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Thesis

Automated image-based recognition and targeted laser transfection techniques for drug development and stem cell research

Abstract:

Advances in several areas of scientific research is currently hampered by the slow progress in developing a non-viral, high precision technique capable of safely and efficiently injecting targeted single cells with impermeable molecules. To date, one of the most promising techniques employs the laser to temporarily create a pore in the cell membrane to allow the entry of exogenous molecules. This technique has potentially wide applications.

In this thesis, I utilised the precision of laser transfection, also known as optoporation, to deliver two histone demethylase inhibitors (8-hydroxyquinoline and FMF1293) of the JmjC-domain protein JMJD3 into vital cells. The enzyme, JMJD3, demethylates histone H3 lysine K27, the methylation state of which has been shown in previous studies to regulate genes in such a way as to play a key role in the formation of tumours and even maintenance of stem cell pluripotency. The research here shows proof of principle that optoporation can be employed to quickly screen and test the efficacy of novel drugs by delivering them into cells at significantly low concentrations while still maintaining inhibition activity. I also used optoporation to deliver relatively large proteins such as bovine serum albumin (BSA), phalloidin and novel synthetic antibodies into living cells without fixatives. This offers the possibility of using reporter systems to monitor living cells over time. Finally, an attempt was made to generate iPS colonies by optoporating plasmid DNA into somatic cells, however, I find that this technique was unable to efficiently transfect and reprogram primary cells.

Two automated image-based systems that can be integrated into existing microscopes are presented here. First, an image processing algorithm that can quickly identify stem cell colonies non-invasively was implemented. When tested, the algorithm’s resulting specificity was excellent (95 – 98.5%). Second, because optoporation is a manual and time consuming procedure, an algorithm to automate optoporation by using image processing to locate the position of cells was developed. To my knowledge, this is the first publication of a system which automates optoporation of human fibroblasts in this way.

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Wolfson College
Role:
Author

Contributors

Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor


Publication date:
2011
DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
Keywords:
Subjects:
UUID:
uuid:9592871b-9faf-46c9-9927-69cf8a414589
Local pid:
ora:6654
Deposit date:
2013-01-15
ARK identifier:

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