High-throughput siRNA screening as a method of perturbation of biological systems and identification of targeted pathways coupled with compound screening

RefCell: multi-dimensional analysis of image-based high-throughput screens based on 'typical cells'

BACKGROUND

Image-based high-throughput screening (HTS) reveals a high level of heterogeneity in single cells and multiple cellular states may be observed within a single population. Currently available high-dimensional analysis methods are successful in characterizing cellular heterogeneity, but suffer from the "curse of dimensionality" and non-standardized outputs.

RESULTS

Here we introduce RefCell, a multi-dimensional analysis pipeline for image-based HTS that reproducibly captures cells with typical combinations of features in reference states and uses these "typical cells" as a reference for classification and weighting of metrics. RefCell quantitatively assesses heterogeneous deviations from typical behavior for each analyzed perturbation or sample.

CONCLUSIONS

We apply RefCell to the analysis of data from a high-throughput imaging screen of a library of 320 ubiquitin-targeted siRNAs selected to gain insights into the mechanisms of premature aging (progeria). RefCell yields results comparable to a more complex clustering-based single-cell analysis method; both methods reveal more potential hits than a conventional analysis based on averages.

Establishing an Infrastructure for High-Throughput Short-Interfering RNA Screening

RNA interference (RNAi) is a readily available research tool that can be used to accelerate the identification and functional validation of a multitude of new candidate drug targets by experimentally perturbing gene expression and function. High-throughput RNAi technology using libraries of short-interfering RNA (siRNA) makes it possible to rapidly identify genes and biomarkers associated with biological processes such as diseases or a cellular response to therapy. Thus, RNAi-based screening is an extremely powerful technology that can provide tremendous insights into the mechanisms of action and contexts of vulnerability of a particular drug treatment. This chapter describes the infrastructure requirements needed to successfully perform HT-RNAi screening. Information on the methodology, instrumentation, experimental design, and workflow aspects is provided, as well as insights on how to successfully implement a high-throughput RNAi screen.

High Throughput siRNA Screening Using Reverse Transfection

RNA interference (RNAi) is a commonly used technique to knockdown gene function. Here, we describe a high throughput screening method for siRNA mediated gene silencing of the breast cancer cell line MDA-MB-231 using reverse transfection. Furthermore, we describe the setup for two separate methods for detecting viable and dead cells using either homogenous assays or image-based analysis.

siRNAs with decreased off-target effect facilitate the identification of essential genes in cancer cells

Since the essential genes are crucial to the proliferation and survival of cancer cells, the interference of these genes is promising to be an option for cancer therapy to overcome heterogeneity. However, the essential genes are highly overestimated by RNA interference (RNAi) screenings, which is mainly caused by the pervasive off-target effect of small interference RNA (siRNA) and short hairpin RNA (shRNA). In the present study, we designed Match-Mismatch paired siRNAs to discriminate the on-target effect from off-target effect of siRNAs on cell viability. Only one of the 7 potential essential genes was validated as essential to cell viability, which demonstrates the high false positive rate in RNAi screenings. We modified the siRNA by introducing random nucleotides (N) into the guide strand to mitigate the off-target effect, without significantly compromising the on-target effect. The whole transcriptome profile analysis of cells transfected with siRNAs with or without Nindicates that siRNA-dN (with Ns on both the 2^nd and the 18^th bases of the guide strand) weakens the off-target effect by decreasing the unintended targets. The optimized siRNAs can be applied in the characterization of essential genes in cancer cells.

High-Throughput RNAi Screening Identifies a Role for the Osteopontin Pathway in Proliferation and Migration of Human Aortic Smooth Muscle Cells

PURPOSE

Understanding of the mechanisms of vascular smooth muscle cells (VSMCs) phenotypic regulation is critically important to identify novel candidates for future therapeutic intervention. While HTS approaches have recently been used to identify novel regulators in many cell lines, such as cancer cells and hematopoietic stem cells, no studies have so far systematically investigated the effect of gene inactivation on VSMCs with respect to cell survival and growth response.

METHODS AND RESULTS

257 out of 2000 genes tested resulted in an inhibition of cell proliferation in HaoSMCs. After pathway analysis, 38 significant genes were selected for further study. 23 genes were confirmed to inhibit proliferation, and 13 genes found to induce apoptosis in the synthetic phenotype. 11 genes led to an aberrant nuclear phenotype indicating a central role in cell mitosis. 4 genes affected the cell migration in synthetic HaoSMCs. Using computational biological network analysis, 11 genes were identified to have an indirect or direct interaction with the Osteopontin pathway. For 10 of those genes, levels of proteins downstream of the Osteopontin pathway were found to be down-regulated, using RNAi methodology.

CONCLUSIONS

A phenotypic high-throughput siRNA screen could be applied to identify genes relevant for the cell biology of HaoSMCs. Novel genes were identified which play a role in proliferation, apoptosis, mitosis and migration of HaoSMCs. These may represent potential drug candidates in the future.

Functional toxicology: tools to advance the future of toxicity testing

The increased presence of chemical contaminants in the environment is an undeniable concern to human health and ecosystems. Historically, by relying heavily upon costly and laborious animal-based toxicity assays, the field of toxicology has often neglected examinations of the cellular and molecular mechanisms of toxicity for the majority of compounds—information that, if available, would strengthen risk assessment analyses. Functional toxicology, where cells or organisms with gene deletions or depleted proteins are used to assess genetic requirements for chemical tolerance, can advance the field of toxicity testing by contributing data regarding chemical mechanisms of toxicity. Functional toxicology can be accomplished using available genetic tools in yeasts, other fungi and bacteria, and eukaryotes of increased complexity, including zebrafish, fruit flies, rodents, and human cell lines. Underscored is the value of using less complex systems such as yeasts to direct further studies in more complex systems such as human cell lines. Functional techniques can yield (1) novel insights into chemical toxicity; (2) pathways and mechanisms deserving of further study; and (3) candidate human toxicant susceptibility or resistance genes.

Functional annotation of differentially regulated gene set using WebGestalt: a gene set predictive of response to ipilimumab in tumor biopsies

Most high-throughput methods which are used in molecular biology generate gene lists. Interpreting large gene lists can reveal mechanistic insights and generate useful testable hypotheses. The process can be cumbersome and challenging. Multiple commercial and open solution currently exist that can aid researchers in the functional annotation of gene lists. The process of gene set annotation includes dataset preparation, which is method specific, gene list annotation and analysis and interpretation of the significant associations that were found. In this chapter, we demonstrate how WebGestalt can be applied to gene lists generated from transcriptional profiling data.

Discovering thiamine transporters as targets of chloroquine using a novel functional genomics strategy

Chloroquine (CQ) and other quinoline-containing antimalarials are important drugs with many therapeutic benefits as well as adverse effects. However, the molecular targets underlying most such effects are largely unknown. By taking a novel functional genomics strategy, which employs a unique combination of genome-wide drug-gene synthetic lethality (DGSL), gene-gene synthetic lethality (GGSL), and dosage suppression (DS) screens in the model organism Saccharomyces cerevisiae and is thus termed SL/DS for simplicity, we found that CQ inhibits the thiamine transporters Thi7, Nrt1, and Thi72 in yeast. We first discovered a thi3Δ mutant as hypersensitive to CQ using a genome-wide DGSL analysis. Using genome-wide GGSL and DS screens, we then found that a thi7Δ mutation confers severe growth defect in the thi3Δ mutant and that THI7 overexpression suppresses CQ-hypersensitivity of this mutant. We subsequently showed that CQ inhibits the functions of Thi7 and its homologues Nrt1 and Thi72. In particular, the transporter activity of wild-type Thi7 but not a CQ-resistant mutant (Thi7^T287N) was completely inhibited by the drug. Similar effects were also observed with other quinoline-containing antimalarials. In addition, CQ completely inhibited a human thiamine transporter (SLC19A3) expressed in yeast and significantly inhibited thiamine uptake in cultured human cell lines. Therefore, inhibition of thiamine uptake is a conserved mechanism of action of CQ. This study also demonstrated SL/DS as a uniquely effective methodology for discovering drug targets.

By using a novel SL/DS methodology in the model organism yeast, we discovered that the antimalarial drug CQ inhibits thiamine transporters and consequently causes thiamine (vitamin B1) deficiency and growth defects. This mechanism of action (MOA) is conserved in human cells and possibly also in other organisms. Given that both thiamine deficiency and treatment with CQ cause retinal, neurological, and cardiovascular disorders in humans, our results suggest that thiamine deficiency might be a root cause of some of CQ's adverse effects, which might be preventable with concomitant dietary thiamine supplementation. Such a MOA by CQ could also be responsible for its therapeutic effects against malarial parasites, which need exogenous thiamine for survival. Such a possibility needs to be investigated before dietary thiamine supplementation can be used to prevent CQ's adverse effects.

The role of computational methods in the identification of bioactive compounds

Computational methods play an ever increasing role in lead finding. A vast repertoire of molecular design and virtual screening methods emerged in the past two decades and are today routinely used. There is increasing awareness that there is no single best computational protocol and correspondingly there is a shift recommending the combination of complementary methods. A promising trend for the application of computational methods in lead finding is to take advantage of the vast amounts of HTS (High Throughput Screening) data to allow lead assessment by detailed systems-based data analysis, especially for phenotypic screens where the identification of compound-target pairs is the primary goal. Herein, we review trends and provide examples of successful applications of computational methods in lead finding.

Functional toxicogenomics: mechanism-centered toxicology

Traditional toxicity testing using animal models is slow, low capacity, expensive and assesses a limited number of endpoints. Such approaches are inadequate to deal with the increasingly large number of compounds found in the environment for which there are no toxicity data. Mechanism-centered high-throughput testing represents an alternative approach to meet this pressing need but is limited by our current understanding of toxicity pathways. Functional toxicogenomics, the global study of the biological function of genes on the modulation of the toxic effect of a compound, can play an important role in identifying the essential cellular components and pathways involved in toxicity response. The combination of the identification of fundamental toxicity pathways and mechanism-centered targeted assays represents an integrated approach to advance molecular toxicology to meet the challenges of toxicity testing in the 21^st century.

RNA interference in Schistosoma mansoni schistosomula: selectivity, sensitivity and operation for larger-scale screening

BACKGROUND

The possible emergence of resistance to the only available drug for schistosomiasis spurs drug discovery that has been recently incentivized by the availability of improved transcriptome and genome sequence information. Transient RNAi has emerged as a straightforward and important technique to interrogate that information through decreased or loss of gene function and identify potential drug targets. To date, RNAi studies in schistosome stages infecting humans have focused on single (or up to 3) genes of interest. Therefore, in the context of standardizing larger RNAi screens, data are limited on the extent of possible off-targeting effects, gene-to-gene variability in RNAi efficiency and the operational capabilities and limits of RNAi.

METHODOLOGY/PRINCIPAL FINDINGS

We investigated in vitro the sensitivity and selectivity of RNAi using double-stranded (ds)RNA (approximately 500 bp) designed to target 11 Schistosoma mansoni genes that are expressed in different tissues; the gut, tegument and otherwise. Among the genes investigated were 5 that had been previously predicted to be essential for parasite survival. We employed mechanically transformed schistosomula that are relevant to parasitism in humans, amenable to screen automation and easier to obtain in greater numbers than adult parasites. The operational parameters investigated included defined culture media for optimal parasite maintenance, transfection strategy, time- and dose-dependency of RNAi, and dosing limits. Of 7 defined culture media tested, Basch Medium 169 was optimal for parasite maintenance. RNAi was best achieved by co-incubating parasites and dsRNA (standardized to 30 µg/ml for 6 days); electroporation provided no added benefit. RNAi, including interference of more than one transcript, was selective to the gene target(s) within the pools of transcripts representative of each tissue. Concentrations of dsRNA above 90 µg/ml were directly toxic. RNAi efficiency was transcript-dependent (from 40 to >75% knockdown relative to controls) and this may have contributed to the lack of obvious phenotypes observed, even after prolonged incubations of 3 weeks. Within minutes of their mechanical preparation from cercariae, schistosomula accumulated fluorescent macromolecules in the gut indicating that the gut is an important route through which RNAi is expedited in the developing parasite.

CONCLUSIONS

Transient RNAi operates gene-selectively in S. mansoni newly transformed schistosomula yet the sensitivity of individual gene targets varies. These findings and the operational parameters defined will facilitate larger RNAi screens.

RNAi screening of the kinome identifies modulators of cisplatin response in ovarian cancer cells

OBJECTIVE

Ovarian cancer retains a poor prognosis among the female gynaecological malignancies. It constitutes about 3% of all malignancies in women and accounts for 5% of all female cancer related deaths. A standard treatment is cytoreductive surgery followed by adjuvant chemotherapy, and re-treatment with platinum based chemotherapy at the time of relapse. In order to improve cisplatin response in ovarian cancer cells, we utilized a high-throughput RNAi screening to identify kinase modulators.

METHODS

A high-throughput RNAi screen was performed using a siRNA library targeting 572 kinases to identify potentiators of cisplatin response in the ovarian cancer cell line SKOV3.

RESULTS

RNAi screening identified at least 55 siRNAs that potentiated the growth inhibitory effects of cisplatin in SKOV3 cells. Inhibition of ATR and CHK1 resulted in the greatest modulation of cisplatin response. Drug dose response of cisplatin in the presence of siRNA validated the effects of these target genes. To show that the siRNA data could be successfully translated into potential therapeutic strategies, CHK1 was further targeted with small molecule inhibitor PD 407824 in combination with cisplatin. Results showed that treatment of SKOV3 and OVCAR3 cells with CHK1 inhibitor PD 407824 led to sensitization of ovarian cancer cells to cisplatin.

CONCLUSIONS

Our data provides kinase targets that could be exploited to design better therapeutics for ovarian cancer patients. We also demonstrate the effectiveness of high-throughput RNAi screening as a tool for identifying sensitizing targets to known and established chemotherapeutic agents.