Three-dimensional architecture of Thermomyces lanuginosus small subunit ribosomal RNA

Beniac, Daniel R.; Czarnota, Gregory J.; Rutherford, Brenda; Ottensmeyer, F. P.; Harauz, George

doi:10.1016/s0968-4328(97)00009-7

Cited by 2 publications

(1 citation statement)

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“…(2) The ratio between the post and the pre-edge images (also known as the jump method), used mainly in Material Science to avoid crystal diffraction effects (Krivanek et al, 1992;Hofer et al, 1995). Both methods increase the signal-to-noise ratio (SNR) of the maps, and they are presently used for this reason (Olins et al, 1996, Beniac et al, 1997a. In spite of rendering a good SNR, scaled two-window methods may produce false positive signals in high density areas, irrespective of the presence of P (Leapman, 1986).…”

Section: Introductionmentioning

confidence: 99%

Optimization of phosphorus localization by EFTEM of nucleic acid containing structures

Quintana

Marco

Bonnet

et al. 1998

Micron

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Energy Filtered Transmission Electron Microscopy (EFTEM) has been used to study nucleic acids localization in unstained thin sections of virus-infected cells. For this purpose, phosphorus maps (P-maps) have been obtained by applying the N-windows Egerton model for background subtraction from data acquired by a non-dedicated TEM Jeol 1200EXII equipped with a post-column PEELS Gatan 666-9000 and a Gatan Image Filter (GIF-100). To prevent possible errors in the evaluation of elemental maps and thus incorrect nucleic acid localization, we have studied different regions of swine testis (ST) cells with similar local density containing either high concentration of nucleic acids (condensed chromatin and ribosomes) or a very low concentration (mitochondria). Special care was taken to optimize the sample preparation conditions to avoid as much as possible the traditional artifacts derived from this source. Selection of the best set of pre-edge images for background fitting was also considered in order to produce "true P-maps". A new software for interactive processing of images series has been applied to estimate this set. Multivariate Statistical Analysis was used as a filtering tool to separate the "useful information" present in the inelastic image series (characteristic signal) from the "non-useful information" (noise and acquisition artifacts). The reconstitution of the original image series preserving mainly the useful information allowed the computation of P-maps with improved signal-to-noise ratio (SNR). This methodology has been applied to study the RNA content of maturation intermediate coronavirus particles found inside infected cells.

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