Abstract: Propanol have been widely used as a precursor for erythromycin synthesis in industrial production. However, the knowledge on the exact metabolic fate of propanol was still unclear. In the present study, the metabolic fate of propanol in industrial erythromycin-producing strain S. erythraea E3 was explored via13C labeling experiments. An unexpected pathway in which propanol was channeled into tricarboxylic acid cycle was uncovered, resulting in uneconomic catabolism of propanol. By deleting the sucC gene, which encodes succinyl-CoA synthetase that catalyse a reaction in the unexpected propanol utilization pathway, a novel strain E3-ΔsucC was constructed. The strain E3-ΔsucC showed a significant enhancement in erythromycin production in the chemically defined medium compared to E3 (786.61 vs 392.94 mg/L). Isotopic dilution mass spectrometry metabolomics and isotopically nonstationary 13C metabolic flux analysis were employed to characterize the metabolic differences between S. erythraea E3 and E3-ΔsucC. The results showed that compared with the starting strain E3, the fluxes of pentose phosphate pathway in E3-△sucC increased by almost 200%. The most significant difference located in the tricarboxylic acid cycle was also found. The flux of the metabolic reaction catalyzed by succinyl-CoA synthetase in E3-ΔsucC was almost zero, while the glyoxylate bypass flux significantly increased. These new insights into the precursor utilization of antibiotic biosynthesis by rational metabolic engineering in S. erythraea provide the new vision in increasing industrial production of secondary metabolites.
Keywords: Saccharopolyspora erythraea , Erythromycin, Metabolic flux analysis, N-propanol, Succinyl-CoA synthetase.
Introduction
Erythromycin is an important broad-spectrum antibiotic of macrolides (Oliynyk et al., 2007) and Saccharopolyspora erythraea is the major industrial erythromycin-producing strain (Butler, 2008). With the accumulation of knowledge on erythromycin biosynthesis genes and biochemical pathways, rational strain design has become a powerful strategy to improve the titer and productivity of erythromycin and the proportion of active component (Chen et al., 2008; Li et al., 2013; Wu et al., 2011; Liu et al., 2017). The biosynthesis of erythromycin is mainly divided into two parts. One propionyl-CoA and six methylmalonyl-CoA are firstly condensed to 6-deoxyerythromycinB (6-dEB), then 6-dEB is post-modified to erythromycin A (Mironov et al., 2004). Wang et al. (2007) integrated the exogenous S-adenosylmethionine (SAM) synthase gene into the S. erythraea genome to promote the post-modification of 6-deoxyerythronolideb, which ultimately increased the yield of erythromycin A by 132%. Chen and Liu et al. (2008) succeeded in reducing the contents of the impurity components of erythromycin B and C in the fermentation broth by regulating the copy number of the genes (eryG and eryK ) encoding the erythromycin post-modification enzymes.
Propanol has been widely used as a precursor of propionyl-CoA for erythromycin synthesis (Chen et al. 2013). And it has been well known that the addition of propionic acid or n-propanol significantly stimulates the synthesis of erythromycin. Bojanowsa et al. (1973) firstly found that propionate kinase activity was positively correlated with the rate of erythromycin synthesis. Recently, Hong Ming et al. (2016) pointed out that the change of intracellular propionyl-CoA concentration presented a direct positive correlation with the erythromycin productivity. On the other hand, Chen et al. (2013) demonstrated that the addition of n-propanol caused an obvious drop of dissolved oxygen, indicating that n-propanol might be utilized as a carbon source apart from glucose, however, it is considered to be not cost-effective for industrial fermentation process as the relatively high price of commercial n-propanol.
13C isotope labeling experiment is a quantitative method enabling to directly study the effects of environmental or genetic changes on cell metabolism, thereby providing scientific guidance for further metabolic engineering and fermentation process regulation (Becker and Wittmann, 2012). Hong Ming et al. (2017) carried out isotope labeling experiments with [U-13C] glucose and naturally-labelled proline in S. erythraea and showed that proline was catabolized into TCA cycle to provide energy and NADPH. In addition, proline could also increase the energy load of the cells, thereby reducing the cellular metabolism burden.
In this study, on the basis of carbon atom transition map of propanol catabolism derived from KEGG database, two possible propanol catabolism pathways in S. erythraea were identified by labeling experiments using 13C-labeled sodium propionate as the substrate. Subsequently, a novel strain was constructed by knocking-out the genes involved in the unexpected uneconomic propanol catabolism pathway. And the effects of gene modification was investigated by integration of isotopic dilution mass spectrometry (IDMS) metabolomics and isotopically non-steady 13C metabolic flux analysis (13C-MFA). This study demonstrated how13C labeling experiments can be applied to identify unknown metabolic pathways and to rationally explore the potential targets of gene engineering of S. erythraea , thus achieving a ”design-build-validate-guidance” metabolic engineering cycle (Fig. 1).
  1. Materials and methods
  2. Strains and culture conditions
S. erythraea E3 was used as the parent strain. Other strains and plasmids used were listed in the supplementary materials.
Spores were inoculated to 500 mL shake flasks at 220 rpm and cultured at 34 ℃ for 48 h. Before inoculating the culture solution to a 5 L tank for fermentation culture, the shake flask culture solution was firstly washed, and then cultured and sampled according to the previous reported method (Hong et al., 2017). 5 μg/mL thiostrepton and 10 μg/mL apramycin were added to the medium. The E. coli DH5α was used in cloning experiments, which was grown at 37 ℃ in the Luria-Bertani liquid medium (Hopwood et al., 2000).
Intracellular sample preparation
The samples in the labeling experiment were obtained by a fast sampling device independently designed by our research group (Fig. 2). The rapid sampling device has the characteristics of simplicity, reliability, strong applicability, which can quickly draw a sample within 1 second under minimum hardware conditions, and introduce multiple sets of sampling pipes of different pipe diameters to improve the compatibility of different fermentation processes (broth with low or high viscosity) (Wang et al., 2018). Methods for extracting different intracellular metabolites were performed according to the previous report (Hong et al., 2017). Briefly, phosphorylated sugar and coenzyme A substances were extracted by liquid nitrogen grinding method, while boiling ethanol method was suitable for organic acid extraction.
  1. Analytical methods
  2. Cell concentration and erythromycin titer
5 mL fermentation broth was centrifuged at 4000 rpm for 5min. After removing the supernatant, the precipitate was dried at 80 ℃ for 48 h, and dry cell weight was used to represent the cell concentration (Zhang et al., 2014). Oxygen uptake rate (OUR) and carbon dioxide evolution rate (CER) was calculated online as reported (Liang et al., 2011; Parekh et al., 2000). The erythromycin titer and components were measured by high performance liquid chromatography as previously described by Zou et al. (2009).
[1-13C] sodium propionate labeling experiment
The labeling experiments were carried out at 34°C in a 250 mL mini tank (Fig. 3). Due to the absence of labeled n-propanol for sale on the market and considering the fact that n-propanol firstly converts into propionic acid under the presence of alcohol dehydrogenase,13C labeled sodium propionate instead of n-propanol was used as labled substrate. The temperature of the fermentation broth was controlled at 34°C using the heating coil of the tank. By controlling the stirring rate and the aeration, the dissolved oxygen of the fermentation broth was maintained over 30%. The maximum agitation was 500 rpm and the maximum aeration was 300 mL/min.
After inoculating for 48 h in a 5 L bioreactor, 150 mL of the fermentation broth in the 5 L bioreactor was pumped into a 250 mL mini bioreactor using a sterile tube. At the same time, 0.2 g/L [1-13C] sodium propionate (Cambridge Isotope Laboratories, 98% isotopic purity) (the final concentration in the fermentation broth) was added into the 250 mL mini tank. Then, continuous sampling was carried out from the mini tank at the designed time point.
Metabolic transformation of S. erythraea strain
Plasmid pOJ260 (Bierman et al., 1992), which was used for generating the knockout of sucC in strain S. erythraea E3, has thiostrepton-resistance gene (tsr ) and apramycin-resistance gene (acc ). Plasmid pOJ260 can be amplified in E. coli , but it cannot be amplified in S. erythraea . The plasmid pOJ260-ΔsucC as a gene knockout cassette was generated as following steps (Fig. S1). The 1.021-kb fragment of sucC -H was made by PCR amplification of the S. erythraea genomic DNA using the primers A1, 5’-CCC AAG CTT GGG ATG AGG CCA AGA CGA A-3’and A2, 5’-GAA GAT CTT CGC CCT GGA CGA TGA CCT TG -3’. The sucC-H fragment and the plasmid pOJ260-tsr were digested with restriction enzymesHin dIII and Bgl II simultaneously, and the products were ligated. The plasmid pOJ260-ΔsucC was constructed and propagated in E. coli DH5α. The DNA sequence of the gene knockout cassette was verified by sequencing (Takara). Finally, it was introduced fromE. coli to S. erythraea E3 using the standard conjugational transfer methods.
The mutant S. erythraea E3-ΔsucC (E3-ΔsucC ) was constructed by the addition of sucC partial ORF via the sucC-H fragment from the cassette (Fig. S1). A single crossover plasmid insertion was performed with pOJ260-ΔsucC by homologous recombination (Matsushima et al., 1994) into the genome of original strain E3 with screening by thiostrepton resistance and apramycin resistance, to form the gene-knockout strain E3-ΔsucC .
The primers B1, 5’-AAC TCT TCG CCT CCC ACG GCG T-3’ , B2, 5’-TCA CCA GCT CCG CGA AGT CGC T-3’, C1, 5’-CTG ACC GGC AAT CAC CAA CGC AA-3’ and C2, 5’-ACG GAG CCG AAG ACG GTG AGC T-3’ flanking, the inserted gene knockout cassette were used for the identification of correct mutants by PCR.
Isotopically nonstationary labeling experiments
Triplicate cultures of E3 and E3-ΔsucC were inoculated to an initial 0.78 gDCW/L in 3 L optimized synthetic medium in the 5 L fermenter. The labeling experiment was initiated at 50h, when the cells reached a cell density of approximately 5~6 gDCW/L. A 140-mL sample corresponding to t=0 (unlabeled) was withdrawn from the 5 L fermenter using a pump and sterilized latex tube to the three parallel 250 mL fermenters. 6 M NaOH filter bottle was used to prevent unlabeled CO2 in the air entering the system. A 30 mL aliquot of media with different ratios of labeling glucose (Cambridge Isotope Laboratories, 99% isotopic purity) was quickly introduced to the fermenter to achieve a final trace concentration. Following this pulse, a series of 2-mL samples were withdrawn and rapidly quenched at time points 10, 20, 30, 40, 50, 60, 80, 100, 130, 150, 180 s, respectively. Each sample was quenched in a 50-mL centrifuge tube that contained 30-mL liquid nitrogen. In particular, one needed to be filtered into the liquid nitrogen after the supernatant was filtered for removal of extracellular organic acids, since the concentration of extracellular organic acids are several orders of magnitude higher than the intracellular organic acids (Mashego et al., 2007). The cell pellet was extracted using a previously reported extraction method (Hong et al., 2017). Dried extracts were stored at -80℃ prior to detection.
LC–MS/MS measurement of metabolite abundance information and pool size
The major fragment patterns of metabolites and its 13C derivative was adapted from Seifar et al. (2013) and was performed on a Thermal Ultimate 3000 UPLC system coupled to a Thermal TSQ QUANTUM ULTRA mass spectrum system at the State Key Laboratory of Bioengineering, East China University of Science and Technology, Shanghai China. An ACQUITY UPLC BEH C18 column (1.7 μm, 2.1*150 mm) was used with gradient elution. The eluents used were 5% acetonitrile aqueous solution with 5mM dibutylammonium acetate (A) and 84% acetonitrile aqueous solution with 5mM dibutylammonium acetate (B). All the chemicals were HPLC or LC-MS grade and purchased from Sigma Aldrich, USA. An injection volume of 2 μL was used, and the column flow rate and temperature were kept constant at 5 μL/min and 25℃, respectively. In order to determine the intracellular metabolites precisely,13C-labeled internal standards were added to the samples after quenching (Wu et al., 2005). The gradient profile of different metabolites was adapted from Hong et al. (2017). The acquisition of concentration and isotope data was performed using negative electrospray ionization in the selected reaction monitoring (SRM) mode. The final parameters used for isotomer measurements are listed in Supplementary materials. All data acquisition and evaluation were performed on the Xcalibur software (Thermal Scientific) supplied with the instrument.
Metabolic network model and 13C-metabolic flux analysis
The central carbon metabolism network of S. erythraea consists of EMP pathway, TCA cycle, PP pathway, ED pathway, glyoxylate shunt, amino acid synthesis reaction, one-carbon unit metabolism, amphibolic reactions, acetic acid synthesis, exchange reaction (transport reaction) and bacterial synthesis reaction with a total of 68 reactions. The metabolic network is a simplification of the metabolic model of S. erythraea in the KEGG database. The central carbon metabolic network ofS. erythraea can be found in the supplementary materials (Table S3).
All 13C-metabolic flux analysis was calculated with INCA software (Young, 2014), which was based on the EMU algorithm framework (Young et al., 2008). Metabolic fluxes were estimated by minimizing the variance-weighted sum of squared residuals (SSR) between the experimentally measured and model predicted external rates and mass isotopomer distributions using non-linear least-squares regression (Antoniewicz et al., 2006). All measured mass isotopomers were provided in Supplemental materials. Flux estimation was repeated more than 10 times starting with random initial values for some key fluxes to find a global answer. The exact 95% confidence interval for all estimated fluxes was calculated by evaluating the sensitivity of the minimized SSR to flux changes. Standard deviations of estimated fluxes were determined as follows:
SD= [(fluxupper bound 95%)-(fluxlower bound 95%)]/4 (1)
To determine the goodness-of-fit, 13C-MFA fitting results were subjected to a χ2-statistical test. In short, assuming the model is correct and the data has no serious measurement errors, the minimized SSR is a random variable with a χ2 distribution (Antoniewicz et al., 2006). Acceptable range of SSR values is between χ2α/ 2(n-p ) and χ21-α/ 2(n-p ), where α is a certain selected threshold value, for example, 0.05 for 95% confidence interval.
  1. Results
  2. Identification of n-propanol catabolism pathways
According to KEGG database, two pathways were speculated to catabolize the propanol into tricarboxylic acid (TCA) cycle (Fig. 4). Propanol was firstly converted to propionyl-CoA, then to methylmalonyl-CoA and succinyl-CoA sequentially in pathway I, or to malonyl-CoA and acetyl-CoA sequentially in pathway II. In terms of the previous report (Mironov et al., 2004), malonyl-CoA decarboxylase in S. erythraea catalyzes the conversion of malonyl-CoA to acetyl-CoA. However, it existed many gaps in the remaining metabolic pathways, and the complete metabolic pathway cannot be actually presented.
The labeling experiments using 13C-labeled sodium propionate were conducted to identify the activities of these two possible pathways on the basis of carbon atom transition map derived from KEGG database (Fig. 5). The temporal significant increases of labelling enrichments (M1, M2 and M3) in propionyl-CoA (Fig. 6A) and succinyl-CoA (Fig. 6B) indicated the obvious activity of pathway I. The increase of M2 and M3 in malonyl-CoA (Fig. 6C) hinted the activities of the reactions from propionyl-CoA to malonyl-CoA in pathway II, but the almost unchanged labelling enrichments in acetyl-CoA (Fig. 6D) showed the very low or even no activity of the reaction which converts malonyl-CoA to acetyl-CoA. In order to increase the industrial conversion of n-propanol to erythromycin, blocking pathway I to reduce the catabolism of n-propanol should be a feasible strategy.
Construction of engineered strain E3-ΔsucC and comparison of cell growth and erythromycin synthesis
As the fact that propanol can be catalyzed through the pathway I and TCA cycle (Fig. 5), it was assumed that the block of the connection from n-propanol metabolism to TCA cycle could improve the conversion yield of n-propanol to erythromycin. A novel strain E3-ΔsucC was constructed by knocking-out the sucC gene (succinyl-CoA synthetase), which catalyzes succinyl-CoA to succinate. Theoretically, more carbon flux can be pushed towards erythromycin production insucC -knockout strain due to succinyl-CoA and unable to be converted to succinate (Fig. 7). Moreover, as the conversion of α-ketoglutarate to succinyl-CoA was irreversible, this strategy can not only decrease the catabolism of n-propanol, but also can promote the precursors derived from glucose to erythromycin synthesis.
Initially, it was hypothesized that the partial defect of TCA cycle in E3-ΔsucC might result in the decrease of cell growth, however, the influence on DCW of E3-ΔsucC was not significantly different with E3 (Fig. 8A), indicating the low metabolic burden due to initial medium composition and increased glyoxylate cycle activity to compensate for short circuit in TCA cycle. As expected, it was observed that the erythromycin concentration of E3-ΔsucC (786.6 mg/L) was almost two-fold of E3 (392.94 mg/L) in 5 L fermenter (Fig. 8A), and similar trends were observed in flasks (Fig. S3), which was in supplementary materials.
Although the feeding rates of n-propanol were basically the same in the fermentation processes of two strains, the residual n-propanol concentration of E3-∆sucC was obviously lower than that of E3 (Fig. 8B), demonstrating that the n-propanol consumption of E3-∆sucC was higher. The decline of residual n-propanol concentration after 84 h might imply the insufficient supply of n-propanol. The metabolic activity of the engineered strain might be stronger compared with the starting strain. After entering the stationary period, the engineered strain showed a stable OUR level compared with the OUR of the starting strain, which presented a gradual decline in the late phase, moreover, the CER level of the engineered stain in the whole fermentation process were higher than that of the starting strain (Fig. 8C).
After knocking out of sucC gene, S. erythraea exhibited obvious changes in some key physiological parameters (Table S3). The specific glucose consumption rate and propanol consumption rate were increased from 0.049 to 0.067 mmol/gDCW/h and 0.058 to 0.083 mmol/gDCW/h, respectively. In contrast, the specific erythromycin production rate (qerythromycin) and the conversion yield of n-propanol to erythromycin (Yerythromycin/propanol) were significantly increased by 52% and 81%, respectively. In terms of cell respiratory metabolism, including the specific carbon dioxide evolution rate and specific oxygen uptake rate, the engineered strain had no significant changes compared to the starting strain.
Intracellular metabolites pool size and isotopically non-stationary metabolic flux analysis
Targeted metabolomics analysis was applied to examine the intracellular metabolite levels in each strain since intracellular reaction rates are correlated with intracellular metabolite pool sizes and activities of correspondent enzymes (Jazmin et al., 2017). Fig. 9 showed the pool sizes of key metabolites in glycolysis (EMP), TCA cycle and pentose phosphate (PP) pathway during the stationary phase. Knocking outsucC gene led to an almost 2-fold increase in α-ketoglutaric pool size compared to E3, indirectly identifying the inactivation of succinyl-CoA synthetase. This result may be caused by the feedback inhibition of α-oxoglutarate (AKG) on citrate synthase (Wright et al., 1967). The intracellular phosphorylated compounds, such as glucose 6-phosphate (G6P) and fructose 1,6-bisphosphate (FBP)presented downward trends. Notably, the concentration of FBP in E3-ΔsucC was relatively lower than that in E3 (Fig. 9), indicating a low metabolic flux of the EMP pathway (Bennett et al., 2009). Interestingly, the intracellular metabolites in PP pathway showed opposite trends. The ribulose-5-phosphate (Ru5P), R5P (ribose-5-phosphate) and E4P (erythrose 4-phosphate) in E3-ΔsucC were in upward trends during the stationary period, which reflected a high activity of PP pathway.
The synthesis of erythromycin required one propionyl-CoA and six methylmalonyl-CoA (Chan et al., 2009). As two important precursors of erythromycin, the rise of the intracellular pools of propionyl-CoA and methylmalonyl-CoA was consistent with the increase of erythromycin synthesis rate. Comparing to the coenzyme A trend in E3-ΔsucC , the intracellular pools of both propionyl-CoA and methylmalonyl-CoA increased, implying that the significant decrease in the concentration of intracellular precursor coenzyme A was a key factor affecting erythromycin synthesis.
INST-MFA was applied to characterize the metabolic phenotypes of E3 and E3-ΔsucC . The measured MIDs, the substrate consumption rates, the cell growth rate and the erythromycin productivity were used to construct comprehensive flux networks using a modified version of the reaction network developed by Hong et al. (2017). The flux network of E3-ΔsucC and E3 (Fig. 10) were statistically acceptable based on a chi-square test of the SSR (SSR = 471.9 was within the expected range [380.0, 495.7] for E3 and SSR = 193.9 was also within the expected range of [184.4, 267.3] for E3-ΔsucC ). The full list of optimal parameter estimates including net fluxes and exchange fluxes for both E3 and E3-ΔsucC could be found in the Supplementary Materials.
The metabolic flux distribution indicated that most of the NADPH was from PP pathway, which provides reducing power for erythromycin synthesis. It could be speculated that the overexpression of NADPH synthase or increasing the metabolic flux of PP pathway would further improve the erythromycin yield (Chen et al., 2017). We also observed little or no flux through the reaction of ‘SucCoA→Suc’, which was in agreement with the expectation of genetic manipulation in E3-ΔsucC . Additionally, there was minimal flux through the EMP pathway, which was consistent with intracellular phosphorylated sugar concentration. In particular, the fluxes of reaction ‘F6P→FBP’ of E3-ΔsucC was almost zero (Fig. 10), indicating that the glucose was seldom metabolized through the EMP pathway. This result might be caused by the inhibition of phosphofructokinase (PFK) (Borodina et al., 2008; Hong et al., 2017).
The flux analysis highlighted the activity of glyoxylate shunt in E3-ΔsucC (0.23 vs 0.00 mmol/gDCW/h). Glyoxylate by-pass can replenish and repair defective TCA cycles. However, there was minimal flux through the oxidative arm of the TCA cycle (from citrate to α-ketoglutarate), which reduced the level of oxidative phosphorylation and limited the energy supply. The significant decrease in succinyl-CoA synthetase flux was necessary to supply substrate for erythromycin production. This finding verified a major alternative route for succinic acid formation and demonstrated that the strains constructed for metabolic engineering exhibited a relatively significant advantage in the erythromycin synthesis.
Discussion
This study demonstrated that the knowledge from pathway identification could be used to guide rational metabolic engineering to improve strain performance. The labeling experiments using 1-13C sodium propionate identified the activity of n-propanol catabolism pathway in S. erythraea based on the carbon atom transitions of n-propanol and the measured enrichments of intracellular coenzyme A metabolites. The availability of carbon atom transitions is critical for revealing the activity of alternative metabolic pathways (Fan Jing et al., 2014; Li Bo et al., 2014; Andrew R. Mullen et al., 2012). To the best of our knowledge, the carbon atom transitions of n-propanol catabolism pathways in S. erythraea was constructed and used to demonstrate the presence of oxidative catabolism in the utilization of propanol in S. erythraea for the first time.
According to the fact that n-propanol was not only acting as a precursor for erythromycin synthesis but also could be catabolized into TCA circle through pathway I, the genes involved in this pathway reasonably became the target for gene manipulations in order to enhance erythromycin synthesis. The significant increase of erythromycin production in strain E3-ΔsucC (Fig. 8) was expectable. Although the beneficial effects on erythromycin synthesis by deleting genes involved in n-propanol catabolism have been reported in our previous study (Chen et al., 2016), where the knock-out of mutB gene encoding the beta subunit of methylmalonyl-CoA mutase led to an obvious increase of erythromycin synthesis, the results of knocking-out sucC gene was reported for the first time. In this study, atomic migration and labeling experiments rationally confirmed the n-propanol metabolic pathway and corresponding transformation target, and combining the intracellular metabolomics with metabolic flux analysis elucidate the mechanism and guide the future industrial production, which had universal significance and application for the antibiotic strain construction.
Metabolic modification of specific targets for industrial production strains is one of the most important ways to improve antibiotic production (Young et al., 2011; Jazmin et al., 2017). Deletion ofSACE_Lrp (an efficient regulator for transporting and catabolizing branched-chain amino acids (BCAAs)) of industrial strain WB combined with overexpression of its target SACE_5387-5386enhanced erythromycin production by 41% (Liu et al., 2017). In this study, deletion of SACE_6669 (sucC ) of industrial strain E3 significantly increased erythromycin production. It is of great interest to improve the potential synergies of erythromycin production through different synergistic mechanisms. Therefore, further study will continue to knock out gene encoding succinyl-CoA mutase and succinyl-CoA synthetase to block the flow of n-propanol to the TCA cycle and over-express the polyketide synthase gene to introduce the precursor into erythromycin synthesis, which is expected to obtain high-efficient industrial recombinant producer. Importantly, our work also reveals a potential for broader applications for metabolic reconstruction of industrial strains.
The metabolic flux networks of E3 and E3-ΔsucC were determined using chemically-defined medium by INST-MFA. INST-MFA is ideally suited to systems that label slowly due to the presence of large intermediate pools or pathway bottlenecks (Cheah and Young, 2018). The observation of very little flux of reaction converting succinyl-CoA to succinate in strain E3-ΔsucC was consistent with the expectation of knocking out sucC gene. Previous studies have inferred that the erythromycin synthesis was increased by 126% by blocking the flux to TCA cycle (Reeves et al., 2006). Therefore, the low flux throughsucC may serve as a key route in order to pull more carbon to erythromycin synthesis. In spite of the apparent importance ofsucC flux, the E3-ΔsucC strain showed a rapid drop of cell density in the stationary phase, which seemed to be ascribed to the depletion of intracellular succinate (Fig. 9), suggesting that decreasing the flux from succinyl-CoA toward succinate should be balanced by increasing the flux of glyoxylate bypass simultaneously.
One potential concern is that we did not attempt to optimize the culture conditions of fermentation systematically, since this was not a goal of our study. We performed all experiments under the same standard culture conditions described in the Materials and Methods section, and when the engineered strain was in the stationary phase, the cell mass decreased rapidly, leading to a shortened final fermentation duration, which restricted the further synthesis of erythromycin. According to the literatures, we noted that nitrogen source in the erythromycin production phase played an important role that stimulating the synthesis of ppGpp and initiating transcription and translation of antibiotic synthesis genes (Chakraburtty and Bibb, 1997). In previous study, Enshasy et al. (2008) used molasses as a carbon source, corn syrup and ammonium sulphate as nitrogen sources, and erythromycin production increased by 33% compared to the original formulation. Therefore, we performed an additional experiment to investigate the effects of ammonium sulphate supplementation on the erythromycin of E3-ΔsucCstrain (Fig. S4). Importantly, the total content of erythromycin A was significantly improved than E3-ΔsucC in ammonium sulphate-free media. This result suggests that the addition of the ammonium sulphate can enhance cell growth of mid-late of phase of fermentation. The mechanism of the enhancement of erythromycin A by the addition of ammonium sulfate will be further explored. Finally, it is important to note that this article is a general DBVG method that can be extended to the other strains for its genetic modification and process optimization.
Conclusions
Overall, this study demonstrated the metabolic fate of propanol in the erythromycin production process via 13C labeling experiment. At first, the metabolic engineering target was identified, and subsequently an engineered erythromycin high producer was constructed. Finally, the effectiveness of engineering strain modification was analyzed through combining INST-MFA with targeted metabolomics. [1-13C] sodium propionate labeling experiment revealed an active pathway in S. erythraea E3 and suggested that enzymes involved in propanol catabolism could be potential targets for debottlenecking flux towards TCA cycle. The target was deleted in the parental S. erythraea E3 strain, and erythromycin production were significantly enhanced. It was the first report, to the best of our knowledge, that the gene encoding succinyl-CoA synthetase has been involved in microbial research, and using unsteady isotope labeling experiment for metabolic flux analysis of secondary metabolism of S. erythraea . However, further work shall quantify the medium composition and optimization of culture process in order to realize the industrialization of engineered strain. In addition, future studies are required to examine additional engineering targets to increase precursor conversion rate. In short, our work on account of 13C flux analysis was proved useful to identify rational targets for strain improvement that provide basis and valuable information for further enhancement in erythromycin production.