DNA microarrays for expression profiling

Phosphosite-Specific Antibodies: A Brief Update on Generation and Applications

Phosphate addition is a posttranslational modification of proteins, and this modification can affect the activity and other properties of intracellular proteins. Different animal species can be used to generate phosphosite-specific antibodies as either polyclonals or monoclonals, and each approach offers its own benefits and disadvantages. The validation of phosphosite-specific antibodies requires multiple techniques and tactics to demonstrate their specificity. These antibodies can be used in arrays, flow cytometry, and imaging platforms. The specificity of phosphosite-specific antibodies is vital for their use in proteomics and profiling of disease.

Overview of the generation, validation, and application of phosphosite-specific antibodies

Protein phosphorylation is a universal key posttranslational modification that affects the activity and other properties of intracellular proteins. Phosphosite-specific antibodies can be produced as polyclonals or monoclonals in different animal species, and each approach offers its own benefits and disadvantages. The validation of phosphosite-specific antibodies requires multiple techniques and tactics to demonstrate their specificity. These antibodies can be used in arrays, flow cytometry, and imaging platforms. The specificity of phosphosite-specific antibodies is key for their use in proteomics and profiling of disease.

Diagnostic microarrays in hematologic oncology: applications of high- and low-density arrays

Microarrays have become important tools for high-throughput analysis of gene expression, chromosome aberrations, and gene mutations in cancer cells. In addition to high-density experimental microarrays, low-density, gel-based biochip technology represents a versatile platform for translation of research into clinical practice. Gel-based microarrays (biochips) consist of nanoliter gel drops on a hydrophobic surface with different immobilized biopolymers (primarily nucleic acids and proteins). Because of the high immobilization capacity of the gel, such biochips have a high probe concentration and high levels of fluorescence signals after hybridization, which allow the use of simple, portable detection systems. The notable accuracy of the analysis is reached as a result of the high level of discrimination between positive and negative gel-bound probes. Different applications of biochips in the field of hematologic oncology include analysis of chromosomal translocations in leukemias, diagnostics of T-cell lymphomas, and pharmacogenetics.

Comparative genomics of wild type yeast strains unveils important genome diversity

Background

Genome variability generates phenotypic heterogeneity and is of relevance for adaptation to environmental change, but the extent of such variability in natural populations is still poorly understood. For example, selected Saccharomyces cerevisiae strains are variable at the ploidy level, have gene amplifications, changes in chromosome copy number, and gross chromosomal rearrangements. This suggests that genome plasticity provides important genetic diversity upon which natural selection mechanisms can operate.

Results

In this study, we have used wild-type S. cerevisiae (yeast) strains to investigate genome variation in natural and artificial environments. We have used comparative genome hybridization on array (aCGH) to characterize the genome variability of 16 yeast strains, of laboratory and commercial origin, isolated from vineyards and wine cellars, and from opportunistic human infections. Interestingly, sub-telomeric instability was associated with the clinical phenotype, while Ty element insertion regions determined genomic differences of natural wine fermentation strains. Copy number depletion of ASP3 and YRF1 genes was found in all wild-type strains. Other gene families involved in transmembrane transport, sugar and alcohol metabolism or drug resistance had copy number changes, which also distinguished wine from clinical isolates.

Conclusion

We have isolated and genotyped more than 1000 yeast strains from natural environments and carried out an aCGH analysis of 16 strains representative of distinct genotype clusters. Important genomic variability was identified between these strains, in particular in sub-telomeric regions and in Ty-element insertion sites, suggesting that this type of genome variability is the main source of genetic diversity in natural populations of yeast. The data highlights the usefulness of yeast as a model system to unravel intraspecific natural genome diversity and to elucidate how natural selection shapes the yeast genome.

Anchoring of unmodified oligonucleotides on a chitosan-based array: applications to genotyping and gene expression

Oligonucleotide arrays are one of the most used technologies in genotyping and gene expression experiments. Here, a previously developed chitosan-based platform is characterized in its binding of unmodified oligonucleotides, increasing the cost effectiveness of the microarray production process. The unmodified oligonucleotides on the activated chitosan surface showed the same or better performances than amino-modified probes. Moreover, we show applications in genotyping (a ligation detection reaction experiment on cyanobacteria) and in gene expression (on peach RNA samples). The platform was demonstrated to be reliable, robust, and reproducible for immobilizing unmodified oligonucleotides in high quality oligonucleotide array fabrication.

Reagent preparation and storage for amplification of microarray hybridization targets with a fully automated system

The advent of automated systems for gene expression profiling has accentuated the need for the development of convenient and cost-effective methods for reagent preparation. We have developed a method for the preparation and storage of pre-aliquoted cocktail plates that contain all reagents required for amplification of nucleic acid by reverse transcription and in vitro transcription reactions. Plates can be stored at -80 degrees C for at least 1 month and kept in a hotel at 4 degrees C for at least 24 h prior to use. Microarray data quality generated from these pre-aliquoted reagent plates is not statistically different between cRNA amplified with stored cocktails and cRNA amplified with freshly prepared cocktails. Deployment of pre-aliquoted, stored cocktail plates in a fully automated system not only increases the throughput of amplifying cRNA targets from thousands of RNA samples, but could also considerably reduce reagent costs and potentially improve process robustness.

Molecular profiling of experimental endometriosis identified gene expression patterns in common with human disease

OBJECTIVE

To validate a rat model of endometriosis using complimentary DNA (cDNA) microarrays by identifying common gene expression patterns between experimental and natural disease.

DESIGN

Autotransplantation rat model.

SETTING

Medical school department.

ANIMALS

Female Sprague-Dawley rats.

INTERVENTION(S)

Endometriosis was surgically induced by suturing uterine horn implants next to the small intestine's mesentery. Control rats received sutures with no implants. After 60 days, endometriotic implants and uterine horn were obtained.

MAIN OUTCOME MEASURE(S)

Gene expression levels determined by cDNA microarrays and real-time quantitative polymerase chain reaction (qPCR). The Cy5-labeled cDNA was synthesized from total RNA obtained from endometriotic implants. The Cy3-labeled cDNA was synthesized using uterine RNA from a control rat. Gene expression levels were analyzed after hybridizing experimental and control labeled cDNA to PIQOR (Parallel Identification and Quantification of RNAs) Toxicology Rat Microarrays (Miltenyi Biotec, Cologne, Germany) containing 1,252 known genes. The Cy5/Cy3 ratios were determined, and genes with >2-fold higher or <0.5-fold lower expression levels were selected. Microarray results were validated by QRT-PCR.

RESULT(S)

We observed differential expression of genes previously shown to be up-regulated in patients, including growth factors, inflammatory cytokines/receptors, tumor invasion/metastasis factors, adhesion molecules, and antiapoptotic factors.

CONCLUSION(S)

This study presents evidence in support of using this rat model to study the natural history of endometriosis and to test novel therapeutics for this incurable disease.

Striptease on glass: validation of an improved stripping procedure for in situ microarrays

Microarrays have rapidly become an indispensable tool for gene analysis. Microarray experiments can be cost prohibitive, however, largely due to the price of the arrays themselves. Whilst different methods for stripping filter arrays on membranes have been established, only very few protocols are published for thermal and chemical stripping of microarrays on glass. Most of these protocols for stripping microarrays on glass were developed in combination with specific surface chemistry and different coatings for covalently immobilizing presynthesized DNA in a deposition process. We have developed a method for stripping commercial in situ microarrays using a multi-step procedure. We present a method that uses mild chemical degradation complemented by enzymatic treatment. We took advantage of the differences in biochemical properties of covalently linked DNA oligonucleotides on in situ synthesized microarrays and the antisense cRNA hybridization probes. The success of stripping protocols for microarrays on glass was critically dependent on the type of arrays, the nature of sample used for hybridization, as well as hybridization and washing conditions. The protocol employs alkali hydrolysis of the cRNA, several enzymatic degradation steps using RNAses and Proteinase K, combined with appropriate washing steps. Stripped arrays were rehybridized using the same protocols as for new microarrays. The stripping method was validated with microarrays from different suppliers and rehybridization of stripped in situ arrays yielded comparable results to hybridizations done on unused, new arrays with no significant loss in precision or accuracy. We show that stripping of commercial in situ arrays is feasible and that reuse of stripped arrays gave similar results compared to unused ones. This was true even for biological samples that show only slight differences in their expression profiles. Our analyses indicate that the stripping procedure does not significantly influence data quality derived from post-primary hybridizations. The method is robust, easy to perform, inexpensive, and results after reuse are of comparable accuracy to new arrays.

Identification of molecular markers for endometriosis in blood lymphocytes by using deoxyribonucleic acid microarrays

OBJECTIVE

To identify molecular biomarkers for endometriosis in peripheral blood lymphocytes by using DNA microarrays.

DESIGN

Case-control.

SETTING

Multicenter academic research programs.

PATIENT(S)

Premenopausal women with or without endometriosis, determined by obstetrics and gynecology specialists during surgery. Microarray analysis included six endometriosis patients and five controls; 15 endometriosis patients and 15 controls were analyzed by using real-time reverse-transcription polymerase chain reaction (RT-PCR). Patients with all disease stages were included.

INTERVENTION(S)

Peripheral blood samples were collected by venipuncture.

MAIN OUTCOME MEASURE(S)

The expression levels of mRNAs in blood lymphocytes from endometriosis patients and controls were compared with those of a standard total RNA. Gene expression data were validated by real-time RT-PCR analysis.

RESULT(S)

A gene selection program identified genes that were differentially expressed in samples from endometriosis patients. To validate the gene expression data, the nine most discriminatory genes were analyzed by real-time RT-PCR. Two of the nine genes identified, IL2RG and LOXL1, were shown to be significantly differentially expressed.

CONCLUSION(S)

This is the first report of genes that are differentially expressed in peripheral blood lymphocytes of patients with endometriosis, which may provide important clues regarding the pathogenesis of this disease. Moreover, they could be considered potential targets for noninvasive diagnostic assays for endometriosis and need to be validated in a larger population.

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.

Genome-wide expression profiling and identification of gene activities during early flower development in Arabidopsis

We have used oligonucleotide microarrays to detect Arabidopsis gene expression during early flower development. Among the 22,746 genes represented on the Affymetrix ATH1 chip, approximately 14,660 (approximately 64.5%) genes were expressed with signal intensity at or more than 50 in each of the six organs/structures examined, including young inflorescences (floral stages 1-9), stage-12 floral buds, developing siliques, leaves, stems, and roots. 17,583 genes were expressed with an intensity at or above 50 in at least one tissue, including 12,245 genes that were expressed in all the six tissues. Comparison of genes expressed between young inflorescence or stage-12 floral buds with other tissues suggests that relatively large numbers of genes are expressed at similar levels in tissues that are related morphologically and/or developmentally, as supported by a cluster analysis with data from two other studies. Further analysis of the genes preferentially expressed in floral tissues has uncovered new genes potentially involved in Arabidopsis flower development. One hundred and four genes were determined to be preferentially expressed in young inflorescences, including 22 genes encoding putative transcription factors. We also identified 105 genes that were preferentially expressed in three reproductive structures (the young inflorescences, stage-12 floral buds and developing siliques), when compared with the vegetative tissues. RT-PCR results of selected genes are consistent with the results from these microarrays and suggest that the relative signal intensities detected with the Affymetrix microarray are reliable estimates of gene expression.

Hyperspectral microarray scanning: impact on the accuracy and reliability of gene expression data

Background

Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions.

Results

Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images.

Conclusion

Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of quality control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring.

Purmorphamine induces osteogenesis by activation of the hedgehog signaling pathway

Previously, a small molecule, purmorphamine, was identified that selectively induces osteogenesis in multipotent mesenchymal progenitor cells. In order to gain insights into the mechanism of action of purmorphamine, high-density oligonucleotide microarrays were used to profile gene expression in multipotent mesenchymal progenitor cells treated with either purmorphamine or bone morphogenetic protein-4 (BMP-4). In contrast to BMP-4 treatment, purmorphamine activates the Hedgehog (Hh) signaling pathway, resulting in the up- and downregulation of its downstream target genes, including Gli1 and Patched. Moreover, the known Hh signaling antagonists, cyclopamine and forskolin, completely block the osteogenesis and Glimediated transcription induced by purmorphamine. These results demonstrate that purmorphamine is a small molecule agonist of Hedgehog signaling, and it may ultimately be useful in the treatment of bone-related disease and neurodegenerative disease.

Evaluation of 50-mer oligonucleotide arrays for detecting microbial populations in environmental samples

Microarrays fabricated with oligonucleotides longer than 40 bp have been introduced for monitoring whole genome expression but have not been evaluated with environmental samples. To determine the potential of this type of microarray for environmental studies, a 50-mer oligonucleotide microarray was constructed using 763 genes involved in nitrogen cycling: nitrite reductase (nirS and nirK), ammonia monooxygenase (amoA), nitrogenase (nifH), methane monooxygenase (pmoA), and sulfite reductase (dsrAB) from public databases and our own sequence collections. The comparison of the sequences from pure cultures indicated that the developed microarrays could provide species-level resolution for analyzing microorganisms involved in nitrification, denitrification, nitrogen fixation, methane oxidation, and sulfite reduction. Sensitivity tests suggested that the 50-mer oligonucleotide arrays could detect dominant populations in the environments, although sensitivity still needs to be improved. A significant quantitative relationship was also obtained with a mixture of DNAs from eight different bacteria. These results suggest that the 50-mer oligonucleotide array can be used as a specific and quantitative parallel tool for the detection of microbial populations in environmental samples.

Identification of genetic networks

In this report, we propose the use of structural equations as a tool for identifying and modeling genetic networks and genetic algorithms for searching the most likely genetic networks that best fit the data. After genetic networks are identified, it is fundamental to identify those networks influencing cell phenotypes. To accomplish this task we extend the concept of differential expression of the genes, widely used in gene expression data analysis, to genetic networks. We propose a definition for the differential expression of a genetic network and use the generalized T2 statistic to measure the ability of genetic networks to distinguish different phenotypes. However, describing the differential expression of genetic networks is not enough for understanding biological systems because differences in the expression of genetic networks do not directly reflect regulatory strength between gene activities. Therefore, in this report we also introduce the concept of differentially regulated genetic networks, which has the potential to assess changes of gene regulation in response to perturbation in the environment and may provide new insights into the mechanism of diseases and biological processes. We propose five novel statistics to measure the differences in regulation of genetic networks. To illustrate the concepts and methods for reconstruction of genetic networks and identification of association of genetic networks with function, we applied the proposed models and algorithms to three data sets.

In situ synthesis of oligonucleotide microarrays

This contribution presents a brief overall look of the methods for the preparation of various types of DNA microarrays and a thorough examination of the methods for in situ synthesis of oligonucleotide microarrays.

Hippocampal gene expression profiling across eight mouse inbred strains: towards understanding the molecular basis for behaviour

Mouse inbred strains differ in many aspects of their phenotypes, and it is known that gene expression does so too. This gives us an opportunity to isolate the genetic aspect of variation in expression and compare it to other phenotypic variables. We have investigated these issues using an eight-strain expression profile comparison with four replicates per strain on Affymetrix MGU74av2 GeneChips focusing on one well-defined brain tissue (the hippocampus). We identified substantial strain-specific variation in hippocampal gene expression, with more than two hundred genes showing strain differences by a very conservative criterion. Many such genetically driven differences in gene expression are likely to result in functional differences including differences in behaviour. A large panel of inbred strains could be used to identify genes functionally involved in particular phenotypes, similar to genetic correlation. The genetic correlation between expression profiles and function is potentially very powerful, especially given the current large-scale generation of phenotypic data on multiple strains (the Mouse Phenome Project). As an example, the strongest genetic correlation between more than 200 probe sets showing significant differences among our eight inbred strains and a ranking of these strains by aggression phenotype was found for Comt, a gene known to be involved in aggression.

Identification of Genetic Networks

In this report, we propose the use of structural equations as a tool for identifying and modeling genetic networks and genetic algorithms for searching the most likely genetic networks that best fit the data. After genetic networks are identified, it is fundamental to identify those networks influencing cell phenotypes. To accomplish this task we extend the concept of differential expression of the genes, widely used in gene expression data analysis, to genetic networks. We propose a definition for the differential expression of a genetic network and use the generalized T  2 statistic to measure the ability of genetic networks to distinguish different phenotypes. However, describing the differential expression of genetic networks is not enough for understanding biological systems because differences in the expression of genetic networks do not directly reflect regulatory strength between gene activities. Therefore, in this report we also introduce the concept of differentially regulated genetic networks, which has the potential to assess changes of gene regulation in response to perturbation in the environment and may provide new insights into the mechanism of diseases and biological processes. We propose five novel statistics to measure the differences in regulation of genetic networks. To illustrate the concepts and methods for reconstruction of genetic networks and identification of association of genetic networks with function, we applied the proposed models and algorithms to three data sets.

Molecular markers in cervical cytology

It is expected that in the near future, the high sensitivity of array-based technologies and identification of panels of molecular fingerprints that are specific for each disease process will allow the pathologist to analyze cytologic samples and tissue biopsies by these technologies in conjunction with morphologic evaluation. This approach could lead to a new era in diagnosis and patient management, where each patient may receive individualized treatment according to the molecular characteristics of the disease that are obtained from a minute amount of tissue. Therefore, it is important for pathologists and other clinical specialists to have an understanding of these molecular technologies. It is hoped that this article will allow practitioners to incorporate these concepts into their training, and, eventually, into their daily practice.

Genome comparisons and analysis

As we enter the post-genomic era, with the accelerating availability of complete genome sequences, new theoretical approaches and new experimental techniques, our ability to dissect cellular processes at the molecular level continues to expand. Recent advances include the application of RNA interference methods to characterize loss-of-function phenotype genes in higher eukaryotes, comparative analysis of the human and mouse genome sequences, and methods for reconciling contradictory phylogenetic reconstructions. New developments feed into the increasingly rich content of databases such as the COG database. The next phase of research will be increasingly dominated by efforts to integrate the deluge of data into our understanding of biological systems.

Application of high-resolution capillary array electrophoresis with automated fraction collection for GeneCalling trade mark analysis of the yeast genomic DNA

Capillary array instrument was applied to transcript profiling of the yeast genomic DNA using GeneCalling trade mark chemistry. The instrument integrated a 12-capillary array for DNA separation with a replaceable sieving matrix, laser-induced fluorescence detection and an automated microfraction collector. The DNA fractions, exiting the separation capillaries, were continuously deposited in a 1536-well collection plate made of agarose gel. DNA fragments recovered from selected fractions were cloned and then sequenced. Over 80% of theoretically predicted fragments could be recovered in the collected fractions, cloned and sequenced with an average redundancy of threefold. Excellent correlation of the experimentally obtained sequences with the theoretically predicted gene fragments demonstrated the suitability of capillary array electrophoresis for micropreparative recovery of DNA fragments. This approach, useful especially for rapid DNA expression profiling of unknown genes for nonsequenced organisms, demonstrates the practical capability of the prototype multicapillary fraction collector.

Genetic predictors of cardiovascular disease: the use of chip technology

Cardiovascular disease, a primary cause of mortality in the United States, has a complex pathologic process involving many genes. The high-throughput technology (microarray or "DNA chip") used to decipher the human genome is now being employed to identify key genes in its development. A study focusing on candidate genes associated with premature cardiovascular disease discovered that missense variations in the thrombospondin 1 and 4 genes were associated with premature coronary artery disease, while a mutation in the non-coding region of a thrombospondin 2 gene imparts protection from developing heart disease. Although the clinical implications of microarray technology are still under investigation, this research may lead to a diagnostic test to determine a patient's risk for developing heart disease.

EST analysis of mRNAs expressed in neurula of Chinese amphioxus

Amphioxus, a cephalochordate, is the closest living relative to the vertebrates. In order to investigate the molecular mechanisms of the early embryogenesis of amphioxus, we constructed a neurula embryo cDNA library of Chinese amphioxus (Branchiostoma belcheri tsingtauense) and generated 5235 expressed sequenced tags in the present study. The initial ESTs consisted of 638 clusters and 1855 singletons, which revealed approximately 2493 unique genes in the data set. Of these sequences, 35.52% ESTs matched to known genes, 12.76% matched to other ESTs, and 51.71% had no match to any known sequences in GenBank. Interestingly we found homologous genes related to neural development and human disease. Bioinformatic analysis showed the direct evidence that the gene homologue found only in vertebrates in previous studies also exists in the amphioxus genome. This study provides a preliminary view of the gene information involved in the development of neurula embryos of Chinese amphioxus and helps our understanding of vertebrate evolution at gene level.

DNA microarray technology: devices, systems, and applications

In this review, recent advances in DNA microarray technology and their applications are examined. The many varieties of DNA microarray or DNA chip devices and systems are described along with their methods for fabrication and their use. This includes both high-density microarrays for high-throughput screening applications and lower-density microarrays for various diagnostic applications. The methods for microarray fabrication that are reviewed include various inkjet and microjet deposition or spotting technologies and processes, in situ or on-chip photolithographic oligonucleotide synthesis processes, and electronic DNA probe addressing processes. The DNA microarray hybridization applications reviewed include the important areas of gene expression analysis and genotyping for point mutations, single nucleotide polymorphisms (SNPs), and short tandem repeats (STRs). In addition to the many molecular biological and genomic research uses, this review covers applications of microarray devices and systems for pharmacogenomic research and drug discovery, infectious and genetic disease and cancer diagnostics, and forensic and genetic identification purposes. Additionally, microarray technology being developed and applied to new areas of proteomic and cellular analysis are reviewed.

DNA chips for yeast biotechnology. The case of wine yeasts

The yeast Saccharomyces cerevisiae is one of the most popular model organisms. It was the first eukaryote whose genome was sequenced. Since then many functional analysis projects have tried to find the function of many genes and to understand its metabolism in a holistic way. Apart from basic science this microorganism is of great interest in several biotechnology processes, such as winemaking. Only global studies of the cell as a whole can help us to understand many of the technical problems facing winemaking. DNA chip technology is one of the most promising tools for the analysis of cell physiology. Yeast has been the model organism for the development of this technique. Many of the studies can be applied to improve our knowledge of wine strains. Nevertheless wine strains are quite different in some aspects from the laboratory reference strains so a particular study of wine strains and especially during the winemaking process is needed. During the past two years some groups have started this study and the first results have been published. We review here the current state of the knowledge of wine yeast and the capacity of DNA chip technology for its improvement.

Optimization of oligonucleotide-based DNA microarrays

Oligonucleotide-based DNA microarrays are becoming increasingly useful for the analysis of gene expression and single nucleotide polymorphisms. Here we report a systematic study of the sensitivity, specificity and dynamic range of microarray signals and their dependence on the labeling and hybridization conditions as well as on the length, concentration, attachment moiety and purity of the oligonucleotides. Both a controlled set of in vitro synthesized transcripts and RNAs from biological samples were used in these experiments. An algorithm is presented that allows the efficient selection of oligonucleotides able to discriminate a single nucleotide mismatch. Critical parameters for various applications are discussed based on statistical analysis of the results. These data will facilitate the design and standardization of custom-made microarrays applicable to gene expression profiling and sequencing analyses.

Microarrays in hematology

Microarrays are fast becoming routine tools for the high-throughput analysis of gene expression in a wide range of biologic systems, including hematology. Although a number of approaches can be taken when implementing microarray-based studies, all are capable of providing important insights into biologic function. Although some technical issues have not been resolved, microarrays will continue to make a significant impact on hematologically important research.

Identification of up-regulated Ras-like GTPase, Rap1b, by suppression subtractive hybridization

BACKGROUND

Diabetic nephropathy accounts for over 30% of the end-stage renal disease (ESRD). A number of defined mechanisms and molecules that are involved in its pathogenesis are known, while others remain to be identified.

METHODS

Suppression subtraction hybridization (SSH)-polymerase chain reaction (PCR) was employed to search for new genes that may be relevant to the pathogenesis of diabetic nephropathy during embryonic development, the time when the kidney is most susceptible to various forms of stress. A diabetic state was induced in pregnant mice at day-13 of gestation by administration of streptozotocin. The kidneys of newborn mice with blood glucose level> 200 mg/dL were harvested, mRNA isolated and subjected to SSH-PCR. Several differentially expressed cDNA fragments with up-regulated expression were isolated. One of the cDNA fragments had homology with human Ras-like guanine 5'-triphosphate (GTPase), Rap1b gene. By utilizing the lambdaZAP II mouse cDNA library and SMART RACE amplification, a full-length Rap1b cDNA was isolated. A recombinant protein was generated in pET15b bacterial expression system. An anti-Rap1b antibody was raised in rabbits by immunizing them with the fusion protein, and its specificity was confirmed by Western blot analysis.

RESULTS

Rap1b cDNA had an open reading frame of 552 bp with a predicted putative protein size of approximately 21 kD. In vitro translation verified the authentication of the Rap1b cDNA clone. Northern blot analyses revealed a single approximately 2.3 kb Rap1b mRNA transcript. Its expression was up-regulated in several tissues, including the kidney of newborn diabetic mice. The degree of up-regulation of Rap1b mRNA expression was proportional to the blood glucose levels. Western blot analyses confirmed the hyperglycemia-induced up-regulation of the Rap1b expression. In situ hybridization and immunofluorescence studies revealed that Rap1b was expressed in the inner medullary collecting tubules. During hyperglycemia, its expression was accentuated and extended into the outer medullary and cortical collecting tubules. Similar up-regulation of Rap1b was observed when embryonic kidneys, harvested at day-13 of gestation, were exposed to high glucose ambience.

CONCLUSION

The data suggest that Rap1b, a GTP-binding protein that plays a critical role in various signaling intracellular events, is another molecule that may be relevant to the pathobiology of diabetic nephropathy.

From symptomatic treatments to causative therapy?

The search for genes that predispose individuals to develop common chronic diseases such as asthma, diabetes and Alzheimer's promises to give insights into their molecular pathogenesis. This will lead to the development of therapies that modulate the pathology, rather than the physiology of these diseases. As academia and the pharmaceutical industry increasingly focus on this challenge, the genetic dissection of Alzheimer's is spearheading attempts to shift the therapeutic paradigm away from symptomatic to curative treatments.