The overall goal of this procedure is to grow an anodic electroactive microbial biofilm from wastewater inoculate, and to characterize its bio electro catalytic properties. This is accomplished by first setting up inoculating and starting a potential statically controlled bio electrochemical fed batch reactor. The second step is to monitor the current production using Krono Pyrometry.
Next, the medium is exchanged regularly after substrate exhaustion until a reproducible maximum current density is reached, representing a steady state biofilm formation. The final step is to study the extracellular electron transfer of electroactive bacteria using cyclic vol telemetry during the presence and absence of the substrate. Ultimately, data analysis provides fundamental insights into the microbial electron transfer thermodynamics, and allows the formal potential of possible and actual extracellular electron transfer sites to be determined.
The main advantage of this technique is that one can obtain direct insight into the electron transfer between microorganisms and solid electrodes, and thus derive fundamental information on the microbial extracellular electron transfer. Generally, individuals new to the method will struggle with the right parameter choice and the correct interpretation of the derived plot. During data acquisition and data analysis, severe mistakes can be made.
Before starting this procedure, prepare a suitable amount of the growth medium by using a phosphate buffer, including further nutrients according to the following reference. Use 10 millimolar of sodium acetate as substrate. Add one milliliter of primary wastewater per 20 milliliters of growth, medium as inoculum.
Then insert a needle in the medium and flush it with nitrogen for at least half an hour. To de aerate it while flushing with nitrogen, measure the size of the electrode for the three electrode setup. Insert the working electrode, the counter electrode, and the reference electrode in a modified four neck, 250 milliliter round bottom flask via silicone plugs.
Wrap the silicone plugs with paraform to seal the system while flushing with nitrogen. Pour 250 milliliters of the growth medium and inoculum mixture through the sampling port into the reactor. Close the sampling port with a silicone plug and seal it airtight with perfil.
Place the vessel in a 35 degree Celsius temperature controlled chamber in order to ensure constant environmental conditions. Next, connect the electrodes to the respective cables of the potential stat. Open the software to control the potential stat and choose the technique.
Chrono pyrometry. Set the working electrode to a constant potential of 0.2 volts for a duration time of 500 hours recording every 600 seconds following this, start the chrono pyrometry and observe the graph of the measured current over time. After calculating the preferential current densities plot the measured current density as a function of time.
After the oxidative current reaches a plateau and returns to zero current, pause the chrono amper metric measurement for a medium exchange. Therefore, transfer the vessel to a laminar flow box and flush the system with nitrogen. Carefully discharge the medium and replenish with fresh de aerated medium following replenishment of the medium.
Close the sampling port and seal it with paraform. Repeat the previous steps until the maximum oxidative current reaches a steady state After every growth cycle, take a one milliliter sample of the fresh and the exchanged medium solutions for substrate analysis by HPLC. To study extracellular electron transfer, select the technique cyclic vol telemetry in the potentials stat controlling software.
Then set the initial potential EI of the working electrode to negative 0.5 volts versus the reference electrode, the vertex potential E one to 0.3 volts, and the final potential E two to negative 0.5 volts. Use a scan rate of one millivolt per second. Start the experiment and record at least three cycles to obtain a reproducible cv.
After calculating the preferentially current densities plot the measured current density as a function of the potential of the working electrode. From the chrono amper metric measurements, the maximum current density and the Kula efficiency can be measured. Shown here is a typical chronometric biofilm growth curve of several growth cycles using a fed batch reactor.
After the initial lag phase, a first current density maximum commences then the current decreases to nearly zero current flow due to substrate depletion. Following substrate replenishment. The current density increases again with a higher maximum current density.
After several growth cycles, the maximum current density is constant, which indicates a steady state biofilm formation. As the steady state maximum. Current density value is dependent on several parameters.
It is often considered as a characteristic of electroactive microbial biofilm electrode systems. The second operational characteristic is the omic efficiency, which is the number of electrons recorded as electric current flow per fed batch cycle related to the theoretical maximum number of electrons. See the text protocol for details on how to calculate the call efficiency, the electric current flow, and the theoretical maximum number of electrons shown.
Here is a typical CV for non turnover conditions. At a high scan rate, the CV of a biofilm for high scan rates where only one peak pair and thus one formal potential EF can be identified is pictured.Here. In general, the formal potential of a redox couple can be calculated from the peak potential of the oxidation peak EPA and the reduction peak of the respective species EPC.
By forming the arithmetic mean, see the text protocol for details on how to calculate the formal potential. When applying a low enough scan rate to the identical biofilm, up to four redox pairs can be identified. However, the non turnover CV only shows all redox active compounds at the electrode, and thus the EF of the possible extracellular electron transfer sites.
Only analysis of the turnover CV provides the EF of the actual EET sites when further analyzing the non turnover cvs. Other characteristic parameters like peak separation, maximum peak current and minimum peak current density can be analyzed. These parameters, especially when recorded for different scan rates, can be used for mechanistic and kinetic analyses of electron transfer processes at electrodes.
However, this kinetic analysis that is well established for chemical systems is not straightforward for electroactive microbial biofilms. When performing the CV measurement in the presence of substrate, a turnover CV is obtained. After plotting the data, the typical S-shaped bio electro catalytic curve is observed.
When further analyzing the data, the maximum of the first derivative or the inflection point of the curve provides the formal potential EF of the actual EET sites. In the case of a thin geobacter ratio dominated biofilm, two inflection points can be observed. Subsequently, the derivative shows two maxima corresponding to the formal potential of the bio electro catalytic active EET sites, which are denominated as EF two and EF three respectively.
This finding also shows that the redox processes associated with the formal potentials EF one and EF four are not related to bio electrolysis. As the biofilm grows and gets thicker, the CV shows only one inflection point. This formal potential EEF negative 0.32 volts versus silver, silver chloride is roughly equal to the arithmetic mean of the two formal potentials assigned to the EET of the thin biofilm.
This result shows that the fundamental CV analysis does provide insights into the EET thermodynamics in a fast and non-invasive way. Once master, this technique can be easily tailored to different systems of interest, and depending on the data, does allow a different depth of data analysis if performed properly. Following this procedure and learning the basics of microbial biofilm geometry, one can easily learn other methods like square wave telemetry or electrochemical impedance spectroscopy, as well as in-depth data analysis.
