The tagged microarray marker (TAM) method for high-throughput detection of single nucleotide and indel polymorphisms

The tagged microarray marker (TAM) method allows high-throughput differentiation between predicted alternative PCR products. Typically, the method is used as a molecular marker approach to determining the allelic states of single nucleotide polymorphisms (SNPs) or insertion-deletion (indel) alleles at genomic loci in multiple individuals. Biotin-labeled PCR products are spotted, unpurified, onto a streptavidin-coated glass slide and the alternative products are differentiated by hybridization to fluorescent detector oligonucleotides that recognize corresponding allele-specific tags on the PCR primers. The main attractions of this method are its high throughput (thousands of PCRs are analyzed per slide), flexibility of scoring (any combination, from a single marker in thousands of samples to thousands of markers in a single sample, can be analyzed) and flexibility of scale (any experimental scale, from a small lab setting up to a large project). This protocol describes an experiment involving 3,072 PCRs scored on a slide. The whole process from the start of PCR setup to receiving the data spreadsheet takes 2 d.

GeneMCL in microarray analysis

Accurately and reliably identifying the actual number of clusters present with a dataset of gene expression profiles, when no additional information on cluster structure is available, is a problem addressed by few algorithms. GeneMCL transforms microarray analysis data into a graph consisting of nodes connected by edges, where the nodes represent genes, and the edges represent the similarity in expression of those genes, as given by a proximity measurement. This measurement is taken to be the Pearson correlation coefficient combined with a local non-linear rescaling step. The resulting graph is input to the Markov Cluster (MCL) algorithm, which is an elegant, deterministic, non-specific and scalable method, which models stochastic flow through the graph. The algorithm is inherently affected by any cluster structure present, and rapidly decomposes a graph into cohesive clusters. The potential of the GeneMCL algorithm is demonstrated with a 5730 gene subset (IGS) of the Van't Veer breast cancer database, for which the clusterings are shown to reflect underlying biological mechanisms. (c) 2005 Elsevier Ltd. All rights reserved.

Neoglycolipid probes prepared via oxime ligation for microarray analysis of oligosaccharide-protein interactions

Neoglycolipid technology is the basis of a microarray platform for assigning oligosaccharide ligands for carbohydrate-binding proteins. The strategy for generating the neoglycolipid probes by reductive amination results in ring opening of the core monosaccharides. This often limits applicability to short-chain saccharides, although the majority of recognition motifs are satisfactorily presented with neoglycolipids of longer oligosaccharides. Here, we describe neoglycolipids prepared by oxime ligation. We provide evidence from NMR studies that a significant proportion of the oxime-linked core monosaccharide is in the ring-closed form, and this form selectively interacts with a carbohydrate-binding protein. By microarray analyses we demonstrate the effective presentation with oxime-linked neoglycolipids of (1) Lewis(x) trisaccharide to antibodies to Lewisx, (2) sialyllactose analogs to the sialic acid-binding receptors, siglecs, and (3) N-glycans to a plant lectin that requires an intact N-acetylglucosamine core.

Phenotype MicroArray (TM) in the metabolic characterisation of Salmonella serotypes Agona, Enteritidis, Give, Hvittingfoss, Infantis, Newport and Typhimurium

The Phenotype MicroArray (TM) (PM) technology was used to study the metabolic characteristics of 29 Salmonella strains belonging to seven serotypes of S. enterica spp. enterica. Strains of serotypes Typhimurium (six strains among definite phage types DTs 1, 40 and 104) and Agona (two strains) were tested for 949 substrates, Enteritidis (six strains of phage type PT1), Give, Hvittingfoss, Infantis and Newport strains (two of each) were tested for 190 substrates and seven other Agona strains for 95 substrates. The strains represented 18 genotypes in pulsed-field gel electrophoresis (PFGE). Among 949 substrates, 18 were identified that could be used to differentiate between the strains of those seven serotypes or within a single serotype. Unique metabolic differences between the Finnish endemic Typhimurium DT1 and Agona strains were detected, for example, in the metabolism of d-tagatose, d-galactonic acid gamma-lactone and l-proline as a carbon source. Thus, the PM technique is a useful tool for identifying potential differential markers on a metabolic basis that could be used for epidemiological surveillance.

A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

Development of a miniaturised microarray-based assay for the rapid identification of antimicrobial resistance genes in Gram-negative bacteria

We describe the development of a miniaturised microarray for the detection of antimicrobial resistance genes in Gram-negative bacteria. Included on the array are genes encoding resistance to aminoglycosides, trimethoprim, sulphonamides, tetracyclines and beta-lactams, including extended-spectrum beta-lactamases. Validation of the array with control strains demonstrated a 99% correlation between polymerase chain reaction and array results. There was also good correlation between phenotypic and genotypic results for a large panel of Escherichia coli and Salmonella isolates. Some differences were also seen in the number and type of resistance genes harboured by E. coli and Salmonella strains. The array provides an effective, fast and simple method for detection of resistance genes in clinical isolates suitable for use in diagnostic laboratories, which in future will help to understand the epidemiology of isolates and to detect gene linkage in bacterial populations. (C) 2008 Published by Elsevier B.V. and the International Society of Chemotherapy.

Identification of core and variable components of the Salmonella enterica subspecies I genome by microarray

We have performed microarray hybridization studies on 40 clinical isolates from 12 common serovars within Salmonella enterica subspecies I to identify the conserved chromosomal gene pool. We were able to separate the core invariant portion of the genome by a novel mathematical approach using a decision tree based on genes ranked by increasing variance. All genes within the core component were confirmed using available sequence and microarray information for S. enterica subspecies I strains. The majority of genes within the core component had conserved homologues in Escherichia coli K-12 strain MG1655. However, many genes present in the conserved set which were absent or highly divergent in K-12 had close homologues in pathogenic bacteria such as Shigella flexneri and Pseudomonas aeruginosa. Genes within previously established virulence determinants such as SPI1 to SPI5 were conserved. In addition several genes within SPI6, all of SPI9, and three fimbrial operons (fim, bcf, and stb) were conserved within all S. enterica strains included in this study. Although many phage and insertion sequence elements were missing from the core component, approximately half the pseudogenes present in S. enterica serovar Typhi were conserved. Furthermore, approximately half the genes conserved in the core set encoded hypothetical proteins. Separation of the core and variant gene sets within S. enterica subspecies I has offered fundamental biological insight into the genetic basis of phenotypic similarity and diversity across S. enterica subspecies I and shown how the core genome of these pathogens differs from the closely related E. coli K-12 laboratory strain.

Transcriptomic analysis of rhizobium leguminosarum biovar viciae in symbiosis with host plants pisum sativum and Vicia cracca

Rhizobium leguminosarum bv. viciae forms nitrogen-fixing nodules on several legumes, including pea (Pisum sativum) and vetch (Vicia cracca), and has been widely used as a model to study nodule biochemistry. To understand the complex biochemical and developmental changes undergone by R. leguminosarum bv. viciae during bacteroid development, microarray experiments were first performed with cultured bacteria grown on a variety of carbon substrates (glucose, pyruvate, succinate, inositol, acetate, and acetoacetate) and then compared to bacteroids. Bacteroid metabolism is essentially that of dicarboxylate-grown cells (i.e., induction of dicarboxylate transport, gluconeogenesis and alanine synthesis, and repression of sugar utilization). The decarboxylating arm of the tricarboxylic acid cycle is highly induced, as is gamma-aminobutyrate metabolism, particularly in bacteroids from early (7-day) nodules. To investigate bacteroid development, gene expression in bacteroids was analyzed at 7, 15, and 21 days postinoculation of peas. This revealed that bacterial rRNA isolated from pea, but not vetch, is extensively processed in mature bacteroids. In early development (7 days), there were large changes in the expression of regulators, exported and cell surface molecules, multidrug exporters, and heat and cold shock proteins. fix genes were induced early but continued to increase in mature bacteroids, while nif genes were induced strongly in older bacteroids. Mutation of 37 genes that were strongly upregulated in mature bacteroids revealed that none were essential for nitrogen fixation. However, screening of 3,072 mini-Tn5 mutants on peas revealed previously uncharacterized genes essential for nitrogen fixation. These encoded a potential magnesium transporter, an AAA domain protein, and proteins involved in cytochrome synthesis.

Linking molecular and population stress responses in Daphnia magna exposed to cadmium

DNA microarrays can be used to measure environmental stress responses. If they are to be predictive of environmental impact, we need to determine if altered gene expression translates into negative impacts on individuals and populations. A large cDNA microarray (14000 spots) was created to measure molecular stress responses to cadmium in Daphnia magna,the most widely used aquatic indicator species, and relate responses to population growth rate (pgr). We used the array to detect differences in the transcription of genes in juvenile D. magna (24 h old) after 24 h exposure to a control and three cadmium concentrations (6, 20, and 37 mu g Cd2+ L-1). Stress responses at the population level were estimated following a further 8 days exposure. Pgr was approximately linear negative with increasing cadmium concentration over this range. The microarray profile of gene expression in response to acute cadmium exposure begins to provide an overview of the molecular responses of D. magna, especially in relation to growth and development. Of the responding genes, 29% were involved with metabolism including carbohydrate, fat and peptide metabolism, and energy production, 31% were involved with transcription/translation, while 40% of responding genes were associated with cellular processes like growth and moulting, ion transport, and general stress responses (which included oxidative stress). Our production and application of a large Daphnia magna microarray has shown that measured gene responses can be logically linked to the impact of a toxicant such as cadmium on somatic growth and development, and consequently pgr.

Characterization of the quaternary amine transporters of Rhizobium leguminosarum bv. viciae 3841

Rhizobium leguminosarum bv. viciae 3841 contains six putative quaternary ammonium transporters (Qat), of the ABC family. Qat6 was strongly induced by hyperosmosis although the solute transported was not identified. All six systems were induced by the quaternary amines choline and glycine betaine. It was confirmed by microarray analysis of the genome that pRL100079-83 (qat6) is the most strongly upregulated transport system under osmotic stress, although other transporters and 104 genes are more than threefold upregulated. A range of quaternary ammonium compounds were tested but all failed to improve growth of strain 3841 under hyperosmotic stress. One Qat system (gbcXWV) was induced 20-fold by glycine betaine and choline and a Tn5::gbcW mutant was severely impaired for both transport and growth on these compounds, demonstrating that it is the principal system for their use as carbon and nitrogen sources. It transports glycine betaine and choline with a high affinity (apparent K-m, 168 and 294 nM, respectively).

Systems biology meets stress ecology: linking molecular and organismal stress responses in Daphnia magna

Background: Ibuprofen and other nonsteroidal anti-inflammatory drugs have been designed to interrupt eicosanoid metabolism in mammals, but little is known of how they affect nontarget organisms. Here we report a systems biology study that simultaneously describes the transcriptomic and phenotypic stress responses of the model crustacean Daphnia magna after exposure to ibuprofen. Results: Our findings reveal intriguing similarities in the mode of action of ibuprofen between vertebrates and invertebrates, and they suggest that ibuprofen has a targeted impact on reproduction at the molecular, organismal, and population level in daphnids. Microarray expression and temporal real-time quantitative PCR profiles of key genes suggest early ibuprofen interruption of crustacean eicosanoid metabolism, which appears to disrupt signal transduction affecting juvenile hormone metabolism and oogenesis. Conclusion: Combining molecular and organismal stress responses provides a guide to possible chronic consequences of environmental stress for population health. This could improve current environmental risk assessment by providing an early indication of the need for higher tier testing. Our study demonstrates the advantages of a systems approach to stress ecology, in which Daphnia will probably play a major role.

Comparison of the global gene expression profiles produced by methylparaben, n-butylparaben and 17 beta-oestradiol in MCF7 human breast cancer cells

Since the alkyl esters of p-hydroxybenzoic acid (parabens) can be measured intact in the human breast and possess oestrogenic properties, it has been suggested that they could contribute to an aberrant burden of oestrogen signalling in the human breast and so play a role in the rising incidence of breast cancer. However, although parabens have been shown to regulate a few single genes (reporter genes, pS2, progesterone receptor) in a manner similar to that of 17 beta-oestradiol, the question remains as to the full extent of the similarity in the overall gene profile induced in response to parabens compared with 17 beta-oestradiol. The GE-Amersham CodeLink 20 K human expression microarray system was used to profile the expression of 19881 genes in MCF7 human breast cancer cells following a 7-day exposure to 5 x 10(-4) m methylparaben, 10(-5) m n-butylparaben and 10(-8) m 17 beta-oestradiol. At these concentrations, the parabens gave growth responses in MCF7 cells of similar magnitude to 17 beta-oestradiol. The study identified genes which are upregulated or downregulated to a similar extent by methylparaben, n-butylparaben and 17 beta-oestradiol. However, the majority of genes were not regulated in the same way by all three treatments. Some genes responded differently to parabens from 17 beta-oestradiol, and furthermore, differences in expression of some genes could be detected even between the two individual parabens. Therefore, although parabens possess oestrogenic properties, their mimicry in terms of global gene expression patterns is not perfect and differences in gene expression profiles could result in consequences to the cells that are not identical to those following exposure to 17 beta-oestradiol. Copyright (c) 2006 John Wiley & Sons, Ltd.

Transcriptional profiling of the LPS induced NF-kappaB response in macrophages

BACKGROUND: Exposure of macrophages to bacterial products such as lipopolysaccharide (LPS) results in activation of the NF-kappaB transcription factor, which orchestrates a gene expression programme that underpins the macrophage-dependent immune response. These changes include the induction or repression of a wide range of genes that regulate inflammation, cell proliferation, migration and cell survival. This process is tightly regulated and loss of control is associated with conditions such as septic shock, inflammatory diseases and cancer. To study this response, it is important to have in vitro model systems that reflect the behaviour of cells in vivo. In addition, it is necessary to understand the natural differences that can occur between individuals. In this report, we have investigated and compared the LPS response in macrophage derived cell lines and peripheral blood mononuclear cell (PBMC) derived macrophages. RESULTS: Gene expression profiles were determined following LPS treatment of THP-1 cells for 1 and 4 hours. LPS significantly induced or repressed 72 out of 465 genes selected as being known or putative NF-kappaB target genes, which exhibited 4 temporal patterns of expression. Results for 34 of these genes, including several genes not previously identified as LPS target genes, were validated using real time PCR. A high correlation between microarray and real time PCR data was found. Significantly, the LPS induced expression profile of THP-1 cells, as determined using real time PCR, was found to be very similar to that of human PBMC derived macrophages. Interestingly, some differences were observed in the LPS response between the two donor PBMC macrophage populations. Surprisingly, we found that the LPS response in U937 cells was dramatically different to both THP-1 and PBMC derived macrophages. CONCLUSION: This study revealed a dynamic and diverse transcriptional response to LPS in macrophages, involving both the induction and repression of gene expression in a time dependent manner. Moreover, we demonstrated that the LPS induced transcriptional response in the THP-1 cell line is very similar to primary PBMC derived macrophages. Therefore, THP-1 cells represent a good model system for studying the mechanisms of LPS and NF-kappaB dependent gene expression.

Expression of target and reference genes in Daphnia magna exposed to ibuprofen

Background: Transcriptomic techniques are now being applied in ecotoxicology and toxicology to measure the impact of stressors and develop understanding of mechanisms of toxicity. Microarray technology in particular offers the potential to measure thousands of gene responses simultaneously. However, it is important that microarrays responses should be validated, at least initially, using real-time quantitative polymerase chain reaction (QPCR). The accurate measurement of target gene expression requires normalisation to an invariant internal control e. g., total RNA or reference genes. Reference genes are preferable, as they control for variation inherent in the cDNA synthesis and PCR. However, reference gene expression can vary between tissues and experimental conditions, which makes it crucial to validate them prior to application. Results: We evaluated 10 candidate reference genes for QPCR in Daphnia magna following a 24 h exposure to the non-steroidal anti-inflammatory drug (NSAID) ibuprofen (IB) at 0, 20, 40 and 80 mg IB l(-1). Six of the 10 candidates appeared suitable for use as reference genes. As a robust approach, we used a combination normalisation factor (NF), calculated using the geNorm application, based on the geometric mean of three selected reference genes: glyceraldehyde-3-phosphate dehydrogenase, ubiquitin conjugating enzyme and actin. The effects of normalisation are illustrated using as target gene leukotriene B4 12-hydroxydehydrogenase (Ltb4dh), which was upregulated following 24 h exposure to 63-81 mg IB l(-1). Conclusions: As anticipated, use of the NF clarified the response of Ltb4dh in daphnids exposed to sublethal levels of ibuprofen. Our findings emphasise the importance in toxicogenomics of finding and applying invariant internal QPCR control(s) relevant to the study conditions.

Development and application of in vivo expression technology (IVET) for analysing microbial gene expression in complex environments

Establishing the mechanisms by which microbes interact with their environment, including eukaryotic hosts, is a major challenge that is essential for the economic utilisation of microbes and their products. Techniques for determining global gene expression profiles of microbes, such as microarray analyses, are often hampered by methodological restraints, particularly the recovery of bacterial transcripts (RNA) from complex mixtures and rapid degradation of RNA. A pioneering technology that avoids this problem is In Vivo Expression Technology (IVET). IVET is a 'promoter-trapping' methodology that can be used to capture nearly all bacterial promoters (genes) upregulated during a microbe-environment interaction. IVET is especially useful because there is virtually no limit to the type of environment used (examples to date include soil, oomycete, a host plant or animal) to select for active microbial promoters. Furthermore, IVET provides a powerful method to identify genes that are often overlooked during genomic annotation, and has proven to be a flexible technology that can provide even more information than identification of gene expression profiles. A derivative of IVET, termed resolvase-IVET (RIVET), can be used to provide spatio-temporal information about environment-specific gene expression. More recently, niche-specific genes captured during an IVET screen have been exploited to identify the regulatory mechanisms controlling their expression. Overall, IVET and its various spin-offs have proven to be a valuable and robust set of tools for analysing microbial gene expression in complex environments and providing new targets for biotechnological development.