title: STEM Tomography Imaging of Hypertrophied Golgi Stacks in Mucilage-Secreting Cells.
abstract: Because of the weak penetrating power of electrons, the signal-to-noise ratio of a transmission electron micrograph (TEM) worsens as section thickness increases. This problem is alleviated by the use of the scanning transmission electron microscopy (STEM). Tomography analyses using STEM of thick sections from yeast and mammalian cells are of higher quality than are bright-field (BF) images. In this study, we compared regular BF tomograms and STEM tomograms from 500-nm thick sections from hypertrophied Golgi stacks of alfalfa root cap cells. Due to their thickness and intense heavy metal staining, BF tomograms of the thick sections suffer from poor contrast and high noise levels. We were able to mitigate these drawbacks by using STEM tomography. When we performed STEM tomography of densely stained chloroplasts of Arabidopsis cotyledon, we observed similar improvements relative to BF tomograms. A longer time is required to collect a STEM tilt series than similar BF TEM images, and dynamic autofocusing required for STEM imaging often fails at high tilt angles. Despite these limitations, STEM tomography is a powerful method for analyzing structures of large or dense organelles of plant cells.
authors.affiliation: School of Life Sciences, Centre for Cell and Developmental Biology and State Key Laboratory of Agrobiotechnology, Chinese University of Hong Kong, Hong Kong, China. bkang@cuhk.edu.hk.
authors.forename: Byung-Ho
authors.initials: BH
authors.lastname: Kang
mesh_terms: D017360:Arabidopsis / Q000378:metabolism / Q000648:ultrastructure*; D018548:Cotyledon / Q000378:metabolism / Q000648:ultrastructure*; D006056:Golgi Apparatus / Q000378:metabolism / Q000648:ultrastructure*; D008855:Microscopy, Electron, Scanning / Q000379:methods*; D046529:Microscopy, Electron, Transmission / Q000379:methods*
keywords: Electron tomography; Golgi stacks; High-angle annular dark field detector; Scanning transmission electron microscopy; Signal-to-noise ratio