HUNGARIAN JOURNAL OF INDUSTRY AND CHEMISTRY Vol. 45(2) pp. 19–21 (2017) hjic.mk.uni-pannon.hu DOI: 10.1515/hjic-2017-0015 EXAMINATION OF INNOVATIVE HIGH-THROUGHPUT FERMENTATIONS ÁRON NÉMETH* Department of Applied Biotechnology and Food Science, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, 1111, HUNGARY During the investigation of fermentations, issues such as the need for numerous parallel experiments with re- gard to strain improvement or screening were often met, or in the case of media optimization the need for online measurements to avoid a lack of night-samples was also required. Therefore, several new instruments were in- troduced to solve one or more of these problems: impedimetric- and reverse-spin-technologies (RST) were compared via fermentation of a well-known species of yeast, Saccharomyces cerevisiae, under both aerobic and anaerobic conditions, resulting in a diauxic growth curve. To identify the most accurate method, a well- known mathematical description was fitted to the measured data. Since the initial parameters were considered reliable as they originated from real experiments, during model fitting, the parameters were further fine-tuned, and the less modifications reported the better the system since it produces a growth curve that is more similar to standard bioreactors. According to our study, the impedimetric equipment was more efficient, and could run 40 parallel experiments, but the RST was more flexible. Keywords: fermentation, high-throughput, scale-down, online measurement, mathematical model- ling 1. Introduction Developments in fermentations face numerous chal- lenges which may require expensive analytics, media components or special tools to facilitate aseptic work and sampling. Furthermore, these biological processes vary significantly. To overcome these difficulties, the process should be scaled-down in combination with high-throughput methods, resulting in many parallel, small-scale experiments. Such experiments are used in terms of strain and technological improvements as well as media optimization. A good solution may be the consideration of mi- cro-bioreactors. However, because of their high invest- ment and operational costs, they have not become wide- spread in Hungary. While each can provide almost eve- ry service required for bioreactors, for example, aera- tion, agitation and sampling in addition to pH and tem- perature control, they possess considerable limitations, namely non-standard conformations resulting in scale- up difficulties, or special measurement techniques that are incompatible with standard methods. A readily available alternative, to be more precise, Microtiter-Plates (MTP), for microscale high- throughput fermentations has already been presented and reported [1]. The basic principle is to use sterile ’96-Well’ microtiter plates with a special “sandwich cover” that facilitate sufficient aeration but reduce the likelihood of cross-infection. This system requires an *Correspondence: naron@f-labor.mkt.bme.hu adapter to be able to mount microtiter plates into a commercial rotary incubator shaker. The next issue is to analyse and follow the processes in the wells since their volumes are so small (ca. 100 L) that sampling is im- possible. Therefore, either a microplate reader is re- quired or a simple office scanner to produce a grey- scale photo taken from the bottom of the plate. The col- our of high cell-densities is close to white, but empty broths have a black background. In the case of species that produce high levels of acid, like Lactobacillus, even a pH indicator can be applied and besides a grey- scale photo a coloured one has to be taken as well; al- ternatively, CaCO3 should be added at the start but this can disturb the scanner-based “photometry”. Our partner (enzyscreen.com) even offers micro- titer plates for fed-batch fermentations. To achieve this, the feed components are adsorbed onto the material of the MTP, and are programmed to slowly release the fresh substrate during cultivation. However, another innovative solution has been developed for small-scale fermentations using online monitoring: Biosan Ltd. (Lithuania) applies Reverse-Spin Technology in the equipment of their Personal Bioreactor (RTS-1). This cost-effective equipment rotates a standard Falcon tube, filled with ca. 10 ml of fermentation media, at different rotation speeds in several directions at various con- trolled temperatures using a variety of aeration holes on the cap. This instrument also involves a photometer to facilitate the programming of measuring frequencies at a given wavelength (= 850 nm). For calibrated and reproducible measurements, a constant film layer is necessary, therefore, the instruments increase the rate of NÉMETH Hungarian Journal of Industry and Chemistry 20 rotation until 2000 rpm. The changes in parameters ef- fect shear forces as well as levels of aeration. Finally, this comparative study used an impedimet- ric system by SY-LAB (Austria) which is called Bac- Trac 4100 [2]. This equipment possesses a block ther- mostat composed of 40 measurement cells, each con- taining 4 electrodes. One pair of them follows the changes in the impedance of the media, M%, caused by the secreted acids and metabolites. In the case of micro- organisms that exhibit high levels of ionic strength in the media, it is hard to detect M%, therefore, with the application of a different frequency the changes in im- pedance on the other electrode surface (E%) can be fol- lowed. In direct measurements, these electrodes are immersed directly into the culture, but in the case of indirect measurements, they are rinsed with KOH which can adsorb the formed CO2 released by the culture. While this system does not possess mixer/aerator solu- tions, this result can be transferred carefully to the known systems, namely benchtop fermenters or shaking flasks. However, it is able to follow forty different cul- tures. In this study, a well-known model organism (S. cerevisiae) was chosen that exhibits special biochemical behaviour. It was used to test the compare the ability of the three systems introduced above. What is special about S. cerevisiae is that it can change from aerobic to anaerobic cultivation according to Pasteur and Crabtree effects; i.e. under lack of oxygen or excess to sugar, respectively. After changing to anaerobic metabolism, it produces mostly alcohol but later this can be consumed by yeast as well resulting in a stepwise growth curve, also referred to as a diauxic growth profile. Thus, the question was whether such a system could show and follow this diauxic growth. 2. Experimental Commercial S. cerevisiae, i.e. baking yeast produced by Lesaffre, was cultured on a media of molasses that were diluted by a factor of 10 resulting in a saccharose con- centration of ca. 75 g dm -3 and a 20:1 volume of molas- ses to NH4OH ratio at 34°C. The 100 L of inoculum possessed a cell-dry-weight (CDW) content of 10 g/dm 3 . RTS-1 collected the data in a Microsoft Excel database. BacTrac only provided the data collected on screen plots, but with the help of Digitizelt v.2.3 soft- ware the measurement data was transported into Mi- crosoft Excel. To compare the data in Microsoft Excel, the structured model of Blanch et al. [3] was adopted and programmed in Berkeley Madonna for Windows 8.1. This model can describe both anaerobic cell growth on excess sugar with the formation of alcohol and aero- bic cell growth on alcohol as a substrate. It divides cells into two main compartments, i.e. substructures: one is responsible for metabolism (both aerobic and anaero- bic), and the other is responsible for cell division. The parameters, for example reciprocal yields and stoichio- metric coefficients of the model, were partly determined experimentally, but others were determined by non- linear model fitting, i.e. model calibration on real sam- ples. 3. Results and Analysis 3.1. Reverse-Spin Technology vs. Personal Bioreactor (RTS-1) Fig.1 presents the results of RTS-1. While optical densi- ty (OD), i.e. turbidity at = 850nm, changed slowly, the specific growth rate calculated online only reflected the uncertainty of the OD measurements, but the tempera- ture remained constant as expected. Additionally diaux- ic growth was also detected but over a very long period of time. The model fitting was quite difficult because a satisfactory fit was only achieved after remarkable changes to basic constants, for example maximum spe- cific growth rates on both substrates, etc., had been ap- plied. 3.2. Impedimetric System: BacTrac In the case of the impedimetric experiments, three dif- ferent arrangements were tested: an anaerobic cell with (A) (B) Figure 1. The measured parameters (temperature, , OD850) and calculated data (CDW from OD850) along with the data of the predicted (i.e. fitted) model. (A) green line: temperature; blue line: measured turbidity at 850nm; brown line: measured specific growth rate. (B) green line: temperature; red crosses: calculated cell dry weight from the measured turbidity at 850nm; purple line: fitted model-based prediction for CDW. 0 5 10 15 20 25 30 35 40 -2 -1 0 1 2 3 4 0 50 100 150 200 250 300 350 T(°C) OD (850nm) Fermentation Time (h) OD(850nm) µ (h ̄ ¹) T °C Growth on sugar Growth on ethanol D I A U X I C G R O W T H 0 5 10 15 20 25 30 35 40 0 2 4 6 8 10 12 14 16 18 0 50 100 150 200 250 300 350 T(°C)CDW Fermentation Time (h) CDW Predicted CDW T °C EXAMINATION OF INNOVATIVE HIGH-THROUGHPUT FERMENTATIONS 45(2) pp. 19–21 (2017) 21 an incorporated valve for gas release, an aerobic one, and an indirect one (Fig.2). Only M% values yielded explainable curves. Indirect measurements yielded an inverse growth curve (decreasing) as expected, but did not exhibit a two-step decrease, i.e. diauxic growth, therefore, M% values of direct measurements were evaluated. The two curves of aerobic and anaerobic M% values were very similar to each other, but perhaps the anaerobic example is more relevant as in the case of high sugar content, the metabolism of yeast shifted in the anaerobic direction. Fig.3 shows the fits of the mod- el in which less constants had to be changed and diauxic growth was detected. 4. Conclusion Both tested systems – Personal Bioreactor (RTS-1, Bio- san) and BacTrac (SY-LAB) – detected diauxic cell growth of baking yeast. RTS-1 seemed to be a little bit more flexible, but BacTrac gave faster results, was able to make 40 measurements at the same time and offered three options in terms of evaluation. Maybe in the near future a solution to regular automatic sampling from larger-scale fermenters will be found and then the re- sults can be compared with the ones presented here. Acknowledgement We are sincerely grateful to SY-LAB for the support provided with regard to BacTrac, and to Biocenter Kft. for importing RTS-1. REFERENCES [1] Németh, Á.; Kiss, Á.; Sevella, B.: Experiments for D-lactic acid production with fermentation, Hung. J. Ind. Chem., 2011 39(3), 359–362 [2] Bankovsky, V.; Bankovsky, I.; Bankovsky, P.; Isakova, J.; Djackova, I.; Sharipo, A.; Eskin, J.; Dišlers, A.; Rozenstein, R.; Saricev, V.; Djacenko, S.; Makarenko, V.; Balodis, U.: Reverse–Spin® Technology - Innovative Principle of Microbial Cultivation, Manufacturer's online leaflet: https://biosan.lv/images/uploads/content/files/reverse_spinner.pdf [3] Blanch, H.W.; Clark, D.S.: Biochemical Engineering (Marcel Dekker, NY, USA), 1996, pp. 231–236 ISBN 9780824700997 (A) (B) (C) Figure 2. The results of three BacTrac measurements: relative changes in impedancy in the M% of media vs. time (h) - (A) indirect-; (B) aerobic-direct-; (C) anaerobic-direct measurements. Figure 3. Model fitting to the anaerobic BacTrac curve (M%): red crosses: measured data; purple line: model- predicted values; green line: temperature (°C). 0 5 10 15 20 25 30 35 40 0 2 4 6 8 10 12 0 20 40 60 80 100 120 T(°C) Measured (M%) and predicted impedancy Fermentation Time (h) M(%) Predicted Impedancy T °C D I A U X I C G R O W T H Growth on ethanol Growth on sugar