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Microarrays, Volume 5, Issue 2 (June 2016)

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Open AccessArticle
SNPConvert: SNP Array Standardization and Integration in Livestock Species
Microarrays 2016, 5(2), 17; https://doi.org/10.3390/microarrays5020017 - 09 Jun 2016
Cited by 1 | Viewed by 1661
Abstract
One of the main advantages of single nucleotide polymorphism (SNP) array technology is providing genotype calls for a specific number of SNP markers at a relatively low cost. Since its first application in animal genetics, the number of available SNP arrays for each [...] Read more.
One of the main advantages of single nucleotide polymorphism (SNP) array technology is providing genotype calls for a specific number of SNP markers at a relatively low cost. Since its first application in animal genetics, the number of available SNP arrays for each species has been constantly increasing. However, conversely to that observed in whole genome sequence data analysis, SNP array data does not have a common set of file formats or coding conventions for allele calling. Therefore, the standardization and integration of SNP array data from multiple sources have become an obstacle, especially for users with basic or no programming skills. Here, we describe the difficulties related to handling SNP array data, focusing on file formats, SNP allele coding, and mapping. We also present SNPConvert suite, a multi-platform, open-source, and user-friendly set of tools to overcome these issues. This tool, which can be integrated with open-source and open-access tools already available, is a first step towards an integrated system to standardize and integrate any type of raw SNP array data. The tool is available at: https://github. com/nicolazzie/SNPConvert.git. Full article
(This article belongs to the Special Issue SNP Array)
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Open AccessFeature PaperArticle
Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays
Microarrays 2016, 5(2), 16; https://doi.org/10.3390/microarrays5020016 - 08 Jun 2016
Cited by 7 | Viewed by 1958
Abstract
Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the [...] Read more.
Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts. Full article
(This article belongs to the Special Issue Antibody Microarrays in Clinical Proteomics)
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Open AccessFeature PaperArticle
Enhancing Interpretability of Gene Signatures with Prior Biological Knowledge
Microarrays 2016, 5(2), 15; https://doi.org/10.3390/microarrays5020015 - 08 Jun 2016
Cited by 2 | Viewed by 1505
Abstract
Biological interpretability is a key requirement for the output of microarray data analysis pipelines. The most used pipeline first identifies a gene signature from the acquired measurements and then uses gene enrichment analysis as a tool for functionally characterizing the obtained results. Recently [...] Read more.
Biological interpretability is a key requirement for the output of microarray data analysis pipelines. The most used pipeline first identifies a gene signature from the acquired measurements and then uses gene enrichment analysis as a tool for functionally characterizing the obtained results. Recently Knowledge Driven Variable Selection (KDVS), an alternative approach which performs both steps at the same time, has been proposed. In this paper, we assess the effectiveness of KDVS against standard approaches on a Parkinson’s Disease (PD) dataset. The presented quantitative analysis is made possible by the construction of a reference list of genes and gene groups associated to PD. Our work shows that KDVS is much more effective than the standard approach in enhancing the interpretability of the obtained results. Full article
(This article belongs to the Special Issue Computational Modeling and Analysis of Microarray Data: New Horizons)
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Open AccessArticle
Retrospective Proteomic Analysis of Cellular Immune Responses and Protective Correlates of p24 Vaccination in an HIV Elite Controller Using Antibody Arrays
Microarrays 2016, 5(2), 14; https://doi.org/10.3390/microarrays5020014 - 02 Jun 2016
Cited by 2 | Viewed by 2176
Abstract
Background: HIV p24 is an extracellular HIV antigen involved in viral replication. Falling p24 antibody responses are associated with clinical disease progression and their preservation with non-progressive disease. Stimulation of p24 antibody production by immunization to delay progression was the basis of discontinued [...] Read more.
Background: HIV p24 is an extracellular HIV antigen involved in viral replication. Falling p24 antibody responses are associated with clinical disease progression and their preservation with non-progressive disease. Stimulation of p24 antibody production by immunization to delay progression was the basis of discontinued p24 vaccine. We studied a therapy-naive HIV+ man from Sydney, Australia, infected in 1988. He received the HIV-p24-virus like particle (VLP) vaccine in 1993, and continues to show vigorous p24 antigen responses (>4% p24-specific CD4+ T cells), coupled with undetectable plasma viremia. We defined immune-protective correlates of p24 vaccination at the proteomic level through parallel retrospective analysis of cellular immune responses to p24 antigen in CD4+ and CD8+ T cells and CD14+ monocytes at viremic and aviremic phases using antibody-array. We found statistically significant coordinated up-regulation by all three cell-types with high fold-changes in fractalkine, ITAC, IGFBP-2, and MIP-1α in the aviremic phase. TECK and TRAIL-R4 were down-regulated in the viremic phase and up-regulated in the aviremic phase. The up-regulation of fractalkine in all three cell-types coincided with protective effect, whereas the dysfunction in anti-apoptotic chemokines with the loss of immune function. This study highlights the fact that induction of HIV-1-specific helper cells together with coordinated cellular immune response (p < 0.001) might be important in immunotherapeutic interventions and HIV vaccine development. Full article
(This article belongs to the Special Issue Antibody Microarrays in Clinical Proteomics)
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Open AccessArticle
Small-Molecule Inhibition of Rho/MKL/SRF Transcription in Prostate Cancer Cells: Modulation of Cell Cycle, ER Stress, and Metastasis Gene Networks
Microarrays 2016, 5(2), 13; https://doi.org/10.3390/microarrays5020013 - 28 May 2016
Cited by 5 | Viewed by 1884
Abstract
Metastasis is the major cause of cancer deaths and control of gene transcription has emerged as a critical contributing factor. RhoA- and RhoC-induced gene transcription via the actin-regulated transcriptional co-activator megakaryocytic leukemia (MKL) and serum response factor (SRF) drive metastasis in breast cancer [...] Read more.
Metastasis is the major cause of cancer deaths and control of gene transcription has emerged as a critical contributing factor. RhoA- and RhoC-induced gene transcription via the actin-regulated transcriptional co-activator megakaryocytic leukemia (MKL) and serum response factor (SRF) drive metastasis in breast cancer and melanoma. We recently identified a compound, CCG-1423, which blocks Rho/MKL/SRF-mediated transcription and inhibits PC-3 prostate cancer cell invasion. Here, we undertook a genome-wide expression study in PC-3 cells to explore the mechanism and function of this compound. There was significant overlap in the genes modulated by CCG-1423 and Latrunculin B (Lat B), which blocks the Rho/MKL/SRF pathway by preventing actin polymerization. In contrast, the general transcription inhibitor 5,6-dichloro-1-β-d-ribofuranosyl-1H-benzimidazole (DRB) showed a markedly different pattern. Effects of CCG-1423 and Lat B on gene expression correlated with literature studies of MKL knock-down. Gene sets involved in DNA synthesis and repair, G1/S transition, and apoptosis were modulated by CCG-1423. It also upregulated genes involved in endoplasmic reticulum stress. Targets of the known Rho target transcription factor family E2F and genes related to melanoma progression and metastasis were strongly suppressed by CCG-1423. These results confirm the ability of our compound to inhibit expression of numerous Rho/MKL-dependent genes and show effects on stress pathways as well. This suggests a novel approach to targeting aggressive cancers and metastasis. Full article
(This article belongs to the Special Issue Diagnostic, Prognostic and Predictive Cancer Biomarkers)
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Open AccessReview
Advantages of Array-Based Technologies for Pre-Emptive Pharmacogenomics Testing
Microarrays 2016, 5(2), 12; https://doi.org/10.3390/microarrays5020012 - 28 May 2016
Cited by 1 | Viewed by 1848
Abstract
As recognised by the National Institutes of Health (NIH) Precision Medicine Initiative (PMI), microarray technology currently provides a rapid, inexpensive means of identifying large numbers of known genomic variants or gene transcripts in experimental and clinical settings. However new generation sequencing techniques are [...] Read more.
As recognised by the National Institutes of Health (NIH) Precision Medicine Initiative (PMI), microarray technology currently provides a rapid, inexpensive means of identifying large numbers of known genomic variants or gene transcripts in experimental and clinical settings. However new generation sequencing techniques are now being introduced in many clinical genetic contexts, particularly where novel mutations are involved. While these methods can be valuable for screening a restricted set of genes for known or novel mutations, implementation of whole genome sequencing in clinical practice continues to present challenges. Even very accurate high-throughput methods with small error rates can generate large numbers of false negative or false positive errors due to the high numbers of simultaneous readings. Additional validation is likely to be required for safe use of any such methods in clinical settings. Custom-designed arrays can offer advantages for screening for common, known mutations and, in this context, may currently be better suited for accredited, quality-controlled clinical genetic screening services, as illustrated by their successful application in several large-scale pre-emptive pharmacogenomics programs now underway. Excessive, inappropriate use of next-generation sequencing may waste scarce research funds and other resources. Microarrays presently remain the technology of choice in applications that require fast, cost-effective genome-wide screening of variants of known importance, particularly for large sample sizes. This commentary considers some of the applications where microarrays continue to offer advantages over next-generation sequencing technologies. Full article
(This article belongs to the Special Issue Microarrays in the Era of Next Generation Sequencing)
Open AccessReview
Living Cell Microarrays: An Overview of Concepts
Microarrays 2016, 5(2), 11; https://doi.org/10.3390/microarrays5020011 - 26 May 2016
Cited by 7 | Viewed by 2096
Abstract
Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of [...] Read more.
Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. Full article
(This article belongs to the Special Issue Cell-Based Microarrays)
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Open AccessArticle
Stromal Activation by Tumor Cells: An in Vitro Study in Breast Cancer
Microarrays 2016, 5(2), 10; https://doi.org/10.3390/microarrays5020010 - 18 May 2016
Cited by 4 | Viewed by 2042
Abstract
Background: The tumor microenvironment participates in the regulation of tumor progression and influences treatment sensitivity. In breast cancer, it also may play a role in determining the fate of non-invasive lesions such as ductal carcinoma in situ (DCIS), a non-obligate precursor of invasive [...] Read more.
Background: The tumor microenvironment participates in the regulation of tumor progression and influences treatment sensitivity. In breast cancer, it also may play a role in determining the fate of non-invasive lesions such as ductal carcinoma in situ (DCIS), a non-obligate precursor of invasive diseases, which is aggressively treated despite its indolent nature in many patients since no biomarkers are available to predict the progression of DCIS to invasive disease. In vitro models of stromal activation by breast tumor cells might provide clues as to specific stromal genes crucial for the transition from DCIS to invasive disease. Methods: normal human dermal fibroblasts (NHDF) were treated under serum-free conditions with cell culture media conditioned by breast cancer cell lines (SkBr3, MDA-MB-468, T47D) for 72 h and subjected to gene expression profiling with Illumina platform. Results: TGM2, coding for a tissue transglutaminase, was identified as candidate gene for stromal activation. In public transcriptomic datasets of invasive breast tumors TGM2 expression proved to provide prognostic information. Conversely, its role as an early biosensor of tumor invasiveness needs to be further investigated by in situ analyses. Conclusion: Stromal TGM2 might probably be associated with precancerous evolution at earlier stages compared to DCIS. Full article
(This article belongs to the Special Issue Diagnostic, Prognostic and Predictive Cancer Biomarkers)
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Open AccessReview
Microarray-Based Comparative Genomic and Transcriptome Analysis of Borrelia burgdorferi
Microarrays 2016, 5(2), 9; https://doi.org/10.3390/microarrays5020009 - 16 Apr 2016
Cited by 6 | Viewed by 1983
Abstract
Borrelia burgdorferi, the spirochetal agent of Lyme disease, is maintained in nature in a cycle involving a tick vector and a mammalian host. Adaptation to the diverse conditions of temperature, pH, oxygen tension and nutrient availability in these two environments requires the [...] Read more.
Borrelia burgdorferi, the spirochetal agent of Lyme disease, is maintained in nature in a cycle involving a tick vector and a mammalian host. Adaptation to the diverse conditions of temperature, pH, oxygen tension and nutrient availability in these two environments requires the precise orchestration of gene expression. Over 25 microarray analyses relating to B. burgdorferi genomics and transcriptomics have been published. The majority of these studies has explored the global transcriptome under a variety of conditions and has contributed substantially to the current understanding of B. burgdorferi transcriptional regulation. In this review, we present a summary of these studies with particular focus on those that helped define the roles of transcriptional regulators in modulating gene expression in the tick and mammalian milieus. By performing comparative analysis of results derived from the published microarray expression profiling studies, we identified composite gene lists comprising differentially expressed genes in these two environments. Further, we explored the overlap between the regulatory circuits that function during the tick and mammalian phases of the enzootic cycle. Taken together, the data indicate that there is interplay among the distinct signaling pathways that function in feeding ticks and during adaptation to growth in the mammal. Full article
(This article belongs to the Special Issue Microfluidics Technology)
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Open AccessArticle
Time-Resolved Study of Nanoparticle Induced Apoptosis Using Microfabricated Single Cell Arrays
Microarrays 2016, 5(2), 8; https://doi.org/10.3390/microarrays5020008 - 15 Apr 2016
Cited by 3 | Viewed by 2218
Abstract
Cell fate decisions like apoptosis are heterogeneously implemented within a cell population and, consequently, the population response is recognized as sum of many individual dynamic events. Here, we report on the use of micro-patterned single-cell arrays for real-time tracking of nanoparticle-induced (NP) cell [...] Read more.
Cell fate decisions like apoptosis are heterogeneously implemented within a cell population and, consequently, the population response is recognized as sum of many individual dynamic events. Here, we report on the use of micro-patterned single-cell arrays for real-time tracking of nanoparticle-induced (NP) cell death in sets of thousands of cells in parallel. Annexin (pSIVA) and propidium iodide (PI), two fluorescent indicators of apoptosis, are simultaneously monitored after exposure to functionalized polystyrene (PS NH 2) nanobeads as a model system. We find that the distribution of Annexin onset times shifts to later times and broadens as a function of decreasing NP dose. We discuss the mean time-to-death as a function of dose, and show how the EC 50 value depends both on dose and time of measurement. In addition, the correlations between the early and late apoptotic markers indicate a systematic shift from apoptotic towards necrotic cell death during the course of the experiment. Thus, our work demonstrates the potential of array-based single cell cytometry for kinetic analysis of signaling cascades in a high-throughput format. Full article
(This article belongs to the Special Issue Cell-Based Microarrays)
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Open AccessFeature PaperArticle
A Mismatch EndoNuclease Array-Based Methodology (MENA) for Identifying Known SNPs or Novel Point Mutations
Microarrays 2016, 5(2), 7; https://doi.org/10.3390/microarrays5020007 - 05 Apr 2016
Cited by 1 | Viewed by 2005
Abstract
Accurate and rapid identification or confirmation of single nucleotide polymorphisms (SNPs), point mutations and other human genomic variation facilitates understanding the genetic basis of disease. We have developed a new methodology (called MENA (Mismatch EndoNuclease Array)) pairing DNA mismatch endonuclease enzymology with tiling [...] Read more.
Accurate and rapid identification or confirmation of single nucleotide polymorphisms (SNPs), point mutations and other human genomic variation facilitates understanding the genetic basis of disease. We have developed a new methodology (called MENA (Mismatch EndoNuclease Array)) pairing DNA mismatch endonuclease enzymology with tiling microarray hybridization in order to genotype both known point mutations (such as SNPs) as well as identify previously undiscovered point mutations and small indels. We show that our assay can rapidly genotype known SNPs in a human genomic DNA sample with 99% accuracy, in addition to identifying novel point mutations and small indels with a false discovery rate as low as 10%. Our technology provides a platform for a variety of applications, including: (1) genotyping known SNPs as well as confirming newly discovered SNPs from whole genome sequencing analyses; (2) identifying novel point mutations and indels in any genomic region from any organism for which genome sequence information is available; and (3) screening panels of genes associated with particular diseases and disorders in patient samples to identify causative mutations. As a proof of principle for using MENA to discover novel mutations, we report identification of a novel allele of the beethoven (btv) gene in Drosophila, which encodes a ciliary cytoplasmic dynein motor protein important for auditory mechanosensation. Full article
(This article belongs to the Special Issue Microarrays in the Era of Next Generation Sequencing)
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