On-line estimation of biomass through pH control analysis in aerobic yeast fermentation systems

Ammonia nitrogen recovery from biogas slurry by SCP production using Candida utilis

The safe and robust yeast Candida utilis was employed for nitrogen recovery as single cell protein from biogas slurry. The maximum biomass of 6.2 g/L with protein content of 53.5% was produced in batch cultivation with glucose as the carbon source, C/N ratio of 3:1, NH₄⁺-N concentration of 3000 mg/L, initial pH of 8.0, and the addition of 0.35% (w/v) Na₂HPO₄. It was speculated that C. utilis can grow well with free ammonia below 197 mg/L. In fed-batch fermentation, a biomass of 14.8 g/L was obtained, and the maintenance of aerobic conditions was critical to improving the production of single cell protein. The sterilized and non-sterilized biogas slurry can be used as an effective pH regulator. The obtained single cell protein was a nutritious, safe, and reliable protein source. This study provides novel insights into nitrogen recovery via C. utilis as a single cell protein from biogas slurry.

Fermentation of Saccharomyces cerevisiae - Combining kinetic modeling and optimization techniques points out avenues to effective process design

A combined experimental/theoretical approach is presented, for improving the predictability of Saccharomyces cerevisiae fermentations. In particular, a mathematical model was developed explicitly taking into account the main mechanisms of the fermentation process, allowing for continuous computation of key process variables, including the biomass concentration and the respiratory quotient (RQ). For model calibration and experimental validation, batch and fed-batch fermentations were carried out. Comparison of the model-predicted biomass concentrations and RQ developments with the corresponding experimentally recorded values shows a remarkably good agreement for both batch and fed-batch processes, confirming the adequacy of the model. Furthermore, sensitivity studies were performed, in order to identify model parameters whose variations have significant effects on the model predictions: our model responds with significant sensitivity to the variations of only six parameters. These studies provide a valuable basis for model reduction, as also demonstrated in this paper. Finally, optimization-based parametric studies demonstrate how our model can be utilized for improving the efficiency of Saccharomyces cerevisiae fermentations.

Model-based analysis on the relationship of signal quality to real-time extraction of information in bioprocesses

Quality by design (QbD) is a current structured approach to design processes yielding a quality product. Knowledge and process understanding cannot be achieved without proper experimental data; hence requirements for measurement error and frequency of measurement of bioprocess variables have to be defined. In this contribution, a model-based approach is used to investigate impact factors on calculated rates to predict the obtainable information from real-time measurements (= signal quality). Measurement error, biological activity, and averaging window (= period of observation) were identified as biggest impact factors on signal quality. Moreover, signal quality has been set in context with a quantifiable measure using statistical error testing, which can be used as a benchmark for process analytics and exploitation of data. Results have been validated with data from an E. coli batch process. This approach is useful to get an idea which process dynamics can be observed with a given bioprocess setup and sampling strategy beforehand.

Characterization of Nerolidol Biotransformation Based on Indirect On-Line Estimation of Biomass Concentration and Physiological State in Batch Cultures of Aspergillus niger

Biotransformation of the sesquiterpenoid trans-nerolidol by Aspergillus niger has previously been investigated as a method for the formation of 12-hydroxy-trans-nerolidol, a precursor in the synthesis of the industrially interesting flavor alpha-sinensal. We characterized biotransformations of cis-nerolidol, trans-nerolidol, and a commercially available cis/trans-nerolidol mixture in repeated batch cultures of A. niger grown in computer-controlled bioreactors. On-line quantification of titrant addition in pH control allowed characterization of (1) maximal specific growth rate in exponential growth phases, (2) exponential induction of acid formation in postexponential phases, (3) inhibition of organic acid formation after nerolidol addition, and (4) exponential recovery from this inhibition. Addition of a (+/-)-cis/trans-nerolidol mixture during exponential or postexponential phase to cultures grown in minimal medium at high dissolved oxygen tension (above 50% air saturation), to cultures at low dissolved oxygen tension (5% air saturation), or to cultures grown in rich medium demonstrated that the physiological state before nerolidol addition had a major influence on biotransformation. The maximal molar yield of 12-hydroxy-trans-nerolidol (9%) was obtained by addition of a (+/-)-cis/trans-nerolidol mixture to the culture in the postexponential phase at high dissolved oxygen tension in minimal medium. Similar yields were obtained in rich medium, where the rate of biotransformation was doubled.

Software sensors for fermentation processes

Four software sensors based on standard on-line data from fermentation processes and simple mathematical models were used to monitor a number of state variables in Escherichia coli fed-batch processes: the biomass concentration, the specific growth rate, the oxygen transfer capacity of the bioreactor, and the new R(O/S) sensor which is the ratio between oxygen and energy substrate consumption. The R(O/S) variable grows continuously in a fed-batch culture with constant glucose feed, which reflects the increasing maintenance demand at declining specific growth rate. The R(O/S) sensor also responded to rapid pH shift-downs reflecting the increasing demand for maintenance energy. It is suggested that this sensor may be used to monitor the extent of physiological stress that demands energy for survival.

Microbial biomass estimation

The development of a fully automated on-line monitoring and control system is very important in bioprocesses. One of the most important parameters in these processes is biomass. This review discusses different methods for biomass quantification. A general definition of biomass and biovolume are presented. Interesting concepts about active but not culturable cells considerations are included as well as concepts that must be taken into account when selecting biomass quantification technology. Chemical methods have had few applications in biomass measurement to date; however, bioluminescence can selectively enumerate viable cells. Photometric methods including fluorescence and scattered light measurements are presented. Reference methods including dry and wet weight, viable counts and direct counts are discussed, as well as the physical methods of flow cytometry, impedancimetric and dielectric techniques.

Control of yeast fed-batch process through regulation of extracellular ethanol concentration

At high growth rates, the biomass yield of baker's yeast (Saccharomyces cerevisiae) decreases due to the production of ethanol. For this reason, it is standard industrial practice to use a fed-batch process whereby the specific growth rate, mu, is fixed at a level below the point of ethanol production, i.e., mucrit. Optimally, growth should be maintained at mucrit, but in practice, this is difficult because mucrit is dependent upon strain and culture conditions. In this work, growth was maintained at a point just above mucrit by regulating ethanol concentration in the bioreactor. The models used for control design are shown, as are the experimental results obtained when this strategy was implemented. This technique should be applicable to all microorganisms that exhibit an "overflow" type metabolism.

Modification of A-stat for the characterization of microorganisms

Two novel modifications of continuous culture with gradual change of dilution rate (A-stat): D-stat and auxo-accelerostat were evaluated in the studies of the effect of changing individual environmental parameters (T, pH, pO(2), substrate concentration, etc.) on growth characteristics of different microorganisms. Common for those cultivation methods is that one environmental parameter is programmed to change with constant change rate (change-stat) while the others are kept constant or in the range not affecting the growth characteristics. The environment response growth curves were obtained starting with chemostat (in A-stat and D-stat) or auxostat (in auxo-accelerostat) steady-state cultures followed by change of set-point value of the desired cultivation parameter. Physiological studies of Saccharomyces sp. and Lactococcus lactis were combined with validation of the different modifications of the A-stat method based on well-known cultivation techniques: chemostat, pH-auxostat, pO(2)-auxostat CO(2)-auxostat and fed-batch. The auxo-accelerostat was shown to be very efficient for cell characterization and dynamic studies in growth environments with excess of essential substrates. Choosing the rate of change of environmental parameters was shown to be critical in comparative physiological studies of microorganisms.

Influence of pH on the xylose reductase activity of Candida guilliermondii during fed-batch xylitol bioproduction

The influence of pH on the xylose reductase (XR) activity was studied. The fed-batch fermentation using exponential feeding rate was employed to produce xylitol. The feeding started when the xylose concentration in the fermenter reached 50 g/l and the pH was adjusted to 2.5, 4.0 or 6.0. The best results for XR activity (0.567 U/mg(protein)) and xylitol volumetric productivity (1.06 g/l.h) were achieved with pH 6.0.

Automatic inducer addition and harvesting of recombinant Escherichia coli cultures based on indirect on-line estimation of biomass concentration and specific growth rate

This article describes a novel bioreactor configuration for production optimization of recombinant proteins in Escherichia coli. Inducer addition and harvesting are controlled on-line based on indirect estimation of biomass concentration and specific growth rate from addition of NaOH to maintain constant pH. When either a predetermined biomass concentration is reached or the cultures have obtained, a constant specific growth rate inducer is introduced automatically. The induction period is ended by automatic harvesting of the cultures either at a predetermined biomass concentration or when substrate (in this study glucose) is depleted, detected as an increase of pH, or dissolved oxygen tension. During harvesting, metabolic activities are quenched within 3 min by cooling of the cell suspension. The system has been used to optimize expression of glutathione S-transferase (GST) fusion protein of the ligand binding domain of mouse peroxisome proliferator-activated receptor, GST-PPARalpha LBD. Total yield of GST-PPARalpha LBD was independent of the time of inducer addition as long as the length of induction period corresponded to at least 0.25 cell divisions while the yield of soluble GST-PPARalpha LBD, the only active form, increased with the length of induction period. Highest yields were obtained when the inducer was added at low cell concentration as soon as constant specific growth rate was detected, resulting in induction periods corresponding to 3.4 +/- 0.4 cell divisions. The specific growth rate remained almost constant for one cell division after inducer addition, whereafter it decreased. No decrease of specific growth rate was observed when inducer was added in the lag-phase, and no soluble protein was produced. These results suggest that solely soluble GST-PPARalpha LBD acts as a growth inhibitor and that GST-PPARalpha LBD is expressed predominantly as inclusion bodies immediately after inducer addition whereas the proportion expressed as soluble protein is increased after 1 h of induction. Compared to the procedures, which are generally used for protein expression in the laboratory, this system is less labor intensive, it automatically provides recording of biomass concentration and specific growth rate, and it allows direct comparisons between expression of different proteins and performance of different constructs since the induction period is linked to growth.