Universal microarray for pattern-based bacterial species identification
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PROVIDER: PRJNA117129 | ENA |
REPOSITORIES: ENA
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Project description:Microarrays have become a powerful tool for DNA-based molecular diagnostics and identification of pathogens. However, most of them target a limited range of organisms and are generally based on only one or very few genes for organism identification. Although such microarrays are proven tools for species identification, they suffer from the fact that identification is only possible for organisms for which probes were specifically pre-developed. Furthermore, this approach often leads to problems with taxonomic-level resolution with insufficient diagnostic differences between closely related taxa found in the commonly used DNA sequences. An alternative strategy is to use the hybridisation pattern generated by many different anonymous markers distributed over the entire genome for identification based on comparison to a type database. We realised this strategy using a high density microarray containing 95,000 different 13-mer probes. Here, we demonstrate the specificity of our microarray based on results obtained with nine different bacterial species and strains. The hybridisation patterns allowed clear differentiation at the strain and even variant level. The reproducibility of our system was high as shown by high correlation coefficients between replicates, despite the occurrence of mismatch hybridisation. The results indicate the potential for identification of all bacterial taxa at the subspecies level using our universal microarray.
2010-03-16 | GSE15391 | GEO
Project description:Microarrays have become a powerful tool for DNA-based molecular diagnostics and identification of pathogens. However, most of them target a limited range of organisms and are generally based on only one or very few genes for organism identification. Although such microarrays are proven tools for species identification, they suffer from the fact that identification is only possible for organisms for which probes were specifically pre-developed. Furthermore, this approach often leads to problems with taxonomic-level resolution with insufficient diagnostic differences between closely related taxa found in the commonly used DNA sequences. An alternative strategy is to use the hybridisation pattern generated by many different anonymous markers distributed over the entire genome for identification based on comparison to a type database. We realised this strategy using a high density microarray containing 95,000 different 13-mer probes. Here, we demonstrate the specificity of our microarray based on results obtained with nine different bacterial species and strains. The hybridisation patterns allowed clear differentiation at the strain and even variant level. The reproducibility of our system was high as shown by high correlation coefficients between replicates, despite the occurrence of mismatch hybridisation. The results indicate the potential for identification of all bacterial taxa at the subspecies level using our universal microarray. Hybridisation patterns of DNA from bacterial type strains (E. coli strains K12 and B, Pantoea agglomerans strains ATCC27155T and C9-1, Pantoea stewartii pv stewartii strain DC283, Salmonella Typhimurium strains LT2 and DT204 and Micrococcus luteus) were compared to each other. Using GeneSpring v7.3.1, cluster analyses were performed as well as ANOVA in order to determine the more discriminative probes out of our 95,000-probe panel.
2010-05-06 | E-GEOD-15391 | biostudies-arrayexpress
Project description:BackgroundMicroarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database.ResultsA high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system.ConclusionsThese results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups.
| S-EPMC2830168 | biostudies-literature
Project description:A method based on a modified broad-range PCR and an oligonucleotide microarray for the simultaneous detection and identification of 12 bacterial pathogens at the species level.
2009-08-31 | GSE17221 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE3972: Contribution of unique genes by individual cell lines to Universal Human Reference RNA GSE3973: Microarray Coverage of Universal Human Reference RNA on microarrays with yeast controls GSE3974: Contribution of unique genes by individual cell lines to Universal Mouse Reference RNA Abstract: BACKGROUND: Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR), developed with the goal of providing hybridization signal at each microarray probe location (spot). Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. RESULTS: Human, mouse and rat URR (UHRR, UMRR and URRR, respectively) were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage). Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97). CONCLUSION: Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and laboratories. Refer to individual Series
2006-03-07 | E-GEOD-4389 | biostudies-arrayexpress
Project description:28 Streptomyces strains isolated from common scab lesions of potato tubers from a wide geographic range in Norway, were selected for microarray analysis. The selected strains were subjected to species identification by microarray, 16S phylogenetic analysis and PCR; and microarray-based comparative genome analysis. To our knowledge, this is the first report of S. turgidiscabies and S. europaeiscabiei in Norway.
2010-05-01 | GSE20487 | GEO
Project description:LncRNA-mRNA expression pattern in invasive pituitary adenomas: A microarray analysis
| PRJNA789793 | ENA
Project description:We have developed a rapid microarray-based assay for the reliable detection and discrimination of six species of the Listeria genus: L. monocytogenes, L. ivanovii, L. innocua, L. welshimeri, L. seeligeri, and L. grayi. The approach used in this study involves one-tube multiplex PCR amplification of six target bacterial virulence factor genes (iap, hly, inlB, plcA, plcB, and clpE), synthesis of fluorescently labeled single-stranded DNA, and hybridization to the multiple individual oligonucleotide probes specific for each Listeria species and immobilized on a glass surface. Results of the microarray analysis of 53 reference and clinical isolates of Listeria spp. demonstrated that this method allowed unambiguous identification of all six Listeria species based on sequence differences in the iap gene. Another virulence factor gene, hly, was used for detection and genotyping all L. monocytogenes, all L. ivanovii, and 8 of 11 L. seeligeri isolates. Other members of the genus Listeria and three L. seeligeri isolates did not contain the hly gene. There was complete agreement between the results of genotyping based on the hly and iap gene sequences. All L. monocytogenes isolates were found to be positive for the inlB, plcA, plcB, and clpE virulence genes specific only to this species. Our data on Listeria species analysis demonstrated that this microarray technique is a simple, rapid, and robust genotyping method that is also a potentially valuable tool for identification and characterization of bacterial pathogens in general.
| S-EPMC154633 | biostudies-literature
Project description:Abstract: BACKGROUND: Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR), developed with the goal of providing hybridization signal at each microarray probe location (spot). Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. RESULTS: Human, mouse and rat URR (UHRR, UMRR and URRR, respectively) were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage). Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97). CONCLUSION: Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and laboratories. This SuperSeries is composed of the SubSeries listed below.
2006-03-08 | GSE4389 | GEO
Project description:Rapid Identification of Bacterial Pathogens using a PCR- and Microarray-Based Assay
| PRJNA119185 | ENA