Parallel use of shake flask and microtiter plate online measuring devices (RAMOS and BioLector) reduces the number of experiments in laboratory-scale stirred tank bioreactors

Background Conventional experiments in small scale are often performed in a Black Box fashion, analyzing only the product concentration in the final sample. Online monitoring of relevant process characteristics and parameters such as substrate limitation, product inhibition and oxygen supply is lacking. Therefore, fully equipped laboratory-scale stirred tank bioreactors are hitherto required for detailed studies of new microbial systems. However, they are too spacious, laborious and expensive to be operated in larger number in parallel. Thus, the aim of this study is to present a new experimental approach to obtain dense quantitative process information by parallel use of two small-scale culture systems with online monitoring capabilities: Respiration Activity MOnitoring System (RAMOS) and the BioLector device. Results The same mastermix (medium plus microorganisms) was distributed to the different small-scale culture systems: 1) RAMOS device; 2) 48-well microtiter plate for BioLector device; and 3) separate shake flasks or microtiter plates for offline sampling. By adjusting the same maximum oxygen transfer capacity (OTRmax), the results from the RAMOS and BioLector online monitoring systems supplemented each other very well for all studied microbial systems (E. coli, G. oxydans, K. lactis) and culture conditions (oxygen limitation, diauxic growth, auto-induction, buffer effects). Conclusions The parallel use of RAMOS and BioLector devices is a suitable and fast approach to gain comprehensive quantitative data about growth and production behavior of the evaluated microorganisms. These acquired data largely reduce the necessary number of experiments in laboratory-scale stirred tank bioreactors for basic process development. Thus, much more quantitative information is obtained in parallel in shorter time.Cluster of Excellence “Tailor-Made Fuels from Biomass”, which is funded by the Excellence Initiative by the German federal and state governments to promote science and research at German universities

Experimental design for fermentation media development : statistical design or global random search?

The diversity of combinatorial interactions of medium components with the metabolism of cells as wed as the large number of medium constituents necessary for cellular growth and production do not permit satisfactory detailed modelling. For this reason, experimental search procedures in simultaneous shaking flask experiments are used to optimise fermentation media. As an alternative to the methods of statistical experimental design employed in this field for many decades, the use of stochastic search procedures has been evaluated recently, since these require neither the unimodality of the response surface nor limitations in the number of medium components under consideration. Genetic algorithms were selected due to their basic capability for efficient exploration of large variable spaces. Using a genetic algorithm, it has been experimentally verified, with the aid of process examples, that process improvements can be achieved both for microbial and enzymatic conversions and for cell cultures despite the large number of medium components under simultaneous consideration (about 10 or more). In exploring a new variable space, process improvements of more than 100% were generally achieved. For initial reaction conditions previously 'optimised' via standard procedures it has been possible in most cases to achieve a further improvement of 20-40% of the target quantity. Although the genetic algorithm can be very efficient for exploration of large variable spaces, it is improbable that a 'global optimum' can be precisely identified because of the relatively small number of shaking flask experiments usually performed. As a consequence, a combination of highly directed random searches to explore the n-dimensional variable space with the genetic algorithm and subsequent application of classical statistical experimental design is recommended for media development