Qattan, ATM;
(2013)
Large scale quantitative organelle proteomics of protein distribution in Breast Cancer MCF-7 cells.
Doctoral thesis , UCL (University College London).
Abstract
This thesis analyzes the dynamic complexity involved in the subcellular distribution of the proteins for the malignant breast epithelial MCF-7 cell line, using mass spectrometry based quantitative proteomics for the indirect measurement of the subcellular dispersion of the constituent proteins of core cellular functions. The thesis demonstrates that there are many proteins which can be present in more than one subcellular organelle. Quantitative proteomics using LFQP (Label-Free Quantitative Proteomics) methodology based on mass spectrometry was shown to be suitable for the indirect measurement of the distribution of the proteins in the malignant breast epithelial cell line. The study used partial purification by means of dynamic sucrose gradient centrifugation to avoid the need of multiple purification procedures for different organelles and loss of proteins during purification. This was followed by proteomics identification and analysis of the protein content from the sucrose gradient fractions corresponding to the major organellar compartment. These included the nucleus, cytosol, mitochondria, plasma membrane and endoplasmi c reti cul um. The first part of the thesis indicates that 50.00% - 75.00% of the proteins detected showed multiple-locations. Out of the total quantified proteome using LFQP methodology, 2184 proteins were securely identified. 481 proteins (22.00%) were found in unique sucrose gradient fractions which suggest that they may have unique locations, while 454 proteins (20.80%) were found to be ubiquitously distributed and the remaining 1249 proteins (57.20%) were consistent with intermediate distribution over multiple locations. 94 proteins implicated in breast cancer and 478 other proteins which share the same major cellular biological processes with most of the breast cancer proteins were observed in 334 and 1223 subcellular locations respectively. The second part of the thesis concentrates on the spatial distribution of proteins between two organelles of particular interest for cancer: the nucleus and mitochondria. Two important characteristics of cancer cellular function include high degrees of genetic instability and major changes in cellular energy metabolism. The genetic instability, which is associated with the cell nucleus, allows cells to escape from a variety of normal restrictions on proliferation, whereas the changes in energy metabolism are associated with mitochondria and the need for new cellular components to be produced in the proliferating cells. The large scale proteomics analysis of the partitioning of proteins between mitochondria and the nucleus reveals that 40.00% of all the proteins were shared between the mitochondria and the nucleus. The observed partitioning of these proteins between these two organelles showed a functional distribution which is consistent with the first part of the thesis. The analysis of the distribution between the nucleus and mitochondria of specific subgroups of the proteins involved in oxidative phosphorylation, the tricarboxylic acid cycle, RNA processing/translation, glycolysis and Ras-related signalling suggests that the spatial distribution of numerous proteins over multiple sites is critical to cellular function and that there are unrecognized aspects of functional coordination between the mitochondria and the nuclei which need further investigation. In addition, the large number of proteins identified to be in multiple locations indicates that subcellular spatial integration of function may be a vital aspect of cancer. The findings in this study also reveal that most of the observed proteins with multiple subcellular locations had current annotations of location which are still sparse in public databases. In general terms, the extensive subcellular dispersion of the constitute proteins of core cellular functions may be a fundamental feature of the cell which may be constituent with the requirements for robustness in a complex system.
| Type: | Thesis (Doctoral) |
|---|---|
| Title: | Large scale quantitative organelle proteomics of protein distribution in Breast Cancer MCF-7 cells |
| Language: | English |
| Additional information: | Permission for digitisation has not been received. |
| UCL classification: | |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1415963 |
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