For a full understanding of molecular mechanisms, it is important to macromolecular assemblies into the broader context of a cell. This context can be visualized in 3D by electron cryo-tomography, which requires time-consuming data collection and processing. Furthermore, detection of molecular assemblies in tomograms is prone to false positives, especially in dense regions of the cell, such as the nucleolus. Our lab developed a 2D template matching (2DTM) approach that uses high-resolution information in 2D images of cells to detect molecules with high specificity without the need to collect a tomogram.
Using 2DTM, we are able to detect 60S ribosome biogenesis intermediates in the nucleus of yeast cells and distinguish different states of maturation. This approach can also be used to detect the presence or absence of specific maturation factors. We describe a maximum-likelihood formalism to determine the confidence in assigning detected targets to specific templates. Finally, we show that by averaging detected particles, 2D template matching can be used for in situ structure determination.
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