFAR1 under the control of PADH6, PBDH2 and PGAL1, 10 had the highest fatty alcohol production of 194 mg/L in strain GNFOH97 (Fig. 4A).
Peroxisomal engineering for enhancing the supply of acyl-CoA and NADPH
In spite of the sufficient supply of cytosolic acyl-CoA and NADPH [21], the background strain was further engineered to achieve high-level production of fatty alcohols by enhancing the supply of peroxisomal acyl-CoA and NADPH. Firstly, the acyl-CoA transporter PXA1/PXA2 and a peroxisomal copy of acyl-CoA synthase FAA2 were overexpressed (Fig. 5A), which improved fatty alcohol titer by 12% and 19%, respectively (Fig. 5B). The combined overexpression of PXA1/PXA2 and FAA2 had a decreased fatty alcohol titer (Fig. 5B), which might be due to the disturbance of metabolic balance.
In addition, a peroxisomal malate shuttling pathway was constructed, including the essential genes of malic enzyme (RtME) [10], pyruvate carboxylase (PYC1) and malate dehydrogenase (MDH3) (Fig. 5A). Surprisingly, only the overexpression of RtME slightly increased fatty alcohol titer, and a combined overexpression of PYC1 and MDH3 had a negative effect (Fig. 5C). In particular, overexpression of PYC1 strongly hindered cell growth and introduction of MDH3 partially relieved the growth repression (comparing strains GNFOH105 with GNFOH104), but did not improve fatty alcohol production. Considering the specific fatty alcohol titer of strain GNFOH104 was higher than that of GNFOH103 and GNFOH105, a combined expression of RtME and PYC1 was adopted to maintain the shuttling pathway.
It has been shown that overexpressing NADP+-dependent isocitrate dehydrogenase (IDH) was helpful for improving the production of FFAs [19]. We thus targeted the cytosolic NADP+-dependent Idp2 to peroxisome by adding the peroxisomal targeting signal per2 [22] and also overexpressed the peroxisomal isoform Idp3 (Fig. 5A). Overexpressing the encoding gene perIDP2 or IDP3 slightly improved fatty alcohol production and the combined overexpression improved fatty alcohol titer by 18.5% compared with the control strain GNFOH97 (Fig. 5D). Implementing these engineering strategies in strain GNFOH111 further improved fatty alcohol production (Fig. 5E). Interestingly, the introduction of malate shuttling pathway, coupled with the overexpressed isocitrate dehydrogenase, successfully improved fatty alcohol biosynthesis, which suggested that sufficient acyl-CoA supply required extra NADPH to drive a functional malate shuttling pathway. Combining all engineering strategies enabled fatty alcohol production of 242 mg/L, a 10% improvement compared with the control strain GNFOH111 (Fig. 5E).
Peroxisomes are inferred to be induced by ROS triggered chemicals like H2O2 [23], which might be helpful for enhancing fatty alcohol production in peroxisomes. Indeed, supplementing low concentrations of H2O2 (< 1 mM) in cell culture, slightly increased fatty alcohol titers with no obviously negative effects on cell growth of strain GNFOH120 (Fig. 5F) and the highest 282 mg/L fatty alcohol was obtained with 1 mM H2O2. However, higher concentrations of H2O2 decreased both biomass and fatty alcohols, which could be due to cell damage caused by H2O2. Therefore, H2O2 addition could be used as a feasible strategy to boost the efficiency of peroxisomal biosynthetic pathways.
We further expressed a copy of cytosolic MaFAR1 with constitutive promoters PTEF1 and PTDH3 for converting the cytosolic fatty acid/acyl-CoA at the early stage, which slightly improved fatty alcohol production by 6.6% (Additional file 1: Figure S6A). This result suggested the acyl-CoA was mainly used for cell components such as phospholipids at the early stage and there was excessive acyl-CoA for fatty alcohol biosynthesis at the late fermentation stage. In addition, this spatial–temporal regulation via fatty acid/acyl-CoA responsive promoters and cellular compartmentalization did not significantly influence the composition of fatty alcohol (Additional file 1: Figure S6B), which resulted a partially coordinated of fatty alcohol biosynthesis and cellular metabolism in yeast.
Discussion
Construction of heterologous artificial biosynthetic pathways always brings perturbation to the cellular metabolism, which, in turn, compromises the biosynthetic efficiency of target products. The cellular metabolism is spatial-temporally regulated to respond to extracellular signals or cell function, and construction of stable biosynthetic pathways might result in un-coordinated metabolic network as well as insufficient supply of precursors and cofactors. We here showed that spatial–temporal regulation of the fatty alcohol biosynthetic pathway significantly improved the production of fatty alcohols in model eukaryotic yeast S. cerevisiae.
It is well-recognized that the cellular metabolism is temporally regulated to respond to the nutrient availability, cell cycle and else [24]. In the exponential growth phase, the metabolic flux is mainly redirected for the synthesis of cellular components, and thus there is limited resources for biosynthesis of product of interest. Dynamically engineering biosynthetic pathways to separate from cell growth was helpful for overproduction [25,26,27,28]. We here also showed that dynamically regulating pathways with GAL promoters that are activated at glucose depletion, improved fatty alcohol production compared with that of constitutive promoters. In eukaryotes, cellular metabolism is distributed in sub-organelles for suitable physicochemical environments and condensed precursors/enzymes to avoid unnecessary interference. Metabolic compartmentalization has been extensively applied for improving the production of a variety of chemicals by targeting the biosynthetic pathways or specific enzymes into sub-organelles such as mitochondria [29, 30] and peroxisome [22, 31,32,33]. However, the temporal biogenesis of sub-organelle was largely ignored, and the mismatched biosynthetic pathways with sub-organelle biogenesis should largely compromise the engineering endeavor. For example, the peroxisomes mainly proliferate under the nutritional shortage or oxidative stress and are greatly repressed under the early growth stage with high-level of glucose [34, 35]. We actually observed that peroxisomal targeting the fatty alcohol biosynthesis pathway that was driven by the glucose activating promoters resulted low fatty alcohol production, while the partial coordination of peroxisome biogenesis using GAL promoters resulted much higher fatty alcohol production in peroxisomes. Further dynamically enhancing the supply of peroxisomal cofactors and precursor acyl-CoA significantly improved fatty alcohol production. These results clearly showed that spatial-temporally regulating the biosynthetic pathways was beneficial for production by smartly coping the complex cellular metabolism.
Dynamic regulation of metabolic pathways can be realized for genetically encoded control systems, among which the promoter-based transcriptional regulation is a convenient approach for construction of dynamic pathways. Several artificial promoters have been constructed to sense specific metabolites and improve the biosynthetic efficiency in bacteria [36, 37]. However, the complex structure of eukaryotic promoters makes it challenging to construct sensitive promoters for dynamic regulation. We here showed that transcriptomic analysis identified several promoters that respond to fatty acids/acyl-CoA, which helped to drive fatty alcohol production. Furthermore, these promoters significantly drove the production of 3-hydroxypropionic acid (3-HP), an important platform chemical (Additional file 1: Figure S7).
Conclusions
This study proposed the spatial–temporal regulation of biosynthetic pathways to significantly improve the production of fatty alcohols and other acetyl-CoA derived chemicals, such as 3-HP. A coordination of cytoplasmic and peroxisomal biosynthetic pathways via pathway compartmentalization and dynamic regulation by screening fatty acid/acyl-CoA responsive promoters increased the product titer by up to 2.52-fold. We can image this strategy should be helpful for further improving fatty alcohol production in previously described cell factories such as oleaginous yeasts [9, 38] and S. cerevisiae [8], and may be used as an universal strategy for construction of efficient microbial cell factories.
Materials and methods
Strains and plasmids
Strains used in this study were listed in Additional file 1: Table S3 and Figure S1. Plasmids and primers were listed in Additional file 1: Table S4 and Table S5. Guide RNAs (gRNAs) sequences were listed in Additional file 1: Table S4. Fatty alcohol biosynthetic pathways were assembled on yeast chromosome, or plasmids pESC or pYX212 [39]. All S. cerevisiae strains used in this study were derived from CEN.PK113-11C (MATa; SUC2; MAL2-8c; his3Δ1; ura3-52;).
Media and cultivation conditions
S. cerevisiae was generally cultivated at 30 °C in YPD medium consisting of 20 g/L glucose, 20 g/L peptone and 10 g/L yeast extract. Strains containing URA3/HIS3-based plasmids or gene expression cassettes were selected on synthetic dextrose media without uracil (SD-URA) or histidine (SD-HIS), which consisted of 20 g/L glucose and 6.7 g/L yeast nitrogen base (YNB, without amino acids). The SD + URA + HIS + 5-FOA plates consisting of 20 g/L glucose, 6.7 g/L yeast nitrogen base (YNB, without amino acids), 20 mg/L uracil, 20 mg/L histidine and 2 g/L 5-fluoroorotic acid were used to remove URA3 maker. Fatty alcohol production was conducted in Delft minimal medium consisting of 14.4 g/L KH2PO4, 2.5 g/L (NH4)2SO4, 0.5 g/L MgSO4•7H2O, trace metal and vitamin solutions according to previous report [40], and 20 g/L glucose was added as carbon source, 60 mg/L uracil and 40 mg/L histidine were added if needed. Escherichia coli was cultivated at 37 °C in LB media (5 g/L yeast extract, 10 g/L tryptone and 10 g/L NaCl).
Commonly used reagents and primers were purchased from Sangon Biotech, Shanghai, China, unless otherwise specified. All codon optimized genes based on S. cerevisiae codon preference were synthesized by Exsyn-bio Technology Co., Ltd (Shanghai, China) and GENEWIZ (Suzhou, China).
Genetic manipulation
The genetic manipulation was performed using CRISPR/Cas9 system as described previously [41]. CAS9 gene was integrated into the genomic XI-5 site [42]. Seamless gene deletion was performed using corresponding guide RNA (gRNA) expressing plasmids and donor DNA. The donor DNA was constructed by overlap extension PCR (OE-PCR), of which homologous arms (HA, 200–500 bp) were amplified from the upstream and downstream of the target site. For gene integration, expression cassettes were constructed by OE-PCR to fuse the upstream HA, promoter, open reading frame (ORF), terminator and downstream HA [39], as shown in Figure S8. The integration modular was integrated at different neutral sites [43]. The proteins were targeted to peroxisome by adding the peroxisomal targeting signal (per1 and per2) at the C-terminal of the specific genes [22]. The gene expression cassettes or plasmids were transformed to S. cerevisiae according to previous report [44]. The mutants were verified by colony PCR. Transformants with successful integration were plated on SD + URA + HIS + 5-FOA plates to remove gRNA expressing plasmids that contain URA3 maker. All codon-optimized genes were listed in Additional file 1: Table S6.
Batch fermentation and metabolites quantification
Batch fermentations in shake flask were carried out as follows: three to four biological replicates were each inoculated into 2 mL YPD medium and incubated for about 24 h. Cell cultures were then inoculated again into 2 mL Delft minimal medium and cultivated for 24 h. The 24 h cultures were inoculate into 15 mL minimal medium to an optical density (OD600) of 0.1 in 100 mL-baffled flask, and cultivated at 30 °C, 220 rpm, for 72 h or 96 h. The OD600 of the culture was measured to evaluate cell growth.
For fatty alcohol, after 96 h cultivation, 1 mL cell culture was used to extract fatty alcohols as previously described [45]. Samples were analyzed by GC (Thermo fisher) as previously described [46]. Free fatty acids were extracted from 72 h cultivations and quantified as described in our previous study [10]. For quantification of 3-hydroxypropionic acid (3-HP), the samples were analyzed using high-performance liquid chromatography (Shimadzu LC-2030, Japan) as previously described [18].
Screening of fatty acids/acyl-CoA-responsive promoters
To identify endogenous promoters that respond to fatty acids/acyl-CoA, transcriptional analysis was conducted in wild-type strain CEN.PK-113C, free fatty acid (FFA) producing strain YJZ121, and acyl-CoA accumulating strain JV03 [17]. Strains were pre-cultivated in minimal medium with 20 g/L glucose for 24 h, and then batch fermentation was carried out in 1.0 L bioreactors (Eppendorf) containing 0.3 L minimal medium with 20 g/L glucose. Wild-type strain was cultured in minimal media without, or with 0.3% (v/v) of oleic acid. Fatty acid producing strain was cultivated in minimal media without oleic acid. Acyl-CoA strain (JV03) was cultivated in minimal media without, or with 0.3% (v/v) of oleic acid. 0.1% (v/v) Tween80 was supplemented to dissolve oleic acid. Samples were taken at the early log phase, late log phase, and stationary phase. Cells were collected and washed twice with sterile ddH2O before extracting total RNA using RNeasy® Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Three biologically independent replicates were applied to minimize errors.
Qualified total RNA was clustered by TruSeq PE Cluster Kit v3-cBot-HS (Illumia), and sequenced on Illumina Novaseq platform (Novogene Bioinformatics Technology Co. Ltd). Software Hisat2, FeatureCounts v1.5.0-p3, and DESeq2 R package (1.20.0) were used for mapping, reads counting, and differential expression analysis, respectively. To identify fatty acid responsive promoters, two group comparisons, CEN.PK 113-11C vs CEN.PK 113-11C in oleate, and CEN.PK 113-11C vs YJZ121, were adopted, among which top 50 DEGs in all three sampling points were included, and the final 10 candidate promoters were selected from the intersection of these two groups (Additional file 1: Table S1). Similarly, 10 candidate promoters that responded fatty acyl-CoA were derived from two group comparisons, CEN.PK 113-11C vs JV03, and JV03 vs JV03 in oleate (Additional file 1: Table S2).
Characterization of fatty acid/acyl-CoA responsive promoters
20 candidate promoters in Table S1 and Table S2 were characterized on episomal plasmid using eGFP as a reporter. The plasmids were constructed as illustrated in Figure S9. Briefly, the eGFP gene was first inserted into an empty plasmid pYX312 by enzymatic digestion with Hind III and Sal I and ligation and the strong constitutive promoter PUAS-TDH3 [47] was adopted as positive control, generating pSc01. Subsequently, pSc01 was digested by Kpn I and Hind III, and the promoter fragments were inserted to obtain a series of plasmids pSc02 ~ pSc21.
To characterize fatty acid responsive promoters, plasmids pSc01 ~ pSc21 were transformed into both wild-type strain (CEN.PK-113C) and FFA producing strain (YJZ121). Wild-type derived strains were cultivated in minimal media with or without 0.5% (v/v) oleic acid to evaluate the responses to exogenous fatty acids. Samples were taken to measure OD600 and fluorescence intensity, and the promoter activities were represented by the fluorescence intensity per OD600. To evaluate the responses to endogenous fatty acids, fluorescence intensity per OD600 of each promoter were characterized in wild-type and YJZ121 background strains that cultivated in minimal medium. In particular, to test the effects of supplemented carbon sources on the promoter (PUAS-TDH3, PADH6, POYE3, PPDR5, PHSP31, PAAD6) responses to endogenous fatty acids, 20 g/L glucose, or galactose was supplemented to the medium at 16 h. Strains were cultured for 64 h, and samples were taken to measure the fluorescence intensity per OD600. Similarly, plasmids pSc01 ~ pSc21 were transformed into acyl-CoA producing strain (JV03) for characterizing acyl-CoA responsive promoters in minimal media using wild-type derived strains as the control.
Statistics analysis
Statistics analysis is performed in Office Excel Software using two-tailed t test method of variance ANOVA hypothesis. Significant differences are marked as n.s. p > 0.05, *p < 0.05, **p < 0.01, and ***p < 0.001. All data are presented as mean ± s.e.m. The number of biologically independent samples for each panel is typically three unless otherwise stated in the figure legends.
Availability of data and materials
All data supporting the findings of this study are included in the paper and its supplementary information.
Abbreviations
- CAR:
-
Carboxylic acid reductase
- FAR:
-
Fatty acyl-CoA reductase
- FFA:
-
Free fatty acid
- DEG:
-
Differentially expressed gene
- RPKM:
-
Reads per kilobase million
- ROS:
-
Reactive oxygen species
- 3-HP:
-
3-Hydroxypropionic acid
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Acknowledgements
The authors wish to thank Prof. Jens Nielsen (Chalmers University of Technology, Sweden) for the constructive guidance and kindly providing the S. cerevisiae strains JV03 and Y&Z036, as well as Dr. Yi Liu (Chalmers University of Technology, Sweden) for the help in engineering peroxisome biogenesis.
Funding
The authors acknowledge funding from National Natural Science Foundation of China (21877111). The authors thank the Energy Biotechnology Platform of DICP for providing facility assistance.
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NG, JG, WY, SK, performed all the experiments and data analysis. JQ and YJZ wrote the manuscript. YJZ conceived the study. All authors read and approved the final manuscript.
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Yongjin J. Zhou, Ning Gao and Jiaoqi Gao have filed a patent for protecting the production of fatty alcohol in yeast. All other authors declare no conflicts of interest.
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Additional file 1: Figure S1
. Flowchart of yeast strain construction for fatty alcohol production. S. cerevisiae strain was constructed for fatty alcohol production with either episomal synthetic pathway (plasmids), or integrated synthetic pathway (genome). Figure S2. Changes in fluorescence intensity with time of GFP under control of promoter PGAL1,10. Figure S3. Fatty alcohol production by fatty acyl-CoA reductase (FAR) from different species. Figure S4. Promoter characterization that responds to exogenous fatty acid and endogenous acyl-CoA based on transcriptional data. Figure S5. Promoter characterization that responds to endogenous fatty acid based on transcriptional data. Figure S6. Coordinated cytosolic and peroxisomal biosynthetic pathways promoted fatty alcohol production. Figure S7. Fatty acid/acyl-CoA responsive promoters for enhanced production of 3-hydroxypropionic acid (3-HP). Figure S8. Expression cassettes for genetic manipulation by CRISPR/Cas9 in this study. Figure S9. Sketch map of plasmid construction for screening fatty acid/acyl-CoA responsive promoter. Table S1. Promoter candidates that respond to fatty acid. Table S2. Promoter candidates that respond to fatty acyl-CoA. Table S3. Strains used in this study. Table S4. Plasmids used in this study. Table S5. Primers used in this study. Table S6. Codon optimized genes used in this study.
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Gao, N., Gao, J., Yu, W. et al. Spatial–temporal regulation of fatty alcohol biosynthesis in yeast. Biotechnol Biofuels 15, 141 (2022). https://doi.org/10.1186/s13068-022-02242-7
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DOI: https://doi.org/10.1186/s13068-022-02242-7