Abstract

AbstractImaging techniques based on transmission electron microscopy can elucidate the structure and function of macromolecular complexes in a cellular environment. In addition to providing contrast based on structure, electron microscopy combined with electron spectroscopy can also generate nanoscale contrast from endogenous chemical elements present in biomolecules, as well as from exogenous elements introduced into tissues and cells as imaging probes or as therapeutic drugs. These capabilities complement biomedical imaging used in diagnostics while also providing insight into fundamental cell biological processes. We have developed electron tomography (ET) techniques based on unconventional imaging modes in the electron microscope to map specific types of macromolecules within cellular compartments. ET is used to determine the three-dimensional structure from a series of two-dimensional projections acquired successively by tilting a specimen through a range of angles, and then by reconstructing the three-dimensional volume. We have focused on two approaches that combine ET with other imaging modes: energy filtered transmission electron microscopy (EFTEM) based on collection of inelastically scattered electrons, and scanning transmission electron microscopy (STEM) based on collection of elastically scattered electrons. EFTEM tomography provides 3D elemental mapping and STEM tomography provides 3D mapping of heavy atom clusters used to label specific macromolecular assemblies. These techniques are illustrated by EFTEM imaging of the subcellular nucleic acid distribution through measurement of the intrinsic marker, elemental phosphorus; and by STEM imaging of gold clusters used to immunolabel specific proteins within the cell nucleus. We have also used the EFTEM and STEM techniques to characterize nanoparticles that might be used as drug delivery systems.KeywordsCharge Couple DeviceScanning Transmission Electron MicroscopyElectron Energy Loss SpectrumScanning Transmission Electron Microscopy ImagingCharge Couple Device DetectorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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