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Past STSMs

Massimiliano Lucidi

Correlative multimodal approach based on nanoscale far-field, near-field and topographic imaging to characterize the morphology and antibiotic susceptibility of ESKAPE pathogen bacteria

Nanoscopy techniques can overcome the Abbe’s diffraction limit, which is about half the wavelength of the excitation light, and are capable to achieve resolutions of less than 50 nm. Stimulated Emission Depletion (STED) microscopy can increase the optical resolution of a conventional confocal microscope with up to one order of magnitude, by switching off the fluorescence of dye molecules positioned in the outer regions of the excitation area with an intense doughnut shaped laser beam that depletes the electrons from the excited levels. In our work, we stained different pathogenic bacterial species using the Abberior® STAR RED NHS, which has been previously utilized in STED imaging of eukaryotic cells. To our knowledge, this is the first experimental demonstration on prokaryotes’ staining with this dye, and the obtained results suggest that Abberior® STAR RED NHS is able to label the membranes of both Gram-positive and Gram-negative bacteria. We also characterized the same bacterial species with scattering-type Scanning Near-field Optical Microscopy (s-SNOM), a label-free technique for optical nanoscale imaging that we used in combination with Atomic Force Microscopy (AFM) to place the optical information into a topographic context, which is relevant for the viability of the imaged organisms. s-SNOM relies on the fact that the interaction between the enhanced near-field at the tip apex, which results upon its illumination with a focused laser beam, and the sample volume underneath modifies both the amplitude and the phase of the scattered light. Besides qualitative studies, s-SNOM was recently used to determine at nanoscale resolution the refractive index (RI) of human erythrocytes. For the first time, we use the same approach to determine the RI of both commensal and pathogen bacteria, which is useful for understanding in detail their optical properties and morphology.

All these preliminary data were obtained Center for Microscopy-Microanalysis and Information Processing of University Politehnica of Bucharest, allowing me to acquire novel and fundamental skills in AFM and STED sample preparations. This experience has represented for me a great opportunity for my scientific carrier and growth, and it has opened new possibilities of future collaborations between my Institute (University of Roma Tre in Rome) and the Center for Microscopy-Microanalysis and Information Processing, which represent for me and my colleagues a reference center for imaging and super-resolution approaches. In addition, I have also experimented the great Romanian hospitality, finding new friends other than valid collaborators!


Ana Laura Sousa

High-accuracy CLEM for Plants

The High-accuracy CLEM for Plants STSM enabled the optimization of a CLEM protocol for the locomotory apparatus in the plant model organism Physcomitrella patens. This on-section CLEM work-flow started to be developed at the Instituto Gulbenkian de Ciencia – Electron Microscopy Facility, however technical difficulties were encountered that did not allow a good correlation.

During this STSM at EMBL, it was possible to optimize the on-section CLEM protocol and we could overcome the technical difficulties encountered before. By the end of the STSM, we could confirm the location of the endogenous proteins in the structure of interest.

There is still room for technical improvementsthat are currently underway at the home institution Instituto Gulbenkian de Ciencia - Electron Microscopy Facility in Portugal. The focus is now on improving the overall fixation quality of the sample ultrastructure without overly compromising the endogenous fluorescent signal.

After optimization, the protocol will be implemented within the facility and be available to a broad community of users. Furthermore, in the near future there will be additional technical developments so the protocol can be adapted for the study of other biological models.


Francesca Brescia

Influence of nutrient conditions on secondary metabolite production in terms of concentration and structure of Lysobacter capsici AZ78 studied by SEM and MALDI MSI

The rate of novel antibiotic discovery is constantly decreasing and antibiotic resistance among pathogens is becoming a major worldwide concern. Considered as a potential source of novel antimicrobial compounds, the genus Lysobacter is included in the Xanthomonadaceae family and it is ubiquitous in the environment. Many Lysobacter strains, including L. capsici AZ78 (AZ78), produce an impressive diversity of bioactive compounds against diverse microorganisms including fungi, Gram-positive and Gram-negative bacteria, as well as clinical methicillin-resistant Staphilococcus aureus isolates.

Recent studies on the Lysobacter sequenced genomes have reported the presence of genes potentially involved in the biosynthesis of still unknown bioactive secondary metabolites. However, in laboratory culture conditions many genes are silenced, while a growth condition more similar to a natural one could induce a different gene expression.

Lysobacter capsici AZ78 was isolated from tobacco rhizosphere, an ecological niche in which microbial diversity is high and bacteria have to constantly compete for nutrients and space. Using optical microscopy and MALDI TOF MSI we demonstrated that different nutrient conditions can affect the growth behaviour and the production of secondary metabolites. In particular, a nutrient condition similar to the plant rhizosphere stimulates the production and the diffusion of antibiotics in the external part of the colony and in the growth medium. We will now correlate this metabolic information with biofilm information taken from SEM analysis (image generation still in progress at home institution) to better understand how such a biofilm affects the diffusion of bioactive compounds in the surrounding environment.


Pedro Macías Gordaliza

Expert Processing of Multimodality-lmages to Evaluate Pulmonary Tuberculosis

The Short-Term Scientific Mission (STSM) has facilitated the development of an artificial intelligence based application for the quantification of the lung damage caused by Tuberculosis. Potentially, this application would be of use to asses the necessary drug trials for the development of new and more effective Tuberculosis treatments.

The use of suitable software for disease quantification purposes, as the one implemented during the STSM, has direct repercussions on the people lives. Our specific solution allows to perform more economic and efficients drug essays which has a direct impact on the reduction on the time design on new vaccines and antibiotics against the disease, which is key in the Tuberculosis case due to its high rates of drug resistance and bacteria mutation.


Suman Khan

Obtaining a Mechanistic Understanding of Cell Fusion Using Correlative Microscopy

My research is aimed to understand the sequence of molecular events that lead to fusion of muscle precursor cells, called myoblasts to form skeletal muscles development during myogenesis, and muscle regeneration in adults. Defects in myoblast fusion is implicated in several myopathies as well as muscle depletion with age. For instance studies of Limb Girdle Muscular Dystrophy and Duchenne Muscular Dystrophy, have indicated that fusion is impaired leading to a reduction in the ability of muscle fibers to repair muscle degeneration and regenerate. Hence there is a need to understand myoblast fusion, especially for developing treatment of myopathies. Nevertheless the molecular mechanism of myoblast fusion is poorly understood, as we do not know which proteins apply forces on the membranes in order to merge them.

My goal is to identify the proteins that localize to the contact sites between fusing myoblasts, and determine how they localize relative to the fusing membranes and reveal how membrane architecture changes during fusion. These data will allow us to determine the organization of the fusion machinery at sites of fusion, and how it mediates this process. To achieve these goals, I have optimized a pipeline based on Correlative Light 3D Electron Microscopy (CLEM) which would allow me to visualize the ultra-structure of the membrane between fusing cells and identify proteins that localize to the membrane during the fusion process. In our lab in Weizmann Institute of Science, we are able to target the fluorescence microscopy signals of the region of interest (ROI) to acquire the underlying ultra-structures with electron microscopy (EM). But for a descriptive studies in cell biology especially to understand the cell morphologies at an ultra-structural level, often requires acquiring multiple images of the same object at different stages. Since we manually select the coordinates of the ROI for EM acquisitions, there is still a need to increase the throughput of EM data acquisitions through automation. To accomplish this goal, I visited the lab of Prof. Yannick Schwab at the EMBL Heidelberg, to learn how data acquisition can be automated based on in-situ image analysis and correlation. They have recently developed software for automated Transmission Electron Microscopy (TEM). My aim was to get acquainted with the automated workflow for the possibility of technology transfer to our group by adopting the codes to acquire Scanning Transmission Electron Microscopy (STEM) data. This would enable automation to be applied in our current CLEM workflow. Post-STSM, my current undertaking at my home institution is to adopt and tailor an automated workflow for our electron microscopes in our institute.

Keywords Cell-fusion, Myogenesis, Myoblast Fusion, CLEM.