Biomedical subjects

Erica Stec

Publications and source records attributed to Erica Stec.

3 recordsLinked to original sources

PubMed2006

LRRTM3 promotes processing of amyloid-precursor protein by BACE1 and is a positional candidate gene for late-onset Alzheimer's disease.

Rare familial forms of Alzheimer's disease (AD) are thought to be caused by elevated proteolytic production of the Abeta42 peptide from the beta-amyloid-precursor protein (APP). Although the pathogenesis of the more common late-onset AD (LOAD) is not understood, BACE1, the protease that cleaves APP to generate the N terminus of Abeta42, is more active in patients with LOAD, suggesting that increased amyloid production processing might also contribute to the sporadic disease. Using high-throughput siRNA screening technology, we assessed 15,200 genes for their role in Abeta42 secretion and identified leucine-rich repeat transmembrane 3 (LRRTM3) as a neuronal gene that promotes APP processing by BACE1. siRNAs targeting LRRTM3 inhibit the secretion of Abeta40, Abeta42, and sAPPbeta, the N-terminal APP fragment produced by BACE1 cleavage, from cultured cells and primary neurons by up to 60%, whereas overexpression increases Abeta secretion. LRRTM3 is expressed nearly exclusively in the nervous system, including regions affected during AD, such as the dentate gyrus. Furthermore, LRRTM3 maps to a region of chromosome 10 linked to both LOAD and elevated plasma Abeta42, and is structurally similar to a family of neuronal receptors that includes the NOGO receptor, an inhibitor of neuronal regeneration and APP processing. Thus, LRRTM3 is a functional and positional candidate gene for AD, and, given its receptor-like structure and restricted expression, a potential therapeutic target.

Alzheimer Disease↗

PubMed2006

Robust statistical methods for hit selection in RNA interference high-throughput screening experiments.

RNA interference (RNAi) high-throughput screening (HTS) experiments carried out using large (>5000 short interfering [si]RNA) libraries generate a huge amount of data. In order to use these data to identify the most effective siRNAs tested, it is critical to adopt and develop appropriate statistical methods. To address the questions in hit selection of RNAi HTS, we proposed a quartile-based method which is robust to outliers, true hits and nonsymmetrical data. We compared it with the more traditional tests, mean +/- k standard deviation (SD) and median +/- 3 median of absolute deviation (MAD). The results suggested that the quartile-based method selected more hits than mean +/- k SD under the same preset error rate. The number of hits selected by median +/- k MAD was close to that by the quartile-based method. Further analysis suggested that the quartile-based method had the greatest power in detecting true hits, especially weak or moderate true hits. Our investigation also suggested that platewise analysis (determining effective siRNAs on a plate-by-plate basis) can adjust for systematic errors in different plates, while an experimentwise analysis, in which effective siRNAs are identified in an analysis of the entire experiment, cannot. However, experimentwise analysis may detect a cluster of true positive hits placed together in one or several plates, while platewise analysis may not. To display hit selection results, we designed a specific figure called a plate-well series plot. We thus suggest the following strategy for hit selection in RNAi HTS experiments. First, choose the quartile-based method, or median +/- k MAD, for identifying effective siRNAs. Second, perform the chosen method experimentwise on transformed/normalized data, such as percentage inhibition, to check the possibility of hit clusters. If a cluster of selected hits are observed, repeat the analysis based on untransformed data to determine whether the cluster is due to an artifact in the data. If no clusters of hits are observed, select hits by performing platewise analysis on transformed data. Third, adopt the plate-well series plot to visualize both the data and the hit selection results, as well as to check for artifacts.

Cluster Analysis↗

PubMed2004

A cell-based beta-lactamase reporter gene assay for the identification of inhibitors of hepatitis C virus replication.

This report describes the development, optimization, and implementation of a cell-based assay for high-throughput screening (HTS) to identify inhibitors to hepatitis C virus (HCV) replication. The assay is based on a HCV subgenomic RNA replicon that expresses beta-lactamase as a reporter for viral replication in enhanced Huh-7 cells. The drug targets in this assay are viral and cellular enzymes required for HCV replication, which are monitored by fluorescence resonance energy transfer using cell-permeable CCF4-AM as a beta-lactamase substrate. Digital image processing was used to visualize cells that harbor viral RNA and to optimize key assay development parameters such as transfection and culturing conditions to obtain a cell line which produced a robust assay window. Formatting the assay for compound screening was problematic due to small signal-to-background ratio and reduced potency to known HCV inhibitors. These technical difficulties were solved by using clavulanic acid, an irreversible inhibitor of beta-lactamase, to eliminate residual beta-lactamase activity after HCV replication was terminated, thus resulting in an improved assay window. HTS was carried out in 384-well microplate format, and the signal-to-background ratio and Z factor for the assay plates during the screen were approximately 13-fold and 0.5, respectively.

Antiviral Agents↗