Nowadays, commercial CLEM dishes or coverslips are routinely used for correlating fluorescence imaging of fixed or living cells with transmission EM (TEM; Stierhof et al., 1994; Polishchuk et al., 2000). Typical sample preparation for EM, i.e., by chemical fixation or high-pressure freezing, includes a resin embedding step. Upon removal of the coverslip from the resin block, the region of interest (ROI) is located using the topology of the coordinate system that marks the block surface. For TEM imaging, the block is then trimmed so the sections containing an ROI can fit onto an EM grid. Regardless of the initial dimensions of the substrate, selecting the ROI usually entails the loss of surrounding areas, preventing the analysis of multiple cells if they were distributed across the full surface of the culture dish or coverslip.
Logic Pro X 2020 Crack With Serial Key Full Free Download
In recent years, volume scanning electron microscopy (SEM) modalities have been used for CLEM on cultured cells. Besides offering access to large volumes, both serial block-face SEM (SBF-SEM; Titze and Genoud, 2016) and array tomography (Hayworth et al., 2015; Kislinger et al., 2020) also require block trimming before imaging and therefore suffer from the same limitations as TEM when utilized for CLEM. Focused ion beam SEM (FIB-SEM; Russell et al., 2017) however can accommodate the imaging of large specimens without the need for trimming. In particular, multiple cultured cells grown on a Petri dish or coverslip can be imaged in a CLEM workflow, even when scattered across the full surface of the substrate (Cosenza et al., 2017). Despite this capability, CLEM has been performed one cell at a time and for a limited number of cells (Narayan and Subramaniam, 2015; Cosenza et al., 2017; Fermie et al., 2018; Luckner and Wanner, 2018b), because up to now, FIB-SEM microscopes lack automation procedures to acquire multiple sites without interruption.
Using the novel workflow we developed, it was shown that correlative imaging using FIB-SEM can acquire multiple targets within a single experiment (up to 30 over 1 wk of acquisition) with full automation. Detection of local landmarks imprinted in the culture substrate enables automated correlation and targeting with a 5 µm accuracy. We estimate that this number could still be improved by customizing a gridded substrate with a smaller mesh size, consequently, shortening the distance between landmarks and targets. Our detection algorithm could be extrapolated to other customized dishes or commercial substrates for cell culture in SEM samples (Luckner and Wanner, 2018b). An advantage of using local landmarks for the correlation is that they mitigate the impact of sample surface defects or optical aberration across long distances. Alternatively, targeting individual cells with a FIB-SEM has been achieved by mapping the resin-embedded cells with microscopic x-ray computed tomography (Hoffman et al., 2020). We speculate that such tools could be an alternative to a gridded substrate yet cannot predict its adaptability to large resin blocks such as the ones we used in this study.
Thanks to the utilization of a FIB-SEM, nearly the whole sample surface is accessible, enabling the correlation of multiple cells. In the case of highly distributed and distant rare events (Guérin et al., 2019), the respective targets are still within reach. We demonstrate the workflow on commercial dishes with a usable surface on the order of 40 mm2, but much larger surface areas are possible. The limitation is dictated mainly by the dimensions and travel range of the microscope stage. With such potential, the other main feature of our software is the ability to trigger an autonomous acquisition in multiple sites in one microscopy session. This fully automated triggering has not previously been achieved on biological samples. This is made possible through the automation of key steps of the imaging pipeline, i.e., (1) setting the coincidence point of both ion and electron beams, (2) automated selection of key focusing ROIs using computer vision, and (3) constant tracking of the sample position within the field of view of the microscope. In summary, all interactions with the microscope that are usually supervised by a human operator during acquisition, be it several hours or days, are automated.
2ff7e9595c
Comments