Faculty Bibliography

We report a realization of an associative memory signal/information processing system based on simple enzyme-catalyzed biochemical reactions. Optically detected chemical output is always obtained in response to the triggering input, but the system can also "learn" by association, to later respond to the second input if it is initially applied in combination with the triggering input as the "training" step. This second chemical input is not self-reinforcing in the present system, which therefore can later "unlearn" to react to the second input if it is applied several times on its own. Such processing steps realized with (bio)chemical kinetics promise applications of bioinspired/memory-involving components in "networked" (concatenated) biomolecular processes for multisignal sensing and complex information processing.

We consider growth of nanoclusters and nanopillars in a model of surface deposition and restructuring yielding morphologies of interest in designing catalysis applications. Kinetic Monte Carlo numerical modeling yields examples of the emergence of face centered cubic (fcc) symmetry surface features in Pt-type metal nanostructures, allowing evaluation of the fraction of the resulting active sites with desirable properties, such as (111)-like coordination, as well as suggesting the optimal growth regimes.

We realize a biochemical filtering process by introducing a buffer in a biocatalytic signal-transduction logic system based on the function of an enzyme, esterase. The input, ethyl butyrate, is converted into butyric acid--the output signal, which in turn is measured by the drop in the pH value. The developed approach offers a versatile "network element" for increasing the complexity of biochemical information processing systems. Evaluation of an optimal regime for quality filtering is accomplished in the framework of a kinetic rate-equation model.

We consider a realization of the XOR logic gate in a process biocatalyzed by an enzyme which can be inhibited by a substrate when the latter is inputted at large enough concentrations. A model is developed for describing such systems in an approach suitable for evaluation of the analog noise amplification properties of the gate. The obtained data are fitted for gate quality evaluation within the developed model, and we discuss aspects of devising XOR gates for functioning in "biocomputing" systems utilizing biomolecules for information processing.

Biomolecular logic systems processing biochemical input signals and producing "digital" outputs in the form of YES/NO were developed for analysis of physiological conditions characteristic of liver injury, soft tissue injury, and abdominal trauma. Injury biomarkers were used as input signals for activating the logic systems. Their normal physiological concentrations were defined as logic-0 level, while their pathologically elevated concentrations were defined as logic-1 values. Since the input concentrations applied as logic 0 and 1 values were not sufficiently different, the output signals being at low and high values (0, 1 outputs) were separated with a short gap making their discrimination difficult. Coupled enzymatic reactions functioning as a biomolecular signal processing system with a built-in filter property were developed. The filter process involves a partial back-conversion of the optical-output-signal-yielding product, but only at its low concentrations, thus allowing the proper discrimination between 0 and 1 output values.

Takotsubo cardiomyopathy, or transient left ventricular apical ballooning or broken heart syndrome, is characterized by excessive sympathetic stimulation induced acute coronary vasospasm. A 46-year-old female presented with polyuria and polydypsia and was diagnosed with new-onset diabetes mellitus, treated with insulin and intravenous fluids. During the hospital stay, she complained of an episode of left-sided chest pain and had mildly elevated cardiac enzymes. EKG showed new ST-segment elevation in V2, V3 leads without reciprocal changes. Her coronary angiogram showed no significant coronary artery stenosis, but severe systolic dysfunction and akinesis of the mid-anterior, anteroapical, mid-inferior and inferoapical segments. Further workup was negative except for plasma metanephrine being elevated. MRI of the abdomen showed a right adrenal mass consistent with pheochromocytoma. Surgical resection of the adrenal mass showed evidence of pheochromocytoma and the patient's symptoms were resolved.

In this critical review we review enzymatic systems which involve biocatalytic reactions utilized for information processing (biocomputing). Extensive ongoing research in biocomputing, mimicking Boolean logic gates has been motivated by potential applications in biotechnology and medicine. Furthermore, novel sensor concepts have been contemplated with multiple inputs processed biochemically before the final output is coupled to transducing "smart-material" electrodes and other systems. These applications have warranted recent emphasis on networking of biocomputing gates. First few-gate networks have been experimentally realized, including coupling, for instance, to signal-responsive electrodes for signal readout. In order to achieve scalable, stable network design and functioning, considerations of noise propagation and control have been initiated as a new research direction. Optimization of single enzyme-based gates for avoiding analog noise amplification has been explored, as were certain network-optimization concepts. We review and exemplify these developments, as well as offer an outlook for possible future research foci. The latter include design and uses of non-Boolean network elements, e.g., filters, as well as other developments motivated by potential novel sensor and biotechnology applications (136 references).

The first realization of a designed, rather than natural, biochemical filter process is reported and analyzed as a promising network component for increasing the complexity of biomolecular logic systems. Key challenge in biochemical logic research has been achieving scalability for complex network designs. Various logic gates have been realized, but a "toolbox" of analog elements for interconnectivity and signal processing has remained elusive. Filters are important as network elements that allow control of noise in signal transmission and conversion. We report a versatile biochemical filtering mechanism designed to have sigmoidal response in combination with signal-conversion process. Horseradish peroxidase-catalyzed oxidation of chromogenic electron donor by H(2)O(2) was altered by adding ascorbate, allowing to selectively suppress the output signal, modifying the response from convex to sigmoidal. A kinetic model was developed for evaluation of the quality of filtering. The results offer improved capabilities for design of scalable biomolecular information processing systems.

We consider a realization of the XOR logic gate in a system involving two competing biocatalytic reactions, for which the logic-1 output is defined by these two processes causing a change in the optically detected signal. A model is developed for describing such systems in an approach suitable for evaluation of the analog noise amplification properties of the gate and optimization of its functioning. The initial data are fitted for gate quality evaluation within the developed model, and then modifications are proposed and experimentally realized for improving the gate functioning.

Experimental and theoretical analyses of the lactate dehydrogenase and glutathione reductase based enzymatic AND logic gates in which the enzymes and their substrates serve as logic inputs are performed. These two systems are examples of the novel, previously unexplored class of biochemical logic gates that illustrate potential biomedical applications of biochemical logic. They are characterized by input concentrations at logic 0 and 1 states corresponding to normal and pathophysiological conditions. Our analysis shows that the logic gates under investigation have similar noise characteristics. Both significantly amplify random noise present in inputs; however, we establish that for realistic widths of the input noise distributions, it is still possible to differentiate between the logic 0 and 1 states of the output. This indicates that reliable detection of pathophysiological conditions is indeed possible with such enzyme logic systems.