Enhanced protocatechuic acid production using metabolically engineered Corynebacterium glutamicum

Enhanced protocatechuic acid production using metabolically engineered Corynebacterium glutamicum | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhanced protocatechuic acid production using metabolically engineered Corynebacterium glutamicum Jiwoon Chung, Jaehoon Cho, Woo-Shik Shin, Chulhwan Park This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3814902/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Protocatechuate acid (PCA) is a phenolic acid naturally synthesized by various microorganisms. To enhance PCA production during fermentation using Corynebacterium glutamicum , a statistical optimization of the production medium was performed using full factorial design, the steepest ascent method, and the response surface method. The optimized production medium enabled PCA production of over 5 g/L in a 72-h batch culture. PCA cytotoxicity affected strain growth and PCA production rate, with an inhibitory concentration of approximately 5 g/L in the fermentation broth. Finally, continuous fermentation was operated for 150 h in steady-state mode, maintaining the concentration of PCA below 5 g/L. The optimization method established in this study successfully increased PCA production levels, and the findings presented herein are anticipated to contribute to the industrialization of PCA production using C. glutamicum. Protocatechuate Corynebacterium glutamicum Statistical medium optimization Continuous cultivation Figures Figure 1 Figure 2 Figure 3 Introduction Protocatechuic acid (PCA; 3,4-dihydrobenzoic acid) (Lin et al., 2007 ) is a phenolic compound commonly found in over 500 plant and microbial species (Liu et al., 2016 ; Buskaran et al., 2021 ; Punvittayagul et al., 2022 ; Tian et al., 2022 ). PCA is a precursor of industrially significant aromatic compounds such as vanillin and cis-cis muconate (Lin et al., 2011 ; Weber et al., 2012 ; Zhang et al., 2021 ). Additionally, PCA anticancer activities have been demonstrated against human cancer cell lines such as MCF-7, A549, HepG2, HeLa, and LNCaP (Yin et al., 2009 ). High production expenses and limited production yields are the complications associated with PCA (Juurlink et al., 2014 ; Pugh et al., 2014 ; Wang et al., 2018 ). Several studies have been conducted on microbial production to enhance PCA yield, and its synthesis has been attempted using microorganisms such as Escherichia coli (Chen et al., 2020 ), Pseudomonas putida (Li and Ye, 2021 ; Om et al., 2021), and Corynebacterium glutamicum (Shmonova et al., 2020 ; Kogure et al., 2021 ). C. glutamicum strains are used industrially to produce amino acids and nucleotides and are generally recognized as safe microorganisms (Wendisch et al., 2016 ; Lee and Kim, 2018 ). C. glutamicum maintains its growth rate even at concentrations that inhibit aromatic compound growth in other strains (Li et al., 1999 ; Liu et al., 2016 ; Kogure and Inui, 2016; Chen et al., 2017 ; Conrady et al., 2019 ; Lin et al., 2022 ). However, 1.5 g/L PCA restricts the growth of E. coli (Pugh et al., 2014 ) because of the hydrophobic characteristic of aromatic compounds, such as PCA, which can accumulate in phospholipids within the membranes and cause membrane instability (Pugh et al., 2014 ; Kogure et al., 2021 ; Zhang et al., 2021 ). The enzyme 3-dehydroshikimate dehydrogenase of the PCA production pathway affects PCA productivity by feedback inhibition, which can be reduced by PCA with a Ki of approximately 0.38 mM and a Ki' of approximately 0.96 mM through competitive and non-competitive inhibition mechanisms (Shmonova et al., 2020 ). In addition, P. putida strains with similar metabolic pathways show feedback inhibition of aromatic amino acids on intermediate enzymes in the PCA production pathway, where conversion of erythrose-4-prosphate and phosphoenolpyruvate to 3-deoxy-D-arabino-heptulosonic acid 7-phosphate affects the production rates (Li and Ye, 2021 ). In this study, we employed process optimization to overcome these limitations and enhance PCA production efficiency. The strain utilized in PCA production, C. glutamicum AK103, was engineered: the pcaGH gene, which encodes the enzyme that converts PCA to catechol, and the aroE gene, which encodes the enzyme that converts the PCA precursor, 3-dehydroshikimate (DHS), to shikimate, were removed (Li et al., 1999 ; Li et al., 2018). These modifications allow the strain to accumulate PCA. Deletion of the aroE gene in the AK103 strain blocks the biosynthetic pathway of aromatic amino acids, resulting in feedback inhibition of DHAP synthase (Li et al., 1999 ; Li and Ye, 2021 ). However, supplying aromatic amino acids to the culture medium is problematic. To solve this problem, we optimized the concentration of yeast extract that supplied aromatic amino acids to the initial PCA production medium. We further used statistical optimization methods, such as full factorial design, steepest ascent method (SAM), and response surface method (RSM), to adjust the medium composition. The three statistical media optimization methods presented were used for process development or bio-based production, and the experiments designed using the program were used to identify the interactions between media components and the product and the optimal point. We also established the conditions for continuous culture of C. glutamicum through preliminary experiments, thereby overcoming limitations in the maximum concentration of the product. Material and Methods Strains, media, and plasmids The C. glutamicum AK103 strain was derived from the wild-type strain ATCC 13032 (Li et al., 2018). Yeast extract and brain heart infusion (BHI) were purchased from Becton Dickinson (Franklin Lakes, NJ, USA). Glucose, ammonium sulfate, and sodium hydroxide were purchased from Duksan (Ansan, Korea). Hydrochloric acid, Antifoam 204, kanamycin sulfate, magnesium sulfate, and calcium chloride were purchased from Sigma-Aldrich (St. Louis, MO, USA). The Masterflex® L/S® pump used for flow-through and continuous culture was purchased from Masterflex (Gelsenkirchen, Germany). C. glutamicum strains were grown in BHI medium, with 48 h growth cultures in solid medium. BHI was composed of calf brain infusion 7.7 g/L, beef heart infusion 9.8 g/L, proteose peptone 10 g/L, dextrose 2 g/L, sodium chloride 5 g/L, and disodium phosphate 2.5 g/L. Liquid cultures were grown by inoculating the colonies in BHI broth and performing a 15 h primary liquid culture at 30℃ and 200 rpm, followed by a 9 h secondary growth culture. The secondary growth culture was used as an inoculum for PCA production cultures. The PCA production medium was inoculated with a secondary culture aliquot at 5% (v/v). After inoculation, the cultures were shaken for 72 h at 30°C and 200 rpm. In addition, for the vector-inserted strains, 25 ppm kanamycin was added at all stages of culture. Flask cultures and 5L fermentation For PCA production, a single colony was grown in 37 g/L BHI agar at 30°C for 16 h. The secondary culture was cultivated using 1% (v/v) of the inoculum in the same medium. The production culture was grown in a 300 mL flask, 220 rpm at 30°C, with a working volume of 40 mL, for 3 days. For the production cultures, CPM_1 [50 g/L glucose; 2 g/L yeast extract; 5 g/L urea; 5 g/L ammonium sulfate; 0.5 g/L magnesium sulfate heptahydrate; 0.5 g/L potassium phosphate dibasic; 0.5 g/L potassium phosphate monobasic; and 0.01 g/L calcium chloride] production was used with the appropriate antibiotics. For 5L fermentation, the bottom-driven fermenter used for the production culture was KF-5 (Inchon, Korea), and the culture was grown in 3 L. Air was supplied at 1 bar and 1 vvm, the amount of dissolved oxygen was monitored with a DO probe (Mettler Toledo, Switzerland), and the culture was agitated at 100–300 rpm. Antifoam was added (1 mL/L of production medium) to suppress foam formation. An Inpro® 3030 (Mettler Toledo, Switzerland) pH probe was used to keep the cultures within the optimal growth pH range (6.5–7.2) with 6 N HCl and 6 N NaOH. An inoculum dose of 5% was used for both the growth and production cultures. The fed-batch cultures were supplied with specific components or entire components of the production medium to provide the required limiting substrate (see Results and Discussion). Metabolite analysis PCA and DHS were analyzed using a Waters W2695 HPLC system (34 Maple St., Milford, MA, USA). Samples collected during fermentation were diluted 100 times with distilled water, and the diluted fermentation broth was filtered through a syringe filter (20 µm pore size). HPLC analysis was performed on an HPX-87H column (300 × 7.8 hydrogen form, 9 µm particle size, 8% cross-linkage, Bio-Rad Laboratories, Hercules, California) with an injection volume of 10 µL and column heating at 50 ℃. A 10 mM H 2 SO 4 solution was used as the mobile phase and the flow rate was maintained at 0.6 mL/min. A UV detector was used to analyze the C. glutamicum metabolome. The C. glutamicum , PCA, and DHS metabolites were detected and analyzed at 262 nm using the Waters W2998 HPLC system. The detector's temperature was maintained at 40℃ during analysis. Standard curves were generated to observe organic acid production and sugar consumption. To monitor cell growth, the OD 600 was measured with a UV spectrophotometer (UV1800, Shimadzu, Kyoto, Japan). The optical density at 600 nm was converted to dry cell weight (DCW) using a correlation coefficient of 0.25 (Wei et al., 2022 ). Results Effects of yeast extract as a nitrogen source in production medium To optimize the 5 L lab-scale fermentation, experiments were conducted using the previously developed Corynebacterium glutamicum AK103 strain as the parent strain (Lee et al., 2018). The aroE gene was knocked out in the AK103 strain to enable the biosynthesis of PCA using glucose as the carbon source. The removal of aroE resulted in no aromatic amino acid biosynthesis in AK103 cells. During 80 h of fermentation, PCA production reached approximately 1 g/L, and the PCA precursor, 3-dehydroshikimic acid (DHS), was produced at 0.13 g/L (Fig. 1). DCW increased steadily up to 60 h of incubation, being approximately 4.2 g/L at 60 h, and then decreased slightly to 3.67 g/L at 80 h of incubation, which was confirmed to persist until 132 h, when the fermentation was completed (Fig. 1). In contrast, the initially supplied glucose was utilized in small amounts, with approximately 5 g/L consumed after 80 h of fermentation, indicating low glucose utilization by the AK103 strain. A DCW of 1 g/L was assumed to result from the slow growth rate, and the low yeast extract concentration provided an insufficient supply of amino acids for cell growth. It can also be inferred that the low PCA production levels resulted from the low glucose uptake. In the AK103 strain, the intermediate genes of the metabolic pathway required for the synthesis of aromatic amino acids were also removed. To further confirm the effect of a sufficient supply of aromatic amino acids on PCA production, 100 g/L of dissolved yeast extract was pulse-fed at 82 h (Fig. 1). The results showed that the PCA concentration increased to 3.41 g/L by the end of the fermentation period, and glucose consumption was approximately 15 g/L. This demonstrated that an additional supply of yeast extract in the AK103 strain promoted PCA production. Furthermore, because approximately 300 mL of additional yeast extract was supplied and there was no culture medium evaporation in the fermenter. As our experiments demonstrated the effect of yeast extract on PCA production in CPM_1, we conducted experiments to optimize the production medium containing yeast extract. Statistical optimization of the production medium Factorial design Using C. glutamicum AK103 strains, we optimized the medium for efficient PCA production. We optimized the yeast extract concentration at the flask scale and observed an average production of the highest PCA, of 2.48 g/L, in a production medium containing 18 g/L of yeast extract (Fig. S1). Therefore, for the next step, the concentration of yeast extract in CPM_1 medium was adjusted to 18 g/L. We used a fractional factorial design (FFD) to minimize the number of experiments. The experimental design is shown in Tables S1 and S2. Analysis of variance (ANOVA) was performed using the statistical program Design Expert 12, and the p-value was significant at 0.0128 (Table 1). This indicates that the experimental results were highly reliable, with a validity of > 98%. The equation derived from the ANOVA results was used to evaluate the association between the factors and PCA productivity (Table 1). The ANOVA results showed that, in the current medium composition, urea had a significant effect on PCA productivity compared to other components, with a coefficient of -1.31, indicating that urea composition should be reduced. The coefficient of yeast extract was -0.13, which indicated that it should be similarly reduced in the production medium to increase PCA productivity. Based on the FFD, we determined the major factors affecting PCA productivity and found that optimization should be aimed at reducing the composition of yeast extract and urea, which are nitrogen sources in the production medium. Table 1. ANOVA generated using Design Expert software (Stat-Ease 12) for the two-level factorial design for optimized PCA production. Analysis of variance (ANOVA) Source Sum of squares DF Mean square F-value P-value Model 81.63 25 3.27 6.64 0.0128 A 1.7 1 1.7 3.45 0.1127 B 59.31 1 59.31 120.66 < 0.0001 C 0.2733 1 0.2733 0.5559 0.4841 D 0.5475 1 0.5475 1.11 0.3319 E 0.0323 1 0.0323 0.0658 0.8061 F 0.8839 1 0.8839 1.8 0.2285 AB 0.1042 1 0.1042 0.2119 0.6615 AC 1.66 1 1.66 3.37 0.116 AD 0.0988 1 0.0988 0.201 0.6696 AE 0.5691 1 0.5691 1.16 0.3233 AF 0.0161 1 0.0161 0.0327 0.8624 BC 1.64 1 1.64 3.33 0.1166 BD 1.36 1 1.36 2.77 0.1474 BE 0.1024 1 0.1024 0.2082 0.6642 BF 0.7674 1 0.7674 1.56 0.258 CD 0.0556 1 0.0556 0.1132 0.748 CE 0.6184 1 0.6184 1.26 0.3049 CF 0.0449 1 0.0449 0.0913 0.7727 DE 0.608 1 0.608 1.24 0.3087 DF 4.18 1 4.18 8.51 0.0267 EF 2.52 1 2.52 5.12 0.0642 Residual 2.95 6 0.4916 Cor total 84.58 31 A: glucose; B: urea; C: (NH 4 ) 2 SO 4 ; D: yeast extract; E: KH 2 PO 4 ; F: MgSO 4 ⋅7H 2 O. DF: degree of freedom. Response surface method (RSM) Based on the first-order model equation obtained from the FFD experiments above, the parameters for the SAM experiments were calculated (Table S3) (Jeong et al., 2019). As shown in Table S3, SAM experiments were conducted in six steps, and the highest PCA production was observed in step 4. We designed the central composite design with three key factors (urea, yeast extract, and MgSO 4 ⋅7H 2 O), which most affected PCA production based on FFD (Table 2). The experimental design and the corresponding results are summarized in Table S4. ANOVA of the RSM experiments showed that the model was significant, with a p-value of 0.0159, and a quadratic polynomial was calculated to explain the influence and interaction of the medium components (Table 3). In Fig. 2A, the RSM results are shown in a three-dimensional model with the interactions between each medium composition and the productivity of PCA. The chosen medium composition was named CPM_2 and was comprised of 53 g/L glucose, 1.8 g/L urea, 12.5 g/L yeast extract, 6.6 g/L (NH 4 ) 2 SO 4 , 1.6 g/L MgSO 4 ⋅7H 2 O, 0.6 g/L KH 2 PO 4 , and 0.01 g/L CaCl 2 . To confirm whether the components of CPM_2 enhanced PCA production, flask cultures were established. In flask cultures with CPM_1 containing 2 g/L of yeast extract, 0.26 g/L of PCA was produced. However, with the CPM_2 medium in flask fermentation, PCA production increased approximately 17-fold to 4.4 g/L. These results demonstrated that the series of media optimizations effectively increased PCA productivity. In addition, to determine whether the increased PCA production observed with CPM_2 was applicable at the fermenter scale, we conducted a 5 L fermenter culture fermentation. Batch culture using CPM_2 medium for 72 h resulted in 5.27 g/L of PCA, a 5.27-fold increase in productivity compared to the initial 5 L fermenter fermentation using CPM_1 (Fig. 2B). Moreover, we observed that the DCW, which was initially less than 1 g/L in CPM_1, was greater than 8 g/L after medium optimization. These results suggested that the medium optimization at the flask scale was applicable at the fermenter scale. Table 2. Coding and assigned concentration (g/L) of variables of different central composite design levels (alpha = 1.68). Factor Variable (g/L) -alpha (1.68) -1 0 +1 +alpha (1.68) A Urea 0.52 0.8 1.2 1.6 1.87 B Yeast extract 11.43 12.8 14.8 16.8 18.16 C MgSO 4 ⋅7H 2 O 0.63 0.84 1.14 1.44 1.64 The concentrations of the other components in the production medium were set according to the conditions of Step 4 in Table S3. Code levels -alpha/+alpha represent the axial points, -1/+1 the factorial points as reduced and elevated concentrations and 0 the center point of each factor. Table 3. ANOVA generated using Design Expert software (Stat-Ease 12) of the quadratic models for the central composite design (CCD) for optimized PCA production. Analysis of variance (ANOVA) Source Sum of squares DF Mean square F-value P-value Model 8.35 9 0.9276 5.7 0.0159 A-Urea 6.25 1 6.25 38.38 0.0004 B-Yeast extract 0.9814 1 0.9814 6.03 0.0438 C-MgSO 4 ⋅7H 2 O 0.0316 1 0.0316 0.1939 0.673 AB 0.559 1 0.559 3.43 0.1063 AC 0.0189 1 0.0189 0.1163 0.743 BC 0.0211 1 0.0211 0.1299 0.7292 A 2 0.2917 1 0.2917 1.79 0.2226 B 2 0.0306 1 0.0306 0.1879 0.6777 C 2 0.0291 1 0.0291 0.1789 0.685 Residual 1.14 7 0.1628 Lack of Fit 1.13 5 0.2259 45.48 0.0217 Pure Error 0.0099 2 0.005 Cor Total 9.49 16 A: urea; B: yeast extract; C: MgSO 4 ⋅7H 2 O. DF: degree of freedom. Continuous cultivation: Strategy to address PCA cytotoxicity To confirm PCA cytotoxicity, we conducted gradient plate assays with PCA. For gradient plates, 37 g/L BHI agar was poured into a tilted plate, left to solidify, and 10 g/L PCA-containing BHI agar was added to a flat region of the plate (Fig. S2). The results showed that cells were grown only in the area corresponding to approximately 5 g/L PCA. This phenomenon was also observed in a fed-batch culture supplying additional nutrients. Even when the fed-batch cultures were carried out with yeast extract or the entire CPM_2 medium, the concentration of PCA did not exceed 5 g/L (Fig. S3). We aimed to maintain a steady-state through continuous chemostat cultures. The chemostat achieved a steady-state by supplying medium at a constant rate and removing the same amount of medium to maintain constant cell growth and bioreactor volume. To establish the conditions for maintaining a steady-state in continuous cultures, four preliminary experiments were conducted. The experiments involved adjusting the pump speed in the range of 0.1–0.91 mL/min to control D and supplying medium at various concentrations (1´, 2´, 4´, and 8´) of CPM_2 to adjust the substrate supply rate (Fig. S4). When 1´ medium was supplied, the pump speed was adjusted to provide the necessary substrate for cell growth and PCA production. However, increasing the dilution rate to increase the substrate supply rate led to a washout of cells and an inability to maintain a steady-state (Fig. S3). This result is related to the condition that the specific growth rate (μ) must be equal to the dilution rate to maintain a steady-state in continuous culture. The experiments with 4´ and 8´ medium resulted in a decrease in the PCA concentration. Preliminary experiments to establish the conditions for continuous culture showed that the PCA concentration in the medium could not be kept constant. However, a pump speed of 0.5–0.8 mL/min was adequate to maintain a steady state, and the production medium supplied under these conditions had to be adjusted to a concentration between 1´ and 4´. Supplying 1.2´ glucose and the remaining components at 2´ as CPM_2 at a rate of 0.55 to 0.68 mL/min allowed the maintenance of a steady state. Under steady-state conditions, PCA remained at approximately 4 g/L, and glucose was maintained at approximately 10 g/L (Fig. 3). In addition, by introducing a continuous culture process using C. glutamicum strains, we showed that a continuous culture eliminated the need for multiple batch cultures and achieved the same product concentration, which saves media and the time required for the growth of cultures. Discussion The PCA production process using C. glutamicum was improved using statistical media optimization and continuous culture processes. Aromatic amino acids are essential for cell replication and thus directly affect cell growth and growth associated product formation. The production of PCA by C. glutamicum showed a growth associated product formation in the reference experiment(Fig S1 ), so that a deficit could cause a standstill of cell growth and the entire process. This leads to the assumption that C. glutamicum is auxotrophic for these aromatic amino acids so that they have to be taken up from the medium containing yeast extract. Klotz et al showed the lactic acid concentration and productivity of S. inulinus depending on the nutrient source (Klotz et al, 2017 ). In addition, Lee et al. showed that the presence of sufficient amino acids, provided by the complex ingredients, accelerated cell growth, and subsequent metabolite production presumably increased in the production of muconic acid (Lee et al., 2018 ). Also, our results showed an approximately 17-fold increase in production capacity compared to a previous production medium containing 2 g/L of yeast extract (Fig. S1 ). Based on the above results, it was estimated that 2 g/L of yeast extract in the CPM_1 medium was a limiting substrate for cell growth and PCA production (Fig. 1 ). To evaluate the interaction between two factors, we employed a fractional factorial design (FFD). These were expressed as the following mass balance: PCA = 3.11 + 2.23A-1.36B + 0.09C-0.13D + 0.03E + 0.17F-0.06AB + 0.23AC + 0.06AD-013AD + 0.02AE-0.23BC + 0.21BD + 0.06BE-0.15BF-0.04CD + 0.14CE-0.04CF + 0.14DE-0.36DF + 0.28EF (A, glucose; B, urea, C, (NH 4 ) 2 SO 4 ; D, Yeast extract; E, KH 2 PO 4 ; F, MgSO 4 ⋅7H 2 O 4 ). Interestingly, designing a high concentration of yeast extract in FFD resulted in a diminished effect of the extract because of high initial concentration. Yeast extract with a coefficient of -0.065 had the effect on the production rate and a negative value, which implied a decrease in concentration implying a decline in concentration. As each culture medium component comprising a carbon source, a nitrogen source, and various other substances did not play an independent role but interacted with other components, it was critical to identify their optimal concentrations. The response surface method (RSM), based on the quadratic model of a central composite design (CCD), allows for the evaluation of interactions among all components (Lee et al., 2018 ). Thus, it can statistically lead to maximal production. CCD requires multiple experiments to obtain statistically significant results. In contrast, the SAM design is a statistical experimental method that efficiently evaluates the optimal culture medium concentration based on the FFD design. The center point used in the FFD design showed a PCA production rate of 3.31 g/L (Table S3). Statistical optimization of the production medium CPM_2 achieved a PCA production of 5.27 g/L, a 5.27-fold increase compared to that of CPM_1. Therefore, the process of culture medium optimization enabled decreasing the production of intermediate metabolites and identifying the optimal culture medium concentration that maximized PCA production. However, PCA concentrations exceeding 5 g/L severely inhibited C. glutamicum PCA production. To address the issue of reduced production rates owing to cell toxicity, we introduced a continuous culture process. Continuous cultures are characterized by the dilution rate ( D ), which represents the relationship between the volume of medium supplied per unit of time ( F ) and the bioreactor volume ( V ) (Graf et al., 2020 ). Continuous cultures must be maintained at a steady-state through a continuous supply of media. The steady-state is defined as a constant concentration of cells, products, substrates, pH, and other environmental factors (Yufu et al., 2021). We therefore developed a continuous culture method that operated for 150 h in steady-state mode. In the steady-state, where 4 g/L of PCA was reached, 0.064 g PCA/L⋅h was produced from the elution rate of 16 mL/h of the actual medium, which was 78% higher than the productivity of batch culture. These experiments demonstrated that, compared to batch culture, higher total PCA concentrations could be achieved using continuous culture, successfully addressing the reduced production rates resulting from cell toxicity. By reducing PCA concentration in the production medium, PCA production continued without inhibiting cell growth. These findings suggest various options for improving PCA production and are expected to contribute to an efficient synthesis process. Abbreviations ANOVA, analysis of variance BHI, brain heart infusion DCW, dry cell weight DHS, 3-dehydroshikimate FFD, fractional factorial design PCA, protocatechuate acid RSM, response surface method SAM, steepest ascent method Declarations Availability of data and materials Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was supported by the Technology Development Program [grant number S3148236] funded by the Ministry of SMEs and Startups (Korea) and the Korea Institute of Industrial Technology under the project “Development of eco-friendly production system technology for total periodic resource cycle” (Kitech EO210014). Acknowledgments Authors’ information Jiwoon Chung and Woo-Shik Shin contributed equally as first authors. Chulhwan Park and Jaehoon Cho contributed equally as corresponding authors. 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Lin HH, Chen JH, Huang CC, Wang CJ (2007) Apoptotic effect of 3,4-dihydroxybenzoic acid on human gastric carcinoma cells involving JNK/p38 MAPK signaling activation. Int. J. Cancer 120, 2306–2316. https://doi.org/10.1002/ijc.22571. Lin K, Han S, Zheng S (2022) Application of Corynebacterium glutamicum engineering display system in three generations of biorefinery. Microb. Cell Fact. 21, 14. https://doi.org/10.1186/s12934-022-01741-4. Liu X, Yang Y, Zhang W, Sun Y, Peng F, Jeffrey L, Harvey L, McNeil B, Bai Z (2016) Expression of recombinant protein using Corynebacterium Glutamicum : progress, challenges and applications. Crit. Rev. Biotechnol. 36, 652–664. https://doi.org/10.3109/07388551.2015.1004519. Orn OE, Sacchetto S, van Niel EWJ, Hatti-Kaul R (2021) Enhanced protocatechuic acid production from glucose using Pseudomonas putida 3-dehydroshikimate dehydratase expressed in a phenylalanine-overproducing mutant of Escherichia coli . Front. Bioeng. Biotechnol. 9, 695704. https://doi.org/10.3389/fbioe.2021.695704. Liu C, Wang W, Lin W, Ling W, Wang D (2016) Established atherosclerosis might be a prerequisite for chicory and its constituent protocatechuic acid to promote endothelium-dependent vasodilation in mice. Mol. Nutr. Food Res. 60, 2141–2150. https://doi.org/10.1002/mnfr.201600002. Pugh S, McKenna R, Osman M, Thompson B, Nielsen DR (2014) Rational engineering of a novel pathway for producing the aromatic compounds p-hydroxybenzoate, protocatechuate, and catechol in Escherichia coli . Process. Biochem. 49, 1843–1850. https://doi.org/10.1016/j.procbio.2014.08.011. Punvittayagul, C., Luangsuphabool, T., Wongpoomchai, R (2022) Protocatechuic acid as a potent anticarcinogenic compound in purple rice bran against diethylnitrosamine-initiated rat hepatocarcinogenesis. Sci. Rep. 12, 10548. https://doi.org/10.1038/s41598-022-14888-2. Shmonova EA, Voloshina OV, Ovsienko MV, Smirnov SV, Nolde DE, Doroshenko VG (2020) Characterization of the Corynebacterium glutamicum dehydroshikimate dehydratase QsuB and its potential for microbial production of protocatechuic acid. PLoS One 15, e0231560. https://doi.org/10.1371/journal.pone.0231560. Tian Y, Yang M, Lin CY, Park JH, Wu CY, Kakumanu R, De Ben CM, Dalton J, Vuu KM, Shih PM, Baidoo EEK, Temple S, Putnam DH, Scheller HV, Scown CD, Eudes A (2022) Expression of dehydroshikimate dehydratase in sorghum improves biomass yield, accumulation of protocatechuate, and biorefinery economics. ACS Sustain. Chem. Eng. 10, 12520–12528. https://doi.org/10.1021/acssuschemeng.2c01160. Yufu Zhang, Haibo Xiong, Zhichao Chen, Yunpeng Fu, Qingyang Xu & Ning Chen (2021) Effect of fed-batch and chemostat cultivation processes of C. glutamicum CP for L-leucine production. Bioengineered, 12, 426-439. https://doi.org/10.1080/21655979.2021.1874693 Wang J, Shen X, Rey J, Yuan Q, Yan Y (2018) Recent advances in microbial production of aromatic natural products and their derivatives. Appl. Microbiol. Biotechnol. 102, 47–61. https://doi.org/10.1007/s00253-017-8599-4. Weber C, Bruckner C, Weinreb S, Lehr C, Essl C, Boles E (2012) Biosynthesis of cis,cis-muconic acid and its aromatic precursors, catechol and protocatechuic acid, from renewable feedstocks by Saccharomyces cerevisiae . Appl. Environ. Microbiol. 78, 8421–8430. https://doi.org/10.1128/AEM.01983-12. Wei L, Zhao J, Wang Y, Gao J, Du M, Zhang Y, Xu N, Du H, Ju J, Liu Q, Liu J (2022) Engineering of Corynebacterium glutamicum for high-level gamma-aminobutyric acid production from glycerol by dynamic metabolic control. Metab. Eng. 69, 134–146. https://doi.org/10.1016/j.ymben.2021.11.010. Wendisch VF, Jorge JMP, Perez-Garcia F, Sgobba E (2016) Updates on industrial production of amino acids using Corynebacterium glutamicum . World J. Microbiol. Biotechnol. 32, 105. https://doi.org/105. 10.1007/s11274-016-2060-1. Yin MC, Lin CC, Wu HC, Tsao SM, Hsu CK (2009) Apoptotic effects of protocatechuic acid in human breast, lung, liver, cervix, and prostate cancer cells: potential mechanisms of action. J. Agric. Food. Chem. 57, 6468–6473. https://doi.org/10.1021/jf9004466. Zhang S, Gai Z, Gui T, Chen J, Chen Q, Li Y (2021) Antioxidant effects of protocatechuic acid and protocatechuic aldehyde: Old wine in a new bottle. Evid. Based Complement. Alternat. Med. 2021, 6139308. https://doi.org/10.1155/2021/6139308. 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A total of 100 g/L of dissolved yeast extract was pulse-fed for 82 h. Error bars represent the standard deviation of two independent experiments. DCW, dry cell weight; PCA, protocatechuic acid; DHS, dehyroshikimic acid.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3814902/v1/58b596c3592986bc2f65503a.jpeg"},{"id":50903476,"identity":"5eff7847-42a6-4645-9bd5-c0c8d497dc82","added_by":"auto","created_at":"2024-02-09 09:22:49","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":582211,"visible":true,"origin":"","legend":"\u003cp\u003e(a) 3D response surface for PCA production of \u003cem\u003eC. glutamicum\u003c/em\u003e. (b) Fermentation for medium optimization on PCA production in a 5 L fermenter. Fermentation was conducted for 72 h in batch culture by \u003cem\u003eC. glutamicum\u003c/em\u003e AK103 with CPM_2. Error bars represent the standard deviation of two independent experiments. DCW, dry cell weight; PCA, protocatechuic acid; DHS, dehyroshikimic acid.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3814902/v1/57a06aed823fe6e3ed2d9c5c.jpeg"},{"id":50903473,"identity":"8ec6d680-909e-4bac-978c-cc70d331d581","added_by":"auto","created_at":"2024-02-09 09:22:49","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":314494,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of culture method on PCA production during fermentation in a 5 L fermenter.\u003c/strong\u003e Fermentation was conducted for 224 h continuous culture by \u003cem\u003eC. glutamicum\u003c/em\u003e AK104 with CPM_2 (63 h pump start; production medium: CPM_2; feeding: 2´ CPM_2 medium). Error bars represent the standard deviation of two independent experiments. DCW, dry cell weight; PCA, protocatechuic acid; DHS, dehyroshikimic acid.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3814902/v1/97de16cc6e0f5687b5fab21e.jpeg"},{"id":51422858,"identity":"40e27afd-7efe-4264-88bb-cc6cafd34113","added_by":"auto","created_at":"2024-02-21 09:59:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":585688,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3814902/v1/f55252fc-5ecc-481b-823a-ac9f52d2c98d.pdf"},{"id":50903474,"identity":"836098a6-4884-4853-8986-c039dd72af89","added_by":"auto","created_at":"2024-02-09 09:22:49","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":346440,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementdata.docx","url":"https://assets-eu.researchsquare.com/files/rs-3814902/v1/27c42ec828e8cad7893f89bb.docx"}],"financialInterests":"","formattedTitle":"Enhanced protocatechuic acid production using metabolically engineered Corynebacterium glutamicum","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProtocatechuic acid (PCA; 3,4-dihydrobenzoic acid) (Lin et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) is a phenolic compound commonly found in over 500 plant and microbial species (Liu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Buskaran et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Punvittayagul et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tian et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). PCA is a precursor of industrially significant aromatic compounds such as vanillin and cis-cis muconate (Lin et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Weber et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, PCA anticancer activities have been demonstrated against human cancer cell lines such as MCF-7, A549, HepG2, HeLa, and LNCaP (Yin et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). High production expenses and limited production yields are the complications associated with PCA (Juurlink et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Pugh et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Several studies have been conducted on microbial production to enhance PCA yield, and its synthesis has been attempted using microorganisms such as \u003cem\u003eEscherichia coli\u003c/em\u003e (Chen et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), \u003cem\u003ePseudomonas putida\u003c/em\u003e (Li and Ye, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Om et al., 2021), and \u003cem\u003eCorynebacterium glutamicum\u003c/em\u003e (Shmonova et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kogure et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). \u003cem\u003eC. glutamicum\u003c/em\u003e strains are used industrially to produce amino acids and nucleotides and are generally recognized as safe microorganisms (Wendisch et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Lee and Kim, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). \u003cem\u003eC. glutamicum\u003c/em\u003e maintains its growth rate even at concentrations that inhibit aromatic compound growth in other strains (Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kogure and Inui, 2016; Chen et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Conrady et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lin et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, 1.5 g/L PCA restricts the growth of \u003cem\u003eE. coli\u003c/em\u003e (Pugh et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) because of the hydrophobic characteristic of aromatic compounds, such as PCA, which can accumulate in phospholipids within the membranes and cause membrane instability (Pugh et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kogure et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The enzyme 3-dehydroshikimate dehydrogenase of the PCA production pathway affects PCA productivity by feedback inhibition, which can be reduced by PCA with a Ki of approximately 0.38 mM and a Ki' of approximately 0.96 mM through competitive and non-competitive inhibition mechanisms (Shmonova et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, \u003cem\u003eP. putida\u003c/em\u003e strains with similar metabolic pathways show feedback inhibition of aromatic amino acids on intermediate enzymes in the PCA production pathway, where conversion of erythrose-4-prosphate and phosphoenolpyruvate to 3-deoxy-D-arabino-heptulosonic acid 7-phosphate affects the production rates (Li and Ye, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, we employed process optimization to overcome these limitations and enhance PCA production efficiency. The strain utilized in PCA production, \u003cem\u003eC. glutamicum\u003c/em\u003e AK103, was engineered: the \u003cem\u003epcaGH\u003c/em\u003e gene, which encodes the enzyme that converts PCA to catechol, and the \u003cem\u003earoE\u003c/em\u003e gene, which encodes the enzyme that converts the PCA precursor, 3-dehydroshikimate (DHS), to shikimate, were removed (Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Li et al., 2018). These modifications allow the strain to accumulate PCA. Deletion of the \u003cem\u003earoE\u003c/em\u003e gene in the AK103 strain blocks the biosynthetic pathway of aromatic amino acids, resulting in feedback inhibition of DHAP synthase (Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Li and Ye, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, supplying aromatic amino acids to the culture medium is problematic. To solve this problem, we optimized the concentration of yeast extract that supplied aromatic amino acids to the initial PCA production medium. We further used statistical optimization methods, such as full factorial design, steepest ascent method (SAM), and response surface method (RSM), to adjust the medium composition. The three statistical media optimization methods presented were used for process development or bio-based production, and the experiments designed using the program were used to identify the interactions between media components and the product and the optimal point. We also established the conditions for continuous culture of \u003cem\u003eC. glutamicum\u003c/em\u003e through preliminary experiments, thereby overcoming limitations in the maximum concentration of the product.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStrains, media, and plasmids\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eC. glutamicum\u003c/em\u003e AK103 strain was derived from the wild-type strain ATCC 13032 (Li et al., 2018). Yeast extract and brain heart infusion (BHI) were purchased from Becton Dickinson (Franklin Lakes, NJ, USA). Glucose, ammonium sulfate, and sodium hydroxide were purchased from Duksan (Ansan, Korea). Hydrochloric acid, Antifoam 204, kanamycin sulfate, magnesium sulfate, and calcium chloride were purchased from Sigma-Aldrich (St. Louis, MO, USA). The Masterflex\u0026reg; L/S\u0026reg; pump used for flow-through and continuous culture was purchased from Masterflex (Gelsenkirchen, Germany). \u003cem\u003eC. glutamicum\u003c/em\u003e strains were grown in BHI medium, with 48 h growth cultures in solid medium. BHI was composed of calf brain infusion 7.7 g/L, beef heart infusion 9.8 g/L, proteose peptone 10 g/L, dextrose 2 g/L, sodium chloride 5 g/L, and disodium phosphate 2.5 g/L. Liquid cultures were grown by inoculating the colonies in BHI broth and performing a 15 h primary liquid culture at 30℃ and 200 rpm, followed by a 9 h secondary growth culture. The secondary growth culture was used as an inoculum for PCA production cultures. The PCA production medium was inoculated with a secondary culture aliquot at 5% (v/v). After inoculation, the cultures were shaken for 72 h at 30\u0026deg;C and 200 rpm. In addition, for the vector-inserted strains, 25 ppm kanamycin was added at all stages of culture.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eFlask cultures and 5L fermentation\u003c/h2\u003e \u003cp\u003eFor PCA production, a single colony was grown in 37 g/L BHI agar at 30\u0026deg;C for 16 h. The secondary culture was cultivated using 1% (v/v) of the inoculum in the same medium. The production culture was grown in a 300 mL flask, 220 rpm at 30\u0026deg;C, with a working volume of 40 mL, for 3 days. For the production cultures, CPM_1 [50 g/L glucose; 2 g/L yeast extract; 5 g/L urea; 5 g/L ammonium sulfate; 0.5 g/L magnesium sulfate heptahydrate; 0.5 g/L potassium phosphate dibasic; 0.5 g/L potassium phosphate monobasic; and 0.01 g/L calcium chloride] production was used with the appropriate antibiotics. For 5L fermentation, the bottom-driven fermenter used for the production culture was KF-5 (Inchon, Korea), and the culture was grown in 3 L. Air was supplied at 1 bar and 1 vvm, the amount of dissolved oxygen was monitored with a DO probe (Mettler Toledo, Switzerland), and the culture was agitated at 100\u0026ndash;300 rpm. Antifoam was added (1 mL/L of production medium) to suppress foam formation. An Inpro\u0026reg; 3030 (Mettler Toledo, Switzerland) pH probe was used to keep the cultures within the optimal growth pH range (6.5\u0026ndash;7.2) with 6 N HCl and 6 N NaOH. An inoculum dose of 5% was used for both the growth and production cultures. The fed-batch cultures were supplied with specific components or entire components of the production medium to provide the required limiting substrate (see Results and Discussion).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMetabolite analysis\u003c/h2\u003e \u003cp\u003ePCA and DHS were analyzed using a Waters W2695 HPLC system (34 Maple St., Milford, MA, USA). Samples collected during fermentation were diluted 100 times with distilled water, and the diluted fermentation broth was filtered through a syringe filter (20 \u0026micro;m pore size). HPLC analysis was performed on an HPX-87H column (300 \u0026times; 7.8 hydrogen form, 9 \u0026micro;m particle size, 8% cross-linkage, Bio-Rad Laboratories, Hercules, California) with an injection volume of 10 \u0026micro;L and column heating at 50 ℃. A 10 mM H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e solution was used as the mobile phase and the flow rate was maintained at 0.6 mL/min. A UV detector was used to analyze the \u003cem\u003eC. glutamicum\u003c/em\u003e metabolome. The \u003cem\u003eC. glutamicum\u003c/em\u003e, PCA, and DHS metabolites were detected and analyzed at 262 nm using the Waters W2998 HPLC system. The detector's temperature was maintained at 40℃ during analysis. Standard curves were generated to observe organic acid production and sugar consumption. To monitor cell growth, the OD\u003csub\u003e600\u003c/sub\u003e was measured with a UV spectrophotometer (UV1800, Shimadzu, Kyoto, Japan). The optical density at 600 nm was converted to dry cell weight (DCW) using a correlation coefficient of 0.25 (Wei et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eEffects of yeast extract as a nitrogen source in production medium\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo optimize the 5 L lab-scale fermentation, experiments were conducted using the previously developed \u003cem\u003eCorynebacterium glutamicum\u003c/em\u003e AK103 strain as the parent strain (Lee et al., 2018). The \u003cem\u003earoE\u003c/em\u003e gene was knocked out in the AK103 strain to enable the biosynthesis of PCA using glucose as the carbon source. The removal of \u003cem\u003earoE\u003c/em\u003e resulted in no aromatic amino acid biosynthesis in AK103 cells. During 80 h of fermentation, PCA production reached approximately 1 g/L, and the PCA precursor, 3-dehydroshikimic acid (DHS), was produced at 0.13 g/L (Fig. 1). DCW increased steadily up to 60 h of incubation, being approximately 4.2 g/L at 60 h, and then decreased slightly to 3.67 g/L at 80 h of incubation, which was confirmed to persist until 132 h, when the fermentation was completed (Fig. 1). In contrast, the initially supplied glucose was utilized in small amounts, with approximately 5 g/L consumed after 80 h of fermentation, indicating low glucose utilization by the AK103 strain. A DCW of 1 g/L was assumed to result from the slow growth rate, and the low yeast extract concentration provided an insufficient supply of amino acids for cell growth. It can also be inferred that the low PCA production levels resulted from the low glucose uptake. In the AK103 strain, the intermediate genes of the metabolic pathway required for the synthesis of aromatic amino acids were also removed. To further confirm the effect of a sufficient supply of aromatic amino acids on PCA production, 100 g/L of dissolved yeast extract was pulse-fed at 82 h (Fig. 1). The results showed that the PCA concentration increased to 3.41 g/L by the end of the fermentation period, and glucose consumption was approximately 15 g/L. This demonstrated that an additional supply of yeast extract in the AK103 strain promoted PCA production. Furthermore, because approximately 300 mL of additional yeast extract was supplied and there was no culture medium evaporation in the fermenter. As our experiments demonstrated the effect of yeast extract on PCA production in CPM_1, we conducted experiments to optimize the production medium containing yeast extract.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical optimization of the production medium\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactorial design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing \u003cem\u003eC. glutamicum\u003c/em\u003e AK103 strains, we optimized the medium for efficient PCA production. We optimized the yeast extract concentration at the flask scale and observed an average production of the highest PCA, of 2.48 g/L, in a production medium containing 18 g/L of yeast extract (Fig. S1). Therefore, for the next step, the concentration of yeast extract in CPM_1 medium was adjusted to 18 g/L. We used a fractional factorial design (FFD) to minimize the number of experiments. The experimental design is shown in Tables S1 and S2. Analysis of variance (ANOVA) was performed using the statistical program Design Expert 12, and the p-value was significant at 0.0128 (Table 1). This indicates that the experimental results were highly reliable, with a validity of \u0026gt; 98%. The equation derived from the ANOVA results was used to evaluate the association between the factors and PCA productivity (Table 1). The ANOVA results showed that, in the current medium composition, urea had a significant effect on PCA productivity compared to other components, with a coefficient of -1.31, indicating that urea composition should be reduced. The coefficient of yeast extract was -0.13, which indicated that it should be similarly reduced in the production medium to increase PCA productivity. Based on the FFD, we determined the major factors affecting PCA productivity and found that optimization should be aimed at reducing the composition of yeast extract and urea, which are nitrogen sources in the production medium. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e ANOVA generated using Design Expert software (Stat-Ease 12) for the two-level factorial design for optimized PCA production. \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"515\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalysis of variance (ANOVA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSum of squares\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean square\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e\u003cstrong\u003eF-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e81.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e6.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.1127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n 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width=\"20.6963249516441%\"\u003e\n \u003cp\u003eAE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.5691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.5691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.3233\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eAF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0161\u003c/p\u003e\n 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width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.1474\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eBE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.1024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.1024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.2082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.6642\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eBF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.7674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.7674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.1132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.748\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.6184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.6184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.3049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eCF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.7727\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eDE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.3087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eDF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e8.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eEF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e5.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.0642\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e0.4916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.6963249516441%\"\u003e\n \u003cp\u003eCor total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e84.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.86073500967118%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA: glucose; B: urea; C:\u0026nbsp;(NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e; D: yeast extract;\u0026nbsp;E: KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e; F: MgSO\u003csub\u003e4\u003c/sub\u003e\u0026sdot;7H\u003csub\u003e2\u003c/sub\u003eO. DF: degree of freedom.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResponse surface method (RSM)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the first-order model equation obtained from the FFD experiments above, the parameters for the SAM experiments were calculated (Table S3) (Jeong et al., 2019). As shown in Table S3, SAM experiments were conducted in six steps, and the highest PCA production was observed in step 4. We designed the central composite design with three key factors (urea, yeast extract, and MgSO\u003csub\u003e4\u003c/sub\u003e\u0026sdot;7H\u003csub\u003e2\u003c/sub\u003eO), which most affected PCA production based on FFD (Table 2). The experimental design and the corresponding results are summarized in Table S4. ANOVA of the RSM experiments showed that the model was significant, with a p-value of 0.0159, and a quadratic polynomial was calculated to explain the influence and interaction of the medium components (Table 3). In Fig. 2A, the RSM results are shown in a three-dimensional model with the interactions between each medium composition and the productivity of PCA. The chosen medium composition was named CPM_2 and was comprised of 53 g/L glucose, 1.8 g/L urea, 12.5 g/L yeast extract, 6.6 g/L (NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, 1.6 g/L MgSO\u003csub\u003e4\u003c/sub\u003e\u0026sdot;7H\u003csub\u003e2\u003c/sub\u003eO, 0.6 g/L KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, and 0.01 g/L CaCl\u003csub\u003e2\u003c/sub\u003e. To confirm whether the components of CPM_2 enhanced PCA production, flask cultures were established. In flask cultures with CPM_1 containing 2 g/L of yeast extract, 0.26 g/L of PCA was produced. However, with the CPM_2 medium in flask fermentation, PCA production increased approximately 17-fold to 4.4 g/L. These results demonstrated that the series of media optimizations effectively increased PCA productivity. In addition, to determine whether the increased PCA production observed with CPM_2 was applicable at the fermenter scale, we conducted a 5 L fermenter culture fermentation. Batch culture using CPM_2 medium for 72 h resulted in 5.27 g/L of PCA, a 5.27-fold increase in productivity compared to the initial 5 L fermenter fermentation using CPM_1 (Fig. 2B). Moreover, we observed that the DCW, which was initially less than 1 g/L in CPM_1, was greater than 8 g/L after medium optimization. These results suggested that the medium optimization at the flask scale was applicable at the fermenter scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Coding and assigned concentration (g/L) of variables of different central composite design levels (alpha = 1.68). \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"523\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.281070745697896%\" valign=\"top\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.694072657743785%\" valign=\"top\"\u003e\n \u003cp\u003eVariable (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.94455066921606%\" valign=\"top\"\u003e\n \u003cp\u003e-alpha (1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\" valign=\"top\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\" valign=\"top\"\u003e\n \u003cp\u003e+1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.709369024856596%\" valign=\"top\"\u003e\n \u003cp\u003e+alpha (1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.281070745697896%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.694072657743785%\"\u003e\n \u003cp\u003eUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.94455066921606%\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.709369024856596%\"\u003e\n \u003cp\u003e1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.281070745697896%\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.694072657743785%\"\u003e\n \u003cp\u003eYeast extract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.94455066921606%\"\u003e\n \u003cp\u003e11.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.709369024856596%\"\u003e\n \u003cp\u003e18.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.281070745697896%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.694072657743785%\"\u003e\n \u003cp\u003eMgSO\u003csub\u003e4\u003c/sub\u003e\u0026sdot;7H\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.94455066921606%\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.45697896749522%\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.709369024856596%\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe concentrations of the other components in the production medium were set according to the conditions of Step 4 in Table S3. Code levels -alpha/+alpha represent the axial points, -1/+1 the factorial points as reduced and elevated concentrations and 0 the center point of each factor.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e ANOVA generated using Design Expert software (Stat-Ease 12) of the quadratic models for the central composite design (CCD) for optimized PCA production. \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"514\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003e\n \u003cp\u003eAnalysis of variance (ANOVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003eSum of squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003eDF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003eMean square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003eF-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e8.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.9276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.0159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eA-Urea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e6.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e6.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e38.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eB-Yeast extract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.9814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.9814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e6.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.0438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eC-MgSO\u003csub\u003e4\u003c/sub\u003e\u0026sdot;7H\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.0316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.0316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e0.1939\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eAB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e3.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.1063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.0189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.0189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e0.1163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.0211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.0211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e0.1299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.7292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eA\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.2917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.2917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.2226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eB\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.0306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.0306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e0.1879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.6777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eC\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.0291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.0291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e0.1789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.1628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eLack of Fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.2259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\n \u003cp\u003e45.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\n \u003cp\u003e0.0217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003ePure Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.0099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003eCor Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003e9.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.237816764132553%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.933723196881093%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.695906432748538%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.077972709551656%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0.1949317738791423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA: urea; B: yeast extract; C:\u0026nbsp;MgSO\u003csub\u003e4\u003c/sub\u003e\u0026sdot;7H\u003csub\u003e2\u003c/sub\u003eO. DF: degree of freedom.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContinuous cultivation: Strategy to address PCA cytotoxicity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo confirm PCA cytotoxicity, we conducted gradient plate assays with PCA. For gradient plates, 37 g/L BHI agar was poured into a tilted plate, left to solidify, and 10 g/L PCA-containing BHI agar was added to a flat region of the plate (Fig. S2). The results showed that cells were grown only in the area corresponding to approximately 5 g/L PCA. This phenomenon was also observed in a fed-batch culture supplying additional nutrients. Even when the fed-batch cultures were carried out with yeast extract or the entire CPM_2 medium, the concentration of PCA did not exceed 5 g/L (Fig. S3). We aimed to maintain a steady-state through continuous chemostat cultures. The chemostat achieved a steady-state by supplying medium at a constant rate and removing the same amount of medium to maintain constant cell growth and bioreactor volume. To establish the conditions for maintaining a steady-state in continuous cultures, four preliminary experiments were conducted. The experiments involved adjusting the pump speed in the range of 0.1\u0026ndash;0.91 mL/min to control \u003cem\u003eD\u003c/em\u003e and supplying medium at various concentrations (1\u0026acute;, 2\u0026acute;, 4\u0026acute;, and 8\u0026acute;) of CPM_2 to adjust the substrate supply rate (Fig. S4). When 1\u0026acute;\u0026nbsp;medium was supplied, the pump speed was adjusted to provide the necessary substrate for cell growth and PCA production. However, increasing the dilution rate to increase the substrate supply rate led to a washout of cells and an inability to maintain a steady-state (Fig. S3). This result is related to the condition that the specific growth rate (\u0026mu;) must be equal to the dilution rate to maintain a steady-state in continuous culture. The experiments with 4\u0026acute;\u0026nbsp;and 8\u0026acute;\u0026nbsp;medium resulted in a decrease in the PCA concentration. Preliminary experiments to establish the conditions for continuous culture showed that the PCA concentration in the medium could not be kept constant. However, a pump speed of 0.5\u0026ndash;0.8 mL/min was adequate to maintain a steady state, and the production medium supplied under these conditions had to be adjusted to a concentration between 1\u0026acute;\u0026nbsp;and 4\u0026acute;. Supplying 1.2\u0026acute;\u0026nbsp;glucose and the remaining components at 2\u0026acute;\u0026nbsp;as CPM_2 at a rate of 0.55 to 0.68 mL/min allowed the maintenance of a steady state. Under steady-state conditions, PCA remained at approximately 4 g/L, and glucose was maintained at approximately 10 g/L (Fig. 3). In addition, by introducing a continuous culture process using \u003cem\u003eC. glutamicum\u003c/em\u003e strains, we showed that a continuous culture eliminated the need for multiple batch cultures and achieved the same product concentration, which saves media and the time required for the growth of cultures.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe PCA production process using \u003cem\u003eC. glutamicum\u003c/em\u003e was improved using statistical media optimization and continuous culture processes. Aromatic amino acids are essential for cell replication and thus directly affect cell growth and growth associated product formation. The production of PCA by \u003cem\u003eC. glutamicum\u003c/em\u003e showed a growth associated product formation in the reference experiment(Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), so that a deficit could cause a standstill of cell growth and the entire process. This leads to the assumption that \u003cem\u003eC. glutamicum\u003c/em\u003e is auxotrophic for these aromatic amino acids so that they have to be taken up from the medium containing yeast extract. Klotz et al showed the lactic acid concentration and productivity of \u003cem\u003eS. inulinus\u003c/em\u003e depending on the nutrient source (Klotz et al, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In addition, Lee et al. showed that the presence of sufficient amino acids, provided by the complex ingredients, accelerated cell growth, and subsequent metabolite production presumably increased in the production of muconic acid (Lee et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Also, our results showed an approximately 17-fold increase in production capacity compared to a previous production medium containing 2 g/L of yeast extract (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Based on the above results, it was estimated that 2 g/L of yeast extract in the CPM_1 medium was a limiting substrate for cell growth and PCA production (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). To evaluate the interaction between two factors, we employed a fractional factorial design (FFD). These were expressed as the following mass balance: PCA\u0026thinsp;=\u0026thinsp;3.11\u0026thinsp;+\u0026thinsp;2.23A-1.36B\u0026thinsp;+\u0026thinsp;0.09C-0.13D\u0026thinsp;+\u0026thinsp;0.03E\u0026thinsp;+\u0026thinsp;0.17F-0.06AB\u0026thinsp;+\u0026thinsp;0.23AC\u0026thinsp;+\u0026thinsp;0.06AD-013AD\u0026thinsp;+\u0026thinsp;0.02AE-0.23BC\u0026thinsp;+\u0026thinsp;0.21BD\u0026thinsp;+\u0026thinsp;0.06BE-0.15BF-0.04CD\u0026thinsp;+\u0026thinsp;0.14CE-0.04CF\u0026thinsp;+\u0026thinsp;0.14DE-0.36DF\u0026thinsp;+\u0026thinsp;0.28EF (A, glucose; B, urea, C, (NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e; D, Yeast extract; E, KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e; F, MgSO\u003csub\u003e4\u003c/sub\u003e\u0026sdot;7H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e). Interestingly, designing a high concentration of yeast extract in FFD resulted in a diminished effect of the extract because of high initial concentration. Yeast extract with a coefficient of -0.065 had the effect on the production rate and a negative value, which implied a decrease in concentration implying a decline in concentration. As each culture medium component comprising a carbon source, a nitrogen source, and various other substances did not play an independent role but interacted with other components, it was critical to identify their optimal concentrations.\u003c/p\u003e \u003cp\u003eThe response surface method (RSM), based on the quadratic model of a central composite design (CCD), allows for the evaluation of interactions among all components (Lee et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Thus, it can statistically lead to maximal production. CCD requires multiple experiments to obtain statistically significant results. In contrast, the SAM design is a statistical experimental method that efficiently evaluates the optimal culture medium concentration based on the FFD design. The center point used in the FFD design showed a PCA production rate of 3.31 g/L (Table S3). Statistical optimization of the production medium CPM_2 achieved a PCA production of 5.27 g/L, a 5.27-fold increase compared to that of CPM_1. Therefore, the process of culture medium optimization enabled decreasing the production of intermediate metabolites and identifying the optimal culture medium concentration that maximized PCA production. However, PCA concentrations exceeding 5 g/L severely inhibited \u003cem\u003eC. glutamicum\u003c/em\u003e PCA production. To address the issue of reduced production rates owing to cell toxicity, we introduced a continuous culture process. Continuous cultures are characterized by the dilution rate (\u003cem\u003eD\u003c/em\u003e), which represents the relationship between the volume of medium supplied per unit of time (\u003cem\u003eF\u003c/em\u003e) and the bioreactor volume (\u003cem\u003eV\u003c/em\u003e) (Graf et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Continuous cultures must be maintained at a steady-state through a continuous supply of media. The steady-state is defined as a constant concentration of cells, products, substrates, pH, and other environmental factors (Yufu et al., 2021). We therefore developed a continuous culture method that operated for 150 h in steady-state mode. In the steady-state, where 4 g/L of PCA was reached, 0.064 g PCA/L\u0026sdot;h was produced from the elution rate of 16 mL/h of the actual medium, which was 78% higher than the productivity of batch culture. These experiments demonstrated that, compared to batch culture, higher total PCA concentrations could be achieved using continuous culture, successfully addressing the reduced production rates resulting from cell toxicity. By reducing PCA concentration in the production medium, PCA production continued without inhibiting cell growth. These findings suggest various options for improving PCA production and are expected to contribute to an efficient synthesis process.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eANOVA, analysis of variance\u003c/p\u003e\n\u003cp\u003eBHI, brain heart infusion\u003c/p\u003e\n\u003cp\u003eDCW, dry cell weight\u003c/p\u003e\n\u003cp\u003eDHS, 3-dehydroshikimate\u003c/p\u003e\n\u003cp\u003eFFD, fractional factorial design\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCA, protocatechuate acid\u003c/p\u003e\n\u003cp\u003eRSM, response surface method\u003c/p\u003e\n\u003cp\u003eSAM, steepest ascent method\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Technology Development Program [grant number S3148236] funded by the Ministry of SMEs and Startups (Korea) and the Korea Institute of Industrial Technology under the project \u0026ldquo;Development of eco-friendly production system technology for total periodic resource cycle\u0026rdquo; (Kitech EO210014).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJiwoon Chung and Woo-Shik Shin contributed equally as first authors.\u003c/p\u003e\n\u003cp\u003eChulhwan Park and Jaehoon Cho contributed equally as corresponding authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBuskaran K, Bullo S, Hussein MZ, Masarudin MJ, Mohd Moklas MA, Fakurazi S (2021) Anticancer molecular mechanism of protocatechuic acid loaded on folate coated functionalized graphene oxide nanocomposite delivery system in human hepatocellular carcinoma. 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Med. 2021, 6139308. https://doi.org/10.1155/2021/6139308.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Protocatechuate, Corynebacterium glutamicum, Statistical medium optimization, Continuous cultivation","lastPublishedDoi":"10.21203/rs.3.rs-3814902/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3814902/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eProtocatechuate acid (PCA) is a phenolic acid naturally synthesized by various microorganisms. To enhance PCA production during fermentation using \u003cem\u003eCorynebacterium glutamicum\u003c/em\u003e, a statistical optimization of the production medium was performed using full factorial design, the steepest ascent method, and the response surface method. The optimized production medium enabled PCA production of over 5 g/L in a 72-h batch culture. PCA cytotoxicity affected strain growth and PCA production rate, with an inhibitory concentration of approximately 5 g/L in the fermentation broth. Finally, continuous fermentation was operated for 150 h in steady-state mode, maintaining the concentration of PCA below 5 g/L. The optimization method established in this study successfully increased PCA production levels, and the findings presented herein are anticipated to contribute to the industrialization of PCA production using \u003cem\u003eC. glutamicum.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Enhanced protocatechuic acid production using metabolically engineered Corynebacterium glutamicum","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-09 09:22:44","doi":"10.21203/rs.3.rs-3814902/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5260c082-503c-4fb7-9469-aa35ea84a974","owner":[],"postedDate":"February 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-21T09:51:37+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-09 09:22:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3814902","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3814902","identity":"rs-3814902","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}