Functionalized carbon nanotube nanoelectrodes for biomolecular recognition

The objective of this research is to develop nanoscale ultrasensitive transducers for detection of biological species at molecular level using carbon nanotubes as nanoelectrodes. Rapid detection of ultra low concentration or even single DNA molecules are essential for medical diagnosis and treatment, pharmaceutical applications, gene sequencing as well as forensic analysis. Here the use of functionalized single walled carbon nanotubes (SWNT) as nanoscale detection platform for rapid detection of single DNA molecules is demonstrated. The detection principle is based on obtaining electrical signal from a single amine terminated DNA molecule which is covalently bridged between two ends of an SWNT separated by a nanoscale gap. The synthesis, fabrication, chemical functionalization of nanoelectrodes and DNA attachment were optimized to perform reliable electrical characterization these molecules. Using this detection system fundamental study on charge transport in DNA molecule of both genomic and non genomic sequences is performed. We measured an electrical signal of about 30 pA through a hybridized DNA molecule of 80 base pair in length which encodes a portion of sequence of H5N1 gene of avian Influenza A virus. Due the dynamic nature of the DNA molecules the local environment such as ion concentration, pH and temperature significantly influence its physical properties. We observed a decrease in DNA conductance of about 33% in high vacuum conditions. The counterion variation was analyzed by changing the buffer from sodium acetate to tris(hydroxymethyl) aminomethane, which resulted in a two orders of magnitude increase in the conductivity of the DNA. The fabrication of large array of identical SWNT nanoelectrodes was achieved by using ultralong SWNTs. Using these nanoelectrode array we have investigated the sequence dependent charge transport in DNA. A systematic study performed on PolyG - PolyC sequence with varying number of intervening PolyA - PolyT pairs showed a decrease in electrical signal from 180 pA (PolyG - PolyC) to 30 pA with increasing number of the PolyA - PolyT pairs. This work also led to the development of ultrasensitive nanoelectrodes based on enzyme functionalized vertically aligned high density multiwalled CNTs for electrochemical detection of cholesterol. The nanoelectrodes exhibited selectively detection of cholesterol in the presence of common interferents found in human blood.

The potential role of environmental exposures and genomic signaling in development of central nervous system tumors

The etiology of central nervous system tumors (CNSTs) is mainly unknown. Aside from extremely rare genetic conditions, such as neurofibromatosis and tuberous sclerosis, the only unequivocally identified risk factor is exposure to ionizing radiation, and this explains only a very small fraction of cases. Using meta-analysis, gene networking and bioinformatics methods, this dissertation explored the hypothesis that environmental exposures produce genetic and epigenetic alterations that may be involved in the etiology of CNSTs. A meta-analysis of epidemiological studies of pesticides and pediatric brain tumors revealed a significantly increased risk of brain tumors among children whose mothers had farm-related exposures during pregnancy. A dose response was recognized when this risk estimate was compared to those for risk of brain tumors from maternal exposure to non-agricultural pesticides during pregnancy, and risk of brain tumors among children exposed to agricultural activities. Through meta-analysis of several microarray studies which compared normal tissue to astrocytomas, we were able to identify a list of 554 genes which were differentially expressed in the majority of astrocytomas. Many of these genes have in fact been implicated in development of astrocytoma, including EGFR, HIF-1α, c-Myc, WNT5A, and IDH3A. Reverse engineering of these 554 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme (GBM) were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. Lastly, bioinformatics analysis of environmental databases and curated published results on GBM was able to identify numerous potential pathways and geneenvironment interactions that may play key roles in astrocytoma development. Findings from this research have strong potential to advance our understanding of the etiology and susceptibility to CNSTs. Validation of our ‘key genes’ and pathways could potentially lead to useful tools for early detection and novel therapeutic options for these tumors.