Symbiodiniaceae is a family of dinoflagellates which often live in a symbiotic relationship with cnidarian hosts such as corals. Symbiodiniaceae are vital for host survival, providing energy from photosynthesis and in return gaining protection from environmental stress and nutrients. However, when these symbiont cells are exposed to environmental stress such as elevated temperatures they can be expelled from their host, leading to the coral bleaching, a global issue. Coral reefs are vital for marine biodiversity and hold a large economic importance due to fishing and tourism. This thesis aims to develop a computational pipeline to study growth, shape and size of Symbiodiniaceae cells, which takes microscopy images using a mother machine microfluidics device and segments the Symbiodiniaceae cells. This enables extraction ofcellular features such as area, circularity and cell count to study morphology and growth of Symbiodiniaceae based on segmentation labels. To achieve this, pretrained segmentation models from the Cellpose algorithm were evaluated to decide which was the best to use to extract features most accurately. The results showed the pretrained ‘cyto3’ model with default parameters performed the best based on the Dice score. The feature extraction showed indications of division events of Symbiodiniaceae linked to light and dark cycles, suggesting synchronicity among cells. However, segmentation needs further investigation to accurately capture cells and add statistical significance to the feature extraction.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-534140 |
| Date | January 2024 |
| Creators | Kinsella, Michael |
| Publisher | Uppsala universitet, Institutionen för biologisk grundutbildning, Uppsala University |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0621 seconds