The functional role of piezoelectricity and of other modes of electromechanical coupling across the hierarchical structures of biological materials garnered interest many years ago. Many biological materials have been described as exhibiting piezoelectric behavior, from wool fibers to wood planks and even to living mammalian cells, but efforts are on-going towards understanding how electromechanical coupling in biological systems transcends from the molecular to tissue levels.
In pursuit of high-resolution measurements of such hierarchical electromechanical coupling, scanning probe microscopy-based techniques are considered. Piezoresponse force microscopy (PFM) becomes the specific focus of this work, and the nascent development of PFM is reviewed through its first applications in liquid environments and with biological materials. Beginning with our initial publication, the contribution of mechanical properties of soft materials to electromechanical image formation is recognized. If PFM is to be applied to soft, biological materials in liquids, then mechanical and electromechanical contributions to the response must be separated, and accurate measurement of both mechanical and electromechanical properties is desired. Band excitation PFM (BEPFM) has been introduced as having the capability to track contact resonance frequencies and hence account for some mechanical contributions. Yet, reliable interpretation of BEPFM data and results for soft materials awaits well-founded establishment.
Establishment of BEPFM as a routine method for studying biological systems will require performance in liquids, including culture media, demonstration of effectiveness over a hierarchical range of scale and of promise of medical relevance, and delineation of image formation mechanisms with constitutive relations to physical properties of samples. In Chapter Three, the electromechanical response of amyloid fibrils on mica in water is measured using BEPFM, and using a double layer coupling model for electromechanical response, BEPFM response is correlated with mechanical properties of the fibrils relative to the underlying mica, showing that the Young's modulus of the material is the main parameter that determines the magnitude of electromechanical coupling. In Chapter Four, BEPFM is applied to living cells and established for functional recognition imaging, using bacterial cells as simple model cells imaged in deionized water and identifying the cells based on differences in electromechanical properties using artificial neural networks (ANNs). In Chapter Five, functional fitting of the BEPFM spectra in deionized water and in electrolyte solutions is performed to understand the underlying physical mechanism responsible for image formation and subsequent functional recognition. BEPFM response is shown to be influenced mainly by surface-associated properties. Differences in BEPFM responses in electrolyte solution are shown between live bacteria and bacteria of the same type killed by ethanol, as verified by fluorescence live/dead assay images. To apply BEPFM to measurement of electromechanical and mechanical properties of mammalian cells, in Chapter Six, we begin comparison of the results from force-distance curves and from BEPFM for the physical properties of cells and neurites, and an example of BEPFM performance in serum media is shown. Thus, BEPFM currently is capable of performance to a limited extent in physiologically-relevant liquids, qualitative interpretations about the mechanical and electromechanical properties of biological systems can be made, and biological systems, including types of cells, can be distinguished relatively using BEPFM.