Improved microarray gene expression profiling of virus-infected cells after removal of viral RNA

<p>Abstract</p> <p>Background</p> <p>Sensitivity and accuracy are key points when using microarrays to detect alterations in gene expression under different conditions. Critical to the acquisition of reliable results is the preparation of the RNA. In the field of virology, when analyzing the host cell's reaction to infection, the often high representation of viral RNA (vRNA) within total RNA preparations from infected cells is likely to interfere with microarray analysis. Yet, this effect has not been investigated despite the many reports that describe gene expression profiling of virus-infected cells using microarrays.</p> <p>Results</p> <p>In this study we used coronaviruses as a model to show that vRNA indeed interferes with microarray analysis, decreasing both sensitivity and accuracy. We also demonstrate that the removal of vRNA from total RNA samples, by means of virus-specific oligonucleotide capturing, significantly reduced the number of false-positive hits and increased the sensitivity of the method as tested on different array platforms.</p> <p>Conclusion</p> <p>We therefore recommend the specific removal of vRNA, or of any other abundant 'contaminating' RNAs, from total RNA samples to improve the quality and reliability of microarray analyses.</p

Abstract 1870: Development of a standard operating procedure for exosome isolation and analysis using clinical samples: Application to cancer biomarker discovery

Abstract Exosomes are small vesicles (30-150 nm) found in abundance in human body fluids which function as carriers of different species of RNA and protein between diverse locations in the body. The spectrum of current scientific interest in exosomes is wide and ranges from studying their functions and pathways to utilizing them in diagnostics and therapeutics development. As such, there is a growing need for quick and easy methods for both isolation of exosomes and analysis of their cargo. We present herein a workflow for exosome isolation and analysis which entails: (i) fast and efficient isolation of exosomes from serum, plasma, and urine of both healthy donors and patients with prostate cancer, using Total Exosome Isolation reagents; (ii) characterization of their size distribution and count with Nanosight LM10 instrument; (iii) extraction of exosome “cargo” with Total Exosome RNA and Protein Isolation kit; (iv) characterization of exosomal RNA content using the Ion Torrent PGM sequencing and qRT-PCR. The protocol described herein lays the groundwork for the development of a standardized operating procedure (SOP) for isolation of exosomes and downstream analysis of their constituents, using clinical samples. We demonstrate that cancer-specific RNA signatures residing within the exosomes can be delineated from different patient cohorts. This is the first step towards developing a method whereby performance characteristics can be measured and used to optimize a validated assay useful for routine testing of clinical samples. Citation Format: Robert A. Setterquist, Alex J. Rai, Emily Zeringer, Mu Li, Tim Barta, Jeoffrey Schageman, Susan Magdaleno, Alexander V. Vlassov. Development of a standard operating procedure for exosome isolation and analysis using clinical samples: Application to cancer biomarker discovery. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1870. doi:10.1158/1538-7445.AM2014-1870</jats:p

Abstract 1382: A complete workflow for high-throughput isolation and analysis of cell-free DNA from urine

Abstract Circulating cell-free DNA (cfDNA) shed from tumors has gained considerable attention as a source of nucleic acid for testing cancer biomarkers. Critical to finding and implementing a diagnostic biomarker for cfDNA is the consistent and efficient isolation of the nucleic acid from blood. Sample preparation technologies are now commercially available for cfDNA isolation from plasma and serum, making these sample types used for most applications. However, plasma and serum require blood drawn by trained phlebotomist and only limited amounts can be obtained; additionally, individuals with advanced disease usually require routine monitoring and may not be able to spare additional blood drawn for cfDNA testing. Recently, it has been appreciated that urine may also serve as a valuable source for cfDNA. DNA from tissues and organs of the genitourinary system may be shed directly into urine and cfDNA circulating in blood can filter through the glomeruli in the kidneys to end up in urine. Compared to plasma and serum, urine is much easier to obtain, does not require a needle stick, and it can be collected in larger volumes making longitudinal studies more accessible. Urine presents a number of new challenges for the preparation of cfDNA that need to be overcome before this sample source can truly be utilized. The objective of this project was to develop reagents and workflows optimized for analysis of cfDNA from urine. Through our studies, we found that the slightly shorter cfDNA in urine requires optimized chemistry to maximize yield, a larger volume of urine may be necessary to isolate sufficient cfDNA compared to plasma/serum and urine must be treated with stabilization agents to minimize further degradation of cfDNA after collection. Using the MagMAX™ cell-free DNA isolation kit, we have developed a magnetic bead-based sample preparation protocol specific for isolating cfDNA from urine. Workflows for preparing cfDNA from urine through manual processing or by automated high throughput sample processing on the KingFisher™ instruments were developed. A small cohort of healthy donors was used to demonstrate compatibility of the cfDNA with qPCR, dPCR and next generation sequencing platforms. The effectiveness of this fast and easy workflow will be further tested on cfDNA from urine samples from donors with and without metastatic disease. We will analyze cfDNA from paired urine and plasma to understand the applicability to different tumor types. Citation Format: Alex J. Rai, Robert A. Setterquist, Xingwang Fang, Hannah E. Saunders, Matthew Carter, Charmaine San Jose Hinahon, Sarah E. Larocca, Susan M. Magdaleno. A complete workflow for high-throughput isolation and analysis of cell-free DNA from urine. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1382.</jats:p

Improved microarray gene expression profiling of virus-infected cells after removal of viral RNA-1

ActD (20 μg/ml) 1 h prior to infection, and maintained in the presence of this drug throughout the experiment. Total RNA was isolated from mock- or MHV-infected cells at 6 h p.i. (A) A representative mRNA amplification plot of a total RNA sample derived from MHV-infected, ActD-treated cells at 6 h p.i. The arrow indicates the marker peak. (B) The scatter plot displays the average expression values from independent dye-swap hybridizations (n = 6) for each gene present on the arrays as described in legend of Fig.2. (C) The Venn diagram shows a comparison between the experiments in the absence or presence of ActD.<p><b>Copyright information:</b></p><p>Taken from "Improved microarray gene expression profiling of virus-infected cells after removal of viral RNA"</p><p>http://www.biomedcentral.com/1471-2164/9/221</p><p>BMC Genomics 2008;9():221-221.</p><p>Published online 14 May 2008</p><p>PMCID:PMC2397413.</p><p></p

Improved microarray gene expression profiling of virus-infected cells after removal of viral RNA-4

Ive RT-PCR at the indicated time points. The data are presented as relative vRNA levels. (B) Successful amplification of the mRNA within the individual samples was monitored by analyzing the cRNA samples with a Bioanalyzer (Agilent), according to the manufacturer's instructions. Representative mRNA amplification plots of total RNA samples obtained from mock- or MHV-infected cells at 4 h and 6 h p.i. are shown. The indicated plots represent the size distribution of the total mRNA content present in the samples. The marker peak is indicated by the arrow. Note that the scaling is different between the plots in order to visualize the complete profile. (C) Total RNA was isolated and processed for microarray analysis as described in the Methods section. The scatter plots display the average expression values from independent dye-swap hybridizations (n = 6) for each gene present on the arrays at the indicated time-points p.i. Red spots represent upregulated gene transcripts while green spots represent downregulated gene transcripts upon infection of cells with MHV. The dashed lines indicate the 2-fold change cut-off.<p><b>Copyright information:</b></p><p>Taken from "Improved microarray gene expression profiling of virus-infected cells after removal of viral RNA"</p><p>http://www.biomedcentral.com/1471-2164/9/221</p><p>BMC Genomics 2008;9():221-221.</p><p>Published online 14 May 2008</p><p>PMCID:PMC2397413.</p><p></p

Improved microarray gene expression profiling of virus-infected cells after removal of viral RNA-2

To the vRNA depletion protocol as detailed in the Materials and methods section. (A) Amplification of the mRNA was monitored by analyzing the cRNA samples with a Bioanalyzer. A representative mRNA amplification plot of a total RNA sample derived from MHV-infected cells at 6 h p.i. after vRNA removal is shown. The arrow indicates the marker peak. (B) Total RNA samples were treated with the biotinylated oligo's (indicated as vRNA depleted) and were processed for microarray analysis as described in the Methods section. The scatter plots display the average expression values from independent dye-swap hybridizations (n = 6) for each gene present on the arrays as described in legend of Fig.2. (C) The Venn diagrams show a comparison between the experiments with and without vRNA depletion.<p><b>Copyright information:</b></p><p>Taken from "Improved microarray gene expression profiling of virus-infected cells after removal of viral RNA"</p><p>http://www.biomedcentral.com/1471-2164/9/221</p><p>BMC Genomics 2008;9():221-221.</p><p>Published online 14 May 2008</p><p>PMCID:PMC2397413.</p><p></p