Engineering a Temperature-Programmable Biosensor Toolkit for Recombinant Protein Production in Corynebacterium glutamicum

Engineering a Temperature-Programmable Biosensor Toolkit for Recombinant Protein Production in Corynebacterium glutamicum | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Engineering a Temperature-Programmable Biosensor Toolkit for Recombinant Protein Production in Corynebacterium glutamicum Haofei Xu, Yanbo Li, Yiran Gan, Songzhou Liu, Bin Lin, Shijun Cen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8832594/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Dynamic metabolic regulation is crucial for optimizing microbial cell factories. To address the limitations of chemical inducers, this study developed a temperature-responsive synthetic biology toolkit for Corynebacterium glutamicum . A high-performance, heat-inducible biosensor was engineered by optimizing the CI 857 repressor and its cognate promoter, yielding a variant (CI 857 -M3/H1) with a 107-fold dynamic range and minimal background leakage. Additionally, a cold-inducible RNA thermometer was implemented using the Escherichia coli csapA 5'UTR. These components were integrated into a dual-functional genetic circuit enabling bidirectional metabolic control. Finally, the optimized heat-inducible sensor was applied to the production of three secretory proteins with distinct characteristics (AmyE, XylA, and VHH), and the scale-up cultivation of AmyE was successfully achieved in 1-L shake-flasks. This work provides an efficient, inducer-free strategy for precise metabolic regulation, offering a scalable and cost-effective tool for advanced biomanufacturing. Thermosensitive biosensor Dynamic metabolic regulation Corynebacterium glutamicum Recombinant protein production Synthetic biology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Highlights Engineered a high-performance thermosensitive biosensor in C. glutamicum . Identified a novel RNA thermometer ( csapA 5'UTR) for cold-inducible gene regulation. Created a dual-temperature-responsive genetic circuit for bidirectional metabolic control. Demonstrated the sensor’s utility in inducer-free production of diverse recombinant proteins. Introduction With the advancement of synthetic biology, microbial cell factories have emerged as a green manufacturing platform for the production of bulk chemicals, proteins, natural products, and more [ 1 , 2 ]. Traditional metabolic engineering strategies often rely on static regulation which can achieve through one-time, heritable modifications such as knocking out competing pathways, overexpressing key enzymes, or promoter engineering to irreversibly channel metabolic flux toward the desired product[ 3 ]. However, this approach has significant limitations that can easily disrupt intracellular metabolic networks, leading to metabolic imbalance and the accumulation of intermediates and byproducts resulting in suboptimal production efficiency and yield[ 4 , 5 ]. Therefore, developing more intelligent metabolic regulation strategies is key to the rational design and efficient operation of cell factories[ 6 ]. To overcome the limitations of static regulation, dynamic metabolic regulation strategies have emerged, centered on the introduction of feedback control loops[ 7 ]. These systems enable the real-time, automatic reprogramming of metabolic flux in response to physiological or environmental cues, thereby achieving a dynamic balance and spatiotemporal decoupling of growth and production[ 8 ]. Based on the nature of the sensed signal, dynamic regulation systems are primarily categorized as follows. Sensors based on intracellular metabolites[ 9 ], such as transcription factors responsive to cofactors or pathway intermediates, provide the most direct metabolic feedback but often face challenges like insufficient specificity and poor orthogonality. Systems relying on exogenous chemical inducers[ 10 ], exemplified by tetracycline or IPTG induction, offer precise control and a broad dynamic range, yet their high cost and potential incompatibility with large-scale production remain significant drawbacks. Alternatively, systems utilizing physical signals, including optogenetic and thermosensitive control, present distinct profiles. Optogenetics[ 11 , 12 ] affords exceptional spatiotemporal resolution but is hampered by complex equipment requirements and limited light penetration in fermentation broths. In contrast, temperature stands out as a traceless, inexpensive, and easily monitored and controlled macro-scale parameter, demonstrating unique practical advantages for industrial fermentation scale-up, making it a particularly promising signal for dynamic control[ 13 ]. As an ideal signal for dynamic regulation, the application of temperature relies on thermosensitive biosensors[ 14 , 15 ]. The core components of these sensors are thermosensitive proteins whose conformation or activity undergoes reversible changes in response to temperature, thereby regulating downstream gene expression. Research in this field has been highly active in recent years. For instance, the thermosensitive transcriptional repressor CI 857 from bacteriophage lambda has been utilized to construct a heat-inducible expression system in Escherichia coli ( E. coli )for controlling protein production and metabolic pathways[ 16 ]. Similarly, the heat-shock RNA polymerase[ 17 ] from Rhodothermus marinus and its corresponding promoter system have been developed as a versatile tool for high-temperature induction. Beyond heat induction, cold-inducible systems based on cold-shock proteins have also been reported[ 18 ]. These systems have been successfully applied in dynamic regulation. For example, Li et al. enhanced the thermal stability of the CI 857 repressor through protein engineering (L185P mutation) and constructed an efficient temperature-responsive switch[ 19 ]. This system successfully enabled dynamic control of pyruvate derivative synthesis in E. coli , increasing production yield several-fold. These findings demonstrate that thermosensitive biosensors are a powerful tool for achieving efficient and low-cost dynamic metabolic regulation. However, the development of such efficient and industrially scalable thermosensitive regulatory tools remains limited in the important industrial workhorse[ 20 ], Corynebacterium glutamicum ( C. glutamicum ). C. glutamicum is a premier chassis cell for producing amino acids, organic acids, and recombinant proteins, owing to its high metabolic efficiency, amenability to genetic manipulation, strong protein secretion capacity, and Generally Recognized as Safe (GRAS) status[ 21 ]. Therefore, to address this gap, this study first aims to develop a high-performance, heat-inducible gene expression system based on the classic thermosensitive repressor CI 857 . This will be achieved by optimizing its expression, regulatory elements, and screening mutant libraries to attain high sensitivity, low leakage, and a wide dynamic range. Subsequently, a cold-inducible biosensor based on the cspA 5’UTR RNA thermometer will be screened and validated in C. glutamicum , followed by the construction of a dual-functional, temperature-responsive genetic circuit. Finally, the applicability of this system will be demonstrated by dynamically regulating the secretory production of Recombinant proteins in C. glutamicum , validating its effectiveness in balancing cell growth and product synthesis. This work not only expands the dynamic regulation tool for C. glutamicum but also provides a reference for developing intelligent dynamic metabolic control strategies in other industrial microorganisms. Material and methods Strains and Culture Conditions The strains utilized in this study are listed in Table 1 . E.coli DH5α was cultured at 37°C in LBB medium, composed of 5 g/L yeast extract, 10 g/L peptone, 10 g/L brain heart infusion, and 10 g/L NaCl. In the present study, E.coli DH5α was used for recombinant plasmid construction. C. glutamicum ATCC13032 was cultivated at 30°C in LBHis medium, containing 2.5 g/L yeast extract, 5 g/L peptone, 5 g/L NaCl, 18.5 g/L brain heart infusion, and 91 g/L sorbitol. In the present study, C. glutamicum ATCC13032 was used for gene expression and protein production. When necessary, specific antibiotics were added to the culture media to maintain plasmid stability, at final concentrations of 50µg/mL or 25µg/mL kanamycin and 30µg/mL or 10µg/mL chloramphenicol. Table 1 Strains used in this study Strains Characteristics Source E.coli DH5α The cloning host This lab C.glutamicum ATCC 13032 Wild type This lab CH C.glutamicum ATCC13032 , the P RM -CI 857 expression cassette was integrated into the genome. This study Plasmid Construction All primers used in this study are listed in Table 2 . The pXMJ19 plasmid was utilized for constructing the heat-inducible gene expression system, while the pEC plasmid was used for the cold-inducible system. Genomic integration of the CI 857 gene was performed according to a previously described method. Briefly, upstream and downstream homologous arms (each 1000 base pairs) flanking the target genomic locus, along with a DNA fragment containing the P RM -CI 857 expression cassette, were amplified by polymerase chain reaction (PCR). These amplified fragments were then fused by overlap extension PCR and subsequently recombined with the linearized pk18mobsacB vector[ 22 ]. The resulting plasmid was introduced into C.glutamicum ATCC13032 via electroporation. Positive integrants were obtained through two rounds of selection: first on media supplemented with 20% (w/v) sucrose, followed by counter-selection on media containing 25 µg/mL kanamycin. Table 2 Plasmids used in this study Plasmids Characteristics Source pXMJ19- mCherry Cm r , expression of the red fluorescent protein This lab pEC- egfp Kan r , expression of the green fluorescent protein This lab pk18mobsacB Kan r , sacB, for genomic integration and gene deletion in C.glutamicum . This lab pWT pXMJ19- mCherry derived plasmid, containing the CI 857 -P RM expression cassette This study pP1 pWT derived plasmid, promoter replace with the P1 promoter This study pP2 pWT derived plasmid, promoter replace with the P2 promoter This study pP3 pWT derived plasmid, promoter replace with the P3 promoter This study pH1 pWT derived plasmid, promoter replace with the H1 promoter This study pH2 pWT derived plasmid, promoter replace with the H2 promoter This study pH3 pWT derived plasmid, promoter replace with the H3 promoter This study pORD0/1/2/3/4 pH1 derived plasmid, knockout of OR2(CGTGC) This study pCM0 pH1 derived plasmid, CI 857 L185P This study pCM pH1 derived plasmid, CI 857 A83QE176S This study pUG pXMJ19- cspA 5’UTR - mCherry This study pUGD ± 10/20/30/40 pUG derived plasmid, knockout of 5' UTRs with different lengths This study pUR pEC- cspA 5’UTR- egfp pk18-857 help the CI 857 -P RM expression cassette into genome This study pH-A/X/V for the expression of amyE, xylA, vhh under the control of the H1 promoter This study pI-A/X/V for IPTG-inducible expression of amyE, xylA, vhh , This study Construction and Screening of the Mutant Library To construct the CI 857 mutant library, the plasmid pH1 was used as the template. DNA fragments containing the gene of interest were amplified by PCR using primer pairs respectively. Error-prone PCR was performed using the QuickMutation™ Random Mutagenesis Kit (Beyotime, China) according to the manufacturer's instructions to introduce random mutations. Subsequently, the parental plasmid template was digested with Dpn I at 37°C for 2 hours. The mutated PCR products were then ligated to generate the CI 857 mutant library. This library was transformed into E. coli DH5α competent cells (Takara, Japan). Transformed cells were cultured, and plasmids were extracted to obtain the mutant plasmid library for subsequent screening. To screen for thermosensitive variants with distinct activation thresholds, recombinant C. glutamicum ATCC13032 strains harboring the mutant plasmid library were inoculated into 10 mL of liquid LBB medium and cultured at 30°C with shaking at 220 rpm for 12 hours. Subsequently, the cultures were sub-inoculated at a 1% (v/v) ratio into 50 mL of fresh liquid LBB medium and incubated for 24 hours at specified temperature gradients to induce differential expression. Following induction, 1 mL of each culture was harvested, washed three times with 1× PBS, and the cell density was adjusted to an OD₆₀₀ of 0.3–0.4 for analysis. Finally, the cells were analyzed and sorted using a flow cytometer (BD FACSAria™ III, USA) to isolate populations exhibiting the desired fluorescence profiles. Fluorescent Protein Characterization To validate the functionality of the thermosensitive biosensors in C. glutamicum , recombinant strains harboring the respective expression plasmids were first inoculated into liquid LBB medium and cultured at 30°C for 10 hours. Subsequently, the cultures were sub-inoculated at a 1% (v/v) ratio into a 96-well fluorescence plate containing 500 µL of LBB medium supplemented with chloromycin per well. The plate was then incubated under different temperature gradients for 24 hours. Finally, cell growth (OD₆₀₀) and fluorescence intensities were measured using a Cytation multi-mode microplate reader (BioTek, USA). The fluorescence of mCherry was measured at excitation/emission wavelengths of 575 nm and 615 nm, respectively, while EGFP fluorescence was measured at 485 nm and 535 nm. The relative fluorescence unit (RFU) was defined as the background-subtracted fluorescence intensity divided by the background-subtracted OD₆₀₀ value. Fermentation Conditions Shake flask fermentation: A single colony was selected and inoculated into 2 mL of liquid LBB medium, followed by overnight cultivation at 30℃with shaking at 220 rpm. The seed culture was then used for inoculation at a 5% inoculum ratio into a 1 L baffled shake flask containing 200 mL of CGXII fermentation medium. The fermentation was carried out at 30℃and 220 rpm for 10 hours. Subsequently, the culture was either shifted to 37℃ to induce temperature-sensitive expression or supplemented with IPTG (for comparative control) and continued for an additional 24 hours before sampling. CGXII medium: A protocatechuic acid stock (30 mg/mL) was prepared by dissolving 300 mg of the compound in 1 mL of 1 M NaOH and adjusting the volume to 10 mL with ddH 2 O, followed by aliquoting and storage at -20℃. A 1000×trace elements stock solution containing FeSO 4 ·7ddH 2 O (10 g/L), MnSO 4 ·H 2 O (10 g/L), ZnSO 4 ·7H 2 O (1 g/L), CuSO 4 ·5H 2 O (0.313 g/L), and NiCl 2 ·6H 2 O (0.02 g/L) was prepared in ddH 2 O, adjusted to pH 1.0 with HCl, filter-sterilized, and stored at 4℃. Separate 1000×stock solutions of MgSO 4 , CaCl 2 , and biotin were made by dissolving 12.5 g of MgSO 4 ·7H 2 O, 665 mg of CaCl 2 , and 10 mg of biotin, each in 50 mL of sterile water. For the CGXII basal medium, 20 g (NH 4 ) 2 SO 4 , 5 g urea, 42 g MOPS, 1 g KH 2 PO 4 , and 1 g K 2 HPO 4 were dissolved in approximately 700 mL ddH 2 O; then, 1 mL each of the CaCl 2 , MgSO 4 , and biotin stock solutions were added. The pH was adjusted to 7.0 with KOH, and the volume was brought to 960 mL with ddH 2 O. Complete CGXII medium was prepared fresh by combining 960 mL of this basal solution with 40 mL of 50% (w/v) sucrose and 1 mL of the 1000×trace elements stock solution, upon which a characteristic color change from pale yellow to pink/violet was observed. Protein Sample Preparation and α-Amylase Activity Assay Following fermentation, C. glutamicum cultures were centrifuged at 10,000 rpm and 4°C for 10 minutes to collect the supernatant. α-Amylase (AmyE) activity was determined using the 3,5-dinitrosalicylic acid (DNS) method[ 23 ]. Briefly, appropriately diluted enzyme solution was incubated with 1% (w/v) soluble starch substrate (in 50 mM sodium phosphate buffer, pH 6.8) at 37°C for 10 min. The reaction was terminated by adding DNS reagent, followed by heating in a boiling water bath for 5 min for color development. After cooling, the absorbance was measured at 540 nm. One unit of enzyme activity was defined as the amount of enzyme required to release 1 µmol of reducing sugar (expressed as glucose equivalent) per minute under the described conditions. A standard curve was prepared using known concentrations of glucose for quantification. Results and discussion Construction, Optimization, and Characterization of a CI 857 -Based Thermosensitive Biosensor To develop a thermosensitive gene expression tool applicable to C. glutamicum , this study first constructed a foundational biosensor based on the λ phage-derived thermosensitive transcriptional repressor CI 857 . At the permissive temperature (e.g., 30°C), the CI 857 protein binds specifically as an active dimer to the operator sequences (OR) within the target promoter P R , effectively repressing the transcription of downstream genes. When the temperature is elevated to the induction temperature (e.g., 40°C), the CI 857 protein undergoes a conformational change and dissociates, thereby relieving repression and activating gene expression[ 24 , 25 ]. Based on this principle, a foundational thermoregulated genetic circuit was constructed by co-localizing the CI 857 gene and the reporter gene mCherry on the pXMJ19 plasmid. Characterization of this basic sensor (Fig. 1 b) revealed low background expression at 30°C, with a RFU of only 48. Upon temperature upshift to 40°C, the reporter gene was strongly induced, achieving an RFU of 3217, corresponding to an induction fold (dynamic range) of approximately 67. This result confirms the temperature-responsive functionality of the CI 857 /P R system in C. glutamicum . However, it is noteworthy that the fluorescence intensity did not reach a plateau even at the inducing condition of 40°C, suggesting that the CI 857 protein may not be fully inactivated and likely retains a partial repressive effect on transcription, thereby limiting the maximal expression output of the system. To optimize the sensor's performance, the known constitutive strong promoters H 36 and P tac from C. glutamicum was selected. The CI 857 binding sequences OR1 and OR2 were precisely inserted, in various combinations and orientations, into key regulatory regions of these promoters—including the − 35 box, the − 10 box, and the transcription start site (+ 1)—to construct a series of hybrid promoter variants (Fig. 1 c). By systematically comparing the reporter gene expression levels of all these variants at different temperatures, a top-performing sensor variant was identified, designated H1 (Fig. 1 d). Compared to the original P R promoter system, the H1 sensor exhibited improvement in specific performance metrics. At 30°C, its leaky expression was tightly repressed (RFU = 181), whereas at 40°C, its expression output reached the highest level at 17,241 RFU. The dynamic range of the H1 sensor was calculated to be substantially improved to 95-fold. These results indicate that rational promoter engineering can effectively enhance the induced expression level of the thermosensitive system without significantly increasing the background leakage, thereby achieving a superior on/off ratio. Given that previous studies have indicated a high degree of sequence conservation in the OR2 region (CGTGC) of the CI 857 binding sequence[ 13 ], it has been hypothesized that this region is crucial for the repressor's thermal sensitivity. To investigate the fine-tuning role of this region on sensor performance, specific base-pair deletion mutations into the OR2 region were introduced within the optimized H1 sensor. However, characterization results (Fig. 1 e) revealed that, compared to the wild-type OR2 sequence, these deletion mutants did not further increase the response threshold of CI 857 or significantly alter its temperature-expression response profile. Screening of High-Performance CI 857 Mutants Although the engineered H1 sensor achieved a high dynamic range, its background (leaky) expression at 30°C (181 RFU) was elevated compared to the wild-type PR system (48 RFU). To develop a sensor with lower leakage and a higher signal-to-noise ratio, this research focused on optimizing the core regulatory component, the CI 857 protein itself. First, the reported mutant CI 857 L185P was introduced[ 19 ], which has been suggested to enhance DNA-binding stability and reduce leakage. However, in C. glutamicum , this mutant did not significantly improve the leakage level of the H1 sensor (Fig. 2 b), indicating that the effect of this mutation may be host-specific. To specifically obtain optimized mutants suitable for C. glutamicum , an error-prone PCR technique was employed to introduce random mutations into the CI 857 gene, resulting in a mutant library with a capacity greater than 1.0×10⁴. A dual screening strategy based on fluorescence intensity was designed. First, fermentation was conducted at 37°C, and the top 1% of cells with the highest fluorescence intensity in the population were isolated using flow cytometry, aiming to enrich for mutants exhibiting partial dissociation and higher sensitivity near the physiological temperature. Subsequently, a secondary screen was performed on this enriched pool, where clones were cultured at 30°C and those with the lowest fluorescence intensity were selected to stringently identify mutants with low leakage expression. Through this sequential "high-low" screening, combined with verification via 96-well plate fermentation(Fig. 2 a) and the subsequent reconstruction of the mutant, a strain with significantly optimized performance was obtained (Fig. 2 b). This strain exhibited mitigated leakage expression at 30°C (144 RFU) while largely maintaining reporter gene expression intensity at 40°C (15,402 RFU), leading to a further expanded dynamic range of 107. Sequencing of the CI 857 gene from this strain revealed amino acid substitutions at three positions in the coding region (A82Q, E176S). This triple mutant (designated CI 857 -M) was reassembled into the H1 sensor circuit, and its performance was validated via flow cytometry, as shown in Fig. 2 c. Given its superior performance, the CI 857 -M mutant was utilized for all subsequent experiments. Identification of a Cold-Inducible RNA Thermometer and Construction of a Dual-Functional Thermosensitive Genetic Circuit Compared to heat-inducible systems, cold-inducible biosensors suitable for C. glutamicum remain underdeveloped, although low temperature is good for promoting the correct folding of recombinant proteins, reducing the formation of inclusion bodies, and keeping the stability of bioactive molecules[ 26 ]. In this study, the 5' untranslated region (5' UTR) of the cspA gene, encoding a major cold shock protein, was identified through screening as a functional RNA thermometer. At low temperatures (e.g., 30°C), its mRNA secondary structure is altered, exposing the ribosome binding site and thereby activating the translation of downstream genes. Conversely, at elevated temperatures (e.g., 37°C), this structure closes, repressing gene expression[ 27 ]. First, its thermoregulatory function was validated in a reporter system based on the pXMJ19-mCherry plasmid, as shown in Fig. 3 a, the dynamic range was determined to be only 1.44 across the temperature shift from 30°C to 37°C, with a relatively high level of leakage observed. Nevertheless, the successful characterization of the cold-inducible biosensor still provides a feasible solution for constructing a temperature-mediated control system capable of activating and repressing multiple metabolic nodes, thereby enabling better redirection of intracellular metabolic flux. Subsequently, through systematic base-pair deletion mutagenesis, a core region approximately 64 base pairs in length, essential for its temperature-sensing function, was identified (Fig. 3 b). The identification of this core element laid the foundation for constructing a streamlined and efficient cold-inducible tool. Based on the aforementioned research, a dual-channel genetic circuit integrating both heat- and cold-inducible functions was successfully constructed (Fig. 3 c). This circuit combined the optimized heat-inducible subsystem (based on the genomically integrated CI 857 -M mutant and the H1 promoter) with the cold-inducible subsystem (based on the core cspA 5’UTR element). The red fluorescent protein (mCherry) and the green fluorescent protein (eGFP) were employed as reporter genes for parallel characterization. As shown in Fig. 3 d, within a single cultivation system, this platform achieved precise discrimination and response to temperature signals: at the elevated temperature (37°C), the red fluorescence channel was predominantly activated, while at the lower temperature (30°C), the green fluorescence channel was mainly induced. Under the low-temperature condition of 30°C, the relative fluorescence intensity from the red channel was only 0.4% of that from the green channel, meeting the criterion for orthogonality. This result indicates that a versatile biosensing platform capable of temperature-programmable, bidirectional regulation in C. glutamicum was successfully created. However, its practical utility at the elevated temperature of 37°C was compromised by a high leakage level associated with the cold-inducible system. Therefore, in future studies, the performance of the cold-inducible thermosensitive biosensor could be enhanced by employing strategies such as adjusting the stem-loop structure of the cspA 5'UTR through site-directed mutagenesis or constructing random mutant libraries for high-throughput screening, thereby improving its application potential. Validation of the Heat-Inducible Biosensor for Recombinant Protein Production in C. glutamicum To validate the efficacy of the optimized heat-inducible biosensor (CI 857 -M3/H1) in practical production, it was applied to induce the expression of three recombinant proteins with distinct characteristics and values, including the secretory α-amylase (AmyE), xylosidase (XylA) and nanobody (VHH). Corresponding expression plasmids were constructed by placing each target gene under the control of the optimized sensor and transforming them into C. glutamicum . A standard two-stage fermentation strategy was employed: cell growth was first carried out at the permissive temperature (30°C), followed by a rapid shift to the induction temperature (37°C) upon reaching mid-log phase to activate high-level expression of the target proteins. The expression of the target proteins was confirmed by SDS-PAGE, with their expected molecular sizes established from previous laboratory results[ 28 ], and a comparison with the results achieved under IPTG induction is shown in Fig. 4 b. In summary, the optimized heat-inducible sensor demonstrates strong driving capacity and broad versatility in the production of three distinct proteins. Application of Optimized Biosensors for AmyE Production in 1-L Shake-Flask Cultivation To evaluate the scalability and comparative performance of the engineered genetic tools, the production of α-amylase (AmyE) was conducted in a 1-L shake flask using the optimized thermosensitive biosensor (CI 857 -M3/H1) and a conventional IPTG-inducible system as a control. A time-course analysis was performed, where samples were periodically withdrawn to monitor cell growth (OD₆₀₀) and extracellular amylase activity. As shown in Fig. 5 a, upon activation by a temperature shift from 30°C to 37°C at 10 hours post-inoculation, the strain induced by the thermosensitive sensor reached a peak extracellular amylase activity of 100 U/mL at the 28-hour sampling point. This represented a 78% increase compared to the peak activity (56 U/mL) achieved by the IPTG-induced strain. Meanwhile, the OD₆₀₀ levels were maintained at comparable levels between the two induction systems. Furthermore, protein samples from key time points were analyzed by SDS-PAGE, as shown in Fig. 5 b, which visually confirmed a marked increase in the secretion of AmyE from the 16-hour time point onward. Its two-stage control mode, growth at low temperature, production at high temperature, effectively decouples cell growth from product synthesis, significantly enhancing target protein activity while maintaining robust cell viability. These results fully affirm the potential of this engineered sensor as a reliable, efficient, and versatile tool for controlling protein expression in C. glutamicum . Conclusion This study established a suite of thermosensitive biosensors in C. glutamicum . Through protein and promoter engineering, we optimized a CI 857 -based heat-inducible sensor, achieving a dynamic range of 107-fold. The cspA 5'UTR sequence was identified and validated as a cold-inducible RNA thermometer, enabling the creation of a dual-functional, temperature-responsive genetic circuit. Application tests demonstrated that simple temperature shifts could efficiently drive the production of three distinct proteins, underscoring the versatility and industrial potential of this physical induction strategy. This study found that the application of heterologous regulatory elements, such as CI 857 , in C. glutamicum requires targeted re-optimization, highlighting the critical influence of the host cellular environment on the functionality of genetic circuits. The temperature-induction system developed here provides a control strategy that is completely free of chemical inducers, cost-effective, and readily scalable, thereby serving as a core tool for constructing smart cell factories and achieving spatiotemporal regulation of metabolic pathways. Future research could further elucidate the molecular mechanisms of the key mutants and explore how to utilize this sensor network to coordinate multi-target metabolic fluxes for the synthesis of structurally more complex chemicals. Declarations Ethics approval and consent to participate This article contains no studies with human participants or animals performed by any author. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was supported by the National Natural Science Foundation of China (No.22378167) and the Key Research and Development Project of Henan Province(251111310300). Author Contribution Haofei Xu : Investigation, Writing – original draft. Yanbo Li, Yiran Gan, Songzhou Liu, Bin Lin, Shijun Cen, Yankun Yang, Chunli Liu : Data curation, Investigation. 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Li Y, Liu M, Yang C, Zheng Y, Xu G, Fu H, Wang J. Engineering Temperature-Powered Synthetic Multilayer MolecularBioswitch for High-Level Pyruvate Derivative Production in Escherichia coli. ACS Synth Biol. 2025;14(7):3127–41. https://doi.org/10.1021/acssynbio.5c00269 . Ye Z, Wang S, Wang Q, Ouyang L, Li Y, Zhang L. Engineering Dual-Input Glucose- and Temperature-Sensitive Lysis Circuits in Corynebacterium glutamicum for Efficient Intracellular Product Recovery. Microorganisms. 2025;13(12):2758. https://doi.org/10.3390/microorganisms13122758 . Liu J, Zhang W, Rao Z. Transcriptional regulator-based biosensors for biomanufacturing in Corynebacterium glutamicum. Microbiol Res. 2025;297:128169. https://doi.org/10.1016/j.micres.2025.128169 . Schäfer A, Tauch A, Jäger W, Kalinowski J, Thierbach G, Pühler A. Small mobilizable multi-purpose cloning vectors derived from the Escherichia coli plasmids pK18 and pK19: selection of defined deletions in the chromosome of Corynebacterium glutamicum. Gene. 1994;145(1):69–73. https://doi.org/10.1016/0378- 1119(94)90324-7 . Miller GL. Use of Dinitrosalicylic Acid Reagent for Determination of Reducing Sugar. Anal Chem. 1959;31(3):426–8. https://doi.org/10.1021/ac60147a030 . Wulff DL. The nature of the temperature-sensitive step in the CI857 repressor of bacteriophage λ. J Mol Biol. 1976;101(1):77–91. Valdez-Cruz NA, Caspeta L, Pérez NO, Ramírez OT, Trujillo-Roldán MA. Production of recombinant proteins in E. coli by the heat inducible expression system based on the phage lambda pL and/or pR promoters. Microb Cell Fact. 2010;9:18. https://doi.org/10.1186/1 475-2859-9-18. Zheng Y, Meng F, Zhu Z, Wei W, Sun Z, Chen J, Yu B, Lou C, Chen G-Q. A tight cold-inducible switch built by coupling thermosensitive transcriptional and proteolytic regulatory parts. Nucleic Acids Res. 2019;47(21):e137. https://doi.org/10.1093/nar/gkz785 . Kortmann J, Narberhaus F. Bacterial RNA thermometers: molecular zippers and switches. Nat Rev Microbiol. 2012;10(4):255–65. https://doi.org/10.1038/nrmicro2730 . Liu X, Li G, Cui S, Jiang M. Combinatorial tuning of 5′UTR and N-terminal coding sequences for enhanced recombinant protein expression in Corynebacterium glutamicum. ACS Synth Biol. 2025. https://doi.org/10.1021/acssynbio.5c00250 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-8832594","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":591805376,"identity":"156dd6cc-f2c9-4c89-9867-c120cdc5070a","order_by":0,"name":"Haofei Xu","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Haofei","middleName":"","lastName":"Xu","suffix":""},{"id":591805377,"identity":"5563c4ea-5c28-4c17-8f10-aed43ba0812c","order_by":1,"name":"Yanbo Li","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Yanbo","middleName":"","lastName":"Li","suffix":""},{"id":591805380,"identity":"b9a370e0-e587-42c0-9908-572790cc64d3","order_by":2,"name":"Yiran Gan","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Yiran","middleName":"","lastName":"Gan","suffix":""},{"id":591805381,"identity":"b5da5e49-c3b9-4581-8e24-84a01d827fb6","order_by":3,"name":"Songzhou Liu","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Songzhou","middleName":"","lastName":"Liu","suffix":""},{"id":591805383,"identity":"27d3064a-8a14-48e2-8bc0-2f532da6d8ae","order_by":4,"name":"Bin Lin","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Lin","suffix":""},{"id":591805385,"identity":"931a8c29-eec8-44ff-9bd8-20aa88efbc1b","order_by":5,"name":"Shijun Cen","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Shijun","middleName":"","lastName":"Cen","suffix":""},{"id":591805386,"identity":"6ebe35e5-facc-46c9-a00a-b5efc4575488","order_by":6,"name":"Yankun Yang","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Yankun","middleName":"","lastName":"Yang","suffix":""},{"id":591805387,"identity":"da97e82b-1f2d-4505-8db1-75aad1ff3475","order_by":7,"name":"Chunli Liu","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Chunli","middleName":"","lastName":"Liu","suffix":""},{"id":591805388,"identity":"85367a00-3506-4765-8351-27b74fcdd9fd","order_by":8,"name":"Xiuxia Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIie2Pv0oDQRCHNxzcNXtuJxuiuVfYQ7AK+CqzBFLaBFJpOBCm8wFC/PMK2ojlHAumOVKfxOLSGzCdIgE3CEeK3CWl4H6wP5bh9zEMYw7HH+TAswGMcRYkQOWY1yh+qXDaVyl/EjbGtUrAT+UczZEYFXP6er48F+OkUSyQReKQtiseP1Eae1zOANLrbNKXb+TFt8ji0RiqlLjQ2OHMKhTii05y8FshMlCzSkWRRsmjV4J0ZZX7HILvHcrvFpUzMCFe6Ae7xatX/L6CaY/HGYA5RtKPub5q3kxl5S1CmKfm58CctSdZd7nAob7Lu+nH+6ATidZ2ZQO+bhj7GokNuau+JiAbw32aDofD8c/4AW0BXiY15Eo1AAAAAElFTkSuQmCC","orcid":"","institution":"Jiangnan University","correspondingAuthor":true,"prefix":"","firstName":"Xiuxia","middleName":"","lastName":"Liu","suffix":""},{"id":591805392,"identity":"db11c033-6474-4a55-940b-8a5e120a129b","order_by":9,"name":"Zhonghu Bai","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Zhonghu","middleName":"","lastName":"Bai","suffix":""}],"badges":[],"createdAt":"2026-02-09 16:23:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8832594/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8832594/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102936920,"identity":"5ad53076-4e3b-43ed-963d-0c1200c14f3b","added_by":"auto","created_at":"2026-02-18 16:27:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47042,"visible":true,"origin":"","legend":"\u003cp\u003eDesign, construction and optimization of the thermosensitive biosensor (a) Schematic of the plasmid construction based on the regulatory mechanism of the transcription factor CI\u003csup\u003e857\u003c/sup\u003e (b) Characterization of CI\u003csup\u003e857\u003c/sup\u003e function in \u003cem\u003eC. glutamicum\u003c/em\u003e with a CI\u003csup\u003e857\u003c/sup\u003e-knockout strain as control (c) Schematic of hybrid promoter construction (d) RFU of hybrid promoters in \u003cem\u003eC. glutamicum\u003c/em\u003e at different temperatures (e) RFU of promoters with OR2 sequence deletion mutations in \u003cem\u003eC. glutamicum\u003c/em\u003e at different temperatures\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8832594/v1/5bea7d2121a7a16221d3a1b8.png"},{"id":102936943,"identity":"d3fe957b-8648-4f2c-9b2a-e46d9b11eb14","added_by":"auto","created_at":"2026-02-18 16:27:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":29617,"visible":true,"origin":"","legend":"\u003cp\u003eScreening and validation of CI\u003csup\u003e857\u003c/sup\u003e mutants (a) RFU of two mutants CI\u003csup\u003e857 L185P\u003c/sup\u003e, CI\u003csup\u003e857\u003c/sup\u003e-M compared to wild-type CI\u003csup\u003e857\u003c/sup\u003e and CI\u003csup\u003e857\u003c/sup\u003e-H1 at 30, 32, 34, 37, and 40°C (b) Secondary screening in 96-well plates. Following two rounds of flow cytometry screening, 192 single colonies were selected for fermentation at 30 and 37°C with RFU determination (c) Flow cytometry analysis of mutant CI\u003csup\u003e857\u003c/sup\u003e-M fluorescence intensity. Top to bottom: 30, 32, 34, 37, 40 °C.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8832594/v1/7b7a50ade17c6ba482682206.png"},{"id":102936917,"identity":"daae6842-ec25-400a-b7fe-a11c7a3b5533","added_by":"auto","created_at":"2026-02-18 16:27:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":29298,"visible":true,"origin":"","legend":"\u003cp\u003eConstruction and characterization of a cold-inducible biosensor and a dual-functional thermosensitive genetic circuit (a) Functional characterization of the cspA 5' UTR in \u003cem\u003eC. glutamicum\u003c/em\u003e (b) Validation of the core region of the cspA 5' UTR. RFU of a 64-bp fragment (obtained by deleting 40 bp from the upstream and 30 bp from the downstream of the original cspA 5' UTR) at 23, 30, and 37°C and of 64-bp (L) and (R) fragments (obtained by deleting 50 bp upstream and 40 bp downstream) under the same conditions (c) Schematic of the dual-functional thermosensitive genetic circuit construction (d) RFU of the dual-functional genetic circuit in \u003cem\u003eC. glutamicum\u003c/em\u003eat 28, 30, 32, 34, and 37°C\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8832594/v1/f984d8214858b3182a78ed5c.png"},{"id":102936931,"identity":"aa76064d-eea5-4cab-8c30-bb14d2075d55","added_by":"auto","created_at":"2026-02-18 16:27:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":90846,"visible":true,"origin":"","legend":"\u003cp\u003eProduction of three secretory proteins induced by the thermosensitive biosensor versus the IPTG system (a) Schematic of the expression plasmid construction for the three proteins (b) SDS-PAGE analysis. Lane M: protein molecular weight marker\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8832594/v1/b340f2a1b0e22453a9a0208f.png"},{"id":102936919,"identity":"61008885-53dd-4719-b854-61fba9fe00fd","added_by":"auto","created_at":"2026-02-18 16:27:00","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":73813,"visible":true,"origin":"","legend":"\u003cp\u003eThermosensitive biosensor and IPTG induction for AmyE fermentation (a) Growth curves and the AmyE enzyme activity in the culture supernatant (b)SDS-PAGE analysis of the purified AmyE. The upper panel shows temperature induction, and the lower panel shows IPTG induction. Lane M: protein markers; Lanes 1-13;samples were taken at 4,8,12,16 20 24 28 32 36 40 44, 48and 52h respectively\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8832594/v1/d4555dd00f70e67132325efb.png"},{"id":102964233,"identity":"3deffc73-92bb-4f22-9f76-c624d0cf16b1","added_by":"auto","created_at":"2026-02-19 04:21:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1268874,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8832594/v1/10ec0529-e55f-40aa-920d-5f238f67cf1f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Engineering a Temperature-Programmable Biosensor Toolkit for Recombinant Protein Production in Corynebacterium glutamicum","fulltext":[{"header":"Highlights","content":"\u003cp\u003eEngineered a high-performance thermosensitive biosensor in \u003cem\u003eC. glutamicum\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eIdentified a novel RNA thermometer (\u003cem\u003ecsapA\u003c/em\u003e 5\u0026apos;UTR) for cold-inducible gene regulation.\u003c/p\u003e\n\u003cp\u003eCreated a dual-temperature-responsive genetic circuit for bidirectional metabolic control.\u003c/p\u003e\n\u003cp\u003eDemonstrated the sensor\u0026rsquo;s utility in inducer-free production of diverse recombinant proteins.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eWith the advancement of synthetic biology, microbial cell factories have emerged as a green manufacturing platform for the production of bulk chemicals, proteins, natural products, and more [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Traditional metabolic engineering strategies often rely on static regulation which can achieve through one-time, heritable modifications such as knocking out competing pathways, overexpressing key enzymes, or promoter engineering to irreversibly channel metabolic flux toward the desired product[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, this approach has significant limitations that can easily disrupt intracellular metabolic networks, leading to metabolic imbalance and the accumulation of intermediates and byproducts resulting in suboptimal production efficiency and yield[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, developing more intelligent metabolic regulation strategies is key to the rational design and efficient operation of cell factories[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo overcome the limitations of static regulation, dynamic metabolic regulation strategies have emerged, centered on the introduction of feedback control loops[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These systems enable the real-time, automatic reprogramming of metabolic flux in response to physiological or environmental cues, thereby achieving a dynamic balance and spatiotemporal decoupling of growth and production[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Based on the nature of the sensed signal, dynamic regulation systems are primarily categorized as follows. Sensors based on intracellular metabolites[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], such as transcription factors responsive to cofactors or pathway intermediates, provide the most direct metabolic feedback but often face challenges like insufficient specificity and poor orthogonality. Systems relying on exogenous chemical inducers[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], exemplified by tetracycline or IPTG induction, offer precise control and a broad dynamic range, yet their high cost and potential incompatibility with large-scale production remain significant drawbacks. Alternatively, systems utilizing physical signals, including optogenetic and thermosensitive control, present distinct profiles. Optogenetics[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] affords exceptional spatiotemporal resolution but is hampered by complex equipment requirements and limited light penetration in fermentation broths. In contrast, temperature stands out as a traceless, inexpensive, and easily monitored and controlled macro-scale parameter, demonstrating unique practical advantages for industrial fermentation scale-up, making it a particularly promising signal for dynamic control[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs an ideal signal for dynamic regulation, the application of temperature relies on thermosensitive biosensors[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The core components of these sensors are thermosensitive proteins whose conformation or activity undergoes reversible changes in response to temperature, thereby regulating downstream gene expression. Research in this field has been highly active in recent years. For instance, the thermosensitive transcriptional repressor CI\u003csup\u003e857\u003c/sup\u003e from bacteriophage lambda has been utilized to construct a heat-inducible expression system in \u003cem\u003eEscherichia coli\u003c/em\u003e(\u003cem\u003eE. coli\u003c/em\u003e)for controlling protein production and metabolic pathways[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Similarly, the heat-shock RNA polymerase[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] from \u003cem\u003eRhodothermus marinus\u003c/em\u003e and its corresponding promoter system have been developed as a versatile tool for high-temperature induction. Beyond heat induction, cold-inducible systems based on cold-shock proteins have also been reported[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These systems have been successfully applied in dynamic regulation. For example, Li et al. enhanced the thermal stability of the CI\u003csup\u003e857\u003c/sup\u003e repressor through protein engineering (L185P mutation) and constructed an efficient temperature-responsive switch[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This system successfully enabled dynamic control of pyruvate derivative synthesis in \u003cem\u003eE. coli\u003c/em\u003e, increasing production yield several-fold. These findings demonstrate that thermosensitive biosensors are a powerful tool for achieving efficient and low-cost dynamic metabolic regulation.\u003c/p\u003e \u003cp\u003eHowever, the development of such efficient and industrially scalable thermosensitive regulatory tools remains limited in the important industrial workhorse[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], \u003cem\u003eCorynebacterium glutamicum\u003c/em\u003e(\u003cem\u003eC. glutamicum\u003c/em\u003e). \u003cem\u003eC. glutamicum\u003c/em\u003e is a premier chassis cell for producing amino acids, organic acids, and recombinant proteins, owing to its high metabolic efficiency, amenability to genetic manipulation, strong protein secretion capacity, and Generally Recognized as Safe (GRAS) status[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Therefore, to address this gap, this study first aims to develop a high-performance, heat-inducible gene expression system based on the classic thermosensitive repressor CI\u003csup\u003e857\u003c/sup\u003e. This will be achieved by optimizing its expression, regulatory elements, and screening mutant libraries to attain high sensitivity, low leakage, and a wide dynamic range. Subsequently, a cold-inducible biosensor based on the \u003cem\u003ecspA\u003c/em\u003e 5\u0026rsquo;UTR RNA thermometer will be screened and validated in \u003cem\u003eC. glutamicum\u003c/em\u003e, followed by the construction of a dual-functional, temperature-responsive genetic circuit. Finally, the applicability of this system will be demonstrated by dynamically regulating the secretory production of Recombinant proteins in \u003cem\u003eC. glutamicum\u003c/em\u003e, validating its effectiveness in balancing cell growth and product synthesis. This work not only expands the dynamic regulation tool for \u003cem\u003eC. glutamicum\u003c/em\u003e but also provides a reference for developing intelligent dynamic metabolic control strategies in other industrial microorganisms.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStrains and Culture Conditions\u003c/h2\u003e \u003cp\u003eThe strains utilized in this study are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cem\u003eE.coli DH5α\u003c/em\u003e was cultured at 37\u0026deg;C in LBB medium, composed of 5 g/L yeast extract, 10 g/L peptone, 10 g/L brain heart infusion, and 10 g/L NaCl. In the present study, \u003cem\u003eE.coli DH5α\u003c/em\u003e was used for recombinant plasmid construction. \u003cem\u003eC. glutamicum ATCC13032\u003c/em\u003e was cultivated at 30\u0026deg;C in LBHis medium, containing 2.5 g/L yeast extract, 5 g/L peptone, 5 g/L NaCl, 18.5 g/L brain heart infusion, and 91 g/L sorbitol. In the present study, \u003cem\u003eC. glutamicum ATCC13032\u003c/em\u003e was used for gene expression and protein production. When necessary, specific antibiotics were added to the culture media to maintain plasmid stability, at final concentrations of 50\u0026micro;g/mL or 25\u0026micro;g/mL kanamycin and 30\u0026micro;g/mL or 10\u0026micro;g/mL chloramphenicol.\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\u003eStrains 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\u003eStrains\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eE.coli DH5α\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe cloning host\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThis lab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC.glutamicum ATCC 13032\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWild type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThis lab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eC.glutamicum ATCC13032\u003c/em\u003e, the P\u003csub\u003eRM\u003c/sub\u003e-CI\u003csup\u003e857\u003c/sup\u003e expression cassette was integrated into the genome.\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 \u003c/div\u003e\n\u003ch3\u003ePlasmid Construction\u003c/h3\u003e\n\u003cp\u003eAll primers used in this study are listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The pXMJ19 plasmid was utilized for constructing the heat-inducible gene expression system, while the pEC plasmid was used for the cold-inducible system. Genomic integration of the CI\u003csup\u003e857\u003c/sup\u003e gene was performed according to a previously described method. Briefly, upstream and downstream homologous arms (each 1000 base pairs) flanking the target genomic locus, along with a DNA fragment containing the P\u003csub\u003eRM\u003c/sub\u003e-CI\u003csup\u003e857\u003c/sup\u003e expression cassette, were amplified by polymerase chain reaction (PCR). These amplified fragments were then fused by overlap extension PCR and subsequently recombined with the linearized pk18mobsacB vector[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The resulting plasmid was introduced into \u003cem\u003eC.glutamicum ATCC13032\u003c/em\u003e via electroporation. Positive integrants were obtained through two rounds of selection: first on media supplemented with 20% (w/v) sucrose, followed by counter-selection on media containing 25 \u0026micro;g/mL kanamycin.\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\u003ePlasmids 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\u003ePlasmids\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epXMJ19-\u003cem\u003emCherry\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCm\u003csup\u003er\u003c/sup\u003e, expression of the red fluorescent protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThis lab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epEC-\u003cem\u003eegfp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKan\u003csup\u003er\u003c/sup\u003e, expression of the green fluorescent protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThis lab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epk18mobsacB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKan\u003csup\u003er\u003c/sup\u003e, sacB, for genomic integration and gene deletion in \u003cem\u003eC.glutamicum\u003c/em\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThis lab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epWT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epXMJ19-\u003cem\u003emCherry\u003c/em\u003e derived plasmid, containing the CI\u003csup\u003e857\u003c/sup\u003e-P\u003csub\u003eRM\u003c/sub\u003e expression cassette\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\u003epP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epWT derived plasmid, promoter replace with the P1 promoter\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\u003epP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epWT derived plasmid, promoter replace with the P2 promoter\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\u003epP3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epWT derived plasmid, promoter replace with the P3 promoter\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\u003epH1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epWT derived plasmid, promoter replace with the H1 promoter\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\u003epH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epWT derived plasmid, promoter replace with the H2 promoter\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\u003epH3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epWT derived plasmid, promoter replace with the H3 promoter\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\u003epORD0/1/2/3/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH1 derived plasmid, knockout of OR2(CGTGC)\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\u003epCM0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH1 derived plasmid, CI\u003csup\u003e857 L185P\u003c/sup\u003e\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\u003epCM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH1 derived plasmid, CI\u003csup\u003e857 A83QE176S\u003c/sup\u003e\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\u003epUG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epXMJ19- \u003cem\u003ecspA\u003c/em\u003e 5\u0026rsquo;UTR -\u003cem\u003emCherry\u003c/em\u003e\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\u003epUGD\u0026thinsp;\u0026plusmn;\u0026thinsp;10/20/30/40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epUG derived plasmid, knockout of 5' UTRs with different lengths\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\u003epUR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epEC-\u003cem\u003ecspA\u003c/em\u003e 5\u0026rsquo;UTR-\u003cem\u003eegfp\u003c/em\u003e\u003c/p\u003e \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\u003epk18-857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehelp the CI\u003csup\u003e857\u003c/sup\u003e-P\u003csub\u003eRM\u003c/sub\u003e expression cassette into genome\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\u003epH-A/X/V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efor the expression of \u003cem\u003eamyE, xylA, vhh\u003c/em\u003e under the control of the H1 promoter\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\u003epI-A/X/V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efor IPTG-inducible expression of \u003cem\u003eamyE, xylA, vhh\u003c/em\u003e,\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\n\u003ch3\u003eConstruction and Screening of the Mutant Library\u003c/h3\u003e\n\u003cp\u003eTo construct the CI\u003csup\u003e857\u003c/sup\u003e mutant library, the plasmid pH1 was used as the template. DNA fragments containing the gene of interest were amplified by PCR using primer pairs respectively. Error-prone PCR was performed using the QuickMutation\u0026trade; Random Mutagenesis Kit (Beyotime, China) according to the manufacturer's instructions to introduce random mutations. Subsequently, the parental plasmid template was digested with \u003cem\u003eDpn\u003c/em\u003eI at 37\u0026deg;C for 2 hours. The mutated PCR products were then ligated to generate the CI\u003csup\u003e857\u003c/sup\u003e mutant library. This library was transformed into \u003cem\u003eE. coli DH5α\u003c/em\u003e competent cells (Takara, Japan). Transformed cells were cultured, and plasmids were extracted to obtain the mutant plasmid library for subsequent screening.\u003c/p\u003e \u003cp\u003eTo screen for thermosensitive variants with distinct activation thresholds, recombinant \u003cem\u003eC. glutamicum ATCC13032\u003c/em\u003e strains harboring the mutant plasmid library were inoculated into 10 mL of liquid LBB medium and cultured at 30\u0026deg;C with shaking at 220 rpm for 12 hours. Subsequently, the cultures were sub-inoculated at a 1% (v/v) ratio into 50 mL of fresh liquid LBB medium and incubated for 24 hours at specified temperature gradients to induce differential expression. Following induction, 1 mL of each culture was harvested, washed three times with 1\u0026times; PBS, and the cell density was adjusted to an OD₆₀₀ of 0.3\u0026ndash;0.4 for analysis. Finally, the cells were analyzed and sorted using a flow cytometer (BD FACSAria\u0026trade; III, USA) to isolate populations exhibiting the desired fluorescence profiles.\u003c/p\u003e\n\u003ch3\u003eFluorescent Protein Characterization\u003c/h3\u003e\n\u003cp\u003eTo validate the functionality of the thermosensitive biosensors in \u003cem\u003eC. glutamicum\u003c/em\u003e, recombinant strains harboring the respective expression plasmids were first inoculated into liquid LBB medium and cultured at 30\u0026deg;C for 10 hours. Subsequently, the cultures were sub-inoculated at a 1% (v/v) ratio into a 96-well fluorescence plate containing 500 \u0026micro;L of LBB medium supplemented with chloromycin per well. The plate was then incubated under different temperature gradients for 24 hours. Finally, cell growth (OD₆₀₀) and fluorescence intensities were measured using a Cytation multi-mode microplate reader (BioTek, USA). The fluorescence of mCherry was measured at excitation/emission wavelengths of 575 nm and 615 nm, respectively, while EGFP fluorescence was measured at 485 nm and 535 nm. The relative fluorescence unit (RFU) was defined as the background-subtracted fluorescence intensity divided by the background-subtracted OD₆₀₀ value.\u003c/p\u003e\n\u003ch3\u003eFermentation Conditions\u003c/h3\u003e\n\u003cp\u003eShake flask fermentation: A single colony was selected and inoculated into 2 mL of liquid LBB medium, followed by overnight cultivation at 30℃with shaking at 220 rpm. The seed culture was then used for inoculation at a 5% inoculum ratio into a 1 L baffled shake flask containing 200 mL of CGXII fermentation medium. The fermentation was carried out at 30℃and 220 rpm for 10 hours. Subsequently, the culture was either shifted to 37℃ to induce temperature-sensitive expression or supplemented with IPTG (for comparative control) and continued for an additional 24 hours before sampling.\u003c/p\u003e \u003cp\u003eCGXII medium: A protocatechuic acid stock (30 mg/mL) was prepared by dissolving 300 mg of the compound in 1 mL of 1 M NaOH and adjusting the volume to 10 mL with ddH\u003csub\u003e2\u003c/sub\u003eO, followed by aliquoting and storage at -20℃. A 1000\u0026times;trace elements stock solution containing FeSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;7ddH\u003csub\u003e2\u003c/sub\u003eO (10 g/L), MnSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;H\u003csub\u003e2\u003c/sub\u003eO (10 g/L), ZnSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;7H\u003csub\u003e2\u003c/sub\u003eO (1 g/L), CuSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;5H\u003csub\u003e2\u003c/sub\u003eO (0.313 g/L), and NiCl\u003csub\u003e2\u003c/sub\u003e\u0026middot;6H\u003csub\u003e2\u003c/sub\u003eO (0.02 g/L) was prepared in ddH\u003csub\u003e2\u003c/sub\u003eO, adjusted to pH 1.0 with HCl, filter-sterilized, and stored at 4℃. Separate 1000\u0026times;stock solutions of MgSO\u003csub\u003e4\u003c/sub\u003e, CaCl\u003csub\u003e2\u003c/sub\u003e, and biotin were made by dissolving 12.5 g of MgSO\u003csub\u003e4\u003c/sub\u003e\u0026middot;7H\u003csub\u003e2\u003c/sub\u003eO, 665 mg of CaCl\u003csub\u003e2\u003c/sub\u003e, and 10 mg of biotin, each in 50 mL of sterile water. For the CGXII basal medium, 20 g (NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, 5 g urea, 42 g MOPS, 1 g KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, and 1 g K\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e were dissolved in approximately 700 mL ddH\u003csub\u003e2\u003c/sub\u003eO; then, 1 mL each of the CaCl\u003csub\u003e2\u003c/sub\u003e, MgSO\u003csub\u003e4\u003c/sub\u003e, and biotin stock solutions were added. The pH was adjusted to 7.0 with KOH, and the volume was brought to 960 mL with ddH\u003csub\u003e2\u003c/sub\u003eO. Complete CGXII medium was prepared fresh by combining 960 mL of this basal solution with 40 mL of 50% (w/v) sucrose and 1 mL of the 1000\u0026times;trace elements stock solution, upon which a characteristic color change from pale yellow to pink/violet was observed.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eProtein Sample Preparation and α-Amylase Activity Assay\u003c/h2\u003e \u003cp\u003eFollowing fermentation, \u003cem\u003eC. glutamicum\u003c/em\u003e cultures were centrifuged at 10,000 rpm and 4\u0026deg;C for 10 minutes to collect the supernatant.\u003c/p\u003e \u003cp\u003eα-Amylase (AmyE) activity was determined using the 3,5-dinitrosalicylic acid (DNS) method[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Briefly, appropriately diluted enzyme solution was incubated with 1% (w/v) soluble starch substrate (in 50 mM sodium phosphate buffer, pH 6.8) at 37\u0026deg;C for 10 min. The reaction was terminated by adding DNS reagent, followed by heating in a boiling water bath for 5 min for color development. After cooling, the absorbance was measured at 540 nm. One unit of enzyme activity was defined as the amount of enzyme required to release 1 \u0026micro;mol of reducing sugar (expressed as glucose equivalent) per minute under the described conditions. A standard curve was prepared using known concentrations of glucose for quantification.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eConstruction, Optimization, and Characterization of a CI\u003csup\u003e857\u003c/sup\u003e-Based Thermosensitive Biosensor\u003c/h2\u003e \u003cp\u003eTo develop a thermosensitive gene expression tool applicable to \u003cem\u003eC. glutamicum\u003c/em\u003e, this study first constructed a foundational biosensor based on the λ phage-derived thermosensitive transcriptional repressor CI\u003csup\u003e857\u003c/sup\u003e. At the permissive temperature (e.g., 30\u0026deg;C), the CI\u003csup\u003e857\u003c/sup\u003e protein binds specifically as an active dimer to the operator sequences (OR) within the target promoter P\u003csub\u003eR\u003c/sub\u003e, effectively repressing the transcription of downstream genes. When the temperature is elevated to the induction temperature (e.g., 40\u0026deg;C), the CI\u003csup\u003e857\u003c/sup\u003e protein undergoes a conformational change and dissociates, thereby relieving repression and activating gene expression[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Based on this principle, a foundational thermoregulated genetic circuit was constructed by co-localizing the CI\u003csup\u003e857\u003c/sup\u003e gene and the reporter gene mCherry on the pXMJ19 plasmid. Characterization of this basic sensor (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) revealed low background expression at 30\u0026deg;C, with a RFU of only 48. Upon temperature upshift to 40\u0026deg;C, the reporter gene was strongly induced, achieving an RFU of 3217, corresponding to an induction fold (dynamic range) of approximately 67. This result confirms the temperature-responsive functionality of the CI\u003csup\u003e857\u003c/sup\u003e/P\u003csub\u003eR\u003c/sub\u003e system in \u003cem\u003eC. glutamicum\u003c/em\u003e. However, it is noteworthy that the fluorescence intensity did not reach a plateau even at the inducing condition of 40\u0026deg;C, suggesting that the CI\u003csup\u003e857\u003c/sup\u003e protein may not be fully inactivated and likely retains a partial repressive effect on transcription, thereby limiting the maximal expression output of the system.\u003c/p\u003e \u003cp\u003eTo optimize the sensor's performance, the known constitutive strong promoters H\u003csub\u003e36\u003c/sub\u003e and P\u003csub\u003etac\u003c/sub\u003e from \u003cem\u003eC. glutamicum\u003c/em\u003e was selected. The CI\u003csup\u003e857\u003c/sup\u003e binding sequences OR1 and OR2 were precisely inserted, in various combinations and orientations, into key regulatory regions of these promoters\u0026mdash;including the \u0026minus;\u0026thinsp;35 box, the \u0026minus;\u0026thinsp;10 box, and the transcription start site (+\u0026thinsp;1)\u0026mdash;to construct a series of hybrid promoter variants (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). By systematically comparing the reporter gene expression levels of all these variants at different temperatures, a top-performing sensor variant was identified, designated H1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Compared to the original P\u003csub\u003eR\u003c/sub\u003e promoter system, the H1 sensor exhibited improvement in specific performance metrics. At 30\u0026deg;C, its leaky expression was tightly repressed (RFU\u0026thinsp;=\u0026thinsp;181), whereas at 40\u0026deg;C, its expression output reached the highest level at 17,241 RFU. The dynamic range of the H1 sensor was calculated to be substantially improved to 95-fold. These results indicate that rational promoter engineering can effectively enhance the induced expression level of the thermosensitive system without significantly increasing the background leakage, thereby achieving a superior on/off ratio.\u003c/p\u003e \u003cp\u003eGiven that previous studies have indicated a high degree of sequence conservation in the OR2 region (CGTGC) of the CI\u003csup\u003e857\u003c/sup\u003e binding sequence[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], it has been hypothesized that this region is crucial for the repressor's thermal sensitivity. To investigate the fine-tuning role of this region on sensor performance, specific base-pair deletion mutations into the OR2 region were introduced within the optimized H1 sensor. However, characterization results (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e1\u003c/span\u003ee) revealed that, compared to the wild-type OR2 sequence, these deletion mutants did not further increase the response threshold of CI\u003csup\u003e857\u003c/sup\u003e or significantly alter its temperature-expression response profile.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eScreening of High-Performance CI\u003csup\u003e857\u003c/sup\u003e Mutants\u003c/h2\u003e \u003cp\u003eAlthough the engineered H1 sensor achieved a high dynamic range, its background (leaky) expression at 30\u0026deg;C (181 RFU) was elevated compared to the wild-type PR system (48 RFU). To develop a sensor with lower leakage and a higher signal-to-noise ratio, this research focused on optimizing the core regulatory component, the CI\u003csup\u003e857\u003c/sup\u003e protein itself. First, the reported mutant CI\u003csup\u003e857 L185P\u003c/sup\u003e was introduced[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], which has been suggested to enhance DNA-binding stability and reduce leakage. However, in \u003cem\u003eC. glutamicum\u003c/em\u003e, this mutant did not significantly improve the leakage level of the H1 sensor (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), indicating that the effect of this mutation may be host-specific.\u003c/p\u003e \u003cp\u003eTo specifically obtain optimized mutants suitable for \u003cem\u003eC. glutamicum\u003c/em\u003e, an error-prone PCR technique was employed to introduce random mutations into the CI\u003csup\u003e857\u003c/sup\u003e gene, resulting in a mutant library with a capacity greater than 1.0\u0026times;10⁴. A dual screening strategy based on fluorescence intensity was designed. First, fermentation was conducted at 37\u0026deg;C, and the top 1% of cells with the highest fluorescence intensity in the population were isolated using flow cytometry, aiming to enrich for mutants exhibiting partial dissociation and higher sensitivity near the physiological temperature. Subsequently, a secondary screen was performed on this enriched pool, where clones were cultured at 30\u0026deg;C and those with the lowest fluorescence intensity were selected to stringently identify mutants with low leakage expression. Through this sequential \"high-low\" screening, combined with verification via 96-well plate fermentation(Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) and the subsequent reconstruction of the mutant, a strain with significantly optimized performance was obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). This strain exhibited mitigated leakage expression at 30\u0026deg;C (144 RFU) while largely maintaining reporter gene expression intensity at 40\u0026deg;C (15,402 RFU), leading to a further expanded dynamic range of 107. Sequencing of the CI\u003csup\u003e857\u003c/sup\u003e gene from this strain revealed amino acid substitutions at three positions in the coding region (A82Q, E176S). This triple mutant (designated CI\u003csup\u003e857\u003c/sup\u003e-M) was reassembled into the H1 sensor circuit, and its performance was validated via flow cytometry, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003ec. Given its superior performance, the CI\u003csup\u003e857\u003c/sup\u003e-M mutant was utilized for all subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of a Cold-Inducible RNA Thermometer and Construction of a Dual-Functional Thermosensitive Genetic Circuit\u003c/h2\u003e \u003cp\u003eCompared to heat-inducible systems, cold-inducible biosensors suitable for \u003cem\u003eC. glutamicum\u003c/em\u003e remain underdeveloped, although low temperature is good for promoting the correct folding of recombinant proteins, reducing the formation of inclusion bodies, and keeping the stability of bioactive molecules[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this study, the 5' untranslated region (5' UTR) of the \u003cem\u003ecspA\u003c/em\u003e gene, encoding a major cold shock protein, was identified through screening as a functional RNA thermometer. At low temperatures (e.g., 30\u0026deg;C), its mRNA secondary structure is altered, exposing the ribosome binding site and thereby activating the translation of downstream genes. Conversely, at elevated temperatures (e.g., 37\u0026deg;C), this structure closes, repressing gene expression[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. First, its thermoregulatory function was validated in a reporter system based on the pXMJ19-mCherry plasmid, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, the dynamic range was determined to be only 1.44 across the temperature shift from 30\u0026deg;C to 37\u0026deg;C, with a relatively high level of leakage observed. Nevertheless, the successful characterization of the cold-inducible biosensor still provides a feasible solution for constructing a temperature-mediated control system capable of activating and repressing multiple metabolic nodes, thereby enabling better redirection of intracellular metabolic flux. Subsequently, through systematic base-pair deletion mutagenesis, a core region approximately 64 base pairs in length, essential for its temperature-sensing function, was identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The identification of this core element laid the foundation for constructing a streamlined and efficient cold-inducible tool.\u003c/p\u003e \u003cp\u003eBased on the aforementioned research, a dual-channel genetic circuit integrating both heat- and cold-inducible functions was successfully constructed (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). This circuit combined the optimized heat-inducible subsystem (based on the genomically integrated CI\u003csup\u003e857\u003c/sup\u003e-M mutant and the H1 promoter) with the cold-inducible subsystem (based on the core \u003cem\u003ecspA\u003c/em\u003e 5\u0026rsquo;UTR element). The red fluorescent protein (mCherry) and the green fluorescent protein (eGFP) were employed as reporter genes for parallel characterization. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, within a single cultivation system, this platform achieved precise discrimination and response to temperature signals: at the elevated temperature (37\u0026deg;C), the red fluorescence channel was predominantly activated, while at the lower temperature (30\u0026deg;C), the green fluorescence channel was mainly induced. Under the low-temperature condition of 30\u0026deg;C, the relative fluorescence intensity from the red channel was only 0.4% of that from the green channel, meeting the criterion for orthogonality. This result indicates that a versatile biosensing platform capable of temperature-programmable, bidirectional regulation in \u003cem\u003eC. glutamicum\u003c/em\u003e was successfully created. However, its practical utility at the elevated temperature of 37\u0026deg;C was compromised by a high leakage level associated with the cold-inducible system. Therefore, in future studies, the performance of the cold-inducible thermosensitive biosensor could be enhanced by employing strategies such as adjusting the stem-loop structure of the \u003cem\u003ecspA\u003c/em\u003e 5'UTR through site-directed mutagenesis or constructing random mutant libraries for high-throughput screening, thereby improving its application potential.\u003c/p\u003e \u003cp\u003e \u003cb\u003eValidation of the Heat-Inducible Biosensor for Recombinant Protein Production in\u003c/b\u003e \u003cb\u003eC. glutamicum\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo validate the efficacy of the optimized heat-inducible biosensor (CI\u003csup\u003e857\u003c/sup\u003e-M3/H1) in practical production, it was applied to induce the expression of three recombinant proteins with distinct characteristics and values, including the secretory α-amylase (AmyE), xylosidase (XylA) and nanobody (VHH). Corresponding expression plasmids were constructed by placing each target gene under the control of the optimized sensor and transforming them into \u003cem\u003eC. glutamicum\u003c/em\u003e. A standard two-stage fermentation strategy was employed: cell growth was first carried out at the permissive temperature (30\u0026deg;C), followed by a rapid shift to the induction temperature (37\u0026deg;C) upon reaching mid-log phase to activate high-level expression of the target proteins. The expression of the target proteins was confirmed by SDS-PAGE, with their expected molecular sizes established from previous laboratory results[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and a comparison with the results achieved under IPTG induction is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003eb. In summary, the optimized heat-inducible sensor demonstrates strong driving capacity and broad versatility in the production of three distinct proteins.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eApplication of Optimized Biosensors for AmyE Production in 1-L Shake-Flask Cultivation\u003c/h2\u003e \u003cp\u003eTo evaluate the scalability and comparative performance of the engineered genetic tools, the production of α-amylase (AmyE) was conducted in a 1-L shake flask using the optimized thermosensitive biosensor (CI\u003csup\u003e857\u003c/sup\u003e-M3/H1) and a conventional IPTG-inducible system as a control. A time-course analysis was performed, where samples were periodically withdrawn to monitor cell growth (OD₆₀₀) and extracellular amylase activity. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, upon activation by a temperature shift from 30\u0026deg;C to 37\u0026deg;C at 10 hours post-inoculation, the strain induced by the thermosensitive sensor reached a peak extracellular amylase activity of 100 U/mL at the 28-hour sampling point. This represented a 78% increase compared to the peak activity (56 U/mL) achieved by the IPTG-induced strain. Meanwhile, the OD₆₀₀ levels were maintained at comparable levels between the two induction systems. Furthermore, protein samples from key time points were analyzed by SDS-PAGE, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, which visually confirmed a marked increase in the secretion of AmyE from the 16-hour time point onward. Its two-stage control mode, growth at low temperature, production at high temperature, effectively decouples cell growth from product synthesis, significantly enhancing target protein activity while maintaining robust cell viability. These results fully affirm the potential of this engineered sensor as a reliable, efficient, and versatile tool for controlling protein expression in \u003cem\u003eC. glutamicum\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study established a suite of thermosensitive biosensors in \u003cem\u003eC. glutamicum\u003c/em\u003e. Through protein and promoter engineering, we optimized a CI\u003csup\u003e857\u003c/sup\u003e-based heat-inducible sensor, achieving a dynamic range of 107-fold. The \u003cem\u003ecspA\u003c/em\u003e 5'UTR sequence was identified and validated as a cold-inducible RNA thermometer, enabling the creation of a dual-functional, temperature-responsive genetic circuit. Application tests demonstrated that simple temperature shifts could efficiently drive the production of three distinct proteins, underscoring the versatility and industrial potential of this physical induction strategy.\u003c/p\u003e\n\u003cp\u003eThis study found that the application of heterologous regulatory elements, such as CI\u003csup\u003e857\u003c/sup\u003e, in \u003cem\u003eC. glutamicum\u003c/em\u003e requires targeted re-optimization, highlighting the critical influence of the host cellular environment on the functionality of genetic circuits. The temperature-induction system developed here provides a control strategy that is completely free of chemical inducers, cost-effective, and readily scalable, thereby serving as a core tool for constructing smart cell factories and achieving spatiotemporal regulation of metabolic pathways. Future research could further elucidate the molecular mechanisms of the key mutants and explore how to utilize this sensor network to coordinate multi-target metabolic fluxes for the synthesis of structurally more complex chemicals.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThis article contains no studies with human participants or animals performed by any author.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \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 \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the National Natural Science Foundation of China (No.22378167) and the Key Research and Development Project of Henan Province(251111310300).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eHaofei Xu : Investigation, Writing \u0026ndash; original draft. Yanbo Li, Yiran Gan, Songzhou Liu, Bin Lin, Shijun Cen, Yankun Yang, Chunli Liu : Data curation, Investigation. Xiuxia Liu and Zhonghu Bai : Writing \u0026ndash; review \u0026amp; editing, Supervision, Funding acquisition, Conceptualization.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData will be made available on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhang K, Cui B. Optogenetic control of intracellular signaling pathways. Trends Biotechnol. 2015;33(2):92\u0026ndash;100. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tibtech.2014.11.007\u003c/span\u003e\u003cspan address=\"10.1016/j.tibtech.2014.11.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNielsen J, Keasling JD. Engineering cellular metabolism. 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ACS Synth Biol. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acssynbio.5c00250\u003c/span\u003e\u003cspan address=\"10.1021/acssynbio.5c00250\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Thermosensitive biosensor, Dynamic metabolic regulation, Corynebacterium glutamicum, Recombinant protein production, Synthetic biology","lastPublishedDoi":"10.21203/rs.3.rs-8832594/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8832594/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDynamic metabolic regulation is crucial for optimizing microbial cell factories. To address the limitations of chemical inducers, this study developed a temperature-responsive synthetic biology toolkit for \u003cem\u003eCorynebacterium glutamicum\u003c/em\u003e. A high-performance, heat-inducible biosensor was engineered by optimizing the CI\u003csup\u003e857 \u003c/sup\u003erepressor and its cognate promoter, yielding a variant (CI\u003csup\u003e857\u003c/sup\u003e-M3/H1) with a 107-fold dynamic range and minimal background leakage. Additionally, a cold-inducible RNA thermometer was implemented using the \u003cem\u003eEscherichia coli\u003c/em\u003e \u003cem\u003ecsapA\u003c/em\u003e 5'UTR. These components were integrated into a dual-functional genetic circuit enabling bidirectional metabolic control. Finally, the optimized heat-inducible sensor was applied to the production of three secretory proteins with distinct characteristics (AmyE, XylA, and VHH), and the scale-up cultivation of AmyE was successfully achieved in 1-L shake-flasks. This work provides an efficient, inducer-free strategy for precise metabolic regulation, offering a scalable and cost-effective tool for advanced biomanufacturing.\u003c/p\u003e","manuscriptTitle":"Engineering a Temperature-Programmable Biosensor Toolkit for Recombinant Protein Production in Corynebacterium glutamicum","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-18 16:26:32","doi":"10.21203/rs.3.rs-8832594/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"46dfcb10-eafc-4032-839f-80955c2a3945","owner":[],"postedDate":"February 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T01:39:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-18 16:26:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8832594","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8832594","identity":"rs-8832594","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}