Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Role of phosphatidylethanolamine in the function and assembly of phenylalanine-specific permease of Escherichia coli

Transmembrane segments of polytopic membrane proteins once inserted are generally considered stably oriented due to the large free energy barrier for topological reorientation of adjacent extra-membrane domains. However, proper topology and function of the polytopic membrane protein lactose permease (LacY) of Escherichia coli is dependent on the membrane phospholipid composition revealing topological dynamics of transmembrane domains (Bogdanov, M., Heacock, P. N., and Dowhan, W. (2002) EMBO J. 21, 2107–2116). The high affinity phenylalanine permease PheP shares many topological similarities with LacY. In this study, mutant E. coli cells lacking phosphatidylethanolamine (PE) as a membrane component were used to evaluate the role of PE in the function and assembly of PheP. Active transport of phenylalanine by cells lacking PE was severely inhibited (both Vmax and Km were altered), whereas the PheP protein level in membranes was unaffected. Cysteine residues were introduced into predicted periplasmic or cytoplasmic segments of cysteine-less PheP, and the topology of the protein was explored using a membrane-impermeable thiol-specific biotinylated probe. Based on the biotinylation patterns of PheP in whole cells, the N-terminus and adjoining transmembrane hairpin of PheP adopted an inverted topological orientation in PE-lacking cells. Introduction of PE following the assembly of PheP triggered a reorientation of the N-terminus and adjacent hairpin to their native orientation associated with regain of wild type transport function. These results coupled with the results for LacY support a specific role for membrane lipid composition in determining topological organization and function of membrane proteins. Several other secondary symporters are compromised for activity in PE-lacking cells suggesting that lipid-assisted topogenesis is a general property of such transporters. The reversible orientation of these secondary transport proteins in response to a change of phospholipid composition might be a result of inherent conformational flexibility necessary for transport function or during protein assembly. ^

EVALUATION OF THE EFFECTIVENESS OF ANISOTROPIC ANALYTICAL ALGORITHM IN FLATTENED AND FLATTENING-FILTER-FREE BEAMS FOR HIGH ENERGY LUNG DOSE DELIVERY USING THE RADIOLOGICAL PHYSICS CENTER LUNG PHANTOM

The effectiveness of the Anisotropic Analytical Algorithm (AAA) implemented in the Eclipse treatment planning system (TPS) was evaluated using theRadiologicalPhysicsCenteranthropomorphic lung phantom using both flattened and flattening-filter-free high energy beams. Radiation treatment plans were developed following the Radiation Therapy Oncology Group and theRadiologicalPhysicsCenterguidelines for lung treatment using Stereotactic Radiation Body Therapy. The tumor was covered such that at least 95% of Planning Target Volume (PTV) received 100% of the prescribed dose while ensuring that normal tissue constraints were followed as well. Calculated doses were exported from the Eclipse TPS and compared with the experimental data as measured using thermoluminescence detectors (TLD) and radiochromic films that were placed inside the phantom. The results demonstrate that the AAA superposition-convolution algorithm is able to calculate SBRT treatment plans with all clinically used photon beams in the range from 6 MV to 18 MV. The measured dose distribution showed a good agreement with the calculated distribution using clinically acceptable criteria of ±5% dose or 3mm distance to agreement. These results show that in a heterogeneous environment a 3D pencil beam superposition-convolution algorithms with Monte Carlo pre-calculated scatter kernels, such as AAA, are able to reliably calculate dose, accounting for increased lateral scattering due to the loss of electronic equilibrium in low density medium. The data for high energy plans (15 MV and 18 MV) showed very good tumor coverage in contrast to findings by other investigators for less sophisticated dose calculation algorithms, which demonstrated less than expected tumor doses and generally worse tumor coverage for high energy plans compared to 6MV plans. This demonstrates that the modern superposition-convolution AAA algorithm is a significant improvement over previous algorithms and is able to calculate doses accurately for SBRT treatment plans in the highly heterogeneous environment of the thorax for both lower (≤12 MV) and higher (greater than 12 MV) beam energies.