An electrochemical nano-biochip for water toxicity detection is presented. We describe chip design, fabrication, and performance. Bacteria, which have been genetically engineered to respond to environmental stress, act as a sensor element and trigger a sequence of processes, which leads to generation of electrical current. This novel, portable and miniature device provides rapid and sensitive real-time electrochemical detection of acute toxicity in water. A clear signal is produced within less than 10 min of exposure to various concentrations of toxicants, or to stress conditions, with a direct correlation between the toxicant concentration and the induced current.
"Fully integrated electrochemical microsystems for DNA and detection of bacteria and biomolecules have been reported –, but these systems do not provide all the features needed for nanostructured protein interfaces  targeted by this work, such as the necessity for extremely clean and flat electrodes. This paper reports a complete, single chip electrochemical instrumentation system with a broad current range amperometric readout circuit and a digitally programmable voltage waveform generator supporting a diverse set of electrochemical techniques. "
[Show abstract][Hide abstract] ABSTRACT: An integrated CMOS amperometric instrument with on-chip electrodes and packaging for biosensor arrays is pre- sented. The mixed-signal integrated circuit supports a variety of electrochemical measurement techniques including linear sweep, constant potential, cyclic and pulse voltammetry. Implemented in CMOS, the chip dissipates 22.5 mW for a 200 kHz clock. The highly programmable chip provides a wide range of user-controlled stimulus rate and amplitude settings with a maximum scan range of 2 V and scan rates between 1 mV/sec and 400 V/sec. The amperometric readout circuit provides linear resolution and supports inputs up to .A2 2 gold electrode array was fabricated on the surface of the CMOS instrumentation chip. An all-parylene packaging scheme was developed for compatibility with liquid test environments as well as a harsh piranha electrode cleaning process. The chip was tested using cyclic voltammetry of different concentrations of potassium ferricyanide at 100 mV/s and 200 mV/s, and results were identical to measurements using commercial instruments.
IEEE Transactions on Biomedical Circuits and Systems 10/2011; 5(5):439-448. DOI:10.1109/TBCAS.2011.2171339 · 2.48 Impact Factor
"Silicon, extensively used within the semiconductor field, is an attractive option, as integrated circuit technologies can easily be employed for cell array fabrication (Bolton et al., 2002; Bhattacharya et al., 2007). Popovtzer and colleagues (2005) developed a silicon biochip with 100 nl electrochemical chambers, harbouring genetically engineered E. coli cells. Cell arrays can also be generated directly on electrical components, such as photo-diodes, lightemitting diodes or field effect transistors. "
[Show abstract][Hide abstract] ABSTRACT: The coming of age of whole-cell biosensors, combined with the continuing advances in array technologies, has prepared the ground for the next step in the evolution of both disciplines - the whole-cell array. In the present review, we highlight the state-of-the-art in the different disciplines essential for a functional bacterial array. These include the genetic engineering of the biological components, their immobilization in different polymers, technologies for live cell deposition and patterning on different types of solid surfaces, and cellular viability maintenance. Also reviewed are the types of signals emitted by the reporter cell arrays, some of the transduction methodologies for reading these signals and the mathematical approaches proposed for their analysis. Finally, we review some of the potential applications for bacterial cell arrays, and list the future needs for their maturation: a richer arsenal of high-performance reporter strains, better methodologies for their incorporation into hardware platforms, design of appropriate detection circuits, the continuing development of dedicated algorithms for multiplex signal analysis and - most importantly - enhanced long-term maintenance of viability and activity on the fabricated biochips.
"Aside from these generally useful enhancements, a number of changes can be made to modify the system for use with other systems and novel experimental paradigms. The individual cells can be fitted with sensors for specific chemicals (dissolved oxygen, waste products, pH sensors, toxins, etc.) to monitor or screen for any desired physiological reaction (Epstein and Walt, 2003; Mano et al., 2003; Thrush et al., 2003; Lee et al., 2004; Popovtzer et al., 2005; Tian et al., 2005; Zhang et al., 2005). The image analysis software could be augmented with morphometric analysis modules (Klingenberg et al., 1998; Klingenberg and Zaklan, 2000; Albertson and Kocher, 2001 "
[Show abstract][Hide abstract] ABSTRACT: Efforts to understand cognition will be greatly facilitated by computerized systems that enable the automated analysis of animal behavior. A number of controversies in the invertebrate learning field have resulted from difficulties inherent in manual experiments. Driven by the necessity to overcome these problems during investigation of neural function in planarian flatworms and frog larvae, we designed and developed a prototype for an inexpensive, flexible system that enables automated control and analysis of behavior and learning. Applicable to a variety of small animals such as flatworms and zebrafish, this system allows automated analysis of innate behavior, as well as of learning and memory in a plethora of conditioning paradigms. We present here the schematics of a basic prototype, which overcomes experimenter effects and operator tedium, enabling a large number of animals to be analyzed with transparent on-line access to primary data. A scaled-up version of this technology represents an efficient methodology to screen pharmacological and genetic libraries for novel neuroactive reagents of basic and biomedical relevance.
Journal of Neurobiology 08/2006; 66(9):977-90. DOI:10.1002/neu.20290 · 3.84 Impact Factor
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