Simultaneous quantification of multiple nucleic acid targets in complex rRNA mixtures using high density microarrays and nonspecific hybridization as a source of information

Accurate predictions of postmortem interval using linear regression analyses of gene meter expression data

In criminal and civil investigations, postmortem interval is used as evidence to help sort out circumstances at the time of human death. Many biological, chemical, and physical indicators can be used to determine the postmortem interval - but most are not accurate. Here, we sought to validate an experimental design to accurately predict the time of death by analyzing the expression of hundreds of upregulated genes in two model organisms, the zebrafish and mouse. In a previous study, the death of healthy adults was conducted under strictly controlled conditions to minimize the effects of confounding factors such as lifestyle and temperature. A total of 74,179 microarray probes were calibrated using the Gene Meter approach and the transcriptional profiles of 1063 genes that significantly increased in abundance were assembled into a time series spanning from life to 48 or 96h postmortem. In this study, the experimental design involved splitting the transcription profiles into training and testing datasets, randomly selecting groups of profiles, determining the modeling parameters of the genes to postmortem time using over- and/or perfectly-defined linear regression analyses, and calculating the fit (R²) and slope of predicted versus actual postmortem times. This design was repeated several thousand to million times to find the top predictive groups of gene transcription profiles. A group of eleven zebrafish genes yielded R² of 1 and a slope of 0.99, while a group of seven mouse liver genes yielded a R² of 0.98 and a slope of 0.97, and seven mouse brain genes yielded a R² of 0.95 and a slope of 0.87. In all cases, groups of gene transcripts yielded better postmortem time predictions than individual gene transcripts. The significance of this study is two-fold: selected groups of gene transcripts provide accurate prediction of postmortem time, and the successfully validated experimental design can now be used to accurately predict postmortem time in cadavers.

Information Limited Oligonucleotide Amplification Assay for Affinity-Based, Parallel Detection Studies

Molecular communication systems encounter similar constraints as telecommunications. In either case, channel crosstalk at the receiver end will result in information loss that statistical analysis cannot compensate. This is because in any communication channel there is a physical limit to the amount of information that can be transmitted. We present a novel and simple modified end amplification (MEA) technique to generate reduced and defined amounts of specific information in form of short fragments from an oligonucleotide source that also contains unrelated and redundant information. Our method can be a valuable tool to investigate information overflow and channel capacity in biomolecular recognition systems.

The Hydrogenase Chip: a tiling oligonucleotide DNA microarray technique for characterizing hydrogen-producing and -consuming microbes in microbial communities

We developed a broad-ranging method for identifying key hydrogen-producing and consuming microorganisms through analysis of hydrogenase gene content and expression in complex anaerobic microbial communities. The method is based on a tiling hydrogenase gene oligonucleotide DNA microarray (Hydrogenase Chip), which implements a high number of probes per gene by tiling probe sequences across genes of interest at 1.67 × -2 × coverage. This design favors the avoidance of false positive gene identification in samples of DNA or RNA extracted from complex microbial communities. We applied this technique to interrogate interspecies hydrogen transfer in complex communities in (i) lab-scale reductive dehalogenating microcosms enabling us to delineate key H(2)-consuming microorganisms, and (ii) hydrogen-generating microbial mats where we found evidence for significant H(2) production by cyanobacteria. Independent quantitative PCR analysis on selected hydrogenase genes showed that this Hydrogenase Chip technique is semiquantitative. We also determined that as microbial community complexity increases, specificity must be traded for sensitivity in analyzing data from tiling DNA microarrays.

Beyond Affymetrix arrays: expanding the set of known hybridization isotherms and observing pre-wash signal intensities

Microarray hybridization studies have attributed the nonlinearity of hybridization isotherms to probe saturation and post-hybridization washing. Both processes are thought to distort ‘true’ target abundance because immobilized probes are saturated with excess target and stringent washing removes loosely bound targets. Yet the paucity of studies aimed at understanding hybridization and dissociation makes it difficult to align physicochemical theory to microarray results. To fill the void, we first examined hybridization isotherms generated on different microarray platforms using a ribosomal RNA target and then investigated hybridization signals at equilibrium and after stringent wash. Hybridization signal at equilibrium was achieved by treating the microarray with isopropanol, which prevents nucleic acids from dissolving into solution. Our results suggest that (i) the shape of hybridization isotherms varied by microarray platform with some being hyperbolic or linear, and others following a power-law; (ii) at equilibrium, fluorescent signal of different probes hybridized to the same target were not similar even with excess of target and (iii) the amount of target removed by stringent washing depended upon the hybridization time, the probe sequence and the presence/absence of nonspecific targets. Possible physicochemical interpretations of the results and future studies are discussed.