Savitzky-Golay processing and bidimensional plotting of current-time signals from stochastic blocking electrochemistry to analyze mixtures of rod-shaped bacteria.

In stochastic blocking electrochemistry, adsorptive collisions of nano and micro-particles with an ultramicroelectrode (UME) generate steps of decreasing current overlaid on the current-time (i-t) baseline of an electroactive mediator reacting at the UME. The step amplitude (Δi) induced by particle blockage informs about its size, while collision frequency correlates with particle transport. However, because most particles arrive at the UME faster than the acquisition speed of conventional electrochemical instruments, current steps appear vertical. Recently, when analyzing rod-shape bacteria (bacilli), we detected slanted steps of duration Δt (∼0.6 to 1.1 s) that were found to scale up with bacillus length (∼1 to 5 µm, respectively). In this work, we apply a Savitzky-Golay (SG) algorithm coded in MATLAB to convert experimental i-t recordings into derivative plots of Δi/Δt versus t. As a result, current steps become peaks on a flat baseline. Unlike the original values of Δi and Δt that require manual gauging, the coded SG-algorithm generates both parameters automatically from peak integration. We then display Δi and Δt in bidimensional scatter plots comparing mixtures of A. erythreum (∼1 µm) and B. subtilis (∼5 µm). The spread of Δi and Δt values complies with the size distribution observed using scanning electron microscopy. By introducing SG-processing and bidimensional plotting of i-t recordings from stochastic blocking data we broaden the scope of the technique. The approach facilitates distinguishing bacilli in mixtures because both Δt and Δi increase with bacillus length and now they can be displayed in a single graph along with adsorption frequency. Moreover, density distribution and proportion of data points from groups of bacteria are also discernible from the plots.

Average collision velocity of single yeast cells during electrochemically induced impacts.

We recorded current-time (i-t) profiles for oxidizing ferrocyanide (FCN) while spherical yeast cells of radius (rc ≈ 2 µm) collided with disk ultramicroelectrodes (UMEs) of increasing radius (re ≈ 12-45 µm). Collision signals appear as minority steps and majority blips of decreased current overlayed on the i-t baseline when cells block ferrocyanide flux (JFCN). We assigned steps to adsorption events and blips to bouncing collisions or contactless passages. Yeast cells exhibit impact signals of long duration (Δt ≈ 15-40 s) likely due to sedimentation. We assume cells travel a threshold distance (T) to generate collision signals of duration Δt. Thus, T represents a distance from the UME surface, at which cell perturbations on JFCN blend in with the UME noise level. To determine T, we simulated the UME current, while placing the cell at increasing distal points from the UME surface until matching the bare UME current. T-Values at 90°, 45°, and 0° from the UME edge and normal to the center were determined to map out T-regions in different experimental conditions. We estimated average collision velocities using the formula T/Δt, and mimicked cells entering and leaving T-regions at the same angle. Despite such oversimplification, our analysis yields average velocities compatible with rigorous transport models and matches experimental current steps and blips. We propose that single-cells encode collision dynamics into i-t signals only when cells move inside the sensitive T-region, because outside, perturbations of JFCN fall within the noise level set by JFCN and rc/re (experimentally established). If true, this notion will enable selecting conditions to maximize sensitivity in stochastic blocking electrochemistry. We also exploited the long Δt recorded here for yeast cells, which was undetectable for the fast microbeads used in early pioneering work. Because Δt depends on transport, it provides another analytical parameter besides current for characterizing slow-moving cells like yeast.

Estimating Average Velocities of Particle Arrival Using the Time Duration of the Current Signal in Stochastic Blocking Electrochemistry.

In stochastic blocking electrochemistry, microparticles generate individual current steps when they adsorb on a microelectrode and decrease the current and flux of a redox mediator reacting at the surface. The amplitude of the current step informs on particle size and landing locus, while step frequency correlates with particle transport. Here, we report a new method to estimate the average arrival velocities of single rod-shaped bacteria (bacilli). The method relies on simulating the nearby threshold distance from the surface where the bacillus no longer perturbs mediator flux and the current step approaches zero. We estimated the average velocities of bacillus arrival by dividing the threshold distance over the current step duration, a parameter that here we detect for the first time and increases with bacillus length. By comparing diffusional fluctuations to bacillus average velocity, we estimated diffusion and migration contributions as a function of bacterium size. Average arrival velocities increase with bacillus length at the same time as migration intensifies and diffusion weakens. Our analysis is universal and more effective in determining transport mode contributions than the present approach of comparing theoretical and experimental step frequencies. Uncertainty in landing locus is inconsequential because the step duration used to calculate the average arrival speed already contains such information and knowing bacillus electrophoretic mobility or ζ-potential is not needed. Additionally, by simulating and assigning edge landings to the most repeated values of current steps in a recording, we obtain bacilli lengths and widths similar to scanning electron microscopy, from which we infer landing orientation.

Dynamics of Collisions and Adsorption in the Stochastic Electrochemistry of Emulsion Microdroplets.

Current-time recordings of emulsified toluene microdroplets containing 20 mM Ferrocene (Fc), show electrochemical oxidation peaks from individual adsorption events on disk microelectrodes (5 µm diameter). The average droplet diameter (∼0.7 µm) determined from peak area integration was close to Dynamic Light Scattering measurements (∼1 µm). Random walk simulations were performed deriving equations for droplet electrolysis using the diffusion and thermal velocity expressions from Einstein. The simulations show that multiple droplet-electrode collisions, lasting ∼0.11 µs each, occur before a droplet wanders away. Updating the Fc-concentration at every collision shows that a droplet only oxidizes ∼0.58% of its content in one collisional journey. In fact, it would take ∼5.45 × 106 collisions and ∼1.26 h to electrolyze the Fc in one droplet with the collision frequency derived from the thermal velocity (∼0.52 cm/s) of a 1 µm-droplet. To simulate adsorption, the droplet was immobilized at first contact with the electrode while the electrolysis current was computed. This approach along with modeling of instrumental filtering, produced the best match of experimental peaks, which were attributed to electrolysis from single adsorption events instead of multiple consecutive collisions. These results point to a heightened sensitivity and speed when relying on adsorption instead of collisions. The electrochemical current for the former is limited by the probability of adsorption per collision, whereas for the latter, the current depends on the collision frequency and the probability of electron transfer per collision (J. Am. Chem. Soc. 2017, 139, 16923-16931).