On-line analysis and in situ pH monitoring of mixed acid fermentation by Escherichia coli using combined FTIR and Raman techniques

Development of automated metabolite control using mid-infrared probe for bioprocesses and vaccine manufacturing

Automation of metabolite control in fermenters is fundamental to develop vaccine manufacturing processes more quickly and robustly. We created an end-to-end process analytical technology and quality by design-focused process by replacing manual control of metabolites during the development of fed-batch bioprocesses with a system that is highly adaptable and automation-enabled. Mid-infrared spectroscopy with an attenuated total reflectance probe in-line, and simple linear regression using the Beer-Lambert Law, were developed to quantitate key metabolites (glucose and glutamate) from spectral data that measured complex media during fermentation. This data was digitally connected to a process information management system, to enable continuous control of feed pumps with proportional-integral-derivative controllers that maintained nutrient levels throughout fed-batch stirred-tank fermenter processes. Continuous metabolite data from mid-infrared spectra of cultures in stirred-tank reactors enabled feedback loops and control of the feed pumps in pharmaceutical development laboratories. This improved process control of nutrient levels by 20-fold and the drug substance yield by an order of magnitude. Furthermore, the method is adaptable to other systems and enables soft sensing, such as the consumption rate of metabolites. The ability to develop quantitative metabolite templates quickly and simply for changing bioprocesses was instrumental for project acceleration and heightened process control and automation.

ONE-SENTENCE SUMMARY

Intelligent digital control systems using continuous in-line metabolite data enabled end-to-end automation of fed-batch processes in stirred-tank reactors.

The Good pH probe: non-invasive pH in-line monitoring using Good buffers and Raman spectroscopy

In bioprocesses, the pH value is a critical process parameter that requires monitoring and control. For pH monitoring, potentiometric methods such as pH electrodes are state of the art. However, they are invasive and show measurement value drift. Spectroscopic pH monitoring is a non-invasive alternative to potentiometric methods avoiding this measurement value drift. In this study, we developed the Good pH probe, which is an approach for spectroscopic pH monitoring in bioprocesses with an effective working range between pH 6 and pH 8 that does not require the estimation of activity coefficients. The Good pH probe combines for the first time the Good buffer 3-(N-morpholino)propanesulfonic acid (MOPS) as pH indicator with Raman spectroscopy as spectroscopic technique, and Indirect Hard Modeling (IHM) for the spectral evaluation. During a detailed characterization, we proved that the Good pH probe is reversible, exhibits no temperature dependence between 15 and 40 °C, has low sensitivity to the ionic strength up to 1100 mM, and is applicable in more complex systems, in which other components significantly superimpose the spectral features of MOPS. Finally, the Good pH probe was successfully used for non-invasive pH in-line monitoring during an industrially relevant enzyme-catalyzed reaction with a root mean square error of prediction (RMSEP) of 0.04 pH levels. Thus, the Good pH probe extends the list of critical process parameters monitorable using Raman spectroscopy and IHM by the pH value.

Formate production is dispensable for Haemophilus ducreyi virulence in human volunteers

Haemophilus ducreyi is a causative agent of cutaneous ulcers in children who live in the tropics and of the genital ulcer disease chancroid in sexually active persons. In the anaerobic environment of abscesses and ulcers, anaerobic respiration and mixed acid fermentation (MAF) can be used to provide cellular energy. In Escherichia coli, MAF produces formate, acetate, lactate, succinate, and ethanol; however, MAF has not been studied in H. ducreyi. In human challenge experiments with H. ducreyi 35000HP, transcripts of the formate transporter FocA and pyruvate formate lyase (PflB) were upregulated in pustules compared to the inocula. We made single and double mutants of focA and pflB in 35000HP. Growth of 35000HPΔfocA was similar to 35000HP, but 35000HPΔpflB and 35000HPΔfocA-pflB had growth defects during both aerobic and anaerobic growth. Mutants lacking pflB did not secrete formate into the media. However, formate was secreted into the media by 35000HPΔfocA, indicating that H. ducreyi has alternative formate transporters. The pH of the media during anaerobic growth decreased for 35000HP and 35000HPΔfocA, but not for 35000HPΔpflB or 35000HPΔfocA-pflB, indicating that pflB is the main contributor to media acidification during anaerobic growth. We tested whether formate production and transport were required for virulence in seven human volunteers in a mutant versus parent trial between 35000HPΔfocA-pflB and 35000HP. The pustule formation rate was similar for 35000HP (42.9%)- and 35000HPΔfocA-pflB (62%)-inoculated sites. Although formate production occurs during in vitro growth and focA-pflB transcripts are upregulated during human infection, focA and pflB are not required for virulence in humans.

Development of Raman Calibration Model Without Culture Data for In-Line Analysis of Metabolites in Cell Culture Media

In this study, we developed a method to build Raman calibration models without culture data for cell culture monitoring. First, Raman spectra were collected and then analyzed for the signals of all the mentioned analytes: glucose, lactate, glutamine, glutamate, ammonia, antibody, viable cells, media, and feed agent. Using these spectral data, the specific peak positions and intensities for each factor were detected. Next, according to the design of the experiment method, samples were prepared by mixing the above-mentioned factors. Raman spectra of these samples were collected and were used to build calibration models. Several combinations of spectral pretreatments and wavenumber regions were compared to optimize the calibration model for cell culture monitoring without culture data. The accuracy of the developed calibration model was evaluated by performing actual cell culture and fitting the in-line measured spectra to the developed calibration model. As a result, the calibration model achieved sufficiently good accuracy for the three components, glucose, lactate, and antibody (root mean square errors of prediction, or RMSEP = 0.23, 0.29, and 0.20 g/L, respectively). This study has presented innovative results in developing a culture monitoring method without using culture data, while using a basic conventional method of investigating the Raman spectra of each component in the culture media and then utilizing a design of experiment approach.

Factors affecting the competitiveness of bacterial fermentation

Sustainable production of chemicals and materials from renewable non-food biomass using biorefineries has become increasingly important in an effort toward the vision of 'net zero carbon' that has recently been pledged by countries around the world. Systems metabolic engineering has allowed the efficient development of microbial strains overproducing an increasing number of chemicals and materials, some of which have been translated to industrial-scale production. Fermentation is one of the key processes determining the overall economics of bioprocesses, but has recently been attracting less research attention. In this Review, we revisit and discuss factors affecting the competitiveness of bacterial fermentation in connection to strain development by systems metabolic engineering. Future perspectives for developing efficient fermentation processes are also discussed.

Hydrogen production in the presence of oxygen by Escherichia coli K-12

Escherichia coli is a facultative anaerobe that can grow in a variety of environmental conditions. In the complete absence of O₂, E. coli can perform a mixed-acid fermentation that contains within it an elaborate metabolism of formic acid. In this study, we use cavity-enhanced Raman spectroscopy (CERS), FTIR, liquid Raman spectroscopy, isotopic labelling and molecular genetics to make advances in the understanding of bacterial formate and H₂ metabolism. It is shown that, under anaerobic (anoxic) conditions, formic acid is generated endogenously, excreted briefly from the cell, and then taken up again to be disproportionated to H₂ and CO₂ by formate hydrogenlyase (FHL-1). However, exogenously added D-labelled formate behaves quite differently from the endogenous formate and is taken up immediately, independently, and possibly by a different mechanism, by the cell and converted to H₂ and CO₂. Our data support an anion-proton symport model for formic acid transport. In addition, when E. coli was grown in a micro-aerobic (micro-oxic) environment it was possible to analyse aspects of formate and O₂ respiration occurring alongside anaerobic metabolism. While cells growing under micro-aerobic conditions generated endogenous formic acid, no H₂ was produced. However, addition of exogenous formate at the outset of cell growth did induce FHL-1 biosynthesis and resulted in formate-dependent H₂ production in the presence of O₂.

Advanced spectroscopic analysis and 15N-isotopic labelling study of nitrate and nitrite reduction to ammonia and nitrous oxide by E. coli

Nitrate and nitrite reduction to ammonia and nitrous oxide by anaerobic E. coli batch cultures is investigated by advanced spectroscopic analytical techniques with ¹⁵N-isotopic labelling. Non-invasive, in situ analysis of the headspace is achieved using White cell FTIR and cavity-enhanced Raman (CERS) spectroscopies alongside liquid-phase Raman spectroscopy. For gas-phase analysis, White cell FTIR measures CO₂, ethanol and N₂O while CERS allows H₂, N₂ and O₂ monitoring. The 6 m pathlength White cell affords trace gas detection of N₂O with a noise equivalent detection limit of 60 nbar or 60 ppbv in 1 atm. Quantitative analysis is discussed for all four ¹⁴N/¹⁵N-isotopomers of N₂O. Monobasic and dibasic phosphates, acetate, formate, glucose and NO₃^- concentrations are obtained by liquid-phase Raman spectroscopy, with a noise equivalent detection limit of 0.6 mM for NO₃^- at 300 s integration time. Concentrations of the phosphate anions are used to calculate the pH in situ using a modified Henderson-Hasselbalch equation. NO₂^- concentrations are determined by sampling for colorimetric analysis and NH₄⁺ by basifying samples to release ¹⁴N/¹⁵N-isotopomers of NH₃ for measurement in a second FTIR White cell. The reductions of ¹⁵NO₃^-, ¹⁵NO₂^-, and mixed ¹⁵NO₃^- and ¹⁴NO₂^- by anaerobic E. coli batch cultures are discussed. In a major pathway, NO₃^- is reduced to NH₄⁺via NO₂^-, with the bulk of NO₂^- reduction occurring after NO₃^- depletion. Using isotopically labelled ¹⁵NO₃^-, ¹⁵NH₄⁺ production is distinguished from background ¹⁴NH₄⁺ in the growth medium. In a minor pathway, NO₂^- is reduced to N₂O via the toxic radical NO. With excellent detection sensitivities, N₂O serves as a monitor for trace NO₂^- reduction, even when cells are predominantly reducing NO₃^-. The analysis of N₂O isotopomers reveals that for cultures supplemented with mixed ¹⁵NO₃^- and ¹⁴NO₂^- enzymatic activity to reduce ¹⁴NO₂^- occurs immediately, even before ¹⁵NO₃^- reduction begins. Optical density and pH measurements are discussed in the context of acetate, formate and CO₂ production. H₂ production is repressed by NO₃^-; but in experiments with NO₂^- supplementation only, CERS detects H₂ produced by formate disproportionation after NO₂^- depletion.

Real-time and on-line monitoring of ethanol fermentation process by viable cell sensor and electronic nose

In this study, introduction of a viable cell sensor and electronic nose into ethanol fermentation was investigated, which could be used in real-time and on-line monitoring of the amount of living cells and product content, respectively. Compared to the conventional off-line biomass determination, the capacitance value exhibited a completely consistent trend with colony forming units, indicating that the capacitance value could reflect the living cells in the fermentation broth. On the other hand, in comparison to the results of off-line determination by high-performance liquid chromatography, the ethanol concentration measured by electronic nose presented an excellent consistency, so as to realize the on-line monitoring during the whole process. On this basis, a dynamic feeding strategy of glucose guided by the changes of living cells and ethanol content was developed. And consequently, the ethanol concentration, productivity and yield were enhanced by 15.4%, 15.9% and 9.0%, respectively. The advanced sensors adopted herein to monitor the key parameters of ethanol fermentation process could be readily extended to an industrial scale and other similar fermentation processes.

Non-invasive Raman spectroscopy for time-resolved in-line lipidomics

Oil-producing yeast cells are a valuable alternative source for palm oil production and, hence, may be one important piece of the puzzle for a more sustainable future.