We report multiplexed label-free measurements of biomolecular interactions using silicon wire waveguide sensor arrays. The sensors are addressed using both wavelength division multiplexing and power broadcasting approaches. We demonstrate the real-time monitoring of antibody-antigen reactions using complementary and mismatched IgG receptor-analyte pairs and bovine serum albumin. The measured level of detection for each sensor element corresponds to a surface coverage of less than ~ 0.02% of a protein monolayer. The two addressing approaches are compared.

We present an SOI biosensor microarray chip that allows multiple molecular binding reactions to be simultaneously monitored. The individual biosensors are formed using 0.26 x 0.45 mu m(2) silicon photonic wire waveguides, which are arranged in compact Mach-Zehnder interferometer geometries with near temperature independent response. The sharp bend radius permitted by the photonic wires is exploited to form dense spiral waveguide structures that provide several millimeters of path length in a compact 130 mu m diameter circular area. This design provides the high sensitivity of a long waveguide, while maintaining compatibility with commercial microarray spotting tools. For low volume analyte delivery the sensor array chip contains a monolithically integrated microfluidic channel formed in an SU-8 overlayer. Multiple antibody-antigen reactions are observed in real-time by using an infrared camera to monitor the optical powers emerging from the sensor array output waveguides.

Background: Multi-Locus Sequence Typing (MLST) has emerged as a leading molecular typing method owing to its high ability to discriminate among bacterial isolates, the relative ease with which data acquisition and analysis can be standardized, and the high portability of the resulting sequence data. While MLST has been successfully applied to the study of the population structure for a number of different bacterial species, it has also provided compelling evidence for high rates of recombination in some species. We have analyzed a set of Campylobacter jejuni strains using MLST and Comparative Genomic Hybridization (CGH) on a full-genome microarray in order to determine whether recombination and high levels of genomic mosaicism adversely affect the inference of strain relationships based on the analysis of a restricted number of genetic loci.Results: Our results indicate that, in general, there is significant concordance between strain relationships established by MLST and those based on shared gene content as established by CGH. While MLST has significant predictive power with respect to overall genome similarity of isolates, we also found evidence for significant differences in genomic content among strains that would otherwise appear to be highly related based on their MLST profiles.Conclusion: The extensive genomic mosaicism between closely related strains has important implications in the context of establishing strain to strain relationships because it suggests that the exact gene content of strains, and by extension their phenotype, is less likely to be "predicted" based on a small number of typing loci. This in turn suggests that a greater emphasis should be placed on analyzing genes of clinical interest as we forge ahead with the next generation of molecular typing methods.

Genome sequencing has revealed the remarkable amount of genetic diversity that can be encountered in bacterial genomes. In particular, the comparison of genome sequences from closely related strains has uncovered significant differences in gene content, hinting at the dynamic nature of bacterial genomes. The study of these genome dynamics is crucial to leveraging genomic information because the genome sequence of a single bacterial strain may not accurately represent the genome of the species. The dynamic nature of bacterial genome content has required us to apply the concepts of comparative genomics (CG) at the species level. Although direct genome sequence comparisons are an ideal method of performing CG, one current constraint is the limited availability of multiple genome sequences from a given bacterial species. DNA microarray-based comparative genomic hybridization (MCGH), which can be used to determine the presence or absence of thousands of genes in a single hybridization experiment, provides a powerful alternative for determining genome content and has been successfully used to investigate the genome dynamics of a wide number of bacterial species. Although MCGH-based studies have already provided a new vista on bacterial genome diversity, original methods for MCGH have been limited by the absence of novel gene sequences included in the microarray. New applications of the MCGH platform not only promise to accelerate the pace of novel gene discovery but will also help provide an integrated microarray-based approach to the study of bacterial CG.

Background: Aeromonas salmonicida has been isolated from numerous fish species and shows wide variation in virulence and pathogenicity. As part of a larger research program to identify virulence genes and candidates for vaccine development, a DNA microarray was constructed using a subset of 2024 genes from the draft genome sequence of A. salmonicida subsp. salmonicida strain A449. The microarray included genes encoding known virulence-associated factors in A. salmonicida and homologs of virulence genes of other pathogens. We used microarray-based comparative genomic hybridizations (M-CGH) to compare selected A. salmonicida sub-species and other Aeromonas species from different hosts and geographic locations.Results: Results showed variable carriage of virulence- associated genes and generally increased variation in gene content across sub-species and species boundaries. The greatest variation was observed among genes associated with plasmids and transposons. There was little correlation between geographic region and degree of variation for all isolates tested.Conclusion: We have used the M-CGH technique to identify subsets of conserved genes from amongst this set of A. salmonicida virulence genes for further investigation as potential vaccine candidates. Unlike other bacterial characterization methods that use a small number of gene or DNA-based functions, M-CGH examines thousands of genes and/or whole genomes and thus is a more comprehensive analytical tool for veterinary or even human health research.

BACKGROUND:Microarray-based Comparative Genomic Hybridization (M-CGH) has been used to characterize the extensive intraspecies genetic diversity found in bacteria at the whole-genome level. Although conventional microarray analytical procedures have proved adequate in handling M-CGH data, data interpretation using these methods is based on a continuous character model in which gene divergence and gene absence form a spectrum of decreasing gene conservation levels. However, whereas gene divergence may yet be accompanied by retention in gene function, gene absence invariably leads to loss of function. This distinction, if ignored, leads to a loss in the information to be gained from M-CGH data. We present here results from experiments in which two genome-sequenced strains of C. jejuni were compared against each other using M-CGH. Because the gene content of both strains was known a priori, we were able to closely examine the effects of sequence divergence and gene absence on M-CGH data in order to define analytical parameters for M-CGH data interpretation. This would facilitate the examination of the relative effects of sequence divergence or gene absence in comparative genomics analyses of multiple strains of any species for which genome sequence data and a DNA microarray are available.RESULTS:As a first step towards improving the analysis of M-CGH data, we estimated the degree of experimental error in a series of experiments in which identical samples were compared against each other by M-CGH. This variance estimate was used to validate a Log Ratio-based methodology for identification of outliers in M-CGH data. We compared two genome strains by M-CGH to examine the effect of probe/target identity on the Log Ratios of signal intensities using prior knowledge of gene divergence and gene absence to establish Log Ratio thresholds for the identification of absent and conserved genes.CONCLUSION:The results from this empirical study validate the Log Ratio thresholds that have been used in other studies to establish gene divergence/absence. Moreover, the analytical framework presented here enhances the information content derived from M-CGH data by shifting the focus from divergent/absent gene detection to accurate detection of conserved and absent genes. This approach closely aligns the technical limitations of M-CGH analysis with practical limitations on the biological interpretation of comparative genomics data.