published_or_final_version / Paediatrics and Adolescent Medicine / Master / Master of Philosophy

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Human serum transferrin (hTF) is a bilobal glycoprotein that plays a central role in iron metabolism. Each lobe of hTF (N- and C-lobe) can reversibly bind a single ferric iron. Iron binds to hTF at neutral pH in the plasma; diferric hTF binds to specific hTF receptors (TFR) on the cell surface and the complex undergoes receptor mediated endocytosis. The pH within the endosome is lowered to ~5.6 and iron is released from hTF. Apo hTF remains bound to the TFR and recycles back to the cell surface. Upon fusion with the plasma membrane, apo hTF dissociates from the TFR and is free to bind more iron and continue the cycle. The iron release process is complicated by various factors which include pH, anions, a chelator, lobe-lobe cooperativity and interaction with the TFR. All of these influence iron release in a complex manner. Because they are intricately linked, it is difficult to determine the effect of any single parameter. We have utilized stopped-flow and steady-state fluorescence and urea gel electrophoresis to dissect the iron release process as a function of lobe-lobe interactions, the presence of the TFR, and changes in pH and salt concentration. Application of recombinant protein production and site-directed mutagenesis has allowed us to generate a variety of hTF constructs in which the iron status of each lobe is completely controlled. Thus, we have created authentic monoferric hTFs unable to bind iron in one lobe, diferric hTFs with iron locked in one lobe and diferric hTF in which iron can be removed from both lobes. Importantly, we have produced the soluble portion of the TFR (sTFR) to analyze interactions between hTF and the sTFR and to monitor iron release from hTF/sTFR complexes. Together, we are able to provide a more precise picture of iron release from the two lobes of hTF in the presence and absence of the TFR. Steady-state fluorescence emission scans and urea gel electrophoresis provide a qualitative evaluation of the iron status of each construct after a predetermined incubation in iron removal buffer (i.e. an endpoint). However, these techniques do not provide information regarding the kinetic pathway to reach that endpoint. Combined with stopped-flow fluorescence time-based kinetics, a more precise assessment of the iron release process has been obtained. We have determined that changes in pH and salt affect endpoint iron release from the C-lobe, but not the N-lobe, however, the kinetics of iron release from both lobes are highly sensitive to pH and salt. Kinetic analysis in the absence and presence of the sTFR reveals the complexity of the iron release process. In the absence of the sTFR, the kinetics of iron release are insensitive to the iron status of the opposite lobe. However, in the presence of the sTFR, the kinetics of iron release from both lobes are affected by the iron status of the opposite lobe. Determination of conformational changes induced by anion binding, lobe-lobe communication and sTFR interactions have now been confidently assigned. We have created kinetic models of iron release from diferric hTF ± the sTFR and incorporated specific events pertaining to anion binding, lobe-lobe communication and conformational changes associated with sTFR interactions. We provide irrefutable evidence that a critical role of the sTFR is to accelerate the rate of iron release from the C-lobe, while decreasing the rate of iron release from the N-lobe such that the two lobes effectively release iron on a time scale relevant to one cycle of endocytosis.

The thesis work contains two projects under the same umbrella. The first project is to provide a detailed analysis on the behavior of interfacial water molecules at protein-protein complexes, in this case focusing on homodimeric complexes, and to investigate their effect with respect to different residue types. For that reason the homodimeric data-set, which includes high-resolution (≤ 2.30 Å) X-ray crystal structures of 252 (140 Biological & 112 Non-biological) protein complexes was chosen to explore fundamental differences between interfaces that Nature has “engineered” vs. compared to interfaces found under man-made conditions. The data set was comprised of 5391 water molecules where a maximum of 4 Å from both interfacing proteins. Our analysis is applied a suite of modeling tools based on HINT, a program for hydropathic analysis developed in our laboratory. HINT is based on the experimental measurement of the hydrophobic effect. The second project is designed to explore various means of suppressing the expression of human genes that play critical role in HIV pathogenesis. To achieve this aim, a data set of Affymetrix Human HG Focus Target Array, which measures the expression levels of HIV seronegative and seropositive individuals in human PBMCs, was analyzed with Pathway Studio 9.0 software. This work gives insight into the elucidation of the important mechanisms of human proteins interactions in HIV seropositive individuals and their implications. Hence, we found the kind and types of microRNAs that are suppressing the human genes which have great role for HIV replication in a cell.

In this thesis we propose some new approaches to the study of complex networks, and apply them to multiple domains, focusing in particular on protein-protein interaction networks. We begin by examining the roles of individual proteins; specifically, the influential idea of 'date' and 'party' hubs. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. We show that the observations underlying this proposal appear to have been largely illusory, and that topological properties of hubs do not in general correlate with interactor co-expression, thus undermining the primary basis for the categorisation. However, we find significant correlations between interaction centrality and the functional similarity of the interacting proteins, indicating that it might be useful to conceive of roles for protein-protein interactions, as opposed to individual proteins. The observation that examining just one or a few network properties can be misleading motivates us to attempt to develop a more holistic methodology for network investigation. A wide variety of diagnostics of network structure exist, but studies typically employ only small, largely arbitrarily selected subsets of these. Here we simultaneously investigate many networks using many diagnostics in a data-driven fashion, and demonstrate how this approach serves to organise both networks and diagnostics, as well as to relate network structure to functionally relevant characteristics in a variety of settings. These include finding fast estimators for the solution of hard graph problems, discovering evolutionarily significant aspects of metabolic networks, detecting structural constraints on particular network types, and constructing summary statistics for efficient model-fitting to networks. We use the last mentioned to suggest that duplication-divergence is a feasible mechanism for protein-protein interaction evolution, and that interactions may rewire faster in yeast than in larger genomes like human and fruit fly. Our results help to illuminate protein-protein interaction networks in multiple ways, as well as providing some insight into structure-function relationships in other types of networks. We believe the methodology outlined here can serve as a general-purpose, data-driven approach to aid in the understanding of networked systems.