Real time monitoring of acylations during solid phase peptide synthesis: a method based on electrochemical detection

Monitoring of acylation reactions during solid phase peptide synthesis is important to ensure high coupling yields in all steps of the synthesis. We describe in this paper a simple and reliable method for monitoring the time course of the acylation steps as well as the washing and deprotection steps during computer-controlled solid phase peptide synthesis. The method is based on the continuous measurement of electrical conductivity in the reaction vessel. It is shown that there is a close correspondence between the degree of acylation (as determined from the amount of 9-fluorenylmethoxycarbonyl- (Fmoc) groups released during deprotection) and the conductivity profile obtained during coupling of the amino acids to the growing peptide chain. The measurements are fed back to the computer providing data for software control of the duration of the acylation, deprotection and washing steps. The method is demonstrated with pentafluorophenol esters, but is equally applicable to dihydroxybenzotriazole esters and symmetric anhydrides using the Fmoc-polyamide strategy in a continuous flow set-up with dimethylformamide (DMF) as the general solvent.     

Multivariate statistical monitoring of batch processes: an industrial case study of fermentation supervision

This article describes the development of Multivariate Statistical Process Control (MSPC) procedures for monitoring batch processes and demonstrates its application with respect to industrial tylosin biosynthesis. Currently, the main fermentation phase is monitored using univariate statistical process control principles implemented within the G2 real-time expert system package. This development addresses integrating various process stages into a monitoring system and observing interactions among individual variables through the use of multivariate projection methods. The benefits of this approach will be discussed from an industrial perspective.     

Optimization of batch fermentation processes by graphical method

A graphical method is proposed for batch fermentation process optimization. Its objective function is the maximum output of the product when the time of process is fixed or free. The technique of optimization is based on Bellman's dynamic programming concepts and the assumption that the process can be described by mathematical models of generalized structure. An example of the proposed technique's application is presented.     

Detection of phase shifts in batch fermentation via statistical analysis of the online measurements: a case study with rifamycin B fermentation

Industrial production of antibiotics, biopharmaceuticals and enzymes is typically carried out via a batch or fed-batch fermentation process. These processes go through various phases based on sequential substrate uptake, growth and product formation, which require monitoring due to the potential batch-to-batch variability. The phase shifts can be identified directly by measuring the concentrations of substrates and products or by morphological examinations under microscope. However, such measurements are cumbersome to obtain. We present a method to identify phase transitions in batch fermentation using readily available online measurements. Our approach is based on Dynamic Principal Component Analysis (DPCA), a multivariate statistical approach that can model the dynamics of non-stationary processes. Phase-transitions in fermentation produce distinct patterns in the DPCA scores, which can be identified as singular points. We illustrate the application of the method to detect transitions such as the onset of exponential growth phase, substrate exhaustion and substrate switching for rifamycin B fermentation batches. Further, we analyze the loading vectors of DPCA model to illustrate the mechanism by which the statistical model accounts for process dynamics. The approach can be readily applied to other industrially important processes and may have implications in online monitoring of fermentation batches in a production facility.     

Optimization of batch fermentation processes. II. Optimum temperature profiles for batch penicillin fermentations

Optimization methods based on the continuous maximum principle and the calculus of variations were used to calculate optimum temperature profiles for batch penicillin fermentations. These methods were first applied to several general models to develop effective techniques for the numerical solution of the equations. Subsequently, these methods were applied to two particular models, derived from experimental data, and the optimum temperature profiles were determined. The results indicated that an improvement, in penicillin yield of about 15% was possible if the optimum temperature profiles were followed.     

Robust spectral estimation for speed of sound with phase shift correction applied online in yeast fermentation processes

Ultrasound techniques are well suited to provide real‐time characterization of bioprocesses in non‐invasive, non‐contact, and non‐destructive low‐power consumption measurements. In this paper, a spectral analysis method was proposed to estimate time of flight (TOF) between the propagated echoes, and its corresponding speed of sound (USV). Instantaneous power spectrum distribution was used for accurate detection of echo start times, and phase shift distribution for correcting the involved phase shifts. The method was validated by reference USV for pure water at 9–30.8°C, presenting a maximum error of 0.22%, which is less than that produced by the crosscorrelation method. Sensitivity analyses indicated a precision of 6.4 × 10^?3% over 50 repeated experiments, and 0.11% over two different configurations. The method was competently implemented online in a yeast fermentation process, and the calculated USV was combined with temperature and nine signal features in an artificial neural network. The network was designed by back propagation algorithm to estimate the instantaneous density of the fermentation mixture, producing a maximum error of 0.95%.     

Real time ultrasonic monitoring of hepatic cryosurgery

Cryosurgery has a number of advantages that make it particularly appealing in the treatment of liver cancer. However, a major problem in the clinical application of hepatic cryosurgery is the lack of a precise means of monitoring the freezing process in situ. Preliminary investigations on simulated tissue have shown that standard ultrasonography is capable of accurately determining the amount of frozen material during a cryosurgical procedure. To extend these results to living tissue, cryosurgery was performed, in vivo, on the livers of four mongrel dogs. An ultrasound imaging device using a new intraoperative ultrasound transducer monitored the entire process in real time. The results indicate that the entire freezing and thawing cycle can be monitored easily using real time ultrasound. During freezing, the solidification interface can be seen to move through the tissue allowing clear imaging of the cryolesion. After complete thawing, the cryolesion became less echogenic than before freezing and was therefore distinguishable under ultrasound. Postsurgical pathologic examination showed excellent correlation between the lesion size and its ultrasonic image.     

Optimization of batch fermentation processes. I. Development of mathematical models for batch penicillin fermentations

Two kinds of mathematical models have been developed for batch penicillin fermentations: (1) general models, based on averaged, nondimensionalized cell and penicillin synthesis curves from plant, scale fermentors and (2) particular models developed from specific sets of experimental data from two sources. Parameter-temperature functions used with the general models were assumed to have general shapes which could apply to many fermentations, i.e., they were based on the familiar temperature response of enzyme-catalyzed reactions. Parameter-temperature functions for the particular models were determined from experimental data for batch runs at various temperatures.     

On-line monitoring of lipase production in fermentation processes

Summary The results obtained in on-line monitoring of lipase production byCandida rugosa in a batch fermentation process are presented. For this purpose an automatic lipase concentration analyzer has been developed and tested. Its good reproducibility and its capability to perform the analysis in less time than the classical titrimetric method make it very suitable for on-line determination lipase concentration in fermentation processes.     

Application of dynamic calorimetry for monitoring fermentation processes

The rate of heat evolution (kcal/liter-hr) in mycelial fermentations for novobiocin and cellulase production with media containing noncellular solids was measured by an in situ dynamic calorimetric procedure. Thermal data so obtained have proved significant both in monitoring cell concentration during the trophophase (growth phase) and in serving as a physiological variable in the fermentation process. The validity of this technique has been demonstrated by closing the overall material and energy balances. The maintenance energy in a batch fermentation can also be calculated by integrating heat evolution data. This integration method is applicable to a fermentation lacking a precise cell growth curve. The maintenance coefficient, obtained for the novobiocin fermentation by Streptomyces niveus, is equal to 0.028 g glucose equivalent/g cell-hr. The production of novobiocin in the idio-phase (production phase) also correlates well with the amount of energy catabolixed for maintenance and this results in an observed conversion yield of glucose to novobiocin of 11.8 mg of novobiocin produced per gram of glucose catabolized. A new physiological variable, kilocalories of heat evolved per millimole of oxygen consumed, has been proposed to monitor the state of cells during the fermentation. This method may provide a simple way to monitor on-line shifts in the efficiency of cell respiration and changes in growth yields during a microbial process.     

On-line monitoring and controlling system for fermentation processes

A personal computer-based on-line monitoring and controlling system was developed for the fermentation of microorganism. The on-line HPLC system for the analysis of glucose and ethanol in the fermentation broth was connected to the fermenter via an auto-sampling equipment, which could perform the pipetting, filtration and dilution of the sample and final injection onto the HPLC through automation based on a programmed procedure. The A/D and D/A interfaces were equipped in order to process the signals from electrodes and from the detector of HPLC, and to direct the feed pumps, the motor of stirrer and gas flow-rate controller. The software that supervised the control of the stirring speed, gas flow-rate, pH value, feed flow-rate of medium, and the on-line measurement of glucose and ethanol concentration was programmed by using Microsoft Visual Basic under Microsoft Windows. The signal for chromatographic peaks from on-line HPLC was well captured and processed using an RC filter and a smoothing algorithm. This monitoring and control system was demonstrated to be effective in the ethanol fermentation of Zymomonas mobilis operated in both batch and fed-batch modes. In addition to substrate and product concentrations determined by on-line HPLC, the biomass concentration in Z. mobilis fermentation could also be on-line estimated by using the pH control and an implemented software sensor. The substrate concentration profile in the fed-back fermentation followed well the set point profile due to the fed-back action of feed flow-rate control.     

Comparative metabolomic analysis on industrial continuous and batch ethanol fermentation processes by GC-TOF-MS

The intracellular metabolic profile characterization of Saccharomyces cerevisiae throughout industrial ethanol fermentation was investigated using gas chromatography coupled to time-of-flight mass spectrometry. A total of 143 and 128 intracellular metabolites in S. cerevisiae were detected and quantified in continuous and batch fermentations, respectively. The two fermentation processes were both clearly distinguished into three main phases by principal components analysis. Furthermore, the levels of some metabolites involved in central carbon metabolism varied significantly throughout both processes. Glycerol and phosphoric acid were principally responsible for discriminating seed, main and final phases of continuous fermentation, while lactic acid and glycerol contributed mostly to telling different phases of batch fermentation. In addition, the levels of some amino acids such as glycine varied significantly during both processes. These findings provide new insights into the metabolomic characteristics during industrial ethanol fermentation processes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Analysis of fermentation processes using flow microflourometry: Single-parameter observations of batch bacterial growth

The laser flow microfluorometer (FMF) can determine the amounts of certain components in single cells at sample rates of several thousand cells per second. This technique has been employed to characterize Bacillus subtilis populations in batch fermentations with different inocula. Protein and distributions obtained by FMF analyses at different times during the batch have been decomposed using an optimized fit of summed subpopulation distributions. The results of these decomposition calculations, some of which have been approximately confirmed by independent microscopic observations, indicate cells relative numbers of single rods, cell chains, spores, and swollen rounded cells change dramatically during the entire fermentation including the stationary phase. The dynamics of these subpopulations may be related to secondary metabolite production.     

Analysis of fermentation processes using flow microfluorometry: Single-parameter observations of batch bacterial growth

The laser flow microfluorometer (FMF) can determine the amounts of certain components in single cells at sample rates of several thousand cells per second. This technique has been employed to characterize Bacillus subtilis populations in batch fermentations with different inocula. Protein and nucleic acid distributions obtained by FMF analyses at different times during the batch have been decomposed using an optimized fit of summed subpopulation distributions. The results of these decomposition calculations, some of which have been approximately confirmed by independent microscopic observations, indicate that the relative numbers of single rods, cell chains, spores, and swollen rounded cells change dramatically during the entire fermentation including the stationary phase. The dynamics of these subpopulations may be related to secondary metabolite production.     

Performances of aseptic sampling devices for on-line monitoring of fermentation processes

Two liquid sampling systems, which are set in the bioreactor and can be sterilized in place, are described. They are composed primarily of an inorganic membrane filter which is either stationary or is set in a rotating motion. These systems have been tested during three types of fermentation processes (ethanol, lactic acid, and polysaccharide productions). The rotating system gave better filtration performances than the stationary sampler which can be used only in alcoholic fermentation. The rotating sampler was coupled with a high-pressure liquid chromatograph for the on-line quantitation of the major compounds present in the filtrate. The results are in good agreement with those obtained from off-line analysis on samples taken manually. (c) 1992 John Wiley & Sons, Inc.     

Assessment of in-line near-infrared spectroscopy for continuous monitoring of fermentation processes

The application of NIR in-line to monitor and control fermentation processes was investigated. Determination of biomass, glucose, and lactic and acetic acids during fermentations of Staphylococcus xylosus ES13 was performed by an interactance fiber optic probe immersed into the culture broth and connected to a NIR instrument. Partial least squares regression (PLSR) calibration models of second derivative NIR spectra in the 700-1800 nm region gave satisfactory predictive models for all parameters of interest: biomass, glucose, and lactic and acetic acids. Batch, repeated batch, and continuous fermentations were monitored and automatically controlled by interfacing the NIR to the bioreactor control unit. The high frequency of data collection permitted an accurate study of the kinetics, supplying lots of data that describe the cultural broth composition and strengthen statistical analysis. Comparison of spectra collected throughout fermentation runs of S. xylosus ES13, Lactobacillus fermentum ES15, and Streptococcus thermophylus ES17 demonstrated the successful extension of a unique calibration model, developed for S. xylosus ES13, to other strains that were differently shaped but growing in the same medium and fermentation conditions. NIR in-line was so versatile as to measure several biochemical parameters of different bacteria by means of slightly adapted models, avoiding a separate calibration for each strain.