Exploring the interplay between autonomous immunity and S. aureus during intracellular infection by super-resolution microscopy
Duration: 48 weeks
BACKGROUND
In Europe, the burden caused by antibiotic resistant bacterial infections is equivalent to influenza, HIV/Aids and Tuberculosis combined. Infections caused by Staphylococcus aureus (S. aureus) strains are the second most relevant in this context. A chief factor suggested to contribute for the high incidence and prevalence of S. aureus infections is its capacity to persist and divide inside host cells, escaping antibiotics and extracellular immune recognition. Formerly regarded as an exclusively extracellular pathogen, S. aureus is in fact a facultative intracellular pathogen. S. aureus can infect immune and non-immune cells and evade autonomous immunity (intracellular recognition of pathogens). This is thought to be a major factor in continuance of carriage, chronicity of infection and dissemination within the host. The cell surface molecular signatures important for host autonomous immunity recognition of facultative intracellular pathogens, such as S. aureus, and the host autonomous immunity factors responsible for identifying them are still not fully understood. In this project we propose to develop an experimental framework that will have far-reaching impact on our understanding of autonomous immunity function and how we approach the mechanisms of intracellular recognition of pathogens. The knowledge gained here will be applicable to other bacterial pathogens and in the development of new chemotherapy options to tackle the challenges of bacterial infections.
OBJECTIVES
To create a high-resolution map of the interplay between S. aureus and host cell components we need a multi-target near-molecular scale resolution strategy. For this purpose we will use super-resolution microscopy (SRM) which seamlessly provides multi-target molecular specific labelling and sub-diffraction spatial resolution. SRM congregates several approaches the lab has expertise on, from classical single-molecular localization microscopy (SMLM) and structured illumination microscopy (SIM) to very recent expansion microscopy (ExM). These approaches permit achieving spatial resolution bellow diffraction (as low as 10 nm) of multiple host and bacterial targets. However, these techniques rely heavily in immunolabelling (the use of antibodies to localize specific biological targets). In S. aureus biology this is not a trivial task as this in this bacteria Protein A is a major cell wall component. Protein A is a virulence factor of Staphylococcus aureus that binds to the Fc region of IgG antibodies. By binding to the Fc portion of antibodies, protein A renders them inaccessible to opsonins, thus impairing phagocytosis of the bacteria via immune cell attack. This helps protect S. aureus from being engulfed and subsequently killed by immune cells. For microscopy purposes this also signifies that most antibodies will bind to S. aureus cells. Hence TASK 1 of this master project is to develop a blocking strategy to “saturate” all protein A binding sites before labelling with the antibody of interest, this way permitting immunolabelling of the target of interest to be specific. In parallel TASK 2 we will map the interaction of S. aureus cells at different times post infection with cytoskeletal and autonomous immune host factors. Task 2 will be performed using antibodies, for which we will use a protein A mutant of S. aureus, albeit not ideal from a biological perspective (as this strain is lacking a virulence factor) it will permit to optimize the analysis pipeline. A major prospect if to analyse this interaction in live cells to understand the spatiotemporal dynamics of the process, however most high-resolution SRM approached are light intensive an often do not allow multi-colour imaging. To overcome this, TASK 3 will entail developing and using image analysis pipelines based on deep learning approaches to correlate low resolution data with high-resolution data. The combination of these approaches will allow constructing a high-resolution image of the multi-component host cell cytoskeleton and S. aureus containing subcellular compartments. This will permit to correlate how endocytosis, autophagy and cytoskeleton markers correlate with S.aureus cell division and how antibiotic chemotherapy influences these processes. This master project will provide training in microbiology, cell biology, microscopy, and deep learning strategies.
About the PI
Pedro Pereira completed his degree in Applied Chemistry in 2006 at FCT NOVA and his PhD in Cell Biology from ITQB NOVA in 2013. He did post-doctoral work at UCL in the UK developing super-resolution approaches and applying them to host-pathogen interaction cell biology questions. In late 2021, he secured an Auxiliary Researcher position at the ITQB NOVA, through a Mostmicro open call. Throughout his career path, he published 31 articles in peer-reviewed international journals and presented his results in several national and international conferences, seminars, and workshops. His research focuses on 1) exploring the dynamic interaction between human cells and bacterial pathogens, 2) the development of imaging approaches to fully understand these interactions and 3) developing strategies to overcome the antimicrobial molecule shortage challenge.
Ciência ID: 2112-9437-36FA
ORCID ID: 0000-0002-1426-9540