Shane Marine

New Regulators of Wnt/β-Catenin Signaling Revealed by Integrative Molecular Screening

Integration of protein-protein interaction networks and human genome-wide RNAi screens produces mechanistic insight into Wnt/β-catenin signaling. Finding the Right Candidate A genome-wide RNAi screen in human colon cancer cells, followed by two additional validation steps, reveals new components of the Wnt pathway. Combining RNAi analysis with protein-protein interaction data provides a powerful approach that not only identifies new players in a signaling pathway, but also provides functional insight about the modulators, leading to the generation of testable hypotheses. The identification and characterization of previously unidentified signal transduction molecules has expanded our understanding of biological systems and facilitated the development of mechanism-based therapeutics. We present a highly validated small interfering RNA (siRNA) screen that functionally annotates the human genome for modulation of the Wnt/β-catenin signal transduction pathway. Merging these functional data with an extensive Wnt/β-catenin protein interaction network produces an integrated physical and functional map of the pathway. The power of this approach is illustrated by the positioning of siRNA screen hits into discrete physical complexes of proteins. Similarly, this approach allows one to filter discoveries made through protein-protein interaction screens for functional contribution to the phenotype of interest. Using this methodology, we characterized AGGF1 as a nuclear chromatin-associated protein that participates in β-catenin–mediated transcription in human colon cancer cells.

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 Alzheimers disease (AD) are thought to be caused by elevated proteolytic production of the Aβ42 peptide from the β-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 Aβ42, 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 Aβ42 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 Aβ40, Aβ42, and sAPPβ, the N-terminal APP fragment produced by BACE1 cleavage, from cultured cells and primary neurons by up to 60%, whereas overexpression increases Aβ 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 Aβ42, 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.

The Use of Strictly Standardized Mean Difference for Hit Selection in Primary RNA Interference High-Throughput Screening Experiments

RNA interference (RNAi) high-throughput screening (HTS) has been hailed as the 2nd genomics wave following the 1st genomics wave of gene expression microarrays and single-nucleotide polymorphism discovery platforms. Following an RNAi HTS, the authors are interested in identifying short interfering RNA (siRNA) hits with large inhibition/activation effects. For hit selection, the z-score method and its variants are commonly used in primary RNAi HTS experiments. Recently, strictly standardized mean difference (SSMD) has been proposed to measure the siRNA effect represented by the magnitude of difference between an siRNA and a negative reference group. The links between SSMD and d +-probability offer a clear interpretation of siRNA effects from a probability perspective. Hence, SSMD can be used as a ranking metric for hit selection. In this article, the authors investigated both the SSMD-based testing process and the use of SSMD as a ranking metric for hit selection in 2 primary siRNA HTS experiments. The analysis results showed that, as a ranking metric, SSMD was more stable and reliable than percentage inhibition and led to more robust hit selection results. Using the SSMD -based testing method, the false-negative rate can more readily be obtained. More important, the use of the SSMD-based method can result in a reduction in both the false-negative and false-positive rates. The applications presented in this article demonstrate that the SSMD method addresses scientific questions and fills scientific needs better than both percentage inhibition and the commonly used z-score method for hit selection. (Journal of Biomolecular Screening 2007:497-509)

siRNA off-target effects in genome-wide screens identify signaling pathway members

We introduce a method for analyzing small interfering RNA (siRNA) genetic screens based entirely on off-target effects. Using a screen for members of the Wnt pathway, we demonstrate that this method identifies known pathway components, some of which are not present in the screening library. This technique can be applied to siRNA screen results retroactively to confirm positives and identify genes missed using conventional methods for on-target gene selection.

Hit selection with false discovery rate control in genome-scale RNAi screens

RNA interference (RNAi) is a modality in which small double-stranded RNA molecules (siRNAs) designed to lead to the degradation of specific mRNAs are introduced into cells or organisms. siRNA libraries have been developed in which siRNAs targeting virtually every gene in the human genome are designed, synthesized and are presented for introduction into cells by transfection in a microtiter plate array. These siRNAs can then be transfected into cells using high-throughput screening (HTS) methodologies. The goal of RNAi HTS is to identify a set of siRNAs that inhibit or activate defined cellular phenotypes. The commonly used analysis methods including median ± kMAD have issues about error rates in multiple hypothesis testing and plate-wise versus experiment-wise analysis. We propose a methodology based on a Bayesian framework to address these issues. Our approach allows for sharing of information across plates in a plate-wise analysis, which obviates the need for choosing either a plate-wise or experimental-wise analysis. The proposed approach incorporates information from reliable controls to achieve a higher power and a balance between the contribution from the samples and control wells. Our approach provides false discovery rate (FDR) control to address multiple testing issues and it is robust to outliers.

Integrating Experimental and Analytic Approaches to Improve Data Quality in Genome-wide RNAi Screens

RNA interference (RNAi) not only plays an important role in drug discovery but can also be developed directly into drugs. RNAi high-throughput screening (HTS) biotechnology allows us to conduct genome-wide RNAi research. A central challenge in genome-wide RNAi research is to integrate both experimental and computational approaches to obtain high quality RNAi HTS assays. Based on our daily practice in RNAi HTS experiments, we propose the implementation of 3 experimental and analytic processes to improve the quality of data from RNAi HTS biotechnology: (1) select effective biological controls; (2) adopt appropriate plate designs to display and/or adjust for systematic errors of measurement; and (3) use effective analytic metrics to assess data quality. The applications in 5 real RNAi HTS experiments demonstrate the effectiveness of integrating these processes to improve data quality. Due to the effectiveness in improving data quality in RNAi HTS experiments, the methods and guidelines contained in the 3 experimental and analytic processes are likely to have broad utility in genome-wide RNAi research. (Journal of Biomolecular Screening 2008:378-389)

USP6 oncogene promotes Wnt signaling by deubiquitylating Frizzleds

Significance Ubiquitin-specific protease 6 (USP6) is a deubiquitylase that is overexpressed by chromosome translocation in two human neoplasms, aneurysmal bone cyst and nodular fasciitis. The relevant substrates of this ubiquitin-specific protease are not clear. Here, we identify the Wnt receptor Frizzled (Fzd) as a key target of the USP6 oncogene. Increased expression of USP6 increases the membrane abundance of Fzd, and hence increases cellular sensitivity to Wnts. USP6 opposes the activity of the ubiquitin ligase and tumor suppressor ring finger protein 43 (RNF43). This study identifies a new mechanism for pathological Wnt pathway activation in human disease and suggests a new approach to regulate Wnt activity therapeutically. The Wnt signaling pathways play pivotal roles in carcinogenesis. Modulation of the cell-surface abundance of Wnt receptors is emerging as an important mechanism for regulating sensitivity to Wnt ligands. Endocytosis and degradation of the Wnt receptors Frizzled (Fzd) and lipoprotein-related protein 6 (LRP6) are regulated by the E3 ubiquitin ligases zinc and ring finger 3 (ZNRF3) and ring finger protein 43 (RNF43), which are disrupted in cancer. In a genome-wide small interfering RNA screen, we identified the deubiquitylase ubiquitin-specific protease 6 (USP6) as a potent activator of Wnt signaling. USP6 enhances Wnt signaling by deubiquitylating Fzds, thereby increasing their cell-surface abundance. Chromosomal translocations in nodular fasciitis result in USP6 overexpression, leading to transcriptional activation of the Wnt/β-catenin pathway. Inhibition of Wnt signaling using Dickkopf-1 (DKK1) or a Porcupine (PORCN) inhibitor significantly decreased the growth of USP6-driven xenograft tumors, indicating that Wnt signaling is a key target of USP6 during tumorigenesis. Our study defines an additional route to ectopic Wnt pathway activation in human disease, and identifies a potential approach to modulate Wnt signaling for therapeutic benefit.

The Use of SSMD-Based False Discovery and False Nondiscovery Rates in Genome-Scale RNAi Screens

In genome-scale RNA interference (RNAi) screens, it is critical to control false positives and false negatives statistically. Traditional statistical methods for controlling false discovery and false nondiscovery rates are inappropriate for hit selection in RNAi screens because the major goal in RNAi screens is to control both the proportion of short interfering RNAs (siRNAs) with a small effect among selected hits and the proportion of siRNAs with a large effect among declared nonhits. An effective method based on strictly standardized mean difference (SSMD) has been proposed for statistically controlling false discovery rate (FDR) and false nondiscovery rate (FNDR) appropriate for RNAi screens. In this article, the authors explore the utility of the SSMD-based method for hit selection in RNAi screens. As demonstrated in 2 genome-scale RNAi screens, the SSMD-based method addresses the unmet need of controlling for the proportion of siRNAs with a small effect among selected hits, as well as controlling for the proportion of siRNAs with a large effect among declared nonhits. Furthermore, the SSMD-based method results in reasonably low FDR and FNDR for selecting inhibition or activation hits. This method works effectively and should have a broad utility for hit selection in RNAi screens with replicates.

Pathway-Based Analysis of Genome-Wide siRNA Screens Reveals the Regulatory Landscape of App Processing

The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimers Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPPα. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the “regulatory landscape” of APP.

A 1,536-well ultra-high-throughput siRNA screen to identify regulators of the Wnt/β-catenin pathway

High-throughput siRNA screens are now widely used for identifying novel drug targets and mapping disease pathways. Despite their popularity, there remain challenges related to data variability, primarily due to measurement errors, biological variance, uneven transfection efficiency, the efficacy of siRNA sequences, or off-target effects, and consequent high false discovery rates. Data variability can be reduced if siRNA screens are performed in replicate. Running a large-scale siRNA screen in replicate is difficult, however, because of the technical challenges related to automating complicated steps of siRNA transfection, often with multiplexed assay readouts, and controlling environmental humidity during long incubation periods. Small-molecule screens have greatly benefited in the past decade from assay miniaturization to high-density plates such that 1,536-well nanoplate screenings are now a routine process, allowing fast, efficient, and affordable operations without compromising underlying biology or important assay characteristics. Here, we describe the development of a 1,536-well nanoplate siRNA transfection protocol that utilizes the instruments commonly found in small-molecule high throughput screening laboratories. This protocol was then successfully demonstrated in a triplicate large-scale siRNA screen for the identification of regulators of the Wnt/beta-catenin pathway.