Microscopie | EPFL Graph Search

La microscopie est un ensemble de techniques d' des objets de petites dimensions. Quelle que soit la technique employée, l'appareil utilisé pour rendre possible cette observation est appelé un . Des mots grecs anciens mikros et skopein signifiant respectivement « petit » et « examiner », la microscopie désigne étymologiquement l'observation d'objets invisibles à l'œil nu. On distingue principalement trois types de microscopies : la microscopie optique, la microscopie électronique et la microscopie à sonde locale. En microscopie optique et électronique, un faisceau lumineux ou un faisceau d'électrons interagit avec l'objet à observer et est recueilli par un détecteur (œil, caméra...) alors qu'en microscopie à sonde locale, un capteur sonde directement la surface de l'objet. Rendant possible l'imagerie jusqu'à l'échelle atomique, la microscopie est aujourd'hui utilisée dans de nombreuses disciplines scientifiques ; son développement a, par exemple, révolutionné la biologie en rendant

Multidisciplinary Investigation of the Gut-Brain Ecosystem in a Model of Alzheimer's Disease

Arielle Louise Planchette

The search for an understanding of the causal elements that lead to neurodegenerative diseases has motivated researchers for decades. Today, Alzheimer's disease is the most prevalent form of dementia and affects approximately fifty million people worldwide, with only 5% of patients carrying causal genetic mutations. In recent years, studies of animal models as well as observations in humans have brought the gut microbiome to the forefront of AD research, as a significant contributor to the development of Alzheimer's disease. In fact, the gut microbiome is now understood to be a modulator of health and disease in numerous areas of physiology, including energy metabolism, immunity, endocrinology, and most relevant to this thesis, brain health and cognition. The gut microbiome is a complex environment composed of symbiotic bacteria, fungi and viruses (the microbiota) that produce a wide range of signalling molecules that are interpreted both by members of the microbiota and by the host (the microbiome). The host-gut interface is an ecosystem that consists of bi-directional signals and pressures applied by both constituents in order to maintain symbiotic homeostasis. Significant deleterious effects on health occur when homeostasis is lost, which may take place due to a variety of factors. These include host genetic factors and environmental factors, such as diet. Modulation of the gut microbiome has become a potentially viable therapeutic avenue for Alzheimer's disease, though it currently remains at the early stage of discovery. In this thesis, I characterize the evolution of Alzheimer's disease in the 5xFAD mouse model, with a focus on the gut microbiome and on cognitive decline and brain biochemistry. Gut microbiota modulaiton was implemented using germ-free and low-complexity bacterial cocktails, in which I outline the effects microbiota modulation on hallmarks of AD and provide insights into the metabolite profile of the brain altered by the microbiota and AD. The work in this thesis was equally motivated by the development of diagnostic tools using microscopy techniques. Biochemical assessments of disease status and progression provide information pertaining to "what" is interacting and "how much" this affects disease. With microscopy, we may gain the additional knowledge of "where" physiological constituents are and how they interact with the surrounding environment. I describe a novel multi-modal microscopy pipeline that enables the observation of signals of interest in large volumes and at high resolution with a capacity to cross-reference regions of interest in both modalities. The pipeline, known as gutOPT, consists of a sample preparation workflow compatible with mesoscale optical projection tomography (OPT) of fluorescently-labelled targets and subsequent imaging of pre-selected regions of interest in high-resolution modalities, such as confocal microscopy.

EPFL2022

Software Tools for Handling Magnetically Collected Ultra-thin Sections for Microscopy

Jelena Banjac

This report presents the software tools that will be available online to help users accurately segment ultra-thin sections of brain tissue in a large image to determine the section’s coordinates. In order to predict these coordinates, the goal was to use a state-of-art object instance segmentation framework called Masked Region-based Convolutional Neural Network (Masked R-CNN) on the dataset containing sections of brain tissue in the light microscopy images. The predicted coordinates of the sections will later be used for automated image acquisition in the high-resolution electron microscope. We will demonstrate that Masked R-CNN can be used to perform highly effective and efficient automatic segmentation of microscopy images containing the sections. The machine learning pipeline used will be explained in detail. In addition, we will show the results of how different parameters and settings of this pipeline were changing the performance. This semester's project was done in collaboration with the Center for Interdisciplinary Electron Microscopy (CIME) lab and Machine Learning and Optimization (MLO) lab at EPFL.

2019

Preparation and Analysis of Bacteria Surface-Modified with Polymer Nanoparticles

Lisa Patricia Elisabeth Bader

Cell-based drug carriers present an interesting approach to improve the targeted delivery of therapeutic drugs in vivo. Specifically, bacterial cells possess interesting properties such as motility and sensing that allow some strains to selectively target tumor areas. Immobilization of abiotic materials on the cell surface of such bacterial cells can therefore enable the delivery of therapeutic compounds at the desired location. The work presented in this thesis explores the fabrication and characterization of bacteria-nanoparticle biohybrids as potential carriers for drug delivery applications.Chapter 1 presents a review of the scientific literature that covers the different approaches to immobilize abiotic materials on the surface of bacteria. It highlights the advantages of using cells as carriers for the transport of therapeutics. An effective drug delivery agent should present great motility, viability, biodistribution and biocompatibility with human cells. Examples of various chemical approaches to surface-modify bacteria are presented. Chapter 2 systematically explores the immobilization of polystyrene nanoparticles on the surface of Escherichia coli (E. coli) and Salmonella typhimurium (Salmonella) cells. We compared the nanoparticle immobilization using four different conjugations strategies (electrostatic, covalent and ligand-ligand) and characterized the bio-hybrids systems using flow cytometry and confocal microscopy. Two different microscopy techniques were used: the first was based on 3D-reconstruction of z-stacks of single bacterium to investigate position of nanoparticles on the membrane; the second allowed for a large screening of bacteria followed by image processing determining the area of bacteria covered by nanoparticles. We observed that the efficiency of the surface modification is correlated to the initial nanoparticle/cell ratio and that non-covalent strategies allowed for increased number of biohybrids formed and nanoparticle attached. This study provides an overview of the variety of conjugation strategies (and their conjugation efficiencies) available for fabricating nanoparticle-decorated bacteria and presents us an opportunity to better understand and design bacteria-based target-specific drug delivery systems.Chapter 3 presents the characterization of the previously developed bacteria-nanoparticle biohybrids as potential carriers for nanoparticle transport. The viability of the various conjugates was determined by flow cytometry indicating a decrease in cell viability with increasing numbers of nanoparticles immobilized on the membrane. The motility was studied to investigate the impact of nanoparticle attachment on the bacterial velocity as well as the capacity to transport the cargo. Bacteria were able to transport nanoparticles when prepared with low ratios of nanoparticle/cell.

EPFL2022

Multidisciplinary Investigation of the Gut-Brain Ecosystem in a Model of Alzheimer's Disease

Arielle Louise Planchette

EPFL2022

Preparation and Analysis of Bacteria Surface-Modified with Polymer Nanoparticles

Lisa Patricia Elisabeth Bader

EPFL2022