Study Lead: Prof. Ralf Bartenschlager, Heidelberg University, Dept of Molecular Virology, Germany


The sudden emergence and rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has endangered global health and the economy. While clinically approved vaccines have become available at an unprecedented record pace, there are still no clinically approved drugs specifically targeting SARS-CoV-2 and little is known about the molecular interactions between the virus and its host.

A key to developing drugs that suppress SARS-CoV-2 and the pathology induced by the virus is to understand the intracellular phases of virus replication and the perturbations induced in infected cells. Soft X-ray Microscopy (SXM) will be the central technology employed, allowing holistic analyses of whole cells which is not possible with other imaging techniques.

Apart from extensive remodelling of endoplasmic reticulum and Golgi apparatus, we expect to detect morphological changes of other organelles such as mitochondria, endosomes and lipid droplets (Khan et al. 2015). SXM will be combined with automated segmentation based on machine learning and correlated with fluorescence and electron microscopy.

Through quantitative studies of the interplay between the viral replication cycle and spatiotemporal morphological changes within individual cells, we expect to reveal new principles of the mechanisms of SARS-CoV-2 virus-induced alteration of infected cells. This will provide important information for the development of antiviral therapy.


Currently, it is unclear which strategies SARS-CoV-2 has developed to exploit cellular resources facilitating viral propagation. Moreover, it is unclear to what extent disease severity is linked to direct cytopathogenity of the virus. It is also unknown whether the magnitude and type of virus-induced cell perturbations depend on the cell type.

To establish a 3D model of intracellular modification of SARS-CoV-2 infected cells, we will combine advanced soft x-ray imaging methods with automated segmentation based on machine learning. Quantitative studies of the interplay between the virus and its host cell will reveal new principles of cellular homeostasis and its perturbation by SARS-CoV-2 infection. These studies provide important information for the development of therapy suppressing virus replication and reducing disease severity.


Aim 1: To reconstruct SARS-CoV-2 induced 3D intracellular phenotypic modifications:

To study how SARS-CoV-2 remodels the cell for efficient replication, we will use established cells lines: Calu-3 (human, lung), A549 expressing ACE2 (human, lung) and Vero (monkey, kidney). All three cell lines are fully permissive for SARS-CoV-2 and thus, well suited for virus-host interactions studies.

  • We will employ SXM to analyse cellular remodelling by using it to visualize the presence, distribution, volume and morphological changes of cellular organelles, including mitochondria (in collaboration with Use Case 2). The cells will be placed in cylindrical capillaries allowing for rapid tomogram of the entire cell at different times of viral infection. We already employed electron tomography to gain fist insights into SARS-CoV-2 remodelling of the cellular endomembrane system (see figure; adapted from Cortese et al., Cell Host & Microbe 2020).
  • To assemble morphological profiles, manually segmented data will be prepared for training of machine learning and automatic segmentation of SARS-CoV-2 virions and cellular organelles. Based on automatic segmentation, we will assemble an average 3D phenotype of cellular remodelling induced by viral infection. This concept was developed in previous work phenotyping teleost fish (Weinhardt et al., 2018). At the intracellular level, the approach is similar to assembly of structure obtained by protein crystallography in the cellPAINT software (, which can be adapted to 3D data within this project.
  • For detailed view of membrane alterations, we will use the prototype SXM to image cells prepared on TEM grids and in capillaries and correlate this data with data from light microscopy by use of an integrated fluorescence microscope. This correlative approach will help to analyse rare events in a cell with extremely high precision.

Aim 2: To identify whether this remodelling is unique among other cell types with SARS-CoV-2 receptor:

To characterize viral entry into different types of cells, we will employ a methodical pipeline established in Aim 1 and automatic data reconstruction pipeline. Based on pathological data, we will preliminarily focus on epithelia of small intestine, arterial and venous endothelial cells and arterial smooth muscle cells (Hamming et al. 2004).

For imaging of different cell types and potentially tissue sections, the prototype SXM and the subsequent SXT-200 will be equipped with cylindrical and flat specimen holders. Similar to lung epithelial cells, we will assemble morphological profiles for different stages of the SARS-CoV-2 replication cycle. For cell types with distinct remodelling of cellular organelles, we will use complementary imaging techniques, such as super-resolution microscopy, electron tomography and FIB-SEM/CLEM.

These comparative results will help to identify factors that are commonly used by the virus for replication in different tissues and possibly suitable as target for the development of antiviral drugs.

Figure: Electron tomography and 3D rendering of SARS-CoV-2-infected Calu-3 cells (MOI = 0.5) harvested 24 h after infection. On the left side you see a slice through the tomogram with superimposed rendering of cellular and viral organelles that are specified on the bottom of the figure.

The image on the upper right depicts a 3D rendering of visualized organelles. The image in the lower right is a zoom-in view of the vesicular-tubular compartment (VTC) and the Golgi apparatus (dark blue) with budding virions (yellow), and fully assembled virions (orange). Scale bars, 200 nm (adapted from Cortese et al., 2020 Cell Host & Microbe)