A proximal CCD imaging system for high-throughput detection of microarray-based assays

A multiplexed immunoassay system based upon reciprocating centrifugal microfluidics

A novel, centrifugal disk-based micro-total analysis system (μTAS) for low cost and high throughput semi-automated immunoassay processing was developed. A key innovation in the disposable immunoassay disk design is in a fluidic structure that enables very efficient micro-mixing based on a reciprocating mechanism in which centrifugal acceleration acting upon a liquid element first generates and stores pneumatic energy that is then released by a reduction of the centrifugal acceleration, resulting in a reversal of direction of flow of the liquid. Through an alternating sequence of high and low centrifugal acceleration, the system reciprocates the flow of liquid within the disk to maximize incubation/hybridization efficiency between antibodies and antigen macromolecules during the incubation/hybridization stage of the assay. The described reciprocating mechanism results in a reduction in processing time and reagent consumption by one order of magnitude.

Real-time processing and compression of DNA microarray images

In this paper, we present a pipeline architecture specifically designed to process and compress DNA microarray images. Many of the pixilated image generation methods produce one row of the image at a time. This property is fully exploited by the proposed pipeline that takes in one row of the produced image at each clock pulse and performs the necessary image processing steps on it. This will remove the present need for sluggish software routines that are considered a major bottleneck in the microarray technology. Moreover, two different structures are proposed for compressing DNA microarray images. The proposed architecture is proved to be highly modular, scalable, and suited for a standard cell VLSI implementation.

Nucleic acid microarray technology for toxicology: promise and practicalities

Much ongoing research in toxicology focuses on a hypothesis-driven mechanism of action approach aimed at understanding the molecular events mediating the actions of the chemicals of interest. Using this approach, investigators develop hypotheses based on observations, which may be derived from a host of resources but most frequently have been made within their own laboratories, or uncovered by others and reported in the scientific literature. Although the bulk of current understanding ofbiochemical toxicology emerged using studies based on observations derived in this way, this process, which is essentially based on existing information, may often limit the expansion knowledge. More simply expressed, one only finds that which one seeks. Without a clear understanding of the processes targeted by a specific toxin the problem of making observations that globally and accurately reflect the events mediating pathology which have been induced by the toxic agent is challenging. Recently, the development of high-throughput technologies for biochemical analysis of gene expression has led to innovative approaches in addressing the problem of making broad-based observations that more accurately reflect the entire spectrum of molecular lesions induced by specific toxins. These strategies include the use of new techniques in analysis of gene expression to convey information on alterations in mRNA levels, one of the earliest cellular signs initiated in response to a potential toxin. Prior to this time studies on toxicant-induced altered gene expression were limited to single, or small numbers of identified genes chosen by an investigator who reasoned, based on an existing observations, that levels of the proteins encoded by these genes were likely to be altered during toxic injury. Now, using cDNA or oligonucleotide genome-wide arrays, toxin-induced alterations in gene expression of thousands of genes can be examined simultaneously. Using these tools, molecular toxicologists can for the first time employ reasoned strategies to make observations, and then formulate hypotheses based on these observations.

Parallel fluorescence detection of single biomolecules in microarrays by a diffractive-optical-designed 2 x 2 fan-out element

We have developed a multifocal diffractive-optical fluorescence correlation spectroscopy system for parallel excitation and detection of single tetramethylrhodamine biomolecules in microarrays. Multifocal excitation was made possible through the use of a 2 x 2 fan-out diffractive-optical element with uniform intensity in all foci. Characterization of the 2 x 2 fan-out diffractive-optical element shows formation of almost perfect Gaussian foci of submicrometer lateral diameter, as analyzed by thermal motion of tetramethylrhodamine dye molecules in solution. Results of parallel excitation and detection in a high-density microarray of circular wells show single-biomolecule sensitivity in all four foci simultaneously.

Genomics and proteomics: the new millennium of drug discovery and development

One of the most pressing issues facing the pharmaceutical and biotechnology industry is the tremendous dropout rate of lead drug candidates. Over the last two decades, several new genomic technologies have been developed in hopes of addressing the issues of target identification and lead candidate optimization. Gene expression microarray is one of these technologies and this review describes the four main formats, which are currently available: (a) cDNA; (b) oligonucleotide; (c) electrokinetic; and (d) fiberoptic. Many of these formats have been developed with the goal of screening large numbers of genes. Recently, a high-throughput array format has been developed where a large number of samples can be assayed using arrays in parallel. In addition, focusing on gene expression may be only one avenue in preventing lead candidate failure. Proteomics or the study of protein expression may also play a role. Two-dimensional polyacrylamide gel electrophoresis (2-DE) coupled with mass spectroscopy has been the most widely accepted format to study protein expression. However, protein microarrays are now being developed and modified to a high-throughput screening format. Examples of several gene and protein expression studies as they apply to drug discovery and development are reviewed. These studies often result in large data sets. Examples of how several statistical methods (principal components analysis [PCA], clustering methods, Shannon entropy, etc.) have been applied to these data sets are also described. These newer genomic and proteomic technologies and their analysis and visualization methods have the potential to make the drug discovery and development process less costly and more efficient by aiding to select better target and lead candidates.