Dominic Suciu

DETECTION OF CANCER WITH SERUM MIRNAS ON AN OLIGONUCLEOTIDE MICROARRAY

Micro RNAs (miRNAs) are a class of small, non-coding RNA species that play critical roles throughout cellular development and regulation. miRNA expression patterns taken from various tissue types often point to the cellular lineage of an individual tissue type, thereby being a more invariant hallmark of tissue type. Recent work has shown that these miRNA expression patterns can be used to classify tumor cells, and that this classification can be more accurate than the classification achieved by using messenger RNA gene expression patterns. One aspect of miRNA biogenesis that makes them particularly attractive as a biomarker is the fact that they are maintained in a protected state in serum and plasma, thus allowing the detection of miRNA expression patterns directly from serum. This study is focused on the evaluation of miRNA expression patterns in human serum for five types of human cancer, prostate, colon, ovarian, breast and lung, using a pan-human microRNA, high density microarray. This microarray platform enables the simultaneous analysis of all human microRNAs by either fluorescent or electrochemical signals, and can be easily redesigned to include newly identified miRNAs. We show that sufficient miRNAs are present in one milliliter of serum to detect miRNA expression patterns, without the need for amplification techniques. In addition, we are able to use these expression patterns to correctly discriminate between normal and cancer patient samples.

Identification of Upper Respiratory Tract Pathogens Using Electrochemical Detection on an Oligonucleotide Microarray

Bacterial and viral upper respiratory infections (URI) produce highly variable clinical symptoms that cannot be used to identify the etiologic agent. Proper treatment, however, depends on correct identification of the pathogen involved as antibiotics provide little or no benefit with viral infections. Here we describe a rapid and sensitive genotyping assay and microarray for URI identification using standard amplification and hybridization techniques, with electrochemical detection (ECD) on a semiconductor-based oligonucleotide microarray. The assay was developed to detect four bacterial pathogens (Bordetella pertussis, Streptococcus pyogenes, Chlamydia pneumoniae and Mycoplasma pneumoniae) and 9 viral pathogens (adenovirus 4, coronavirus OC43, 229E and HK, influenza A and B, parainfluinza types 1, 2, and 3 and respiratory syncytial virus. This new platform forms the basis for a fully automated diagnostics system that is very flexible and can be customized to suit different or additional pathogens. Multiple probes on a flexible platform allow one to test probes empirically and then select highly reactive probes for further iterative evaluation. Because ECD uses an enzymatic reaction to create electrical signals that can be read directly from the array, there is no need for image analysis or for expensive and delicate optical scanning equipment. We show assay sensitivity and specificity that are excellent for a multiplexed format.

Use of Semiconductor-Based Oligonucleotide Microarrays for Influenza A Virus Subtype Identification and Sequencing

ABSTRACT In the face of concerns over an influenza pandemic, identification of virulent influenza A virus isolates must be obtained quickly for effective responses. Rapid subtype identification, however, is difficult even in well-equipped virology laboratories or is unobtainable in the field under more austere conditions. Here we describe a genome assay and microarray design that can be used to rapidly identify influenza A virus hemagglutinin subtypes 1 through 15 and neuraminidase subtypes 1 through 9. Also described is an array-based enzymatic assay that can be used to sequence portions of both genes or any other sequence of interest.

Seasonal changes in bacterial and archaeal gene expression patterns across salinity gradients in the Columbia River coastal margin

Through their metabolic activities, microbial populations mediate the impact of high gradient regions on ecological function and productivity of the highly dynamic Columbia River coastal margin (CRCM). A 2226-probe oligonucleotide DNA microarray was developed to investigate expression patterns for microbial genes involved in nitrogen and carbon metabolism in the CRCM. Initial experiments with the environmental microarrays were directed toward validation of the platform and yielded high reproducibility in multiple tests. Bioinformatic and experimental validation also indicated that >85% of the microarray probes were specific for their corresponding target genes and for a few homologs within the same microbial family. The validated probe set was used to query gene expression responses by microbial assemblages to environmental variability. Sixty-four samples from the river, estuary, plume, and adjacent ocean were collected in different seasons and analyzed to correlate the measured variability in chemical, physical and biological water parameters to differences in global gene expression profiles. The method produced robust seasonal profiles corresponding to pre-freshet spring (April) and late summer (August). Overall relative gene expression was high in both seasons and was consistent with high microbial abundance measured by total RNA, heterotrophic bacterial production, and chlorophyll a. Both seasonal patterns involved large numbers of genes that were highly expressed relative to background, yet each produced very different gene expression profiles. April patterns revealed high differential gene expression in the coastal margin samples (estuary, plume and adjacent ocean) relative to freshwater, while little differential gene expression was observed along the river-to-ocean transition in August. Microbial gene expression profiles appeared to relate, in part, to seasonal differences in nutrient availability and potential resource competition. Furthermore, our results suggest that highly-active particle-attached microbiota in the Columbia River water column may perform dissimilatory nitrate reduction (both dentrification and DNRA) within anoxic particle microniches.

Integrated Microfluidic CustomArray Device for Bacterial Genotyping and Identification

The ongoing threat of the potential use of biothreat agents (such as Bacillus anthracis) as a biochemical weapon emphasizes the need for a rapid, miniature, fully automated, and highly specific detection assay. An integrated and self-contained microfluidic device has been developed to rapidly detect B. anthracis and many other bacteria. The device consists of a semiconductor-based DNA microarray chip with 12,000 features and a microfluidic cartridge that automates the fluid handling steps required to carry out a genotyping assay for pathogen identification. This fully integrated and disposable device consists of low-cost microfluidic pumps, mixers, valves, fluid channels, reagent storage chambers, and DNA microarray silicon chip. Microarray hybridization and subsequent fluid handling and reactions were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. The genotyping results showed that the device was able to identify and distinguish B. anthracis from the other members of the closely related Bacillus cereus group, demonstrating the potential of integrated microfluidic and microarray technology for highly specific pathogen detection. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluid handling steps and allows the detection and identification of biological warfare agents in a rapid and automated fashion.