A single neuron sensor has been developed based on the interaction of gradient electric fields and the cell membrane. Single neurons are rapidly positioned over individual microelectrodes using positive dielectrophoretic traps. This enables the continuous extracellular electrophysiological measurements from individual neurons. The sensor developed using this technique provides the first experimental method for determining single cell sensitivity; the speed of response and the associated physiological changes to a broad spectrum of chemical agents. Binding of specific chemical agents to a specific combination of receptors induces changes to the extracellular membrane potential of a single neuron, which can be translated into unique "signature patterns" (SP), which function as identification tags. Signature patterns are derived using Fast Fourier Transformation (FFT) analysis and Wavelet Transformation (WT) analysis of the modified extracellular action potential. The validity and the sensitivity of the system are demonstrated for a variety of chemical agents ranging from behavior altering chemicals (ethanol), environmentally hazardous agents (hydrogen peroxide, EDTA) to physiologically harmful agents (pyrethroids) at pico- and femto-molar concentrations. The ability of a single neuron to selectively identify specific chemical agents when injected in a serial manner is demonstrated in "cascaded sensing".
"This technique was simple, but had large bounds of error. That is because at the low concentration regimes, especially in the case of chemical mixtures, it has been established that there is a slight shift in the frequency peak (±5 Hz) (Prasad et al., 2004). The shift was also observed in the case of individual chemical analytes (Yang et al., 2003). "
[Show abstract][Hide abstract] ABSTRACT: A technique has been developed to determine the efficiency and the selectivity of a single neuron-based sensor in identifying the nature of the chemical agents in an unknown sample. This has been achieved by exploiting the unique electrical identifiers, also known as "signature patterns", generated by the neuronal cell membrane. These were generated based on the variations to the extracellular electrical activity, due to the effect of a broad range of chemical agents. We demonstrate the prediction capability of the sensor in identifying the nature of an unknown test sample from a combination of three chemical agents, namely, ethanol, pyrethroid, and hydrogen peroxide. This was achieved through a two-step process. The first step was experimentally achieved by in situ recording of the changes to the extracellular electrical activity from the sensing sites or the array of microelectrodes that form the platform for patterning neurons. Simultaneous optical characterization of the cell array during the sensing process was performed to identify the associated physiological changes. The second step was mathematical and was based on developing a library of signature patterns for a set of concentrations of the various combinations of the three chemical agents. Two variants of the nearest neighbor algorithm scheme - (a) partial distance search method, and (b) search tree method, were implemented for the accurate detection of all the components with varying concentrations in the test samples of unknown nature. This technique exhibits reliability in identification up to parts-per-billion (ppb) sensitivity. The capability of standardization of this technique for potential commercial applications is also discussed.
[Show abstract][Hide abstract] ABSTRACT: We present a novel sensing scheme for detecting the effects of unburned fossil fuels by integrating microarray technology and dielectrophoresis to develop single-neuron arrays. These arrays have the capability to sense and identify the two fuels, at parts per billion (ppb) concentrations, as well to determine the associated physiological changes at the single-cell level. Identification is achieved through frequency domain analysis of the measured changes to the extracellular electrical activity due to the effect of the fossil fuels. This yields unique electrical identifiers known as "signature patterns". Simultaneous optical visualization to the physiological changes is obtained by specific fluorescent staining. The correlation between the signature patterns and the cellular biological behavior establishes the veracity of this identification technique.
[Show abstract][Hide abstract] ABSTRACT: A biosensor is an analytical device that consists of an immobilized biocomponent in conjunction with a transducer, and represents a synergistic combination of biotechnology and microelectronics. This review summarizes the use of biosensors for detecting and quantifying heavy metal ions. Heavy metal contamination is of serious concern to human health since these substances are non-biodegradable and retained by the ecological system. Conventional analytical techniques for heavy metals (such as cold vapour atomic absorption spectrometry, and inductively coupled plasma mass spectrometry) are precise but suffer from the disadvantages of high cost, the need for trained personnel and the fact that they are mostly laboratory bound. Biosensors have the advantages of specificity, low cost, ease of use, portability and the ability to furnish continuous real time signals. The analysis of heavy metal ions can be carried out with biosensors by using both protein (enzyme, metal-binding protein and antibody)-based and whole-cell (natural and genetically engineered microorganism)-based approaches.
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