NanoString nCounter Analysis System Research Articles

NanoStriDE: normalization and differential expression analysis of NanoString nCounter data

BackgroundThe nCounter analysis system (NanoString Technologies, Seattle, WA) is a technology that enables the digital quantification of multiplexed target RNA molecules using color-coded molecular barcodes and single-molecule imaging. This system gives discrete counts of RNA transcripts and is capable of providing a high level of precision and sensitivity at less than one transcript copy per cell.ResultsWe have designed a web application compatible with any modern web browser that accepts the raw count data produced by the NanoString nCounter analysis system, normalizes it according to guidelines provided by NanoString Technologies, performs differential expression analysis on the normalized data, and provides a heatmap of the results from the differential expression analysis.ConclusionNanoStriDE allows biologists to take raw data produced by a NanoString nCounter analysis system and easily interpret differential expression analysis of this data represented through a heatmap. NanoStriDE is freely accessible to use on the NanoStriDE website and is available to use under the GPL v2 license.

Abstract 1192: Regulation of CCND2, HMGA2, and the IGF pathway by LIN28B in HPV negative head and neck squamous cell carcinoma (HNSCC)

Abstract Background: Lin28 and Lin28B have recently been implicated in the post-transcriptional regulation of Let-7/miR-98 biogenesis. While Lin28B over-expression has been associated with worse clinical outcome in several human cancers, the prognostic significance of Lin28B expression and the molecular mechanism(s) by which it drives tumour progression remains largely unknown. Methods: Let-7-Resist Lin28B-expression plasmid was stably transfected into the FaDu human hypopharyngeal squamous cell carcinoma line. MicoRNA expression profiling was conducted using the Nanostring nCounter Analysis System. Genome-wide micro-array and in silico analyses were utilized to identify Let-7/miR-98 targets. Cell viability and apoptosis were measured using MTS assay and flow cytometry, respectively. In vivo experiments were conducted using SCID mice. Results: qRT-PCR analysis of genes involved in the miRNA biogenesis pathway (DICER, LIN28, LIN28B, and TUT4) suggested an inverse relationship between the expression of Lin28B and mature Let-7 miRNA. Over-expression of Lin28B mediated significant increase in the migration of FaDu cells in vitro, and tumor growth in SCID mice, which in turn, was associated with marked reduction in the Let-7 family of microRNAs. Using a tri-Pronged approach by combining prediction algorithms, experimentally-derived mRNA profiling, along with gene expression data in primary HNSCC samples identified several upregulated Let-7/miR98 gene targets in Lin28B-FaDu cells, including CCND2, HMGA2, and regulators of the insulin growth factor (IGF) mitogenic pathway. Concordantly, treating FaDu-Lin28B cells with IGF (10-50 nM) led to a 26% and 50% increase in cell viability under stress conditions (serum starvation), whereas treating FaDu-GFP cells with IGF had no effect on viability, suggesting the relevance of the IGF axis in FaDu-Lin28B cells. Furthermore, analyzing publicly available data sets on primary HPV positive vs. HPV negative HNSCC samples revealed a significantly higher expression of HMGA2, and genes that regulate the IGF pathway in the latter group of tumours, suggesting a possible role for Lin28B, Let-7/miR-98 and their downstream targets in mediating the more aggressive behavior of HPV negative HNSCC. Conclusions: Our data report for the first time, a potentially important role for Lin28B in regulating the IGF mitogenic pathway, as one possible mechanism in driving the biological behaviour of HPV negative HNSCC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1192. doi:10.1158/1538-7445.AM2011-1192

Orientation and expression of methicillin-resistant Staphylococcus aureus small RNAs by direct multiplexed measurements using the nCounter of NanoString technology

Staphylococcus aureus is a versatile bacterial opportunist responsible for a wide spectrum of infections. Several genomes of this major human pathogen have been publicly available for almost 10 years, but comprehensive links between virulence or epidemicity and genome content of the bacterium are still missing. This project aims at characterizing a set of small transcribed molecules currently ignored by standard automated annotation algorithms. We assessed the NanoString's nCounter Analysis System for its ability to determine the orientation and quantity of the expressed small RNA (sRNA) molecules that we recently detected with RNA-Sequencing (RNA-Seq). The expression of approximately seventy small RNAs, including sRNA localized in pathogenic islands, was assessed at 5 time points during growth of the bacterium in a rich medium. In addition, two extraction strategies were tested: RNA was either purified on columns or simply prepared from crude lysates in the presence of a chaotropic buffer. The nCounter System allowed us to perform these 64 measurements in a single experiment, without any enzymatic reaction, thus avoiding well-known technical biases. We evaluated the reproducibility and reliability of the nCounter compared to quantitative RT-PCR (RT-qPCR). By using two different designs for the two coding strands, we were able to identify the coding strand of 61 small RNA molecules (95%). Overall, the nCounter System provided an identification of the coding strand in perfect concordance with RNA-Seq data. In addition, expression results were also comparable to those obtained with RT-qPCR. The sensitivity and minimal requirements of the nCounter system open new possibilities in the field of gene expression analysis, for assessing bacterial transcript profiles from complex media (i.e. during host–pathogen interactions) or when starting from poorly purified RNA or even directly from lysed infected tissues.