Novel spectroscopy method to reveal optimal culture conditions in Escherichia coli fermenter

Novel spectroscopy method to reveal optimal culture conditions in Escherichia coli fermenter | 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 Novel spectroscopy method to reveal optimal culture conditions in Escherichia coli fermenter Huakun Wu, Jingru Chen, Jia Zheng, Jie Shao, Meifang Yu, Wen Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4588876/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 Fermentation engineering has played a pivotal role in modern industry for mass-producing chemicals, food additives, and medicines, with optimal culture conditions crucial for maximizing microbial growth and metabolite production. Thus, bacteria growth monitoring was crucial in fermentation processes, with current methods falling into two categories: off-line sampling and in-situ on-line monitoring. While off-line methods suffered from discrete monitoring points and potential pollution, current on-line methods faced limitations including an inability to distinguish living from dead cells and impurities and a lack of direct representation of metabolism. Carbon dioxide (CO 2 ) levels, which closely correlated with chemical synthesis, could be measured with high sensitivity with Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology, enabling non-invasive, high-sensitivity detection of CO 2 concentrations in microbial fermentation, offering a powerful tool for optimizing conditions and enhancing production efficiency. This study presented a novel approach to reveal the optimal culture conditions for Escherichia coli (E. coli) fermentation. Through the implementation of a custom metabolism monitoring system based on TDLAS technology in a simulated fermenter, alongside varied pH and temperature settings, we elucidated the influence of these factors on E. coli metabolism curves and calculated the growth rates via threshold times, identifying 38°C as the optimal temperature and pH 7.5 as the optimal pH. Integration of this spectroscopy method into fermenters held promise for enhanced in situ online real-time monitoring of metabolism in future fermentations. Escherichia coli fermenter Tunable diode laser absorption spectroscopy pH Temperature Carbon dioxide metabolism curve Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction In contemporary industry, fermentation engineering has assumed an increasingly pivotal role in the large-scale production of chemicals, food additives, and medicines(Daba et al. 2021 ). Within fermentation domains, a key concern revolves around capacity utilization, with the productivity of bacterial fermentation intricately linked to bacterial growth, as the production process essentially stems from cellular metabolism. Consequently, the culture conditions of microorganisms wield substantial influence over yield, underscoring the importance of determining the appropriate culture environment(Harrison and Loveless 1971 ). To ensure optimal growth and productivity, it becomes imperative to regulate and modulate the culture conditions of microorganisms. Factors such as temperature, pH, oxygenation, nutrient availability(Tsai et al. 1997 ), and agitation(Park et al. 2002 ) all play critical roles in fostering the ideal environment for microbial growth and metabolite production. Through meticulous control of these parameters, scientists and engineers could enhance the yield of desired products while mitigating the generation of unwanted byproducts or microbial contamination. Additionally, advanced methodologies like computer modeling(Lopez et al. 2004 ) and automation(Habash and Johns 2009 ) were utilized to refine fermentation processes, resulting in heightened efficiency and cost-effectiveness in production methodologies. Thus, the bacteria growth monitoring was very critical during the fermentation process. Currently, the monitoring method could be divided into two types(Christensen et al. 1996 ): the off-line sampling method and the in-situ on-line monitoring method. In the off-line method, a small portion of the bacterial solution was sampled at intervals and the dry/wet weight ratio was measured to calculate the bacterial quantities(Cao et al. 2024 ). The off-line method was widely used but there were some obvious drawbacks including discrete points in monitoring time, hysteretic statistics and possibility of pollution. In the on-line method, the capacitance measuring method was limited by requiring certain bacterial concentration and the inserted probes in fermentation broth(Ikonen et al. 2017 ). Meanwhile, the optical density/backward scattering method took advantages of the high sensitivity and non-invasiveness based on the light absorption and scattering of microorganisms(Meyers et al. 2018 ). Although the optical method has been widely used in the fermentation process monitoring, there were still several limitations such as not being able to tell living cells from dead cells and not being a direct representation of metabolism. Throughout the fermentation process, the synthesis of chemicals coincided with the generation of CO 2 as a byproduct of microbial metabolism(Renger 1991 ). Consequently, the yield of the desired product was closely linked to the production of CO 2 . The correlation between CO 2 production and product yield underscored the importance of monitoring CO 2 levels as a key parameter for optimizing fermentation conditions and maximizing production efficiency(Guadalupe-Daqui et al. 2023 ). By monitoring the change in CO 2 concentration in the headspace of the microbial fermentation bottle under various culture conditions, the metabolic curve of microorganisms was obtained. TDLAS technology could be applied for microbial detection(Brueckner et al. 2017 ) by transmitting a modulated laser beam through the headspace of the fermentation vessel(Xin et al. 2021 ), enabling non-invasive detection of CO 2 concentration with high sensitivity. In recent years, there has been an emergence of TDLAS technology in microbiological detection. Shao et al. successfully employed this technology to predict microbial growth curves(Shao et al. 2016 ) and realize total viable counts(Shao et al. 2018 ). Given the reputation of E. coli in fermentation engineering for its rapid growth rate, ease of cultivation, metabolic adaptability, and extensive genetic repertoire(Hou et al. 2024 ; Zhou et al. 2018 ), it was a natural choice as the experimental strain for our study. This paper proposed a novel method to find the optimal conditions for the culture environment during E. coli fermentation. The home-made metabolism monitoring system, based on TDLAS technology, was tested, with the signal-to-noise ratio of this system being 9.6 and the detection limit at 125 ppm/3 cm. Through conducting fermentations under various pH and temperature conditions, CO 2 metabolic curves of E. coli were obtained in these diverse environmental settings. By analyzing the threshold time, we were able to understand how the growth rate of E. coli was influenced by pH and temperature(Minkevich et al. 2006 ; Xu et al. 2015 ). The optimal culture temperature in the E. coli fermenter was found to be 38°C, with the optimal pH being 7.5. In the future work, integration of this spectroscopy method into commercial fermenters could offer invasive, real-time, and highly sensitive in situ online monitoring of metabolism during real fermentations. 2. Materials and methods 2.1. Inoculum development Nutrient broth (NB) and nutrient agar (NA) were acquired from Shanghai Sangong Biological Company. To prepare the NB medium, 9.0 g of NB dry powder was dissolved in 500 mL of distilled water in a container and autoclaved for usage. For the NA medium, 15.0 g of agar was incorporated into the main components, similar to those of NB, to solidify the medium. To adjust the pH of the medium, HCl and NaOH was purchased from SinopHarm Chemical Reagent Company. The pH measurements were conducted using a pH meter obtained from Shanghai Precision Science Company. 2.2. Microorganism development and fermentation The E. coli used in this study was obtained from the city's Food and Drug Inspection and Testing Institute. E. coli was removed from the strain-specific refrigerator at -80 ℃and placed on a sterile clean bench for activation. 20 µL of the original bacterial solution was added to a test tube containing 5 mL of NB medium and incubated at 36 ℃ for 24 h to obtain the E. coli bacterial solution. The simulated fermentation process took place in a sealed flask, measuring 3 cm in diameter and with a volume of 50 mL, procured from Zhejiang Hengda Medical Devices. The fermentation temperature was maintained using a custom-made incubator. 2.3. The principle of WM-TDLAS technology The fundamentals of WM-TDLAS utilized in spectral fitting were detailed in the following references. The acquired spectral signal was processed in the following manner. A theoretical calculation of the 2f waveforms proposed by Ove was performed, which could be expressed as Eq. (1) in the case of a small absorbance(Guha and Schoegl 2014 ; Rivera et al. 2004 ). \({\varvec{S}}_{2\varvec{f}}\left({\stackrel{̄}{\varvec{\nu }}}_{\varvec{d}},{\stackrel{̄}{\varvec{\nu }}}_{\varvec{a}}\right)=-\varvec{\eta }{\varvec{I}}_{\varvec{D}}{\varvec{\alpha }}_{0}{\stackrel{̄}{\varvec{\chi }}}_{\varvec{L},2}\left({\stackrel{̄}{\varvec{\nu }}}_{\varvec{d}},{\stackrel{̄}{\varvec{\nu }}}_{\varvec{a}}\right)\) Eq. (1) Where \(\varvec{\eta }\) is the photoelectric amplification factor, \({\varvec{I}}_{\varvec{D}}\) is the optical power, \({\stackrel{̄}{\varvec{\nu }}}_{\varvec{a}}\) is the modulation factor, \(\varvec{P}\) is the pressure of the environment, \(\varvec{X}\) is the gas mole fraction, \(\varvec{L}\) is the optical path length, S is the line intensity of the absorption line, \(\varDelta \varvec{\nu }\) is the linewidth of the absorption line of the gas in the Lorentz line pattern, and \({\stackrel{̄}{\varvec{\chi }}}_{\varvec{L},2}\) is the second harmonic component of the peak normalized absorption line shape function. 2.4 The custom metabolism monitoring system The schematic diagram of the homemade metabolism monitoring system, based on WM-TDLAS technology, was depicted in Fig. 1 . A tunable distributed feedback diode laser (mp-2004, Nanoplus GmbH) served as the excitation source, with its wavelength precisely tuned to 4989.97 \({\varvec{c}\varvec{m}}^{-1}\) using a low-frequency 22 Hz trapezoidal wave and a high-frequency 11 kHz sine wave. The emitted beam underwent collimation through an antireflection coated lens (F260APC-1550, THORLABS) before traversing the headspace of the fermenter. Upon transmission through the fermenter, the laser beam was focused onto a custom-built detector module, featuring a photodiode (G12183–010 K, Hamamatsu Photonics). The signal captured by the detector module bifurcated into two paths for further processing. One path conveyed the direct absorption (DA) signal directly to the signal processing module, where it underwent normalization to mitigate variations in laser intensities. The other path led to the demodulation module, responsible for extracting the 2f signal. Subsequently, the signal processing module facilitated the acquisition and processing of both the DA and 2f signals, enabling comprehensive analysis of metabolic activity within the fermenter. The simulated fermenter was placed inside a homemade incubator designed for experimentation. This incubator was equipped with a temperature control system utilizing a heated circuit board, allowing precise regulation of temperatures ranging from room temperature to 100 ℃. This setup ensured a stable and customizable thermal environment for the fermenter, optimizing conditions for the simulated fermentation process. 2.5 The growth rate analysis via threshold time intervals Microorganisms grew and underwent metabolic activities under suitable environmental conditions, resulting in an increase in cell numbers, known as growth. This growth was typically divided into four phases: lag phase, exponential phase, stationary phase, and death phase. During the logarithmic growth phase, the growth rate of microorganisms was relatively stable. A certain biomass, such as a certain CO 2 concentration, was chosen as the threshold. When the threshold was reached, the microbial population in the growth environment was the same. Under identical growth conditions, different initial microbial quantities required different times to reach the threshold. In this study, the initial concentration of E. coli was diluted in gradients of tenfold increments, and the time difference between two dilution gradients reaching the threshold was measured as the threshold time interval. The reciprocal of this threshold time interval was used to reflect the microbial growth rate. This study determined the optimal threshold through the following steps: initially, signal values of the last dilution gradient (10 − 5 ) were computed for the initial 10 hours of the curve, resulting in a mean and a standard deviation. The threshold was then calculated by adding 3 to 10 times the standard deviation (with n varying from 3 to 10) to the mean, generating threshold values of 343, 408, 463,518, 673, 628, 683,738 for temperature series in Section 3.2 and 177, 210, 243, 276, 309, 342, 375, 408 for pH series in Section 3.3 , respectively. Subsequently, a relationship curve between threshold time and dilution gradient was plotted, as displayed in Fig. 2 (a) and (c). The threshold times for consecutive dilution gradients were then analyzed under different thresholds, and the sum of squared residuals between the measured and fitted data. was plotted in Fig. 2 (b) and (d). The sum of squared residuals at each threshold was calculated as the average of the five data points corresponding to that threshold. Eventually, the threshold with the least sum of residuals was identified as the optimal threshold. 3. Results and discussions 3.1. Detection performance of the home-made metabolism monitoring system To clarify the detection capability of the metabolism monitoring system, the fermenter filled with the standard gas was tested. As shown in Fig. 3 (a), the red line depicted the actual signal data collected by the instrument, the blue line represented the second harmonic signal fitted according to the formula, and the black line in Fig. 3 (b) indicated the fitting residual. According to the calculation, the second harmonic signal-to-noise ratio of this system was 9.6 and the detection limit was 125 ppm. This confirmed the system's ability to precisely measure CO 2 signals as low as 125 ppm within an optical distance of 3 cm, meeting the requirement for assessing the CO 2 profile of microbial metabolites. Considering the significant diameter variations in fermenter used in industrial production, ranging from tens of centimeters to even meters, the optical path length was much larger than in our simulated fermenter, that could certainly result in the one-tenth or even lower detection limit. To validate the feasibility of continuous CO 2 monitoring, a flask containing E. coli was prepared to simulate fermentation. Following inoculation of the microbial broth into the flask, it was promptly placed into the incubator, marking the commencement of CO 2 concentration monitoring within the fermenter. This monitoring spanned 25 hours, with second harmonic signals recorded hourly. Figure 4 (a) displayed data at 5-hour intervals, with the peak-peak values representing the CO 2 concentration. The peak-peak values were subsequently calculated from each curve in Fig. 4 (a), serving as the vertical coordinate, while the incubation time served as the horizontal coordinate, as depicted in Fig. 4 (b). This S-type curve observed in microbial metabolite CO 2 signals suggested the metabolite curve of E. coli and the dynamics associated with microbial growth. Consequently, the metabolism monitoring system aptly monitored fluctuations in microbial metabolite CO 2 content over time. This capability established it as a dependable indicator of microbial growth dynamics, offering valuable insights into fermentation processes. The homemade metabolism monitoring system employed laser-transmitted light to directly penetrate the culture bottle without contacting the microorganisms, and no third-party testing media were introduced into the bottle. Moreover, the entire testing apparatus maintained a constant temperature, ensuring that the microbial growth environment remained undisturbed. Consequently, the home-made metabolism monitoring system was non-intrusive as it did not impede microbial growth. In summary, this system facilitated real-time monitoring of metabolic processes within the fermenter by harnessing WM-TDLAS principles, delivering a well sensitivity and accuracy in metabolic analysis. 3.2. The optimal culture temperature of E. coli The optimal culture temperature during fermentation was determined using our homemade metabolism monitoring system. The same bacterial solution, with an concentration of 1.9×10 8 CFU/mL, was divided into eight groups and cultured using the same medium developed in Section 2.1 . In each group, the E. coli solution was diluted in gradients of tenfold increments, from 10 − 1 to 10 − 5 . The simulated fermenters were then placed into our homemade metabolism monitoring system and the only difference among eight groups was the culture temperature, which ranged from 28 ℃ to 42 ℃. The CO 2 metabolic curves were recorded in Fig. 5 (a-h). It was evident that the logarithmic growth rates of E. coli varied across different temperatures, demonstrating a trend of lower CO 2 accumulation as pH temperatures became increasingly unfavorable. This suggested a correlation between temperatures and the growth rates of E. coli, with unfavorable temperatures leading to reduced growth rates as evidenced by the lower CO 2 accumulation. To gain insights into the impact of temperatures on the growth rate of E. coli, the threshold time interval method proposed in Section 2.5 was applied. According to Fig. 2 (b), the threshold value was chosen to be 518 for further analysis. The corresponding relationships between dilution gradients and threshold times at each temperature were analyzed based on metabolic curves of E. coli as depicted in Fig. 5 (i-p). The solid red line represented the linear regression result. The linear equation of the fit and the coefficient of determination were also provided. The high coefficient of determination indicated a good fit of the linear model. According to the above fitting results at different pH, the threshold time interval of E. coli growth at different pH was obtained, and the reciprocal of the threshold time interval was calculated to represent the growth rate shown in Table 1. To obtain the curve of growth rate variation with temperature using the threshold time interval method, the reciprocals of threshold time intervals under different temperatures were plotted as shown in Fig. 6 . Table 1 Threshold time intervals and growth rates (reciprocal of threshold time intervals) of E. coli at different temperatures Overall, E. coli exhibited optimal growth around a temperature of 38°C, with environments deviating from this temperature potentially inhibiting its growth and metabolic activity. This emphasized the critical role of temperature regulation in production settings to ensure the most favorable conditions for E. coli growth, thereby enhancing growth efficiency and target yields. This observation underscored the sensitivity of E. coli growth and metabolism to fluctuations in temperature conditions, highlighting the importance of understanding the environmental factors that influence microbial growth. 3.3. The optimal culture pH of E. coli The optimal pH culture condition during fermentation was determined using our homemade metabolism monitoring system. The same bacterial solution, with an concentration of 1.9×10 8 CFU/mL, was divided into six groups and cultured using the same medium developed in Section 2.1 . The only difference among six groups was the pH, which ranged from 5.5 to 8.0. In each group, the E. coli solution was diluted in gradients of tenfold increments, from 10 − 1 to 10 − 5 . The simulated fermenters were then placed into our homemade metabolism monitoring system and cultured at 38 ℃, while the CO 2 metabolic curves were recorded in Fig. 7 (a-f). It was evident that the logarithmic growth rates of E. coli varied across different pH levels, demonstrating a trend of lower CO 2 accumulation as pH conditions became increasingly unfavorable. This suggested a correlation between pH levels and the growth rates of E. coli, with unfavorable pH levels leading to reduced growth rates as evidenced by the lower CO 2 accumulation. To gain insights into the impact of pH on the growth rate of E. coli, the threshold time interval method proposed in Section 2.5 was applied. According to Fig. 2 (d), the threshold value was chosen to be 309 for further analysis. The corresponding relationships between dilution gradients and threshold times at each pH level were analyzed based on metabolic curves of E. coli as depicted in Fig. 7 (g-l). The solid red line represented the linear regression result. The linear equation of the fit and the coefficient of determination were also provided. The high coefficient of determination indicated a good fit of the linear model. According to the above fitting results at different pH, the threshold time interval of E. coli growth at different pH was obtained, and the reciprocal of the threshold time interval was calculated to represent the growth rate shown in Table 2. To obtain the curve of growth rate variation with pH using the threshold time interval method, the reciprocals of threshold time intervals under different pH conditions were plotted as shown in Fig. 8 . Table 2 Threshold time intervals and growth rates (reciprocal of threshold time intervals) of E. coli at different pH values Overall, E. coli demonstrated optimal growth around a pH of approximately 7.5 with more acidic or alkaline environments potentially inhibiting its growth and metabolic activity. This underscored the importance of regulating pH levels in production settings to provide the most conducive conditions for E. coli growth and thereby enhance growth efficiency and target yields. This observation highlighted the sensitivity of E. coli growth and metabolism to changes in pH conditions, which were crucial for understanding the environmental factors that influence microbial growth. 4. Conclusions This paper introduced a novel spectroscopy strategy to analyze microbial metabolism under different fermentation conditions invasively. The CO 2 concentration of the headspace of the fermenter was measured based on the relatively high absorption line of CO 2 at 4989.97 \({\mathbf{c}\mathbf{m}}^{-1}\) . The metabolism monitoring system consisted of a tuned laser beam, a home-made detection board, a photodiode and an incubator. Subsequently, the signal-to-noise ratio of this system was 9.6 and the detection limit was 125 ppm within a relatively short optical distance of 3 cm which could be ten times larger in a real fermenter resulting in a lower detection limit. Simulated fermentations were further conducted and the mentalism curves were measured under different temperatures and pH levels. The optimal culture temperature in the E. coli fermenter was determined to be 38°C and the optimal pH was 7.5. The spectroscopy in situ online method, compared to conventional online techniques, was invasive, real time, highly sensitive and easy integrable, showing promise for application in real fermenters. Declarations Author Contribution Huakun Wu: Investigation, Measurements, Writing – original draft. Jingru Chen: Conceptualization, Methodology.Jia Zheng: Writing − review and editing.Jie Shao: Data curation. Meifang Yu: Software, Validation.Wen Liu: Writing – review & editing, Formal analysis, Supervision. Acknowledgements This study was supported by the Key Research and Development of Zhejiang Province (2022C03066), Key Science and Technology project of Jinhua City (20213032, 2022-1-084, 2022-3-071), Science and Technology project of Jinhua City (2023A221073), Biomedical Optical Instrument Engineering Technology Research Center Open Subjects of Anhui Province (2023BMP08), Natural Science Foundation of Zhejiang Province Public Welfare Project (LTGN23C130002). References . Brueckner D, Roesti D, Zuber U, Sacher M, Duncan D, Krähenbühl S, Braissant O (2017) Tunable diode laser absorption spectroscopy as method of choice for non-invasive and automated detection of microbial growth in media fills. Talanta 167:21-29 doi:10.1016/j.talanta.2017.01.088 Cao X, Xiong H, Fan Y, Xiong L (2024) Comparing the Effects of Two Culture Methods to Determine the Total Heterotrophic Bacterial Colony Count in Hospital Purified Water. 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World Journal of Microbiology and Biotechnology 31(6):941-950 doi:10.1007/s11274-015-1848-8 Zhou YL, Lu ZH, Wang X, Selvaraj JN, Zhang GM (2018) Genetic engineering modification and fermentation optimization for extracellular production of recombinant proteins using Escherichia coli. Appl Microbiol Biotechnol 102(4):1545-1556 doi:10.1007/s00253-017-8700-z 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-4588876","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320250775,"identity":"7d95032b-4504-4a96-bcc7-ee60cf9a38c9","order_by":0,"name":"Huakun Wu","email":"","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Huakun","middleName":"","lastName":"Wu","suffix":""},{"id":320250776,"identity":"ea0b350e-625b-412a-9235-f7952b359102","order_by":1,"name":"Jingru Chen","email":"","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Jingru","middleName":"","lastName":"Chen","suffix":""},{"id":320250777,"identity":"cc1bbec4-5c80-4267-ab20-bb598dd60fa9","order_by":2,"name":"Jia Zheng","email":"","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Jia","middleName":"","lastName":"Zheng","suffix":""},{"id":320250778,"identity":"01f92eaf-e1d6-4d8f-9642-2334e12da548","order_by":3,"name":"Jie Shao","email":"","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Shao","suffix":""},{"id":320250779,"identity":"1bbc13cf-5aee-4e44-b78d-0ecc130042f8","order_by":4,"name":"Meifang Yu","email":"","orcid":"","institution":"Jinhua Guangfu Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Meifang","middleName":"","lastName":"Yu","suffix":""},{"id":320250781,"identity":"1ab401c7-432c-47ee-abf6-8b86435d240e","order_by":5,"name":"Wen Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYHACxgMJDDYMjA0gNhuReoBa0kjVwsBwGMokRovB8d4DBx62nbdnnt1jwPCh7DAD/+wGAlrOnEs4kNh2m5lxzhkDxhnnDjNI3DmAX4vZjRwDkBY2xhk5Bsy8bYcZDCQSCGi5/wak5RwPWMtforTc4AFpOSAB1sJIjBb7M0CHJZxLBvojreBgz7l0HokbBLRItp8xfPijzM7ecEbyxgc/yqzl+GcQ0AIHhg3gCGLgIVI9EMgTr3QUjIJRMApGGgAAEy5F/7/JFEEAAAAASUVORK5CYII=","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":true,"prefix":"","firstName":"Wen","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-06-16 07:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4588876/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4588876/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59548665,"identity":"bacc117b-1b5d-4050-bd03-7739acd26500","added_by":"auto","created_at":"2024-07-03 05:47:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":181870,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the home-made metabolism monitoring systembased on WM-TDLAS technology.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/f6f3132a87b24c08878b7c82.png"},{"id":59548672,"identity":"3118ff8a-3ac4-46ee-afc3-7067a9336543","added_by":"auto","created_at":"2024-07-03 05:47:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":336193,"visible":true,"origin":"","legend":"\u003cp\u003e(a)Relationship between the dilution gradient and threshold time for temperature series. (b)The sum of squared residuals of measured data and fitted data in (a). (c)Relationship between the dilution gradient and threshold time for pH series. (d)The sum of squared residuals of measured data and fitted data in (c).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/deeba90d1e7027a695edf747.png"},{"id":59548670,"identity":"b545ebd4-e64a-402d-b5d3-2830857e5aa0","added_by":"auto","created_at":"2024-07-03 05:47:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":122522,"visible":true,"origin":"","legend":"\u003cp\u003e(a)The measured 2f signal and the fitted 2f signal. (b)The residual resulting from the 2f signal fitting.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/a6f0deb780cf6fb835fcc20c.png"},{"id":59549191,"identity":"d3e06982-d19c-4792-8964-64cb4bc91fff","added_by":"auto","created_at":"2024-07-03 05:55:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":158992,"visible":true,"origin":"","legend":"\u003cp\u003e(a)Second harmonic signals at 5-hour intervals of CO\u003csub\u003e2\u003c/sub\u003e within the fermenter. (b)Peak-peak values at every hour representing the CO\u003csub\u003e2 \u003c/sub\u003econcentration.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/41070dc56eaa8a3b96fbd057.png"},{"id":59549194,"identity":"f66c0f3d-8e01-4701-84d8-5b5af403330c","added_by":"auto","created_at":"2024-07-03 05:55:49","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1301401,"visible":true,"origin":"","legend":"\u003cp\u003eMetabolic curves of E. coli measured at different dilutions at (a)28 ℃, (b)30 ℃, (c)32 ℃, (d)34 ℃, (e)36 ℃, (f)38 ℃, (g)40 ℃and (h)42 ℃. (i-p) The corresponding relationship between dilution gradients and threshold times at each temperature. The solid red line represented the linear regression result. The linear equation of the fit and the coefficient of determination were also provided.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/8ad9eededa6821be1283f260.png"},{"id":59549192,"identity":"4de14acc-21ca-40ea-8af0-9caf5159d005","added_by":"auto","created_at":"2024-07-03 05:55:49","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":69761,"visible":true,"origin":"","legend":"\u003cp\u003eThe growth rate of E. coli under different temperatures.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/872a6e67cd40d39f6155bf7c.png"},{"id":59549193,"identity":"e5a368d4-1ee8-479d-a0aa-abec0a0f6764","added_by":"auto","created_at":"2024-07-03 05:55:49","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":214219,"visible":true,"origin":"","legend":"\u003cp\u003eMetabolic curves of E. coli measured at different dilutions at (a) pH 5.5, (b) pH 6.0, (c) pH 6.5, (d) pH 7.0, (e) pH 7.5, (f) pH 8.0. (g-l) The corresponding relationship between dilution gradients and threshold times at each pH level. The solid red line represented the linear regression result. The linear equation of the fit and the coefficient of determination were also provided.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/6bdb64e7da18ea708197baea.png"},{"id":59548666,"identity":"690d1aa8-d19b-4298-930d-c12b38c4e61f","added_by":"auto","created_at":"2024-07-03 05:47:49","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":71809,"visible":true,"origin":"","legend":"\u003cp\u003eThe growth rate of E. coli under different pH conditions.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/37189f170b818dfe1f9de9d4.png"},{"id":61022263,"identity":"cac79878-aa91-424c-a933-4dc8dedd6ed1","added_by":"auto","created_at":"2024-07-24 16:26:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2480645,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4588876/v1/89360f2b-7dda-4f5b-adda-b912bfe03b5a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Novel spectroscopy method to reveal optimal culture conditions in Escherichia coli fermenter","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn contemporary industry, fermentation engineering has assumed an increasingly pivotal role in the large-scale production of chemicals, food additives, and medicines(Daba et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Within fermentation domains, a key concern revolves around capacity utilization, with the productivity of bacterial fermentation intricately linked to bacterial growth, as the production process essentially stems from cellular metabolism. Consequently, the culture conditions of microorganisms wield substantial influence over yield, underscoring the importance of determining the appropriate culture environment(Harrison and Loveless \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1971\u003c/span\u003e). To ensure optimal growth and productivity, it becomes imperative to regulate and modulate the culture conditions of microorganisms. Factors such as temperature, pH, oxygenation, nutrient availability(Tsai et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), and agitation(Park et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) all play critical roles in fostering the ideal environment for microbial growth and metabolite production. Through meticulous control of these parameters, scientists and engineers could enhance the yield of desired products while mitigating the generation of unwanted byproducts or microbial contamination. Additionally, advanced methodologies like computer modeling(Lopez et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and automation(Habash and Johns \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) were utilized to refine fermentation processes, resulting in heightened efficiency and cost-effectiveness in production methodologies.\u003c/p\u003e \u003cp\u003eThus, the bacteria growth monitoring was very critical during the fermentation process. Currently, the monitoring method could be divided into two types(Christensen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1996\u003c/span\u003e): the off-line sampling method and the in-situ on-line monitoring method. In the off-line method, a small portion of the bacterial solution was sampled at intervals and the dry/wet weight ratio was measured to calculate the bacterial quantities(Cao et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The off-line method was widely used but there were some obvious drawbacks including discrete points in monitoring time, hysteretic statistics and possibility of pollution. In the on-line method, the capacitance measuring method was limited by requiring certain bacterial concentration and the inserted probes in fermentation broth(Ikonen et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Meanwhile, the optical density/backward scattering method took advantages of the high sensitivity and non-invasiveness based on the light absorption and scattering of microorganisms(Meyers et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although the optical method has been widely used in the fermentation process monitoring, there were still several limitations such as not being able to tell living cells from dead cells and not being a direct representation of metabolism.\u003c/p\u003e \u003cp\u003eThroughout the fermentation process, the synthesis of chemicals coincided with the generation of CO\u003csub\u003e2\u003c/sub\u003e as a byproduct of microbial metabolism(Renger \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Consequently, the yield of the desired product was closely linked to the production of CO\u003csub\u003e2\u003c/sub\u003e. The correlation between CO\u003csub\u003e2\u003c/sub\u003e production and product yield underscored the importance of monitoring CO\u003csub\u003e2\u003c/sub\u003e levels as a key parameter for optimizing fermentation conditions and maximizing production efficiency(Guadalupe-Daqui et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). By monitoring the change in CO\u003csub\u003e2\u003c/sub\u003e concentration in the headspace of the microbial fermentation bottle under various culture conditions, the metabolic curve of microorganisms was obtained. TDLAS technology could be applied for microbial detection(Brueckner et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) by transmitting a modulated laser beam through the headspace of the fermentation vessel(Xin et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), enabling non-invasive detection of CO\u003csub\u003e2\u003c/sub\u003e concentration with high sensitivity. In recent years, there has been an emergence of TDLAS technology in microbiological detection. Shao et al. successfully employed this technology to predict microbial growth curves(Shao et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and realize total viable counts(Shao et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the reputation of E. coli in fermentation engineering for its rapid growth rate, ease of cultivation, metabolic adaptability, and extensive genetic repertoire(Hou et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), it was a natural choice as the experimental strain for our study. This paper proposed a novel method to find the optimal conditions for the culture environment during E. coli fermentation. The home-made metabolism monitoring system, based on TDLAS technology, was tested, with the signal-to-noise ratio of this system being 9.6 and the detection limit at 125 ppm/3 cm. Through conducting fermentations under various pH and temperature conditions, CO\u003csub\u003e2\u003c/sub\u003e metabolic curves of E. coli were obtained in these diverse environmental settings. By analyzing the threshold time, we were able to understand how the growth rate of E. coli was influenced by pH and temperature(Minkevich et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The optimal culture temperature in the E. coli fermenter was found to be 38\u0026deg;C, with the optimal pH being 7.5. In the future work, integration of this spectroscopy method into commercial fermenters could offer invasive, real-time, and highly sensitive in situ online monitoring of metabolism during real fermentations.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Inoculum development\u003c/h2\u003e \u003cp\u003eNutrient broth (NB) and nutrient agar (NA) were acquired from Shanghai Sangong Biological Company. To prepare the NB medium, 9.0 g of NB dry powder was dissolved in 500 mL of distilled water in a container and autoclaved for usage. For the NA medium, 15.0 g of agar was incorporated into the main components, similar to those of NB, to solidify the medium. To adjust the pH of the medium, HCl and NaOH was purchased from SinopHarm Chemical Reagent Company. The pH measurements were conducted using a pH meter obtained from Shanghai Precision Science Company.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Microorganism development and fermentation\u003c/h2\u003e \u003cp\u003eThe E. coli used in this study was obtained from the city's Food and Drug Inspection and Testing Institute. E. coli was removed from the strain-specific refrigerator at -80 ℃and placed on a sterile clean bench for activation. 20 \u0026micro;L of the original bacterial solution was added to a test tube containing 5 mL of NB medium and incubated at 36 ℃ for 24 h to obtain the E. coli bacterial solution. The simulated fermentation process took place in a sealed flask, measuring 3 cm in diameter and with a volume of 50 mL, procured from Zhejiang Hengda Medical Devices. The fermentation temperature was maintained using a custom-made incubator.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. The principle of WM-TDLAS technology\u003c/h2\u003e \u003cp\u003eThe fundamentals of WM-TDLAS utilized in spectral fitting were detailed in the following references. The acquired spectral signal was processed in the following manner. A theoretical calculation of the 2f waveforms proposed by Ove was performed, which could be expressed as Eq.\u0026nbsp;(1) in the case of a small absorbance(Guha and Schoegl \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Rivera et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\varvec{S}}_{2\\varvec{f}}\\left({\\stackrel{̄}{\\varvec{\\nu }}}_{\\varvec{d}},{\\stackrel{̄}{\\varvec{\\nu }}}_{\\varvec{a}}\\right)=-\\varvec{\\eta }{\\varvec{I}}_{\\varvec{D}}{\\varvec{\\alpha }}_{0}{\\stackrel{̄}{\\varvec{\\chi }}}_{\\varvec{L},2}\\left({\\stackrel{̄}{\\varvec{\\nu }}}_{\\varvec{d}},{\\stackrel{̄}{\\varvec{\\nu }}}_{\\varvec{a}}\\right)\\)\u003c/span\u003e \u003c/span\u003e Eq.\u0026nbsp;(1)\u003c/p\u003e \u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{\\eta }\\)\u003c/span\u003e\u003c/span\u003e is the photoelectric amplification factor, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{I}}_{\\varvec{D}}\\)\u003c/span\u003e\u003c/span\u003e is the optical power, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\stackrel{̄}{\\varvec{\\nu }}}_{\\varvec{a}}\\)\u003c/span\u003e\u003c/span\u003e is the modulation factor, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{P}\\)\u003c/span\u003e\u003c/span\u003e is the pressure of the environment, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{X}\\)\u003c/span\u003e\u003c/span\u003e is the gas mole fraction, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{L}\\)\u003c/span\u003e\u003c/span\u003e is the optical path length, S is the line intensity of the absorption line, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varDelta \\varvec{\\nu }\\)\u003c/span\u003e\u003c/span\u003e is the linewidth of the absorption line of the gas in the Lorentz line pattern, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\stackrel{̄}{\\varvec{\\chi }}}_{\\varvec{L},2}\\)\u003c/span\u003e\u003c/span\u003e is the second harmonic component of the peak normalized absorption line shape function.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 The custom metabolism monitoring system\u003c/h2\u003e \u003cp\u003eThe schematic diagram of the homemade metabolism monitoring system, based on WM-TDLAS technology, was depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A tunable distributed feedback diode laser (mp-2004, Nanoplus GmbH) served as the excitation source, with its wavelength precisely tuned to 4989.97 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{c}\\varvec{m}}^{-1}\\)\u003c/span\u003e\u003c/span\u003e using a low-frequency 22 Hz trapezoidal wave and a high-frequency 11 kHz sine wave. The emitted beam underwent collimation through an antireflection coated lens (F260APC-1550, THORLABS) before traversing the headspace of the fermenter. Upon transmission through the fermenter, the laser beam was focused onto a custom-built detector module, featuring a photodiode (G12183\u0026ndash;010 K, Hamamatsu Photonics).\u003c/p\u003e \u003cp\u003eThe signal captured by the detector module bifurcated into two paths for further processing. One path conveyed the direct absorption (DA) signal directly to the signal processing module, where it underwent normalization to mitigate variations in laser intensities. The other path led to the demodulation module, responsible for extracting the 2f signal. Subsequently, the signal processing module facilitated the acquisition and processing of both the DA and 2f signals, enabling comprehensive analysis of metabolic activity within the fermenter.\u003c/p\u003e \u003cp\u003eThe simulated fermenter was placed inside a homemade incubator designed for experimentation. This incubator was equipped with a temperature control system utilizing a heated circuit board, allowing precise regulation of temperatures ranging from room temperature to 100 ℃. This setup ensured a stable and customizable thermal environment for the fermenter, optimizing conditions for the simulated fermentation process.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 The growth rate analysis via threshold time intervals\u003c/h2\u003e \u003cp\u003eMicroorganisms grew and underwent metabolic activities under suitable environmental conditions, resulting in an increase in cell numbers, known as growth. This growth was typically divided into four phases: lag phase, exponential phase, stationary phase, and death phase. During the logarithmic growth phase, the growth rate of microorganisms was relatively stable. A certain biomass, such as a certain CO\u003csub\u003e2\u003c/sub\u003e concentration, was chosen as the threshold. When the threshold was reached, the microbial population in the growth environment was the same. Under identical growth conditions, different initial microbial quantities required different times to reach the threshold. In this study, the initial concentration of E. coli was diluted in gradients of tenfold increments, and the time difference between two dilution gradients reaching the threshold was measured as the threshold time interval. The reciprocal of this threshold time interval was used to reflect the microbial growth rate.\u003c/p\u003e \u003cp\u003eThis study determined the optimal threshold through the following steps: initially, signal values of the last dilution gradient (10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e) were computed for the initial 10 hours of the curve, resulting in a mean and a standard deviation. The threshold was then calculated by adding 3 to 10 times the standard deviation (with n varying from 3 to 10) to the mean, generating threshold values of 343, 408, 463,518, 673, 628, 683,738 for temperature series in Section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e and 177, 210, 243, 276, 309, 342, 375, 408 for pH series in Section \u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003e3.3\u003c/span\u003e, respectively. Subsequently, a relationship curve between threshold time and dilution gradient was plotted, as displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e(a) and (c). The threshold times for consecutive dilution gradients were then analyzed under different thresholds, and the sum of squared residuals between the measured and fitted data. was plotted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e(b) and (d). The sum of squared residuals at each threshold was calculated as the average of the five data points corresponding to that threshold. Eventually, the threshold with the least sum of residuals was identified as the optimal threshold.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussions","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Detection performance of the home-made metabolism monitoring system\u003c/h2\u003e \u003cp\u003eTo clarify the detection capability of the metabolism monitoring system, the fermenter filled with the standard gas was tested. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(a), the red line depicted the actual signal data collected by the instrument, the blue line represented the second harmonic signal fitted according to the formula, and the black line in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(b) indicated the fitting residual. According to the calculation, the second harmonic signal-to-noise ratio of this system was 9.6 and the detection limit was 125 ppm. This confirmed the system's ability to precisely measure CO\u003csub\u003e2\u003c/sub\u003e signals as low as 125 ppm within an optical distance of 3 cm, meeting the requirement for assessing the CO\u003csub\u003e2\u003c/sub\u003e profile of microbial metabolites. Considering the significant diameter variations in fermenter used in industrial production, ranging from tens of centimeters to even meters, the optical path length was much larger than in our simulated fermenter, that could certainly result in the one-tenth or even lower detection limit.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo validate the feasibility of continuous CO\u003csub\u003e2\u003c/sub\u003e monitoring, a flask containing E. coli was prepared to simulate fermentation. Following inoculation of the microbial broth into the flask, it was promptly placed into the incubator, marking the commencement of CO\u003csub\u003e2\u003c/sub\u003e concentration monitoring within the fermenter. This monitoring spanned 25 hours, with second harmonic signals recorded hourly. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(a) displayed data at 5-hour intervals, with the peak-peak values representing the CO\u003csub\u003e2\u003c/sub\u003e concentration. The peak-peak values were subsequently calculated from each curve in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(a), serving as the vertical coordinate, while the incubation time served as the horizontal coordinate, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(b). This S-type curve observed in microbial metabolite CO\u003csub\u003e2\u003c/sub\u003e signals suggested the metabolite curve of E. coli and the dynamics associated with microbial growth. Consequently, the metabolism monitoring system aptly monitored fluctuations in microbial metabolite CO\u003csub\u003e2\u003c/sub\u003e content over time. This capability established it as a dependable indicator of microbial growth dynamics, offering valuable insights into fermentation processes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe homemade metabolism monitoring system employed laser-transmitted light to directly penetrate the culture bottle without contacting the microorganisms, and no third-party testing media were introduced into the bottle. Moreover, the entire testing apparatus maintained a constant temperature, ensuring that the microbial growth environment remained undisturbed. Consequently, the home-made metabolism monitoring system was non-intrusive as it did not impede microbial growth. In summary, this system facilitated real-time monitoring of metabolic processes within the fermenter by harnessing WM-TDLAS principles, delivering a well sensitivity and accuracy in metabolic analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. The optimal culture temperature of E. coli\u003c/h2\u003e \u003cp\u003eThe optimal culture temperature during fermentation was determined using our homemade metabolism monitoring system. The same bacterial solution, with an concentration of 1.9\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL, was divided into eight groups and cultured using the same medium developed in Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e. In each group, the E. coli solution was diluted in gradients of tenfold increments, from 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e. The simulated fermenters were then placed into our homemade metabolism monitoring system and the only difference among eight groups was the culture temperature, which ranged from 28 ℃ to 42 ℃. The CO\u003csub\u003e2\u003c/sub\u003e metabolic curves were recorded in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e(a-h). It was evident that the logarithmic growth rates of E. coli varied across different temperatures, demonstrating a trend of lower CO\u003csub\u003e2\u003c/sub\u003e accumulation as pH temperatures became increasingly unfavorable. This suggested a correlation between temperatures and the growth rates of E. coli, with unfavorable temperatures leading to reduced growth rates as evidenced by the lower CO\u003csub\u003e2\u003c/sub\u003e accumulation.\u003c/p\u003e \u003cp\u003eTo gain insights into the impact of temperatures on the growth rate of E. coli, the threshold time interval method proposed in Section \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e2.5\u003c/span\u003e was applied. According to Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e(b), the threshold value was chosen to be 518 for further analysis. The corresponding relationships between dilution gradients and threshold times at each temperature were analyzed based on metabolic curves of E. coli as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e(i-p). The solid red line represented the linear regression result. The linear equation of the fit and the coefficient of determination were also provided. The high coefficient of determination indicated a good fit of the linear model. According to the above fitting results at different pH, the threshold time interval of E. coli growth at different pH was obtained, and the reciprocal of the threshold time interval was calculated to represent the growth rate shown in Table\u0026nbsp;1. To obtain the curve of growth rate variation with temperature using the threshold time interval method, the reciprocals of threshold time intervals under different temperatures were plotted as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;1 Threshold time intervals and growth rates (reciprocal of threshold time intervals) of E. coli at different temperatures\u003c/p\u003e \u003cp\u003e\u003cimg 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\" width=\"506\" height=\"95\"\u003e\u003c/p\u003e \u003cp\u003eOverall, E. coli exhibited optimal growth around a temperature of 38\u0026deg;C, with environments deviating from this temperature potentially inhibiting its growth and metabolic activity. This emphasized the critical role of temperature regulation in production settings to ensure the most favorable conditions for E. coli growth, thereby enhancing growth efficiency and target yields. This observation underscored the sensitivity of E. coli growth and metabolism to fluctuations in temperature conditions, highlighting the importance of understanding the environmental factors that influence microbial growth.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3. The optimal culture pH of E. coli\u003c/h2\u003e \u003cp\u003eThe optimal pH culture condition during fermentation was determined using our homemade metabolism monitoring system. The same bacterial solution, with an concentration of 1.9\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL, was divided into six groups and cultured using the same medium developed in Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e. The only difference among six groups was the pH, which ranged from 5.5 to 8.0. In each group, the E. coli solution was diluted in gradients of tenfold increments, from 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e. The simulated fermenters were then placed into our homemade metabolism monitoring system and cultured at 38 ℃, while the CO\u003csub\u003e2\u003c/sub\u003e metabolic curves were recorded in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e(a-f). It was evident that the logarithmic growth rates of E. coli varied across different pH levels, demonstrating a trend of lower CO\u003csub\u003e2\u003c/sub\u003e accumulation as pH conditions became increasingly unfavorable. This suggested a correlation between pH levels and the growth rates of E. coli, with unfavorable pH levels leading to reduced growth rates as evidenced by the lower CO\u003csub\u003e2\u003c/sub\u003e accumulation.\u003c/p\u003e \u003cp\u003eTo gain insights into the impact of pH on the growth rate of E. coli, the threshold time interval method proposed in Section \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e2.5\u003c/span\u003e was applied. According to Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e(d), the threshold value was chosen to be 309 for further analysis. The corresponding relationships between dilution gradients and threshold times at each pH level were analyzed based on metabolic curves of E. coli as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e(g-l). The solid red line represented the linear regression result. The linear equation of the fit and the coefficient of determination were also provided. The high coefficient of determination indicated a good fit of the linear model. According to the above fitting results at different pH, the threshold time interval of E. coli growth at different pH was obtained, and the reciprocal of the threshold time interval was calculated to represent the growth rate shown in Table\u0026nbsp;2. To obtain the curve of growth rate variation with pH using the threshold time interval method, the reciprocals of threshold time intervals under different pH conditions were plotted as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;2 Threshold time intervals and growth rates (reciprocal of threshold time intervals) of E. coli at different pH values\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"520\" height=\"96\"\u003e\u003c/p\u003e \u003cp\u003eOverall, E. coli demonstrated optimal growth around a pH of approximately 7.5 with more acidic or alkaline environments potentially inhibiting its growth and metabolic activity. This underscored the importance of regulating pH levels in production settings to provide the most conducive conditions for E. coli growth and thereby enhance growth efficiency and target yields. This observation highlighted the sensitivity of E. coli growth and metabolism to changes in pH conditions, which were crucial for understanding the environmental factors that influence microbial growth.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eThis paper introduced a novel spectroscopy strategy to analyze microbial metabolism under different fermentation conditions invasively. The CO\u003csub\u003e2\u003c/sub\u003e concentration of the headspace of the fermenter was measured based on the relatively high absorption line of CO\u003csub\u003e2\u003c/sub\u003e at 4989.97 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{c}\\mathbf{m}}^{-1}\\)\u003c/span\u003e\u003c/span\u003e. The metabolism monitoring system consisted of a tuned laser beam, a home-made detection board, a photodiode and an incubator. Subsequently, the signal-to-noise ratio of this system was 9.6 and the detection limit was 125 ppm within a relatively short optical distance of 3 cm which could be ten times larger in a real fermenter resulting in a lower detection limit. Simulated fermentations were further conducted and the mentalism curves were measured under different temperatures and pH levels. The optimal culture temperature in the E. coli fermenter was determined to be 38\u0026deg;C and the optimal pH was 7.5. The spectroscopy in situ online method, compared to conventional online techniques, was invasive, real time, highly sensitive and easy integrable, showing promise for application in real fermenters.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eHuakun Wu: Investigation, Measurements, Writing \u0026ndash; original draft. Jingru Chen: Conceptualization, Methodology.Jia Zheng: Writing \u0026minus; review and editing.Jie Shao: Data curation. Meifang Yu: Software, Validation.Wen Liu: Writing \u0026ndash; review \u0026amp; editing, Formal analysis, Supervision.\u003c/p\u003e\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Key Research and Development of Zhejiang Province (2022C03066), Key Science and Technology project of Jinhua City (20213032, 2022-1-084, 2022-3-071), Science and Technology project of Jinhua City (2023A221073), Biomedical Optical Instrument Engineering Technology Research Center Open Subjects of Anhui Province (2023BMP08), Natural Science Foundation of Zhejiang Province Public Welfare Project (LTGN23C130002).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u0026lt;Compact CH4 sensor system based on a CW, low power consumption, room .pdf\u0026gt;. \u003c/li\u003e\n\u003cli\u003eBrueckner D, Roesti D, Zuber U, Sacher M, Duncan D, Kr\u0026auml;henb\u0026uuml;hl S, Braissant O (2017) Tunable diode laser absorption spectroscopy as method of choice for non-invasive and automated detection of microbial growth in media fills. 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Appl Microbiol Biotechnol 102(4):1545-1556 doi:10.1007/s00253-017-8700-z\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Escherichia coli fermenter, Tunable diode laser absorption spectroscopy, pH, Temperature, Carbon dioxide metabolism curve","lastPublishedDoi":"10.21203/rs.3.rs-4588876/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4588876/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFermentation engineering has played a pivotal role in modern industry for mass-producing chemicals, food additives, and medicines, with optimal culture conditions crucial for maximizing microbial growth and metabolite production. Thus, bacteria growth monitoring was crucial in fermentation processes, with current methods falling into two categories: off-line sampling and in-situ on-line monitoring. While off-line methods suffered from discrete monitoring points and potential pollution, current on-line methods faced limitations including an inability to distinguish living from dead cells and impurities and a lack of direct representation of metabolism. Carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) levels, which closely correlated with chemical synthesis, could be measured with high sensitivity with Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology, enabling non-invasive, high-sensitivity detection of CO\u003csub\u003e2\u003c/sub\u003e concentrations in microbial fermentation, offering a powerful tool for optimizing conditions and enhancing production efficiency. This study presented a novel approach to reveal the optimal culture conditions for Escherichia coli (E. coli) fermentation. Through the implementation of a custom metabolism monitoring system based on TDLAS technology in a simulated fermenter, alongside varied pH and temperature settings, we elucidated the influence of these factors on E. coli metabolism curves and calculated the growth rates via threshold times, identifying 38\u0026deg;C as the optimal temperature and pH 7.5 as the optimal pH. Integration of this spectroscopy method into fermenters held promise for enhanced in situ online real-time monitoring of metabolism in future fermentations.\u003c/p\u003e","manuscriptTitle":"Novel spectroscopy method to reveal optimal culture conditions in Escherichia coli fermenter","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-03 05:47:42","doi":"10.21203/rs.3.rs-4588876/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":"210d82ce-9f6a-4419-ac96-2e0ea88ce14b","owner":[],"postedDate":"July 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-24T16:18:42+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-03 05:47:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4588876","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4588876","identity":"rs-4588876","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}