Videodensitometric analysis of electron spectroscopic micrographs — a tool for detection of biologically relevant elements with high resolution

Abstract

SummaryElectron energy-loss spectroscopic imaging (ESI) yields highresolution, element-sensitive images. However, ESI suffers from difficulties in distinguishing element-specific and background contributions. New methods have therefore been introduced which use grey-level measurements in micrographic images for a more accurate detection of element distributions. A videodensitometric method allowed the detection of low phosphorus levels in axoplasmic neurofilaments of squid giant axons. Here we further verify these results by investigating the relationship of videodensitometry and electron energy-loss spectroscopy (EELS), particularly considering the peculiarities of these methods in terms of automatic background correction and representation of the results. Six biological specimens and two nonbiological specimens were examined both by EELS and by videodensitometry. In all cases comparable results were obtained. The overlapping P L2,3 and S L2,3 ionization edges could clearly be recognized individually by both methods, and controls showed that mass density variations within the specimens did not impair elemental analysis. Additional evidence supporting the detection of phosphorylation sites in squid neurofilaments was obtained in both EELS and videodensitometric measurements of neurofilament-enriched pellets and of aggregated axoplasmic particles. Thus, videodensitometry appears to be a useful tool for an improved exploration of the full imaging capabilities of energy filtering electron microscopy.

Detection of low phosphorus contents in neurofilaments of squid axons by Image‐EELS contrast spectroscopy

“…When conventional EEL spectra are presented in this way, similar curves can be observed. This ratiometric presentation of conventional EEL spectra has been extensively demonstrated and its nature discussed (Door et al, 1997). It gives rise to the peculiarities of EELC spectra and proves for their reliability.…”

“…Regions of interest are marked and their grey levels in subsequent images plotted against the energy loss, resulting in an Image-EEL spectrum. Another approach measures the modulation of contrast between a region of interest and their surrounding background throughout an image series on photographic plates (Martin et al, 1993;Door et al, 1997). An advantage of this method is that each micrograph can be exposed to a constant signal-to-noise ratio, eliminating artefacts due to noise modulations.…”