Translational Oncogenomics and Human Cancer Interactome Networks

An overview of translational, human oncogenomics, transcriptomics and cancer interactomic networks is presented together with basic concepts and potential, new applications to Oncology and Integrative Cancer Biology. Novel translational oncogenomics research is rapidly expanding through the application of advanced technology, research findings and computational tools/models to both pharmaceutical and clinical problems. A self-contained presentation is adopted that covers both fundamental concepts and the most recent biomedical, as well as clinical, applications. Sample analyses in recent clinical studies have shown that gene expression data can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies or, in general, ‘personalized medicine’. Several cancer detection techniques are currently under development both in the direction of improved detection sensitivity and increased time resolution of cellular events, with the limits of single molecule detection and picosecond time resolution already reached. The urgency for the complete mapping of a human cancer interactome with the help of such novel, high-efficiency / low-cost and ultra-sensitive techniques is also pointed out

High-throughput isolation and characterization of untagged membrane protein complexes: outer membrane complexes of Desulfovibrio vulgaris.

Cell membranes represent the "front line" of cellular defense and the interface between a cell and its environment. To determine the range of proteins and protein complexes that are present in the cell membranes of a target organism, we have utilized a "tagless" process for the system-wide isolation and identification of native membrane protein complexes. As an initial subject for study, we have chosen the Gram-negative sulfate-reducing bacterium Desulfovibrio vulgaris. With this tagless methodology, we have identified about two-thirds of the outer membrane- associated proteins anticipated. Approximately three-fourths of these appear to form homomeric complexes. Statistical and machine-learning methods used to analyze data compiled over multiple experiments revealed networks of additional protein-protein interactions providing insight into heteromeric contacts made between proteins across this region of the cell. Taken together, these results establish a D. vulgaris outer membrane protein data set that will be essential for the detection and characterization of environment-driven changes in the outer membrane proteome and in the modeling of stress response pathways. The workflow utilized here should be effective for the global characterization of membrane protein complexes in a wide range of organisms

Understanding The Intra And Inter-Cellular Interaction Complexities And Flexibilities Using Systems And Sequence Analysis Approach

The present thesis work has been undertaken to gain an understanding of intra-cellular or inter-cellular interactions between bio-molecular entities utilizing either a systems analysis based perspective or different sequence analysis approaches. During this study different principles likely to be prevalent among intra-cellular and inter-cellular interactions have been studied with the help of computational approaches. Broadly, the complexities in intra-cellular interactions have been studied by determining the effect of perturbations such as over-expression or down-regulation of a key regulator on the intra-cellular interaction network architecture or its components. In particular, network analysis of regulatory network proteins in association with the intra-cellular proteinprotein interaction network, led to a key observation that topologically important effector proteins in the regulatory network could be important signaling proteins. Identification of such important effector proteins essential for the regulatory network integrity of a key regulator may be performed by network analysis. It is likely that alterations in these important effector proteins may lead to disruptions in cellular physiology and as such in this manner probable disease associated entities can be determined. Alternately, the flexibility among protein-protein interactions has been studied by analyzing homologous sequence families of interacting proteins with the help of information theory based measures like mutual information and Bhattacharyya co-efficient. Since interacting proteins may co-evolve, co-variation may allow the preservation of a functional interaction between co-evolving proteins and interdependent residue pair alterations may occur as a result of evolutionary pressure. Analysis of molecular co-evolution in inter-cellular protein interaction complexes determined that co-evolutionary pairings may be present among interface and noninterface residue pairs and such positions are likely to be crucial for a functional interaction between these sets of proteins. Therefore, utilising information contained in biological sequences, co-evolutionary pairings involving structurally or functionally crucial residue positions in disease associated inter-cellular protein-protein interaction complexes were predicted. Thus, different computational approaches have been utilised to study a particular hypothesis in a disease scenario in order to delineate certain themes prevalent in intra-cellular or inter-cellular interactions among bio-molecular entities while predicting disease associated entities or studying interaction patterns among them

Nanobody-Based Interactomic Studies of Single Transcripts During mRNA Maturation

During and after transcription in the nucleus, messenger RNAs (mRNAs) undergo a variety of processing events before being exported to the cytoplasm through the nuclear pore complex. mRNA processing and nuclear export require a wide range of protein factors, which interact with maturing transcripts and each other to form dynamic mRNP complexes. While there are many core, essential mRNP factors, the pathways governing mRNA maturation are not uniform, and different transcripts can be associated with mRNP complexes of dramatically different composition or kinetics. To date though, it has been difficult to study RNP complexes specific to any single mRNA species, as each transcript is relatively unabundant in the cell, and few robust techniques exist to specifically purify a particular mRNP for proteomic analysis. We thus sought to develop a method to isolate mRNPs from a single transcript, allowing us to study the dynamic RNP compositions of individual mRNA maturation pathways. To optimize purifications of the protein tags required for RNP isolations, we first generated high affinity reagents targeting key tags like GFP and mCherry. Instead of traditional antibodies, we chose to use nanobodies: recombinant single domain derivatives of a heavy chain-only antibody variant found in camelids. The recombinant nature and small size of nanobodies make them ideal reagents for affinity isolations. We developed an improved pipeline for the identification of nanobody repertoires against any antigen of interest, which provided us with 25 nanobodies against GFP, the most common and robust protein tag in use. This pipeline has also allowed us to develop nanobodies against a variety of other antigens of biomedical interest. With the help of optimized reagents, we developed a two-step purification method allowing highly targeted isolations of mRNPs, starting in a budding yeast model system. In our approach, a single target transcript is tagged with MS2 hairpin sequences – these hairpins are bound specifically and with high affinity by the bacteriophage MS2 coat protein (MS2CP). In the first purification step, a chosen RNP protein known to be associated with a particular mRNA processing step of interest is Protein A-tagged and affinity isolated. From this material, anti-GFP nanobodies are used in the second step to isolate the MS2-tagged transcript of interest, through purification of MS2CP-GFP fusion proteins bound to the tag. This approach is able to efficiently and cleanly isolate a particular transcript at a chosen step of mRNP maturation. The use of an RNP factor as a separate purification target both improves overall purity and simplifies analysis by limiting heterogeneity of the mRNP mixture. Using this novel method for single mRNP isolations, we have performed a preliminary survey of transcripts with distinct sequence elements suspected to be associated with unique processing machinery. Mass spectrometric (MS) analysis of RNPs co-purified with these transcripts revealed several RNA-specific changes in composition. Most notably, introns from either a house keeping ACT1 gene or the RPS30b ribosomal protein gene led to dramatically different levels of various splicing-related proteins. These differences provide mechanistic insight into changes in the kinetics of spliceosome assembly determined by intron sequence

Fluorescent labeling of DNA : strategies, pitfalls and necessity for fluorescence microscopy investigations of gene therapy

Gene therapy is a field of research in which a huge amount of effort has been spent over the last two decades. To succeed, a correct therapeutic gene needs to be delivered into the cytoplasm of a cell for mRNA and nucleus of a cell for plasmid DNA (pDNA). To protect the nucleic acids, viral vectors and non-viral carriers have been used. Due to the many barriers that are encountered in the delivery, the design and evaluation of especially the non-viral vectors has room for improvement. To this end, fluorescence microscopy has proven to be a useful tool. In this thesis, the main goal was to study the degradation of pDNA with advanced microscopy. Since fluorescence microscopy requires a fluorescent tag on the molecules of interest, an overview of the possible nucleic acid labeling strategies was given. Attention was given to the effect the methods have on the intracellular processing. This is studied in detail for a frequently used random covalent labeling method. When using Lipofectamine, the transfection efficiency drops for high labeling densities, probably due to an increased hydrophobicity which causes a higher affinity for lipid structures and steric hindrance of the labels for transcriptional proteins. Alternative pDNA labeling strategies were also explored. Fluorescence correlation spectroscopy (FCS) and single particle tracking (SPT) were evaluated for their ability to follow pDNA degradation. SPT could measure the degradation of pDNA in cell lysate after lipofection. Finally, the gene delivery potential of 3 polycationic amphiphilic β-cyclodextrins (CDs) was tested for pDNA and mRNA. Due to a lower cellular uptake, no transfection could be induced in the presence of serum. It was seen that the interactions of CDs with cellular cholesterol are likely blocked by the serum proteins. In conclusion, we have shown that the correct use of microscopy methods, and especially SPT, is valuable in the study and evaluation of barriers for non-viral nucleic acid carriers