Biodynsensing: Sensing through dynamics of hybrid affinity/cellular platforms; Towards appraisal of environmental and biological risks of nanobiotechnology

Abstract

Chemical cues and nano-topographies present on the surface or in the extracellular medium strongly influence the fate and adhesion of biological cells. Careful tuning of cell-matrix interaction via engineered surfaces, either attractive or repulsive, require non-invasive, long time monitoring capabilities and lay the foundation of sensing platforms for risk assessment. Aiming to assess changes underwent by biointerfaces due to cell-environment interaction (in particular nanotechnology products), we have developed hybrid cellular platforms allowing for time based dual assays, i.e., impedance/dielectric spectroscopy (IS) and Surface Plasmon Resonance (SPR). Such platforms comprising Flow Injection Analysis (FIA) have been advanced to assess the interaction between selected (normal and malignant) cells and nano-patterned and/or chemically modified surfaces, as well as the impact of engineered nanoparticles, revealed by the related changes exhibited by cell membrane, morphology, adhesion and monolayer integrity. Besides experimental aspects dealing with measurement set-up, we will emphasize theoretical aspects related to: dielectric modeling. Aiming for a quantitative approach, microscopic models on dielectric behavior of ensembles of interconnected cells have been developed and their capabilities will be outlined within the presentation. Assessment of affinity reactions as revealed by dielectric/impedance assays of biointerfaces. Modeling the dynamics of the impedance in relation to the "quality" of cell layer and sensor"s active surface, this study presents further developments of our approach described in Analytical Chemistry, 2002. Data analysis. This issue is related to the following basic question: Are there "simple" Biosensing Platforms? When coping with cellular platforms, either in suspension or immobilized (on filters, adhered on surfaces or entrapped, e.g., on using set-ups) there is an intrinsic nonlinear behavior of biological systems related to cellular mechanisms involved in sensing, i.e., adaptation to stimuli. This should not mean that when coping with living cells, stray effects might not also corrupt the measurement itself, introducing distinct dynamics. Besides targeted/specific process, analytical platforms might exhibit additional ones due to "stray influences" that could include the effect of, e.g.: supporting matrix, nonspecific binding and temperature variation. Stray processes interfere with the desired ones and the measured data could display a non-monotonous behavior. © 2009 Springer Netherlands.