Production enhancement of the glycopeptide antibiotic A40926 produced by an engineered N. gerenzanensis lcu1

Production enhancement of the glycopeptide antibiotic A40926 produced by an engineered N. gerenzanensis lcu1 | 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 Production enhancement of the glycopeptide antibiotic A40926 produced by an engineered N. gerenzanensis lcu1 Bingyu Yan, Wen Gao, Li Tian, Shuai Wang, Huijun Dong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-624980/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective To enhance the production of A40926 by implementing a strategy of the combination of genetically engineered strain construction and medium optimization. Results The engineered strain of Nonomuraea gerenzanensis presented an increment of 30.6 percent in A40926 production compared with that of the parent strain. Subsequently, an assembling medium, which was defined as M9 medium and mainly comprised glucose, maltodextrin, soybean meal, peptone, L-valine, and other inorganic salts, was determined as the optimal medium among the tested nine media. The optimum concentration of medium components was glucose 10 g/l, maltodextrin 37.9 g/l, soybean meal 34.5 g/l, peptone 30.0 g/l, and L-valine 4.3 g/l, respectively. The optimized medium was verified experimentally, and A40926 yield increased significantly from 257 mg/l to 332 mg/l, as compared to the non-optimized medium. The strategy brought a significant increase of A40926 yield by 65.2 percent. Conclusions The engineered mutant with the genetic attributes of the co-expression of the dbv3 and dbv20 genes and the deletion of the dbv23 gene could obviously enhance the production of A40926. In addition, the optimization of medium was an effective and essential tool for the improvement of the secondary metabolites in Actinomyces. Biotechnology and Bioengineering Applied & Industrial Microbiology A40926 N. gerenzanensis Genetic engineering Central composite design Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The antibiotic A40926 belongs to the teicoplanin family of glycopeptides antibiotics (GPAs), which remain a tool of last resort for treating resistant, “superbug” bacterial infections in clinic (Yim et al. 2014 ). It is the precursor of dalbavancin, a second-generation glycopeptide, and consists of a heptapeptide skeleton, two sugar residues, two chlorine atoms, and an acyl chain (Marschall et al. 2019 ). The dbv (from d al b a v ancin) cluster, is involved in the biosynthesis of A40926, had been isolated and characterized from N. gerenzanensis ATCC 39727. It spans approximately 71 kb and consists of 37 open reading frames (ORFs) (Sosio et al. 2010 ). Until now, fermentation has still been the only approach for the production of A40926 in industrial scale. Therefore, how to improve A40926 titer is one of the essential researches about the rare actinomyces N. gerenzanensis . Originally, A40926 yield of the wild-type N. gerenzanensis strain was only 5 mg L − 1 in an early fermentation study using chemically defined media with high concentrations of phosphate (Gunnarsson et al. 2003 ). Later studies demonstrated that initially high inorganic phosphate or ammonium concentrations inhibited A40926 production (Gunnarsson et al. 2004 ). Technikova-Dobrova reported that L-Gln, which replaced ammonium or nitrogen as the sole nitrogen in MM-103 medium, could improve the A40926 yield to 123 mg L − 1 (Technikova-Dobrova et al. 2004 ). Chen and colleagues developed a higher-producing strain by mutagenesis with UV irradiation and diethyl sulfate treatment, which presented the highest yield thus far, 1 g L − 1 of A40926. This group also confirmed that the addition of L-leucine could improve A40926 production. Other studies confirmed that the addition of branched-chain amino acids promotes the production of A40926 and teicoplanin (Chen et al. 2016 ). In our recent studies, the positive impacts of the deletion of dbv23 and the overexpression of regulatory dbv3 and dbv20 on A40926 production had been verified, respectively (Yue et al. 2020a ). Based on the above founds, we constructed a multiple genetic operating strain laboring the knockout of dbv23 and the co-expression of dbv3 and dbv20 . Furthermore, central composition design was carried out to optimize the medium for obtaining the high yield of A40926 by the mutant. Methods Bacterial Strains, Plasmids, and Media All bacterial strains and plasmids used in this work are listed in Table 1. N. gerenzanensis and its derivatives were grown on Mannitol-Soy-agar (MS) solid medium at 30℃ (Marcone et al. 2010). MS medium supplemented with 20 mM MgCl 2 was used for intergeneric conjugation between Escherichia coli and mycelia of N. g erenzanensis. For seed culture, 50 mL of VSP medium in 250-mL shake flasks were inoculated with a single colony from solid MS media and cultured at 30℃, 220 rpm for 72 h . For mycelial collection used for intergenic conjugation, the above seed culture was then transferred into 75 mL of VSP medium in 500-mL shake flask with 4% inoculum for continuous culture at 30℃ for 36 h. For A40926 production, a set of media listed in Table 3 were chosen to evaluate their abilities of A40926 production, and which were conducted in the 500-mL shake flasks with four baffles at 30℃ and 220 rpm for 168 h. The E. coli strains were cultivated on LB agar medium or in LB liquid medium at 37°C. Apramycin (50 µg L -1 ), kanamycin (50 µg L -1 ), chloramphenicol (25 µg L -1 ) and nalidixic acid (25 µg L -1 ), were supplemented when necessary. The E. coli strain ET12567/pUZ8002 was used as a donor for intergenic conjugation and delivered recombinant plasmids into N. gerenzanensis . Plasmids Construction The sequence of promoter gapdh was synthesized with Bam HI/ Nde I sites and further cloned into pIJ8660, yielding pIJ8660-P gapdh . The DNA sequence of the promoter gapdh was provided in Supporting information. Isolation of genomic DNA from N. gerenzanensis were carried out according to instructions of commercial kits (TIANGEN Biotech Co., Ltd, China). The dbv3 and dbv20 genes were amplified from the genome DNA of N . gerenzanensis using the corresponding primers listed in Table 2, respectively. These fragments were cloned into the Eco RV site of pUC57 (Vazyme Biotech Co., Ltd, China), respectively. These plasmids carrying different dbv gene were digested with Nde I and Not I, and the obtained fragment was cloned into respective sites of pIJ8660-P gapdh to produce pIJ8660-P gapdh - dbv3 and pIJ8660-P gapdh - dbv20 , respectively. To co-overexpress dbv3 and dbv20 , the dbv3 fragments with promoter gapdh were amplified from pIJ8660 - P gapdh-dbv3 and ligated into pIJ8660 - P gapdh-dbv20 , generating pIJ8660 - P gapdh-dbv3- P gapdh - dbv20 . The expression of dbv3 and dbv20 was driven by the promoter grpdh separately. Genotype Confirmation of The Exconjugants by PCR The exconjugants on the MS medium were transferred into the VSP medium containing 50 µg mL -1 apramycin and cultured at 30℃ and 200 rpm for 48 h. The mycelia were collected and treated for extracting genome DNA by commercial kit. Primers listed in Table 2 were used for confirmative PCR of gapdh - dbv3 and gapdh - dbv20 fusion fragments. Optimization of A40926 Production Utilizing Central Composite Design (CCD) Here, the optimization process of A40926 production was firstly carried out to identify the preferred media for A40926 production based on the literature (Table 3). A novel medium was designed based on the above optimization results. Subsequently, response surface methodology (RSM) was carried out by the central compost design (CCD) to optimize the redesigned medium, which is a complicated statistical method for determining the optimum experimental conditions that require the minimum number of tests. A software Design Expert 11 (Stat-Ease, Inc., USA, Windows operating system) was applied to perform the experimental design matrix and its statistical experimental design analysis. All assays were performed in triplicate. Three-dimensional curves of the response surfaces were obtained by using Design Expert 11 to visualize individual effects and interaction between significant parameters. The model was evaluated using Fisher´s statistical test for analysis of variance (ANOVA). Shake Flask Fermentation For the shake flask cultivation, the inoculum was prepared by inoculating the mycelia of N. gerenzanensis in 50 mL VSP medium in a 500-ml shake flask. The preculture was incubated at 30℃ and 200 rpm, sustaining for 48 h. Based on the literature reports and novel design, nine different production media (Table 3) were selected for the shake flask tests to evaluate their effects on the A40926 production. All experiments were performed in 500-mL shake flasks, with 75 mL of medium and a 10% (v/v) inoculum prepared as described above. The initial pH was set to 7.2 by the addition of 10% ammonium hydroxide or 1 M HCl. Cultivation was performed at 30℃ and 220 rpm, for 144 h. At the end of the experiments, the cultivation broth was collected and used to detect the A40926 yield using high-performance liquid chromatography (HPLC). Three replicated tests were conducted for each medium. Analytical Methods The A40926 analysis was similar to that described by Gunnarsson with modifications (Gunnarsson et al. 2003). Briefly, the fermentation broth sample was adjusted to pH 11.3 by adding NaOH solution, and then sonicated at 50°C for 1 h. Subsequently, the sample was centrifuged at 5,000 rpm for 5 min. The supernatant was filtered through a 0.45 μm Millipore filter for analysis. A40926 was analyzed by HPLC equipped with a SHIMAZU Shim-pack GIST C 18 column (5 μm, 250 × 4.60 mm) and a UV detector (220 nm) (Technikova-Dobrova et al. 2004). The column temperature was 25°C, the injection volume was 10 μL, and the flow rate was 1.0 mL min -1 . A gradient with two eluents (eluent A: 10% acetonitrile, 90% 12.5 mM NaH 2 PO 4 , pH 7.8; eluent B: 50% acetonitrile, 50% 12.5 mM NaH 2 PO 4 , pH 7.8) was applied as follows: (% eluent B): 0 min, 20%, 5 min 50%, 32 min 65%, 35 min 20%. Statistical Analysis The statistical analyses One-way and Two-way ANOVA were performed using GraphPad Prism version 7. Results Construction of The Engineered Strain Previous studies had verified that the overexpression of positive regulatory gene dbv3 or the deletion of dbv23, encoding an acetyltransferase, could enhance the production of A40926 (Lo Grasso et al. 2015; Sosio et al. 2010; Yue et al. 2020a). In addition, we found that the overexpression of dbv20 gene encoding a mannosyltransferase also improved the A40926 production (Dong et al. 2020). In this study, a strategy of multiple genetic operations referring to co-expressing dbv3 and dbv20 in a dbv23-deleted mutant was adopted to improve the strain. The two dbv genes were separately and simultaneously expressed under the control of each promoter gapdh (Fig. 1A). The recombinant plasmid was transferred to the mutant Δ23 by conjugation, which was expected to obtain the final mutant verified by PCR. As a result, the fragments of Pgapdh-dbv3 and Pgapdh-dbv20 were successfully obtained and about 0.7 kb size (Fig. 1B). Furthermore, we compared the A40926 yield of mutant with that of the other control strains including the original strain (Δ23), the wild-type strain, the dbv3-overexpressed stain (op3) and the dbv20-overexpressed strain (op20). As expected, the co-expression of dbv3 and dbv20 further improved the A40926 yield, which increased from 159 to 262 mg L-1 compared with the wild-type strain (Fig. 1C). Media Screening Experiments Previous studies had reported some suitable media for A40926 production (Table 3). In this work, we applied these media to evaluate their capabilities for A40926 production, and further redesigned medium and optimized the components. The fermentation results demonstrated that the more kinds of natural components, such as maltodextrin, soybean meal, peptone, and corn starch, were contained in the medium, and the higher the yield of A40926 was (Fig. 2). Based on the results, a novel combination medium was designed and named M9, which was composed of carbon resource of glucose and maltodextrin, nitrogen resource of peptone and soybean meal, the amino acid of L-valine, and other inorganic salts. In contrast to media from literature, the engineered strain gave the highest yield of A40926 in M9 medium as expected. It was supposed that the proper ratio of carbon and nitrogen resource, the relative lower viscosity of the medium, and more various inorganic salts were beneficial to improve the A40926 production. Optimization of Medium Components for A40926 Production by CCD To further optimize the components of M9 medium, central composition design was applied. The optimization process focused on investigating the impact of five independent variables: glucose (A) and maltodextrin (B) as carbon sources, soybean meal (C) and peptone (D) as nitrogen sources, L-valine as a precursor (E), on the yield of A40926, using response surface methodology based on central composite design (Table 4). A statistically designed study was performed to evaluate the individual and the interactive effect of five medium ingredients on the A40926 yield. The values of response from the 32 experiments are presented in Fig. 3. The first set of optimal statistical conditions, maximizing A40926 yield by N. gerenzanensis were obtained with 28-32 standard tests (Supplementary Table 1) which corresponded to the medium composition including glucose 10 (g L-1), maltodextrin 35 (g L-1), soybean meal 30% (g L-1), peptone 20 (g L-1), and L-valine 3.5 (g L-1). Here, RSM is a five factorial design where 3D contour plots of surface curves (Fig. 4 and Supplementary Fig. 1) can be generated by linear effects, quadratic effects and two-way interactions between the factors. From these profiles, a semi-empiric model (Eq.1) can be derived that best fits the experimental data. The parameters and results of the CCD experiments are presented in Table 4, Fig. 3 and 4, and Supplementary Table 1 and Fig 1. The statistical significance of the quadratic model was tested by F- and p- values (Table 5). The results from ANOVA indicated that the quadratic regression used to produce a second-order model was significant, as revealed from the p- and F-values: the calculated Model F-value of 37.53 and the p-value of <0.0001 indicate that the model is significant. The Lack of Fit F-value of 0.45 implies that the Lack of Fit is not significant relative to the pure error. There is 81.52% chance that a Lack of Fit F-value this large could occur due to noise. The second–order polynomial equation of the model fitted for A40926 production before eliminating the non-significant terms is: A40926 production yield (mg/l)= 64.4097+0.929924 A+3.31465 B+9.69432 C+0.885795 D+ 8.7298 E-0.0275 AB+0.03375 AC-0.02875 AD+0.175 AE-0.00208333 BC-0.00958333 BD+0.0472222 BE-0.006875 CD+0.0541667 CE+0.179167 DE-0.0404545 A2-0.0389394 B2-0.145114 C2-0.0126136 D2 -2.22727 E2 (Eq. 1) (Degree of freedom=20; F-value=37.53; p-value F (Table 5) lower than 0.05 was considered as the significant terms. On the contrary, if the p-value Prob > F is higher than 0.1, the model terms are non-significant. In this case, the model terms B (maltodextrin), C (soybean meal), E (L-valine), DE, B2, C2, and E2 were considered significant. The R2 value provides a measure of how much variability in the observed response values can be explained by the experimental factors and their interactions. The closer the R2 value to 1.00, the stronger the model is, and the better it predicted the observed response. It was suggested that the R2 value should be at least 0.80, for a good model fitness(Venkatachalam et al. 2020). Here, the calculated R2 value of 0.9543 (Supplementary Table 2), indicated that 4.57% of the total variation could not be explained by the empirical model; this expresses a good enough quadratic fit to navigate the design space. Thus, the response surface model developed in this study for predicting the A40926 production may be considered satisfactory (Eq. 2). The signal to noise ratio was measured by Adeq Precision value of 33.0287, which indicated that this model could be used to navigate the design space. From the above, the second-order polynomial equation of the model fitted for A40926 production, after eliminating the non-significant terms (Supplementary Table 2), is A40926 production yield (mg L-1)=323.91+3.37 B+13.04 C+2.63 E+2.69 DE-8.59 B2-14.34 C2-4.84*E2 (Eq. 2) (Degree of freedom=7; F-value=71.54; p-value <0.0001; R2=0.9543) Whereby the F-value increased, meaning that the mean squares of the model are larger than the square residual average. Thus, with a higher the F-value, the more significant p-value for ANOVA and the more significant the model is. Effect of Significant Components on A40926 Production 3D response surface graphs (Fig. 4 and Supplementary Fig. 1) were plotted to illustrate the interaction of the different paired factors and to determine the optimum of each paired factor for maximum response. Each graph represents the combinations of two test factors in relation to A40926 production yield. The data in Fig. 4 indicate that the increase in significant carbon source (maltodextrin) and amino acid/nitrogen sources (soybean meal, peptone, and L-valine) resulted in increased A40926 production. From the combined effect of maltodextrin and soybean meal concentration (Fig. 4A), the highest production was obtained by the appropriate soybean meal concentration and the proper maltodextrin concentration. Similar results were obtained with the combined effect of L-valine and maltodextrin (Fig. 4B). The effects of L-valine and peptone concentrations, and of L-valine and soybean meal, on A40926 production yield are illustrated in Fig. 4C and 4D. Yield increased as the concentrations of soybean meal and L-valine increased and decreased, respectively. The main medium combination of L-valine and peptone (DE, Table 5) showed the highest p-value for Prob > F (0.0264) and therefore represented a more significant model term combination. L-valine is a well-known precursor for A40926 production and meanwhile is a source of nitrogen(Alduina et al. 2018; Beltrametti et al. 2004; Yue et al. 2020b). It is possible that higher concentrations of these nutrients could have led to a substrate growth inhibition and/or affected A40926 production. The optimal concentrations of the four factors excluding factor glucose that maximized A40926 production yield were predicted using the optimization function of the statistical experimental designs Design Expert 11. Glucose 10 (g L-1), maltodextrin 37.9 (g L-1), soybean meal 34.5 (g L-1), peptone 30.0 (g L-1), and L-valine 4.3 (g L-1) were chosen as the optimal concentrations, resulting in the highest A40926 yield of 328.6 mg L-1. The predicted medium composition roughly coincided with experiment trials from 27 to 32 (Supplementary Table 1). No statistical differences were observed between the predicted maximum production yield and the experimental results (p > 0.05). The optimized results were also confirmed (p > 0.05) by conducting a further fermentation experiment in triplicate at the above-optimized values, resulting in production yield of 332±13 mg L-1. A Parity plot illustrating the distribution of experimental (actual) and predicted (model) values is shown in Fig. 5. Data points are scattered along the diagonal line, also suggesting that the model is adequate to explain A40926 production within the experimental range studied. The process profiles of A40926 production shown in Fig. 6 obtained by the cultivation of the engineered strain lcu1 in the non-optimized and optimized media, respectively. Here, the strain lcu1 was denominated by the abbreviation of Liaocheng University number one, and which has the genetic characteristics of the dbv23 gene deletion and the dbv3-dbv20 gene co-expression. During the first 48 h of culture, there was no difference in the two media for A40926 production. Subsequently, the productivity of A40926 in the optimized medium was always higher than that in the non-optimized medium. In particular, the biosynthesis of A40926 stagnated and even decreased in the last 24 h of fermentation. The yield of A40926 in the optimized medium reached 332 mg L-1 at the end of fermentation, which was significantly higher than that of 257 mg L-1 in the non-optimized medium. Discussion In this study, we combined the genetic manipulation of dbv genes and the traditional media optimization to enhance the production of A40926. The strategy brought a significant increase of A40926 yield by 65.2 percent, which exceeded our expectations. The previous researches referring to the dbv cluster gave us a comprehensive understanding of the biosynthesis of A40926. For instance, the pathway-specific regulatory gene dbv3 and dbv4 were verified to play positive roles in the A40926 production (Alduina et al. 2007 ; Lo Grasso et al. 2015 ). The post-modified genes in dbv cluster exerted significant roles in the biosynthesis of A40926, which included seven genes such as dbv8 encoding an acyltransferase (Kruger et al. 2005 ), dbv21 encoding a deacetylase (Ho et al. 2006 ), dbv23 encoding an acetyltransferase (Sosio et al. 2010 ), and dbv29 encoding a hexose oxidase (Liu et al. 2011 ). Typically, the absence of dbv23 distinctively promoting the production of A40926 had been confirmed by Sosio´s and our previous studies (Sosio et al. 2010 ; Yue et al. 2020a ). Recently, the overexpression of the dbv20 gene, encoding a mannosyltransferase, was verified to improve the A40926 production (Dong et al. 2020 ). Here, we constructed an engineered strain with the deletion of dbv23 and the co-expression of dbv3 and dbv20 to improve the A40926 yield actually. To further improve the A40926 production, the preferred nutrients, including carbon and nitrogen sources for A40926 production, were determined based on the literature and the preliminary fermentation assays. As shown in the results (Fig. 3 ), the delayed natural carbon and nitrogen sources such as maltodextrin and soybean meal were beneficial to producing A40926. Nevertheless, it should be noted that the higher concentration of these delayed carbon and nitrogen sources, such as corn starch and soybean meal, resulted in a decrease of A40926 yield, which might be caused by the limitation of the dissolved oxygen transfer. Therefore, we designed a novel medium M9 based on the comprehensive consideration of viscosity related to oxygen transfer and the mixture of the delayed and quick-acting carbon and nitrogen sources. The M9 medium led to the highest yield of A40926 among the screened media. Furthermore, response surface methodology with central composite design was carried out to obtain a mathematical model to identify the optimum concentrations of the significant components for the improvement of A40926 production. The most optimal concentrations of significant medium components were glucose 10 g L − 1 , maltodextrin 37.9 g L − 1 , soybean meal 34.5 g L − 1 , peptone 30.0 g L − 1 , and L -valine 4.3 g L − 1 . The maximum yield 332 mg L − 1 of A40926 was obtained. Therefore, the response surface statistical methods should be effective for optimizing the medium nutrients for the production of secondary metabolites from microorganisms. Declarations Conflict of interest statement The authors declare that they have no conflict of interest. Ethical approval This article does not contain any studies with human participants or animals performed by any of the authors. 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(2004) Design of mineral medium for growth of Actinomadura sp. ATCC 39727, producer of the glycopeptide A40926: effects of calcium ions and nitrogen sources Appl Microbiol Biotechnol 65:671-677 doi:10.1007/s00253-004-1626-2 Venkatachalam M, Shum-Cheong-Sing A, Dufosse L, Fouillaud M (2020) Statistical Optimization of the Physico-Chemical Parameters for Pigment Production in Submerged Fermentation of Talaromyces albobiverticillius 30548 Microorganisms 8 doi:10.3390/microorganisms8050711 Yan L HC, Zhu CY, et al (2013) Breeding high-producer of glycopeptide antibiotic A40926 Chinese Journal of Pharmaceuticals 44:143-145 Yim G, Thaker MN, Koteva K, Wright G (2014) Glycopeptide antibiotic biosynthesis J Antibiot (Tokyo) 67:31-41 doi:10.1038/ja.2013.117 Yue X, Xia T, Wang S, Dong H, Li Y (2020a) Highly efficient genome editing in N. gerenzanensis using an inducible CRISPR/Cas9-RecA system Biotechnol Lett 42:1699-1706 doi:10.1007/s10529-020-02893-2 Yue X, Yan B, Wang S, Gao W, Zhang R, Dong H (2020b) Preparation of pH-Responsive Alginate-Chitosan Microspheres for L-Valine Loading and Their Effects on the A40926 Production Curr Microbiol 77:1016-1023 doi:10.1007/s00284-020-01894-8 Tables Table 1 Strains and plasmids used in this work Strains or plasmids Characteristics a Sources or reference Escherichia coli DH5α Routine subcloning host Invitrogen ET12567/pUZ8002 Derived from the methylation-defective strain ET12567 carrying plasmid and donor strain for E. coli - Actinomyces conjugation (Gust et al. 2003) Actinomyces N. gerenzanensis ATCC 39727 Wild-type, glycopeptide A40926 producer (Goldstein et al. 1987) Δ23 N. gerenzanensis mutant with the knockout of dbv23 gene (Yue et al. 2020a) lcu1 Δ23 strain laboring pIJ8660 - gapdhp-dbv3-gapdhp-dbv20 This study Plasmids pIJ8660 A pSET152 derivative. Apr r (Sun et al. 1999) pIJ8660-P gapdh pIJ8660 plasmid with promoter gapdh This study pIJ8660 - P gapdh -dbv3- P gapdh - bv20 pIJ8660 plasmid with two promoter gapdh , dbv3 and dbv20 This study a: Apr r , apramycin resistance Table 2 Oligonucleotides and Primers used in this work Primers Sequence (5´-3´) Description p1/p2 tgaaaggggatacgccatatggtgctgttcgggcgagatcgtg acgggctgcagccgggcggccgcctacagccgcactgcctcacg Amplification for dbv3 p3/p4 tgaaaggggatacgccatatgatgtcgcacatcaccatgactc acgggctgcagccgggcggtacctcagcccccgggtgtccg Amplification for dbv20 p5/p6 gctgctccttcggtcggacgtgcgtctacg cacggcccagatcgcccacacctcctccgg Verification of lcu1 strain p7/p8 gctgctccttcggtcggacgtgcgtctacg tccggtacatcaccagcaccgagatcacgc Verification of lcu1 strain Table 3 Media used for the cultivation of the engineered N. gerenzanensis lcu1 in this study Component (g L -1 ) M1 M2 M3 M4 M5 M6 M7 M8 M9 Glucose 10 20 20 50 20 5 30 5 10 Maltodextrin 50 15 30 30 Peptone 10 15 Yeast extract 10 5 8 Soybean meal 20 10 10 30 30 20 Corn starch 40 30 40 Soluble starch 10 Tryptone 15 Cottonseed meal 10 5 Soybean protein 5 40 5 Meat peptone 10 Soybean oil 10 10 Fish powder/peptone 15 Malt extract 15 Casein 2 L-Leu 0.5 3 1 L-Gln 2 1.5 L-Val 0.5 1 1 1 5 L-Tyr 0.5 L-Ile 0.5 K 2 HPO 4 0.5 KH 2 PO 4 0.65 1.5 0.5 MgSO 4 ·7H 2 O 0.2 0.45 0.2 0.4 FeSO 4 ·7H 2 O 0.01 0.2 (NH 4 ) 2 SO 4 3.65 2 CaCO 3 5 4 4 3 NaCl 2 2 CuSO 4 0.03 0.03 pH 7.0-7.2 7.5 7.0 7.0 6.5 7.0 7.4 7.0 7.2 References a b c d e f g h This study a, (Technikova-Dobrova et al. 2004); b, (Jovetic et al. 2008); c, (Chen et al. 2016); d, (Yan L 2013); e, (Liu ZY 2018); f, (Huang LL 2012); g, (Marcone et al. 2014); h, (Chen CF 2015). Table 4 Levels of carbon and nitrogen resources selected for the experimental central composite design Factor Name Units Min Max Low High Mean A Glucose g L -1 0.0 20.0 5.0 15.0 10.0 B Maltodextrin g L -1 5.0 65.0 20.0 50.0 35.0 C Soybean meal g L -1 10.0 50.0 20.0 40.0 30.0 D Peptone g L -1 0.0 40.0 10.0 30.0 20.0 E L-valine g L -1 0.5 6.5 2.0 5.0 3.5 Table 5 Analysis of variance (ANOVA) for the quadratic model based on Response Surface Method a Source Sum of Squares Df Mean Square F -value p -value ( prob . > F ) Model 13199.26 20 659.96 37.53 < 0.0001 significant A-Glucose 26.04 1 26.04 1.48 0.2491 B-Maltodextrin 273.37 1 273.37 15.54 0.0023 significant C-Soybean meal 4082.04 1 4082.04 232.11 < 0.0001 significant D-Peptone 77.04 1 77.04 4.38 0.0603 E-L-valine 165.38 1 165.38 9.40 0.0107 significant AB 68.06 1 68.06 3.87 0.0749 AC 45.56 1 45.56 2.59 0.1358 AD 33.06 1 33.06 1.88 0.1977 AE 27.56 1 27.56 1.57 0.2366 BC 1.56 1 1.56 0.0888 0.7712 BD 33.06 1 33.06 1.88 0.1977 BE 18.06 1 18.06 1.03 0.3326 CD 7.56 1 7.56 0.4300 0.5255 CE 10.56 1 10.56 0.6006 0.4547 DE 115.56 1 115.56 6.57 0.0264 significant A² 30.00 1 30.00 1.71 0.2182 B² 2251.67 1 2251.67 128.03 < 0.0001 significant C² 6177.00 1 6177.00 351.23 < 0.0001 significant D² 46.67 1 46.67 2.65 0.1316 E² 736.67 1 736.67 41.89 < 0.0001 significant Residual 193.45 11 17.59 Lack of Fit 68.62 6 11.44 0.4581 0.8152 not significant Pure Error 124.83 5 24.97 Corrected Total 13392.72 31 R² 0.9856 Adjusted R² 0.9593 Predicted R² 0.8503 Adequately Precision 24.7638 a, before eliminating the non-significant terms. Supplementary Files Supportinginformation.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 25 Jul, 2021 Reviewers invited by journal 19 Jul, 2021 Editor assigned by journal 09 Jul, 2021 First submitted to journal 08 Jul, 2021 Editorial decision: Major revisions 28 Jun, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-624980","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":40506829,"identity":"4569ab60-d7b5-4b72-9469-550c24c9d6a2","order_by":0,"name":"Bingyu Yan","email":"","orcid":"","institution":"Liaocheng University","correspondingAuthor":false,"prefix":"","firstName":"Bingyu","middleName":"","lastName":"Yan","suffix":""},{"id":40506830,"identity":"08a0e6ce-f9d2-48ec-a05a-3bbc4e371ba1","order_by":1,"name":"Wen Gao","email":"","orcid":"","institution":"Liaocheng University","correspondingAuthor":false,"prefix":"","firstName":"Wen","middleName":"","lastName":"Gao","suffix":""},{"id":40506831,"identity":"dfea78ca-7ea0-472c-ab5a-78ad288b81f9","order_by":2,"name":"Li Tian","email":"","orcid":"","institution":"Liaocheng University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Tian","suffix":""},{"id":40506832,"identity":"4b165bca-a3b9-4b79-ab1f-d7f539f6c903","order_by":3,"name":"Shuai Wang","email":"","orcid":"","institution":"Liaocheng University","correspondingAuthor":false,"prefix":"","firstName":"Shuai","middleName":"","lastName":"Wang","suffix":""},{"id":40506833,"identity":"3a7cd894-2988-43e3-bf98-723ebd7bcb32","order_by":4,"name":"Huijun Dong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIie3PsWvCQBTH8RcenMszt76D/hEHAatU7L9yEnBy6VI6lYOAk+7xH+l8ksElpGsgbh27RLp0KKURXU0yFrwv3A3H7zMcgM/3H3MACMDNgcG3+p2SlLY/AR6LxZ1KXS9yjl9ENtXWtItwv8k+n1bjga4s6JLeSYML6uPyOlF5sXjYrhj1wcE85Yru0aLavl0nulyOouGJlAYy1hVNrBM47EmC5McUpJ3pJNHHhSCwc91E5fkIqWBUpRGgbEwq3SWtfwn36+iLnl/j8Exmj1Imu/rYQpoEN1cMIOvLQ2Bb9014ms66Vj6fz3fD/QGnfE5HSvB3yAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-6899-879X","institution":"Liaocheng University","correspondingAuthor":true,"prefix":"","firstName":"Huijun","middleName":"","lastName":"Dong","suffix":""}],"badges":[],"createdAt":"2021-06-15 17:54:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-624980/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-624980/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":11682647,"identity":"e9dd26e0-ef6a-4211-9906-b178e610e3ee","added_by":"auto","created_at":"2021-07-21 19:49:31","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":255201,"visible":true,"origin":"","legend":"The recombinant plasmid pIJ8660-Pgapdh-dbv3-Pgapdh-dbv20 (A), PCR verification (B), and fermentation assay of the different strains (C).","description":"","filename":"fig1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-624980/v1/e3da51b551f454860fba5a10.jpeg"},{"id":11682650,"identity":"270b3377-3070-41dd-9cee-f48524f4fd31","added_by":"auto","created_at":"2021-07-21 19:49:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13149,"visible":true,"origin":"","legend":"Comparison of A40926 yield produced by engineered N. gerenzanensis strain in different media. ","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-624980/v1/f17427611fdbbee725981e29.png"},{"id":11682648,"identity":"3b824394-ee58-420b-80ff-fcdae82191d1","added_by":"auto","created_at":"2021-07-21 19:49:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":20773,"visible":true,"origin":"","legend":"The response values of A40926 from 32 tests.","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-624980/v1/6d2381b703c9ee5a6f4ee2b6.png"},{"id":11682503,"identity":"73aae69d-8db8-4d57-9662-50e37da4bba7","added_by":"auto","created_at":"2021-07-21 19:46:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":157683,"visible":true,"origin":"","legend":"Three-dimensional response surface curves for A40926 production yield presenting the mutual interactions of independent variables. (A) soybean meal and maltodextrin; (B) L-valine and maltodextrin; (C) L-valine and peptone; (D) L-valine and soybean meal.","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-624980/v1/3ca0e0831ca5416773a32f11.png"},{"id":11682501,"identity":"cc5d98ba-2083-4ccf-9536-5676fb0f96c8","added_by":"auto","created_at":"2021-07-21 19:46:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13624,"visible":true,"origin":"","legend":"Correlation of predicted values versus experimental values of the response surface methodological model developed by central composite design. ","description":"","filename":"fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-624980/v1/b8861220de2a16c97d737088.png"},{"id":11682875,"identity":"59644ae6-9476-42f9-88b6-9e8631c8a3c3","added_by":"auto","created_at":"2021-07-21 19:52:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":16495,"visible":true,"origin":"","legend":"Fermentation profiles of A40926 production in shake flask experiments using the optimized media.","description":"","filename":"fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-624980/v1/9985f52cf3d465de32eccbd7.png"},{"id":15674479,"identity":"72a57491-885b-4349-88c0-80f52263dcff","added_by":"auto","created_at":"2021-11-18 14:23:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1178624,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-624980/v1/1dfff233-66c6-4a9e-abc7-4115935d6d40.pdf"},{"id":11682498,"identity":"4da5f44d-49d8-48a7-abc4-98505f87cb78","added_by":"auto","created_at":"2021-07-21 19:46:31","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":772666,"visible":true,"origin":"","legend":"","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-624980/v1/cdd57c9dc5838ec1e20efca1.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eProduction enhancement of the glycopeptide antibiotic A40926 produced by an engineered \u003cem\u003eN. gerenzanensis\u003c/em\u003e lcu1\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe antibiotic A40926 belongs to the teicoplanin family of glycopeptides antibiotics (GPAs), which remain a tool of last resort for treating resistant, \u0026ldquo;superbug\u0026rdquo; bacterial infections in clinic (Yim et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It is the precursor of dalbavancin, a second-generation glycopeptide, and consists of a heptapeptide skeleton, two sugar residues, two chlorine atoms, and an acyl chain (Marschall et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The \u003cem\u003edbv\u003c/em\u003e (from \u003cem\u003ed\u003c/em\u003eal\u003cem\u003eb\u003c/em\u003ea\u003cem\u003ev\u003c/em\u003eancin) cluster, is involved in the biosynthesis of A40926, had been isolated and characterized from \u003cem\u003eN. gerenzanensis\u003c/em\u003e ATCC 39727. It spans approximately 71 kb and consists of 37 open reading frames (ORFs) (Sosio et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUntil now, fermentation has still been the only approach for the production of A40926 in industrial scale. Therefore, how to improve A40926 titer is one of the essential researches about the rare actinomyces \u003cem\u003eN. gerenzanensis\u003c/em\u003e. Originally, A40926 yield of the wild-type \u003cem\u003eN. gerenzanensis\u003c/em\u003e strain was only 5 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in an early fermentation study using chemically defined media with high concentrations of phosphate (Gunnarsson et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Later studies demonstrated that initially high inorganic phosphate or ammonium concentrations inhibited A40926 production (Gunnarsson et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Technikova-Dobrova reported that L-Gln, which replaced ammonium or nitrogen as the sole nitrogen in MM-103 medium, could improve the A40926 yield to 123 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Technikova-Dobrova et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Chen and colleagues developed a higher-producing strain by mutagenesis with UV irradiation and diethyl sulfate treatment, which presented the highest yield thus far, 1 g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of A40926. This group also confirmed that the addition of L-leucine could improve A40926 production. Other studies confirmed that the addition of branched-chain amino acids promotes the production of A40926 and teicoplanin (Chen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our recent studies, the positive impacts of the deletion of \u003cem\u003edbv23\u003c/em\u003e and the overexpression of regulatory \u003cem\u003edbv3\u003c/em\u003e and \u003cem\u003edbv20\u003c/em\u003e on A40926 production had been verified, respectively (Yue et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Based on the above founds, we constructed a multiple genetic operating strain laboring the knockout of \u003cem\u003edbv23\u003c/em\u003e and the co-expression of \u003cem\u003edbv3\u003c/em\u003e and \u003cem\u003edbv20\u003c/em\u003e. Furthermore, central composition design was carried out to optimize the medium for obtaining the high yield of A40926 by the mutant.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eBacterial Strains, Plasmids, and Media\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll bacterial strains and plasmids used in this work are listed in Table 1.\u0026nbsp;\u003cem\u003eN.\u0026nbsp;\u003c/em\u003e\u003cem\u003egerenzanensis\u003c/em\u003e and its derivatives were grown on Mannitol-Soy-agar (MS) solid medium at 30℃\u0026nbsp;(Marcone et al. 2010).\u0026nbsp;MS medium supplemented with 20 mM MgCl\u003csub\u003e2\u003c/sub\u003e was used for intergeneric conjugation between \u003cem\u003eEscherichia coli\u003c/em\u003e and mycelia of \u003cem\u003eN. g\u003c/em\u003e\u003cem\u003eerenzanensis.\u003c/em\u003e For seed culture, 50 mL of VSP medium in 250-mL shake flasks were inoculated with a single colony from solid MS media and cultured at 30℃, 220 rpm for 72 h\u003cem\u003e.\u003c/em\u003e For mycelial collection used for intergenic conjugation, the above seed culture was then transferred into 75 mL of VSP medium in 500-mL shake flask with 4% inoculum for continuous culture at 30℃ for 36 h.\u003cem\u003e\u0026nbsp;\u003c/em\u003eFor A40926 production, a set of media listed in Table 3 were chosen to evaluate their abilities of A40926 production, and which were conducted\u0026nbsp;in the 500-mL shake flasks with four baffles\u0026nbsp;at 30℃ and 220 rpm for 168 h.\u003c/p\u003e\n\u003cp\u003eThe\u003cem\u003e\u0026nbsp;E. coli\u0026nbsp;\u003c/em\u003estrains were cultivated on LB agar medium or in LB liquid medium at 37\u0026deg;C. Apramycin (50 \u0026micro;g L\u003csup\u003e-1\u003c/sup\u003e), kanamycin (50 \u0026micro;g L\u003csup\u003e-1\u003c/sup\u003e), chloramphenicol (25 \u0026micro;g L\u003csup\u003e-1\u003c/sup\u003e) and nalidixic acid (25 \u0026micro;g L\u003csup\u003e-1\u003c/sup\u003e), were supplemented when necessary. The\u0026nbsp;\u003cem\u003eE. coli\u003c/em\u003e strain ET12567/pUZ8002 was used as a donor for intergenic conjugation and delivered recombinant plasmids into\u0026nbsp;\u003cem\u003eN.\u003c/em\u003e\u003cem\u003e\u0026nbsp;gerenzanensis\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlasmids Construction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequence of promoter \u003cem\u003egapdh\u003c/em\u003e was synthesized with \u003cem\u003eBam\u0026nbsp;\u003c/em\u003eHI/\u003cem\u003eNde\u0026nbsp;\u003c/em\u003eI sites and further cloned into pIJ8660, yielding pIJ8660-P\u003cem\u003egapdh\u003c/em\u003e. The DNA sequence of the promoter\u0026nbsp;\u003cem\u003egapdh\u003c/em\u003e was provided in Supporting information.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eIsolation of genomic DNA from\u0026nbsp;\u003cem\u003eN. gerenzanensis\u003c/em\u003e were carried out according to instructions of commercial kits (TIANGEN Biotech Co., Ltd, China). The\u0026nbsp;\u003cem\u003edbv3\u003c/em\u003e and\u0026nbsp;\u003cem\u003edbv20\u003c/em\u003e genes were amplified from the genome DNA of\u0026nbsp;\u003cem\u003eN\u003c/em\u003e.\u003cem\u003e\u0026nbsp;gerenzanensis\u003c/em\u003e using the corresponding primers listed in Table 2, respectively. These fragments were cloned into the \u003cem\u003eEco\u0026nbsp;\u003c/em\u003eRV site of pUC57 (Vazyme Biotech Co., Ltd, China), respectively. These plasmids carrying different \u003cem\u003edbv\u003c/em\u003e gene were digested with \u003cem\u003eNde\u0026nbsp;\u003c/em\u003eI and\u0026nbsp;\u003cem\u003eNot\u0026nbsp;\u003c/em\u003eI, and the obtained fragment was cloned into respective sites of pIJ8660-P\u003cem\u003egapdh\u003c/em\u003e to produce pIJ8660-P\u003cem\u003egapdh\u003c/em\u003e-\u003cem\u003edbv3\u003c/em\u003e and pIJ8660-P\u003cem\u003egapdh\u003c/em\u003e-\u003cem\u003edbv20\u003c/em\u003e, respectively. To co-overexpress\u0026nbsp;\u003cem\u003edbv3\u003c/em\u003e and\u0026nbsp;\u003cem\u003edbv20\u003c/em\u003e, the\u0026nbsp;\u003cem\u003edbv3\u003c/em\u003e fragments with promoter\u0026nbsp;\u003cem\u003egapdh\u003c/em\u003e were amplified from\u0026nbsp;pIJ8660\u003cem\u003e-\u003c/em\u003eP\u003cem\u003egapdh-dbv3\u003c/em\u003e and ligated into pIJ8660\u003cem\u003e-\u003c/em\u003eP\u003cem\u003egapdh-dbv20\u003c/em\u003e, generating pIJ8660\u003cem\u003e-\u003c/em\u003eP\u003cem\u003egapdh-dbv3-\u003c/em\u003eP\u003cem\u003egapdh\u003c/em\u003e-\u003cem\u003edbv20\u003c/em\u003e. The expression of \u003cem\u003edbv3\u003c/em\u003e and \u003cem\u003edbv20\u003c/em\u003e was driven by the promoter \u003cem\u003egrpdh\u003c/em\u003e separately.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenotype Confirmation of The Exconjugants by PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe exconjugants on the MS medium were transferred into the VSP medium containing 50 \u0026micro;g mL\u003csup\u003e-1\u003c/sup\u003e apramycin and cultured at 30℃ and 200 rpm for 48 h. The mycelia were collected and treated for extracting genome DNA by commercial kit. Primers listed in Table 2 were used for confirmative PCR of\u0026nbsp;\u003cem\u003egapdh\u003c/em\u003e-\u003cem\u003edbv3\u003c/em\u003e and\u0026nbsp;\u003cem\u003egapdh\u003c/em\u003e-\u003cem\u003edbv20\u003c/em\u003e fusion fragments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOptimization of A40926 Production Utilizing Central Composite Design (CCD)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHere, the optimization process of A40926 production was firstly carried out to identify the preferred media for A40926 production based on the literature (Table 3). A novel medium was designed based on the above optimization results. Subsequently, response surface methodology (RSM) was carried out by the central compost design (CCD) to optimize the redesigned medium, which is a complicated statistical method for determining the optimum experimental conditions that require the minimum number of tests. A software Design Expert 11 (Stat-Ease, Inc., USA, Windows operating system) was applied to perform the experimental design matrix and its statistical experimental design analysis. All assays were performed in triplicate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003eThree-dimensional curves of the response surfaces were obtained by using Design Expert 11 to visualize individual effects and interaction between significant parameters. The model was evaluated using Fisher\u0026acute;s statistical test for analysis of variance (ANOVA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShake Flask Fermentation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the shake flask cultivation, the inoculum was prepared by inoculating the mycelia of \u003cem\u003eN. gerenzanensis\u003c/em\u003e in 50 mL VSP medium in a 500-ml shake flask. The preculture was incubated at 30℃ and 200 rpm, sustaining for 48 h. Based on the literature reports and novel design, nine different production media (Table 3) were selected for the shake flask tests to evaluate their effects on the A40926 production. All experiments were performed in 500-mL shake flasks, with 75 mL of medium and a 10% (v/v) inoculum prepared as described above. The initial pH was set to 7.2 by the addition of 10% ammonium hydroxide or 1 M HCl. Cultivation was performed at 30℃ and 220 rpm, for 144 h. At the end of the experiments, the cultivation broth was collected and used to detect the A40926 yield using high-performance liquid chromatography (HPLC). Three replicated tests were conducted for each medium.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalytical Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe A40926 analysis was similar to that described by Gunnarsson with modifications\u0026nbsp;(Gunnarsson et al. 2003). Briefly, the fermentation broth sample was adjusted to pH 11.3 by adding NaOH solution, and then sonicated at 50\u0026deg;C for 1 h. Subsequently, the sample was centrifuged at 5,000 rpm for 5 min. The supernatant was filtered through a 0.45 \u0026mu;m Millipore filter for analysis. A40926 was analyzed by HPLC equipped with a SHIMAZU Shim-pack GIST C\u003csub\u003e18\u003c/sub\u003e column (5 \u0026mu;m, 250 \u0026times; 4.60 mm) and a UV detector (220 nm)\u0026nbsp;(Technikova-Dobrova et al. 2004). The column temperature was 25\u0026deg;C, the injection volume was 10 \u0026mu;L, and the flow rate was 1.0 mL min\u003csup\u003e-1\u003c/sup\u003e. A gradient with two eluents (eluent A: 10% acetonitrile, 90% 12.5 mM NaH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, pH 7.8; eluent B: 50% acetonitrile, 50% 12.5 mM NaH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, pH 7.8) was applied as follows: (% eluent B): 0 min, 20%, 5 min 50%, 32 min 65%, 35 min 20%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe statistical analyses One-way and Two-way ANOVA were performed using GraphPad Prism version 7.\u003c/p\u003e"},{"header":"Results","content":"Construction of The Engineered Strain\n\nPrevious studies had verified that the overexpression of positive regulatory gene dbv3 or the deletion of dbv23, encoding an acetyltransferase, could enhance the production of A40926 (Lo Grasso et al. 2015; Sosio et al. 2010; Yue et al. 2020a). In addition, we found that the overexpression of dbv20 gene encoding a mannosyltransferase also improved the A40926 production (Dong et al. 2020). In this study, a strategy of multiple genetic operations referring to co-expressing dbv3 and dbv20 in a dbv23-deleted mutant was adopted to improve the strain. The two dbv genes were separately and simultaneously expressed under the control of each promoter gapdh (Fig. 1A). The recombinant plasmid was transferred to the mutant Δ23 by conjugation, which was expected to obtain the final mutant verified by PCR. As a result, the fragments of Pgapdh-dbv3 and Pgapdh-dbv20 were successfully obtained and about 0.7 kb size (Fig. 1B). Furthermore, we compared the A40926 yield of mutant with that of the other control strains including the original strain (Δ23), the wild-type strain, the dbv3-overexpressed stain (op3) and the dbv20-overexpressed strain (op20). As expected, the co-expression of dbv3 and dbv20 further improved the A40926 yield, which increased from 159 to 262 mg L-1 compared with the wild-type strain (Fig. 1C). \n\nMedia Screening Experiments\n\nPrevious studies had reported some suitable media for A40926 production (Table 3). In this work, we applied these media to evaluate their capabilities for A40926 production, and further redesigned medium and optimized the components. The fermentation results demonstrated that the more kinds of natural components, such as maltodextrin, soybean meal, peptone, and corn starch, were contained in the medium, and the higher the yield of A40926 was (Fig. 2). Based on the results, a novel combination medium was designed and named M9, which was composed of carbon resource of glucose and maltodextrin, nitrogen resource of peptone and soybean meal, the amino acid of L-valine, and other inorganic salts. In contrast to media from literature, the engineered strain gave the highest yield of A40926 in M9 medium as expected. It was supposed that the proper ratio of carbon and nitrogen resource, the relative lower viscosity of the medium, and more various inorganic salts were beneficial to improve the A40926 production.\n\nOptimization of Medium Components for A40926 Production by CCD\n\nTo further optimize the components of M9 medium, central composition design was applied. The optimization process focused on investigating the impact of five independent variables: glucose (A) and maltodextrin (B) as carbon sources, soybean meal (C) and peptone (D) as nitrogen sources, L-valine as a precursor (E), on the yield of A40926, using response surface methodology based on central composite design (Table 4).\n\n A statistically designed study was performed to evaluate the individual and the interactive effect of five medium ingredients on the A40926 yield. The values of response from the 32 experiments are presented in Fig. 3. The first set of optimal statistical conditions, maximizing A40926 yield by N. gerenzanensis were obtained with 28-32 standard tests (Supplementary Table 1) which corresponded to the medium composition including glucose 10 (g L-1), maltodextrin 35 (g L-1), soybean meal 30% (g L-1), peptone 20 (g L-1), and L-valine 3.5 (g L-1).\n\n Here, RSM is a five factorial design where 3D contour plots of surface curves (Fig. 4 and Supplementary Fig. 1) can be generated by linear effects, quadratic effects and two-way interactions between the factors. From these profiles, a semi-empiric model (Eq.1) can be derived that best fits the experimental data. The parameters and results of the CCD experiments are presented in Table 4, Fig. 3 and 4, and Supplementary Table 1 and Fig 1. The statistical significance of the quadratic model was tested by F- and p- values (Table 5). The results from ANOVA indicated that the quadratic regression used to produce a second-order model was significant, as revealed from the p- and F-values: the calculated Model F-value of 37.53 and the p-value of \u003c0.0001 indicate that the model is significant. The Lack of Fit F-value of 0.45 implies that the Lack of Fit is not significant relative to the pure error. There is 81.52% chance that a Lack of Fit F-value this large could occur due to noise. \n\nThe second–order polynomial equation of the model fitted for A40926 production before eliminating the non-significant terms is: A40926 production yield (mg/l)= 64.4097+0.929924*A+3.31465*B+9.69432*C+0.885795*D+ 8.7298*E-0.0275*AB+0.03375*AC-0.02875*AD+0.175*AE-0.00208333*BC-0.00958333*BD+0.0472222* BE-0.006875*CD+0.0541667*CE+0.179167*DE-0.0404545*A2-0.0389394*B2-0.145114*C2-0.0126136*D2 -2.22727*E2 (Eq. 1) (Degree of freedom=20; F-value=37.53; p-value \u003c0.0001; R2=0.9856)\n\n In this study, the model terms with the values of p-value Prob \u003e F (Table 5) lower than 0.05 was considered as the significant terms. On the contrary, if the p-value Prob \u003e F is higher than 0.1, the model terms are non-significant. In this case, the model terms B (maltodextrin), C (soybean meal), E (L-valine), DE, B2, C2, and E2 were considered significant. The R2 value provides a measure of how much variability in the observed response values can be explained by the experimental factors and their interactions. The closer the R2 value to 1.00, the stronger the model is, and the better it predicted the observed response. It was suggested that the R2 value should be at least 0.80, for a good model fitness(Venkatachalam et al. 2020). Here, the calculated R2 value of 0.9543 (Supplementary Table 2), indicated that 4.57% of the total variation could not be explained by the empirical model; this expresses a good enough quadratic fit to navigate the design space. Thus, the response surface model developed in this study for predicting the A40926 production may be considered satisfactory (Eq. 2). The signal to noise ratio was measured by Adeq Precision value of 33.0287, which indicated that this model could be used to navigate the design space.\n\nFrom the above, the second-order polynomial equation of the model fitted for A40926 production, after eliminating the non-significant terms (Supplementary Table 2), is A40926 production yield (mg L-1)=323.91+3.37*B+13.04*C+2.63*E+2.69*DE-8.59*B2-14.34*C2-4.84*E2 (Eq. 2) (Degree of freedom=7; F-value=71.54; p-value \u003c0.0001; R2=0.9543)\n\nWhereby the F-value increased, meaning that the mean squares of the model are larger than the square residual average. Thus, with a higher the F-value, the more significant p-value for ANOVA and the more significant the model is.\n\nEffect of Significant Components on A40926 Production\n\n3D response surface graphs (Fig. 4 and Supplementary Fig. 1) were plotted to illustrate the interaction of the different paired factors and to determine the optimum of each paired factor for maximum response. Each graph represents the combinations of two test factors in relation to A40926 production yield. The data in Fig. 4 indicate that the increase in significant carbon source (maltodextrin) and amino acid/nitrogen sources (soybean meal, peptone, and L-valine) resulted in increased A40926 production. From the combined effect of maltodextrin and soybean meal concentration (Fig. 4A), the highest production was obtained by the appropriate soybean meal concentration and the proper maltodextrin concentration. Similar results were obtained with the combined effect of L-valine and maltodextrin (Fig. 4B). The effects of L-valine and peptone concentrations, and of L-valine and soybean meal, on A40926 production yield are illustrated in Fig. 4C and 4D. Yield increased as the concentrations of soybean meal and L-valine increased and decreased, respectively. The main medium combination of L-valine and peptone (DE, Table 5) showed the highest p-value for Prob \u003e F (0.0264) and therefore represented a more significant model term combination. L-valine is a well-known precursor for A40926 production and meanwhile is a source of nitrogen(Alduina et al. 2018; Beltrametti et al. 2004; Yue et al. 2020b). It is possible that higher concentrations of these nutrients could have led to a substrate growth inhibition and/or affected A40926 production.\n\n The optimal concentrations of the four factors excluding factor glucose that maximized A40926 production yield were predicted using the optimization function of the statistical experimental designs Design Expert 11. Glucose 10 (g L-1), maltodextrin 37.9 (g L-1), soybean meal 34.5 (g L-1), peptone 30.0 (g L-1), and L-valine 4.3 (g L-1) were chosen as the optimal concentrations, resulting in the highest A40926 yield of 328.6 mg L-1. The predicted medium composition roughly coincided with experiment trials from 27 to 32 (Supplementary Table 1). No statistical differences were observed between the predicted maximum production yield and the experimental results (p \u003e 0.05). The optimized results were also confirmed (p \u003e 0.05) by conducting a further fermentation experiment in triplicate at the above-optimized values, resulting in production yield of 332±13 mg L-1. A Parity plot illustrating the distribution of experimental (actual) and predicted (model) values is shown in Fig. 5. Data points are scattered along the diagonal line, also suggesting that the model is adequate to explain A40926 production within the experimental range studied.\n\n The process profiles of A40926 production shown in Fig. 6 obtained by the cultivation of the engineered strain lcu1 in the non-optimized and optimized media, respectively. Here, the strain lcu1 was denominated by the abbreviation of Liaocheng University number one, and which has the genetic characteristics of the dbv23 gene deletion and the dbv3-dbv20 gene co-expression. During the first 48 h of culture, there was no difference in the two media for A40926 production. Subsequently, the productivity of A40926 in the optimized medium was always higher than that in the non-optimized medium. In particular, the biosynthesis of A40926 stagnated and even decreased in the last 24 h of fermentation. The yield of A40926 in the optimized medium reached 332 mg L-1 at the end of fermentation, which was significantly higher than that of 257 mg L-1 in the non-optimized medium."},{"header":"Discussion","content":"\u003cp\u003eIn this study, we combined the genetic manipulation of \u003cem\u003edbv\u003c/em\u003e genes and the traditional media optimization to enhance the production of A40926. The strategy brought a significant increase of A40926 yield by 65.2 percent, which exceeded our expectations. The previous researches referring to the \u003cem\u003edbv\u003c/em\u003e cluster gave us a comprehensive understanding of the biosynthesis of A40926. For instance, the pathway-specific regulatory gene \u003cem\u003edbv3\u003c/em\u003e and \u003cem\u003edbv4\u003c/em\u003e were verified to play positive roles in the A40926 production (Alduina et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Lo Grasso et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The post-modified genes in \u003cem\u003edbv\u003c/em\u003e cluster exerted significant roles in the biosynthesis of A40926, which included seven genes such as \u003cem\u003edbv8\u003c/em\u003e encoding an acyltransferase (Kruger et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), \u003cem\u003edbv21\u003c/em\u003e encoding a deacetylase (Ho et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), \u003cem\u003edbv23\u003c/em\u003e encoding an acetyltransferase (Sosio et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and \u003cem\u003edbv29\u003c/em\u003e encoding a hexose oxidase (Liu et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Typically, the absence of \u003cem\u003edbv23\u003c/em\u003e distinctively promoting the production of A40926 had been confirmed by Sosio\u0026acute;s and our previous studies (Sosio et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Yue et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Recently, the overexpression of the \u003cem\u003edbv20\u003c/em\u003e gene, encoding a mannosyltransferase, was verified to improve the A40926 production (Dong et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Here, we constructed an engineered strain with the deletion of \u003cem\u003edbv23\u003c/em\u003e and the co-expression of \u003cem\u003edbv3\u003c/em\u003e and \u003cem\u003edbv20\u003c/em\u003e to improve the A40926 yield actually.\u003c/p\u003e \u003cp\u003eTo further improve the A40926 production, the preferred nutrients, including carbon and nitrogen sources for A40926 production, were determined based on the literature and the preliminary fermentation assays. As shown in the results (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the delayed natural carbon and nitrogen sources such as maltodextrin and soybean meal were beneficial to producing A40926. Nevertheless, it should be noted that the higher concentration of these delayed carbon and nitrogen sources, such as corn starch and soybean meal, resulted in a decrease of A40926 yield, which might be caused by the limitation of the dissolved oxygen transfer. Therefore, we designed a novel medium M9 based on the comprehensive consideration of viscosity related to oxygen transfer and the mixture of the delayed and quick-acting carbon and nitrogen sources. The M9 medium led to the highest yield of A40926 among the screened media.\u003c/p\u003e \u003cp\u003eFurthermore, response surface methodology with central composite design was carried out to obtain a mathematical model to identify the optimum concentrations of the significant components for the improvement of A40926 production. The most optimal concentrations of significant medium components were glucose 10 g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, maltodextrin 37.9 g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, soybean meal 34.5 g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, peptone 30.0 g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eL\u003c/span\u003e-valine 4.3 g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The maximum yield 332 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of A40926 was obtained. Therefore, the response surface statistical methods should be effective for optimizing the medium nutrients for the production of secondary metabolites from microorganisms.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies with human participants or animals performed by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Natural Science Foundation of Shandong Province (Grant no. ZR2015CL001).\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003eAlduina R, Lo Piccolo L, D\u0026apos;Alia D, Ferraro C, Gunnarsson N, Donadio S, Puglia AM (2007) Phosphate-controlled regulator for the biosynthesis of the dalbavancin precursor A40926 J Bacteriol 189:8120-8129 doi:10.1128/JB.01247-07\u003c/p\u003e\n\u003cp\u003eAlduina R, Sosio M, Donadio S (2018) Complex Regulatory Networks Governing Production of the Glycopeptide A40926 Antibiotics (Basel) 7 doi:10.3390/antibiotics7020030\u003c/p\u003e\n\u003cp\u003eBeltrametti F, Jovetic S, Feroggio M, Gastaldo L, Selva E, Marinelli F (2004) Valine influences production and complex composition of glycopeptide antibiotic A40926 in fermentations of Nonomuraea sp. ATCC 39727 J Antibiot (Tokyo) 57:37-44 doi:10.7164/antibiotics.57.37\u003c/p\u003e\n\u003cp\u003eChen CF ZH, Zhang CQ, Hu HF (2015) Breeding the high-producer of A40926 and improving its fermentation technology Chinese Journal of Antibiotics 40:28-32 doi:https://doi.org/10.3969/j.issn.1001-8689.2015.01.005\u003c/p\u003e\n\u003cp\u003eChen M, Xu T, Zhang G, Zhao J, Gao Z, Zhang C (2016) High-yield production of lipoglycopeptide antibiotic A40926 using a mutant strain Nonomuraea sp. DP-13 in optimized medium Prep Biochem Biotechnol 46:171-175 doi:10.1080/10826068.2015.1015561\u003c/p\u003e\n\u003cp\u003eDong H, Yue X, Yan B, Gao W, Wang S, Li Y (2020) Improved A40926 production from Nonomuraea gerenzanensis using the promoter engineering and the co-expression of crucial genes J Biotechnol 324:28-33 doi:10.1016/j.jbiotec.2020.09.017\u003c/p\u003e\n\u003cp\u003eGoldstein BP et al. (1987) A40926, a new glycopeptide antibiotic with anti-Neisseria activity Antimicrob Agents Chemother 31:1961-1966 doi:10.1128/aac.31.12.1961\u003c/p\u003e\n\u003cp\u003eGunnarsson N, Bruheim P, Nielsen J (2003) Production of the glycopeptide antibiotic A40926 by Nonomuraea sp. ATCC 39727: influence of medium composition in batch fermentation J Ind Microbiol Biotechnol 30:150-156 doi:10.1007/s10295-003-0024-6\u003c/p\u003e\n\u003cp\u003eGunnarsson N, Bruheim P, Nielsen J (2004) Glucose metabolism in the antibiotic producing actinomycete Nonomuraea sp. ATCC 39727 Biotechnol Bioeng 88:652-663 doi:10.1002/bit.20279\u003c/p\u003e\n\u003cp\u003eGust B, Challis GL, Fowler K, Kieser T, Chater KF (2003) PCR-targeted Streptomyces gene replacement identifies a protein domain needed for biosynthesis of the sesquiterpene soil odor geosmin Proc Natl Acad Sci U S A 100:1541-1546 doi:10.1073/pnas.0337542100\u003c/p\u003e\n\u003cp\u003eHo JY, Huang YT, Wu CJ, Li YS, Tsai MD, Li TL (2006) Glycopeptide biosynthesis: Dbv21/Orf2 from dbv/tcp gene clusters are N-Ac-Glm teicoplanin pseudoaglycone deacetylases and Orf15 from cep gene cluster is a Glc-1-P thymidyltransferase J Am Chem Soc 128:13694-13695 doi:10.1021/ja0644834\u003c/p\u003e\n\u003cp\u003eHuang LL SX, Chen SX (2012) Optimization of fermentation medium and mutation breeding a glycopeptide antibiotic A40926 B producing strain Chinese journal of pharmaceuticals 43:256-259 doi:https://doi.org/10.3969/j.issn.1001-8255.2012.04.006\u003c/p\u003e\n\u003cp\u003eJovetic S, Feroggio M, Marinelli F, Lancini G (2008) Factors influencing cell fatty acid composition and A40926 antibiotic complex production in Nonomuraea sp. ATCC 39727 J Ind Microbiol Biotechnol 35:1131-1138 doi:10.1007/s10295-008-0392-z\u003c/p\u003e\n\u003cp\u003eKruger RG, Lu W, Oberthur M, Tao J, Kahne D, Walsh CT (2005) Tailoring of glycopeptide scaffolds by the acyltransferases from the teicoplanin and A-40,926 biosynthetic operons Chem Biol 12:131-140 doi:10.1016/j.chembiol.2004.12.005\u003c/p\u003e\n\u003cp\u003eLiu YC et al. (2011) Interception of teicoplanin oxidation intermediates yields new antimicrobial scaffolds Nat Chem Biol 7:304-309 doi:10.1038/nchembio.556\u003c/p\u003e\n\u003cp\u003eLiu ZY LJ, Zhu BF, et al (2018) High-throughput screening for A40926 high producing strain Chinese Journal of Pharmaceuticals 49:316-321 doi:https://doi.org/10.16522/j.cnki.cjph.2018.03.008\u003c/p\u003e\n\u003cp\u003eLo Grasso L, Maffioli S, Sosio M, Bibb M, Puglia AM, Alduina R (2015) Two Master Switch Regulators Trigger A40926 Biosynthesis in Nonomuraea sp. 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ATCC 39727 Antimicrob Agents Chemother 58:5191-5201 doi:10.1128/AAC.02626-14\u003c/p\u003e\n\u003cp\u003eMarcone GL, Carrano L, Marinelli F, Beltrametti F (2010) Protoplast preparation and reversion to the normal filamentous growth in antibiotic-producing uncommon actinomycetes J Antibiot (Tokyo) 63:83-88 doi:10.1038/ja.2009.127\u003c/p\u003e\n\u003cp\u003eMarschall E, Cryle MJ, Tailhades J (2019) Biological, chemical, and biochemical strategies for modifying glycopeptide antibiotics J Biol Chem 294:18769-18783 doi:10.1074/jbc.REV119.006349\u003c/p\u003e\n\u003cp\u003eSosio M, Canavesi A, Stinchi S, Donadio S (2010) Improved production of A40926 by Nonomuraea sp. through deletion of a pathway-specific acetyltransferase Appl Microbiol Biotechnol 87:1633-1638 doi:10.1007/s00253-010-2579-2\u003c/p\u003e\n\u003cp\u003eSun J, Kelemen GH, Fernandez-Abalos JM, Bibb MJ (1999) Green fluorescent protein as a reporter for spatial and temporal gene expression in Streptomyces coelicolor A3(2) Microbiology (Reading) 145 ( Pt 9):2221-2227 doi:10.1099/00221287-145-9-2221\u003c/p\u003e\n\u003cp\u003eTechnikova-Dobrova Z et al. (2004) Design of mineral medium for growth of Actinomadura sp. ATCC 39727, producer of the glycopeptide A40926: effects of calcium ions and nitrogen sources Appl Microbiol Biotechnol 65:671-677 doi:10.1007/s00253-004-1626-2\u003c/p\u003e\n\u003cp\u003eVenkatachalam M, Shum-Cheong-Sing A, Dufosse L, Fouillaud M (2020) Statistical Optimization of the Physico-Chemical Parameters for Pigment Production in Submerged Fermentation of Talaromyces albobiverticillius 30548 Microorganisms 8 doi:10.3390/microorganisms8050711\u003c/p\u003e\n\u003cp\u003eYan L HC, Zhu CY, et al (2013) Breeding high-producer of glycopeptide antibiotic A40926 Chinese Journal of Pharmaceuticals 44:143-145\u003c/p\u003e\n\u003cp\u003eYim G, Thaker MN, Koteva K, Wright G (2014) Glycopeptide antibiotic biosynthesis J Antibiot (Tokyo) 67:31-41 doi:10.1038/ja.2013.117\u003c/p\u003e\n\u003cp\u003eYue X, Xia T, Wang S, Dong H, Li Y (2020a) Highly efficient genome editing in N. gerenzanensis using an inducible CRISPR/Cas9-RecA system Biotechnol Lett 42:1699-1706 doi:10.1007/s10529-020-02893-2\u003c/p\u003e\n\u003cp\u003eYue X, Yan B, Wang S, Gao W, Zhang R, Dong H (2020b) Preparation of pH-Responsive Alginate-Chitosan Microspheres for L-Valine Loading and Their Effects on the A40926 Production Curr Microbiol 77:1016-1023 doi:10.1007/s00284-020-01894-8\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Strains and plasmids used in this work\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"93%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003eStrains or plasmids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003eCharacteristics\u003csup\u003ea\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003eSources or reference\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003eDH5\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003eRoutine subcloning host\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003eET12567/pUZ8002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003eDerived from the methylation-defective strain ET12567 carrying plasmid and donor strain for\u0026nbsp;\u003cem\u003eE. coli\u003c/em\u003e-\u003cem\u003eActinomyces\u003c/em\u003e conjugation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003e(Gust et al. 2003)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eActinomyces\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u003cem\u003eN. gerenzanensis\u003c/em\u003e ATCC 39727\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003eWild-type, glycopeptide A40926 producer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003e(Goldstein et al. 1987)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u0026Delta;23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003e\u003cem\u003eN. gerenzanensis\u003c/em\u003e mutant with the knockout of \u003cem\u003edbv23\u003c/em\u003e gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003e(Yue et al. 2020a)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003elcu1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003e\u0026Delta;23 strain laboring pIJ8660\u003cem\u003e-\u003c/em\u003e\u003cem\u003egapdhp-dbv3-gapdhp-dbv20\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003eThis study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlasmids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003epIJ8660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003eA pSET152 derivative.\u0026nbsp;Apr\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003e(Sun et al. 1999)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003epIJ8660-P\u003cem\u003egapdh\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"45.91836734693877%\"\u003e\n \u003cp\u003epIJ8660 plasmid with promoter\u003cem\u003e\u0026nbsp;gapdh\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.551020408163264%\"\u003e\n \u003cp\u003eThis study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003epIJ8660\u003cem\u003e-\u003c/em\u003eP\u003cem\u003egapdh\u003c/em\u003e\u003cem\u003e-dbv3-\u003c/em\u003eP\u003cem\u003egapdh\u003c/em\u003e-\u003cem\u003ebv20\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"45.91836734693877%\"\u003e\n \u003cp\u003epIJ8660 plasmid with two promoter\u003cem\u003e\u0026nbsp;gapdh\u003c/em\u003e,\u0026nbsp;\u003cem\u003edbv3\u003c/em\u003e and\u0026nbsp;\u003cem\u003edbv20\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eThis study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003ea: Apr\u003csup\u003er\u003c/sup\u003e,\u0026nbsp;apramycin resistance\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Oligonucleotides and Primers used in this work\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.224489795918368%\"\u003e\n \u003cp\u003ePrimers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.224489795918366%\"\u003e\n \u003cp\u003eSequence (5\u0026acute;-3\u0026acute;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.224489795918368%\"\u003e\n \u003cp\u003ep1/p2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.224489795918366%\"\u003e\n \u003cp\u003etgaaaggggatacgccatatggtgctgttcgggcgagatcgtg\u003c/p\u003e\n \u003cp\u003eacgggctgcagccgggcggccgcctacagccgcactgcctcacg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eAmplification for \u003cem\u003edbv3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.224489795918368%\"\u003e\n \u003cp\u003ep3/p4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"61.224489795918366%\"\u003e\n \u003cp\u003etgaaaggggatacgccatatgatgtcgcacatcaccatgactc\u003c/p\u003e\n \u003cp\u003eacgggctgcagccgggcggtacctcagcccccgggtgtccg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eAmplification for \u003cem\u003edbv20\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.224489795918368%\"\u003e\n \u003cp\u003ep5/p6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.224489795918366%\"\u003e\n \u003cp\u003egctgctccttcggtcggacgtgcgtctacg\u003c/p\u003e\n \u003cp\u003ecacggcccagatcgcccacacctcctccgg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eVerification of lcu1 strain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.224489795918368%\"\u003e\n \u003cp\u003ep7/p8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.224489795918366%\"\u003e\n \u003cp\u003egctgctccttcggtcggacgtgcgtctacg\u003c/p\u003e\n \u003cp\u003etccggtacatcaccagcaccgagatcacgc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eVerification of lcu1 strain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Media used for the cultivation of the engineered \u003cem\u003eN. gerenzanensis\u003c/em\u003e lcu1 in this study\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"101%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eComponent (g L\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003eM1 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003eM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003eM3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003eM4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003eM5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003eM6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003eM7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003eM8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003eM9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eGlucose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eMaltodextrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003ePeptone\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eYeast extract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eSoybean meal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eCorn starch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eSoluble starch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eTryptone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eCottonseed meal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eSoybean protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eMeat peptone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eSoybean oil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eFish powder/peptone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eMalt extract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eCasein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eL-Leu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eL-Gln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eL-Val\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eL-Tyr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eL-Ile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eK\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eKH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eMgSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;7H\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eFeSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;7H\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003e(NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eCaCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eNaCl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eCuSO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e7.0-7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.649484536082475%\"\u003e\n \u003cp\u003eReferences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003ea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003eb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003ec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003ed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003ee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003ef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003eg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.185567010309279%\"\u003e\n \u003cp\u003eh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003eThis study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea,\u0026nbsp;(Technikova-Dobrova et al. 2004); b,\u0026nbsp;(Jovetic et al. 2008); c,\u0026nbsp;(Chen et al. 2016); d,\u0026nbsp;(Yan L 2013); e,\u0026nbsp;(Liu ZY 2018); f,\u0026nbsp;(Huang LL 2012); g,\u0026nbsp;(Marcone et al. 2014); h,\u0026nbsp;(Chen CF 2015).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Levels of carbon and nitrogen resources selected for the experimental central composite design\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eName\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eUnits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eMin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eGlucose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eg L\u003csup\u003e-1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eMaltodextrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eg L\u003csup\u003e-1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e35.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eSoybean meal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eg L\u003csup\u003e-1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003ePeptone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eg L\u003csup\u003e-1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003eE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eL-valine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eg L\u003csup\u003e-1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5 Analysis of variance (ANOVA) for the quadratic model based on Response Surface Method\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003eSum of Squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003eDf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMean Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value (\u003cem\u003eprob\u003c/em\u003e. \u0026gt;\u003cem\u003eF\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e13199.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e659.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e37.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003esignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eA-Glucose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e26.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e26.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.2491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eB-Maltodextrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e273.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e273.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e15.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.0023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003esignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eC-Soybean meal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e4082.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e4082.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e232.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003esignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eD-Peptone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e77.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e77.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.0603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eE-L-valine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e165.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e165.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e9.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.0107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003esignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eAB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e68.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e68.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e3.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.0749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e45.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e45.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.1358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e33.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e33.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.1977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eAE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e27.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e27.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.2366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.0888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.7712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eBD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e33.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e33.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.1977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eBE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e18.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e18.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.3326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e7.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e7.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.4300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.5255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e10.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e10.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.6006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.4547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eDE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e115.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e115.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e6.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.0264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003esignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eA\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e30.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e30.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.2182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eB\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e2251.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e2251.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e128.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003esignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eC\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e6177.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e6177.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e351.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003esignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eD\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e46.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e46.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.1316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eE\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e736.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e736.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e41.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003esignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e193.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e17.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eLack of Fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e68.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e11.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.4581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.8152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003enot significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003ePure Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e124.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e24.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.711656441717793%\"\u003e\n \u003cp\u003eCorrected Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e13392.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.779141104294478%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.711656441717793%\"\u003e\n \u003cp\u003eR\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.9856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.711656441717793%\"\u003e\n \u003cp\u003eAdjusted R\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.9593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.711656441717793%\"\u003e\n \u003cp\u003ePredicted R\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.779141104294478%\"\u003e\n \u003cp\u003e0.8503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.711656441717793%\"\u003e\n \u003cp\u003eAdequately Precision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.515337423312883%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.779141104294478%\"\u003e\n \u003cp\u003e24.7638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.036809815950921%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea, before eliminating the non-significant terms.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biotechnology-letters","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bile","sideBox":"Learn more about [Biotechnology Letters](https://www.springer.com/journal/10529)","snPcode":"10529","submissionUrl":"https://submission.nature.com/new-submission/10529/3","title":"Biotechnology Letters","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"A40926 ,N. gerenzanensis , Genetic engineering , Central composite design","lastPublishedDoi":"10.21203/rs.3.rs-624980/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-624980/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo enhance the production of A40926 by implementing a strategy of the combination of genetically engineered strain construction and medium optimization.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe engineered strain of \u003cem\u003eNonomuraea gerenzanensis\u003c/em\u003e presented an increment of 30.6 percent in A40926 production compared with that of the parent strain. Subsequently, an assembling medium, which was defined as M9 medium and mainly comprised glucose, maltodextrin, soybean meal, peptone, L-valine, and other inorganic salts, was determined as the optimal medium among the tested nine media. The optimum concentration of medium components was glucose 10 g/l, maltodextrin 37.9 g/l, soybean meal 34.5 g/l, peptone 30.0 g/l, and L-valine 4.3 g/l, respectively. The optimized medium was verified experimentally, and A40926 yield increased significantly from 257 mg/l to 332 mg/l, as compared to the non-optimized medium. The strategy brought a significant increase of A40926 yield by 65.2 percent.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe engineered mutant with the genetic attributes of the co-expression of the \u003cem\u003edbv3\u003c/em\u003e and \u003cem\u003edbv20\u003c/em\u003e genes and the deletion of the \u003cem\u003edbv23\u003c/em\u003e gene could obviously enhance the production of A40926. In addition, the optimization of medium was an effective and essential tool for the improvement of the secondary metabolites in Actinomyces.\u003c/p\u003e","manuscriptTitle":"Production enhancement of the glycopeptide antibiotic A40926 produced by an engineered N. gerenzanensis lcu1","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-07-21 19:46:29","doi":"10.21203/rs.3.rs-624980/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2021-07-25T04:33:59+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-07-19T15:28:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-07-09T08:04:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biotechnology Letters","date":"2021-07-08T05:16:48+00:00","index":"","fulltext":""},{"type":"decision","content":"Major revisions","date":"2021-06-28T10:20:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biotechnology-letters","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bile","sideBox":"Learn more about [Biotechnology Letters](https://www.springer.com/journal/10529)","snPcode":"10529","submissionUrl":"https://submission.nature.com/new-submission/10529/3","title":"Biotechnology Letters","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a71ef0ee-acd5-40dd-835d-1452becc7576","owner":[],"postedDate":"July 21st, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":5876569,"name":"Biotechnology and Bioengineering"},{"id":5876570,"name":"Applied \u0026 Industrial Microbiology"}],"tags":[],"updatedAt":"2021-11-16T09:45:07+00:00","versionOfRecord":[],"versionCreatedAt":"2021-07-21 19:46:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-624980","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-624980","identity":"rs-624980","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}