Computational analysis of microglial dynamics in health and disease

Postgraduate Thesis uoadl:2882294 276 Read counter

Unit:
Κατεύθυνση Βιοπληροφορική
Library of the School of Science
Deposit date:
2019-10-08
Year:
2019
Author:
Roufagalas Ilias
Supervisors info:
Ιωάννης Τρουγκάκος, Καθηγητής, Τμήμα Βιολογίας, Πανεπιστήμιο Αθηνών
Original Title:
Υπολογιστική ανάλυση της δυναμικής της μικρογλοίας του εγκεφάλου σε φυσιολογικές και παθολογικές συνθήκες
Languages:
Greek
Translated title:
Computational analysis of microglial dynamics in health and disease
Summary:
Microglia are the resident immune cells of the Central Nervous System (CNS), with crucial roles in both tissue development and homeostatic maintenance. In the healthy brain, microglia are highly motile ramified cells that constantly extend and retract their processes to survey the CNS parenchyma, a mode of motility that is called microglial surveillance and recently shown to be regulated by the tonic activity of the potassium channel THIK-1. Under pathological conditions, such as brain tissue damage, disease or infection, microglia upregulate several surface receptors such as MHCII and A2A, and their morphology becomes less ramified, with fewer, shorter processes and larger somata.
In this project microglial dynamics were investigated in the healthy brain as well as at different stages of an experimental model of Multiple Sclerosis, Experimental Autoimmune Encephalomyelitis (EAE). By using C57BL/6 and genetically-labelled reporter mice (CX3CR1-GFP), confocal, two-photon microscopy and cranial window techniques, we imaged microglial morphology and recorded microglial motility and surveillance in the healthy brain of anaesthetized mice during the progression of the EAE pathology. The imaging data was analyzed by using high-throughput image analysis tools, including Imaris and ImageJ2/Fiji. For the pre-processing of the images, we developed custom programming scripts written in ImageJ2 macro-language, which were integrated in the tools as additional plugins. For the processing of the image data acquired from the confocal microscope, used for the analysis of the microglial morphology, we developed a specific application (MicroApp), written in the programming languages Java and MATLAB.
Our newly developed automated computational analysis allowed the processing of a very big volume of data, providing for the first time the circumstances for a longitudinal analysis of the microglial dynamics and their morphology in different regions of the brain and during different disease states. The initial results show that the morphological variations of the microglial cells appear in a different manner and in different timepoints during EAE, indicating a region-dependent microglial response during pathological conditions. The morphological analysis also showed that the cerebellum is the brain region which is affected earlier during the disease course, starting from the pre-onset phase. These results raise the interest for the cerebellum region as a future target for studying the mechanism of EAE, something that hasn’t been extensively studied so far. Finally, the results show a reduction of microglial motility and surveillance during the clinical phase of EAE in the cortex. As a future goal, the same study will be conducted in the cerebellum and at earlier pre-onset timepoints of the disease.

The project was held under the supervision of postdoc researcher Dr.Vasiliki Kyrargyri inder the framework of the ELIDEK project «Microglia-driven pathology and altered surveillance in demyelination» (Act 1156), in collaboration with the laboratory of Molecular Genetics (head of the lab: Dr.Lesley Probert) at the Hellenic Pasteur Institute.
Main subject category:
Science
Keywords:
bioinformatics, brain, microglial cells, Multiple Sclerosis, Central Nervous System, cerebellum, Experimental Autoimmune Encephalomyelitis
Index:
No
Number of index pages:
0
Contains images:
Yes
Number of references:
159
Number of pages:
136
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