A novel technology for the generation of light emitting somatic transgenic animals has been developed using lentiviral vectors where luciferase expression is transcriptionally regulated by tandem, synthetic, transcription factor binding elements. This allows signalling pathways in diseased organs to be monitored continually and consciously and in a non-invasive manner. I was able to confirm my hypothesis that long term somatic transgenesis could be achieved within the CNS after a single neonatal intracranial injection of the biosensors. No signs of activated microglia or astrogliosis from the injection or the vector expression was observed. I generated several lentiviral biosensors and this included an astrocyte specific biosensor GFAP. I established and validated a Hypoxic Ischemic Encephalopathy mouse model in outbred CD1 mice. I applied somatic transgenic technology to the HIE mouse model to investigate whether it was possible to predict the severity of the disease in live mice. Unexpectedly, the luciferase expression from the four biosensors failed to correlate with the extent of brain infarct or the weight of the mice. To investigate this surprising results, I challenged the underlying assumption that GP64 enveloped lentiviral vectors target GFAP positive astrocytes. Interestingly very few astrocyte positive cells were being targeted by the GP64 pseudotyped lentiviral vectors. As GFP expression from lentiviral vectors was limited and mainly situated around the injection site, I investigated the use of AAV delivery to the CNS. AAV8 vector generated strong and homogenous GFP expression. An AAV8 NFκB biosensor was made and injected intracranially to new-born mice. This showed substantially more stable luciferase expression compared with lentivirus vectors.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:700678 |
| Date | January 2016 |
| Creators | Karda, Rajvinder |
| Contributors | Johnson, Mark R. ; Waddington, Simon N. ; Hagberg, Henrik H. |
| Publisher | Imperial College London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10044/1/43158 |
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