Successful development of mammalian oocytes, eggs and embryos relies on the production of ATP by their mitochondria, through metabolism of pyruvate and fatty acids. Imaging of lipid droplets in mammalian eggs has proven difficult due to the invasive, unspecific and unquantitative nature of fluorescent lipophilic stains. Here, we show that coherent anti-Stokes Raman scattering (CARS) microscopy can be used to image lipid droplets in live mouse oocytes and pre-implantation embryos, in a label-free, chemically-specific manner. CARS enables visualisation of lipid droplet distributions, and quantitation of droplet size, number and spatial distribution, notably whilst maintaining their developmental viability. CARS also allows examination of the type of lipids comprising lipid droplets, through means of hyperspectral imaging. It is shown that the chemical composition of these droplets differ in oocytes matured in media supplemented with saturated and unsaturated fatty acids. Correlation of CARS measurements with simultaneous two-photon fluorescence (TPF) microscopy of conventionally used lipid dyes demonstrates only partial correlation, and shows their lack of specificity and unpredictable staining patterns. Dynamic monitoring of lipid metabolism in eggs allows determination of the extent of fatty acid oxidation occurring in mouse oocytes and embryos. Investigation into how inhibition of fatty acid metabolism affects the mitochondrial redox state, membrane potential and ATP level allows further understanding of why fatty acid metabolism is significant for egg and pre-implantation embryo development. Starvation and fatty acid-feeding of oocytes shows that the lipid droplet distribution reflects their level of lipid metabolism, while the detrimental effects of palmitic acid are shown to involve its action at the endoplasmic reticulum SERCA pumps.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:704918 |
| Date | January 2016 |
| Creators | Bradley, Josephine |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/97984/ |
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