Microarrays最新文献

{"title":"Gold Nanoparticles Surface Plasmon Resonance Enhanced Signal for the Detection of Small Molecules on Split-Aptamer Microarrays (Small Molecules Detection from Split-Aptamers).","authors":"Feriel Melaine,&nbsp;Yoann Roupioz,&nbsp;Arnaud Buhot","doi":"10.3390/microarrays4010041","DOIUrl":"https://doi.org/10.3390/microarrays4010041","url":null,"abstract":"<p><p>The detection of small molecules by biosensors remains a challenge for diagnostics in many areas like pharmacology, environment or homeland security. The main difficulty comes from both the low molecular weight and low concentrations of most targets, which generally requires an indirect detection with an amplification or a sandwich procedure. In this study, we combine both strategies as the amplification of Surface Plasmon Resonance imaging (SPRi) signal is obtained by the use of gold nanoparticles and the sequence engineering of split-aptamers, short oligonucleotides strands with strong affinity towards small targets, allows for a sandwich structure. Combining those two strategies, we obtained state-of-the-art results in the limit of detection (LOD = 50 nM) with the model target adenosine. Furthermore, the SPRi detection led on aptamer microarrays paves the way for potential multi-target detections thanks to the multi-probe imaging approach. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"4 1","pages":"41-52"},"PeriodicalIF":0.0,"publicationDate":"2015-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays4010041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34367631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcriptome Analysis of Porphyrin-Accumulated and X-Ray-Irradiated Cell Cultures under Limited Proliferation and Non-Lethal Conditions.","authors":"Junko Takahashi,&nbsp;Masaki Misawa,&nbsp;Hitoshi Iwahashi","doi":"10.3390/microarrays4010025","DOIUrl":"https://doi.org/10.3390/microarrays4010025","url":null,"abstract":"<p><p>5-Aminolevulinic acid (ALA) is a precursor of the photosensitizer used in photodynamic therapy. It accumulates in tumor cells and subsequently metabolizes to protoporphyrin IX (PpIX), which generates singlet oxygen after light irradiation. PpIX enhances the generation of reactive oxygen species following physicochemical interactions with X-rays. ALA-based treatment using fractionated doses of irradiation suppressed tumor growth in a mouse melanoma model. To study the transcriptomic effects of PpIX, microarray analyses were conducted using HeLa cells with limited proliferation capacity. Based on the p-values (p < 0.01), we selected genes showing altered expression in each treatment group with reference to the non-treatment (NT) group. We detected 290, 196 and 28 upregulated genes, as well as 203, 146 and 36 downregulated genes after a 6 h-long PpIX treatment (1 μg/mL) prior to 3 Gy X-ray irradiation (PpIX-XT), 3 Gy X-ray irradiation alone (XT) and PpIX treatment alone (PpIXT), respectively. Functional analysis revealed that a majority of the regulated genes in the XT and PpIX-XT groups were related to cell-cycle arrest. The XT and PpIX-XT groups differed in the quantity, but not in the quality of their gene expression. The combined effect of PpIX and X-ray irradiation sensitized HeLa cells to X-ray treatment. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"4 1","pages":"25-40"},"PeriodicalIF":0.0,"publicationDate":"2015-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays4010025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34367629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the Specific Ischemic Core and Penumbra Transcriptome in the Permanent Middle Cerebral Artery Occlusion Mouse Model Brain Treated with the Neuropeptide PACAP38.","authors":"Motohide Hori,&nbsp;Tomoya Nakamachi,&nbsp;Junko Shibato,&nbsp;Randeep Rakwal,&nbsp;Seiji Shioda,&nbsp;Satoshi Numazawa","doi":"10.3390/microarrays4010002","DOIUrl":"https://doi.org/10.3390/microarrays4010002","url":null,"abstract":"<p><p>Our group has been systematically investigating the effects of the neuropeptide pituitary adenylate-cyclase activating polypeptide (PACAP) on the ischemic brain. To do so, we have established and utilized the permanent middle cerebral artery occlusion (PMCAO) mouse model, in which PACAP38 (1 pmol) injection is given intracerebroventrically and compared to a control saline (0.9% sodium chloride, NaCl) injection, to unravel genome‑wide gene expression changes using a high-throughput DNA microarray analysis approach. In our previous studies, we have accumulated a large volume of data (gene inventory) from the whole brain (ipsilateral and contralateral hemispheres) after both PMCAO and post-PACAP38 injection. In our latest research, we have targeted specifically infarct or ischemic core (hereafter abbreviated IC) and penumbra (hereafter abbreviated P) post-PACAP38 injections in order to re-examine the transcriptome at 6 and 24 h post injection. The current study aims to delineate the specificity of expression and localization of differentially expressed molecular factors influenced by PACAP38 in the IC and P regions. Utilizing the mouse 4 × 44 K whole genome DNA chip we show numerous changes (≧/≦ 1.5/0.75-fold) at both 6 h (654 and 456, and 522 and 449 up- and down-regulated genes for IC and P, respectively) and 24 h (2568 and 2684, and 1947 and 1592 up- and down-regulated genes for IC and P, respectively) after PACAP38 treatment. Among the gene inventories obtained here, two genes, brain-derived neurotrophic factor (Bdnf) and transthyretin (Ttr) were found to be induced by PACAP38 treatment, which we had not been able to identify previously using the whole hemisphere transcriptome analysis. Using bioinformatics analysis by pathway- or specific-disease-state focused gene classifications and Ingenuity Pathway Analysis (IPA) the differentially expressed genes are functionally classified and discussed. Among these, we specifically discuss some novel and previously identified genes, such as alpha hemoglobin stabilizing protein (Ahsp), cathelicidin antimicrobial peptide (Camp), chemokines, interferon beta 1 (Ifnb1), and interleukin 6 (Il6) in context of PACAP38-mediated neuroprotection in the ischemic brain. Taken together, the DNA microarray analysis provides not only a great resource for further study, but also reinforces the importance of region-specific analyses in genome-wide identification of target molecular factors that might play a role in the neuroprotective function of PACAP38. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"4 1","pages":"2-24"},"PeriodicalIF":0.0,"publicationDate":"2015-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays4010002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34367156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Screening of Small Molecule Microarrays for Ligands Targeted to the Extracellular Epitopes of Living Cells.","authors":"Jeong Heon Lee,&nbsp;Kai Bao,&nbsp;John V Frangioni,&nbsp;Hak Soo Choi","doi":"10.3390/microarrays4010053","DOIUrl":"https://doi.org/10.3390/microarrays4010053","url":null,"abstract":"<p><p>The screening of living cells using high-throughput microarrays is technically challenging. Great care must be taken in the chemical presentation of potential ligands and the number of collisions that cells make with them. To overcome these issues, we have developed a glass slide-based microarray system to discover small molecule ligands that preferentially bind to one cell type over another, including when the cells differ by only a single receptor. Chemical spots of 300 ± 10 μm in diameter are conjugated covalently to glass slides using an arraying robot, and novel near-infrared fluorophores with peak emission at 700 nm and 800 nm are used to label two different cell types. By carefully optimizing incubation conditions, including cell density, motion, kinetics, detection, etc. we demonstrate that cell-ligand binding occurs, and that the number of cells bound per chemical spot correlates with ligand affinity and specificity. This screening system lays the foundation for high-throughput discovery of novel ligands to the cell surface. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"4 1","pages":"53-63"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays4010053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34231292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variation of RNA Quality and Quantity Are Major Sources of Batch Effects in Microarray Expression Data.","authors":"Mario Fasold,&nbsp;Hans Binder","doi":"10.3390/microarrays3040322","DOIUrl":"https://doi.org/10.3390/microarrays3040322","url":null,"abstract":"<p><p>The great utility of microarrays for genome-scale expression analysis is challenged by the widespread presence of batch effects, which bias expression measurements in particular within large data sets. These unwanted technical artifacts can obscure biological variation and thus significantly reduce the reliability of the analysis results. It is largely unknown which are the predominant technical sources leading to batch effects. We here quantitatively assess the prevalence and impact of several known technical effects on microarray expression results. Particularly, we focus on important factors such as RNA degradation, RNA quantity, and sequence biases including multiple guanine effects. We find that the common variation of RNA quality and RNA quantity can not only yield low-quality expression results, but that both factors also correlate with batch effects and biological characteristics of the samples. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"3 4","pages":"322-39"},"PeriodicalIF":0.0,"publicationDate":"2014-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays3040322","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34366403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data.","authors":"Marcelo Boareto,&nbsp;Nestor Caticha","doi":"10.3390/microarrays3040340","DOIUrl":"https://doi.org/10.3390/microarrays3040340","url":null,"abstract":"<p><p>Microarray data analysis typically consists in identifying a list of differentially expressed genes (DEG), i.e., the genes that are differentially expressed between two experimental conditions. Variance shrinkage methods have been considered a better choice than the standard t-test for selecting the DEG because they correct the dependence of the error with the expression level. This dependence is mainly caused by errors in background correction, which more severely affects genes with low expression values. Here, we propose a new method for identifying the DEG that overcomes this issue and does not require background correction or variance shrinkage. Unlike current methods, our methodology is easy to understand and implement. It consists of applying the standard t-test directly on the normalized intensity data, which is possible because the probe intensity is proportional to the gene expression level and because the t-test is scale- and location-invariant. This methodology considerably improves the sensitivity and robustness of the list of DEG when compared with the t-test applied to preprocessed data and to the most widely used shrinkage methods, Significance Analysis of Microarrays (SAM) and Linear Models for Microarray Data (LIMMA). Our approach is useful especially when the genes of interest have small differences in expression and therefore get ignored by standard variance shrinkage methods. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"3 4","pages":"340-51"},"PeriodicalIF":0.0,"publicationDate":"2014-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays3040340","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34366404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Agreement between miRNA Microarray Platforms.","authors":"Niccolò P Bassani,&nbsp;Federico Ambrogi,&nbsp;Elia M Biganzoli","doi":"10.3390/microarrays3040302","DOIUrl":"https://doi.org/10.3390/microarrays3040302","url":null,"abstract":"<p><p>Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland-Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland-Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland-Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"3 4","pages":"302-21"},"PeriodicalIF":0.0,"publicationDate":"2014-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays3040302","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34422053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication of Homogeneous High-Density Antibody Microarrays for Cytokine Detection.","authors":"Ingeborg Hospach,&nbsp;Yvonne Joseph,&nbsp;Michaela Kathrin Mai,&nbsp;Nadejda Krasteva,&nbsp;Gabriele Nelles","doi":"10.3390/microarrays3040282","DOIUrl":"https://doi.org/10.3390/microarrays3040282","url":null,"abstract":"<p><p>Cytokine proteins are known as biomarker molecules, characteristic of a disease or specific body condition. Monitoring of the cytokine pattern in body fluids can contribute to the diagnosis of diseases. Here we report on the development of an array comprised of different anti-cytokine antibodies on an activated solid support coupled with a fluorescence readout mechanism. Optimization of the array preparation was done in regard of spot homogeneity and spot size. The proinflammatory cytokines Tumor Necrosis Factor alpha (TNFα) and Interleukin 6 (IL-6) were chosen as the first targets of interest. First, the solid support for covalent antibody immobilization and an adequate fluorescent label were selected. Three differently functionalized glass substrates for spotting were compared: amine and epoxy, both having a two-dimensional structure, and the NHS functionalized hydrogel (NHS-3D). The NHS-hydrogel functionalization of the substrate was best suited to antibody immobilization. Then, the optimization of plotting parameters and geometry as well as buffer media were investigated, considering the ambient analyte theory of Roger Ekins. As a first step towards real sample studies, a proof of principle of cytokine detection has been established. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"3 4","pages":"282-301"},"PeriodicalIF":0.0,"publicationDate":"2014-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays3040282","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34422052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expression Comparison of Oil Biosynthesis Genes in Oil Palm Mesocarp Tissue Using Custom Array.","authors":"Yick Ching Wong,&nbsp;Qi Bin Kwong,&nbsp;Heng Leng Lee,&nbsp;Chuang Kee Ong,&nbsp;Sean Mayes,&nbsp;Fook Tim Chew,&nbsp;David R Appleton,&nbsp;Harikrishna Kulaveerasingam","doi":"10.3390/microarrays3040263","DOIUrl":"https://doi.org/10.3390/microarrays3040263","url":null,"abstract":"<p><p>Gene expression changes that occur during mesocarp development are a major research focus in oil palm research due to the economic importance of this tissue and the relatively rapid increase in lipid content to very high levels at fruit ripeness. Here, we report the development of a transcriptome-based 105,000-probe oil palm mesocarp microarray. The expression of genes involved in fatty acid (FA) and triacylglycerol (TAG) assembly, along with the tricarboxylic acid cycle (TCA) and glycolysis pathway at 16 Weeks After Anthesis (WAA) exhibited significantly higher signals compared to those obtained from a cross-species hybridization to the Arabidopsis (p-value < 0.01), and rice (p-value < 0.01) arrays. The oil palm microarray data also showed comparable correlation of expression (r² = 0.569, p < 0.01) throughout mesocarp development to transcriptome (RNA sequencing) data, and improved correlation over quantitative real-time PCR (qPCR) (r² = 0.721, p < 0.01) of the same RNA samples. The results confirm the advantage of the custom microarray over commercially available arrays derived from model species. We demonstrate the utility of this custom microarray to gain a better understanding of gene expression patterns in the oil palm mesocarp that may lead to increasing future oil yield. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"3 4","pages":"263-81"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/microarrays3040263","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34422051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Particle-Based Microarrays of Oligonucleotides and Oligopeptides.","authors":"Alexander Nesterov-Mueller, Frieder Maerkle, Lothar Hahn, Tobias Foertsch, Sebastian Schillo, Valentina Bykovskaya, Martyna Sedlmayr, Laura K Weber, Barbara Ridder, Miriam Soehindrijo, Bastian Muenster, Jakob Striffler, F Ralf Bischoff, Frank Breitling, Felix F Loeffler","doi":"10.3390/microarrays3040245","DOIUrl":"10.3390/microarrays3040245","url":null,"abstract":"<p><p>In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches. </p>","PeriodicalId":56355,"journal":{"name":"Microarrays","volume":"3 4","pages":"245-62"},"PeriodicalIF":0.0,"publicationDate":"2014-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4979057/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34422050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}