The occurrence of bacteriophages in spirit vinegar fermentation

Summary Bacteriophages in concentrations of approximately 10⁸–10⁹ particles/ml were demonstrated in culture lysates of industrial submerged spirit vinegar fermentations running in different European vinegar factories. Besides frequently found fragments of phages, two types of phages could be described. The frequent type I seems to belong to Bradley-group A; type II, with a remarkably larger head, may belong to group C. For simulation in the laboratory a phage-contaminated industrial culture was kept over 102 charges (time of cycle 24->240 h) in a semicontinuously operated 8-1 fermentor. A close relationship between spontaneous breakdowns and phage occurrence exists. Discrimination of breakdowns caused by lack of ethanol could not be made. Attempts to establish a bioassay for the phages failed presumably because of the instability of the phages. Continuing cultivation and waiting for secondary growth finally results in stable and productive fermentation.     

Importance of agitation in acetone-butanol fermentation

The specific rates of anaerobic solvent production by Clostridium acetobutylicum increased with increasing fermentor impeller speed from 190 to 340 rpm (N(Re) = 3.93 x 10(4)). The maximum values were 5.54, 3.85, and 0.8 mmol/h . g cell for butanol, acetone, and ethanol, respectively. Corresponding rates for respective gases produced were 11.60 and 15.88 mmol/h . g cell for H(2) and CO(2). Further increases in agitation speed resulted in generally decreasing specific production rates to the point of inactive fermentation at 560 rpm. A competition observed between the cellular subsystems for butanol + butyric acid and biomass biosynthesis was evaluated through expressing the energetic yield coefficients. An imbalance between the production and outflux of the former metabolites is apparently further enhanced by a mechanical damage of the cells at high shear rates. A correlation was developed between the production of gases and solvents pointing at both H(2)-to-solvent as well as CO(2)-to-solvent ratios following the same pattern, peaking at 410 rpm.     

Recycle in fermentation processes

Until recently, the recycle of the solid (microbial), liquid, or gaseous phases in microbiological processes has only been practiced rarely, with the notable exception of activated sludge processes for wastewater treatment, where recycling of a large fraction of the microbial phase is essential for process stability and performance. During the last decade, the economic impact of a number of politically motivated changes with respect to energy and feedstock costs and availability, and legislation directed towards markedly higher levels of environmental protection have encouraged the evaluation and subsequent development of recycle technology in the fermentation industry. Many of the developments have occurred in isolation and some have failed to result in either an improvement in process economics or any reduction in the quantity of pollutants discharged. This article seeks to review the present diversity of approaches to recycle technology in fermentation processes in order to provide a sensible basis for future developments.     

Kinetics of fermentation processes

Kinetic studies on fermentation processes were made and a general equation of production rate was newly presented applying the kinetic theory on mierobial cell growth which was reported previously by the authors.^l,2 Equations for product concentration in fermentation time courses were derived by developing mathematically the general equation of production rate, and characteristic properties of fermentation processes were clarified. Some examples of fermentations were analyzed kinetically using the new kinetic theory. The calculated values of product, and cell concentrations were in good agreement with the observed values.     

Optimizing scale-up fermentation processes

There are many aims associated with the optimization of fermentation processes. Optimization is expected to increase the yield of the final product but the process must be compliant with good manufacturing practices, the available equipment and the expected final scale of operation. Dealing with genetically modified microorganisms that overproduce recombinant protein has the advantage that the vast majority of the processes use only three different species, namely Escherichia coli, Saccharomyces cerevisiae and Pichia pastoris. Standard processes for each organism are described in textbooks and serve as a basis for the development of a tailored process. This article outlines the general philosophy that we have devised to ensure an efficient approach of scaling up fermentation processes for biopharmaceutical purposes, in a multidisciplinary environment.     

Sliding-mode control of fermentation processes

Continuous fermentation processes described by two nonlinear differential equations with uncertain parameters are considered. Sliding mode control design for these processes is proposed. The control design is carried out with direct use of nonlinear model, expert knowledge and on-line measurement of output variable only. Chattering phenomena are avoided by realizing the sliding mode with respect to the control input derivative. The excellent performance of presented control is proved through simulation investigations.     

Knowledge-based control of fermentation processes

A decade has passed since the first applications of a knowledge-based approach to the control of bioprocesses were reported. During this period, both the development and application of intelligent control in biotechnology have undergone remarkable evolution in terms of concepts, objectives, and tools. Stimulated by rapid progress in the field of real-time expert systems, knowledge-based methodology for the control of fermentation processes has now reached a more mature phase. A growing interest among the biotechnology community and intensive, realistic, and fruitful research being undertaken both in universities and in industry suggest that large-scale application of knowledge-based systems for the control of bioprocesses is inevitable. This article provides a concise summary of the main achievements in this new area and discusses recent trends, porblems, and perspectives.     

Metabolic regulation of fermentation processes

To compete in nature against other forms of life, microorganisms possess regulatory mechanisms which control production of their metabolites, thus, protecting against overproduction and excretion of these primary and secondary metabolites into the environment. To effect such an economical form of life, they possess regulatory mechanisms which control production of these metabolites and protect against overproduction and excretion into the environment of excess concentrations. In the field of industrial fermentation, the opposite concept prevails. Fermentation microbiologists search for a rare overproducing strain in nature, then further deregulate the microorganism so that it overproduces huge quantities of a desired commercially important product such as a metabolite or an enzyme. Deregulation is brought about by nutritional as well as classical and molecular genetic manipulations to bypass and/or remove negative regulatory mechanisms and to enhance positive regulatory mechanisms. These mechanisms include induction, nutritional regulation by sources of carbon, nitrogen and phosphorus, and feedback control. The controls and their modification by biotechnologists are the subjects of this review.     

Studies on fermentation processes in silage

Zusammenfassung Die Menge vergärbarer Kohlenhydrate in Klee und Luzerne ist meistens zu gering, um eine zureichende Milchsäuregärung zu gewährleisten. Nur ein geringer Teil der gesamten Kohlenhydrate des Grünfutters wird zu Milchsäure vergoren. Durch Hydrolyse kann ein Teil der nicht direkt vergärbaren Kohlenhydrate für die Milchsäurebakterien zugänglich werden. Eine solche Hydrolyse scheint bei der Grünfuttergärung vor sich zu gehen, besonders bei einem Material mit relativ hohem Trockensubstanzgehalt, wahrscheinlich weil bei den hohenph-Werten, die in solchem Grünfutter vorliegen, die Pflanzen- und Bakterien-Carbohydrasen aktiv sind und weil die Carbohydrasen produzierenden Bakterien am Anfang der Gärung gut wachsen.Zusatz von verschiedenen Zuckerarten, wie Glucose, Maltose, Saccharose und auch Dextrin, begünstigen die Milchsäuregärung. Verschiedene Stärkearten, in fester Form fein verteilt zugesetzt, werden von den Pflanzen- und Bakterienamylasen nicht oder nur unbedeutend angegriffen und können deshalb durch die Milchsäurebakterien nicht vergoren werden. Malzamylasen vermögen dagegen solche Stärkearten zu hydrolysieren und sind im Grünfutter hoch aktiv. In allen Versuchen begünstigt deshalb Zusatz von Malz oder Malz + Stärke die Milchsäuregärung in hohem Grade. Wahrscheinlich vermögen die Amylasen und die übrigen Carbohydrasen des Malzes auch einen Teil der Polysaccharide des Pflanzenmaterials zu hydrolysieren.     

Computer control of fermentation processes

A review of computer control of fermentation processes is presented. Hardware and software technologies that have been used to implement computer control are discussed. This includes instrumentation, interfacing techniques, computer hardware configurations, data logging and documentation, displays and man-machine interaction, low-level control, back-up and error detection and programming techniques. Advanced control of fermentation processes with the utilization of modern control techniques is also presented. This topic is divided into steady state optimization and dynamic optimization. Finally, on-line estimation of bioreactor parameters for feedback control is presented.     

Studies on fermentation processes in silage

Zusammenfassung Die Beimischung von mäßigen Mengen von Mehl verschiedener Getreidearten in Silage fördert die Milchsäuregärung nicht in nennenswertem Grad, da rohe Stärke nur in unbedeutendem Umfang von den Amylasen (hauptsächlich -Amylasen) des Getreidemehls oder des Grünfutters in für Milchsäurebakterien vergärbaren Zucker hydrolysiert werden kann. Durch -Amylase, welches Enzym in Malz in großen Mengen vorkommt, wird dagegen die rohe Stärke derart angegriffen, daß dadurch in der Silage ein fortgesetzter Abbau zu Milchsäure durch die sich dort befindenden Milchsäurebakterien erfolgt.Durch Beimischung verhältnismäßig geringer Mengen enzymreichen Malzmehles ist es demnach unter praktischen Bedingungen möglich, einen großen Teil der Stärke, welche dem Futter mit den verschiedenen Getreidemehlen zugeführt wurde, den Milchsäurebakterien zugänglich zu machen. Die starke amylolytische Enzymaktivität bei Mischungen von Malz-und Getreidemehl ist ein additiver Effekt von der -Amylase des Malzes und der -Amylase des Malzes, des Getreides und des Grünfutters.     

Studies on fermentation processes in silage

Zusammenfassung Kohlenhydrat-Zusatzmittel dienen bei der natürlichen Gärfutterbereitung einerseits als Nährstoffe für die Mikroorganismen, andererseits beeinflussen sie die Feuchtigkeit des Gärfutters durch ihr Absorptionvermögen.Bei der Milchsäuregärung kann Zucker vollständig ausgenützt werden, Stärke und Cellulose dagenen nicht, oder nur unbedeutend. Zusatz von Gerstenmalz hat wegen seines höheren Zuckerinhaltes und wegen seiner diastasewirkung einen wesentlich besseren Effekt als Gerstegrütze.Malz, Grütze und Cellulose besitzen ein hohes Absorptionsvermögen und können dadurcheine günstige Wirkung bei der Gärfutterbereitung ausüben.

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These studies are still in progress. We are indebted to the Swedish Foundation: Fonden för främjande av forskinings- och försöksverksamheten på jordbrukets område, for generous financial support.     

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.     

Optimal control of continuous fermentation processes

Three layer control structure is proposed for optimal control of continuous fermentation processes. The start-up optimization problems are solved as a first step for optimization layer building. A steady state optimization problem is solved by a decomposition method using prediction principle. A discrete minimum time optimal control problem with state delay is formulated and a decomposition method, based on an augmented Lagrange's function is proposed to solve it. The problem is decomposed in time domain by a new coordinating vector. The obtained algorithms are used for minimum time optimal control calculation of Baker's Yeast fermentation process.List of Symbols x(t) g/l biomass concentration - s(t) g/l limiting substrate concentration - x ⁰ g/l inlet biomass concentration - s ⁰(t) g/l inlet substrate concentration - D(t) h^–1 dilution rate - (t) h^–1 specific growth rate - Y g/g yield coefficient - (t) h^–1 specific limiting substrate consumption rate - k _D h^–1 disappearing constant - w ₁, w ₂ known constant or piece-wise disturbances - _m h^–1 maximum specific growth rate - k _s g/l Michaelis-Menten's parameter - h time delay - x ₀, s ₀ g/l initial concentrations - ¯x, ¯s, ¯D optimal steady state value - V _min , V _max , v=x,s,d,t bounds of variables - t h sampling period - K number of steps in the optimization horison - Js, J _d performance indexes - L _s Lagrange's function - L _d Lagrange's functional - ₀ weighting coefficient for the amount of the limiting substrate throwing out of the fermentor - ₁, ₂ dual variables of Lagrange's function - steps in steady state coordination procedure - errors values for steady state coordination process - _v , v=x, s conjugate variables of Lagrange's functional - _v , v=x,s penalty coefficients of augmented Lagrange's functional - _v , v=x, s interconnections of the time - e _v , v=x,s, D, _x , _s gradients of Lagrange's functional - j, l indexes of calculation procedures - values of errors in calculations The researches was supported by National Scientific Research Foundation under grants No NITN428/94 and No NITN440/94     

Neural network modelling of fermentation processes

This paper deals with an application of neural networks for chemostat modelling. A feedforward neural network, taking into account culture memory is proposed for the specific growth rate approximation within the framework of the classical unstructured model. The investigations are carried out for different network topologies on the example of the growth of a strain Saccharomyces cerevisiae on a glucose limited medium and a model suitable for control synthesis is proposed.     

Automatic computer control of fermentation processes

The application of an optimization algorithm to fermentation processes is described, which is based on information received by means of cascading the input quantities with pseudo random binary signals. The results in optimization of temperature, pH-value as well as productivity are presented and discussed.     

Characterization of six Leuconostoc fallax bacteriophages isolated from an industrial sauerkraut fermentation

Six bacteriophages active against Leuconostoc fallax strains were isolated from industrial sauerkraut fermentation brines. These phages were characterized as to host range, morphology, structural proteins, and genome fingerprint. They were exclusively lytic against the species L. fallax and had different host ranges among the strains of this species tested. Morphologically, three of the phages were assigned to the family Siphoviridae, and the three others were assigned to the family Myovidae: Major capsid proteins detected by electrophoresis were distinct for each of the two morphotypes. Restriction fragment length polymorphism analysis and randomly amplified polymorphic DNA fingerprinting showed that all six phages were genetically distinct. These results revealed for the first time the existence of bacteriophages that are active against L. fallax and confirmed the presence and diversity of bacteriophages in a sauerkraut fermentation. Since a variety of L. fallax strains have been shown to be present in sauerkraut fermentation, bacteriophages active against L. fallax are likely to contribute to the microbial ecology of sauerkraut fermentation and could be responsible for some of the variability observed in this type of fermentation.     

Energy balance in solid state fermentation processes

It was applied a macroscopic energy balance to a solid state fermentation process and an electron balance in order to estimate the temperature and the heat evolved in the process. There were employed several equations that describe the development of the system and offer the possibility to design or control such fermentations.     

Physiological state control of fermentation processes

In this article a novel approach to the control of fermentation processes is introduced. A "physiological state control approach" has been developed using the concept of representing fermentation processes through the current physiological state of the cell culture. No conventional mathematical model is required for the synthesis of such a control system.The main idea is based on the fact that during batch, feed-batch, or even continuous cultivation the physiological characteristics of the cell population, jointly expressed by the term "physiological state", are not constant but rather variable, which is reflected in expected or unexpected changes in the behavior of the control plant, and which requires flexible alteration of the current control strategy. The proposed approach involves decomposition of the physiological state space into several subspaces called "physiological situations." In every physiological situation the cell population expresses stable characteristics, and therefore an invariant control strategy can be effectively applied. The on-line functions of the physiological state control system consist of the calculation of physiological state variables, determination of the current physiological situation as an element of a previously defined set of known physiological situations, switching of the relevant control strategy, and calculation of the control action. Attention is focused on the synthesis of the novel and nonstandard part of the control system - the algorithm for online recognition of the current physiological state. To this end an effective approach, based on artificial intelligence methods, particularly fuzzy sets theory and pattern recognition theory, was developed. Its practical realization is demonstrated using data from a continuous fermentation process for single cell protein production.