Genome-directed primers for selective labeling of bacterial transcripts for DNA microarray analysis

DNA microarrays have the ability to analyze the expression of thousands of the same set of genes under at least two different experimental conditions. However, DNA microarrays require substantial amounts of RNA to generate the probes, especially when bacterial RNA is used for hybridization (50 microg of bacterial total RNA contains approximately 2 microg of mRNA). We have developed a computer-based algorithm for prediction of the minimal number of primers to specifically anneal to all genes in a given genome. The algorithm predicts, for example, that 37 oligonucleotides should prime all genes in the Mycobacterium tuberculosis genome. We tested the usefulness of the genome-directed primers (GDPs) in comparison to random primers for gene expression profiling using DNA microarrays. Both types of primers were used to generate fluorescent-labeled probes and to hybridize to an array of 960 mycobacterial genes. Compared to random-primer probes, the GDP probes were more sensitive and more specific, especially when mammalian RNA samples were spiked with mycobacterial RNA. The GDPs were used for gene expression profiling of mycobacterial cultures grown to early log or stationary growth phases. This approach could be useful for accurate genome-wide expression analysis, especially for in vivo gene expression profiling, as well as directed amplification of sequenced genomes.     

伤寒沙门菌基因组DNA芯片的制备与基因表达谱分析应用

伤寒沙门菌是一种具有鞭毛的革兰阴性人类肠道致病菌,也是一种重要的原核生物研究用模式菌．基因组芯片能够系统、全面且高效地观察生物的基因表达及进行基因组结构比较．利用伤寒沙门菌现有的全基因组序列,以Ty2菌株的基因组为基准,选取CT18菌株和z66阳性菌株的特异性蛋白编码基因,设计特异性引物,经PCR有效扩增出4 201个基因,产物纯化后点样于多聚赖氨酸玻片制备伤寒沙门菌基因组DNA芯片,并验证了芯片样点位次与效果．通过对基因表达谱分析的各种条件进行优化,建立相应的表达谱分析方法,并用于比较伤寒沙门菌野生株在高渗、低渗条件下的基因表达差异,结果与以前的报道基本一致．结果表明,成功建立了伤寒沙门菌基因组DNA芯片及表达谱分析方法,可为有关伤寒沙门菌基因表达调控及致病性机理、进化和基因多样性等方面的深入研究提供有效的技术支持．     

DNA microarrays in clinical cancer research

The recent sequencing of the human genome, coupled with advances in biotechnology, is enabling the comprehensive molecular "profiling" of human tissues. In particular, DNA microarrays are powerful tools for obtaining global views of human tumor gene expression. Complex information from tumor "expression profiling" studies can, in turn, be used to create novel molecular cancer diagnostics. We discuss the utility of DNA microarray-based tumor profiling in clinical cancer research, highlight some important recent studies, and identify future avenues of research in this evolving field.     

A computational framework for optimal masking in the synthesis of oligonucleotide microarrays

High-throughput genomic technologies are revolutionizing modern biology. In particular, DNA microarrays have become one of the most powerful tools for profiling global mRNA expression in different tissues and environmental conditions, and for detecting single nucleotide polymorphisms. The broad applicability of gene expression profiling to the biological and medical realms has generated expanding demand for mass production of microarrays, which in turn has created considerable interest in improving the cost effectiveness of microarray fabrication techniques. We have developed the computational framework for an optimal synthesis strategy for oligonucleotide microarrays. The problem was introduced by Hubbell et al. Here, we formalize the problem, obtain precise bounds on its complexity and devise several computational solutions.     

It's easy to build your own microarrayer!

DNA microarrays are becoming the tool of choice for microbial gene-expression profiling and genotypic analysis. The construction of a gridding robot for the 'in-house' production of microarrays is a choice worth considering, and offers distinct advantages over other options in terms of cost effectiveness and scale. Having built our own robot, we want to dispel some of the myths that might be associated with such a project, as well as provide practical advice for potential builders in the UK and Europe.     

A consolidated approach to analyzing data from high-throughput protein microarrays with an application to immune response profiling in humans.

Motivation: DNA microarrays are a well-known and established technology in biological and pharmaceutical research providing a wealth of information essential for understanding biological processes and aiding drug development. Protein microarrays are quickly emerging as a follow-up technology, which will also begin to experience rapid growth as the challenges in protein to spot methodologies are overcome. Like DNA microarrays, their protein counterparts produce large amounts of data that must be suitably analyzed in order to yield meaningful information that should eventually lead to novel drug targets and biomarkers. Although the statistical management of DNA microarray data has been well described, there is no available report that offers a successful consolidated approach to the analysis of high-throughput protein microarray data. We describe the novel application of a statistical methodology to analyze the data from an immune response profiling assay using human protein microarray with over 5000 proteins on each chip.     

Recent advances of protein microarrays

Technological innovations and novel applications have greatly advanced the field of protein microarrays. Over the past two years, different types of protein microarrays have been used for serum profiling, protein abundance determinations, and identification of proteins that bind DNA or small compounds. However, considerable development is still required to ensure common quality standards and to establish large content repertoires. Here, we summarize applications available to date and discuss recent technological achievements and efforts on standardization.     

Stripping custom microRNA microarrays and the lessons learned about probe-slide interactions

Microarrays have been used extensively in gene expression profiling and genotyping studies. To reduce the high cost and enhance the consistency of microarray experiments, it is often desirable to strip and reuse microarray slides. Our genome-wide analysis of microRNA expression involves the hybridization of fluorescently labeled nucleic acids to custom-made, spotted DNA microarrays based on GAPSII-coated slides. We describe here a simple and effective method to regenerate such custom microarrays that uses a very low-salt buffer to remove labeled nucleic acids from microarrays. Slides can be stripped and reused multiple times without significantly compromising data quality. Moreover, our analyses of the performance of regenerated slides identifies parameters that influence the attachment of oligonucleotide probes to GAPSII slides, shedding light on the interactions between DNA and the microarray surface and suggesting ways in which to improve the design of oligonucleotide probes.     

Gene Expression Profiling of Seizure Disorders

Seizure disorders affect a significant percentage of the population, and researchers worldwide continue to work toward a better understanding of what initiates, propagates, and results from aberrant and excessive neuronal excitation. During the past two decades, one aspect of this research effort has been to describe the effects of seizure activity upon neuronal gene expression, with hopes of identifying the molecular mechanisms that underlie subsequent changes in cell function and survival. Here we review this body of work from the perspective of how these gene profiling efforts have evolved, starting with one-by-one analyses of specific gene targets to the more recent use of DNA microarrays to survey literally thousands of genes simultaneously. With regard to the latter, we present some of our own work that suggests that molecular mechanisms contributing to normal brain development are reiterated during seizure-induced network reorganization.     

News in Brief

Protein microarrays are versatile tools for parallel, miniaturized screening of binding events involving large numbers of immobilized proteins in a time- and cost-effective manner. They are increasingly applied for high-throughput protein analyses in many research areas, such as protein interactions, expression profiling and target discovery. While conventionally made by the spotting of purified proteins, recent advances in technology have made it possible to produce protein microarrays through in situ cell-free synthesis directly from corresponding DNA arrays. This article reviews recent developments in the generation of protein microarrays and their applications in proteomics and diagnostics.     

Q-RRBS: a quantitative reduced representation bisulfite sequencing method for single-cell methylome analyses

Reduced representation bisulfite sequencing (RRBS) is a powerful method of DNA methylome profiling that can be applied to single cells. However, no previous report has described how PCR-based duplication-induced artifacts affect the accuracy of this method when measuring DNA methylation levels. For quantifying the effects of duplication-induced artifacts on methylome profiling when using ultra-trace amounts of starting material, we developed a novel method, namely quantitative RRBS (Q-RRBS), in which PCR-induced duplication is excluded through the use of unique molecular identifiers (UMIs). By performing Q-RRBS on varying amounts of starting material, we determined that duplication-induced artifacts were more severe when small quantities of the starting material were used. However, through using the UMIs, we successfully eliminated these artifacts. In addition, Q-RRBS could accurately detect allele-specific methylation in absence of allele-specific genetic variants. Our results demonstrate that Q-RRBS is an optimal strategy for DNA methylation profiling of single cells or samples containing ultra-trace amounts of cells.     

Protein profiling comes of age

Ever since DNA microarrays were first applied to the quantitation of RNA levels, there has been considerable interest in generating a protein homolog that can be used to assay cellular protein expression. A recent paper describes the first microarray that can be used for such protein profiling.     

Strategy for the design of custom cDNA microarrays

DNA microarrays are valuable but expensive tools for expression profiling of cells, tissues, and organs. The design of custom microarrays leads to cost reduction without necessarily compromising their biological value. Here we present a strategy for designing custom cDNA microarrays and constructed a microarray for mouse immunology research (ImmunoChip). The strategy used interrogates expressed sequence tag databases available in the public domain but overcomes many of the problems encountered. Immunologically relevant clusters were selected based on the expression of expressed sequence tags in relevant libraries. Selected clusters were organized in modules, and the best representative clones were identified. When tested, this microarray was found to have minimal clone identity errors or phage contamination and identified molecular signatures of lymphoid cell lines. Our proposed design of custom microarrays avoids probe redundancy, allows the organization of the chip to optimize chip production, and reduces microarray production costs. The strategy described is also useful for the design of oligonucleotide microarrays.