Doctor of Philosophy / Department of Biochemistry and Molecular Biophysics / John M. Tomich / Branched Amphiphilic Peptide Capsules (BAPCs) are peptide nano-spheres comprised of equimolar proportions of two branched peptide sequences bis(FLIVI)-K-KKKK and bis(FLIVIGSII)-K-KKKK that self-assemble in water to form bilayer delimited poly-cationic capsules capable of trapping solutes. We examined the lipid-like properties of this system including assembly, fusion, solute encapsulation, and resizing by membrane extrusion as well as their capability to be maintained at a specific size by storage at 4˚C. These studies along with earlier work from the lab (Gudlur et al. (2012) PLOS ONE 7(9): e45374) demonstrated that the capsules, while sharing many properties with lipid vesicles, were much more robust. We next investigated the stability, size limitations of encapsulation, cellular localization, retention and, bio-distribution of the BAPCs. We demonstrated that the BAPCs are readily taken up by epithelial cells in culture, escape or evade the endocytotic pathway, and accumulate in the peri-nuclear region where they persist without any apparent degradation. The stability and persistence of the capsules suggested they might be useful in delivering radionuclides. The BAPCs encapsulated alpha particle emitting radionuclides without any apparent leakage, were taken up by cells and were retained for extended periods of time. Their potential in this clinical application is being currently pursued. Lastly we studied the temperature dependence of capsule formation by examining the biophysical characteristics of temperature induced conformational changes in BAPCs and examined the structural parameters within the sequences that contribute to their remarkable stability. A region in the nine-residue sequence was identified as the critical element in this process. The ability to prepare stable uniform nano-scale capsules of desired sizes makes BAPCs potentially attractive as delivery vehicles for various solutes/drugs.

Statins, common cholesterol control drugs, are appreciated to have promising anticancer activity through inhibition of the mevalonate pathway. Several lines of evidence suggest that certain tumours are susceptible to statins, but the underlying molecular features arbitrating this sensitivity remain unknown. We hypothesize that (i) not all statins will behave equivalently in the context of anticancer therapy, and (ii) a molecularly-defined subset of tumours are intrinsically sensitive to statins. My objectives have therefore been to further our understanding of functional differences between statins influencing their anticancer effects, and to investigate molecular features associated with statin sensitivity in breast cancer. Specifically, this thesis addresses two aims: (i) to characterize differential interactions between four statins and the xenobiotic transporter P-glycoprotein (P-gp; also known as ABCB1), and (ii) to identify molecular features associated with fluvastatin and lovastatin sensitivity in breast tumour cell lines. We first characterized the interactions of statins with P-gp in vitro and in multidrug-resistant (MDR) tumour cells. While lovastatin could directly bind to P-gp and modulate MDR, no significant interactions were observed with fluvastatin. Fluvastatin may therefore be appropriate for use in unselected patients, to avoid adverse drug interactions with coadministered P-gp substrate chemotherapeutics. Fluvastatin has also shown promise in breast cancer treatment, where molecular features predictive of statin sensitivity would be particularly valuable. A panel of 19 immortalized breast cell lines was therefore characterized for sensitivity to fluvastatin and lovastatin. Relatively statin-sensitive cells underwent apoptosis upon statin treatment, and were more likely to have an estrogen receptor alpha (ERα)-negative, basal-like phenotype. By mining available baseline gene expression data, a candidate 10-gene signature predictive of fluvastatin sensitivity was also generated. Taken together, this research provides insight into molecular markers of statin sensitivity that may facilitate fast-tracking of these drugs to clinical trials in subsets of cancer patients most likely to respond.

Human maltase-glucoamylase (MGAM) and sucrase-isomaltase (SI) are the small-intestinal glucosidases responsible for catalyzing the last glucose-releasing step in starch digestion. MGAM and SI are each composed of duplicated catalytic domains, N- and C-terminal, which display complementary substrate specificities for the mixture of short linear and branch oligosaccharide substrates that typically make up terminal starch digestion products. As MGAM and SI are involved in post-prandial glucose production, regulating their activities with α-glucosidase inhibitors is an attractive approach to controlling blood glucose levels for the prevention and treatment of Type 2 diabetes. To better understand the complementary activities and mechanism of inhibition of these intestinal glucosidases, this thesis aims to characterize the individual N- and C-terminal MGAM and SI domains using a combination of X-ray crystallographic structural studies, enzyme kinetics, and inhibitor studies. First, the structure of the N-terminal domain of MGAM (ntMGAM) was determined in its apo form and in complex with the inhibitor acarbose. In addition to sequence alignments and kinetics studies, the structures provide insight into the preference of the N-terminal MGAM domain for short linear substrates and the C-terminal domain for longer substrates. Second, the structure of ntMGAM was determined in complex with various α-glucosidase inhibitors, including those currently on the market (acarbose and miglitol), a new class of inhibitors from natural extracts of Salacia reticulata (salacinol, kotalanol and de-O-sulfonated kotalanol) and chemically synthesized derivatives of salacinol. These studies reveal the features of the Salacia reticulata inhibitors that are essential for inhibitory activity and highlight their potential as future drug candidates. Third, the crystal structure of the N-terminal domain of SI (ntSI) was determined in apo-form and in complex with kotalanol. Structural comparison of ntSI and ntMGAM reveal key differences in active site architectures, which are proposed to confer differential substrate specificity.

This thesis examines the advantages to nonlinear least-squares (NLS) fitting of diffusion-weighted MRI data over the commonly used linear least-squares (LLS) approach. A modified fitting algorithm is proposed which accounts for the positive bias experienced in magnitude images at low SNR. For b-values in the clinical range (~1000 s/mm2), the increase in precision of FA and fibre orientation estimates is almost negligible, except at very high anisotropy. The optimal b-value for estimating tensor parameters was slightly higher for NLS. The primary advantage to NLS was improved performance at high b-values, for which complex fibre architectures were more easily resolved. This was demonstrated using a model-selection classifier based on higher-order diffusion models. Using a b-value of 3000 s/mm2 and magnitude-corrected NLS fitting, at least 10% of voxels in the brain exhibited diffusion profiles which could not be represented by the tensor model.

This dissertation provides the foundations of computer-based automated phenotyping methods for analyzing 3D images of mouse embryos. A group-wise registration technique was utilized and optimized and computerized methods were employed for analysis of 3D MRI images of mouse embryos. The assumption that embryo anatomy is highly conserved among genetically identical specimens was verified. The group-wise registration approach was used to align a group of embryos from the 129S1/SvImJ (129Sv) strain as well as a group of C57BL/6J (C57) embryos. Finally, we shed some light on some of the morphological differences between the 129Sv and C57 strains using automated techniques.

Notch signaling plays a key role in development, tissue homeostasis, and cancer. High expression levels of Notch signaling components are associated with aggressive disease and poor patient prognosis in breast cancer. Mesenchymal‐epithelial transition factor (MET) is a receptor tyrosine kinase with an established prognostic significance correlating with poor disease outcome in breast cancer patients as a result of high metastatic rate. We performed expression array analysis to identify candidate Notch target genes; we identified and validated MET as a target of NOTCH1 signaling in breast cancer. We found that NOTCH1 knockdown significantly reduces MET promoter activity, as well as expression levels of MET transcript and protein. The mechanism of NOTCH1 regulation of MET expression will be the focus of future work. To further identify candidate target genes of NOTCH1 signaling, we generated and validated a NOTCH1 antibody for use in chromatin immunoprecipitation experiments.

Notch signaling plays a key role in development, tissue homeostasis, and cancer. High expression levels of Notch signaling components are associated with aggressive disease and poor patient prognosis in breast cancer. Mesenchymal‐epithelial transition factor (MET) is a receptor tyrosine kinase with an established prognostic significance correlating with poor disease outcome in breast cancer patients as a result of high metastatic rate. We performed expression array analysis to identify candidate Notch target genes; we identified and validated MET as a target of NOTCH1 signaling in breast cancer. We found that NOTCH1 knockdown significantly reduces MET promoter activity, as well as expression levels of MET transcript and protein. The mechanism of NOTCH1 regulation of MET expression will be the focus of future work. To further identify candidate target genes of NOTCH1 signaling, we generated and validated a NOTCH1 antibody for use in chromatin immunoprecipitation experiments.

This thesis examines the advantages to nonlinear least-squares (NLS) fitting of diffusion-weighted MRI data over the commonly used linear least-squares (LLS) approach. A modified fitting algorithm is proposed which accounts for the positive bias experienced in magnitude images at low SNR. For b-values in the clinical range (~1000 s/mm2), the increase in precision of FA and fibre orientation estimates is almost negligible, except at very high anisotropy. The optimal b-value for estimating tensor parameters was slightly higher for NLS. The primary advantage to NLS was improved performance at high b-values, for which complex fibre architectures were more easily resolved. This was demonstrated using a model-selection classifier based on higher-order diffusion models. Using a b-value of 3000 s/mm2 and magnitude-corrected NLS fitting, at least 10% of voxels in the brain exhibited diffusion profiles which could not be represented by the tensor model.

This dissertation provides the foundations of computer-based automated phenotyping methods for analyzing 3D images of mouse embryos. A group-wise registration technique was utilized and optimized and computerized methods were employed for analysis of 3D MRI images of mouse embryos. The assumption that embryo anatomy is highly conserved among genetically identical specimens was verified. The group-wise registration approach was used to align a group of embryos from the 129S1/SvImJ (129Sv) strain as well as a group of C57BL/6J (C57) embryos. Finally, we shed some light on some of the morphological differences between the 129Sv and C57 strains using automated techniques.

Human maltase-glucoamylase (MGAM) and sucrase-isomaltase (SI) are the small-intestinal glucosidases responsible for catalyzing the last glucose-releasing step in starch digestion. MGAM and SI are each composed of duplicated catalytic domains, N- and C-terminal, which display complementary substrate specificities for the mixture of short linear and branch oligosaccharide substrates that typically make up terminal starch digestion products. As MGAM and SI are involved in post-prandial glucose production, regulating their activities with α-glucosidase inhibitors is an attractive approach to controlling blood glucose levels for the prevention and treatment of Type 2 diabetes. To better understand the complementary activities and mechanism of inhibition of these intestinal glucosidases, this thesis aims to characterize the individual N- and C-terminal MGAM and SI domains using a combination of X-ray crystallographic structural studies, enzyme kinetics, and inhibitor studies. First, the structure of the N-terminal domain of MGAM (ntMGAM) was determined in its apo form and in complex with the inhibitor acarbose. In addition to sequence alignments and kinetics studies, the structures provide insight into the preference of the N-terminal MGAM domain for short linear substrates and the C-terminal domain for longer substrates. Second, the structure of ntMGAM was determined in complex with various α-glucosidase inhibitors, including those currently on the market (acarbose and miglitol), a new class of inhibitors from natural extracts of Salacia reticulata (salacinol, kotalanol and de-O-sulfonated kotalanol) and chemically synthesized derivatives of salacinol. These studies reveal the features of the Salacia reticulata inhibitors that are essential for inhibitory activity and highlight their potential as future drug candidates. Third, the crystal structure of the N-terminal domain of SI (ntSI) was determined in apo-form and in complex with kotalanol. Structural comparison of ntSI and ntMGAM reveal key differences in active site architectures, which are proposed to confer differential substrate specificity.