Bioinformatic analysis for exploring relationships between genes and gene products

To carry out their specific roles in the cell, genes and gene products often work together in groups, forming many relationships among themselves and with other molecules. Such relationships include physical protein-protein interaction relationships, regulatory relationships, metabolic relationships, genetic relationships, and much more. With advances in science and technology, some high throughput technologies have been developed to simultaneously detect tens of thousands of pairwise protein-protein interactions and protein-DNA interactions. However, the data generated by high throughput methods are prone to noise. Furthermore, the technology itself has its limitations, and cannot detect all kinds of relationships between genes and their products. Thus there is a pressing need to investigate all kinds of relationships and their roles in a living system using bioinformatic approaches, and is a central challenge in Computational Biology and Systems Biology. This dissertation focuses on exploring relationships between genes and gene products using bioinformatic approaches. Specifically, we consider problems related to regulatory relationships, protein-protein interactions, and semantic relationships between genes. A regulatory element is an important pattern or "signal", often located in the promoter of a gene, which is used in the process of turning a gene "on" or "off". Predicting regulatory elements is a key step in exploring the regulatory relationships between genes and gene products. In this dissertation, we consider the problem of improving the prediction of regulatory elements by using comparative genomics data. With regard to protein-protein interactions, we have developed bioinformatics techniques to estimate support for the data on these interactions. While protein-protein interactions and regulatory relationships can be detected by high throughput biological techniques, there is another type of relationship called semantic relationship that cannot be detected by a single technique, but can be inferred using multiple sources of biological data. The contributions of this thesis involved the development and application of a set of bioinformatic approaches that address the challenges mentioned above. These included (i) an EM-based algorithm that improves the prediction of regulatory elements using comparative genomics data, (ii) an approach for estimating the support of protein-protein interaction data, with application to functional annotation of genes, (iii) a novel method for inferring functional network of genes, and (iv) techniques for clustering genes using multi-source data.

Multimode Analysis of Nanoscale Biomolecular Interactions

Biomolecular interactions, including protein-protein, protein-DNA, and protein-ligand interactions, are of special importance in all biological systems. These interactions may occer during the loading of biomolecules to interfaces, the translocation of biomolecules through transmembrane protein pores, and the movement of biomolecules in a crowded intracellular environment. The molecular interaction of a protein with its binding partners is crucial in fundamental biological processes such as electron transfer, intracellular signal transmission and regulation, neuroprotective mechanisms, and regulation of DNA topology. In this dissertation, a customized surface plasmon resonance (SPR) has been optimized and new theoretical and label free experimental methods with related analytical calculations have been developed for the analysis of biomolecular interactions. Human neuroglobin (hNgb) and cytochrome c from equine heart (Cyt c) proteins have been used to optimize the customized SPR instrument. The obtained Kd value (~13 µM), from SPR results, for Cyt c-hNgb molecular interactions is in general agreement with a previously published result. The SPR results also confirmed no significant impact of the internal disulfide bridge between Cys 46 and Cys 55 on hNgb binding to Cyt c. Using SPR, E. coli topoisomerase I enzyme turnover during plasmid DNA relaxation was found to be enhanced in the presence of Mg2+. In addition, a new theoretical approach of analyzing biphasic SPR data has been introduced based on analytical solutions of the biphasic rate equations. In order to develop a new label free method to quantitatively study protein-protein interactions, quartz nanopipettes were chemically modified. The derived Kd (~20 µM) value for the Cyt c-hNgb complex formations matched very well with SPR measurements (Kd ~16 µM). The finite element numerical simulation results were similar to the nanopipette experimental results. These results demonstrate that nanopipettes can potentially be used as a new class of a label-free analytical method to quantitatively characterize protein-protein interactions in attoliter sensing volumes, based on a charge sensing mechanism. Moreover, the molecule-based selective nature of hydrophobic and nanometer sized carbon nanotube (CNT) pores was observed. This result might be helpful to understand the selective nature of cellular transport through transmembrane protein pores.

The construction and optimization of a surface plasmon resonance sensor for the studies of bio-molecular interactions

Bio-molecular interactions exist ubiquitously in all biological systems. This dissertation project was to construct a powerful surface plasmon resonance (SPR) sensor. The SPR system is used to study bio-molecular interactions in real time and without labeling. Surface plasmon is the oscillation of free electrons in metals coupled with surface electromagnetic waves. These surface electromagnetic waves provide a sensitive probe to study bio-molecular interactions on metal surfaces. This project resulted in the successful construction and optimization of a homemade SPR sensor and the development of several new powerful protocols to study bio-molecular interactions. It was discovered through this project that the limitations of earlier SPR sensors are related not only to the instrumentation design and operating procedures, but also to the complex behaviors of bio-molecules on sensor surfaces that were very different from that in solution. Based on these discoveries the instrumentation design and operating procedures were fully optimized. A set of existing sensor surface treatment protocols were tested and evaluated and new protocols were developed in this project. The new protocols have demonstrated excellent performance to study biomolecular interactions. The optimized home-made SPR sensor was used to study protein-surface interactions. These protein-surface interactions are responsible for many complex organic cell activities. The co-existence of different driving forces and their correlation with the structure of the protein and the surface make the understanding of the fundamental mechanism of protein-surface interactions a very challenging task. Using the improved SPR sensor, the electrostatic interaction and hydrophobic interaction were studied separately. The results of this project directly confirmed the theoretical predictions for electrostatic force between the protein and surface. In addition, this project demonstrated that the strength of the protein-surface hydrophobic interaction does not solely depend on the hydrophobicity as reported earlier. Surface structure also plays a significant role.

Pressure induced structural changes and gas diffusion pathways in monomeric fluorescent proteins

Fluorescent proteins (FPs) are extremely valuable biochemical markers which have found a wide range of applications in cellular and molecular biology research. The monomeric variants of red fluorescent proteins (RFPs), known as mFruits, have been especially valuable for in vivo applications in mammalian cell imaging. Fluorescent proteins consist of a chromophore caged in the beta-barrel protein scaffold. The photophysical properties of an FP is determined by its chromophore structure and its interactions with the protein barrel. Application of hydrostatic pressure on FPs results in the modification of the chromophore environment which allows a systematic study of the role of the protein-chromophore interactions on photophysical properties of FPs. Using Molecular Dynamics (MD) computer simulations, I investigated the pressure induced structural changes in the monomeric variants mCherry, mStrawberry, and Citrine. The results explain the molecular basis for experimentally observed pressure responses among FP variants. It is found that the barrel flexibility, hydrogen bonding interactions and chromophore planarity of the FPs can be correlated to their contrasting photophysical properties at vaious pressures. I also investigated the oxygen diffusion pathways in mOrange and mOrange2 which exhibit marked differences in oxygen sensitivities as well as photostability. Such computational identifications of structural changes and oxygen diffusion pathways are important in guiding mutagenesis efforts to design fluorescent proteins with improved photophysical properties.

Pressure Induced Structural Changes and Gas Diffusion Pathways in Monomeric Fluorescent Proteins

Fluorescent proteins (FPs) are extremely valuable biochemical markers which have found a wide range of applications in cellular and molecular biology research. The monomeric variants of red fluorescent proteins (RFPs), known as mFruits, have been especially valuable for in vivo applications in mammalian cell imaging. Fluorescent proteins consist of a chromophore caged in the beta-barrel protein scaffold. The photophysical properties of an FP is determined by its chromophore structure and its interactions with the protein barrel. Application of hydrostatic pressure on FPs results in the modification of the chromophore environment which allows a systematic study of the role of the protein-chromophore interactions on photophysical properties of FPs. Using Molecular Dynamics (MD) computer simulations, I investigated the pressure induced structural changes in the monomeric variants mCherry, mStrawberry, and Citrine. The results explain the molecular basis for experimentally observed pressure responses among FP variants. It is found that the barrel flexibility, hydrogen bonding interactions and chromophore planarity of the FPs can be correlated to their contrasting photophysical properties at vaious pressures. I also investigated the oxygen diffusion pathways in mOrange and mOrange2 which exhibit marked differences in oxygen sensitivities as well as photostability. Such computational identifications of structural changes and oxygen diffusion pathways are important in guiding mutagenesis efforts to design fluorescent proteins with improved photophysical properties.

Specific binding of the mammalian high mobility group protein AT-hook 2 to the minor groove of AT -rich DNAs: Thermodynamic and specificity studies

The mammalian high mobility group protein AT-hook 2 (HMGA2) is a small transcriptional factor involved in cell development and oncogenesis. It contains three "AT-hook" DNA binding domains, which specifically recognize the minor groove of AT-rich DNA sequences. It also has an acidic C-terminal motif. Previous studies showed that HMGA2 mediates all its biological effects through interactions with AT-rich DNA sequences in the promoter regions. In this dissertation, I used a variety of biochemical and biophysical methods to examine the physical properties of HMGA2 and to further investigate HMGA2's interactions with AT-rich DNA sequences. The following are three avenues perused in this study: (1) due to the asymmetrical charge distribution of HMGA2, I have developed a rapid procedure to purify HMGA2 in the milligram range. Preparation of large amounts of HMGA2 makes biophysical studies possible; (2) Since HMGA2 binds to different AT-rich sequences in the promoter regions, I used a combination of isothermal titration calorimetry (ITC) and DNA UV melting experiment to characterize interactions of HMGA2 with poly(dA-dT) 2 and poly(dA)poly(dT). My results demonstrated that (i) each HMGA2 molecule binds to 15 AT bp; (ii) HMGA2 binds to both AT DNAs with very high affinity. However, the binding reaction of HMGA2 to poly(dA-dT) 2 is enthalpy-driven and the binding reaction of HMGA2 with poly(dA)poly(dT) is entropy-driven; (iii) the binding reactions are strongly depended on salt concentrations; (3) Previous studies showed that HMGA2 may have sequence specificity. In this study, I used a PCR-based SELEX procedure to examine the DNA binding specificity of HMGA2. Two consensus sequences for HMGA2 have been identified: 5'-ATATTCGCGAWWATT-3' and 5'-ATATTGCGCAWWATT-3', where W represents A or T. These consensus sequences have a unique feature: the first five base pairs are AT-rich, the middle four to five base pairs are GC-rich, and the last five to six base pairs are AT-rich. All three segments are critical for high affinity binding. Replacing either one of the AT-rich sequences to a non-AT-rich sequence causes at least 100-fold decrease in the binding affinity. Intriguingly, if the GC-segment is substituted by an AT-rich segment, the binding affinity of HMGA2 is reduced approximately 5-fold. Identification of the consensus sequences for HMGA2 represents an important step towards finding its binding sites within the genome.

A Rapid and Sensitive High-Throughput Screening Method to Identify Compounds Targeting Protein–Nucleic Acids Interactions

DNA-binding and RNA-binding proteins are usually considered ‘undruggable’ partly due to the lack of an efficient method to identify inhibitors from existing small molecule repositories. Here we report a rapid and sensitive high-throughput screening approach to identify compounds targeting protein–nucleic acids interactions based on protein–DNA or protein–RNA interaction enzyme-linked immunosorbent assays (PDI-ELISA or PRI-ELISA). We validated the PDI-ELISA method using the mammalian highmobility- group protein AT-hook 2 (HMGA2) as the protein of interest and netropsin as the inhibitor of HMGA2–DNA interactions. With this method we successfully identified several inhibitors and an activator for HMGA2–DNA interactions from a collection of 29 DNA-binding compounds. Guided by this screening excise, we showed that netropsin, the specific inhibitor of HMGA2–DNA interactions, strongly inhibited the differentiation of the mouse pre-adipocyte 3T3-L1 cells into adipocytes, most likely through a mechanism by which the inhibition is through preventing the binding of HMGA2 to the target DNA sequences. This method should be broadly applicable to identify compounds or proteins modulating many DNA-binding or RNA-binding proteins.