Integrated bioprocessing and genetic strategies to enhance soluble expression of anti-HER2 immunotoxin in E. coli

Integrated bioprocessing and genetic strategies to enhance soluble expression of anti-HER2 immunotoxin in E. coli | 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 Integrated bioprocessing and genetic strategies to enhance soluble expression of anti-HER2 immunotoxin in E. coli Sheida Mani, Bahareh Arab, Vajihe Akbari, C. Perry Chou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4155503/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Sep, 2024 Read the published version in AMB Express → Version 1 posted 4 You are reading this latest preprint version Abstract Immunotoxins are widely applied for cancer therapy. However, bacterial expression of immunotoxins usually leads to the formation of insoluble and non-functional recombinant proteins. In this study, we aimed to improve soluble expression of a novel anti-HER2 immunotoxin under the regulation of the trc promoter in Escherichia coli by optimization of the cultivation conditions using response surface methodology (RSM). To conduct RSM, four cultivation variables ( i.e. , inducer concentration, post-induction time, post-induction temperature, and medium recipe), were selected for statistical characterization and optimization using the Box-Behnken design and Design Expert software. Based on the developed model using the Box-Behnken design, the optimal cultivation conditions for soluble expression of anti-HER2 immunotoxin were determined to be 0.1 mM IPTG for induction in the LB medium at 33 °C for 18 h. The expressed immunotoxin was successfully purified using affinity chromatography with more than 90% purity and its bioactivity was confirmed using cell-based ELISA. Technical approach developed in this study can be generally applied to enhance the production yield and quality of recombinant proteins using E. coli as the gene expression system. Immunotoxin Response Surface Methodology (RSM) cultivation optimization protein solubility Escherichia coli Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Immunotoxins are protein molecules widely used for cancer therapy these days (Xing et al. 2021). Successful biological action of immunotoxins relies on their effective attachment to the target cell and subsequent translocation of the toxin's bioactive fragment into the cytosol of the target cell. Because of their high cytotoxicity and potential inhibition of protein synthesis in eukaryotic cells, immunotoxins are often expressed in bacterial hosts for subsequent medical administration. Expression of immunotoxins in E. coli usually leads to the formation and accumulation of insoluble aggregates with no biological function, i.e. , inclusion bodies (Akbari et al. 2017, Kim et al. 2020). This presents a major technological challenge that requires a laborious and time-consuming process for protein refolding. The retrieval of soluble proteins from pre-existing inclusion bodies frequently results in reduced protein yield and biological activity, substantially increasing the production expenses associated with downstream separation processing. Alternatively, the soluble expression of foreign proteins in E. coli can be enhanced by the following bioprocessing and/or genetic strategies, including modulation and optimization of cultivation conditions ( e.g. , temperature, medium composition, and aeration, etc.), co-expression with chaperons, genetic modification of host strains, and modifying the level of inducer and the promoter strength (Rosano et al. 2019). Different promoters have been genetically explored for heterologous gene expression in E. coli . Among them, the T7 promoter appears to be stronger than the common promoters, such as tac, lac , and trp (Rosano, Morales et al. 2019). Although the T7 promoter is widely used to produce recombinant proteins, it usually leads to the formation of inclusion bodies. On the other hand, the trc promoter, a hybrid fusion of the lac and trp promoters, offers more robust regulatory capabilities and higher promoter strength than the native lac promoter (Samuelson 2011). Previous studies (Mayer et al. 2004) demonstrated that the trc promoter, though exhibiting a lower promoter strength compared to the T7 one, can potentially generate a higher quantity of soluble recombinant protein. Mayer and coworkers reported that, upon the overproduction of human proteins for X-ray crystallography and NMR studies, incorporating the trc promoter, instead of the T7 promoter, with proper optimization of culture conditions can effectively increase the solubility and yield of the heterologous proteins (Mayer, Dailey et al. 2004). Therefore, proper integration of genetic and bioprocessing strategies appears to be crucial for more efficient soluble expression of recombinant proteins. Traditionally, optimizing cultivation conditions for recombinant protein expression involves altering one variable at a time (Bezerra et al. 2008). However, this approach is not only time-consuming but also leads to misinterpretation of results due to potential uncharacterized interactions among different variables. Several alternative methods exist to analyze multiple variables simultaneously, such as full factorial and fractional factorial design (Lee et al. 2006). Response Surface Methodology (RSM) is a suitable approach for effectively determining the interactions among experimental/operating variables, resulting in more reliable prediction of the optimal conditions (Liu et al. 2018). In our previous study (Shariaty Vaziri et al. 2023), we developed a novel anti-HER2 immunotoxin containing a modified Pseudomonas toxin (PE35KDEL). This fusion protein ( i.e. , scFv‑PE35KDEL) was expressed using the pET28a vector containing the T7 promoter, resulting in significant formation of inclusion bodies with only 10% of the resulting proteins being soluble. Adjusting the culture conditions ( e.g. , temperature and inducer concentration) barely improved the soluble expression of the recombinant protein (Shariaty Vaziri, Shafiee et al. 2023). In the current study, the immunotoxin was expressed under the regulation of the trc promoter. To improve the soluble expression of this immunotoxin, the cultivation conditions, such as inducer concentration, culture temperature, growth medium, and induction timing were optimized using Box–Behnken design with RSM. Materials and Methods Bacterial strains, plasmids, and oligonucleotides A list of bacterial strains, plasmids, and oligonucleotides used in this study is provided in Table 1 . Standard recombinant DNA technologies were applied for molecular cloning (Hofnung 1993). Phusion HF was obtained from New England Biolabs (Ipswich, MA, USA). All synthesized oligonucleotides and gBlocks were obtained from Integrated DNA Technologies (Coralville, IA, USA). E. coli HI-Control 10G chemically competent cell (Lucigen, Middleton, WI, USA) was used as the host for plasmid cloning and propagation. E. coli BL21(DE3) was used as the expression host to produce recombinant anti-HER2 immunotoxin. Table 1 Bacterial strains, plasmids, and primers used in this study. Name Description or relevant genotype Source E. coli host strains HI-Control 10G mcrA , ∆( mrr-hsdRMS-mcrBC ), endA1, recA1, ϕ 80 dlacZ ∆M15, ∆ lacX74, araD139 , ∆( ara leu ) 7697, galU, galK, rpsL (Str R ), nupG, λ − , tonA , Mini-F lacI q1 (Gent R ) Lucigen BL21(DE3) F – ompT gal dcm lon hsdS B ( r B – m B – ) λ(DE3 [ lacI lacUV5 - T7p07 ind1 sam7 nin5 ]) [ malB + ] K−12 (λ S ) Lab stock Plasmids pTrc99a pBR322 ori, Amp r (Amann et al. 1988) pTrc99a-HER2 pBR322 ori, Amp r , P trc :: scFv‑PE35KDEL This study Primers pTrc99a-HER2F CATCACAAGGATGAGCTTTAAGGCTGTTTTGGCGGATGAGAG This study pTrc99a-HER2R TTCCACTAACTGTACTTCCATTTATTCTTCCTCCTTTTTAAAGTTAATGCTAGC This study The synthetic gene of scFv‑PE35KDEL encoding anti-HER2 immunotoxin (GenBank accession number: PP759094) was codon-optimized and synthesized by Integrated DNA Technologies (Coralville, IA, USA) in two fragments with 21 bp overlap. These two DNA fragments were Gibson–assembled with the PCR-linearized pTrc99a as the backbone, which was amplified using the primer set pTrc99a-HER2F/pTrc99a-HER2R. It is noteworthy that the original ribosome-binding site (RBS) in pTrc99a was substituted with a strong RBS sequence, AAGGAG. Additionally, transcription of the clone synthetic gene was under the regulation of the trc promoter (Supplementary Fig. 1). Characterization of expression of anti-HER2 immunotoxin in E. coli The overnight-grown seed culture of BL21(DE3) harboring pTrc99a-HER2 was transferred to fresh LB medium with an inoculation ratio of 10% v/v. The resulting culture was kept at 37 ºC until reaching the logarithmic phase. Then, the protein expression was induced by adding 1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) with subsequent incubation at 180 rpm at 37 ºC for 3 h (Malekian et al. 2019). Experimental design for bacterial expression and analysis of recombinant immunotoxin A three-level four-factor Behnken experimental design was applied to statistically investigate the effects of four independent cultivation variables on the soluble expression of anti-HER2 immunotoxin in E. coli BL21(DE3). The input factors include IPTG concentration (0.1-1 mM), post-induction time (2–18 h), post-induction temperature (23–37 ºC), and medium recipe (LB, 2 X YT, and TB), whereas the factor levels were coded as − 1 (low), 0 (central point), and 1 (high) (Table 2 ). As a result, 45 cultivations were conducted in parallel (Table 3 ). Data analysis of the experimental design was carried out using the Design Expert software (version 13.0.5.0, StatEase Inc., Minneapolis, USA). Table 2 The variables and their levels used in the experimental design. Symbol Variable Levels Unit -1 0 1 A Post-induction Time 2 10 18 h B Post-induction temperature 23 30 37 °C C IPTG concentration 0.1 0.55 1 mM D Culture medium LB 2xYT TB - Table 3 Box–Behnken experimental design of 4 factors in 3 levels Run A (h) B (°C) C (mM) D Response (soluble immunotoxon (µg/ml) 1 10 23 0.1 2xYT 200.919 2 10 37 0.1 2xYT 63.93 3 10 30 0.55 TB 166.499 4 10 30 0.55 LB 199.62 5 18 30 1 LB 98.123 6 10 23 0.1 LB 234.928 7 10 30 0.55 LB 185 8 18 37 0.55 TB 178.667 9 18 30 1 TB 196.321 10 18 23 0.55 2xYT 205 11 10 30 0.55 2xYT 191.914 12 2 30 0.1 TB 155.118 13 10 30 0.55 2xYT 173 14 2 30 1 LB 85 15 18 30 1 2xYT 223.746 16 2 30 1 TB 80.921 17 18 30 0.1 2xYT 167.631 18 18 30 0.1 LB 259.535 19 10 30 0.55 LB 172.212 20 2 37 0.55 2xYT 22.418 21 18 23 0.55 LB 120 22 18 23 0.55 TB 80 23 2 23 0.55 2xYT 114.134 24 2 30 1 2xYT 70.324 25 10 37 1 LB 108.271 26 10 37 1 2xYT 115.249 27 2 37 0.55 TB 40.554 28 10 30 0.55 2xYT 180 29 10 30 0.55 TB 178 30 2 23 0.55 LB 170.671 31 10 37 1 TB 97.654 32 18 37 0.55 2xYT 174.668 33 10 37 0.1 LB 173.21 34 10 23 1 LB 136.384 35 2 37 0.55 LB 65.743 36 10 23 1 TB 72.028 37 2 23 0.55 TB 180.922 38 10 23 1 2xYT 83.217 39 2 30 0.1 LB 161.417 40 2 30 0.1 2xYT 152 41 10 23 0.1 TB 152.623 42 10 30 0.55 TB 156 43 18 37 0.55 LB 190.667 44 10 37 0.1 TB 76.923 45 18 30 0.1 TB 63.756 After protein expression for each cultivation, bacterial cells were collected by centrifugation at 3,500 g for 20 min, and the resulting cell pellet was resuspended in phosphate-buffered saline (PBS). For cell disruption, the suspension was sonicated for five cycles of 1 min with an interval of 1 min on ice between cycles. The soluble and insoluble fractions of the cell were separated using centrifugation at 7,500 g and 4°C for 15 min. To evaluate the expression level and solubility of the expressed anti-HER2 immunotoxin, the soluble fraction of the sonicated culture sample was analyzed using a 12% (w/v) sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The intensity of the corresponding band was assessed by Gel Analyzer 19.1 software (Lazar Software, Hungary). The soluble fraction of the culture sample was used to purify anti-HER2 immunotoxin using affinity chromatography under native conditions, as described in our previous study with some modifications (Akbari et al. 2015). The protein concentration in each purification fraction was determined using the Bradford method (Malekian, Sima et al. 2019). Biological activity of anti-HER2 immunotoxin through cell-based ELISA To evaluate the bioactivity of the purified anti-HER2 immunotoxin, two cancer cell lines, i.e. , the HER2-overexpressing cell line of SK-OV-3 and the HER2-low-expressing cell of MCF-7, were seeded in a 96-well ELISA plate at a cell density of 2 × 10 5 cells/ml and 37 ºC overnight. The cells were rinsed with PBS and then immobilized with 4% formalin buffer for 20 min. After that, the plate was washed thrice with PBS and then treated with 1% bovine serum albumin in PBS for 2 h at the room temperature. Then, samples containing anti-HER2 immunotoxin in a serial dilution were added to individual wells and incubated for 2 h at 25 ºC with gentle shaking. Each well was rinsed for three times with 0.05% Tween 20 in PBS. HRP-conjugated anti-His antibody (1: 50,000 dilution) was added to each well for incubation for 2 h at the room temperature with gentle shaking. After washing three times, OPD substrate was added to each well for incubation for 20 min. The colorimetric reaction was terminated using 2M H 2 SO 4 , and the absorbance was measured at 450 and 490 nm (Akbari et al. 2014). Results Small-scale expression of anti-HER2 immunotoxin E. coli BL21 (DE3) harboring pTrc99a-HER2 was used to express anti-HER2 immunotoxin while being cultivated at 37 ºC in LB medium for 3 h with a general induction condition at 1 mM IPTG. SDS-PAGE analysis suggested that the full-length immunotoxin was successfully expressed with an envisioned molecular weight of ~ 62 kDa (Fig. 1 A). However, most of the expressed immunotoxin appeared to be in the insoluble fraction as inclusion bodies (data not shown). The results nevertheless confirmed the proper design of the expression plasmid and the expression strategy. Correlation of cultivation conditions using the RSM The effect of the four operating factors ( i.e. , inducer concentration, temperature, induction timing, and medium composition) of the cultivation on the soluble expression of anti-HER2 immunotoxin was characterized using RSM. A total of 45 cultivations was conducted simultaneously, with soluble expression of anti-HER2 immunotoxin ranging between 22.4 and 260 µg/ml (Table 3 ). The results suggest the potential importance of optimization of cultivation conditions. To assess the experimental error and model reproducibility, cultivation was further carried out in triplicate under three central point conditions ( i.e ., 0.55 mM IPTG, 10 h post-induction time, and 30°C in the culture medium of LB (runs 4, 7, and 19), 2xYT ( 11 , 13 , and 28 ) or TB ( 3 , 29 , and 42 )). The anti-HER2 immunotoxin concentrations were determined to be 184 ± 14, 182 ± 10 and 167 ± 1 µg/ml, respectively, with the coefficient of variation ( i.e. , standard deviation/mean×100%) being less than 7.68, 5.26 and 6.59%, for LB, 2xYT, and TB cultures, respectively (Table 3 ). The data of anti-HER2 immunotoxin concentrations obtained from the 45 experiments (Table 3 ) were further analyzed by the Design Expert software (Akbari et al. 2015). Correlation between the level of soluble anti-HER2 immunotoxin expression in each medium culture and the three independent variables was formulated based on the following quadratic equations: Soluble anti-HER2 immunotoxin expression in LB medium (µg/ml) = 141 − 7.84 A + 10.9 B − 110 C + 0.784 AB − 5.90 AC + 2.67 BC − 0.477 A² − 0.374 B² − 20.2 C² Soluble anti-HER2 immunotoxin expression in 2xYT medium (µg/ml) = -261.769 -4.702A + 41.040B -411.109C + 0.274AB + 9.569AC + 13.414BC-0.117A² -0.920B² -102.318C² Soluble anti-HER2 immunotoxin expression in TB medium (µg/ml) = -21.522 -35.427A + 26.748B -214.053C + 1.067AB + 14.358AC + 8.042BC -0.176A -0.725B² -155.636C² The fitting quality of the quadratic model was determined using analysis of variance (ANOVA) and the P values were applied to evaluate the significance of each coefficient (Table 4 ). The correlation coefficient (R²) of the model was 0.993, suggesting that the model could cover and predict 99.3% of the variation in the response. The F-value of 14.7 with a low probability value (P < 0.0001) indicates that the model is significant in terms of predicting soluble expression of anti-HER2 immunotoxin based on cultivation of the engineered E. coli . On the other hand, the lack of fit for the model was insignificant (P > 0.05) with an F value of 3.79, suggesting that there could be a 8.03% probability for a Lack of Fit F-value to appear as a result of the noise. The results indicate that the model could fit the experimental data properly. Table 4 ANOVA results for response surface quadratic model Source Sum of Squares Df Mean Square F-value p-value Model 1.36E + 05 29 4674.13 14.74 < 0.0001 significant A-Time 18089.11 1 18089.11 57.03 < 0.0001 significant B-Temp 8172.32 1 8172.32 25.77 0.0001 significant C-Conc 10199.15 1 10199.15 32.16 < 0.0001 significant D-Culture 7851.57 2 3925.79 12.38 0.0007 significant AB 18882.44 1 18882.44 59.54 < 0.0001 significant AC 5614.2 1 5614.2 17.7 0.0008 significant AD 7915.93 2 3957.96 12.48 0.0006 significant BC 7698.9 1 7698.9 24.27 0.0002 significant BD 1246.78 2 623.39 1.97 0.1745 Not significant CD 10989.26 2 5494.63 17.32 0.0001 significant A² 2990.26 1 2990.26 9.43 0.0078 significant B² 12045.68 1 12045.68 37.98 < 0.0001 significant C² 3903.63 1 3903.63 12.31 0.0032 significant ABD 4052.39 2 2026.19 6.39 0.0098 significant ACD 11626.06 2 5813.03 18.33 < 0.0001 significant BCD 2292.19 2 1146.09 3.61 0.0524 not significant A²D 1124.51 2 562.25 1.77 0.2036 not significant B²D 1357.49 2 678.75 2.14 0.1522 not significant C²D 1410.5 2 705.25 2.22 0.1426 not significant Residual 4757.38 15 317.16 Lack of Fit 3956.16 9 439.57 3.29 0.0803 not significant Pure Error 801.22 6 133.54 Cor Total 1.40E + 05 44 Evaluation of the effects of cultivation variables for optimization As illustrated in Table 4 , the effects of all four cultivation parameters on soluble expression of anti-HER2 immunotoxin were significant though the culture medium (D) had a less significant effect. Additionally, the interaction terms of AB, AC, AD, BC, and CD were shown to have a significant impact on the soluble expression of anti-HER2 immunotoxin (P < 0.05), suggesting their potential combinatory effects on the cultivation performance. However, the interaction of post-induction time and culture medium (BD) was insignificant. Moreover, A², B², C², ABD, and ACD are other significant model terms. The effects of three variables ( i.e. , IPTG concentration, post-induction time, and post-induction temperature) and their interactions and effects on the soluble expression of anti-HER2 immunotoxin in the LB culture ( i.e. , the optimal medium) were graphically shown in the 3-dimensional response surface plots (Fig. 1 ). Figure 1 B shows the response surface plot associated with the interaction and effects of post-induction time and post-induction temperature on the soluble expression of anti-HER2 immunotoxin when the IPTG concentration was maintained at its basal level (0.55 mM). Clearly, soluble expression of the protein was enhanced with increasing time and temperature. As presented in Fig. 1 C, soluble expression of anti-HER2 immunotoxin increases remarkably with increasing time and decreasing inducer concentration when the post-induction temperature was 30 ºC. Figure 1 D further shows the response surface plot of the effects of post-induction temperature and IPTG concentration on soluble expression of the protein when the post-induction time was 10 h. Clearly, soluble expression of the protein was enhanced with decreasing IPTG concentration and temperature. The studentized residuals provide the range of standard deviations associated with the difference between the actual and predicted values. As shown in Fig. 2 A, the plot of normal probability for soluble expression of anti-HER2 immunotoxin shows a normal and linear distribution. Figure 2 B further shows that the actual and predicted levels for soluble expression of anti-HER2 immunotoxin are in reasonable agreement. Additionally, the plot of residuals versus the experimental runs remains within the boundaries specified in Fig. 2 C. These statistical analyses collectively indicate that all data points follow a normal pattern and that the established model is adequate for the prediction of the cultivation performance for soluble expression of anti-HER2 immunotoxin. Finally, according to the model, the optimal solution with the highest soluble expression of the protein (261 µg/ml) would be achieved with 0.1 mM IPTG in LB medium culture at 33°C for 18 h. In average, 272 ± 7.3 µg/ml of soluble anti-HER2 immunotoxin was expressed and this level was rather close to the predicted optimum (Fig. 3 A). Purification and evaluation of the biological activity of anti-HER 2 immunotoxin After the cultivation for the expression of anti-HER2 immunotoxin under the optimal condition, the fusion protein was successfully purified by affinity chromatography using a Ni-NTA column under native conditions (Fig. 3 B). Out of the 1-L of bacterial culture, approximately 27.2 mg of anti-HER2 immunotoxin (340 µg/ml) was recovered, and the purity was determined to be 90%. Using this purified protein, the biological activity was further evaluated using an ELISA assay. As shown in Fig. 4 , the attachment of anti-HER2 immunotoxin to SK-OV-3 cells (HER2-ovrexprssing cell line) was successfully demonstrated in a dose-dependent manner. Discussion Our previous study demonstrated that anti-HER2 immunotoxin could act as a promising candidate for HER2-targetd cancer therapy (North et al. 2005). However, large-scale production of this immunotoxin was limited by the accumulation of insoluble inclusion bodies upon cultivation of the engineered E. coli strain with a transformed immunotoxin-encoded gene whose expression was regulated by the T7 promoter. One approach to enhance soluble expression of recombinant proteins is to modulate, not necessarily increase, promoter strength. In the present study, we demonstrated that proper integration of the genetic ( i.e. , using the trc promoter to replace the T7 one) and bioprocessing ( i.e. , optimization of cultivation conditions) strategies can potentially lead to a remarkable cultivation performance for more soluble expression of the recombinant anti-HER2 immunotoxin. Tegel et al . evaluated the effects of three different IPTG-inducible promoters ( i.e. , T7, trc , and lac UV5) for expression of seventeen fusion proteins in E. coli (Tegel et al. 2011). They observed that the use of the most potent promoter ( i.e. , T7 with the highest promoter strength) often led to an ineffective protein production with a low soluble fraction. Furthermore, such technical issue could be partially alleviated based on the use of the trc or T7 promoter in combination with E. coli Rosetta (DE3) as the expression host, resulting in a higher quantity of soluble protein. Balzer et al . compared three different promoter systems (LacI/ P T7la c , LacI/ P trc , AraC/ P BAD ) for regulated expression of five genes (Balzer et al. 2013). It was observed that the LacI/ P T7lac system, while generating a high-level of mRNA transcript, produced the highest amount of insoluble protein. They also observed that the LacI/ P trc system had a more effective initiation upon protein expression with a more homogeneous protein expression profile. Cultivation condition can potentially influence both the expression and solubility of recombinant proteins and, therefore, should be properly evaluated. The use of statistical design enables not only determination of the optimal culture condition but also characterization of the interactions amongst numerous experimental parameters and operating variables (Behravan et al. 2021). In this study, we specifically apply RSM to optimize the cultivation performance for soluble expression of anti-HER2 immunotoxin under the regulation of the trc promoter in E. coli and we also demonstrated satisfactory predictability based on the established model. Similar application of RSM for optimization of recombinant protein production was previously reported (Shafiee et al. 2017). For example, Shafiee et al . applied RSM to optimize the expression of recombinant DT386-BR2 in E. coli Rosetta (DE3). They reported that the induction with 1 mM IPTG for 2 h at 37°C would result in higher total protein expression of the immunotoxin (Shafiee, Rabbani et al. 2017). All these reports suggest the importance of induction mechanism for bacterial expression of recombinant immunotoxin. Medium composition could have remarkable metabolic effects on cell growth and gene expression upon conducting E. coli cultivation (Kram et al. 2015). It was previously observed that using the TB medium would result in more production of recombinant DT386-BR2, compared to LB and superbroth (SB) (Shafiee, Rabbani et al. 2017). On the other hand, Heydari et al. used the Taguchi method to optimize the medium composition, in particular carbon and nitrogen sources, for the expression of Denileukin diftitox in E. coli . While nutrient components with high energy and carbon levels could potentially enhance biomass production and recombinant protein expression, their effects on the soluble production of recombinant proteins have been controversial. Some studies showed that the use of culture medium with higher yeast extract and tryptone contents could result in more soluble expression of the target protein (Kanno et al. 2019, Aghdam et al. 2022), while others found the opposite (Kim et al. 2017). Kanno et al. reported that the use of enriched media, such as TB, potentially resulted in more soluble expression of recombinant Zika virus ΔNS1 in E. coli (Aghdam, Tohidkia et al. 2022). Though we observed more soluble expression of anti-HER2 immunotoxin in E. coli grown in a less rich medium ( i.e. , LB medium), our current results are in agreement with the previous report comparing three media ( i.e. , LB, TB, 2xYT) for the expression of cis-aconitate decarboxylase in E. coli BL21(DE3) (Kim, Seo et al. 2017). Basically, Kim et al . reported that, though a higher cell density could be obtained in TB medium, more enzyme production with a higher yield was obtained in LB medium (Kim, Seo et al. 2017). This might be attributable to the metabolic load induced by enhanced cell growth that could promote the formation of inclusion bodies. Our finding showed that post-induction time was also critical for soluble expression of anti-HER2 immunotoxin, especially under a low IPTG induction concentration ( i.e. , 0.1 mM). Other researchers also manipulated the inducer concentration and induction timing to reduce metabolic load for the producing cells (Aghdam, Tohidkia et al. 2022). Reducing the metabolic stress based on the use of a low inducer concentration could potentially mediate a metabolic balance between cell growth and recombinant protein expression in E. coli , improving the solubility and folding of the recombinant protein (Papaneophytou et al. 2013). Cultivation temperature is one of the most important factors influencing the expression and solubility of recombinant proteins. While the optimal temperature for soluble expression of anti-HER2 immunotoxin was 33 ºC in this study, more soluble expression of recombinant proteins at a temperature around 30 ºC was observed previously (Mühlmann et al. 2017). It has been perceived that recombinant proteins produced at a low temperature might have higher solubility and bioactivity potentially because of more functional expression of molecular chaperones. However, such temperature effects may not always hold and should be further studied for different recombinant proteins. Some studies reported that higher temperatures promote soluble expression of recombinant proteins. In particular, Vincentelli et al . reported that recombinant protein expression at 37 ºC yielded more soluble protein than 25 ºC and 17 ºC (Vincentelli et al. 2011). Such controversy could be potentially associated with different recombinant protein properties, expression vectors, and expression hosts. In conclusion, RSM was successfully applied to optimize cultivation conditions for soluble expression of anti-HER2 immunotoxin under the regulation of the trc promoter in E. coli such that a sufficient amount of biologically active and soluble recombinant protein could be obtained for subsequent in vitro and in vivo trials. The results suggest that inducer concentration, medium recipe, post-induction temperature, and post-induction time have significant effects on the cultivation performance for soluble expression of anti-HER2 immunotoxin in E. coli . The optimal conditions were determined to be 0.1 mM IPTG for induction of gene expression at 33°C for 18 h in the LB medium. The approaches documented in this study can be generally applied to enhance the expression yield and solubility of recombinant proteins in E. coli . Declarations Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This study was financially supported by the Isfahan University of Medical Sciences (Grant No. 199495). Acknowledgment We are grateful to thank Mrs Fatemeh Moazen for her excellent technical assistance. Availability of data Data will be shared upon request. References Xing Y, Xu K, Li S, Cao L, Nan Y, Li Q, Li W, Hong Z. A single-domain antibody-based anti-PSMA recombinant immunotoxin exhibits specificity and efficacy for prostate cancer therapy. Int. J. Mol. Sci.2021 May 23;22(11):5501. Kim JS, Jun SY, Kim YS. Critical issues in the development of immunotoxins for anticancer therapy. J. Pharm. Sci. 2020 Jan 1;109(1):104-15. Akbari B, Farajnia S, Ahdi Khosroshahi S, Safari F, Yousefi M, Dariushnejad H, Rahbarnia L. Immunotoxins in cancer therapy: Review and update. Int. Rev. Immunol. 2017 Jul 4; 36(4):207-19. Hoffmann F, van den Heuvel J, Zidek N, Rinas U. Minimizing inclusion body formation during recombinant protein production in Escherichia coli at bench and pilot plant scale. Enzyme Microb. Technol. 2004 Mar 1;34(3-4):235-41. Sørensen HP, Mortensen KK: Soluble expression of recombinant proteins in the cytoplasm of Escherichia coli. Microb Cell Fact. 2005, 4(1):1–8. 10.1186/1475-2859-4-1. Rosano GL, Morales ES, Ceccarelli EA. New tools for recombinant protein production in Escherichia coli: A 5‐year update. Protein Sci. 2019 Aug; 28(8):1412-22. Samuelson JC. Recent developments in difficult protein expression: a guide to E. coli strains, promoters, and relevant host mutations. Heterologous Gene Expression in E. coli: Methods Protoc. 2011:195-209. Mayer MR, Dailey TA, Baucom CM, Supernak JL, Grady MC, Hawk HE, Dailey HA. Expression of human proteins at the Southeast Collaboratory for Structural Genomics. J. Struct. Funct.genomics. 2004 Mar;5:159-65. Baş D, Boyacı IH. Modeling and optimization I: Usability of response surface methodology. J Food Eng.2007;78(3):836-845. Bezerra MA, Santelli RE, Oliveira EP, Villar LS,Escaleira LA. Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta 2008;76(5):965-977. Araujo PW, Brereton RG. Experimental design III. Quantification. TrAC Trend Anal Chem. 1996 Mar 1;15(3):156-63. Lee KM, Rhee CH, Kang CK, Kim JH. Sequential and simultaneous statistical optimization by dynamic design of experiment for peptide overexpression in recombinant Escherichia coli. Appl. Biochem. Biotechnol. 2006 Oct;135:59-80. Liu N, Jiang J, Yan F, Xu Y, Yang M, Gao Y, et al. Optimization of simultaneous production of volatile fatty acids and bio-hydrogen from food waste using response surface methodology. RSC Adv.2018;8(19):10457- 10464. Shariaty Vaziri Z, Shafee F, Akbari V. Design and construction of scFv‑PE35KDEL as a novel immunotoxin against human epidermal growth factor receptor 2 for cancer therapy. Biotechnol Lett. 2023 Apr;45(4):537-50. Hofnung, M. A short course in bacterial genetics and a laboratory manual and handbook for Escherichia coli and related bacteria: edited by JH Miller, Cold Spring Harb. Perspect. Med. 1992, Lab man. p 456. Biochim. 1993 Jan 1;75(6):501. Gibson, D.G.; Young, L.; Chuang, R.-Y.; Venter, J.C.; Hutchison III, C.A.; Smith, H.O. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods. 2009, 6, 343-345. Amann, E.; Ochs, B.; Abel, K.-J. Tightly regulated tac promoter vectors useful for the expression of unfused and fused proteins in Escherichia coli. Gene. 1988, 69, 301-315. Malekian R, Sima S, Jahanian-Najafabadi A, Moazen F, Akbari V. Improvement of soluble expression of GM-CSF in the cytoplasm of Escherichia coli using chemical and molecular chaperones. Protein Expr Purif. 2019;160:66-72. Akbari V, Sadeghi HMM, Jafarian-Dehkordi A, Abedi D, Chou CP. Improved biological activity of a single chain antibody fragment against human epidermal growth factor receptor 2 (HER2) expressed in the periplasm of Escherichia coli. Protein Expr Purif. 2015;116:66-74. Akbari V, Mir Mohammad Sadeghi H, Jafrian-Dehkordi A, Abedi D, Chou CP. Functional expression of a single-chain antibody fragment against human epidermal growth factor receptor 2 (HER2) in Escherichia coli. J. Ind. Microbiol.. 2014;41(6):947-56. Akbari V, Sadeghi HM, Jafarian-Dehkordi A, Chou CP, Abedi D. Optimization of a single-chain antibody fragment overexpression in Escherichia coli using response surface methodology. Res Pharm Sci. 2015;10(1):75-83. North BJ, Schwer B, Ahuja N, Marshall B, Verdin E. Preparation of enzymatically active recombinant class III protein deacetylases. Methods. 2005 Aug 1;36(4):338-45. Tegel H, Ottosson J, Hober S. Enhancing the protein production levels in Escherichia coli with a strong promoter. FEBS J. 2011;278(5):729–739. Balzer S, Kucharova V, Megerle J, Lale R, Brautaset T, Valla S. A comparative analysis of the properties of regulated promoter systems commonly used for recombinant gene expression in Escherichia coli. Microb Cell Fact. 2013;12:26. Behravan A, Hashemi A. Statistical optimization of culture conditions for expression of recombinant humanized anti-EpCAM single-chain antibody using response surface methodology. Res Pharm Sci. 2021; 16(2):153-164. Shafiee F, Rabbani M, Jahanian-Najafabadi A. Optimization of the Expression of DT386-BR2 Fusion Protein in Escherichia coli using Response Surface Methodology. Adv Biomed Res. 2017; 6:22. Kram KE, Finkel SE. Rich Medium Composition Affects Escherichia coli Survival, Glycation, and Mutation Frequency during Long-Term Batch Culture. Appl Environ Microb. 2015; 81(13):4442-50. Heydari M, Robatjazi SM, Zeinoddini M, Darabi E. Optimization of chemically defined cell culture media for recombinant ONTAK immunotoxin production. IJMM. 2014;8(3):51-7. Aghdam MA, Tohidkia MR, Ghamghami E, Ahmadikhah A, Khanmahamadi M, Baradaran B, Mokhtarzadeh A. Implementation of a Design of Experiments to Improve Periplasmic Yield of Functional ScFv Antibodies in a Phage Display Platform. Adv. Pharm. Bull. 2022;12(3):583-592. Kanno AI, Leite LCC, Pereira LR, de Jesus MJR, Andreata-Santos R, Alves RPDS, Durigon EL, Ferreira LCS, Gonçalves VM. Optimization and scale-up production of Zika virus ΔNS1 in Escherichia coli: application of Response Surface Methodology. AMB Express. 2019; 10(1):1. Kim J, Seo HM, Bhatia SK, Song HS, Kim JH, Jeon JM, Choi KY, Kim W, Yoon JJ, Kim YG, Yang YH. Production of itaconate by whole-cell bioconversion of citrate mediated by expression of multiple cis-aconitate decarboxylase (cadA) genes in Escherichia coli. Sci Rep. 2017;7:39768. Zhang H, Zheng Y, Liu Q, Tao X, Zheng W, Ma X, et al. Development of a fed-batch process for the production of anticancer drug TATm-survivin(T34A) in Escherichia coli. Biochem Eng J. 2009; 43(2):163-8. Papaneophytou CP, Rinotas V, Douni E, Kontopidis G. A statistical approach for optimization of RANKL overexpression in Escherichia coli: purification and characterization of the protein. Protein Expr Purif. 2013;90(1):9-19. Mühlmann M, Forsten E, Noack S, Büchs J. Optimizing recombinant protein expression via automated induction profiling in microtiter plates at different temperatures. Microb Cell Fact. 2017;16(1):220. Vincentelli R, Cimino A, Geerlof A, Kubo A, Satou Y, Cambillau C. High-throughput protein expression screening and purification in Escherichia coli. Methods. 2011;55(1):65-72. "Araujo PW, Brereton RG. Experimental design III. Quantification. TrAC Trend Anal Chem. 1996 Mar 1;15(3):156-63.". "Baş D, Boyacı IH. Modeling and optimization I: Usability of response surface methodology. J Food Eng.2007;78(3):836-845.". "Heydari M, Robatjazi SM, Zeinoddini M, Darabi E. Optimization of chemically defined cell culture media for recombinant ONTAK immunotoxin production. IJMM. 2014;8(3):51-7.". "Hoffmann F, van den Heuvel J, Zidek N, Rinas U. Minimizing inclusion body formation during recombinant protein production in Escherichia coli at bench and pilot plant scale. Enzyme Microb. Technol. 2004 Mar 1;34(3-4):235-41.". "Sørensen HP, Mortensen KK: Soluble expression of recombinant proteins in the cytoplasm of Escherichia coli. Microb Cell Fact. 2005, 4(1):1–8. 10.1186/1475-2859-4-1.". "Zhang H, Zheng Y, Liu Q, Tao X, Zheng W, Ma X, et al. Development of a fed-batch process for the production of anticancer drug TATm-survivin(T34A) in Escherichia coli. Biochem Eng J. 2009; 43(2):163-8. ." Aghdam, M. A., M. R. Tohidkia, E. Ghamghami, A. Ahmadikhah, M. Khanmahamadi, B. Baradaran and A. Mokhtarzadeh (2022). "Implementation of a Design of Experiments to Improve Periplasmic Yield of Functional ScFv Antibodies in a Phage Display Platform." Advanced pharmaceutical bulletin 12 (3): 583-592. Akbari, B., S. Farajnia, S. Ahdi Khosroshahi, F. Safari, M. Yousefi, H. Dariushnejad and L. Rahbarnia (2017). "Immunotoxins in cancer therapy: Review and update." International reviews of immunology 36 (4): 207-219. Akbari, V., H. Mir Mohammad Sadeghi, A. Jafrian-Dehkordi, D. Abedi and C. P. Chou (2014). "Functional expression of a single-chain antibody fragment against human epidermal growth factor receptor 2 (HER2) in Escherichia coli." Journal of industrial microbiology & biotechnology 41 (6): 947-956. Akbari, V., H. M. Sadeghi, A. Jafarian-Dehkordi, D. Abedi and C. P. Chou (2015). "Improved biological activity of a single chain antibody fragment against human epidermal growth factor receptor 2 (HER2) expressed in the periplasm of Escherichia coli." Protein expression and purification 116 : 66-74. Akbari, V., H. M. Sadeghi, A. Jafarian-Dehkordi, C. P. Chou and D. Abedi (2015). "Optimization of a single-chain antibody fragment overexpression in Escherichia coli using response surface methodology." Research in pharmaceutical sciences 10 (1): 75-83. Amann, E., B. Ochs and K.-J. Abel (1988). "Tightly regulated tac promoter vectors useful for the expression of unfused and fused proteins in Escherichia coli." Gene 69 (2): 301-315. Balzer, S., V. Kucharova, J. Megerle, R. Lale, T. Brautaset and S. Valla (2013). "A comparative analysis of the properties of regulated promoter systems commonly used for recombinant gene expression in Escherichia coli." Microbial cell factories 12 : 26. Behravan, A. and A. Hashemi (2021). "Statistical optimization of culture conditions for expression of recombinant humanized anti-EpCAM single-chain antibody using response surface methodology." Research in pharmaceutical sciences 16 (2): 153-164. Bezerra, M. A., R. E. Santelli, E. P. Oliveira, L. S. Villar and L. A. Escaleira (2008). "Response surface methodology (RSM) as a tool for optimization in analytical chemistry." Talanta 76 (5): 965-977. Hofnung, M. (1993). "A short course in bacterial genetics and a laboratory manual and handbook for Escherichia coli and related bacteria: edited by JH Miller, Cold Spring Harbor Laboratory Press, 1992, Laboratory Manual, p 456." Biochimie 75 (6): 501. Kanno, A. I., L. C. C. Leite, L. R. Pereira, M. J. R. de Jesus, R. Andreata-Santos, R. Alves, E. L. Durigon, L. C. S. Ferreira and V. M. Gonçalves (2019). "Optimization and scale-up production of Zika virus ΔNS1 in Escherichia coli: application of Response Surface Methodology." AMB Express 10 (1): 1. Kim, J., H. M. Seo, S. K. Bhatia, H. S. Song, J. H. Kim, J. M. Jeon, K. Y. Choi, W. Kim, J. J. Yoon, Y. G. Kim and Y. H. Yang (2017). "Production of itaconate by whole-cell bioconversion of citrate mediated by expression of multiple cis-aconitate decarboxylase (cadA) genes in Escherichia coli." Scientific reports 7 : 39768. Kim, J. S., S. Y. Jun and Y. S. Kim (2020). "Critical Issues in the Development of Immunotoxins for Anticancer Therapy." Journal of pharmaceutical sciences 109 (1): 104-115. Kram, K. E. and S. E. Finkel (2015). "Rich Medium Composition Affects Escherichia coli Survival, Glycation, and Mutation Frequency during Long-Term Batch Culture." Applied and environmental microbiology 81 (13): 4442-4450. Lee, K. M., C. H. Rhee, C. K. Kang and J. H. Kim (2006). "Sequential and simultaneous statistical optimization by dynamic design of experiment for peptide overexpression in recombinant Escherichia coli." Applied biochemistry and biotechnology 135 (1): 59-80. Liu, N., J. Jiang, F. Yan, Y. Xu, M. Yang, Y. Gao, A. Aihemaiti and Q. Zou (2018). "Optimization of simultaneous production of volatile fatty acids and bio-hydrogen from food waste using response surface methodology." RSC advances 8 (19): 10457-10464. Malekian, R., S. Sima, A. Jahanian-Najafabadi, F. Moazen and V. Akbari (2019). "Improvement of soluble expression of GM-CSF in the cytoplasm of Escherichia coli using chemical and molecular chaperones." Protein expression and purification 160 : 66-72. Mayer, M. R., T. A. Dailey, C. M. Baucom, J. L. Supernak, M. C. Grady, H. E. Hawk and H. A. Dailey (2004). "Expression of human proteins at the Southeast Collaboratory for Structural Genomics." Journal of structural and functional genomics 5 (1-2): 159-165. Mühlmann, M., E. Forsten, S. Noack and J. Büchs (2017). "Optimizing recombinant protein expression via automated induction profiling in microtiter plates at different temperatures." Microbial cell factories 16 (1): 220. North, B. J., B. Schwer, N. Ahuja, B. Marshall and E. Verdin (2005). "Preparation of enzymatically active recombinant class III protein deacetylases." Methods (San Diego, Calif.) 36 (4): 338-345. Papaneophytou, C. P., V. Rinotas, E. Douni and G. Kontopidis (2013). "A statistical approach for optimization of RANKL overexpression in Escherichia coli: purification and characterization of the protein." Protein expression and purification 90 (1): 9-19. Rosano, G. L., E. S. Morales and E. A. Ceccarelli (2019). "New tools for recombinant protein production in Escherichia coli: A 5-year update." Protein science : a publication of the Protein Society 28 (8): 1412-1422. Samuelson, J. C. (2011). "Recent developments in difficult protein expression: a guide to E. coli strains, promoters, and relevant host mutations." Methods in molecular biology (Clifton, N.J.) 705 : 195-209. Shafiee, F., M. Rabbani and A. Jahanian-Najafabadi (2017). "Optimization of the Expression of DT386-BR2 Fusion Protein in Escherichia coli using Response Surface Methodology." Advanced biomedical research 6 : 22. Shariaty Vaziri, Z., F. Shafiee and V. Akbari (2023). "Design and construction of scFv-PE35KDEL as a novel immunotoxin against human epidermal growth factor receptor 2 for cancer therapy." Biotechnology letters 45 (4): 537-550. Tegel, H., J. Ottosson and S. Hober (2011). "Enhancing the protein production levels in Escherichia coli with a strong promoter." The FEBS journal 278 (5): 729-739. Vincentelli, R., A. Cimino, A. Geerlof, A. Kubo, Y. Satou and C. Cambillau (2011). "High-throughput protein expression screening and purification in Escherichia coli." Methods (San Diego, Calif.) 55 (1): 65-72. Xing, Y., K. Xu, S. Li, L. Cao, Y. Nan, Q. Li, W. Li and Z. Hong (2021). "A Single-Domain Antibody-Based Anti-PSMA Recombinant Immunotoxin Exhibits Specificity and Efficacy for Prostate Cancer Therapy." International journal of molecular sciences 22 (11). Supplementary Files supplimetary.plasmidmap.png Cite Share Download PDF Status: Published Journal Publication published 28 Sep, 2024 Read the published version in AMB Express → Version 1 posted Reviewers agreed at journal 18 May, 2024 Reviewers invited by journal 14 May, 2024 Editor assigned by journal 07 May, 2024 First submitted to journal 06 May, 2024 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-4155503","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":302272601,"identity":"f5c54e24-058b-4a7e-b402-699ddfb99ee9","order_by":0,"name":"Sheida Mani","email":"","orcid":"","institution":"Isfahan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sheida","middleName":"","lastName":"Mani","suffix":""},{"id":302272602,"identity":"5df0c40e-3777-4bb8-941b-5cb7d208e493","order_by":1,"name":"Bahareh Arab","email":"","orcid":"","institution":"University of Waterloo","correspondingAuthor":false,"prefix":"","firstName":"Bahareh","middleName":"","lastName":"Arab","suffix":""},{"id":302272603,"identity":"c9621b75-2f43-4215-96de-600f1628d539","order_by":2,"name":"Vajihe Akbari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYHACZmYgwcPPwAPjg0kJwlokG0jVwmBwgAefIiRgcID5sXFBzT0Z49u9Bz9X5jBEGxxnYPzwg8EiH7cWNuPkGceKeczunEuWPLuNIXfDYQZmyR4GCcsGHFokGxiMD/OwJfCY3cgxkGyEaGGQBvrFAJctkg3snw/z/EvgMZ6RY/wTqoX5Nz4twLA1TuZtS+AxkMgxg9nChtcWoJZi45l9CTwSd86YWTZuk8ideZixzbLHALcWNgb2zdIF3xLs+Wf3GN9s3GaT23f+8OEbPyrqcGphkH8AZUjAScYGYEji1IAE8Eb3KBgFo2AUjGgAAD0MSP6Kb6BAAAAAAElFTkSuQmCC","orcid":"","institution":"Isfahan University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Vajihe","middleName":"","lastName":"Akbari","suffix":""},{"id":302272604,"identity":"795cbf6b-77ab-43e9-81c1-3b7dbe780980","order_by":3,"name":"C. Perry Chou","email":"","orcid":"","institution":"University of Waterloo","correspondingAuthor":false,"prefix":"","firstName":"C.","middleName":"Perry","lastName":"Chou","suffix":""}],"badges":[],"createdAt":"2024-03-23 18:35:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4155503/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4155503/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13568-024-01765-6","type":"published","date":"2024-09-28T15:57:23+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57012450,"identity":"3c3157de-938f-4aa7-a969-c5e9ccfc3d21","added_by":"auto","created_at":"2024-05-23 11:46:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":480697,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e SDS-PAGE analysis of total protein from transformed \u003cem\u003eEscherichia coli\u003c/em\u003e BL21(DE3) with scFv‑PE35KDEL-pTrc99a (lane 1) and \u003cem\u003eE. coli\u003c/em\u003e non-transformed (lane 2) after induction with 1 mM IPTG at 37 ºC in LB medium for 3 h. M: protein marker (PM1500, SMOBIO). The arrow indicates the band of interest. \u003cstrong\u003e(B-D)\u003c/strong\u003e 3D response surface plot representing the interaction between two variables on the soluble expression of anti-HER2 immunotoxin. Each plot shows interactions of two tested variables with another one kept at its zero level and D (medium culture) was LB. \u003cstrong\u003e(B) \u003c/strong\u003eInteraction between post-induction time and post-induction temperature, \u003cstrong\u003e(C)\u003c/strong\u003e interaction between post-induction time and IPTG concentration, and \u003cstrong\u003e(D)\u003c/strong\u003e interaction between post-induction temperature and IPTG concentration.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4155503/v1/e0f71570c1c41c0ee2ef6b42.png"},{"id":57012452,"identity":"a3519839-cf40-4378-abc9-d3603552518b","added_by":"auto","created_at":"2024-05-23 11:46:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":155781,"visible":true,"origin":"","legend":"\u003cp\u003eNormal (%) probability plot of the ‘studentized’ residuals \u003cstrong\u003e(A), \u003c/strong\u003elinear regression plot for the relationship between the predicted and actual values \u003cstrong\u003e(B)\u003c/strong\u003eand the residuals versus run number plot \u003cstrong\u003e(C)\u003c/strong\u003e for the model of soluble expression of anti-HER2 immunotoxin.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4155503/v1/e9335d763acc0bb47fde9f4f.png"},{"id":57012449,"identity":"2739c208-2e25-468a-b83f-dcbc259cff6b","added_by":"auto","created_at":"2024-05-23 11:46:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":434968,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eSDS-PAGE analysis of soluble protein fraction from three repeats (lane 1-3) of experiments under the optimum conditions; M: protein marker (PM1500, SMOBIO). The arrow indicates the band of interest. \u003cstrong\u003e(B) \u003c/strong\u003eSDS–PAGE analysis of the purified anti-HER2 immunotoxin using a Ni–NTA column under native conditions. Lane 1: soluble fraction before loading onto the column; lane 2-5: resin wash with 20 mM imidazole; lane 6-8: resin wash with 40 mM imidazole; lane 9: eluted fraction with 100 mM imidazole; lane 10: eluted fraction with 200 mM imidazole; lane 11: eluted fraction with 400 mM imidazole; lane 12: eluted fraction with 600 mM imidazole; M: protein marker (PM1500, SMOBIO). The arrow indicates the band of interest.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4155503/v1/03dd3f3b6154addd9ad76e64.png"},{"id":57013051,"identity":"a540e34c-5437-43e4-b9c2-e08edf02203e","added_by":"auto","created_at":"2024-05-23 11:54:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":23168,"visible":true,"origin":"","legend":"\u003cp\u003eBinding assay of anti-HER2 immunotoxin to SK-OV-3 and MCF-7 cells using ELISA. Asterisks show the means which were significantly different (P\u0026lt;0.05) from cells treated without the immunotoxin (negative control).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4155503/v1/995e8795c40992ece573a6bf.png"},{"id":65627211,"identity":"3020292b-5c56-4201-bdc7-4a106dc18441","added_by":"auto","created_at":"2024-09-30 16:13:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2421864,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4155503/v1/b354a8c9-771f-4f92-9436-43dff4703d09.pdf"},{"id":57012454,"identity":"3421462b-59a3-48c3-9cab-2023a66e7b22","added_by":"auto","created_at":"2024-05-23 11:46:58","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":366262,"visible":true,"origin":"","legend":"","description":"","filename":"supplimetary.plasmidmap.png","url":"https://assets-eu.researchsquare.com/files/rs-4155503/v1/4e79f0d53a2f9fce9a806fc8.png"}],"financialInterests":"","formattedTitle":"Integrated bioprocessing and genetic strategies to enhance soluble expression of anti-HER2 immunotoxin in E. coli","fulltext":[{"header":"Introduction","content":"\u003cp\u003eImmunotoxins are protein molecules widely used for cancer therapy these days (Xing et al. 2021). Successful biological action of immunotoxins relies on their effective attachment to the target cell and subsequent translocation of the toxin's bioactive fragment into the cytosol of the target cell. Because of their high cytotoxicity and potential inhibition of protein synthesis in eukaryotic cells, immunotoxins are often expressed in bacterial hosts for subsequent medical administration.\u003c/p\u003e \u003cp\u003eExpression of immunotoxins in \u003cem\u003eE. coli\u003c/em\u003e usually leads to the formation and accumulation of insoluble aggregates with no biological function, \u003cem\u003ei.e.\u003c/em\u003e, inclusion bodies (Akbari et al. 2017, Kim et al. 2020). This presents a major technological challenge that requires a laborious and time-consuming process for protein refolding. The retrieval of soluble proteins from pre-existing inclusion bodies frequently results in reduced protein yield and biological activity, substantially increasing the production expenses associated with downstream separation processing. Alternatively, the soluble expression of foreign proteins in \u003cem\u003eE. coli\u003c/em\u003e can be enhanced by the following bioprocessing and/or genetic strategies, including modulation and optimization of cultivation conditions (\u003cem\u003ee.g.\u003c/em\u003e, temperature, medium composition, and aeration, etc.), co-expression with chaperons, genetic modification of host strains, and modifying the level of inducer and the promoter strength (Rosano et al. 2019).\u003c/p\u003e \u003cp\u003eDifferent promoters have been genetically explored for heterologous gene expression in \u003cem\u003eE. coli\u003c/em\u003e. Among them, the T7 promoter appears to be stronger than the common promoters, such as \u003cem\u003etac, lac\u003c/em\u003e, and \u003cem\u003etrp\u003c/em\u003e (Rosano, Morales et al. 2019). Although the T7 promoter is widely used to produce recombinant proteins, it usually leads to the formation of inclusion bodies. On the other hand, the \u003cem\u003etrc\u003c/em\u003e promoter, a hybrid fusion of the \u003cem\u003elac\u003c/em\u003e and \u003cem\u003etrp\u003c/em\u003e promoters, offers more robust regulatory capabilities and higher promoter strength than the native \u003cem\u003elac\u003c/em\u003e promoter (Samuelson 2011). Previous studies (Mayer et al. 2004) demonstrated that the \u003cem\u003etrc\u003c/em\u003e promoter, though exhibiting a lower promoter strength compared to the T7 one, can potentially generate a higher quantity of soluble recombinant protein. Mayer and coworkers reported that, upon the overproduction of human proteins for X-ray crystallography and NMR studies, incorporating the \u003cem\u003etrc\u003c/em\u003e promoter, instead of the T7 promoter, with proper optimization of culture conditions can effectively increase the solubility and yield of the heterologous proteins (Mayer, Dailey et al. 2004). Therefore, proper integration of genetic and bioprocessing strategies appears to be crucial for more efficient soluble expression of recombinant proteins.\u003c/p\u003e \u003cp\u003eTraditionally, optimizing cultivation conditions for recombinant protein expression involves altering one variable at a time (Bezerra et al. 2008). However, this approach is not only time-consuming but also leads to misinterpretation of results due to potential uncharacterized interactions among different variables. Several alternative methods exist to analyze multiple variables simultaneously, such as full factorial and fractional factorial design (Lee et al. 2006). Response Surface Methodology (RSM) is a suitable approach for effectively determining the interactions among experimental/operating variables, resulting in more reliable prediction of the optimal conditions (Liu et al. 2018).\u003c/p\u003e \u003cp\u003eIn our previous study (Shariaty Vaziri et al. 2023), we developed a novel anti-HER2 immunotoxin containing a modified \u003cem\u003ePseudomonas\u003c/em\u003e toxin (PE35KDEL). This fusion protein (\u003cem\u003ei.e.\u003c/em\u003e, scFv‑PE35KDEL) was expressed using the pET28a vector containing the T7 promoter, resulting in significant formation of inclusion bodies with only 10% of the resulting proteins being soluble. Adjusting the culture conditions (\u003cem\u003ee.g.\u003c/em\u003e, temperature and inducer concentration) barely improved the soluble expression of the recombinant protein (Shariaty Vaziri, Shafiee et al. 2023). In the current study, the immunotoxin was expressed under the regulation of the \u003cem\u003etrc\u003c/em\u003e promoter. To improve the soluble expression of this immunotoxin, the cultivation conditions, such as inducer concentration, culture temperature, growth medium, and induction timing were optimized using Box\u0026ndash;Behnken design with RSM.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eBacterial strains, plasmids, and oligonucleotides\u003c/h2\u003e \u003cp\u003eA list of bacterial strains, plasmids, and oligonucleotides used in this study is provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Standard recombinant DNA technologies were applied for molecular cloning (Hofnung 1993). Phusion HF was obtained from New England Biolabs (Ipswich, MA, USA). All synthesized oligonucleotides and gBlocks were obtained from Integrated DNA Technologies (Coralville, IA, USA). \u003cem\u003eE. coli\u003c/em\u003e HI-Control 10G chemically competent cell (Lucigen, Middleton, WI, USA) was used as the host for plasmid cloning and propagation. \u003cem\u003eE. coli\u003c/em\u003e BL21(DE3) was used as the expression host to produce recombinant anti-HER2 immunotoxin.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBacterial strains, plasmids, and primers used in this study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription or relevant genotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e host strains\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHI-Control 10G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003emcrA\u003c/em\u003e, ∆(\u003cem\u003emrr-hsdRMS-mcrBC\u003c/em\u003e), \u003cem\u003eendA1, recA1, ϕ\u003c/em\u003e80\u003cem\u003edlacZ\u003c/em\u003e∆M15, ∆\u003cem\u003elacX74, araD139\u003c/em\u003e, ∆(\u003cem\u003eara leu\u003c/em\u003e)\u003cem\u003e7697, galU, galK, rpsL\u003c/em\u003e (Str\u003csup\u003eR\u003c/sup\u003e), \u003cem\u003enupG, λ\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003etonA\u003c/em\u003e, Mini-F \u003cem\u003elacI\u003c/em\u003e\u003csup\u003eq1\u003c/sup\u003e (Gent\u003csup\u003eR\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLucigen\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBL21(DE3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003csup\u003e\u0026ndash;\u003c/sup\u003e\u0026nbsp;\u003cem\u003eompT\u0026nbsp;gal\u0026nbsp;dcm\u0026nbsp;lon\u0026nbsp;hsdS\u003c/em\u003e\u003csub\u003e\u003cem\u003eB\u003c/em\u003e\u003c/sub\u003e(\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003eB\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u0026ndash;\u003c/sup\u003e\u003cem\u003em\u003c/em\u003e\u003csub\u003e\u003cem\u003eB\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u0026ndash;\u003c/sup\u003e) λ(DE3 [\u003cem\u003elacI\u0026nbsp;lacUV5\u003c/em\u003e-\u003cem\u003eT7p07\u0026nbsp;ind1\u0026nbsp;sam7\u0026nbsp;nin5\u003c/em\u003e]) [\u003cem\u003emalB\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003eK\u0026minus;12\u003c/sub\u003e(λ\u003csup\u003eS\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLab stock\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlasmids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epTrc99a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epBR322 ori, Amp\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Amann et al. 1988)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epTrc99a-HER2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epBR322 ori, Amp\u003csup\u003er\u003c/sup\u003e, P\u003csub\u003e\u003cem\u003etrc\u003c/em\u003e\u003c/sub\u003e:: scFv‑PE35KDEL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epTrc99a-HER2F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCATCACAAGGATGAGCTTTAAGGCTGTTTTGGCGGATGAGAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epTrc99a-HER2R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTTCCACTAACTGTACTTCCATTTATTCTTCCTCCTTTTTAAAGTTAATGCTAGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe synthetic gene of scFv‑PE35KDEL encoding anti-HER2 immunotoxin (GenBank accession number: PP759094) was codon-optimized and synthesized by Integrated DNA Technologies (Coralville, IA, USA) in two fragments with 21 bp overlap. These two DNA fragments were Gibson\u0026ndash;assembled with the PCR-linearized pTrc99a as the backbone, which was amplified using the primer set pTrc99a-HER2F/pTrc99a-HER2R. It is noteworthy that the original ribosome-binding site (RBS) in pTrc99a was substituted with a strong RBS sequence, AAGGAG. Additionally, transcription of the clone synthetic gene was under the regulation of the \u003cem\u003etrc\u003c/em\u003e promoter (Supplementary Fig.\u0026nbsp;1).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cb\u003eCharacterization of expression of anti-HER2 immunotoxin in\u003c/b\u003e \u003cb\u003eE. coli\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe overnight-grown seed culture of BL21(DE3) harboring pTrc99a-HER2 was transferred to fresh LB medium with an inoculation ratio of 10% v/v. The resulting culture was kept at 37 \u0026ordm;C until reaching the logarithmic phase. Then, the protein expression was induced by adding 1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) with subsequent incubation at 180 rpm at 37 \u0026ordm;C for 3 h (Malekian et al. 2019).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003eExperimental design for bacterial expression and analysis of recombinant immunotoxin\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eA three-level four-factor Behnken experimental design was applied to statistically investigate the effects of four independent cultivation variables on the soluble expression of anti-HER2 immunotoxin in \u003cem\u003eE. coli\u003c/em\u003e BL21(DE3). The input factors include IPTG concentration (0.1-1 mM), post-induction time (2\u0026ndash;18 h), post-induction temperature (23\u0026ndash;37 \u0026ordm;C), and medium recipe (LB, 2\u003csub\u003eX\u003c/sub\u003eYT, and TB), whereas the factor levels were coded as \u0026minus;\u0026thinsp;1 (low), 0 (central point), and 1 (high) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). As a result, 45 cultivations were conducted in parallel (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Data analysis of the experimental design was carried out using the Design Expert software (version 13.0.5.0, StatEase Inc., Minneapolis, USA).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe variables and their levels used in the experimental design.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSymbol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eLevels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-induction\u003c/p\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-induction temperature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIPTG concentration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCulture medium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBox\u0026ndash;Behnken experimental design of 4 factors in 3 levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA (h)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC (mM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eResponse (soluble immunotoxon (\u0026micro;g/ml)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e200.919\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e166.499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e199.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98.123\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e234.928\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e178.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e196.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e191.914\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e155.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e223.746\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80.921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e167.631\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e259.535\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e172.212\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e114.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e108.271\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e115.249\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.554\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e170.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e174.668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e173.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e136.384\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65.743\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e180.922\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e161.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2xYT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e152.623\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e190.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.756\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAfter protein expression for each cultivation, bacterial cells were collected by centrifugation at 3,500 \u003cem\u003eg\u003c/em\u003e for 20 min, and the resulting cell pellet was resuspended in phosphate-buffered saline (PBS). For cell disruption, the suspension was sonicated for five cycles of 1 min with an interval of 1 min on ice between cycles. The soluble and insoluble fractions of the cell were separated using centrifugation at 7,500 \u003cem\u003eg\u003c/em\u003e and 4\u0026deg;C for 15 min.\u003c/p\u003e \u003cp\u003eTo evaluate the expression level and solubility of the expressed anti-HER2 immunotoxin, the soluble fraction of the sonicated culture sample was analyzed using a 12% (w/v) sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The intensity of the corresponding band was assessed by Gel Analyzer 19.1 software (Lazar Software, Hungary).\u003c/p\u003e \u003cp\u003eThe soluble fraction of the culture sample was used to purify anti-HER2 immunotoxin using affinity chromatography under native conditions, as described in our previous study with some modifications (Akbari et al. 2015). The protein concentration in each purification fraction was determined using the Bradford method (Malekian, Sima et al. 2019).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBiological activity of anti-HER2 immunotoxin through cell-based ELISA\u003c/h3\u003e\n\u003cp\u003eTo evaluate the bioactivity of the purified anti-HER2 immunotoxin, two cancer cell lines, \u003cem\u003ei.e.\u003c/em\u003e, the HER2-overexpressing cell line of SK-OV-3 and the HER2-low-expressing cell of MCF-7, were seeded in a 96-well ELISA plate at a cell density of 2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/ml and 37 \u0026ordm;C overnight. The cells were rinsed with PBS and then immobilized with 4% formalin buffer for 20 min. After that, the plate was washed thrice with PBS and then treated with 1% bovine serum albumin in PBS for 2 h at the room temperature. Then, samples containing anti-HER2 immunotoxin in a serial dilution were added to individual wells and incubated for 2 h at 25 \u0026ordm;C with gentle shaking. Each well was rinsed for three times with 0.05% Tween 20 in PBS. HRP-conjugated anti-His antibody (1: 50,000 dilution) was added to each well for incubation for 2 h at the room temperature with gentle shaking. After washing three times, OPD substrate was added to each well for incubation for 20 min. The colorimetric reaction was terminated using 2M H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, and the absorbance was measured at 450 and 490 nm (Akbari et al. 2014).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSmall-scale expression of anti-HER2 immunotoxin\u003c/h2\u003e \u003cp\u003e \u003cem\u003eE. coli\u003c/em\u003e BL21 (DE3) harboring pTrc99a-HER2 was used to express anti-HER2 immunotoxin while being cultivated at 37 \u0026ordm;C in LB medium for 3 h with a general induction condition at 1 mM IPTG. SDS-PAGE analysis suggested that the full-length immunotoxin was successfully expressed with an envisioned molecular weight of ~\u0026thinsp;62 kDa (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). However, most of the expressed immunotoxin appeared to be in the insoluble fraction as inclusion bodies (data not shown). The results nevertheless confirmed the proper design of the expression plasmid and the expression strategy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCorrelation of cultivation conditions using the RSM\u003c/h3\u003e\n\u003cp\u003eThe effect of the four operating factors (\u003cem\u003ei.e.\u003c/em\u003e, inducer concentration, temperature, induction timing, and medium composition) of the cultivation on the soluble expression of anti-HER2 immunotoxin was characterized using RSM. A total of 45 cultivations was conducted simultaneously, with soluble expression of anti-HER2 immunotoxin ranging between 22.4 and 260 \u0026micro;g/ml (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The results suggest the potential importance of optimization of cultivation conditions. To assess the experimental error and model reproducibility, cultivation was further carried out in triplicate under three central point conditions (\u003cem\u003ei.e\u003c/em\u003e., 0.55 mM IPTG, 10 h post-induction time, and 30\u0026deg;C in the culture medium of LB (runs 4, 7, and 19), 2xYT (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, and \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) or TB (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, and \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e)). The anti-HER2 immunotoxin concentrations were determined to be 184\u0026thinsp;\u0026plusmn;\u0026thinsp;14, 182\u0026thinsp;\u0026plusmn;\u0026thinsp;10 and 167\u0026thinsp;\u0026plusmn;\u0026thinsp;1 \u0026micro;g/ml, respectively, with the coefficient of variation (\u003cem\u003ei.e.\u003c/em\u003e, standard deviation/mean\u0026times;100%) being less than 7.68, 5.26 and 6.59%, for LB, 2xYT, and TB cultures, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe data of anti-HER2 immunotoxin concentrations obtained from the 45 experiments (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) were further analyzed by the Design Expert software (Akbari et al. 2015). Correlation between the level of soluble anti-HER2 immunotoxin expression in each medium culture and the three independent variables was formulated based on the following quadratic equations:\u003c/p\u003e \u003cp\u003eSoluble anti-HER2 immunotoxin expression in LB medium (\u0026micro;g/ml)\u0026thinsp;=\u0026thinsp;141\u0026thinsp;\u0026minus;\u0026thinsp;7.84 A\u0026thinsp;+\u0026thinsp;10.9 B \u0026minus;\u0026thinsp;110 C\u0026thinsp;+\u0026thinsp;0.784 AB \u0026minus;\u0026thinsp;5.90 AC\u0026thinsp;+\u0026thinsp;2.67 BC \u0026minus;\u0026thinsp;0.477 A\u0026sup2; \u0026minus;\u0026thinsp;0.374 B\u0026sup2; \u0026minus;\u0026thinsp;20.2 C\u0026sup2;\u003c/p\u003e \u003cp\u003eSoluble anti-HER2 immunotoxin expression in 2xYT medium (\u0026micro;g/ml) = -261.769 -4.702A\u0026thinsp;+\u0026thinsp;41.040B -411.109C\u0026thinsp;+\u0026thinsp;0.274AB\u0026thinsp;+\u0026thinsp;9.569AC\u0026thinsp;+\u0026thinsp;13.414BC-0.117A\u0026sup2; -0.920B\u0026sup2; -102.318C\u0026sup2;\u003c/p\u003e \u003cp\u003eSoluble anti-HER2 immunotoxin expression in TB medium (\u0026micro;g/ml) = -21.522 -35.427A\u0026thinsp;+\u0026thinsp;26.748B -214.053C\u0026thinsp;+\u0026thinsp;1.067AB\u0026thinsp;+\u0026thinsp;14.358AC\u0026thinsp;+\u0026thinsp;8.042BC -0.176A -0.725B\u0026sup2; -155.636C\u0026sup2;\u003c/p\u003e \u003cp\u003eThe fitting quality of the quadratic model was determined using analysis of variance (ANOVA) and the \u003cem\u003eP\u003c/em\u003e values were applied to evaluate the significance of each coefficient (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The correlation coefficient (R\u0026sup2;) of the model was 0.993, suggesting that the model could cover and predict 99.3% of the variation in the response. The F-value of 14.7 with a low probability value (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) indicates that the model is significant in terms of predicting soluble expression of anti-HER2 immunotoxin based on cultivation of the engineered \u003cem\u003eE. coli\u003c/em\u003e. On the other hand, the lack of fit for the model was insignificant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) with an F value of 3.79, suggesting that there could be a 8.03% probability for a Lack of Fit F-value to appear as a result of the noise. The results indicate that the model could fit the experimental data properly.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eANOVA results for response surface quadratic model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSum of Squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.36E\u0026thinsp;+\u0026thinsp;05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4674.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA-Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18089.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18089.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB-Temp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8172.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8172.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-Conc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10199.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10199.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7851.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3925.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18882.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18882.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5614.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5614.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7915.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3957.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7698.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7698.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1246.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e623.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot significant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10989.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5494.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2990.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2990.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12045.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12045.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3903.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3903.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4052.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2026.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11626.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5813.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003esignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBCD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2292.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1146.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enot significant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u0026sup2;D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1124.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e562.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.2036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enot significant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u0026sup2;D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1357.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e678.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enot significant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u0026sup2;D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1410.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e705.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enot significant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidual\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4757.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e317.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of Fit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3956.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e439.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enot significant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePure Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e801.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e133.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCor Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40E\u0026thinsp;+\u0026thinsp;05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of the effects of cultivation variables for optimization\u003c/h2\u003e \u003cp\u003eAs illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the effects of all four cultivation parameters on soluble expression of anti-HER2 immunotoxin were significant though the culture medium (D) had a less significant effect. Additionally, the interaction terms of AB, AC, AD, BC, and CD were shown to have a significant impact on the soluble expression of anti-HER2 immunotoxin (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting their potential combinatory effects on the cultivation performance. However, the interaction of post-induction time and culture medium (BD) was insignificant. Moreover, A\u0026sup2;, B\u0026sup2;, C\u0026sup2;, ABD, and ACD are other significant model terms.\u003c/p\u003e \u003cp\u003eThe effects of three variables (\u003cem\u003ei.e.\u003c/em\u003e, IPTG concentration, post-induction time, and post-induction temperature) and their interactions and effects on the soluble expression of anti-HER2 immunotoxin in the LB culture (\u003cem\u003ei.e.\u003c/em\u003e, the optimal medium) were graphically shown in the 3-dimensional response surface plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB shows the response surface plot associated with the interaction and effects of post-induction time and post-induction temperature on the soluble expression of anti-HER2 immunotoxin when the IPTG concentration was maintained at its basal level (0.55 mM). Clearly, soluble expression of the protein was enhanced with increasing time and temperature. As presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, soluble expression of anti-HER2 immunotoxin increases remarkably with increasing time and decreasing inducer concentration when the post-induction temperature was 30 \u0026ordm;C. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD further shows the response surface plot of the effects of post-induction temperature and IPTG concentration on soluble expression of the protein when the post-induction time was 10 h. Clearly, soluble expression of the protein was enhanced with decreasing IPTG concentration and temperature.\u003c/p\u003e \u003cp\u003eThe studentized residuals provide the range of standard deviations associated with the difference between the actual and predicted values. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, the plot of normal probability for soluble expression of anti-HER2 immunotoxin shows a normal and linear distribution. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB further shows that the actual and predicted levels for soluble expression of anti-HER2 immunotoxin are in reasonable agreement. Additionally, the plot of residuals versus the experimental runs remains within the boundaries specified in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC. These statistical analyses collectively indicate that all data points follow a normal pattern and that the established model is adequate for the prediction of the cultivation performance for soluble expression of anti-HER2 immunotoxin. Finally, according to the model, the optimal solution with the highest soluble expression of the protein (261 \u0026micro;g/ml) would be achieved with 0.1 mM IPTG in LB medium culture at 33\u0026deg;C for 18 h. In average, 272\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3 \u0026micro;g/ml of soluble anti-HER2 immunotoxin was expressed and this level was rather close to the predicted optimum (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePurification and evaluation of the biological activity of anti-HER 2 immunotoxin\u003c/h2\u003e \u003cp\u003eAfter the cultivation for the expression of anti-HER2 immunotoxin under the optimal condition, the fusion protein was successfully purified by affinity chromatography using a Ni-NTA column under native conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Out of the 1-L of bacterial culture, approximately 27.2 mg of anti-HER2 immunotoxin (340 \u0026micro;g/ml) was recovered, and the purity was determined to be 90%. Using this purified protein, the biological activity was further evaluated using an ELISA assay. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the attachment of anti-HER2 immunotoxin to SK-OV-3 cells (HER2-ovrexprssing cell line) was successfully demonstrated in a dose-dependent manner.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur previous study demonstrated that anti-HER2 immunotoxin could act as a promising candidate for HER2-targetd cancer therapy (North et al. 2005). However, large-scale production of this immunotoxin was limited by the accumulation of insoluble inclusion bodies upon cultivation of the engineered \u003cem\u003eE. coli\u003c/em\u003e strain with a transformed immunotoxin-encoded gene whose expression was regulated by the T7 promoter. One approach to enhance soluble expression of recombinant proteins is to modulate, not necessarily increase, promoter strength. In the present study, we demonstrated that proper integration of the genetic (\u003cem\u003ei.e.\u003c/em\u003e, using the \u003cem\u003etrc\u003c/em\u003e promoter to replace the T7 one) and bioprocessing (\u003cem\u003ei.e.\u003c/em\u003e, optimization of cultivation conditions) strategies can potentially lead to a remarkable cultivation performance for more soluble expression of the recombinant anti-HER2 immunotoxin. Tegel \u003cem\u003eet al\u003c/em\u003e. evaluated the effects of three different IPTG-inducible promoters (\u003cem\u003ei.e.\u003c/em\u003e, T7, \u003cem\u003etrc\u003c/em\u003e, and \u003cem\u003elac\u003c/em\u003eUV5) for expression of seventeen fusion proteins in \u003cem\u003eE. coli\u003c/em\u003e (Tegel et al. 2011). They observed that the use of the most potent promoter (\u003cem\u003ei.e.\u003c/em\u003e, T7 with the highest promoter strength) often led to an ineffective protein production with a low soluble fraction. Furthermore, such technical issue could be partially alleviated based on the use of the \u003cem\u003etrc\u003c/em\u003e or T7 promoter in combination with \u003cem\u003eE. coli\u003c/em\u003e Rosetta (DE3) as the expression host, resulting in a higher quantity of soluble protein. Balzer \u003cem\u003eet al\u003c/em\u003e. compared three different promoter systems (LacI/\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003eT7la\u003c/em\u003ec\u003c/sub\u003e, LacI/\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrc\u003c/em\u003e\u003c/sub\u003e, AraC/\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003eBAD\u003c/em\u003e\u003c/sub\u003e) for regulated expression of five genes (Balzer et al. 2013). It was observed that the LacI/\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003eT7lac\u003c/em\u003e\u003c/sub\u003e system, while generating a high-level of mRNA transcript, produced the highest amount of insoluble protein. They also observed that the LacI/\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrc\u003c/em\u003e\u003c/sub\u003e system had a more effective initiation upon protein expression with a more homogeneous protein expression profile.\u003c/p\u003e \u003cp\u003eCultivation condition can potentially influence both the expression and solubility of recombinant proteins and, therefore, should be properly evaluated. The use of statistical design enables not only determination of the optimal culture condition but also characterization of the interactions amongst numerous experimental parameters and operating variables (Behravan et al. 2021). In this study, we specifically apply RSM to optimize the cultivation performance for soluble expression of anti-HER2 immunotoxin under the regulation of the \u003cem\u003etrc\u003c/em\u003e promoter in \u003cem\u003eE. coli\u003c/em\u003e and we also demonstrated satisfactory predictability based on the established model. Similar application of RSM for optimization of recombinant protein production was previously reported (Shafiee et al. 2017). For example, Shafiee \u003cem\u003eet al\u003c/em\u003e. applied RSM to optimize the expression of recombinant DT386-BR2 in \u003cem\u003eE. coli\u003c/em\u003e Rosetta (DE3). They reported that the induction with 1 mM IPTG for 2 h at 37\u0026deg;C would result in higher total protein expression of the immunotoxin (Shafiee, Rabbani et al. 2017). All these reports suggest the importance of induction mechanism for bacterial expression of recombinant immunotoxin.\u003c/p\u003e \u003cp\u003eMedium composition could have remarkable metabolic effects on cell growth and gene expression upon conducting \u003cem\u003eE. coli\u003c/em\u003e cultivation (Kram et al. 2015). It was previously observed that using the TB medium would result in more production of recombinant DT386-BR2, compared to LB and superbroth (SB) (Shafiee, Rabbani et al. 2017). On the other hand, Heydari \u003cem\u003eet al.\u003c/em\u003e used the Taguchi method to optimize the medium composition, in particular carbon and nitrogen sources, for the expression of Denileukin diftitox in \u003cem\u003eE. coli\u003c/em\u003e. While nutrient components with high energy and carbon levels could potentially enhance biomass production and recombinant protein expression, their effects on the soluble production of recombinant proteins have been controversial. Some studies showed that the use of culture medium with higher yeast extract and tryptone contents could result in more soluble expression of the target protein (Kanno et al. 2019, Aghdam et al. 2022), while others found the opposite (Kim et al. 2017). Kanno \u003cem\u003eet al.\u003c/em\u003e reported that the use of enriched media, such as TB, potentially resulted in more soluble expression of recombinant Zika virus ΔNS1 in \u003cem\u003eE. coli\u003c/em\u003e (Aghdam, Tohidkia et al. 2022). Though we observed more soluble expression of anti-HER2 immunotoxin in \u003cem\u003eE. coli\u003c/em\u003e grown in a less rich medium (\u003cem\u003ei.e.\u003c/em\u003e, LB medium), our current results are in agreement with the previous report comparing three media (\u003cem\u003ei.e.\u003c/em\u003e, LB, TB, 2xYT) for the expression of cis-aconitate decarboxylase in \u003cem\u003eE. coli\u003c/em\u003e BL21(DE3) (Kim, Seo et al. 2017). Basically, Kim \u003cem\u003eet al\u003c/em\u003e. reported that, though a higher cell density could be obtained in TB medium, more enzyme production with a higher yield was obtained in LB medium (Kim, Seo et al. 2017). This might be attributable to the metabolic load induced by enhanced cell growth that could promote the formation of inclusion bodies. Our finding showed that post-induction time was also critical for soluble expression of anti-HER2 immunotoxin, especially under a low IPTG induction concentration (\u003cem\u003ei.e.\u003c/em\u003e, 0.1 mM). Other researchers also manipulated the inducer concentration and induction timing to reduce metabolic load for the producing cells (Aghdam, Tohidkia et al. 2022). Reducing the metabolic stress based on the use of a low inducer concentration could potentially mediate a metabolic balance between cell growth and recombinant protein expression in \u003cem\u003eE. coli\u003c/em\u003e, improving the solubility and folding of the recombinant protein (Papaneophytou et al. 2013).\u003c/p\u003e \u003cp\u003eCultivation temperature is one of the most important factors influencing the expression and solubility of recombinant proteins. While the optimal temperature for soluble expression of anti-HER2 immunotoxin was 33 \u0026ordm;C in this study, more soluble expression of recombinant proteins at a temperature around 30 \u0026ordm;C was observed previously (M\u0026uuml;hlmann et al. 2017). It has been perceived that recombinant proteins produced at a low temperature might have higher solubility and bioactivity potentially because of more functional expression of molecular chaperones. However, such temperature effects may not always hold and should be further studied for different recombinant proteins. Some studies reported that higher temperatures promote soluble expression of recombinant proteins. In particular, Vincentelli \u003cem\u003eet al\u003c/em\u003e. reported that recombinant protein expression at 37 \u0026ordm;C yielded more soluble protein than 25 \u0026ordm;C and 17 \u0026ordm;C (Vincentelli et al. 2011). Such controversy could be potentially associated with different recombinant protein properties, expression vectors, and expression hosts.\u003c/p\u003e \u003cp\u003eIn conclusion, RSM was successfully applied to optimize cultivation conditions for soluble expression of anti-HER2 immunotoxin under the regulation of the \u003cem\u003etrc\u003c/em\u003e promoter in \u003cem\u003eE. coli\u003c/em\u003e such that a sufficient amount of biologically active and soluble recombinant protein could be obtained for subsequent \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e trials. The results suggest that inducer concentration, medium recipe, post-induction temperature, and post-induction time have significant effects on the cultivation performance for soluble expression of anti-HER2 immunotoxin in \u003cem\u003eE. coli\u003c/em\u003e. The optimal conditions were determined to be 0.1 mM IPTG for induction of gene expression at 33\u0026deg;C for 18 h in the LB medium. The approaches documented in this study can be generally applied to enhance the expression yield and solubility of recombinant proteins in \u003cem\u003eE. coli\u003c/em\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financially supported by the Isfahan University of Medical Sciences (Grant No. 199495).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to thank Mrs Fatemeh Moazen for her excellent technical assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be shared upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eXing Y, Xu K, Li S, Cao L, Nan Y, Li Q, Li W, Hong Z. A single-domain antibody-based anti-PSMA recombinant immunotoxin exhibits specificity and efficacy for prostate cancer therapy. Int. J. Mol. Sci.2021 May 23;22(11):5501.\u003c/li\u003e\n \u003cli\u003eKim JS, Jun SY, Kim YS. Critical issues in the development of immunotoxins for anticancer therapy. J. Pharm. Sci. 2020 Jan 1;109(1):104-15.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAkbari B, Farajnia S, Ahdi Khosroshahi S, Safari F, Yousefi M, Dariushnejad H, Rahbarnia L. Immunotoxins in cancer therapy: Review and update. Int. Rev. Immunol. 2017 Jul 4; 36(4):207-19.\u003c/li\u003e\n \u003cli\u003eHoffmann F, van den Heuvel J, Zidek N, Rinas U. Minimizing inclusion body formation during recombinant protein production in Escherichia coli at bench and pilot plant scale. Enzyme Microb. Technol. 2004 Mar 1;34(3-4):235-41.\u003c/li\u003e\n \u003cli\u003eS\u0026oslash;rensen HP, Mortensen KK: Soluble expression of recombinant proteins in the cytoplasm of Escherichia coli. Microb Cell Fact. 2005, 4(1):1\u0026ndash;8. 10.1186/1475-2859-4-1.\u003c/li\u003e\n \u003cli\u003eRosano GL, Morales ES, Ceccarelli EA. New tools for recombinant protein production in Escherichia coli: A 5‐year update. Protein Sci. 2019 Aug; 28(8):1412-22.\u003c/li\u003e\n \u003cli\u003eSamuelson JC. Recent developments in difficult protein expression: a guide to E. coli strains, promoters, and relevant host mutations. Heterologous Gene Expression in E. coli: Methods Protoc. 2011:195-209.\u003c/li\u003e\n \u003cli\u003eMayer MR, Dailey TA, Baucom CM, Supernak JL, Grady MC, Hawk HE, Dailey HA. Expression of human proteins at the Southeast Collaboratory for Structural Genomics. J. Struct. Funct.genomics. 2004 Mar;5:159-65.\u003c/li\u003e\n \u003cli\u003eBaş D, Boyacı IH. Modeling and optimization I: Usability of response surface methodology. J Food Eng.2007;78(3):836-845.\u003c/li\u003e\n \u003cli\u003eBezerra MA, Santelli RE, Oliveira EP, Villar LS,Escaleira LA. Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta 2008;76(5):965-977.\u003c/li\u003e\n \u003cli\u003eAraujo PW, Brereton RG. Experimental design III. Quantification. TrAC Trend Anal Chem. 1996 Mar 1;15(3):156-63.\u003c/li\u003e\n \u003cli\u003eLee KM, Rhee CH, Kang CK, Kim JH. Sequential and simultaneous statistical optimization by dynamic design of experiment for peptide overexpression in recombinant Escherichia coli. Appl. Biochem. Biotechnol. 2006 Oct;135:59-80.\u003c/li\u003e\n \u003cli\u003eLiu N, Jiang J, Yan F, Xu Y, Yang M, Gao Y, et al. Optimization of simultaneous production of volatile fatty acids and bio-hydrogen from food waste using response surface methodology. RSC Adv.2018;8(19):10457- 10464.\u003c/li\u003e\n \u003cli\u003eShariaty Vaziri Z, Shafee F, Akbari V. Design and construction of scFv‑PE35KDEL as a novel immunotoxin against human epidermal growth factor receptor 2 for cancer therapy. Biotechnol Lett. 2023 Apr;45(4):537-50.\u003c/li\u003e\n \u003cli\u003eHofnung, M. A short course in bacterial genetics and a laboratory manual and handbook for Escherichia coli and related bacteria: edited by JH Miller, Cold Spring Harb. Perspect. Med. 1992, Lab man. p 456. Biochim. 1993 Jan 1;75(6):501.\u003c/li\u003e\n \u003cli\u003eGibson, D.G.; Young, L.; Chuang, R.-Y.; Venter, J.C.; Hutchison III, C.A.; Smith, H.O. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods. 2009, 6, 343-345.\u003c/li\u003e\n \u003cli\u003eAmann, E.; Ochs, B.; Abel, K.-J. Tightly regulated tac promoter vectors useful for the expression of unfused and fused proteins in Escherichia coli. Gene. 1988, 69, 301-315.\u003c/li\u003e\n \u003cli\u003eMalekian R, Sima S, Jahanian-Najafabadi A, Moazen F, Akbari V. Improvement of soluble expression of GM-CSF in the cytoplasm of Escherichia coli using chemical and molecular chaperones. Protein Expr Purif. 2019;160:66-72.\u003c/li\u003e\n \u003cli\u003eAkbari V, Sadeghi HMM, Jafarian-Dehkordi A, Abedi D, Chou CP. Improved biological activity of a single chain antibody fragment against human epidermal growth factor receptor 2 (HER2) expressed in the periplasm of Escherichia coli. Protein Expr Purif. 2015;116:66-74.\u003c/li\u003e\n \u003cli\u003eAkbari V, Mir Mohammad Sadeghi H, Jafrian-Dehkordi A, Abedi D, Chou CP. Functional expression of a single-chain antibody fragment against human epidermal growth factor receptor 2 (HER2) in Escherichia coli. J. Ind. Microbiol.. 2014;41(6):947-56.\u003c/li\u003e\n \u003cli\u003eAkbari V, Sadeghi HM, Jafarian-Dehkordi A, Chou CP, Abedi D. Optimization of a single-chain antibody fragment overexpression in Escherichia coli using response surface methodology. Res Pharm Sci. 2015;10(1):75-83.\u003c/li\u003e\n \u003cli\u003eNorth BJ, Schwer B, Ahuja N, Marshall B, Verdin E. Preparation of enzymatically active recombinant class III protein deacetylases. Methods. 2005 Aug 1;36(4):338-45.\u003c/li\u003e\n \u003cli\u003eTegel H, Ottosson J, Hober S. Enhancing the protein production levels in Escherichia coli with a strong promoter. FEBS J. 2011;278(5):729\u0026ndash;739.\u003c/li\u003e\n \u003cli\u003eBalzer S, Kucharova V, Megerle J, Lale R, Brautaset T, Valla S. A comparative analysis of the properties of regulated promoter systems commonly used for recombinant gene expression in Escherichia coli. Microb Cell Fact. 2013;12:26.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBehravan A, Hashemi A. Statistical optimization of culture conditions for expression of recombinant humanized anti-EpCAM single-chain antibody using response surface methodology. Res Pharm Sci. 2021; 16(2):153-164.\u003c/li\u003e\n \u003cli\u003eShafiee F, Rabbani M, Jahanian-Najafabadi A. Optimization of the Expression of DT386-BR2 Fusion Protein in Escherichia coli using Response Surface Methodology. Adv Biomed Res. 2017; 6:22.\u003c/li\u003e\n \u003cli\u003eKram KE, Finkel SE. Rich Medium Composition Affects Escherichia coli Survival, Glycation, and Mutation Frequency during Long-Term Batch Culture. Appl Environ Microb. 2015; 81(13):4442-50.\u003c/li\u003e\n \u003cli\u003eHeydari M, Robatjazi SM, Zeinoddini M, Darabi E. Optimization of chemically defined cell culture media for recombinant ONTAK immunotoxin production. IJMM. 2014;8(3):51-7.\u003c/li\u003e\n \u003cli\u003eAghdam MA, Tohidkia MR, Ghamghami E, Ahmadikhah A, Khanmahamadi M, Baradaran B, Mokhtarzadeh A. Implementation of a Design of Experiments to Improve Periplasmic Yield of Functional ScFv Antibodies in a Phage Display Platform. Adv. Pharm. Bull. 2022;12(3):583-592.\u003c/li\u003e\n \u003cli\u003eKanno AI, Leite LCC, Pereira LR, de Jesus MJR, Andreata-Santos R, Alves RPDS, Durigon EL, Ferreira LCS, Gon\u0026ccedil;alves VM. Optimization and scale-up production of Zika virus \u0026Delta;NS1 in Escherichia coli: application of Response Surface Methodology. AMB Express. 2019; 10(1):1.\u003c/li\u003e\n \u003cli\u003eKim J, Seo HM, Bhatia SK, Song HS, Kim JH, Jeon JM, Choi KY, Kim W, Yoon JJ, Kim YG, Yang YH. Production of itaconate by whole-cell bioconversion of citrate mediated by expression of multiple cis-aconitate decarboxylase (cadA) genes in Escherichia coli. Sci Rep. 2017;7:39768.\u003c/li\u003e\n \u003cli\u003eZhang H, Zheng Y, Liu Q, Tao X, Zheng W, Ma X, et al. Development of a fed-batch process for the production of anticancer drug TATm-survivin(T34A) in Escherichia coli. Biochem Eng J. 2009; 43(2):163-8.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePapaneophytou CP, Rinotas V, Douni E, Kontopidis G. A statistical approach for optimization of RANKL overexpression in Escherichia coli: purification and characterization of the protein. Protein Expr Purif. 2013;90(1):9-19.\u003c/li\u003e\n \u003cli\u003eM\u0026uuml;hlmann M, Forsten E, Noack S, B\u0026uuml;chs J. Optimizing recombinant protein expression via automated induction profiling in microtiter plates at different temperatures. Microb Cell Fact. 2017;16(1):220.\u003c/li\u003e\n \u003cli\u003eVincentelli R, Cimino A, Geerlof A, Kubo A, Satou Y, Cambillau C. High-throughput protein expression screening and purification in Escherichia coli. Methods. 2011;55(1):65-72.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\"Araujo PW, Brereton RG. Experimental design III. Quantification. TrAC Trend Anal Chem. 1996 Mar 1;15(3):156-63.\".\u003c/p\u003e\n\u003cp\u003e\"Baş D, Boyacı IH. Modeling and optimization I: Usability of response surface methodology. J Food Eng.2007;78(3):836-845.\".\u003c/p\u003e\n\u003cp\u003e\"Heydari M, Robatjazi SM, Zeinoddini M, Darabi E. Optimization of chemically defined cell culture media for recombinant ONTAK immunotoxin production. IJMM. 2014;8(3):51-7.\".\u003c/p\u003e\n\u003cp\u003e\"Hoffmann F, van den Heuvel J, Zidek N, Rinas U. Minimizing inclusion body formation during recombinant protein production in Escherichia coli at bench and pilot plant scale. Enzyme Microb. Technol. 2004 Mar 1;34(3-4):235-41.\".\u003c/p\u003e\n\u003cp\u003e\"Sørensen HP, Mortensen KK: Soluble expression of recombinant proteins in the cytoplasm of Escherichia coli. Microb Cell Fact. 2005, 4(1):1–8. 10.1186/1475-2859-4-1.\".\u003c/p\u003e\n\u003cp\u003e\"Zhang H, Zheng Y, Liu Q, Tao X, Zheng W, Ma X, et al. Development of a fed-batch process for the production of anticancer drug TATm-survivin(T34A) in Escherichia coli. Biochem Eng J. 2009; 43(2):163-8. .\"\u003c/p\u003e\n\u003cp\u003eAghdam, M. A., M. R. Tohidkia, E. Ghamghami, A. Ahmadikhah, M. Khanmahamadi, B. Baradaran and A. Mokhtarzadeh (2022). \"Implementation of a Design of Experiments to Improve Periplasmic Yield of Functional ScFv Antibodies in a Phage Display Platform.\" \u003cu\u003eAdvanced pharmaceutical bulletin\u003c/u\u003e \u003cstrong\u003e12\u003c/strong\u003e(3): 583-592.\u003c/p\u003e\n\u003cp\u003eAkbari, B., S. Farajnia, S. Ahdi Khosroshahi, F. Safari, M. Yousefi, H. Dariushnejad and L. Rahbarnia (2017). \"Immunotoxins in cancer therapy: Review and update.\" \u003cu\u003eInternational reviews of immunology\u003c/u\u003e \u003cstrong\u003e36\u003c/strong\u003e(4): 207-219.\u003c/p\u003e\n\u003cp\u003eAkbari, V., H. Mir Mohammad Sadeghi, A. Jafrian-Dehkordi, D. Abedi and C. P. Chou (2014). \"Functional expression of a single-chain antibody fragment against human epidermal growth factor receptor 2 (HER2) in Escherichia coli.\" \u003cu\u003eJournal of industrial microbiology \u0026amp; biotechnology\u003c/u\u003e \u003cstrong\u003e41\u003c/strong\u003e(6): 947-956.\u003c/p\u003e\n\u003cp\u003eAkbari, V., H. M. Sadeghi, A. Jafarian-Dehkordi, D. Abedi and C. P. Chou (2015). \"Improved biological activity of a single chain antibody fragment against human epidermal growth factor receptor 2 (HER2) expressed in the periplasm of Escherichia coli.\" \u003cu\u003eProtein expression and purification\u003c/u\u003e \u003cstrong\u003e116\u003c/strong\u003e: 66-74.\u003c/p\u003e\n\u003cp\u003eAkbari, V., H. M. Sadeghi, A. Jafarian-Dehkordi, C. P. Chou and D. Abedi (2015). \"Optimization of a single-chain antibody fragment overexpression in Escherichia coli using response surface methodology.\" \u003cu\u003eResearch in pharmaceutical sciences\u003c/u\u003e \u003cstrong\u003e10\u003c/strong\u003e(1): 75-83.\u003c/p\u003e\n\u003cp\u003eAmann, E., B. Ochs and K.-J. Abel (1988). \"Tightly regulated tac promoter vectors useful for the expression of unfused and fused proteins in Escherichia coli.\" \u003cu\u003eGene\u003c/u\u003e \u003cstrong\u003e69\u003c/strong\u003e(2): 301-315.\u003c/p\u003e\n\u003cp\u003eBalzer, S., V. Kucharova, J. Megerle, R. Lale, T. Brautaset and S. Valla (2013). \"A comparative analysis of the properties of regulated promoter systems commonly used for recombinant gene expression in Escherichia coli.\" \u003cu\u003eMicrobial cell factories\u003c/u\u003e \u003cstrong\u003e12\u003c/strong\u003e: 26.\u003c/p\u003e\n\u003cp\u003eBehravan, A. and A. Hashemi (2021). \"Statistical optimization of culture conditions for expression of recombinant humanized anti-EpCAM single-chain antibody using response surface methodology.\" \u003cu\u003eResearch in pharmaceutical sciences\u003c/u\u003e \u003cstrong\u003e16\u003c/strong\u003e(2): 153-164.\u003c/p\u003e\n\u003cp\u003eBezerra, M. A., R. E. Santelli, E. P. Oliveira, L. S. Villar and L. A. Escaleira (2008). \"Response surface methodology (RSM) as a tool for optimization in analytical chemistry.\" \u003cu\u003eTalanta\u003c/u\u003e \u003cstrong\u003e76\u003c/strong\u003e(5): 965-977.\u003c/p\u003e\n\u003cp\u003eHofnung, M. (1993). \"A short course in bacterial genetics and a laboratory manual and handbook for Escherichia coli and related bacteria: edited by JH Miller, Cold Spring Harbor Laboratory Press, 1992, Laboratory Manual, p 456.\" \u003cu\u003eBiochimie\u003c/u\u003e \u003cstrong\u003e75\u003c/strong\u003e(6): 501.\u003c/p\u003e\n\u003cp\u003eKanno, A. I., L. C. C. Leite, L. R. Pereira, M. J. R. de Jesus, R. Andreata-Santos, R. Alves, E. L. Durigon, L. C. S. Ferreira and V. M. Gonçalves (2019). \"Optimization and scale-up production of Zika virus ΔNS1 in Escherichia coli: application of Response Surface Methodology.\" \u003cu\u003eAMB Express\u003c/u\u003e \u003cstrong\u003e10\u003c/strong\u003e(1): 1.\u003c/p\u003e\n\u003cp\u003eKim, J., H. M. Seo, S. K. Bhatia, H. S. Song, J. H. Kim, J. M. Jeon, K. Y. Choi, W. Kim, J. J. Yoon, Y. G. Kim and Y. H. Yang (2017). \"Production of itaconate by whole-cell bioconversion of citrate mediated by expression of multiple cis-aconitate decarboxylase (cadA) genes in Escherichia coli.\" \u003cu\u003eScientific reports\u003c/u\u003e \u003cstrong\u003e7\u003c/strong\u003e: 39768.\u003c/p\u003e\n\u003cp\u003eKim, J. S., S. Y. Jun and Y. S. Kim (2020). \"Critical Issues in the Development of Immunotoxins for Anticancer Therapy.\" \u003cu\u003eJournal of pharmaceutical sciences\u003c/u\u003e \u003cstrong\u003e109\u003c/strong\u003e(1): 104-115.\u003c/p\u003e\n\u003cp\u003eKram, K. E. and S. E. Finkel (2015). \"Rich Medium Composition Affects Escherichia coli Survival, Glycation, and Mutation Frequency during Long-Term Batch Culture.\" \u003cu\u003eApplied and environmental microbiology\u003c/u\u003e \u003cstrong\u003e81\u003c/strong\u003e(13): 4442-4450.\u003c/p\u003e\n\u003cp\u003eLee, K. M., C. H. Rhee, C. K. Kang and J. H. Kim (2006). \"Sequential and simultaneous statistical optimization by dynamic design of experiment for peptide overexpression in recombinant Escherichia coli.\" \u003cu\u003eApplied biochemistry and biotechnology\u003c/u\u003e \u003cstrong\u003e135\u003c/strong\u003e(1): 59-80.\u003c/p\u003e\n\u003cp\u003eLiu, N., J. Jiang, F. Yan, Y. Xu, M. Yang, Y. Gao, A. Aihemaiti and Q. Zou (2018). \"Optimization of simultaneous production of volatile fatty acids and bio-hydrogen from food waste using response surface methodology.\" \u003cu\u003eRSC advances\u003c/u\u003e \u003cstrong\u003e8\u003c/strong\u003e(19): 10457-10464.\u003c/p\u003e\n\u003cp\u003eMalekian, R., S. Sima, A. Jahanian-Najafabadi, F. Moazen and V. Akbari (2019). \"Improvement of soluble expression of GM-CSF in the cytoplasm of Escherichia coli using chemical and molecular chaperones.\" \u003cu\u003eProtein expression and purification\u003c/u\u003e \u003cstrong\u003e160\u003c/strong\u003e: 66-72.\u003c/p\u003e\n\u003cp\u003eMayer, M. R., T. A. Dailey, C. M. Baucom, J. L. Supernak, M. C. Grady, H. E. Hawk and H. A. Dailey (2004). \"Expression of human proteins at the Southeast Collaboratory for Structural Genomics.\" \u003cu\u003eJournal of structural and functional genomics\u003c/u\u003e \u003cstrong\u003e5\u003c/strong\u003e(1-2): 159-165.\u003c/p\u003e\n\u003cp\u003eMühlmann, M., E. Forsten, S. Noack and J. Büchs (2017). \"Optimizing recombinant protein expression via automated induction profiling in microtiter plates at different temperatures.\" \u003cu\u003eMicrobial cell factories\u003c/u\u003e \u003cstrong\u003e16\u003c/strong\u003e(1): 220.\u003c/p\u003e\n\u003cp\u003eNorth, B. J., B. Schwer, N. Ahuja, B. Marshall and E. Verdin (2005). \"Preparation of enzymatically active recombinant class III protein deacetylases.\" \u003cu\u003eMethods (San Diego, Calif.)\u003c/u\u003e \u003cstrong\u003e36\u003c/strong\u003e(4): 338-345.\u003c/p\u003e\n\u003cp\u003ePapaneophytou, C. P., V. Rinotas, E. Douni and G. Kontopidis (2013). \"A statistical approach for optimization of RANKL overexpression in Escherichia coli: purification and characterization of the protein.\" \u003cu\u003eProtein expression and purification\u003c/u\u003e \u003cstrong\u003e90\u003c/strong\u003e(1): 9-19.\u003c/p\u003e\n\u003cp\u003eRosano, G. L., E. S. Morales and E. A. Ceccarelli (2019). \"New tools for recombinant protein production in Escherichia coli: A 5-year update.\" \u003cu\u003eProtein science : a publication of the Protein Society\u003c/u\u003e \u003cstrong\u003e28\u003c/strong\u003e(8): 1412-1422.\u003c/p\u003e\n\u003cp\u003eSamuelson, J. C. (2011). \"Recent developments in difficult protein expression: a guide to E. coli strains, promoters, and relevant host mutations.\" \u003cu\u003eMethods in molecular biology (Clifton, N.J.)\u003c/u\u003e \u003cstrong\u003e705\u003c/strong\u003e: 195-209.\u003c/p\u003e\n\u003cp\u003eShafiee, F., M. Rabbani and A. Jahanian-Najafabadi (2017). \"Optimization of the Expression of DT386-BR2 Fusion Protein in Escherichia coli using Response Surface Methodology.\" \u003cu\u003eAdvanced biomedical research\u003c/u\u003e \u003cstrong\u003e6\u003c/strong\u003e: 22.\u003c/p\u003e\n\u003cp\u003eShariaty Vaziri, Z., F. Shafiee and V. Akbari (2023). \"Design and construction of scFv-PE35KDEL as a novel immunotoxin against human epidermal growth factor receptor 2 for cancer therapy.\" \u003cu\u003eBiotechnology letters\u003c/u\u003e \u003cstrong\u003e45\u003c/strong\u003e(4): 537-550.\u003c/p\u003e\n\u003cp\u003eTegel, H., J. Ottosson and S. Hober (2011). \"Enhancing the protein production levels in Escherichia coli with a strong promoter.\" \u003cu\u003eThe FEBS journal\u003c/u\u003e \u003cstrong\u003e278\u003c/strong\u003e(5): 729-739.\u003c/p\u003e\n\u003cp\u003eVincentelli, R., A. Cimino, A. Geerlof, A. Kubo, Y. Satou and C. Cambillau (2011). \"High-throughput protein expression screening and purification in Escherichia coli.\" \u003cu\u003eMethods (San Diego, Calif.)\u003c/u\u003e \u003cstrong\u003e55\u003c/strong\u003e(1): 65-72.\u003c/p\u003e\n\u003cp\u003eXing, Y., K. Xu, S. Li, L. Cao, Y. Nan, Q. Li, W. Li and Z. Hong (2021). \"A Single-Domain Antibody-Based Anti-PSMA Recombinant Immunotoxin Exhibits Specificity and Efficacy for Prostate Cancer Therapy.\" \u003cu\u003eInternational journal of molecular sciences\u003c/u\u003e \u003cstrong\u003e22\u003c/strong\u003e(11).\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":"amb-express","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ambe","sideBox":"Learn more about [AMB Express](http://amb-express.springeropen.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/AMBE/default.aspx","title":"AMB Express","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Immunotoxin, Response Surface Methodology (RSM), cultivation optimization, protein solubility, Escherichia coli ","lastPublishedDoi":"10.21203/rs.3.rs-4155503/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4155503/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eImmunotoxins are widely applied for cancer therapy. However, bacterial expression of immunotoxins usually leads to the formation of insoluble and non-functional recombinant proteins. In this study, we aimed to improve soluble expression of a novel anti-HER2 immunotoxin under the regulation of the \u003cem\u003etrc\u003c/em\u003e promoter in \u003cem\u003eEscherichia coli\u003c/em\u003e by optimization of the cultivation conditions using response surface methodology (RSM). To conduct RSM, four cultivation variables (\u003cem\u003ei.e.\u003c/em\u003e, inducer concentration, post-induction time, post-induction temperature, and medium recipe), were selected for statistical characterization and optimization using the Box-Behnken design and Design Expert software. Based on the developed model using the Box-Behnken design, the optimal cultivation conditions for soluble expression of anti-HER2 immunotoxin were determined to be 0.1 mM IPTG for induction in the LB medium at 33 °C for 18 h. The expressed immunotoxin was successfully purified using affinity chromatography with more than 90% purity and its bioactivity was confirmed using cell-based ELISA. Technical approach developed in this study can be generally applied to enhance the production yield and quality of recombinant proteins using \u003cem\u003eE. coli\u003c/em\u003e as the gene expression system.\u003c/p\u003e","manuscriptTitle":"Integrated bioprocessing and genetic strategies to enhance soluble expression of anti-HER2 immunotoxin in E. coli","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-23 11:46:53","doi":"10.21203/rs.3.rs-4155503/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-05-18T22:50:50+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-14T09:44:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-07T09:24:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"AMB Express","date":"2024-05-06T08:45:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"amb-express","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ambe","sideBox":"Learn more about [AMB Express](http://amb-express.springeropen.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/AMBE/default.aspx","title":"AMB Express","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"43cdc36f-62d5-4bc1-846f-f2f19494296b","owner":[],"postedDate":"May 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-30T16:02:29+00:00","versionOfRecord":{"articleIdentity":"rs-4155503","link":"https://doi.org/10.1186/s13568-024-01765-6","journal":{"identity":"amb-express","isVorOnly":false,"title":"AMB Express"},"publishedOn":"2024-09-28 15:57:23","publishedOnDateReadable":"September 28th, 2024"},"versionCreatedAt":"2024-05-23 11:46:53","video":"","vorDoi":"10.1186/s13568-024-01765-6","vorDoiUrl":"https://doi.org/10.1186/s13568-024-01765-6","workflowStages":[]},"version":"v1","identity":"rs-4155503","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4155503","identity":"rs-4155503","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}