Spotting effect in microarray experiments

BACKGROUND: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio) and intensity across the array. RESULTS: Using the variogram, a geostatistical tool, we characterized the observed variability, called here the spotting effect because it most probably arises during steps in the array printing procedure. CONCLUSIONS: The spotting effect is not appropriately corrected by current normalization methods, even by those addressing spatial variability. Importantly, the spotting effect may alter differential and clustering analysis

Surface free energy and microarray deposition technology

Microarray techniques use a combinatorial approach to assess complex biochemical interactions. The fundamental goal is simultaneous, large-scale experimentation analogous to the automation achieved in the semiconductor industry. However, microarray deposition inherently involves liquids contacting solid substrates. Liquid droplet shapes are determined by surface and interfacial tension forces, and flows during drying. This article looks at how surface free energy and wetting considerations may influence the accuracy and reliability of spotted microarray experiments

Real-time DNA microarray analysis

We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e. real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation in the capturing spots, washing artifacts, microarray spot-to-spot variations, and other signal amplitude-affecting non-idealities. We demonstrate in both theory and practice that the time-constant of target capturing in microarrays, similar to all affinity-based biosensors, is inversely proportional to the concentration of the target analyte, which we subsequently use as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to empirically validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays

Can Zipf's law be adapted to normalize microarrays?

BACKGROUND: Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented. RESULTS: Using pairwise comparisons using MA plots (log ratio vs. log intensity), we compared this novel method to previously published normalization techniques, namely global normalization to the mean, the quantile method, and a variation on the loess normalization method designed specifically for boutique microarrays. Results indicated that, for single channel microarrays, the quantile method was superior with regard to eliminating intensity-dependent effects (banana curves), but Zipf's law normalization does minimize this effect by rotating the data distribution such that the maximal number of data points lie on the zero of the log ratio axis. For two channel boutique microarrays, the Zipf's law normalizations performed as well as, or better than existing techniques. CONCLUSION: Zipf's law normalization is a useful tool where the Quantile method cannot be applied, as is the case with microarrays containing functionally specific gene sets (boutique arrays)

Beating the reaction limits of biosensor sensitivity with dynamic tracking of single binding events

The clinical need for ultrasensitive molecular analysis has motivated the development of several endpoint-assay technologies capable of single-molecule readout. These endpoint assays are now primarily limited by the affinity and specificity of the molecular-recognition agents for the analyte of interest. In contrast, a kinetic assay with single-molecule readout could distinguish between low-abundance, high-affinity (specific analyte) and high-abundance, low-affinity (nonspecific background) binding by measuring the duration of individual binding events at equilibrium. Here, we describe such a kinetic assay, in which individual binding events are detected and monitored during sample incubation. This method uses plasmonic gold nanorods and interferometric reflectance imaging to detect thousands of individual binding events across a multiplex solid-phase sensor with a large area approaching that of leading bead-based endpoint-assay technologies. A dynamic tracking procedure is used to measure the duration of each event. From this, the total rates of binding and debinding as well as the distribution of binding-event durations are determined. We observe a limit of detection of 19 fM for a proof-of-concept synthetic DNA analyte in a 12-plex assay format.First author draf

Competitive Activation of a Methyl C−H Bond of Dimethylformamide at an Iridium Center

During the synthesis of [AsPh_4][Ir(CO)_2I_3Me] by refluxing IrCl_3·3H_2O in DMF (DMF = dimethylformamide) in the presence of aqueous HCl, followed by sequential treatment with [AsPh_4]Cl, NaI, and methyl iodide and finally recrystallization from methylene chloride/pentane, three crystalline byproducts were obtained: [AsPh4]_2[Ir(CO)I_5], [AsPh_4]_2[trans-Ir(CO)I_4Cl], and [AsPh_4][Ir(CO)(κ^2O,C-CH_2NMeCHO)Cl_2I]. The last of these, whose structure (along with the others) was determined by X-ray diffraction, results from activation of a methyl C−H bond of dimethylformamide, rather than the normally much more reactive aldehydic C−H bond

Modular Nucleic Acid Assembled p/MHC Microarrays for Multiplexed Sorting of Antigen-Specific T Cells

The human immune system consists of a large number of T cells capable of recognizing and responding to antigens derived from various sources. The development of peptide-major histocompatibility (p/MHC) tetrameric complexes has enabled the direct detection of these antigen-specific T cells. With the goal of increasing throughput and multiplexing of T cell detection, protein microarrays spotted with defined p/MHC complexes have been reported, but studies have been limited due to the inherent instability and reproducibility of arrays produced via conventional spotted methods. Herein, we report on a platform for the detection of antigen-specific T cells on glass substrates that offers significant advantages over existing surface-bound schemes. In this approach, called “Nucleic Acid Cell Sorting (NACS)”, single-stranded DNA oligomers conjugated site-specifically to p/MHC tetramers are employed to immobilize p/MHC tetramers via hybridization to a complementary-printed substrate. Fully assembled p/MHC arrays are used to detect and enumerate T cells captured from cellular suspensions, including primary human T cells collected from cancer patients. NACS arrays outperform conventional spotted arrays assessed in key criteria such as repeatability and homogeneity. The versatility of employing DNA sequences for cell sorting is exploited to enable the programmed, selective release of target populations of immobilized T cells with restriction endonucleases for downstream analysis. Because of the performance, facile and modular assembly of p/MHC tetramer arrays, NACS holds promise as a versatile platform for multiplexed T cell detection

Interactive data exploration with targeted projection pursuit

Data exploration is a vital, but little considered, part of the scientific process; but few visualisation tools can cope with truly complex data. Targeted Projection Pursuit (TPP) is an interactive data exploration technique that provides an intuitive and transparent interface for data exploration. A prototype has been evaluated quantitatively and found to outperform algorithmic techniques on standard visual analysis tasks

A study on endocrine disrupters in the environment through the microarray technology

Due to the current rise of exposure to natural and synthetic compounds in our daily life, the debate concerning the safety of many substances is becoming increasingly relevant. The estrogenic activity of various compounds, described as xenoestrogens, is the major part of this debate. Humans beings are exposed to these substances from different environmental contaminations ranging from conscious intake of estrogenic substances, as in contraception or in hormone replace therapy (HRT), to unconscious exposure, from food, the use of synthetic material in daily life and air and water pollution. At this point the need for methods to investigate the activity and the safety of these substances is becoming increasingly important. Classical methods for the analysis of the estrogenic activity of substances, like batteries of in vivo test systems on the rat uterotrophic assay are not able to describe the different pathways of action of recently discovered estrogenic substances. This evidence was already shown by the Organization for Economic Cooperation and Development (OECD), introducing new test guidelines for the investigation of effects of endocrine disruptors (according to enhanced Test Guideline 407). As reviewed by Nilsson (Nilsson et al., 2001), after the interaction of the estrogens with the Estrogen Receptor (ER) in the cells, the mechanism of activation possible is not only via direct binding of the ER to the Estrogen Responsive Elements (EREs) present in the promoter region of the target gene, very well described for many target genes, but that also other mechanisms are used: the interaction of the ER with the AP 1, Sp 1 and NFkB modes, that are discovered but not yet comprehensively described. The aim of my work is to produce a microarray DNA chip for the investigation of the estrogenic activity of different compounds present in the environment. The chip will consist of a selection of 100 genes that are estrogen responsive and it will cover the spectrum of activities of estrogenic compounds in various organs of the body. In the gene selection, genes were chosen that are estrogen responsive in the classical target tissues of estrogens, linked to reproduction, like uterus and mammary gland, and also in tissues not related to reproduction like liver, bones and capillars. In addition, other genes are included to monitor different pathways that are related to disease states; control of cell proliferation, apoptosis or cancer related genes. Currently these kinds of investigations are already in process, but by other methods which are more time consuming and with a lower throughput e.g. the gene expression profiling using the real time RT-PCR. The use of microarray’s satisfies the need for a less time consuming, high throughput method, to obtain a fast characterization of the gene expression finger print of the candidate substances and their mechanism of action in the organism. In my work I investigated the estrogenic potency of different Xenoestrogens that commonly occur in our daily life, in rat cells and tissue using well known estrogen sensitive genes like C3, Clu, IGFBP1 and CaBP9k. I focused on their effect on cell proliferation, studying PCNA expression. For the first time sensitivity of the gene CA2 was proofed in liver and uterus. A new identified mRNA sequence, r52, was characterized for its sensitivity to estrogenic exposure. This sequence was investigated at the molecular level expanding the known nucleic sequence. I produce a microarray chip with 16 genes to investigate the estrogenic potency of different compounds. As proof of principle of the microarray method completely produced in house I compared the result of gene expression obtained by the chip to that obtained by real time RT PCR finding a similarity of results. This new established method is less sensitive than the real-time RT PCR but allows a high throughput of gene expression analysis producing at the end a more complete picture of the expression signature of a compound