Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions

Background

We describe a method for printing protein microarrays, and using these microarrays in a comparative fluorescence assay to measure the abundance of many specific proteins in complex solutions. A robotic device was used to print hundreds of specific antibody or antigen solutions in an array on the surface of derivatized microscope slides. Two complex protein samples, one serving as a standard for comparative quantitation, and the other representing an experimental sample in which the concentrations of specific proteins were to be measured, were labeled by covalent attachment of spectrally-resolvable fluorescent dyes. Specific antibody-antigen interactions localized specific components of the complex mixtures to defined cognate spots in the array, where the relative intensity of the fluorescent signals representing the experimental sample and the reference standard provided a measure of each protein's abundance in the experimental sample. To characterize the specificity, sensitivity and accuracy of this assay, we analyzed the performance of 115 antibody/antigen pairs.

Results

50% of the arrayed antigens, and 20% of the arrayed antibodies, provided specific and accurate measurements of their cognate ligands at or below concentrations of 1.6 µg/ml and 0.34 µg/ml, respectively. Some of the antibody/antigen pairs allowed detection of the cognate ligands at absolute concentrations below 1 ng/ml, and partial concentrations of less than 1 part in 10⁶, sensitivities sufficient for measurement of many clinically important proteins in patient blood samples.

Conclusions

Protein microarrays can provide a simple and practical means to characterize patterns of variation in hundreds or thousands of different proteins, in clinical or research applications.     

Biologically meaningful expression profiling across species using heterologous hybridization to a cDNA microarray

Background  

Unravelling the path from genotype to phenotype, as it is influenced by an organism's environment, is one of the central goals in biology. Gene expression profiling by means of microarrays has become very prominent in this endeavour, although resources exist only for relatively few model systems. As genomics has matured into a comparative research program, expression profiling now also provides a powerful tool for non-traditional model systems to elucidate the molecular basis of complex traits.     

SCOWLP classification: Structural comparison and analysis of protein binding regions

Background  

Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design.     

Detecting variants with Metabolic Design,a new software tool to design probes for explorative functional DNA microarray development

Background  

Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic potential in different ecosystems, we need high throughput tools, such as functional microarrays, that allow the simultaneous analysis of thousands of genes. However, most classical functional microarrays use specific probes that monitor only known sequences, and so fail to cover the full microbial gene diversity present in complex environments. We have thus developed an algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes.     

GenomeViz: visualizing microbial genomes

Background

An increasing number of microbial genomes are being sequenced and deposited in public databases. In addition, several closely related strains are also being sequenced in order to understand the genetic basis of diversity and mechanisms that lead to the acquisition of new genetic traits. These exercises have necessitated the requirement for visualizing microbial genomes and performing genome comparisons on a finer scale. We have developed GenomeViz to enable rapid visualization and subsequent comparisons of several microbial genomes in an interactive environment.

Results

Here we describe a program that allows visualization of both qualitative and quantitative information from complete and partially sequenced microbial genomes. Using GenomeViz, data deriving from studies on genomic islands, gene/protein classifications, GC content, GC skew, whole genome alignments, microarrays and proteomics may be plotted. Several genomes can be visualized interactively at the same time from a comparative genomic perspective and publication quality circular genome plots can be created.

Conclusions

GenomeViz should allow researchers to perform visualization and comparative analysis of up to eight different microbial genomes simultaneously.

     

Comparative genomics and experimental promoter analysis reveal functional liver-specific elements in mammalian hepatic lipase genes

Background

Array-based comparative genomic hybridization (aCGH) is a high-throughput method for measuring genome-wide DNA copy number changes. Current aCGH methods have limited resolution, sensitivity and reproducibility. Microarrays for aCGH are available only for a few organisms and combination of aCGH data with expression data is cumbersome.

Results

We present a novel method of using commercial oligonucleotide expression microarrays for aCGH, enabling DNA copy number measurements and expression profiles to be combined using the same platform. This method yields aCGH data from genomic DNA without complexity reduction at a median resolution of approximately 17,500 base pairs. Due to the well-defined nature of oligonucleotide probes, DNA amplification and deletion can be defined at the level of individual genes and can easily be combined with gene expression data.

Conclusion

A novel method of gene resolution analysis of copy number variation (graCNV) yields high-resolution maps of DNA copy number changes and is applicable to a broad range of organisms for which commercial oligonucleotide expression microarrays are available. Due to the standardization of oligonucleotide microarrays, graCNV results can reliably be compared between laboratories and can easily be combined with gene expression data using the same platform.     

Visualization-based discovery and analysis of genomic aberrations in microarray data

Background  

Chromosomal copy number changes (aneuploidies) play a key role in cancer progression and molecular evolution. These copy number changes can be studied using microarray-based comparative genomic hybridization (array CGH) or gene expression microarrays. However, accurate identification of amplified or deleted regions requires a combination of visual and computational analysis of these microarray data.     

Gene Expression in Chicken Reveals Correlation with Structural Genomic Features and Conserved Patterns of Transcription in the Terrestrial Vertebrates

Background

The chicken is an important agricultural and avian-model species. A survey of gene expression in a range of different tissues will provide a benchmark for understanding expression levels under normal physiological conditions in birds. With expression data for birds being very scant, this benchmark is of particular interest for comparative expression analysis among various terrestrial vertebrates.

Methodology/Principal Findings

We carried out a gene expression survey in eight major chicken tissues using whole genome microarrays. A global picture of gene expression is presented for the eight tissues, and tissue specific as well as common gene expression were identified. A Gene Ontology (GO) term enrichment analysis showed that tissue-specific genes are enriched with GO terms reflecting the physiological functions of the specific tissue, and housekeeping genes are enriched with GO terms related to essential biological functions. Comparisons of structural genomic features between tissue-specific genes and housekeeping genes show that housekeeping genes are more compact. Specifically, coding sequence and particularly introns are shorter than genes that display more variation in expression between tissues, and in addition intergenic space was also shorter. Meanwhile, housekeeping genes are more likely to co-localize with other abundantly or highly expressed genes on the same chromosomal regions. Furthermore, comparisons of gene expression in a panel of five common tissues between birds, mammals and amphibians showed that the expression patterns across tissues are highly similar for orthologuous genes compared to random gene pairs within each pair-wise comparison, indicating a high degree of functional conservation in gene expression among terrestrial vertebrates.

Conclusions

The housekeeping genes identified in this study have shorter gene length, shorter coding sequence length, shorter introns, and shorter intergenic regions, there seems to be selection pressure on economy in genes with a wide tissue distribution, i.e. these genes are more compact. A comparative analysis showed that the expression patterns of orthologous genes are conserved in the terrestrial vertebrates during evolution.     

Evolution of insect proteomes: insights into synapse organization and synaptic vesicle life cycle

Background

The molecular components in synapses that are essential to the life cycle of synaptic vesicles are well characterized. Nonetheless, many aspects of synaptic processes, in particular how they relate to complex behaviour, remain elusive. The genomes of flies, mosquitoes, the honeybee and the beetle are now fully sequenced and span an evolutionary breadth of about 350 million years; this provides a unique opportunity to conduct a comparative genomics study of the synapse.

Results

We compiled a list of 120 gene prototypes that comprise the core of presynaptic structures in insects. Insects lack several scaffolding proteins in the active zone, such as bassoon and piccollo, and the most abundant protein in the mammalian synaptic vesicle, namely synaptophysin. The pattern of evolution of synaptic protein complexes is analyzed. According to this analysis, the components of presynaptic complexes as well as proteins that take part in organelle biogenesis are tightly coordinated. Most synaptic proteins are involved in rich protein interaction networks. Overall, the number of interacting proteins and the degrees of sequence conservation between human and insects are closely correlated. Such a correlation holds for exocytotic but not for endocytotic proteins.

Conclusion

This comparative study of human with insects sheds light on the composition and assembly of protein complexes in the synapse. Specifically, the nature of the protein interaction graphs differentiate exocytotic from endocytotic proteins and suggest unique evolutionary constraints for each set. General principles in the design of proteins of the presynaptic site can be inferred from a comparative study of human and insect genomes.     

Disease-associated pathophysiologic structures in pediatric rheumatic diseases show characteristics of scale-free networks seen in physiologic systems: implications for pathogenesis and treatment

Background

Tamoxifen (TAM) is a well characterized breast cancer drug and selective estrogen receptor modulator (SERM) which also has been associated with a small increase in risk for uterine cancers. TAM's partial agonist activation of estrogen receptor has been characterized for specific gene promoters but not at the genomic level in vivo.Furthermore, reducing uncertainties associated with cross-species extrapolations of pharmaco- and toxicogenomic data remains a formidable challenge.

Results

A comparative ligand and species analysis approach was conducted to systematically assess the physiological, morphological and uterine gene expression alterations elicited across time by TAM and ethynylestradiol (EE) in immature ovariectomized Sprague-Dawley rats and C57BL/6 mice. Differential gene expression was evaluated using custom cDNA microarrays, and the data was compared to identify conserved and divergent responses. 902 genes were differentially regulated in all four studies, 398 of which exhibit identical temporal expression patterns.

Conclusion

Comparative analysis of EE and TAM differentially expressed gene lists suggest TAM regulates no unique uterine genes that are conserved in the rat and mouse. This demonstrates that the partial agonist activities of TAM extend to molecular targets in regulating only a subset of EE-responsive genes. Ligand-conserved, species-divergent expression of carbonic anhydrase 2 was observed in the microarray data and confirmed by real time PCR. The identification of comparable temporal phenotypic responses linked to related gene expression profiles demonstrates that systematic comparative genomic assessments can elucidate important conserved and divergent mechanisms in rodent estrogen signalling during uterine proliferation.     

The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays

Background  

Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available.     

Web-based interrogation of gene expression signatures using EXALT

Background  

Widespread use of high-throughput techniques such as microarrays to monitor gene expression levels has resulted in an explosive growth of data sets in public domains. Integration and exploration of these complex and heterogeneous data have become a major challenge.     

DNA microarray data and contextual analysis of correlation graphs

Background  

DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation.     

Starr: Simple Tiling ARRay analysis of Affymetrix ChIP-chip data

Background  

Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay used for investigating DNA-protein-binding or post-translational chromatin/histone modifications. As with all high-throughput technologies, it requires thorough bioinformatic processing of the data for which there is no standard yet. The primary goal is to reliably identify and localize genomic regions that bind a specific protein. Further investigation compares binding profiles of functionally related proteins, or binding profiles of the same proteins in different genetic backgrounds or experimental conditions. Ultimately, the goal is to gain a mechanistic understanding of the effects of DNA binding events on gene expression.