Fingerprinting closely related xanthomonas pathovars with random nonamer oligonucleotide microarrays

A gDNA microarray for genotyping salvia species

Salvia is an important genus from the Lamiaceae with approximately 1,000 species. This genus is distributed globally and cultivated for ornamental, culinary, and medicinal uses. We report the construction of the first fingerprinting array for Salvia species enriched with polymorphic and divergent DNA sequences and demonstrate the potential of this array for fingerprinting several economically important members of this genus. In order to generate the Salvia subtracted diversity array (SDA) a suppression subtractive hybridization (SSH) was performed between a pool of Salvia species and a pool of angiosperms and non-angiosperms to selectively isolate Salvia-specific sequences. A total of 285-subtracted genomic DNA (gDNA) fragments were amplified and arrayed. DNA fingerprints were obtained for fifteen Salvia genotypes including three that were not part of the original subtraction pool. Hierarchical cluster analysis indicated that the Salvia-specific SDA was capable of differentiating S. officinalis and S. miltiorrhiza from their closely related species and was also able to reveal genetic relationships consistent with geographical origins. In addition, this approach was capable of isolating highly polymorphic sequences from chloroplast and nuclear DNA without preliminary sequence information. Therefore, SDA is a powerful technique for fingerprinting non-model plants and for identifying new polymorphic loci that may be developed as potential molecular markers.

Metatranscriptomic analysis of the response of river biofilms to pharmaceutical products, using anonymous DNA microarrays

Pharmaceutical products are released at low concentrations into aquatic environments following domestic wastewater treatment. Such low concentrations have been shown to induce transcriptional responses in microorganisms, which could have consequences on aquatic ecosystem dynamics. In order to test if these transcriptional responses could also be observed in complex river microbial communities, biofilm reactors were inoculated with water from two rivers of differing trophic statuses and subsequently treated with environmentally relevant doses (ng/liter to microg/liter range) of four pharmaceuticals (erythromycin [ER], gemfibrozil [GM], sulfamethazine [SN], and sulfamethoxazole [SL]). To monitor functional gene expression, we constructed a 9,600-feature anonymous DNA microarray platform onto which cDNA from the biofilms was hybridized. Pharmaceutical treatments induced both positive and negative transcriptional responses from biofilm microorganisms. For instance, ER induced the transcription of several stress, transcription, and replication genes, while GM, a lipid regulator, induced transcriptional responses from several genes involved in lipid metabolism. SN caused shifts in genes involved in energy production and conversion, and SL induced responses from a range of cell membrane and outer envelope genes, which in turn could affect biofilm formation. The results presented here demonstrate for the first time that low concentrations of small molecules can induce transcriptional changes in a complex microbial community. The relevance of these results also demonstrates the usefulness of anonymous DNA microarrays for large-scale metatranscriptomic studies of communities from differing aquatic ecosystems.

Broad spectrum microarray for fingerprint-based bacterial species identification

BACKGROUND

Microarrays 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.

RESULTS

A 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.

CONCLUSIONS

These 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.

Suspension array analysis of 16S rRNA from Fe- and SO(4)2- reducing bacteria in uranium-contaminated sediments undergoing bioremediation

A 16S rRNA-targeted tunable bead array was developed and used in a retrospective analysis of metal- and sulfate-reducing bacteria in contaminated subsurface sediments undergoing in situ U(VI) bioremediation. Total RNA was extracted from subsurface sediments and interrogated directly, without a PCR step. Bead array validation studies with total RNA derived from 24 isolates indicated that the behavior and response of the 16S rRNA-targeted oligonucleotide probes could not be predicted based on the primary nucleic acid sequence. Likewise, signal intensity (absolute or normalized) could not be used to assess the abundance of one organism (or rRNA) relative to the abundance of another organism (or rRNA). Nevertheless, the microbial community structure and dynamics through time and space and as measured by the rRNA-targeted bead array were consistent with previous data acquired at the site, where indigenous sulfate- and iron-reducing bacteria and near neighbors of Desulfotomaculum were the organisms that were most responsive to a change in injected acetate concentrations. Bead array data were best interpreted by analyzing the relative changes in the probe responses for spatially and temporally related samples and by considering only the response of one probe to itself in relation to a background (reference) environmental sample. By limiting the interpretation of the data in this manner and placing it in the context of supporting geochemical and microbiological analyses, we concluded that ecologically relevant and meaningful information can be derived from direct microarray analysis of rRNA in uncharacterized environmental samples, even with the current analytical uncertainty surrounding the behavior of individual probes on tunable bead arrays.

Microarray applications in microbial ecology research

Microarray technology has the unparalleled potential to simultaneously determine the dynamics and/or activities of most, if not all, of the microbial populations in complex environments such as soils and sediments. Researchers have developed several types of arrays that characterize the microbial populations in these samples based on their phylogenetic relatedness or functional genomic content. Several recent studies have used these microarrays to investigate ecological issues; however, most have only analyzed a limited number of samples with relatively few experiments utilizing the full high-throughput potential of microarray analysis. This is due in part to the unique analytical challenges that these samples present with regard to sensitivity, specificity, quantitation, and data analysis. This review discusses specific applications of microarrays to microbial ecology research along with some of the latest studies addressing the difficulties encountered during analysis of complex microbial communities within environmental samples. With continued development, microarray technology may ultimately achieve its potential for comprehensive, high-throughput characterization of microbial populations in near real time.

Application of oligonucleotide microarrays for bacterial source tracking of environmental Enterococcus sp. isolates

In an effort towards adapting new and defensible methods for assessing and managing the risk posed by microbial pollution, we evaluated the utility of oligonucleotide microarrays for bacterial source tracking (BST) of environmental Enterococcus sp. isolates derived from various host sources. Current bacterial source tracking approaches rely on various phenotypic and genotypic methods to identify sources of bacterial contamination resulting from point or non-point pollution. For this study Enterococcus sp. isolates originating from deer, bovine, gull, and human sources were examined using microarrays. Isolates were subjected to Box PCR amplification and the resulting amplification products labeled with Cy5. Fluorescent-labeled templates were hybridized to in-house constructed nonamer oligonucleotide microarrays consisting of 198 probes. Microarray hybridization profiles were obtained using the ArrayPro image analysis software. Principal Components Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were compared for their ability to visually cluster microarray hybridization profiles based on the environmental source from which the Enterococcus sp. isolates originated. The PCA was visually superior at separating origin-specific clusters, even for as few as 3 factors. A Soft Independent Modeling (SIM) classification confirmed the PCA, resulting in zero misclassifications using 5 factors for each class. The implication of these results for the application of random oligonucleotide microarrays for BST is that, given the reproducibility issues, factor-based variable selection such as in PCA and SIM greatly outperforms dendrogram-based similarity measures such as in HCA and K-Nearest Neighbor KNN.

MOLECULAR-GENETIC APPROACHES TO IDENTIFICATION AND TYPING OF PATHOGENIC CANDIDA YEASTS

Currently, invasive candidal infections represent an increasing cause of morbidity and mortality in seriously ill hospitalised patients. Because the accurate diagnosis of candidiasis remains difficult, a fast and reliable assay for characterization of fungal pathogens is critical for the early initiation of adequate antifungal therapy and/or for introduction of preventive measures. As novel molecular genetic techniques are continuously introduced, their role in the management of infectious diseases has also been growing. Today, molecular strategies complement conventional methods and provide more accurate and detailed insight. It can be expected that future technical development will improve their potential furthermore. In this article, we provide a critical review on the value and limitations of molecular tools in pathogenic Candida species identification and strain typing regarding their sensitivity, discriminatory power, reproducibility, cost and ease of performance.

Development and validation of a prototype 16S rRNA-based taxonomic microarray for Alphaproteobacteria

The microarray approach has been proposed for high throughput analysis of the microbial community by providing snapshots of the microbial diversity under different environmental conditions. For this purpose, a prototype of a 16S rRNA-based taxonomic microarray was developed and evaluated for assessing bacterial community diversity. The prototype microarray is composed of 122 probes that target bacteria at various taxonomic levels from phyla to species (mostly Alphaproteobacteria). The prototype microarray was first validated using bacteria in pure culture. Differences in the sequences of probes and potential target DNAs were quantified as weighted mismatches (WMM) in order to evaluate hybridization reliability. As a general feature, probes having a WMM > 2 with target DNA displayed only 2.8% false positives. The prototype microarray was subsequently tested with an environmental sample, which consisted of an Agrobacterium-related polymerase chain reaction amplicon from a maize rhizosphere bacterial community. Microarray results were compared to results obtained by cloning-sequencing with the same DNA. Microarray analysis enabled the detection of all 16S rRNA gene sequences found by cloning-sequencing. Sequences representing only 1.7% of the clone library were detected. In conclusion, this prototype 16S rRNA-based taxonomic microarray appears to be a promising tool for the analysis of Alphaproteobacteria in complex ecosystems.

Challenges and opportunities for pathogen detection using DNA microarrays

DNA microarrays offer the potential for simultaneous detection of many pathogens that are of interest to homeland security, public health, medicine, and veterinary diagnostics. These tools are best suited for detecting the presence or absence of genetic sequences characteristic of specific pathogens, but microarrays are poorly suited for determining pathogen viability, and current methods provide only limited potential for pathogen enumeration. Two basic strategies have been described for pathogen detection: using enzymatic amplification to generate targets for interrogation with a microarray, or using direct interrogation of DNA or RNA without pre-amplification. Multiplex PCR has the advantage of a high degree of sensitivity and specificity, but associated microarrays are necessarily limited in scope. PCR-independent, whole-genome amplification eliminates biases inherent in PCR amplification and can accommodate more extensive microarrays, but assay sensitivity is compromised and these methods are probably of limited use when testing tissue samples. Direct hybridization of DNA or RNA provides the least bias in gene detection, but also the lowest level of analytic sensitivity. Ultimately, cost and limited sample throughput make it unlikely that planar microarrays will play a significant role in future pathogen detection schemes. Alternative microarray formats such as bead arrays, however, may circumvent the cost and throughput limitations and permit us to apply what we have learned from planar microarrays to develop robust pathogen detection systems. Assay validation and sample preparation will continue to be significant challenges for these detection systems.

Ribosomal RNA probes and microarrays: their potential use in assessing microbial biodiversity

The awareness that global biological diversity is affected by numerous, mostly human-made threats has made biodiversity assessment an important scientific issue for decades. Biodiversity includes different levels of complexity, such as community diversity, habitat diversity, genetic diversity, and species diversity. The application of molecular methods to answer ecological questions permits issues of biodiversity to be addressed at all levels. Microorganisms dominate global biological diversity in terms of their species numbers. However, their small size and limited morphological features make it challenging to obtain a comprehensive view of their biodiversity. The application of ribosomal RNA (rRNA) probes contributes significantly to the assessment of biodiversity at the molecular level. DNA microarrays offer a great potential to facilitate the application of molecular probes and other DNA analytical methods to answer ecological and biodiversity questions. We provide an introduction into the application of rRNA probes and DNA microarrays for the assessment of microbial biodiversity, as well as protocols for the implementation of DNA microarrays.

Development of microarray-based diagnostics of voles and shrews for use in biodiversity monitoring studies, and evaluation of mitochondrial cytochrome oxidase I vs. cytochrome b as genetic markers

Molecular methods are widely used for species identification of mammals. In particular, the mitochondrial cytochrome b gene sequence has proven helpful for this purpose. Microarray technology can now open up new perspectives for biodiversity monitoring. With microarrays, many thousands of genetically based characteristics can be tested on one microscopic glass slide called a 'chip'. A 'Mammalia-Chip', for example, could include redundant diagnostic markers to unambiguously identify all European mammal species. Of broader use, and therefore economically more relevant, could be a 'Biodiversity-Chip', containing diagnostic features to distinguish key species in the taxa of bacteria, lichen, molluscs, insects, fungi, mammals, etc. An important prerequisite for any mixed-phyla chip is a standardization of methods. One of the most promising genes as a universal marker for all eukaryotes is cytochrome oxidase I. We show that cytochrome oxidase I is adequate for the discrimination of different species of voles and shrews with cluster analysis. Based on these results we present a diagnostic microarray-chip using cytochrome oxidase I sequences for the identification of three species of Sorex (Soricidae, Insectivora) and four species of Microtus (Arvicolinae, Rodentia). We conclude that cytochrome oxidase I can be used as an alternative marker to cytochrome b in a mixed-phyla chip, or both genes can be used in combination to enhance redundance and thus robustness of a specific chip including small mammals.

Development and assessment of microarray-based DNA fingerprinting in Eucalyptus grandis

Development of improved Eucalyptus genotypes involves the routine identification of breeding stock and superior clones. Currently, microsatellites and random amplified polymorphic DNA markers are the most widely used DNA-based techniques for fingerprinting of these trees. While these techniques have provided rapid and powerful fingerprinting assays, they are constrained by their reliance on gel or capillary electrophoresis, and therefore, relatively low throughput of fragment analysis. In contrast, recently developed microarray technology holds the promise of parallel analysis of thousands of markers in plant genomes. The aim of this study was to develop a DNA fingerprinting chip for Eucalyptus grandis and to investigate its usefulness for fingerprinting of eucalypt trees. A prototype chip was prepared using a partial genomic library from total genomic DNA of 23 E. grandis trees, of which 22 were full siblings. A total of 384 cloned genomic fragments were individually amplified and arrayed onto glass slides. DNA fingerprints were obtained for 17 individuals by hybridizing labeled genome representations of the individual trees to the 384-element chip. Polymorphic DNA fragments were identified by evaluating the binary distribution of their background-corrected signal intensities across full-sib individuals. Among 384 DNA fragments on the chip, 104 (27%) were found to be polymorphic. Hybridization of these polymorphic fragments was highly repeatable (R2>0.91) within the E. grandis individuals, and they allowed us to identify all 17 full-sib individuals. Our results suggest that DNA microarrays can be used to effectively fingerprint large numbers of closely related Eucalyptus trees.

Rational design of DNA sequences for nanotechnology, microarrays and molecular computers using Eulerian graphs

Nucleic acids are molecules of choice for both established and emerging nanoscale technologies. These technologies benefit from large functional densities of 'DNA processing elements' that can be readily manufactured. To achieve the desired functionality, polynucleotide sequences are currently designed by a process that involves tedious and laborious filtering of potential candidates against a series of requirements and parameters. Here, we present a complete novel methodology for the rapid rational design of large sets of DNA sequences. This method allows for the direct implementation of very complex and detailed requirements for the generated sequences, thus avoiding 'brute force' filtering. At the same time, these sequences have narrow distributions of melting temperatures. The molecular part of the design process can be done without computer assistance, using an efficient 'human engineering' approach by drawing a single blueprint graph that represents all generated sequences. Moreover, the method eliminates the necessity for extensive thermodynamic calculations. Melting temperature can be calculated only once (or not at all). In addition, the isostability of the sequences is independent of the selection of a particular set of thermodynamic parameters. Applications are presented for DNA sequence designs for microarrays, universal microarray zip sequences and electron transfer experiments.

Quantitative oligonucleotide microarray fingerprinting of Salmonella enterica isolates

We report on a genome-independent microbial fingerprinting method using nucleic acid microarrays for microbial forensics and epidemiology applications and demonstrate that the microarray method provides high resolution differentiation between closely related microorganisms, using Salmonella enterica strains as the test case. In replicate trials we used a simple 192 probe nonamer array to construct a fingerprint library of 25 closely related Salmonella isolates. Controlling false discovery rate for multiple testing at alpha = 0.05, at least 295 of 300 pairs of S.enterica isolate fingerprints were found to be statistically distinct using a modified Hotelling T2 test. Although most pairs of Salmonella fingerprints are found to be distinct, forensic applications will also require a protocol for library construction and reliable microbial classification against a fingerprint library. We outline additional steps required to produce such a protocol.

Microarrays for bacterial detection and microbial community analysis

Several types of microarrays have recently been developed and evaluated for bacterial detection and microbial community analysis. These studies demonstrated that specific, sensitive and quantitative detection could be obtained with both functional gene arrays and community genome arrays. Although single-base mismatch can be differentiated with phylogenetic oligonucleotide arrays, reliable specific detection at the single-base level is still problematic. Microarray-based hybridization approaches are also useful for defining genome diversity and bacterial relatedness. However, more rigorous and systematic assessment and development are needed to realize the full potential of microarrays for microbial detection and community analysis.