Microarray technology: beyond transcript profiling and genotype analysis

In situ synthesis of DNA microarray on functionalized cyclic olefin copolymer substrate

Thermoplastic materials such as cyclic-olefin copolymers (COC) provide a versatile and cost-effective alternative to the traditional glass or silicon substrate for rapid prototyping and industrial scale fabrication of microdevices. To extend the utility of COC as an effective microarray substrate, we developed a new method that enabled for the first time in situ synthesis of DNA oligonucleotide microarrays on the COC substrate. To achieve high-quality DNA synthesis, a SiO(2) thin film array was prepatterned on the inert and hydrophobic COC surface using RF sputtering technique. The subsequent in situ DNA synthesis was confined to the surface of the prepatterned hydrophilic SiO(2) thin film features by precision delivery of the phosphoramidite chemistry using an inkjet DNA synthesizer. The in situ SiO(2)-COC DNA microarray demonstrated superior quality and stability in hybridization assays and thermal cycling reactions. Furthermore, we demonstrate that pools of high-quality mixed-oligos could be cleaved off the SiO(2)-COC microarrays and used directly for construction of DNA origami nanostructures. It is believed that this method will not only enable synthesis of high-quality and low-cost COC DNA microarrays but also provide a basis for further development of integrated microfluidics microarrays for a broad range of bioanalytical and biofabrication applications.

Effects of antemortem and postmortem variables on human brain mRNA quality: a BrainNet Europe study

Well-characterized and preserved human brain tissue that is prepared and stored in brain banks is an essential resource for research in neurological diseases. This study examined the quality of human brain postmortem tissue from multiple laboratories within the BrainNet Europe brain bank network to identify all possible confounding variables and determine how they may affect RNA quality. Antemortem and postmortem information was retrospectively collected for a large cohort of samples. Total RNA was isolated from anatomically defined brain regions using a standardized procedure; RNA quality was assessed using an Agilent 2100 Bioanalyzer. No significant difference in RNA quality was observed in 6 different brain regions. RNA quality deteriorated with increasing numbers of antemortem events such as hospitalization, coma, respiratory illness, and the use of artificial ventilation; accumulation of such events was associated with elevated hypoxia-inducible factor 1 alpha mRNA expression. Brain pH was found to be a good indicator of RNA quality. There was no correlation of postmortem delay with cerebrospinal fluid pH or RNA quality overall, but some individual RNAs decreased in quality with antemortem events and with postmortem delay. RNA quality did not affect total RNA yield. Determining the factors that are best predictors of RNA quality can help brain banks with selection criteria for storing high-quality brain tissue for research.

Comparative analysis of missing value imputation methods to improve clustering and interpretation of microarray experiments

Background

Microarray technologies produced large amount of data. In a previous study, we have shown the interest of k-Nearest Neighbour approach for restoring the missing gene expression values, and its positive impact of the gene clustering by hierarchical algorithm. Since, numerous replacement methods have been proposed to impute missing values (MVs) for microarray data. In this study, we have evaluated twelve different usable methods, and their influence on the quality of gene clustering. Interestingly we have used several datasets, both kinetic and non kinetic experiments from yeast and human.

Results

We underline the excellent efficiency of approaches proposed and implemented by Bo and co-workers and especially one based on expected maximization (EM_array). These improvements have been observed also on the imputation of extreme values, the most difficult predictable values. We showed that the imputed MVs have still important effects on the stability of the gene clusters. The improvement on the clustering obtained by hierarchical clustering remains limited and, not sufficient to restore completely the correct gene associations. However, a common tendency can be found between the quality of the imputation method and the gene cluster stability. Even if the comparison between clustering algorithms is a complex task, we observed that k-means approach is more efficient to conserve gene associations.

Conclusions

More than 6.000.000 independent simulations have assessed the quality of 12 imputation methods on five very different biological datasets. Important improvements have so been done since our last study. The EM_array approach constitutes one efficient method for restoring the missing expression gene values, with a lower estimation error level. Nonetheless, the presence of MVs even at a low rate is a major factor of gene cluster instability. Our study highlights the need for a systematic assessment of imputation methods and so of dedicated benchmarks. A noticeable point is the specific influence of some biological dataset.

Integrative oncogenomic analysis of microarray data in hematologic malignancies

During the last decade, gene expression microarrays and array-based comparative genomic hybridization (array-CGH) have unraveled the complexity of human tumor genomes more precisely and comprehensively than ever before. More recently, the simultaneous assessment of global changes in messenger RNA (mRNA) expression and in DNA copy number through "integrative oncogenomic" analyses has allowed researchers the access to results uncovered through the analysis of one-dimensional data sets, thus accelerating cancer gene discovery. In this chapter, we discuss the major contributions of DNA microarrays to the study of hematological malignancies, focusing on the integrative oncogenomic approaches that correlate genomic and transcriptomic data. We also present the basic aspects of these methodologies and their present and future application in clinical oncology.

Detection and differentiation of four poultry diseases using asymmetric reverse transcription polymerase chain reaction in combination with oligonucleotide microarrays

Asymmetric reverse transcription polymerase chain reaction (RT-PCR) and microarrays were combined to distinguish 4 viruses, including Avian influenza virus (AIV), Newcastle disease virus (NDV), Infectious bronchitis virus (IBV), and Infectious bursal disease virus (IBDV), and hemagglutinin (HA) subtypes H5, H7, and H9, and neuraminidase (NA) subtypes N1 and N2 of AIV. The AIV matrix protein (M), and HA and NA genes, IBV nucleoprotein (NP) gene, NDV NP gene, and IBDV A fragment gene were cloned into plasmids. These genes were amplified from these positive recombinant plasmids, which included the inserted target genes by PCR. The PCR products were purified and printed on the amino-modified slides as the probes. RNA was extracted from samples and labeled by asymmetric RT-PCR using a cyanine (Cy)3-labeled primers. The labeled complementary (c)DNA was hybridized to the probes immobilized on the glass slides. After hybridization, the microarrays were scanned, and the hybridization pattern agreed perfectly with the known location of each probe. No cross-hybridization could be detected. Results demonstrated that microarray based on asymmetric RT-PCR is an effective way to distinguish AIV, IBV, NDV, and IBDV simultaneously.

Proteomics, pathway array and signaling network-based medicine in cancer

Cancer is a multifaceted disease that results from dysregulated normal cellular signaling networks caused by genetic, genomic and epigenetic alterations at cell or tissue levels. Uncovering the underlying protein signaling network changes, including cell cycle gene networks in cancer, aids in understanding the molecular mechanism of carcinogenesis and identifies the characteristic signaling network signatures unique for different cancers and specific cancer subtypes. The identified signatures can be used for cancer diagnosis, prognosis, and personalized treatment. During the past several decades, the available technology to study signaling networks has significantly evolved to include such platforms as genomic microarray (expression array, SNP array, CGH array, etc.) and proteomic analysis, which globally assesses genetic, epigenetic, and proteomic alterations in cancer. In this review, we compared Pathway Array analysis with other proteomic approaches in analyzing protein network involved in cancer and its utility serving as cancer biomarkers in diagnosis, prognosis and therapeutic target identification. With the advent of bioinformatics, constructing high complexity signaling networks is possible. As the use of signaling network-based cancer diagnosis, prognosis and treatment is anticipated in the near future, medical and scientific communities should be prepared to apply these techniques to further enhance personalized medicine.

Three-dimensional surface patterning by DNA-modifying enzymes

Self-assembled patterned multilayers may be fabricated using DNA monolayers and the orchestrated reactions of DNA-modifying enzymes. To demonstrate this approach, DNA monolayers were formed on silicon and cleaved quantitatively with a restriction enzyme. Subsequently, fluorescently labeled nucleotides were covalently incorporated to the cleaved DNA. Nucleotide addition was shown to be highly selective according to the sequence at the cleavage site, and no nonspecific adsorption to the surface was observed. The dual action of the DNA-modifying enzymes was quantitative and could be utilized in the fabrication of multilayered structures. Other DNA-modifying enzymes can be exploited in this manner to enrich the repertoire of self-assembly supramolecular structure fabrication.

The transcriptome of spermatozoa used in homologous intrauterine insemination varies considerably between samples that achieve pregnancy and those that do not

OBJECTIVE

To differentiate transcripts' expression in the sperm from patients who achieved pregnancy in their first IUI cycle from those who did not. Basic sperm analysis is limited to forecasting pregnancies by means of assisted reproduction. New assays, such as microarray analysis, are potential predictive tools for this purpose.

DESIGN

Nested case-control study.

SETTING

University-affiliated private setting.

PATIENT(S)

Twenty sperm samples were obtained from infertile males undergoing their first IUI cycle with healthy partners. Sperm samples with which pregnancy was achieved (P; n=10) and those with which it was not achieved (NP; n=10) were identified and their respective messenger RNA expression profiles were compared.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Using microarrays, global genome expression was compared in pooled samples from each group. Results were evaluated to detect differentially expressed transcripts (TDEs; FC>2; P<0.05) and to identify those transcripts that were expressed in only one of the groups (exclusive transcripts [ETs]).

RESULT(S)

In group P, 756 TDEs presented increased expression, whereas 194 in group NP were found to be overexpressed. Furthermore, we found 741 ETs that were expressed only in group P and 976 that were expressed only in group NP.

CONCLUSION(S)

Results reveal profound differences between expression profiles of sperm samples that impregnate successfully and those that do not. These differences might improve the predictive power of sperm evaluation to estimate IUI success by complementing the basic sperm analysis.

Profiling protein thiol oxidation in tumor cells using sulfenic acid-specific antibodies

Hydrogen peroxide (H2O2) functions as a second messenger that can activate cell proliferation through chemoselective oxidation of cysteine residues in signaling proteins. The connection between H2O2 signaling, thiol oxidation, and activation of growth pathways has emerged as fertile ground for the development of strategies for cancer treatment. Central to achieving this goal is the development of tools and assays that facilitate characterization of the molecular events associated with tumorigenesis and evaluation of patient response to therapy. Here we report on the development of an immunochemical method for detecting sulfenic acid, the initial oxidation product that results when a thiolate reacts with H2O2. For this approach, the sulfenic acid is derivatized with a chemical tag to generate a unique epitope for recognition. The elicited antibody is exquisitely specific, context-independent, and capable of visualizing sulfenic acid formation in cells. Applying this approach to several systems, including cancer cell lines, shows it can be used to monitor differences in thiol redox status and reveals a diverse pattern of sulfenic acid modifications across different subtypes of breast tumors. These studies demonstrate a general strategy for producing antibodies against a specific oxidation state of cysteine and show the utility of these reagents for profiling thiol oxidation associated with pathological conditions such as breast cancer.

Applications of genomics in melanoma oncogene discovery

The identification of recurrent alterations in the melanoma genome has provided key insights into the biology of melanoma genesis and progression. These discoveries have come about as a result of the systematic deployment and integration of diverse genomic technologies, including DNA sequencing, chromosomal copy number analysis, and gene expression profiling. Here, the discoveries of several key melanoma oncogenes affecting critical cell pathways are described and the role played by evolving genomics technologies in melanoma oncogene discovery is examined. These advances are being exploited to improve prognosis and treatment of melanoma patients through the development of genome-based diagnostic and targeted therapeutic avenues.

Microfabricated microbial fuel cell arrays reveal electrochemically active microbes

Microbial fuel cells (MFCs) are remarkable "green energy" devices that exploit microbes to generate electricity from organic compounds. MFC devices currently being used and studied do not generate sufficient power to support widespread and cost-effective applications. Hence, research has focused on strategies to enhance the power output of the MFC devices, including exploring more electrochemically active microbes to expand the few already known electricigen families. However, most of the MFC devices are not compatible with high throughput screening for finding microbes with higher electricity generation capabilities. Here, we describe the development of a microfabricated MFC array, a compact and user-friendly platform for the identification and characterization of electrochemically active microbes. The MFC array consists of 24 integrated anode and cathode chambers, which function as 24 independent miniature MFCs and support direct and parallel comparisons of microbial electrochemical activities. The electricity generation profiles of spatially distinct MFC chambers on the array loaded with Shewanella oneidensis MR-1 differed by less than 8%. A screen of environmental microbes using the array identified an isolate that was related to Shewanella putrefaciens IR-1 and Shewanella sp. MR-7, and displayed 2.3-fold higher power output than the S. oneidensis MR-1 reference strain. Therefore, the utility of the MFC array was demonstrated.

A polymer-based DNA biochip platform for human papilloma virus genotyping

Genotyping of the human papilloma virus (HPV) is from a clinical point of view an important diagnostic task as some genotypes play a major role in the development of cervical carcinoma. So far PCR combined with blotting or in situ labelling is known to be the most accurate and sensitive method for detection and genotyping of HPV infection in clinical samples. However, specificity, cost-efficiency and sensitivity are not always satisfactory. A novel DNA biochip is described based on a plastic substrate, onto which small polymer droplets and single-stranded DNA are printed in the form of microarrays. Immobilisation of all compounds on the chip surface is achieved by a short UV-irradiation process, inducing photochemical reactions in the polymer. The chip designed for this study contains 36 probes for determining 12 common, different HPV genotypes. After isolation of the DNA, PCR and biochip read-out, the chip allows for genotyping of the most common virus strains, which, according to current prevalence studies, cover 85-95% of all infections. Following this approach as little as 10 virus copies can be detected within a short exposure time. Even using paraffin-embedded material and 10(4) copies per PCR are sufficient to allow rapid and reliable HPV genotyping.

Magnetic bead-based detection of autoimmune responses using protein microarrays

In the present study, a magnetic bead-based detection approach for protein microarrays is described as an alternative approach to the commonly used fluorescence-based detection system. Using the bead-based detection approach with applied magnetic force, it was possible to perform the detection step more rapidly as a result of the accelerated binding between the captured analyte in the microspot and the detection antibody, which was coupled to the magnetic beads. The resulting strong opacity shift on the microspots could be recorded with an ordinary flatbed scanner. In the context of autoimmunity, a set of 24 serum samples was analyzed for the presence of antibodies against 12 autoantigens using standard fluorescence and magnetic bead-based detection methods. Dynamic range, sensitivity, and specificity were determined for both detection methods. We propose from our findings that the magnetic bead-based detection option provides a simplified and cost effective readout method for protein microarrays.

Oncoproteomic profiling with antibody microarrays

The incidence of cancer and its associated mortality are increasing globally, indicating an urgent need to develop even more effective and sensitive sets of biomarkers that could help in early diagnosis and consequent intervention. Given that many cellular processes are carried out by proteins, cancer research has recently shifted toward an exploration of the full proteome for such discovery. Among the advanced methodologies that are being developed for analyzing the proteome, antibody microarrays have become a prominent tool for gathering the information required for a better understanding of disease biology, early detection, discrimination of tumors and monitoring of disease progression. Here, we review the technical aspects and challenges in the development and use of antibody microarray assays and examine recently reported applications in oncoproteomics.

The development of a comparison approach for Illumina bead chips unravels unexpected challenges applying newest generation microarrays

Background

The MAQC project demonstrated that microarrays with comparable content show inter- and intra-platform reproducibility. However, since the content of gene databases still increases, the development of new generations of microarrays covering new content is mandatory. To better understand the potential challenges updated microarray content might pose on clinical and biological projects we developed a methodology consisting of in silico analyses combined with performance analysis using real biological samples.

Results

Here we clearly demonstrate that not only oligonucleotide design but also database content and annotation strongly influence comparability and performance of subsequent generations of microarrays. Additionally, using human blood samples and purified T lymphocyte subsets as two independent examples, we show that a performance analysis using biological samples is crucial for the assessment of consistency and differences.

Conclusion

This study provides an important resource assisting investigators in comparing microarrays of updated content especially when working in a clinical or regulatory setting.

The effects of unnatural base pairs and mispairs on DNA duplex stability and solvation

In an effort to develop unnatural DNA base pairs we examined six pyridine-based nucleotides, d3MPy, d4MPy, d5MPy, d34DMPy, d35DMPy and d45DMPy. Each bears a pyridyl nucleobase scaffold but they are differentiated by methyl substitution, and were designed to vary both inter- and intra-strand packing within duplex DNA. The effects of the unnatural base pairs on duplex stability demonstrate that the pyridine scaffold may be optimized for stable and selective pairing, and identify one self pair, the pair formed between two d34DMPy nucleotides, which is virtually as stable as a dA:dT base pair in the same sequence context. In addition, we found that the incorporation of either the d34DMPy self pair or a single d34DMPy paired opposite a natural dA significantly increases oligonucleotide hybridization fidelity at other positions within the duplex. Hypersensitization of the duplex to mispairing appears to result from global and interdependent solvation effects mediated by the unnatural nucleotide(s) and the mispair. The results have important implications for our efforts to develop unnatural base pairs and suggest that the unnatural nucleotides might be developed as novel biotechnological tools, diagnostics, or therapeutics for applications where hybridization stringency is important.

Systematic evaluation of split-fluorescent proteins for the direct detection of native and methylated DNA

In order to directly detect nucleic acid polymers, we have designed biosensors comprising sequence-specific DNA binding proteins tethered to split-reporter proteins, which generate signal upon binding a predetermined nucleic acid target, in an approach termed SEquence-Enabled Reassembly (SEER). Herein we demonstrate that spectroscopically distinct split-fluorescent protein variants, GFPuv, EGFP, Venus, and mCherry, function effectively in the SEER system, providing sensitive DNA detection and the ability to simultaneously detect two target oligonucleotides. Additionally, a methylation-specific SEER-Venus system was generated, which was found to clearly distinguish between methylated versus non-methylated target DNA. These results will aid in refinement of the SEER system for the detection of user defined nucleic acid sequences and their chemical modifications as they relate to human disease.

Bio-cell chip fabrication and applications

Bio-cell chips are microarrays, which are composed of collections of cell spots attached to the surface. They hold intact cells and therefore enable the study of gene-gene interactions and gene-protein interactions in a cell with three-dimensional positional information. The authors developed a 16 x 6 array bio-cell chip comprising a 1-mm-thick perforated polydimethylsiloxane (PDMS) layer on lattice-patterned 25 mm x75 mm glass slide. The perforations in the PDMS layer formed cylindrical wells of volume approximately 1.7 micro L, which were used to seed cells. The authors constructed bio-cell chips using mononuclear cells from bone marrow specimens and subjected them to fluorescent in situ hybridization (FISH). Bio-cell chip technology is compatible with standard clinical diagnosis protocols, requires smaller samples, provides results quickly, and is highly cost-effective. In addition, bio-cell chips can be used as a platform for distributing real samples for research purposes. These features make it a potential tool for basic research and for clinical diagnosis.

A relationship between mRNA expression levels and protein solubility in E. coli

Each step in the process of gene expression, from the transcription of DNA into mRNA to the folding and posttranslational modification of proteins, is regulated by complex cellular mechanisms. At the same time, stringent conditions on the physicochemical properties of proteins, and hence on the nature of their amino acids, are imposed by the need to avoid aggregation at the concentrations required for optimal cellular function. A relationship is therefore expected to exist between mRNA expression levels and protein solubility in the cell. By investigating such a relationship, we formulate a method that enables the prediction of the maximal levels of mRNA expression in Escherichia coli with an accuracy of 83% and of the solubility of recombinant human proteins expressed in E. coli with an accuracy of 86%.

The role of predictive modelling in rationally re-engineering biological systems

Technologies to synthesize and transplant a complete genome into a cell have opened limitless potential to redesign organisms for complex, specialized tasks. However, large-scale re-engineering of a biological circuit will require systems-level optimization that will come from a deep understanding of operational relationships among all the constituent parts of a cell. The integrated framework necessary for conducting such complex bioengineering requires the convergence of systems and synthetic biology. Here, we review the status of these rapidly developing interdisciplinary fields of biology and provide a perspective on plausible venues for their merger.

Global analysis of cellular protein translation by pulsed SILAC

Current methods for system-wide gene expression analysis detect changes in mRNA abundance, but neglect regulation at the level of translation. Pulse labeling with stable isotopes has been used to measure protein turnover rates, but this does not directly provide information about translation rates. Here, we developed pulsed stable isotope labeling by amino acids in cell culture (pSILAC) with two heavy isotope labels to directly quantify protein translation on a proteome-wide scale. We applied the method to cellular iron homeostasis as a model system and demonstrate that it can confidently identify proteins that are translationally regulated by iron availability.

Expression profiling of zebrafish sox9 mutants reveals that Sox9 is required for retinal differentiation

The transcription factor gene Sox9 plays various roles in development, including differentiation of the skeleton, gonads, glia, and heart. Other functions of Sox9 remain enigmatic. Because Sox9 protein regulates expression of target genes, the identification of Sox9 targets should facilitate an understanding of the mechanisms of Sox9 action. To help identify Sox9 targets, we used microarray expression profiling to compare wild-type embryos to mutant embryos lacking activity for both sox9a and sox9b, the zebrafish co-orthologs of Sox9. Candidate genes were further evaluated by whole-mount in situ hybridization in wild-type and sox9 single and double mutant embryos. Results identified genes expressed in cartilage (col2a1a and col11a2), retina (calb2a, calb2b, crx, neurod, rs1, sox4a and vsx1) and pectoral fin bud (klf2b and EST AI722369) as candidate targets for Sox9. Cartilage is a well-characterized Sox9 target, which validates this strategy, whereas retina represents a novel Sox9 function. Analysis of mutant phenotypes confirmed that Sox9 helps regulate the number of Müller glia and photoreceptor cells and helps organize the neural retina. These roles in eye development were previously unrecognized and reinforce the multiple functions that Sox9 plays in vertebrate development.

Transcript profiling of human platelets using microarray and serial analysis of gene expression (SAGE)

Platelets are anucleated cells that are generated from megakaryocytes via thrombopoiesis. They lack genomic DNA but have a pool of individual mRNA transcripts. Taken together, these mRNAs constitute a platelet transcriptome. Platelets have a unique and reproducible transcript profile, which includes approximately 1,600-3,000 individual transcripts. In this chapter, we will focus on platelet purification and on transcript profiling using an Affymetrix microarray platform and serial analysis of gene expression (SAGE). Platelet purification is described in detail. Large-scale platelet purification schema is designed to purify platelets from apheresis platelet bags (approximately 3-5 x 10(11) platelets/bag). Modification of this schema --small-scale platelet purification--is designed to isolate platelets from 20 ml of peripheral blood. This chapter provides detailed protocols for microarray and SAGE transcript profiling. We also discuss peculiarities of platelet purification, RNA isolation, and transcript profiling.

DNA microarrays: an introduction to the technology

DNA microarrays allow the comprehensive genetic analysis of an organism or a sample. They are based on probes, which are immobilized in an ordered two-dimensional pattern on substrates, such as nylon membranes or glass slides. Probes are either spotted cDNAs or oligonucleotides and are designed to be specific for an organism, a gene, a genetic variant (mutation or polymorphism), or intergenic regions. Thus, they can be used for example for genotyping, expression analysis, or studies of protein-DNA interactions, and in the biomedical field they allow the detection of pathogens, antibiotic resistances, gene mutations and polymorphisms, and pathogenic states and can guide therapy. Microarrays, which cover the whole genome of an organism, are as well available as those which are focussed on genes related to a certain diagnostic application.

All-liquid separations, protein microarrays, and mass spectrometry to interrogate serum proteomes: an application to serum glycoproteomics

Disease-related changes in serum proteins are reasonable targets for early detection particularly due to the noninvasive approach in obtaining samples. Glycoproteins specifically have been implicated in a variety of disease types ranging from immune diseases to cancers. High-throughput screening methods that can assess glycosylation states of all serum proteins in normal and diseased sample groups can facilitate early detection as well as shed light on disease progression mechanisms. Outlined here is a combination of liquid separation, protein microarray, and mass spectrometry approach to highlight candidate proteins involved in diseases through glycosylation mechanisms.

A multiple-loop, double-cube microarray design applied to prostate cancer cell lines with variable sensitivity to histone deacetylase inhibitors

PURPOSE

Although microarray technology has been widely adopted by the scientific community, analysis of the ensuing data remains challenging. In this article, we present our experience with a complex design microarray experiment on resistance mechanisms of histone deacetylase inhibitors (HDACI).

EXPERIMENTAL DESIGN

To improve our understanding of the underlying mechanism of HDACI resistance in prostate cancer cells, we designed a novel "multiple-loop, double-cube" cDNA microarray experiment. In the experiment of 22 arrays, DU145 and PC3 cells were treated with two different HDACIs (vorinostat and valproic acid) and incubation periods (48 and 96 h). Preprocessing included exploratory analyses of the quality of the arrays and intensity-dependent within-array Loess normalization. An ANOVA model was used for inference. The results were validated by Western blot analysis of known treatment targets.

RESULTS

Treatment of PC3 and DU145 cells with HDACIs caused 2.8% to 10% (P<0.001) differential expression across conditions; 51% to 73% of these genes were up-regulated and 28% to 49% were down-regulated. The extent of differential expression was associated with cell line (DU145>PC3), HDACI (valproic acid >or= vorinostat), and duration of treatment (96>48 h). We identified known and new treatment targets involved in cell cycle and apoptosis.

CONCLUSION

A multiple-loop, double-cube microarray design can be used to identify HDACI-induced changes in gene expression possibly related to drug resistance.

A novel approach for reliable microarray analysis of microdissected tumor cells from formalin-fixed and paraffin-embedded colorectal cancer resection specimens

We present a novel approach for microarray analysis of RNA derived from microdissected cells of routinely formalin-fixed and paraffin-embedded (FFPE) cancer resection specimens. Subsequent to RNA sample preparation and hybridization to standard GeneChips (Affymetrix), RNA samples yielded 36.43 +/- 9.60% (FFPE), 49.90 +/- 4.43% (fresh-frozen), and 53.9% (cell line) present calls. Quality control parameters and Q-RT-PCR validation demonstrated reliability of results. Microarray datasets of FFPE samples were informative and comparable to those of fresh-frozen samples. A systematic measurement difference of differentially processed tissues was eliminated by a correction step for comparative unsupervised data analysis of fresh-frozen and FFPE samples. Within FFPE samples, unsupervised clustering analyses clearly distinguished between normal and malignant tissues as well as to further separate tumor samples according to histological World Health Organization (WHO) subtypes. In summary, our approach represents a major step towards integration of microarrays into retrospective studies and enables further investigation of the relevance of microarray analysis for clinico-pathological diagnostics.

Candida albicans–macrophage interactions: genomic and proteomic insights

Candida albicans infection is a significant cause of morbidity and mortality in immunocompromised patients. In vivo and in vitro models have been developed to study both the fungal and the mammalian immune responses. Phagocytic cells (i.e., macrophages) play a key role in innate immunity against C. albicans by capturing, killing and processing the pathogen for presentation to T cells. The use of microarray technology to study global fungal transcriptional changes after interaction with different host cells has revealed how C. albicans adapts to its environment. Proteomic tools complement molecular approaches and computational methods enable the formulation of relevant biological hypotheses. Therefore, the combination of genomics, proteomics and bioinformatics tools (i.e., network analyses) is a powerful strategy to better understand the biological situation of the fungus inside macrophages; part of the fungal population is killed while a significantly high percentage survives.

Non-contact protein microarray fabrication using a procedure based on liquid bridge formation

Contemporary microarrayers of contact or non-contact format used in protein microarray fabrication still suffer from a number of problems, e.g. generation of satellite spots, inhomogeneous spots, misplaced or even absent spots, and sample carryover. In this paper, a new concept of non-contact sample deposition that reduces such problems is introduced. To show the potential and robustness of this pressure-assisted deposition technique, different sample solutions known to cause severe problems or to be even impossible to print with conventional microarrayers were accurately printed. The samples included 200 mg mL(-1) human serum albumin, highly concentrated sticky cell adhesion proteins, pure high-salt cell-lysis buffer, pure DMSO, and a suspension of 5-microm polystyrene beads. Additionally, a water-immiscible liquid fluorocarbon, which was shown not to affect the functionality of the capture molecules, was employed as a lid to reduce evaporation during microarray printing. The fluorocarbon liquid lid was shown to circumvent hydrolysis of water-sensitive activated surfaces during long-term deposition procedures.

The vitamin D3/Hox-A10 pathway supports MafB function during the monocyte differentiation of human CD34+ hemopoietic progenitors

Although a considerable number of reports indicate an involvement of the Hox-A10 gene in the molecular control of hemopoiesis, the conclusions of such studies are quite controversial given that they support, in some cases, a role in the stimulation of stem cell self-renewal and myeloid progenitor expansion, whereas in others they implicate this transcription factor in the induction of monocyte-macrophage differentiation. To clarify this issue, we analyzed the biological effects and the transcriptome changes determined in human primary CD34(+) hemopoietic progenitors by retroviral transduction of a full-length Hox-A10 cDNA. The results obtained clearly indicated that this homeogene is an inducer of monocyte differentiation, at least partly acting through the up-regulation of the MafB gene, recently identified as the master regulator of such a maturation pathway. By using a combined approach based on computational analysis, EMSA experiments, and luciferase assays, we were able to demonstrate the presence of a Hox-A10-binding site in the promoter region of the MafB gene, which suggested the likely molecular mechanism underlying the observed effect. Stimulation of the same cells with the vitamin D(3) monocyte differentiation inducer resulted in a clear increase of Hox-A10 and MafB transcripts, indicating the existence of a precise transactivation cascade involving vitamin D(3) receptor, Hox-A10, and MafB transcription factors. Altogether, these data allow one to conclude that the vitamin D(3)/Hox-A10 pathway supports MafB function during the induction of monocyte differentiation.

Advanced spot quality analysis in two-colour microarray experiments

Background

Image analysis of microarrays and, in particular, spot quantification and spot quality control, is one of the most important steps in statistical analysis of microarray data. Recent methods of spot quality control are still in early age of development, often leading to underestimation of true positive microarray features and, consequently, to loss of important biological information. Therefore, improving and standardizing the statistical approaches of spot quality control are essential to facilitate the overall analysis of microarray data and subsequent extraction of biological information.

Findings

We evaluated the performance of two image analysis packages MAIA and GenePix (GP) using two complementary experimental approaches with a focus on the statistical analysis of spot quality factors. First, we developed control microarrays with a priori known fluorescence ratios to verify the accuracy and precision of the ratio estimation of signal intensities. Next, we developed advanced semi-automatic protocols of spot quality evaluation in MAIA and GP and compared their performance with available facilities of spot quantitative filtering in GP. We evaluated these algorithms for standardised spot quality analysis in a whole-genome microarray experiment assessing well-characterised transcriptional modifications induced by the transcription regulator SNAI1. Using a set of RT-PCR or qRT-PCR validated microarray data, we found that the semi-automatic protocol of spot quality control we developed with MAIA allowed recovering approximately 13% more spots and 38% more differentially expressed genes (at FDR = 5%) than GP with default spot filtering conditions.

Conclusion

Careful control of spot quality characteristics with advanced spot quality evaluation can significantly increase the amount of confident and accurate data resulting in more meaningful biological conclusions.

Generalizing genetical genomics: getting added value from environmental perturbation

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across multiple environments. We propose a generalization of genetical genomics, which combines genetic and sensibly chosen environmental perturbations, to study the plasticity of molecular networks. This strategy forms a crucial step toward understanding why individuals respond differently to drugs, toxins, pathogens, nutrients and other environmental influences. Here we outline a strategy for selecting and allocating individuals to particular treatments, and we discuss the promises and pitfalls of the generalized genetical genomics approach.

A decade of genome-wide gene expression profiling in acute myeloid leukemia: flashback and prospects

The past decade has shown a marked increase in the use of high-throughput assays in clinical research into human cancer, including acute myeloid leukemia (AML). In particular, genome-wide gene expression profiling (GEP) using DNA microarrays has been extensively used for improved understanding of the diagnosis, prognosis, and pathobiology of this heterogeneous disease. This review discusses the progress that has been made, places the technologic limitations in perspective, and highlights promising future avenues.

Current and future directions in genomics of amyotrophic lateral sclerosis

New knowledge of the structure and function of the human genome and novel genomic technologies are being applied to the study of sporadic amyotrophic lateral sclerosis (ALS). These studies can examine tens to hundreds of thousands of items at once, and depend on sophisticated computer processing. Current studies are focused on genetic susceptibility and gene expression and future studies will likely focus on structural variation, gene regulation and non-protein coding regions. The hope is that they will lead to deeper understanding of molecular aspects of the disease and to rational therapeutic targets.

The incredible shrinking world of DNA microarrays

The efficacy of microarrays in examining gene expression, gene and genome structure, protein-DNA interactions, whole-genome similarities and differences, microRNA expression, methylation (and more) is no longer in question. It is a fast-developing, cutting edge technology that has grown up along with massive sequence databases and is likely to become part of everyday patient care. Many advances have recently expanded the power and utility of microarrays; among them is our development of a new array tiling technique that dramatically increases the scope of coverage of an oligonucleotide tiling array without substantially increasing its cost.

Genome-wide studies in thyroid neoplasia

There is much interest in the application of genome biology to the field of thyroid neoplasia, despite the relatively low mortality rate associated with thyroid cancer in general. The principal reason for this interest is that the field of thyroid neoplasia stands to benefit from the application of genomic information to address a variety of pathologic and clinical issues. In addition to practical patient care issues, there is an excellent opportunity of expand the basic understanding of thyroid carcinogenesis. In this article, the most relevant genomic work on thyroid tumors performed to date is reviewed along with some general comments about the potential impact of genomic biology on thyroid pathology and the management of patients with thyroid nodules and cancer.

Babelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments

We present a new version of Babelomics, a complete suite of web tools for the functional profiling of genome scale experiments, with new and improved methods as well as more types of functional definitions. Babelomics includes different flavours of conventional functional enrichment methods as well as more advanced gene set analysis methods that makes it a unique tool among the similar resources available. In addition to the well-known functional definitions (GO, KEGG), Babelomics includes new ones such as Biocarta pathways or text mining-derived functional terms. Regulatory modules implemented include transcriptional control (Transfac, CisRed) and other levels of regulation such as miRNA-mediated interference. Moreover, Babelomics allows for sub-selection of terms in order to test more focused hypothesis. Also gene annotation correspondence tables can be imported, which allows testing with user-defined functional modules. Finally, a tool for the ‘de novo’ functional annotation of sequences has been included in the system. This allows using yet unannotated organisms in the program. Babelomics has been extensively re-engineered and now it includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. Babelomics is available at http://www.babelomics.org

In silico promoters: modelling of cis-regulatory context facilitates target predictio

Elucidation of gene regulatory complexity holds much promise towards aiding therapeutic interventions in medical research. It has become progressively more evident that the characterization of highly conserved regulatory modules within promoters may assist in the elucidation of distinct cis-motif and trans-element regulatory interactions, shared in response to stimulus-evoked pathological changes. With special emphasis on the promoter, accurate analyses of cis-motif architecture combined with integrative in silico modelling might serve as a more refined approach for prediction and study of regulatory targets and major regulators governing transcriptional control. In this review, we have highlighted key examples and recent advances implementing in silico promoter models that could serve as essential contributions for future research in molecular medicine.

Characterization of local geometry of protein surfaces with the visibility criterion

Experimentally determined protein tertiary structures are rapidly accumulating in a database, partly due to the structural genomics projects. Included are proteins of unknown function, whose function has not been investigated by experiments and was not able to be predicted by conventional sequence-based search. Those uncharacterized protein structures highlight the urgent need of computational methods for annotating proteins from tertiary structures, which include function annotation methods through characterizing protein local surfaces. Toward structure-based protein annotation, we have developed VisGrid algorithm that uses the visibility criterion to characterize local geometric features of protein surfaces. Unlike existing methods, which only concerns identifying pockets that could be potential ligand-binding sites in proteins, VisGrid is also aimed to identify large protrusions, hollows, and flat regions, which can characterize geometric features of a protein structure. The visibility used in VisGrid is defined as the fraction of visible directions from a target position on a protein surface. A pocket or a hollow is recognized as a cluster of positions with a small visibility. A large protrusion in a protein structure is recognized as a pocket in the negative image of the structure. VisGrid correctly identified 95.0% of ligand-binding sites as one of the three largest pockets in 5616 benchmark proteins. To examine how natural flexibility of proteins affects pocket identification, VisGrid was tested on distorted structures by molecular dynamics simulation. Sensitivity decreased approximately 20% for structures of a root mean square deviation of 2.0 A to the original crystal structure, but specificity was not much affected. Because of its intuitiveness and simplicity, the visibility criterion will lay the foundation for characterization and function annotation of local shape of proteins.

Snap-to-it probes: chelate-constrained nucleobase oligomers with enhanced binding specificity

We describe snap-to-it probes, a novel probe technology to enhance the hybridization specificity of natural and unnatural nucleic acid oligomers using a simple and readily introduced structural motif. Snap-to-it probes were prepared from peptide nucleic acid (PNA) oligomers by modifying each terminus with a coordinating ligand. The two coordinating ligands constrain the probe into a macrocyclic configuration through formation of an intramolecular chelate with a divalent transition metal ion. On hybridization with a DNA target, the intramolecular chelate in the snap-to-it probe dissociates, resulting in the probe 'snapping-to' and binding the target nucleic acid. Thermal transition analysis of snap-to-it probes with complementary and single-mismatch DNA targets revealed that the transition between free and target-bound probe conformations was a reversible equilibrium, and the intramolecular chelate provided a thermodynamic barrier to target binding that resulted in a significant increase in mismatch discrimination. A 4-6 degrees C increase in specificity (DeltaT(m)) was observed from snap-to-it probes bearing either terminal iminodiacetic acid ligands coordinated with Ni(2+), or terminal dihistidine and nitrilotriacetic acid ligands coordinated with Cu(2+). The difference in specificity of the PNA oligomer relative to DNA was more than doubled in snap-to-it probes. Snap-to-it probes labeled with a fluorophore-quencher pair exhibited target-dependent fluorescence enhancement upon binding with target DNA.