Title :
Low noise signal processing in the biological substrate
Author :
Simpson, M.L. ; Cox, C.D. ; Allen, M. ; Sayler, G.S.
Author_Institution :
Oak Ridge Nat. Lab., Tennessee Univ., Knoxville, TN, USA
Abstract :
There has been a considerable effort to optimize the silicon components of chip-based whole cell biosensors, but virtually no efforts to engineer the bioreporter for optimized noise performance. Thus, while only small improvement in total system performance can be expected from further optimization of the chip, there may yet be significant improvement in sensor sensitivity to be found within the biological substrate. We show through frequency domain gene circuit analysis that, in contrast to photodiodes and other silicon transducers that are characterized by a finite minimum noise, biological transducers have no such minimum noise. Based upon this finding, we propose a strategy to design a transducer and subsequent signal processing in the biological substrate that exploits this lower noise floor via amplification of the signal in the genetic circuit (i.e., upstream of the silicon transducer). The results of these analyses suggest two strategies for improving the noise performance of the genetic circuit and hence the overall sensitivity of chip-based whole cell biosensors: 1) an amplifier consisting of a cascade of genes in which upstream genes positively regulate downstream genes to achieve the required gain; and 2) an oscillator (or repressilator) that chops the bioluminescence signal and allows the use of specialized techniques in the silicon circuitry (e.g. lock-in amplification) to reject dc drift and low frequency noise. We use exact stochastic simulation of the gene circuits to help identify problematic performance conditions for a particular design that could go undetected through analysis alone. Conversely the analysis provides rapid insight into system behavior that would be nearly impossible via simulation alone due to the large parameter space involved. We show that incorporating modeling and simulation that includes the noise behavior of the biological components provide the tools to quickly and accurately explore the design space to isolate the most promising biological circuits, and significantly reduces the time required to develop a functional gene circuit.
Keywords :
amplification; amplifiers; bioluminescence; biomedical transducers; biosensors; cellular biophysics; elemental semiconductors; frequency-domain analysis; genetics; medical signal processing; network analysis; noise; silicon; Si; biological components; biological substrate; biological transducers; bioluminescence signal; bioreporter; chip-based whole cell biosensors; dc drift; frequency domain gene circuit analysis; gain; lock-in amplification; low frequency noise; low noise signal processing; lower noise floor; modeling; noise performance optimization; oscillator; repressilator; sensor sensitivity; signal amplification; silicon components; silicon transducer; simulation; stochastic simulation; transducer design; Analytical models; Biological system modeling; Biomedical signal processing; Biosensors; Circuit noise; Circuit simulation; Genetics; Performance analysis; Silicon; Transducers;
Conference_Titel :
Bio-, Micro-, and Nanosystems, 2003. ASM Conferences
Print_ISBN :
1-55581-279-3
DOI :
10.1109/BMN.2003.1220613