An Unbiased Approach of Sampling TEM Sections in Neuroscience

Abstract

Investigations of the ultrastructural features of neurons and their synapses are only possible with electron microscopy. Especially for comparative studies of the changes in densities and distributions of such features, an unbiased sampling protocol is vital for reliable results. Here, we present a workflow for the image acquisition of brain samples. The workflow allows systematic uniform random sampling within a defined brain region, and the images can be analyzed using a disector. This technique is much faster than extensive examination of serial sections but still presents a feasible approach to estimate the densities and distributions of ultrastructure features. Before embedding, stained vibratome sections were used as a reference to identify the brain region under investigation, which helped speed up the overall specimen preparation process. This approach was used for comparative studies investigating the effect of an enriched-housing environment on several ultrastructural parameters in the mouse brain. Based on the successful use of the workflow, we adapted it for the purpose of elemental analysis of brain samples. We optimized the protocol in terms of the time of user-interaction. Automating all the time-consuming steps by compiling a script for the open source software SerialEM helps the user to focus on the main work of acquiring the elemental maps. As in the original workflow, we paid attention to the unbiased sampling approach to guarantee reliable results.