Figure 1: Automated 3D rendering of the endoplasmic reticulum (blue) from a 3D volume acquired with the FIB-SEM of a high pressure frozen HeLa cell (rendering and image by Julian Hennies).

Figure 1: Automated 3D rendering of the endoplasmic reticulum (blue) from a 3D volume acquired with the FIB-SEM of a high pressure frozen HeLa cell (rendering and image by Julian Hennies).

Figure 2: CLEM aims at imaging the same cells with both fluorescence microscopy and EM. Here, fluorescence imaging was used to target PLK4 overexpressing cells, that display centriolar aberrancies and asymmetric mitotic spindle (Cosenza et al. 2017).

Figure 2: CLEM aims at imaging the same cells with both fluorescence microscopy and EM. In this example, fluorescence imaging was used to target PLK4 overexpressing cells, that display centriolar aberrancies and asymmetric mitotic spindle (more in Cosenza et al. 2017).

The Schwab team is developing tools for the 3D correlation of data generated by fluorescence imaging and by electron microscopy.

Previous and current research

Correlative light and electron microscopy (CLEM) is a set of techniques that allow data acquisition with both imaging modalities on a single object. It is a growing field that now includes a large variety of strategies, and one that reaches a high degree of precision, even in complex biological models. One common challenge when trying to combine imaging modalities on the same sample is to identify spacial cues (external or internal) to track single objects when switching from light microscopy (LM) to electron microscopy (EM).

On cultured cells, substrates with a coordinate system can be utilised to precisely record the position of cells. Commercial substrates were used in the team's collaboration with the Bartenschlager group to visualise the viral infection of cells at the ultrastructural level (Chatel-Chaix et al. 2016, Cortese et al. 2017). Currently, we are exploiting these approaches to develop new workflows allowing the study of a higher number of cells (Cosenza et al. 2017). The team aims to bring automation to the focused ion beam scanning electron microscope (FIB-SEM) in such a CLEM workflow.

On more complex specimens, such as multicellular organisms, this targeting is even more critical, as systematic EM acquisition of their entire volume is close to impossible. For this reason, we are developing methods to map the region of interest (ROI) within large living specimens, taking advantage of structural hallmarks in the sample that are visible with both LM and EM (Schieber et al. 2017). The position of the ROI is mapped in 3D by confocal or multiphoton microscopy and then tracked at the EM level by targeted ultramicrotomy (Kolotuev et al. 2009, 2012; Goetz et al. 2014, Durdu et al. 2014, Karreman et al. 2014). The precision and throughput is improved buy using microCT as a bridging modality (Karreman et al. 2015, 2017; Weinhard et al. 2018).

Future projects and goals

In parallel to the fast evolution of CLEM techniques over the past decade, acquisition methods in electron microscopes have significantly evolved with special breakthroughs in the volume analysis of cells by TEM tomography and automated serial imaging in scanning electron microscopy (ASI-SEM). Our team, in collaboration with other scientists and our industrial partners, combines these advanced techniques to perform CLEM in the 3D space on complex model specimens for cell and developmental biology. We aim to develop new techniques, engineer new tools and software to facilitate and automate the correlation and acquisition of large amounts and volumes of sample. By automating these tedious procedures, we intend to improve the throughput of data collection.