Nanogenomics and Nanoproteomics Enabling Personalized, Predictive and Preventive Medicine

Since the discovery of the nucleic acid, molecular biology has made tremendous progresses, achieving a lot of results. Despite this, there is still a gap between the classical and traditional medical approach and the molecular world. Inspired by the incredible wealth of data generated by the "omics"-driven techniques and the “high-trouhgput technologies” (HTTs), I have tried to develop a protocol that could reduce the actually extant barrier between the phenomenological medicine and the molecular medicine, facilitating a translational shift from the lab to the patient bedside. I also felt the urgent need to integrate the most important omics sciences, that is to say genomics and proteomics. Nucleic Acid Programmable Protein Arrays (NAPPA) can do this, by utilizing a complex mammalian cell free expression system to produce proteins in situ. In alternative to fluorescent-labeled approaches a new label free method, emerging from the combined utilization of three independent and complementary nanobiotechnological approaches, appears capable to analyze gene and protein function, gene-protein, gene-drug, protein-protein and protein-drug interactions in studies promising for personalized medicine. Quartz Micro Circuit nanogravimetry (QCM), based on frequency and dissipation factor, mass spectrometry (MS) and anodic porous alumina (APA) overcomes indeed the limits of correlated fluorescence detection plagued by the background still present after extensive washes. Work is in progress to further optimize this approach a homogeneous and well defined bacterial cell free expression system able to realize the ambitious objective to quantify the regulatory gene and protein networks in humans. Implications for personalized medicine of the above label free protein array using different test genes and proteins are reported in this PhD thesis

Physics of epigenetic landscapes and statistical inference by cells

Biology is currently in the midst of a revolution. Great technological advances have led to unprecedented quantitative data at the whole genome level. However, new techniques are needed to deal with this deluge of high-dimensional data. Therefore, statistical physics has the potential to help develop systems biology level models that can incorporate complex data. Additionally, physicists have made great strides in understanding non-equilibrium thermodynamics. However, the consequences of these advances have yet to be fully incorporated into biology. There are three specific problems that I address in my dissertation. First, a common metaphor for describing development is a rugged "epigenetic landscape" where cell fates are represented as attracting valleys resulting from a complex regulatory network. I introduce a framework for explicitly constructing epigenetic landscapes that combines genomic data with techniques from spin-glass physics. The model reproduces known reprogramming protocols and identifies candidate transcription factors for reprogramming to novel cell fates, suggesting epigenetic landscapes are a powerful paradigm for understanding cellular identity. Second, I examine the dynamics of cellular reprogramming. By reanalyzing all available time-series data, I show that gene expression dynamics during reprogramming follow a simple one-dimensional reaction coordinate that is independent of both the time and details of experimental protocol used. I show that such a reaction coordinate emerges naturally from epigenetic landscape models of cell identity where cellular reprogramming is viewed as a "barrier-crossing" between the starting and ending cell fates. Overall, the analysis and model suggest that gene expression dynamics during reprogramming follow a canonical trajectory consistent with the idea of an "optimal path"' in gene expression space for reprogramming. Third, an important task of cells is to perform complex computations in response to external signals. Intricate networks are required to sense and process signals, and since cells are inherently non-equilibrium systems, these networks naturally consume energy. Since there is a deep connection between thermodynamics, computation, and information, a natural question is what constraints does thermodynamics place on statistical estimation and learning. I modeled a single chemical receptor and established the first fundamental relationship between the energy consumption and statistical accuracy of a receptor in a cell

High-throughput genetic analysis and combinatorial chiral separations based on capillary electrophoresis

Capillary electrophoresis offers many advantages over conventional analytical methods, such as speed, simplicity, high resolution, low cost, and small sample consumption, especially for the separation of enantiomers. However, chiral method developments still can be time consuming and tedious. We designed a comprehensive enantioseparation protocol employing neutral and sulfated cyclodextrins as chiral selectors for common basic, neutral, and acidic compounds with a 96-capillary array system. By using only four judiciously chosen separation buffers, successful enantioseparations were achieved for 49 out of 54 test compounds spanning a large variety of pKs and structures. Therefore, unknown compounds can be screened in this manner to identify optimal enantioselective conditions in just one run. In addition to superior separation efficiency for small molecules, CE is also the most powerful technique for DNA separations. Using the same multiplexed capillary system with UV absorption detection, DNA sequencing of a short template was done without any dye-labels. Two internal standards were utilized to adjust the migration time variations among capillaries, so that the four electropherograms for the A, T, C, G Sanger reactions can be aligned and base calling can be completed with a level of high confidence. The CE separation of DNA can be applied to study differential gene expression as well. Combined with pattern recognition techniques, small variations among electropherograms obtained by the separation of cDNA fragments produced from the total RNA samples of different human tissues can be revealed. These variations reflect the differences in total RNA expression among tissues. Thus, this CE-based approach can serve as an alternative to the DNA array techniques in gene expression analysis

Principle and Development of Phage-Based Biosensors

Detection and identification of pathogenic bacteria is important in the field of public health, medicine, food safety, environmental monitoring and security. Worldwide, the common cause of mortality and morbidity is bacterial infection often due to misdiagnosis or delay in diagnosis. Existing bacterial detection methods rely on conventional culture or microscopic techniques and molecular methods that often time consuming, laborious and expensive, or need trained users. In recent years, biosensor remained an interesting topic for bacterial detection and many biosensors involving different bio-probes have been reported. Compared to antibodies, nucleic acids and enzymes etc., based biosensors, bacteriophages can be cheaply produced and are relatively much stable to elevated temperature, extreme pH, and diverse ionic strength. Therefore, there is an urgent need for phage-based biosensor for bacterial pathogen detection. Furthermore, bearing high affinity and specificity, bacteriophages are perfect bio-recognition probes in biosensor development for bacterial detection. In this regard, active and oriented phages immobilization is the key step toward phage-based biosensor development. This chapter compares different bacterial detection techniques, and introduces the basic of biosensor and different bio-probes involved in biosensor development. Further we highlight the involvement and importance of phages in biosensor and finally we briefed different phage immobilization approaches used in development of phage-based biosensors

Immobilisation of DNA using the fluorous effect

Reversible biomolecule attachment onto solid supports is of importance to many distinct research fields ranging from microarray development to the synthesis of metamaterials. One method used to immobilised biomolecules in a reversible fashion relies on non-covalent fluorous-fluorous interactions. The primary focus of this thesis was to investigate the immobilisation characteristics of DNA, tagged with a range of perfluorinated carbon chains, onto fluorinated solid supports. This work showed that the fluorous effect could be used to immobilise single stranded DNA onto patterned arrays permitting hybridisation to its complementary sequence. This duplex could then be removed via the fluorous tag, completely regenerating the surface and allowing for the immobilisation procedure to be repeated. This was then built upon by varying the fluorine content of the fluorinated carbon chain, allowing for comparison to be made between the fluorine content of the tag and the stringency of the washes required to remove the duplex from the surface. It was further noted that the effect of the linker group had a significant impact on the immobilisation densities of the DNA strands, with longer linkers showing higher hybridisation densities. Finally, DNA strands modified with fluorinated carbon chains were incorporated into DNA nanostructures. It was found that the inclusion of fluorous tags had a profound effect on the facial immobilisation orientation of the DNA nanostructures onto mica. It was found that the inclusion of one per fluorinated tag influenced the face on which the nanostructures were immobilised, with around 80 % of the structures immobilising on the face opposite to that modified with a fluorous tag. Therefore, it is thought that this work has potential application in reusable microarray development and as a means to control the deposition of nanostructures onto solids supports to aid in bottom-up self-assembly

Genome-wide temporal-spatial gene expression profiling of drought responsiveness in rice

<p>Abstract</p> <p>Background</p> <p>Rice is highly sensitive to drought, and the effect of drought may vary with the different genotypes and development stages. Genome-wide gene expression profiling was used as the initial point to dissect molecular genetic mechanism of this complex trait and provide valuable information for the improvement of drought tolerance in rice. Affymetrix rice genome array containing 48,564 <it>japonica </it>and 1,260 <it>indica </it>sequences was used to analyze the gene expression pattern of rice exposed to drought stress. The transcriptome from leaf, root, and young panicle at three developmental stages was comparatively analyzed combined with bioinformatics exploring drought stress related <it>cis</it>-elements.</p> <p>Results</p> <p>There were 5,284 genes detected to be differentially expressed under drought stress. Most of these genes were tissue- or stage-specific regulated by drought. The tissue-specific down-regulated genes showed distinct function categories as photosynthesis-related genes prevalent in leaf, and the genes involved in cell membrane biogenesis and cell wall modification over-presented in root and young panicle. In a drought environment, several genes, such as <it>GA2ox, SAP15</it>, and <it>Chitinase III</it>, were regulated in a reciprocal way in two tissues at the same development stage. A total of 261 transcription factor genes were detected to be differentially regulated by drought stress. Most of them were also regulated in a tissue- or stage-specific manner. A <it>cis</it>-element containing special CGCG box was identified to over-present in the upstream of 55 common induced genes, and it may be very important for rice plants responding to drought environment.</p> <p>Conclusions</p> <p>Genome-wide gene expression profiling revealed that most of the drought differentially expressed genes (DEGs) were under temporal and spatial regulation, suggesting a crosstalk between various development cues and environmental stimuli. The identification of the differentially regulated DEGs, including TF genes and unique candidate <it>cis</it>-element for drought responsiveness, is a very useful resource for the functional dissection of the molecular mechanism in rice responding to environment stress.</p