Reprogrammable In Vivo Architecture

The biological cell is the intricate, yet ubiquitous component of life, able to grow, adapt and reproduce. The genetic material contained within a cell encodes information which directs its development and behaviour, and this information is passed down from one generation of cell to the next. One emerging interest, resulting from collaborations between the disciplines of Molecular Biology and Computer Science, is to encode computational programs, sets of engineered, information processing instructions, in genetic material, to be executed by living cells.So far, the large majority of in vivo computation research has been based on the detection and conditional manipulation of protein concentrations inside cells, which is the biological method of gene expression. In contrast, this thesis describes how a computational program, encoded in genetic material inside a bacterium, can be triggered by external stimuli to reassemble itself in a directed manner to create a newly arranged computational program.In order to investigate the potential utility of in vivo self-arranging programs, software was designed to explore a search space of candidate computational programs, encoded in genetic material, which are able to rearrange themselves; to simulate these candidates and to evaluate their behaviour against a set of criteria. Rearrangements were facilitated by biological catalysts which can selectively sever and rejoin genetic material in a cooperative manner. Their ability to perform compound operations was found to allow for a general purpose mechanismAs a proof of concept, one of the candidate computational programs, a two-colour switch which can be set irreversibly through its rearrangement, was encoded in genetic material. Measurements of in vivo expression were observed resulting from in vitro rearrangement manipulations, to illustrate its operation

Global MicroRNA Expression Profiling Identifies MiR-210 Associated with Tumor Proliferation, Invasion and Poor Clinical Outcome in Breast Cancer

Aberrant microRNA (miRNA) expression is associated with cancer and has potential diagnostic and prognostic value in various malignancies. In this study, we investigated miRNA profiling as a complementary tool to improve our understanding of breast cancer (BC) biology and to assess whether miRNA expression could predict clinical outcome of BC patients.In VitroJournal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe