The art and design of genetic screens: RNA interference

A genetic interaction map of cell cycle regulators

A combination of genome-scale RNA interference screening and genetic interaction analysis using process-directed phenotypes is used to assign components to specific pathways and complexes for modulators of mitosis and cytokinesis in Drosophila S2 cells.

Cell-based RNA interference (RNAi) is a powerful approach to screen for modulators of many cellular processes. However, resulting candidate gene lists from cell-based assays comprise diverse effectors, both direct and indirect, and further dissecting their functions can be challenging. Here we screened a genome-wide RNAi library for modulators of mitosis and cytokinesis in Drosophila S2 cells. The screen identified many previously known genes as well as modulators that have previously not been connected to cell cycle control. We then characterized ∼300 candidate modifiers further by genetic interaction analysis using double RNAi and a multiparametric, imaging-based assay. We found that analyzing cell cycle–relevant phenotypes increased the sensitivity for associating novel gene function. Genetic interaction maps based on mitotic index and nuclear size grouped candidates into known regulatory complexes of mitosis or cytokinesis, respectively, and predicted previously uncharacterized components of known processes. For example, we confirmed a role for the Drosophila CCR4 mRNA processing complex component l(2)NC136 during the mitotic exit. Our results show that the combination of genome-scale RNAi screening and genetic interaction analysis using process-directed phenotypes provides a powerful two-step approach to assigning components to specific pathways and complexes.

Death receptor-based enrichment of Cas9-expressing cells

Background

The CRISPR/Cas9 genome editing system has greatly facilitated and expanded our capacity to engineer mammalian genomes, including targeted gene knock-outs. However, the phenotyping of the knock-out effect requires a high DNA editing efficiency.

Results

Here, we report a user-friendly strategy based on the extrinsic apoptosis pathway that allows enrichment of a polyclonal gene-edited cell population, by selecting Cas9-transfected cells that co-express dominant-negative mutants of death receptors. The extrinsic apoptosis pathway can be triggered in many mammalian cell types, and ligands are easy to produce, do not require purification and kill much faster than the state-of-the-art selection drug puromycin. Stringent assessment of our advanced selection strategy via Sanger sequencing, T7 endonuclease I (T7E1) assay and direct phenotyping confirmed a strong and rapid enrichment of Cas9-expressing cell populations, in some cases reaching up to 100 % within one hour. Notably, the efficiency of target DNA cleavage in these enriched cells reached high levels that exceeded the reliable range of the T7E1 assay, a conclusion that can be generalized for editing efficiencies above 30 %. Moreover, our data emphasize that the insertion and deletion pattern induced by a specific gRNA is reproducible across different cell lines.

Conclusions

The workflow and the findings reported here should streamline a wide array of future low- or high-throughput gene knock-out screens, and should largely improve data interpretation from CRISPR experiments.

Electronic supplementary material

The online version of this article (doi:10.1186/s12896-016-0250-4) contains supplementary material, which is available to authorized users.

Comprehensive RNAi-based screening of human and mouse TLR pathways identifies species-specific preferences in signaling protein use

Toll-like receptors (TLRs) are a major class of pattern recognition receptors, which mediate the responses of innate immune cells to microbial stimuli. To systematically determine the roles of proteins in canonical TLR signaling pathways, we conducted an RNA interference (RNAi)-based screen in human and mouse macrophages. We observed a pattern of conserved signaling module dependencies across species, but found notable species-specific requirements at the level of individual proteins. Among these, we identified unexpected differences in the involvement of members of the interleukin-1 receptor-associated kinase (IRAK) family between the human and mouse TLR pathways. Whereas TLR signaling in mouse macrophages depended primarily on IRAK4 and IRAK2, with little or no role for IRAK1, TLR signaling and proinflammatory cytokine production in human macrophages depended on IRAK1, with knockdown of IRAK4 or IRAK2 having less of an effect. Consistent with species-specific roles for these kinases, IRAK4 orthologs failed to rescue signaling in IRAK4-deficient macrophages from the other species, and only mouse macrophages required the kinase activity of IRAK4 to mediate TLR responses. The identification of a critical role for IRAK1 in TLR signaling in humans could potentially explain the association of IRAK1 with several autoimmune diseases. Furthermore, this study demonstrated how systematic screening can be used to identify important characteristics of innate immune responses across species, which could optimize therapeutic targeting to manipulate human TLR-dependent outputs.

An update on hypoallergenicity of peanut and soybean: where are we now?

Legumes are one of the major sources of proteins and positively correlate with the development of modern society. At the same time, unfortunately, they significantly contribute to the rising prevalence of food allergy.

A Guide to Genome-Wide In Vivo RNAi Applications in Drosophila

RNAi technologies enable the testing of gene function in a cell-type- and stage-specific manner in Drosophila. The development of genome-wide RNAi libraries has allowed expansion of this approach to the genome scale and supports identification of most genes required for a given process in a cell type of choice. However, a large-scale RNAi approach also harbors many potential pitfalls that can complicate interpretation of the results. Here, we summarize published screens and provide a guide on how to optimally plan and perform a large-scale, in vivo RNAi screen. We highlight the importance of assay design and give suggestions on how to optimize the assay conditions by testing positive and negative control genes. These genes are used to estimate false-negative and false-positive rates of the screen data. We discuss the planning and logistics of a large-scale screen in detail and suggest bioinformatics platforms to identify and select gene groups of interest for secondary assays. Finally, we review various options to confirm RNAi knock-down specificity and thus identify high confidence genes for more detailed case-by-case studies in the future.

Towards a compendium of essential genes - From model organisms to synthetic lethality in cancer cells

Essential genes are defined by their requirement to sustain life in cells or whole organisms. The systematic identification of essential gene sets not only allows insights into the fundamental building blocks of life, but may also provide novel therapeutic targets in oncology. The discovery of essential genes has been tightly linked to the development and deployment of various screening technologies. Here, we describe how gene essentiality was addressed in different eukaryotic model organisms, covering a range of organisms from yeast to mouse. We describe how increasing knowledge of evolutionarily divergent genomes facilitate identification of gene essentiality across species. Finally, the impact of gene essentiality and synthetic lethality on cancer research and the clinical translation of screening results are highlighted.

Virus-Host Interactions: From Unbiased Genetic Screens to Function

Deciphering the many interactions that occur between a virus and host cell over the course of infection is paramount to understanding mechanisms of pathogenesis and to the future development of antiviral therapies. Over the past decade, researchers have started to understand these complicated relationships through the development of methodologies, including advances in RNA interference, proteomics, and the development of genetic tools such as haploid cell lines, allowing high-throughput screening to identify critical contact points between virus and host. These advances have produced a wealth of data regarding host factors hijacked by viruses to promote infection, as well as antiviral factors responsible for subverting viral infection. This review highlights findings from virus-host screens and discusses our thoughts on the direction of screening strategies moving forward.

Pseudomonas aeruginosa essentials: an update on investigation of essential genes

Pseudomonas aeruginosa is the leading cause of nosocomial infections, particularly in immunocompromised, cancer, burn and cystic fibrosis patients. Development of novel antimicrobials against P. aeruginosa is therefore of the highest importance. Although the first reports on P. aeruginosa essential genes date back to the early 2000s, a number of more sensitive genomic approaches have been used recently to better define essential genes in this organism. These analyses highlight the evolution of the definition of an 'essential' gene from the traditional to the context-dependent. Essential genes, particularly those indispensable under the clinically relevant conditions, are considered to be promising targets of novel antibiotics against P. aeruginosa. This review provides an update on the investigation of P. aeruginosa essential genes. Special focus is on recently identified P. aeruginosa essential genes and their exploitation for the development of antimicrobials.

Reagent and Data Resources for Investigation of RNA Binding Protein Functions in Drosophila melanogaster Cultured Cells

RNA binding proteins (RBPs) are involved in many cellular functions. To facilitate functional characterization of RBPs, we generated an RNA interference (RNAi) library for Drosophila cell-based screens comprising reagents targeting known or putative RBPs. To test the quality of the library and provide a baseline analysis of the effects of the RNAi reagents on viability, we screened the library using a total ATP assay and high-throughput imaging in Drosophila S2R+ cultured cells. The results are consistent with production of a high-quality library that will be useful for functional genomics studies using other assays. Altogether, we provide resources in the form of an initial curated list of Drosophila RBPs; an RNAi screening library we expect to be used with additional assays that address more specific biological questions; and total ATP and image data useful for comparison of those additional assay results with fundamental information such as effects of a given reagent in the library on cell viability. Importantly, we make the baseline data, including more than 200,000 images, easily accessible online.

Morphological Profiles of RNAi-Induced Gene Knockdown Are Highly Reproducible but Dominated by Seed Effects

RNA interference and morphological profiling-the measurement of thousands of phenotypes from individual cells by microscopy and image analysis-are a potentially powerful combination. We show that morphological profiles of RNAi-induced knockdown using the Cell Painting assay are in fact highly sensitive and reproducible. However, we find that the magnitude and prevalence of off-target effects via the RNAi seed-based mechanism make morphological profiles of RNAi reagents targeting the same gene look no more similar than reagents targeting different genes. Pairs of RNAi reagents that share the same seed sequence produce image-based profiles that are much more similar to each other than profiles from pairs designed to target the same gene, a phenomenon previously observed in small-scale gene-expression profiling experiments. Various strategies have been used to enrich on-target versus off-target effects in the context of RNAi screening where a narrow set of phenotypes are measured, mostly based on comparing multiple sequences targeting the same gene; however, new approaches will be needed to make RNAi morphological profiling (that is, comparing multi-dimensional phenotypes) viable. We have shared our raw data and computational pipelines to facilitate research.

Functional fingerprinting of human mesenchymal stem cells using high-throughput RNAi screening

Mesenchymal stem cells (MSCs) are promising candidates for cellular therapies ranging from tissue repair in regenerative medicine to immunomodulation in graft versus host disease after allogeneic transplantation or in autoimmune diseases. Nonetheless, progress has been hampered by their enormous phenotypic as well as functional heterogeneity and the lack of uniform standards and guidelines for quality control. In this study, we describe a method to perform cellular phenotyping by high-throughput RNA interference in primary human bone marrow MSCs. We have shown that despite heterogeneity of MSC populations, robust functional assays can be established that are suitable for high-throughput and high-content screening. We profiled primary human MSCs against human fibroblasts. Network analysis showed a kinome fingerprint that differs from human primary fibroblasts as well as fibroblast cell lines. In conclusion, this study shows that high-throughput screening in primary human MSCs can be reliably used for kinome fingerprinting.

High-throughput functional genomics using CRISPR-Cas9

Forward genetic screens are powerful tools for the discovery and functional annotation of genetic elements. Recently, the RNA-guided CRISPR (clustered regularly interspaced short palindromic repeat)-associated Cas9 nuclease has been combined with genome-scale guide RNA libraries for unbiased, phenotypic screening. In this Review, we describe recent advances using Cas9 for genome-scale screens, including knockout approaches that inactivate genomic loci and strategies that modulate transcriptional activity. We discuss practical aspects of screen design, provide comparisons with RNA interference (RNAi) screening, and outline future applications and challenges.

A genome-wide CRISPR library for high-throughput genetic screening in Drosophila cells

The simplicity of the CRISPR/Cas9 system of genome engineering has opened up the possibility of performing genome-wide targeted mutagenesis in cell lines, enabling screening for cellular phenotypes resulting from genetic aberrations. Drosophila cells have proven to be highly effective in identifying genes involved in cellular processes through similar screens using partial knockdown by RNAi. This is in part due to the lower degree of redundancy between genes in this organism, whilst still maintaining highly conserved gene networks and orthologs of many human disease-causing genes. The ability of CRISPR to generate genetic loss of function mutations not only increases the magnitude of any effect over currently employed RNAi techniques, but allows analysis over longer periods of time which can be critical for certain phenotypes. In this study, we have designed and built a genome-wide CRISPR library covering 13,501 genes, among which 8989 genes are targeted by three or more independent single guide RNAs (sgRNAs). Moreover, we describe strategies to monitor the population of guide RNAs by high throughput sequencing (HTS). We hope that this library will provide an invaluable resource for the community to screen loss of function mutations for cellular phenotypes, and as a source of guide RNA designs for future studies.

Development of a cell system for siRNA screening of pathogen responses in human and mouse macrophages

Macrophages play a critical role in the innate immune response to pathogen infection, but few tools exist for systematic dissection of these responses using modern genome-wide perturbation methods. To develop an assay platform for high-throughput analysis of macrophage activation by pathogenic stimuli, we generated reporter systems in human and mouse macrophages with dynamic readouts for NF-κB and/or TNF-α responses. These reporter cells show responsiveness to a broad range of TLR ligands and to gram-negative bacterial infection. There are significant challenges to the use of RNAi in innate immune cells, including efficient small RNA delivery and non-specific immune responses to dsRNA. To permit the interrogation of the macrophage pathogen response pathways with RNAi, we employed the stably expressed reporter genes to develop efficient siRNA delivery protocols for maximal target gene silencing with minimal activation of the innate macrophage response to nucleic acids. We demonstrate the utility of these macrophage cell systems for siRNA screening of pathogen responses by targeting components of the human and mouse TLR pathways, and observe species-specific perturbation of signaling and cytokine responses. Our approach to reporter cell development and siRNA delivery optimization provides an experimental paradigm with significant potential for developing genetic screening platforms in mammalian cells.

Advances in CRISPR-Cas9 genome engineering: lessons learned from RNA interference

The discovery that the machinery of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 bacterial immune system can be re-purposed to easily create deletions, insertions and replacements in the mammalian genome has revolutionized the field of genome engineering and re-invigorated the field of gene therapy. Many parallels have been drawn between the newly discovered CRISPR-Cas9 system and the RNA interference (RNAi) pathway in terms of their utility for understanding and interrogating gene function in mammalian cells. Given this similarity, the CRISPR-Cas9 field stands to benefit immensely from lessons learned during the development of RNAi technology. We examine how the history of RNAi can inform today's challenges in CRISPR-Cas9 genome engineering such as efficiency, specificity, high-throughput screening and delivery for in vivo and therapeutic applications.

RNAi-assisted genome evolution in Saccharomyces cerevisiae for complex phenotype engineering

A fundamental challenge in basic and applied biology is to reprogram cells with improved or novel traits on a genomic scale. However, the current ability to reprogram a cell on the genome scale is limited to bacterial cells. Here, we report RNA interference (RNAi)-assisted genome evolution (RAGE) as a generally applicable method for genome-scale engineering in the yeast Saccharomyces cerevisiae. Through iterative cycles of creating a library of RNAi induced reduction-of-function mutants coupled with high throughput screening or selection, RAGE can continuously improve target trait(s) by accumulating multiplex beneficial genetic modifications in an evolving yeast genome. To validate the RNAi library constructed with yeast genomic DNA and convergent-promoter expression cassette, we demonstrated RNAi screening in Saccharomyces cerevisiae for the first time by identifying two known and three novel suppressors of a telomerase-deficient mutation yku70Δ. We then showed the application of RAGE for improved acetic acid tolerance, a key trait for microbial production of chemicals and fuels. Three rounds of iterative RNAi screening led to the identification of three gene knockdown targets that acted synergistically to confer an engineered yeast strain with substantially improved acetic acid tolerance. RAGE should greatly accelerate the design and evolution of organisms with desired traits and provide new insights on genome structure, function, and evolution.

What's that gene (or protein)? Online resources for exploring functions of genes, transcripts, and proteins

The genomic era has enabled research projects that use approaches including genome-scale screens, microarray analysis, next-generation sequencing, and mass spectrometry-based proteomics to discover genes and proteins involved in biological processes. Such methods generate data sets of gene, transcript, or protein hits that researchers wish to explore to understand their properties and functions and thus their possible roles in biological systems of interest. Recent years have seen a profusion of Internet-based resources to aid this process. This review takes the viewpoint of the curious biologist wishing to explore the properties of protein-coding genes and their products, identified using genome-based technologies. Ten key questions are asked about each hit, addressing functions, phenotypes, expression, evolutionary conservation, disease association, protein structure, interactors, posttranslational modifications, and inhibitors. Answers are provided by presenting the latest publicly available resources, together with methods for hit-specific and data set-wide information retrieval, suited to any genome-based analytical technique and experimental species. The utility of these resources is demonstrated for 20 factors regulating cell proliferation. Results obtained using some of these are discussed in more depth using the p53 tumor suppressor as an example. This flexible and universally applicable approach for characterizing experimental hits helps researchers to maximize the potential of their projects for biological discovery.

Functional Genomics in Pharmaceutical Drug Discovery

Targeted therapies in personalized medicine require the knowledge about the molecular changes within the patient that cause the disease. With the beginning of the new century, a plethora of new technologies became available to detect these changes and use this information as starting point for drug development. Next-generation genome sequencing and sophisticated genome-wide functional genomics' methods have led to a significant increase in the identification of novel drug target candidates and understanding of the relevance of these genomic and molecular changes for the diseases. As functional genomic tool for target identification, high-throughput gene silencing through RNA interference screening has become the established method. RNAi is discussed with its advantages and challenges in this chapter. Furthermore the potential of CRISPR/Cas9, a gene-editing method that has recently been adapted for use as functional screening tool, will be briefly reviewed.

piggyBac transposon-based insertional mutagenesis in mouse haploid embryonic stem cells

Forward genetic screening is a powerful non-hypothesis-driven approach to unveil the molecular mechanisms and pathways underlying phenotypes of interest. In this approach, a genome-wide mutant library is first generated and then screened for a phenotype of interest. Subsequently, genes responsible for the phenotype are identified. There have been a number of successful screens in yeasts, Caenorhabditis elegans and Drosophila. These model organisms all allow loss-of-function mutants to be generated easily on a genome-wide scale: yeasts have a haploid stage in their reproductive cycles and the latter two organisms have short generation times, allowing mutations to be systematically bred to homozygosity. However, in mammals, the diploid genome and long generation time have always hampered rapid and efficient production of homozygous mutant cells and animals. The recent discovery of several haploid mammalian cell lines promises to revolutionize recessive genetic screens in mammalian cells. In this protocol, we describe an overview of insertional mutagenesis, focusing on DNA transposons, and provide a method for an efficient generation of genome-wide mutant libraries using mouse haploid embryonic stem cells.

Single-cell and multivariate approaches in genetic perturbation screens

Large-scale genetic perturbation screens are a classical approach in biology and have been crucial for many discoveries. New technologies can now provide unbiased quantification of multiple molecular and phenotypic changes across tens of thousands of individual cells from large numbers of perturbed cell populations simultaneously. In this Review, we describe how these developments have enabled the discovery of new principles of intracellular and intercellular organization, novel interpretations of genetic perturbation effects and the inference of novel functional genetic interactions. These advances now allow more accurate and comprehensive analyses of gene function in cells using genetic perturbation screens.

Rapid prototyping of microbial cell factories via genome-scale engineering

Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories.

Bacillus subtilis and Escherichia coli essential genes and minimal cell factories after one decade of genome engineering

Investigation of essential genes, besides contributing to understanding the fundamental principles of life, has numerous practical applications. Essential genes can be exploited as building blocks of a tightly controlled cell ‘chassis’. Bacillus subtilis and Escherichia coli K-12 are both well-characterized model bacteria used as hosts for a plethora of biotechnological applications. Determination of the essential genes that constitute the B. subtilis and E. coli minimal genomes is therefore of the highest importance. Recent advances have led to the modification of the original B. subtilis and E. coli essential gene sets identified 10 years ago. Furthermore, significant progress has been made in the area of genome minimization of both model bacteria. This review provides an update, with particular emphasis on the current essential gene sets and their comparison with the original gene sets identified 10 years ago. Special attention is focused on the genome reduction analyses in B. subtilis and E. coli and the construction of minimal cell factories for industrial applications.

Controlling gene networks and cell fate with precision-targeted DNA-binding proteins and small-molecule-based genome readers

Transcription factors control the fate of a cell by regulating the expression of genes and regulatory networks. Recent successes in inducing pluripotency in terminally differentiated cells as well as directing differentiation with natural transcription factors has lent credence to the efforts that aim to direct cell fate with rationally designed transcription factors. Because DNA-binding factors are modular in design, they can be engineered to target specific genomic sequences and perform pre-programmed regulatory functions upon binding. Such precision-tailored factors can serve as molecular tools to reprogramme or differentiate cells in a targeted manner. Using different types of engineered DNA binders, both regulatory transcriptional controls of gene networks, as well as permanent alteration of genomic content, can be implemented to study cell fate decisions. In the present review, we describe the current state of the art in artificial transcription factor design and the exciting prospect of employing artificial DNA-binding factors to manipulate the transcriptional networks as well as epigenetic landscapes that govern cell fate.

Dsh homolog DVL3 mediates resistance to IGFIR inhibition by regulating IGF-RAS signaling

Drugs that inhibit insulin-like growth factor 1 (IGFI) receptor IGFIR were encouraging in early trials, but predictive biomarkers were lacking and the drugs provided insufficient benefit in unselected patients. In this study, we used genetic screening and downstream validation to identify the WNT pathway element DVL3 as a mediator of resistance to IGFIR inhibition. Sensitivity to IGFIR inhibition was enhanced specifically in vitro and in vivo by genetic or pharmacologic blockade of DVL3. In breast and prostate cancer cells, sensitization tracked with enhanced MEK-ERK activation and relied upon MEK activity and DVL3 expression. Mechanistic investigations showed that DVL3 is present in an adaptor complex that links IGFIR to RAS, which includes Shc, growth factor receptor-bound-2 (Grb2), son-of-sevenless (SOS), and the tumor suppressor DAB2. Dual DVL and DAB2 blockade synergized in activating ERKs and sensitizing cells to IGFIR inhibition, suggesting a nonredundant role for DVL3 in the Shc-Grb2-SOS complex. Clinically, tumors that responded to IGFIR inhibition contained relatively lower levels of DVL3 protein than resistant tumors, and DVL3 levels in tumors correlated inversely with progression-free survival in patients treated with IGFIR antibodies. Because IGFIR does not contain activating mutations analogous to EGFR variants associated with response to EGFR inhibitors, we suggest that IGF signaling achieves an equivalent integration at the postreceptor level through adaptor protein complexes, influencing cellular dependence on the IGF axis and identifying a patient population with potential to benefit from IGFIR inhibition.

Improving Detection of Rare Biological Events in High-Throughput Screens

The success of high-throughput screening (HTS) strategies depends on the effectiveness of both normalization methods and study design. We report comparisons among normalization methods in two titration series experiments. We also extend the results in a third experiment with two differently designed but otherwise identical screens: compounds in replicate plates were either placed in the same well locations or were randomly assigned to different locations. Best results were obtained when randomization was combined with normalization methods that corrected for within-plate spatial bias. We conclude that potent, reliable, and accurate HTS requires replication, randomization design strategies, and more extensive normalization than is typically done and that formal statistical testing is desirable. The Statistics and dIagnostic Graphs for HTS (SIGHTS) Microsoft Excel Add-In software is available to conduct most analyses reported here.

RNAi screening comes of age: improved techniques and complementary approaches

Gene silencing through sequence-specific targeting of mRNAs by RNAi has enabled genome-wide functional screens in cultured cells and in vivo in model organisms. These screens have resulted in the identification of new cellular pathways and potential drug targets. Considerable progress has been made to improve the quality of RNAi screen data through the development of new experimental and bioinformatics approaches. The recent availability of genome-editing strategies, such as the CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 system, when combined with RNAi, could lead to further improvements in screen data quality and follow-up experiments, thus promoting our understanding of gene function and gene regulatory networks.

Molecular analysis of the cold tolerant Antarctic nematode, Panagrolaimus davidi

Isolated and established in culture from the Antarctic in 1988, the nematode Panagrolaimus davidi has proven to be an ideal model for the study of adaptation to the cold. Not only is it the best-documented example of an organism surviving intracellular freezing but it is also able to undergo cryoprotective dehydration. As part of an ongoing effort to develop a molecular understanding of this remarkable organism, we have assembled both a transcriptome and a set of genomic scaffolds. We provide an overview of the transcriptome and a survey of genes involved in temperature stress. We also explore, in silico, the possibility that P. davidi will be susceptible to an environmental RNAi response, important for further functional studies.

Dynamic probabilistic threshold networks to infer signaling pathways from time-course perturbation data

BACKGROUND

Network inference deals with the reconstruction of molecular networks from experimental data. Given N molecular species, the challenge is to find the underlying network. Due to data limitations, this typically is an ill-posed problem, and requires the integration of prior biological knowledge or strong regularization. We here focus on the situation when time-resolved measurements of a system's response after systematic perturbations are available.

RESULTS

We present a novel method to infer signaling networks from time-course perturbation data. We utilize dynamic Bayesian networks with probabilistic Boolean threshold functions to describe protein activation. The model posterior distribution is analyzed using evolutionary MCMC sampling and subsequent clustering, resulting in probability distributions over alternative networks. We evaluate our method on simulated data, and study its performance with respect to data set size and levels of noise. We then use our method to study EGF-mediated signaling in the ERBB pathway.

CONCLUSIONS

Dynamic Probabilistic Threshold Networks is a new method to infer signaling networks from time-series perturbation data. It exploits the dynamic response of a system after external perturbation for network reconstruction. On simulated data, we show that the approach outperforms current state of the art methods. On the ERBB data, our approach recovers a significant fraction of the known interactions, and predicts novel mechanisms in the ERBB pathway.

Applications of RNA interference high-throughput screening technology in cancer biology and virology

RNA interference (RNAi) is an ancient intra-cellular mechanism that regulates gene expression and cell function. Large-scale gene silencing using RNAi high-throughput screening (HTS) has opened an exciting frontier to systematically study gene function in mammalian cells. This approach enables researchers to identify gene function in a given biological context and will provide considerable novel insight. Here, we review RNAi HTS strategies and applications using case studies in cancer biology and virology.

Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis

BACKGROUND

RNA interference (RNAi) is an effective and important tool used to study gene function. For large-scale screens, RNAi is used to systematically down-regulate genes of interest and analyze their roles in a biological process. However, RNAi is associated with off-target effects (OTEs), including microRNA (miRNA)-like OTEs. The contribution of reagent-specific OTEs to RNAi screen data sets can be significant. In addition, the post-screen validation process is time and labor intensive. Thus, the availability of robust approaches to identify candidate off-targeted transcripts would be beneficial.

RESULTS

Significant efforts have been made to eliminate false positive results attributable to sequence-specific OTEs associated with RNAi. These approaches have included improved algorithms for RNAi reagent design, incorporation of chemical modifications into siRNAs, and the use of various bioinformatics strategies to identify possible OTEs in screen results. Genome-wide Enrichment of Seed Sequence matches (GESS) was developed to identify potential off-targeted transcripts in large-scale screen data by seed-region analysis. Here, we introduce a user-friendly web application that provides researchers a relatively quick and easy way to perform GESS analysis on data from human or mouse cell-based screens using short interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs), as well as for Drosophila screens using shRNAs. Online GESS relies on up-to-date transcript sequence annotations for human and mouse genes extracted from NCBI Reference Sequence (RefSeq) and Drosophila genes from FlyBase. The tool also accommodates analysis with user-provided reference sequence files.

CONCLUSION

Online GESS provides a straightforward user interface for genome-wide seed region analysis for human, mouse and Drosophila RNAi screen data. With the tool, users can either use a built-in database or provide a database of transcripts for analysis. This makes it possible to analyze RNAi data from any organism for which the user can provide transcript sequences.

An image-based, dual fluorescence reporter assay to evaluate the efficacy of shRNA for gene silencing at the single-cell level

RNA interference (RNAi) is widely used to suppress gene expression in a specific manner. The efficacy of RNAi is mainly dependent on the sequence of small interfering RNA (siRNA) in relation to the target mRNA. Although several algorithms have been developed for the design of siRNA, it is still difficult to choose a really effective siRNA from among multiple candidates. In this article, we report the development of an image-based, quantitative, ratiometric fluorescence reporter assay to evaluate the efficacy of RNAi at the single-cell level. Two fluorescence reporter constructs are used. One expresses the candidate small hairpin RNA (shRNA) together with an enhanced green fluorescent protein (EGFP); the other expresses a 19-nt target sequence inserted into a cassette expressing a red fluorescent protein (either DsRed or mCherry). Effectiveness of the candidate shRNA is evaluated as the extent to which it knocks down expression of the red fluorescent protein. Thus, the red-to-green fluorescence intensity ratio (appropriately normalized to controls) is used as the read-out for quantifying the siRNA efficacy at the individual cell level. We tested this dual fluorescence assay and compared predictions to actual endogenous knockdown levels for three different genes (vimentin, lamin A/C and Arp3) and twenty different shRNAs. For each of the genes, our assay successfully predicted the target sequences for effective RNAi.To further facilitate testing of RNAi efficacy, we developed a negative selection marker (ccdB) method for construction of shRNA and red fluorescent reporter plasmids that allowed us to purify these plasmids directly from transformed bacteria without the need for colony selection and DNA sequencing verification.

Integrative framework for identification of key cell identity genes uncovers determinants of ES cell identity and homeostasis

Identification of genes associated with specific biological phenotypes is a fundamental step toward understanding the molecular basis underlying development and pathogenesis. Although RNAi-based high-throughput screens are routinely used for this task, false discovery and sensitivity remain a challenge. Here we describe a computational framework for systematic integration of published gene expression data to identify genes defining a phenotype of interest. We applied our approach to rank-order all genes based on their likelihood of determining ES cell (ESC) identity. RNAi-mediated loss-of-function experiments on top-ranked genes unearthed many novel determinants of ESC identity, thus validating the derived gene ranks to serve as a rich and valuable resource for those working to uncover novel ESC regulators. Underscoring the value of our gene ranks, functional studies of our top-hit Nucleolin (Ncl), abundant in stem and cancer cells, revealed Ncl's essential role in the maintenance of ESC homeostasis by shielding against differentiation-inducing redox imbalance-induced oxidative stress. Notably, we report a conceptually novel mechanism involving a Nucleolin-dependent Nanog-p53 bistable switch regulating the homeostatic balance between self-renewal and differentiation in ESCs. Our findings connect the dots on a previously unknown regulatory circuitry involving genes associated with traits in both ESCs and cancer and might have profound implications for understanding cell fate decisions in cancer stem cells. The proposed computational framework, by helping to prioritize and preselect candidate genes for tests using complex and expensive genetic screens, provides a powerful yet inexpensive means for identification of key cell identity genes.

A functional screen reveals an extensive layer of transcriptional and splicing control underlying RAS/MAPK signaling in Drosophila

A global RNAi screening approach in Drosophila cells identifies a large group of transcription and splicing factors that modulate RAS/MAPK signaling by altering the expression of MAPK.

The small GTPase RAS is among the most prevalent oncogenes. The evolutionarily conserved RAF-MEK-MAPK module that lies downstream of RAS is one of the main conduits through which RAS transmits proliferative signals in normal and cancer cells. Genetic and biochemical studies conducted over the last two decades uncovered a small set of factors regulating RAS/MAPK signaling. Interestingly, most of these were found to control RAF activation, thus suggesting a central regulatory role for this event. Whether additional factors are required at this level or further downstream remains an open question. To obtain a comprehensive view of the elements functionally linked to the RAS/MAPK cascade, we used a quantitative assay in Drosophila S2 cells to conduct a genome-wide RNAi screen for factors impacting RAS-mediated MAPK activation. The screen led to the identification of 101 validated hits, including most of the previously known factors associated to this pathway. Epistasis experiments were then carried out on individual candidates to determine their position relative to core pathway components. While this revealed several new factors acting at different steps along the pathway—including a new protein complex modulating RAF activation—we found that most hits unexpectedly work downstream of MEK and specifically influence MAPK expression. These hits mainly consist of constitutive splicing factors and thereby suggest that splicing plays a specific role in establishing MAPK levels. We further characterized two representative members of this group and surprisingly found that they act by regulating mapk alternative splicing. This study provides an unprecedented assessment of the factors modulating RAS/MAPK signaling in Drosophila. In addition, it suggests that pathway output does not solely rely on classical signaling events, such as those controlling RAF activation, but also on the regulation of MAPK levels. Finally, it indicates that core splicing components can also specifically impact alternative splicing.

The RAS/MAPK pathway is a cornerstone of the cell proliferation signaling apparatus. It has a notable involvement in cancer as mutations in the components of the pathway are associated with aberrant proliferation. Previous work has focused predominantly on post-translational regulation of RAS/MAPK signaling such that a large and intricate network of factors is now known to act on core pathway components. However, regulation at the pre-translational level has not been examined nearly as extensively and is comparatively poorly understood. In this study, we used an unbiased and global screening approach to survey the Drosophila genome—using Drosophila cultured cells—for novel regulators of this pathway. Surprisingly, a majority of our hits were associated to either transcription or mRNA splicing. We used a series of secondary screening assays to determine which part of the RAS/MAPK pathway these candidates target. We found that these factors were not equally distributed along the pathway, but rather converged predominantly on mapk mRNA expression and processing. Our findings raise the intriguing possibility that regulation of mapk transcript production is a key step for a diverse set of regulatory inputs, and may play an important part in RAS/MAPK signaling dynamics.

Identification of Zinc Finger, MYM-type 2 (ZMYM2) as a regulator of sorafenib resistance in hepatocellular carcinoma cell lines

BACKGROUND AND AIM

Hepatocellular carcinoma (HCC) is an aggressive malignancy with a very complex molecular process. There is no successful therapy for advanced HCC at present. Recently, sorafenib has been used as a systemic therapy to improve survival in patients with advanced HCC, but increasing reports of recurrence or non-responsiveness indicate the limitations of sorafenib as a therapeutic agent. Therefore, identification of genes involved in sorafenib resistance is important to effectively treat advanced HCC.

METHODS

We performed a genomic screening with a short-hairpin RNA library cassette on HCC cell lines to find genes relating resistance to sorafenib.

RESULTS

Zinc finger, MYM type 2 (ZMYM2) was sequenced after three successive screens in vitro as a challengeable target. The inhibition of ZMYM2 resulted in sorafenib-resistance in formerly sensitive HCC cell lines. Immunohistochemical comparison of tumor and non-tumor regions showed stronger ZMYM2 staining intensities in non-tumor regions than in tumor regions.

CONCLUSION

ZMYM2 may play an important role in sorafenib resistance.

Genome-wide recessive genetic screening in mammalian cells with a lentiviral CRISPR-guide RNA library

Identification of genes influencing a phenotype of interest is frequently achieved through genetic screening by RNA interference (RNAi) or knockouts. However, RNAi may only achieve partial depletion of gene activity, and knockout-based screens are difficult in diploid mammalian cells. Here we took advantage of the efficiency and high throughput of genome editing based on type II, clustered, regularly interspaced, short palindromic repeats (CRISPR)-CRISPR-associated (Cas) systems to introduce genome-wide targeted mutations in mouse embryonic stem cells (ESCs). We designed 87,897 guide RNAs (gRNAs) targeting 19,150 mouse protein-coding genes and used a lentiviral vector to express these gRNAs in ESCs that constitutively express Cas9. Screening the resulting ESC mutant libraries for resistance to either Clostridium septicum alpha-toxin or 6-thioguanine identified 27 known and 4 previously unknown genes implicated in these phenotypes. Our results demonstrate the potential for efficient loss-of-function screening using the CRISPR-Cas9 system.

An image-based, dual fluorescence reporter assay to evaluate the efficacy of shRNA for gene silencing at the single-cell level

RNA interference (RNAi) is widely used to suppress gene expression in a specific manner. The efficacy of RNAi is mainly dependent on the sequence of small interfering RNA (siRNA) in relation to the target mRNA. Although several algorithms have been developed for the design of siRNA, it is still difficult to choose a really effective siRNA from among multiple candidates. In this article, we report the development of an image-based, quantitative, ratiometric fluorescence reporter assay to evaluate the efficacy of RNAi at the single-cell level. Two fluorescence reporter constructs are used. One expresses the candidate small hairpin RNA (shRNA) together with an enhanced green fluorescent protein (EGFP); the other expresses a 19-nt target sequence inserted into a cassette expressing a red fluorescent protein (either DsRed or mCherry). Effectiveness of the candidate shRNA is evaluated as the extent to which it knocks down expression of the red fluorescent protein. Thus, the red-to-green fluorescence intensity ratio (appropriately normalized to controls) is used as the read-out for quantifying the siRNA efficacy at the individual cell level. We tested this dual fluorescence assay and compared predictions to actual endogenous knockdown levels for three different genes (vimentin, lamin A/C and Arp3) and twenty different shRNAs. For each of the genes, our assay successfully predicted the target sequences for effective RNAi. To further facilitate testing of RNAi efficacy, we developed a negative selection marker ( ccdB) method for construction of shRNA and red fluorescent reporter plasmids that allowed us to purify these plasmids directly from transformed bacteria without the need for colony selection and DNA sequencing verification.

Efficient isolation of ion beam-induced mutants for homoeologous loci in common wheat and comparison of the contributions of Glu-1 loci to gluten functionality

Ion beam mutations can be efficiently isolated and deployed for functional comparison of homoeologous loci in polyploid plants, and Glu - 1 loci differ substantially in their contribution to wheat gluten functionality. To efficiently conduct genetic analysis, it is beneficial to have multiple types of mutants for the genes under investigation. Here, we demonstrate that ion beam-induced deletion mutants can be efficiently isolated for comparing the function of homoeologous loci of common wheat (Triticum aestivum). Through fragment analysis of PCR products from M2 plants, ion beam mutants lacking homoeologous Glu-A1, Glu-B1 or Glu-D1 loci, which encode high molecular weight glutenin subunits (HMW-GSs) and affect gluten functionality and end-use quality of common wheat, could be isolated simultaneously. Three deletion lines missing Glu-A1, Glu-B1 or Glu-D1 were developed from the original mutants, with the Glu-1 genomic regions deleted in these lines estimated using newly developed DNA markers. Apart from lacking the target HMW-GSs, the three lines all showed decreased accumulation of low molecular weight glutenin subunits (LMW-GSs) and increased amounts of gliadins. Based on the test data of five gluten and glutenin macropolymer (GMP) parameters obtained with grain samples harvested from two environments, we conclude that the genetic effects of Glu-1 loci on gluten functionality can be ranked as Glu-D1 > Glu-B1 > Glu-A1. Furthermore, it is suggested that Glu-1 loci contribute to gluten functionality both directly (by promoting the formation of GMP) and indirectly (through keeping the balance among HMW-GSs, LMW-GSs and gliadins). Finally, the efficient isolation of ion beam mutations for functional comparison of homoeologous loci in polyploid plants and the usefulness of Glu-1 deletion lines for further studying the contribution of Glu-1 loci to gluten functionality are discussed.

A synthetic lethal screen identifies FAT1 as an antagonist of caspase-8 in extrinsic apoptosis

The extrinsic apoptosis pathway is initiated by binding of death ligands to death receptors resulting in the formation of the death-inducing signaling complex (DISC). Activation of procaspase-8 within the DISC and its release from the signaling complex is required for processing executor caspases and commiting cell death. Here, we report that the atypical cadherin FAT1 interacts with caspase-8 preventing the association of caspase-8 with the DISC. We identified FAT1 in a genome-wide siRNA screen for synthetic lethal interactions with death receptor-mediated apoptosis. Knockdown of FAT1 sensitized established and patient-derived glioblastoma cell lines for apoptosis transduced by cell death ligands. Depletion of FAT1 resulted in enhanced procaspase-8 recruitment to the DISC and increased formation of caspase-8 containing secondary signaling complexes. In addition, FAT1 knockout cell lines generated by CRISPR/Cas9-mediated genome engineering were more susceptible for death receptor-mediated apoptosis. Our findings provide evidence for a mechanism to control caspase-8-dependent cell death by the atypical cadherin FAT1. These results contribute towards the understanding of effector caspase regulation in physiological conditions.

Transgene-free genome editing by germline injection of CRISPR/Cas RNA

Genome modification by CRISPR/Cas offers its users the ability to target endogenous sites in the genome for cleavage and for engineering precise genomic changes using template-directed repair, all with unprecedented ease and flexibility of targeting. As such, CRISPR/Cas is just part of a set of recently developed and rapidly improving tools that offer great potential for researchers to functionally access the genomes of organisms that have not previously been extensively used in a laboratory setting. We describe in detail protocols for using CRISPR/Cas to target genes of experimental organisms, in a manner that does not require transformation to obtain transgenic lines and that should be readily applicable to a wide range of previously little-studied species.

Algal photoreceptors: in vivo functions and potential applications

Many algae, particularly microalgae, possess a sophisticated light-sensing system including photoreceptors and light-modulated signaling pathways to sense environmental information and secure the survival in a rapidly changing environment. Over the last couple of years, the multifaceted world of algal photobiology has enriched our understanding of the light absorption mechanisms and in vivo function of photoreceptors. Moreover, specific light-sensitive modules have already paved the way for the development of optogenetic tools to generate light switches for precise and spatial control of signaling pathways in individual cells and even in complex biological systems.

Control-Plate Regression (CPR) Normalization for High-Throughput Screens with Many Active Features

Systematic error is present in all high-throughput screens, lowering measurement accuracy. Because screening occurs at the early stages of research projects, measurement inaccuracy leads to following up inactive features and failing to follow up active features. Current normalization methods take advantage of the fact that most primary-screen features (e.g., compounds) within each plate are inactive, which permits robust estimates of row and column systematic-error effects. Screens that contain a majority of potentially active features pose a more difficult challenge because even the most robust normalization methods will remove at least some of the biological signal. Control plates that contain the same feature in all wells can provide a solution to this problem by providing well-by-well estimates of systematic error, which can then be removed from the treatment plates. We introduce the robust control-plate regression (CPR) method, which uses this approach. CPR’s performance is compared to a high-performing primary-screen normalization method in four experiments. These data were also perturbed to simulate screens with large numbers of active features to further assess CPR’s performance. CPR performs almost as well as the best performing normalization methods with primary screens and outperforms the Z-score and equivalent methods with screens containing a large proportion of active features.

SMG-ly knocking out gene expression in specific cells: an educational primer for use with "a novel strategy for cell-autonomous gene knockdown in caenorhabditis elegans defines a cell-specific function for the G-protein subunit GOA-1"

SUMMARY

A recent article by Maher et al. in GENETICS introduces an alternative approach to cell-type-specific gene knockdown in Caenorhabditis elegans, using nonsense-mediated decay. This strategy has the potential to be applicable to other organisms (this strategy requires that animals can survive without nonsense-mediated decay—not all can). This Primer article provides a guide and resource for educators and students by describing different gene knockdown methodologies, by assisting with the technically difficult portions of the Maher et al. article, and by providing conceptual questions relating to the article.

Related article in GENETICS: Maher, K. N., A. Swaminathan, P. Patel, and D. L. Chase, 2013 A novel strategy for cell-autonomous gene knockdown in Caenorhabditis elegans defines a cell-specific function for the G-protein subunit GOA-1. Genetics 194:363–373.

A multi-level multi-scale approach to study essential genes in Mycobacterium tuberculosis

Background

The set of indispensable genes that are required by an organism to grow and sustain life are termed as essential genes. There is a strong interest in identification of the set of essential genes, particularly in pathogens, not only for a better understanding of the pathogen biology, but also for identifying drug targets and the minimal gene set for the organism. Essentiality is inherently a systems property and requires consideration of the system as a whole for their identification. The available experimental approaches capture some aspects but each method comes with its own limitations. Moreover, they do not explain the basis for essentiality in most cases. A powerful prediction method to recognize this gene pool including rationalization of the known essential genes in a given organism would be very useful. Here we describe a multi-level multi-scale approach to identify the essential gene pool in a deadly pathogen, Mycobacterium tuberculosis.

Results

The multi-level workflow analyses the bacterial cell by studying (a) genome-wide gene expression profiles to identify the set of genes which show consistent and significant levels of expression in multiple samples of the same condition, (b) indispensability for growth by using gene expression integrated flux balance analysis of a genome-scale metabolic model, (c) importance for maintaining the integrity and flow in a protein-protein interaction network and (d) evolutionary conservation in a set of genomes of the same ecological niche. In the gene pool identified, the functional basis for essentiality has been addressed by studying residue level conservation and the sub-structure at the ligand binding pockets, from which essential amino acid residues in that pocket have also been identified. 283 genes were identified as essential genes with high-confidence. An agreement of about 73.5% is observed with that obtained from the experimental transposon mutagenesis technique. A large proportion of the identified genes belong to the class of intermediary metabolism and respiration.

Conclusions

The multi-scale, multi-level approach described can be generally applied to other pathogens as well. The essential gene pool identified form a basis for designing experiments to probe their finer functional roles and also serve as a ready shortlist for identifying drug targets.

A novel phenotypic dissimilarity method for image-based high-throughput screens

Background

Discovering functional relationships of genes through cell-based phenotyping has become an important approach in functional genomics. High-throughput imaging offers the ability to quantitatively assess complex phenotypes after perturbation by RNA interference (RNAi). Such image-based high-throughput RNAi screening studies have facilitated the discovery of novel components of gene networks and their interactions. Images generated by automated microscopy are typically analyzed by extracting quantitative features of individual cells, resulting in large multidimensional data sets. Robust and sensitive methods to interpret these data sets and to derive biologically relevant information in a high-throughput and unbiased manner remain to be developed.

Results

Here we propose a new analysis method, PhenoDissim, which computes the phenotypic dissimilarity between cell populations via Support Vector Machine classification and cross validation. Applying this method to a kinome RNAi screening data set, we demonstrate that the proposed method shows a good replicate reproducibility, separation of controls and clustering quality, and we are able to identify siRNA phenotypes and discover potential functional links between genes.

Conclusions

PhenoDissim is a novel analysis method for image-based high-throughput screen, relying on two parameters which can be automatically optimized without a priori knowledge. PhenoDissim is freely available as an R package.

Profiling of the mammalian mitotic spindle proteome reveals an ER protein, OSTD-1, as being necessary for cell division and ER morphology

Cell division is important for many cellular processes including cell growth, reproduction, wound healing and stem cell renewal. Failures in cell division can often lead to tumors and birth defects. To identify factors necessary for this process, we implemented a comparative profiling strategy of the published mitotic spindle proteome from our laboratory. Of the candidate mammalian proteins, we determined that 77% had orthologs in Caenorhabditis elegans and 18% were associated with human disease. Of the C. elegans candidates (n=146), we determined that 34 genes functioned in embryonic development and 56% of these were predicted to be membrane trafficking proteins. A secondary, visual screen to detect distinct defects in cell division revealed 21 genes that were necessary for cytokinesis. One of these candidates, OSTD-1, an ER resident protein, was further characterized due to the aberrant cleavage furrow placement and failures in division. We determined that OSTD-1 plays a role in maintaining the dynamic morphology of the ER during the cell cycle. In addition, 65% of all ostd-1 RNAi-treated embryos failed to correctly position cleavage furrows, suggesting that proper ER morphology plays a necessary function during animal cell division.