Development of a differential LAPS-based monitoring system to evaluate the metabolic response of bacteria in biogas process analyses
The independence of fossil fuels as energy carriers is an essential future-oriented aim for all nations around the world. The negative influences of global climate changes are strongly noticeable in our daily life. Reports on unexpected natural catastrophes reach many people and make them contemplative finding proper and novel strategies to overcome related future disasters. In this context, scientific efforts and methodologies are in demand to reduce the damage and avoid irreversible and costly interventions. Hence, discoveries and innovations in the field of renewable energy sources are essential. In the last 50 years, investments in technological improvements in the respective research fields allow increasing energy recovery from (bio-)renewable sources.
The current technologies focus on solar, wind, geothermal, water and (bio-)energy sources. Among these potential resources, biogas production plays a significant role. Energy recovery from biomass has shown new possibilities for energy production and transformation. Historical records from ancient China and Persia demonstrate the high interest and efforts of generating thermal energy based on low-cost biogas sources such as animal manures and plant wastes. Since that time, scientific knowledge and technological developments have rapidly increased shoulder by shoulder with other fields of application. Despite ancient efforts for producing methane gas, modern biogas production is still a complex process, in which different scientific and engineering disciplines are merged, e.g., including microbiology of bacteria up to advanced nanotechnology through modern communication systems and controllers.
For the state-of-the-art understanding of biogas processes, depending on the feeding substrate used in the biogas production, different types of microorganisms are involved within this process. In general, four parallelized steps are known to describe the fermentation process, which are: hydrolysis, acidogenesis, acetogenesis, and methanogenesis. In each fermentation step, a particular type of microorganisms is responsible to break down the substrates and transform them into methane gas. The role of microorganisms in such (bio-)fermentation processes cannot be ignored: only metabolically active microorganisms can enable smooth biogas operation and contribute to methane gas production. Concerning this fact, the metabolic activity of microorganisms in the fermentation process is an important overall process parameter, which should be taken into account when analyzing the status of a biogas reactor. Besides other parameters such as the concentration of volatile fatty acids, pH value, redox potential, and temperature, the determination of the extracellular acidification of bacteria in the fermentation broth provides an additional tool to evaluate the intermediate fermentative stages.
In case of disturbances related to microorganisms, the biogas production chain can get blocked, which can be very costly and time-consuming for the provider to refill the biogas tank and start with the procedure again. Therefore, the on-line monitoring of the cellular metabolism of bacteria inside the biogas process is crucial and highly desirable. There are various conventional and commercial techniques to evaluate a biogas process, which are explained in more detail in the Introduction of this thesis. It must be kept in mind that most of these analytical procedures are off-line and can be very time-and cost-intensive, because of use of established external laboratories. Accordingly, on-line monitoring measuring systems are favorable, which can be directly applied at the biogas reactor. This way, the taken sample can be rapidly treated and analyzed without sending them to laboratories for further analyses. In addition, the transport of samples can harm the probes, which can be avoided by on-line measurement systems.
In the last 30 years, analytical devices such as biosensors obtained great interest in a wide range of monitoring and sensing applications. Among them, the usage of light-addressable potentiometric sensors (LAPS), which belong to the class of field-effect- sensors, offers the capability to read out principle concentration changes in an aqueous medium in a spatially resolved manner. This is of particular interest when studying the metabolic activity of bacteria. More details related to the LAPS principle is given in Theory of this thesis.
This work deals with the development and improvement of a differential sensor set-up based on the working principle of LAPS for monitoring and evaluation of the metabolic responses of various types of bacteria. First, different LAPS chips were microfabricated using thin-film technologies. Subsequently, the LAPS chips were physically and electrochemically characterized. In the next step, 3D-printed polymer-based multi-chamber structures were developed with different geometries, which were mounted on the sensor chip surface, enabling defined sensing areas for differential measurements. The differential measurement technique was chosen us to eliminate undesired external influences during measurements such as possible pH value variations of the medium, sensor signal drift, and temperature fluctuations.
The performance of the developed multi-chamber LAPS set-up with Escherichia coli (E. coli) K12 bacteria was compared to literature data. The applied light source was based on an array consisting of 16 light-emitting diodes (LEDs). However the LAPS measurements revealed an unwanted signal drop from the reference chamber, which resulted in the development of a novel light source based on an array of 16 fix-focused tuneable laser-diode modules (LDMs) to improve the light-addressability. The LDMs are frequency-modulated through a field-programmable gate array (FPGA)-based controller and were adapted to the LAPS set-up for simultaneous measurements at different frequencies. Due to the small beam angle of the LDMs in comparison to the LEDs, the reference signal remained stable during all measurements. Depending on the multi-chamber LAPS arrangements, up to four Ag/AgCl reference electrodes were used, which caused potential variations in different chambers. To overcome this problem, further polymer-based structures were printed as salt-bridge chambers between the reference electrode and the multi-chambers. This way, the number of utilized Ag/AgCl reference electrodes was reduced to one, ensuring stable electrode potentials in each measurement chamber.
After validation of the LAPS system and selecting the suitable acid-forming, facultative anaerobic model bacterium, the overall extracellular acidification for three types of bacteria was determined: Escherichia coli (E. coli), Corynebacterium glutamicum (C. glutamicum), and Lactobacillus brevis (L. brevis). Their metabolic response was evaluated after glucose uptake with the multi-chamber LAPS set-up. The extracellular acidification was monitored by varying the glucose concentration or/and cell numbers. The resulting calibration curves describe the metabolic behaviour of each particular microorganism.
The new developed multi-chamber LAPS set-up and its functional principle allow to monitor the extracellular acidification of various bacteria after glucose uptake on a single sensor chip without any additional immobilization steps, sequentially and simultaneously. Furthermore, the number of living cells in a bacterial culture was determined by means of correlations between the LAPS signal and the metabolic response of respective bacteria applying the obtained calibration data. It is shown that by increasing the cell number/glucose concentration, the cellular metabolism of bacteria also increase. In the regard to the practical applications, real biogas samples from a paper-based biogas fermenter were studied with the multi-chamber LAPS set-up. Here, the overall acidification of bacterial populations within the fermentation broth before and after glucose uptake was determined, also resulting in a calibration matrix as for the model bacteria before. In further complementary experiments, these model microorganisms were exposed to the fermentation broth, including its bacterial populations to distinguish the influence on the sensor sample between known (model microorganisms) and unknown bacteria. This way, different biogas process steps can be characterized.
The obtained results in this work show the high potential of the developed differential sensor system based on LAPS to monitor the metabolic response of various types of bacteria in (bio-)fermentation processes.