This study focuses on engineering whole cell-based biosensors for heavy metal detection. Through the exploitation of metalloregulatory proteins, fabrication of metal ion-responsive biosensors is achieved. Metalloregulatory proteins of the SmtB/ArsR family including arsenite-responsive ArsR, cadmium-responsive CadC, zinc-responsive CzrA, and nickel-responsive NmtR were evaluated as biosensor sensing modules. Characterization of these four metal sensing modules was accomplished through quantification of a reporter green fluorescence protein (gfp) gene. As such, biosensors pCTYC-r34ArsR-pL(ArsOvN)GFP and pCTYC-r34CadC-pL(CadOv1)GFP displayed excellent gfp expression and sensitivity to As(III) and Cd (II), respectively. These two biosensors were consequently selected and successfully implemented in soil bacterium Pseudomonas putida. Lastly, a proof of concept arsenite-responsive genetic toggle switch is proposed utilizing PurRcelR467 (PC47), a cellobiose-responsive gene, and an LAA degradation tag. Overall, this study expands the bank of metalloregulatory bioparts for heavy metal sensing in the aim of constructing an optimized water monitoring system.

Ganzzellsensoren sind potentielle Kandidaten für den Einsatz in der Umwelttechnik zur Detektion von Schwermetallen, organischen Lösungsmitteln oder Xenobiotika. Ebenso können mit ihrer Hilfe andauernde Prozesse, wie z.B. in der Biogasentwicklung, überwacht werden. Etablierte, auf Genexpression basierende Ausleseverfahren besitzen unterschiedliche Nachteile, die den Einsatz bisher weitestgehend auf das Labor beschränken. In der vorliegenden Arbeit wurden dazu drei alternative Auslesemöglichkeiten evaluiert, die durch kostengünstige Messverfahren und einem einfachen experimentellen Aufbau realisiert werden können. Die gezielte Morphologieänderung von Sensorhefen, die analytinduzierte Aggregation von Zellen und die analytabhängige Anlagerung von Goldnanopartikeln an Sensorhefen. Während sich die zwei erstgenannten Verfahren derzeit noch in Entwicklungszustand befinden, konnte durch die Anlagerung von Goldnanopartikeln an Sensorhefen der Wirkstoff Diclofenac erfolgreich detektiert werden. Die dazu notwendige Inkubationsdauer der Sensorhefen mit Diclofenac als auch das Detektionslimit wurde im Vergleich zu veröffentlichten Daten um je eine Größenordnung verringert.

Over the course of the last decades, the continuous exposure of bacteria to antibiotics—at least in parts due to misprescription, misuse, and misdosing—has led to the widespread development of antimicrobial resistances. This development poses a threat to the available medication in losing their effectiveness in treating bacterial infections. On the drug development side, only minor advances have been made to bring forward novel therapeutics. In addition to increasing the efforts and approaches of tapping the natural sources of new antibiotics, synthetic approaches to developing novel antimicrobials are being pursued. In this study, BDTL049 was rationally designed using knowledge based on the properties of natural antibiotics. BDTL049 is a carbosilane dendritic system with bow-tie type topology, which has antimicrobial activity at concentrations comparable to clinically established natural antibiotics. In this report, we describe its mechanism of action on the Gram-positive model organism Bacillus subtilis. Exposure to BDTL049 resulted in a complex transcriptional response, which pointed toward disturbance of the cell envelope homeostasis accompanied by disruption of other central cellular processes of bacterial metabolism as the primary targets of BDTL049 treatment. By applying a combination of whole-cell biosensors, molecular staining, and voltage sensitive dyes, we demonstrate that the mode of action of BDTL049 comprises membrane depolarization concomitant with pore formation. As a result, this new molecule kills Gram-positive bacteria within minutes. Since BDTL049 attacks bacterial cells at different targets simultaneously, this might decrease the chances for the development of bacterial resistances, thereby making it a promising candidate for a future antimicrobial agent.

Extracellular neuroelectronic interfacing has important applications in the fields of neural prosthetics, biological computation and whole-cell biosensing for drug screening and toxin detection. While the field of neuroelectronic interfacing holds great promise, the recording of high-fidelity signals from extracellular devices has long suffered from the problem of low signal-to-noise ratios and changes in signal shapes due to the presence of highly dispersive dielectric medium in the neuron-microelectrode cleft. This has made it difficult to correlate the extracellularly recorded signals with the intracellular signals recorded using conventional patch-clamp electrophysiology. For bringing about an improvement in the signalto-noise ratio of the signals recorded on the extracellular microelectrodes and to explore strategies for engineering the neuron-electrode interface there exists a need to model, simulate and characterize the cell-sensor interface to better understand the mechanism of signal transduction across the interface. Efforts to date for modeling the neuron-electrode interface have primarily focused on the use of point or area contact linear equivalent circuit models for a description of the interface with an assumption of passive linearity for the dynamics of the interfacial medium in the cell-electrode cleft. In this dissertation, results are presented from a nonlinear dynamic characterization of the neuroelectronic junction based on Volterra-Wiener modeling which showed that the process of signal transduction at the interface may have nonlinear contributions from the interfacial medium. An optimization based study of linear equivalent circuit models for representing signals recorded at the neuron-electrode interface subsequently iv proved conclusively that the process of signal transduction across the interface is indeed nonlinear. Following this a theoretical framework for the extraction of the complex nonlinear material parameters of the interfacial medium like the dielectric permittivity, conductivity and diffusivity tensors based on dynamic nonlinear Volterra-Wiener modeling was developed. Within this framework, the use of Gaussian bandlimited white noise for nonlinear impedance spectroscopy was shown to offer considerable advantages over the use of sinusoidal inputs for nonlinear harmonic analysis currently employed in impedance characterization of nonlinear electrochemical systems. Signal transduction at the neuron-microelectrode interface is mediated by the interfacial medium confined to a thin cleft with thickness on the scale of 20-110 nm giving rise to Knudsen numbers (ratio of mean free path to characteristic system length) in the range of 0.015 and 0.003 for ionic electrodiffusion. At these Knudsen numbers, the continuum assumptions made in the use of Poisson-Nernst-Planck system of equations for modeling ionic electrodiffusion are not valid. Therefore, a lattice Boltzmann method (LBM) based multiphysics solver suitable for modeling ionic electrodiffusion at the mesoscale neuron-microelectrode interface was developed. Additionally, a molecular speed dependent relaxation time was proposed for use in the lattice Boltzmann equation. Such a relaxation time holds promise for enhancing the numerical stability of lattice Boltzmann algorithms as it helped recover a physically correct description of microscopic phenomena related to particle collisions governed by their local density on the lattice. Next, using this multiphysics solver simulations were carried out for the charge relaxation dynamics of an electrolytic nanocapacitor with the intention of ultimately employing it for a simulation of the capacitive coupling between the neuron and the v planar microelectrode on a microelectrode array (MEA). Simulations of the charge relaxation dynamics for a step potential applied at t = 0 to the capacitor electrodes were carried out for varying conditions of electric double layer (EDL) overlap, solvent viscosity, electrode spacing and ratio of cation to anion diffusivity. For a large EDL overlap, an anomalous plasma-like collective behavior of oscillating ions at a frequency much lower than the plasma frequency of the electrolyte was observed and as such it appears to be purely an effect of nanoscale confinement. Results from these simulations are then discussed in the context of the dynamics of the interfacial medium in the neuron-microelectrode cleft. In conclusion, a synergistic approach to engineering the neuron-microelectrode interface is outlined through a use of the nonlinear dynamic modeling, simulation and characterization tools developed as part of this dissertation research.