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1.  Single-cell analysis of population context advances RNAi screening at multiple levels 
A large set of high-content RNAi screens investigating mammalian virus infection and multiple cellular activities is analysed to reveal the impact of population context on phenotypic variability and to identify indirect RNAi effects.
Cell population context determines phenotypes in RNAi screens of multiple cellular activities (including virus infection, cell size regulation, endocytosis, and lipid homeostasis), which can be accounted for by a combination of novel image analysis and multivariate statistical methods.Accounting for cell population context-mediated effects strongly changes the reproducibility and consistency of RNAi screens across cell lines as well as of siRNAs targeting the same gene.Such analyses can identify the perturbed regulation of population context dependent cell-to-cell variability, a novel perturbation phenotype.Overall, these methods advance the use of large-scale RNAi screening for a systems-level understanding of cellular processes.
Isogenic cells in culture show strong variability, which arises from dynamic adaptations to the microenvironment of individual cells. Here we study the influence of the cell population context, which determines a single cell's microenvironment, in image-based RNAi screens. We developed a comprehensive computational approach that employs Bayesian and multivariate methods at the single-cell level. We applied these methods to 45 RNA interference screens of various sizes, including 7 druggable genome and 2 genome-wide screens, analysing 17 different mammalian virus infections and four related cell physiological processes. Analysing cell-based screens at this depth reveals widespread RNAi-induced changes in the population context of individual cells leading to indirect RNAi effects, as well as perturbations of cell-to-cell variability regulators. We find that accounting for indirect effects improves the consistency between siRNAs targeted against the same gene, and between replicate RNAi screens performed in different cell lines, in different labs, and with different siRNA libraries. In an era where large-scale RNAi screens are increasingly performed to reach a systems-level understanding of cellular processes, we show that this is often improved by analyses that account for and incorporate the single-cell microenvironment.
doi:10.1038/msb.2012.9
PMCID: PMC3361004  PMID: 22531119
cell-to-cell variability; image analysis; population context; RNAi; virus infection
2.  Clustering phenotype populations by genome-wide RNAi and multiparametric imaging 
How to predict gene function from phenotypic cues is a longstanding question in biology.Using quantitative multiparametric imaging, RNAi-mediated cell phenotypes were measured on a genome-wide scale.On the basis of phenotypic ‘neighbourhoods', we identified previously uncharacterized human genes as mediators of the DNA damage response pathway and the maintenance of genomic integrity.The phenotypic map is provided as an online resource at http://www.cellmorph.org for discovering further functional relationships for a broad spectrum of biological module
Genetic screens for phenotypic similarity have made key contributions for associating genes with biological processes. Aggregating genes by similarity of their loss-of-function phenotype has provided insights into signalling pathways that have a conserved function from Drosophila to human (Nusslein-Volhard and Wieschaus, 1980; Bier, 2005). Complex visual phenotypes, such as defects in pattern formation during development, greatly facilitated the classification of genes into pathways, and phenotypic similarities in many cases predicted molecular relationships. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cultured cells has become feasible in many organisms whose genome have been sequenced (Boutros and Ahringer, 2008). One of the current challenges is the computational categorization of visual phenotypes and the prediction of gene function and associated biological processes. With large parts of the genome still being in unchartered territory, deriving functional information from large-scale phenotype analysis promises to uncover novel gene–gene relationships and to generate functional maps to explore cellular processes.
In this study, we developed an automated approach using RNAi-mediated cell phenotypes, multiparametric imaging and computational modelling to obtain functional information on previously uncharacterized genes. To generate broad, computer-readable phenotypic signatures, we measured the effect of RNAi-mediated knockdowns on changes of cell morphology in human cells on a genome-wide scale. First, the several million cells were stained for nuclear and cytoskeletal markers and then imaged using automated microscopy. On the basis of fluorescent markers, we established an automated image analysis to classify individual cells (Figure 1A). After cell segmentation for determining nuclei and cell boundaries (Figure 1C), we computed 51 cell descriptors that quantified intensities, shape characteristics and texture (Figure 1F). Individual cells were categorized into 1 of 10 classes, which included cells showing protrusion/elongation, cells in metaphase, large cells, condensed cells, cells with lamellipodia and cellular debris (Figure 1D and E). Each siRNA knockdown was summarized by a phenotypic profile and differences between RNAi knockdowns were quantified by the similarity between phenotypic profiles. We termed the vector of scores a phenoprint (Figure 3C) and defined the phenotypic distance between a pair of perturbations as the distance between their corresponding phenoprints.
To visualize the distribution of all phenoprints, we plotted them in a genome-wide map as a two-dimensional representation of the phenotypic similarity relationships (Figure 3A). The complete data set and an interactive version of the phenotypic map are available at http://www.cellmorph.org. The map identified phenotypic ‘neighbourhoods', which are characterized by cells with lamellipodia (WNK3, ANXA4), cells with prominent actin fibres (ODF2, SOD3), abundance of large cells (CA14), many elongated cells (SH2B2, ELMO2), decrease in cell number (TPX2, COPB1, COPA), increase in number of cells in metaphase (BLR1, CIB2) and combinations of phenotypes such as presence of large cells with protrusions and bright nuclei (PTPRZ1, RRM1; Figure 3B).
To test whether phenotypic similarity might serve as a predictor of gene function, we focused our further analysis on two clusters that contained genes associated with the DNA damage response (DDR) and genomic integrity (Figure 3A and C). The first phenotypic cluster included proteins with kinetochore-associated functions such as NUF2 (Figure 3B) and SGOL1. It also contained the centrosomal protein CEP164 that has been described as an important mediator of the DNA damage-activated signalling cascade (Sivasubramaniam et al, 2008) and the largely uncharacterized genes DONSON and SON. A second phenotypically distinct cluster included previously described components of the DDR pathway such as RRM1 (Figure 3A–C), CLSPN, PRIM2 and SETD8. Furthermore, this cluster contained the poorly characterized genes CADM1 and CD3EAP.
Cells activate a signalling cascade in response to DNA damage induced by exogenous and endogenous factors. Central are the kinases ATM and ATR as they serve as sensors of DNA damage and activators of further downstream kinases (Harper and Elledge, 2007; Cimprich and Cortez, 2008). To investigate whether DONSON, SON, CADM1 and CD3EAP, which were found in phenotypic ‘neighbourhoods' to known DDR components, have a role in the DNA damage signalling pathway, we tested the effect of their depletion on the DDR on γ irradiation. As indicated by reduced CHEK1 phosphorylation, siRNA knock down of DONSON, SON, CD3EAP or CADM1 resulted in impaired DDR signalling on γ irradiation. Furthermore, knock down of DONSON or SON reduced phosphorylation of downstream effectors such as NBS1, CHEK1 and the histone variant H2AX on UVC irradiation. DONSON depletion also impaired recruitment of RPA2 onto chromatin and SON knockdown reduced RPA2 phosphorylation indicating that DONSON and SON presumably act downstream of the activation of ATM. In agreement to their phenotypic profile, these results suggest that DONSON, SON, CADM1 and CD3EAP are important mediators of the DDR. Further experiments demonstrated that they are also required for the maintenance of genomic integrity.
In summary, we show that genes with similar phenotypic profiles tend to share similar functions. The power of our computational and experimental approach is demonstrated by the identification of novel signalling regulators whose phenotypic profiles were found in proximity to known biological modules. Therefore, we believe that such phenotypic maps can serve as a resource for functional discovery and characterization of unknown genes. Furthermore, such approaches are also applicable for other perturbation reagents, such as small molecules in drug discovery and development. One could also envision combined maps that contain both siRNAs and small molecules to predict target–small molecule relationships and potential side effects.
Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and explore functional relationships. We performed a genome-wide RNAi screen in human cells and used quantitative descriptors derived from high-throughput imaging to generate multiparametric phenotypic profiles. We show that profiles predicted functions of genes by phenotypic similarity. Specifically, we examined several candidates including the largely uncharacterized gene DONSON, which shared phenotype similarity with known factors of DNA damage response (DDR) and genomic integrity. Experimental evidence supports that DONSON is a novel centrosomal protein required for DDR signalling and genomic integrity. Multiparametric phenotyping by automated imaging and computational annotation is a powerful method for functional discovery and mapping the landscape of phenotypic responses to cellular perturbations.
doi:10.1038/msb.2010.25
PMCID: PMC2913390  PMID: 20531400
DNA damage response signalling; massively parallel phenotyping; phenotype networks; RNAi screening
3.  Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens 
BMC Bioinformatics  2008;9:264.
Background
The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens.
Results
Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using Drosophila embryos [Additional files 1, 2], dataset for cell cycle phase identification using HeLa cells [Additional files 1, 3, 4] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a Drosophila genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms.
Conclusion
We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens.
doi:10.1186/1471-2105-9-264
PMCID: PMC2443381  PMID: 18534020
4.  RNAi screen of Salmonella invasion shows role of COPI in membrane targeting of cholesterol and Cdc42 
A genome wide RNAi screen identifies 72 host cell genes affecting S. Typhimurium entry, including actin regulators and COPI. This study implicates COPI-dependent cholesterol and sphingolipid localization as a common mechanism of infection by bacterial and viral pathogens.
Genome-scale RNAi screen identifies 72 host genes affecting S. Typhimurium host cell invasion.Step-specific follow-up assays assign the phenotypes to specific steps of the invasion process.COPI effects on host cell binding, ruffling and invasion were traced to a key role of COPI in membrane targeting of cholesterol, sphingolipids, Rac1 and Cdc42.This new role of COPI explains why COPI is required for host cell infection by numerous bacterial and viral pathogens.
Pathogens are not only a menace to public health, but they also provide excellent tools for probing host cell function. Thus, studying infection mechanisms has fueled progress in cell biology (Ridley et al, 1992; Welch et al, 1997). In the presented study, we have performed an RNAi screen to identify host cell genes required for Salmonella host cell invasion. This screen identified proteins known to contribute to Salmonella-induced actin rearrangements (e.g., Cdc42 and the Arp2/3 complex; reviewed in Schlumberger and Hardt, 2006) and vesicular traffic (e.g., Rab7) as well as unexpected hits, such as the COPI complex. COPI is a known organizer of Golgi-to-ER vesicle transport (Bethune et al, 2006; Beck et al, 2009). Here, we show that COPI is also involved in plasma membrane targeting of cholesterol, sphingolipids and the Rho GTPases Cdc42 and Rac1, essential host cell factors required for Salmonella invasion. This explains why COPI depletion inhibits infection by S. Typhimurium and illustrates how combining bacterial pathogenesis and systems approaches can promote cell biology.
Salmonella Typhimurium is a common food-borne pathogen and worldwide a major public health problem causing severe diarrhea. The pathogen uses the host's gut mucosa as a portal of entry and gut tissue invasion is a key event leading to the disease. This explains the intense interest from medicine and basic biology in the mechanism of Salmonella host cell invasion.
Tissue culture infection models have delineated a sequence of events leading host cell invasion (Figure 1; Schlumberger and Hardt, 2006): (i) pathogen binding to the host cell surface; (ii) activation of a syringe-like apparatus (‘Type III secretion system 1', T1) of the bacterium and injection of a bacterial toxin cocktail into the host cell. These toxins include SopE, a key virulence factor triggering invasion (Hardt et al, 1998), which was analyzed in our study; (iii) toxin-triggered membrane ruffling. To a significant extent, this is facilitated by SopE-triggered activation of Cdc42 and Rac1 and subsequent actin polymerization at the site of infection; (iv) engulfment of the pathogen within a vesicular compartment (SCV) and (v) maturation of the SCV, a process driven by a second Type III secretion system (T2), which is expressed by the pathogen upon bacterial entry (Figure 1). This sequence of events mediates Salmonella invasion into the gut epithelium and illustrates that this pathogen can be used for probing mechanisms of host cell actin control, membrane biogenesis, vesicle formation and vesicular trafficking.
SopE is a key virulence factor of invasion and triggers the activation of Cdc42 and Rac1 and subsequent actin polymerization at the site of infection. We have employed a SopE-expressing S. Typhimurium strain and RNAi screening technology to identify host cell factors affecting invasion. First, we developed an automated fluorescence microscopy assay to quantify S. Typhimurium entry in a high-throughput format (Figure 1C). This assay was based on a GFP reporter expressed by the pathogen after invasion and maturation of the SCV. Using this assay, we screened a ‘druggable genome' siRNA library (6978 genes, 3 oligos each, 1 oligo per well) and identified 72 invasion hits. These included established regulators of the actin cytoskeleton (Cdc42, Arp2/3, Nap1; Schlumberger and Hardt, 2006), some of which have not been implicated so far in Salmonella entry (Pfn1, Cap1), as well as proteins not previously thought to influence infection (Atp1a1, Rbx1, COPI complex). Potentially, these hits could affect any step of the invasion process (Figure 1A).
In the second stage of the study, we have assigned each ‘invasion hit' to particular steps of the invasion process. For this purpose, we developed step-specific assays for Salmonella binding, injection, ruffling and membrane engulfment and re-screened the genes found as hits in the first screen (four siRNAs per gene). As expected, a significant number of ‘hits' affected binding to the host cell, others affected binding and ruffling (e.g., Pfn1, Itgβ5, Cap1), a few were specific for the ruffling step (e.g., Cdc42) and some affected SCV maturation, namely Rab7a, the trafficking protein Vps39 and the vacuolar proton pump Atp6ap2. Thus, our experimental strategy allowed mechanistic interpretation and linked novel hits to particular phenotypes, thus providing a basis for further studies (Figure 1).
COPI depletion impaired effector injection and ruffling. This was surprising, as the COPI complex was known to regulate retrogade Golgi-to-ER transport, but was not expected to affect pathogen interactions at the plasma membrane. Therefore, we have investigated the underlying mechanism. We have observed that COPI depletion entailed dramatic changes in the plasma membrane composition (Figure 6). Cholesterol and sphingolipids, which form domains (‘lipid rafts') in the plasma membrane, were depleted from the cell surface and redirected into a large vesicular compartment. The same was true for the Rho GTPases Rac1 and Cdc42. This strong decrease in the amount of cholesterol-enriched microdomains and Rho GTPases in the plasma membrane explained the observed defects in S. Typhimurium host cell invasion and assigned a novel role for COPI in controlling mammalian plasma membrane composition. It should be noted that other viral and bacterial pathogens do show a similar dependency on host cellular COPI and plasma membrane lipids. This includes notorious pathogens such as Staphylococcus aureus (Ramet et al, 2002; Potrich et al, 2009), Listeria monocytogenes (Seveau et al, 2004; Agaisse et al, 2005; Cheng et al, 2005; Gekara et al, 2005), Mycobacterium tuberculosis (Munoz et al, 2009), Chlamydia trachomatis (Elwell et al, 2008), influenza virus (Hao et al, 2008; Konig et al, 2010), hepatitis C virus (Tai et al, 2009; Popescu and Dubuisson, 2010) and the vesicular stomatitis virus (presented study) and suggests that COPI-mediated control of host cell plasma membrane composition might be of broad importance for pathogenesis. Future work will have to address whether this might offer starting points for developing anti-infective therapeutics with a very broad spectrum of activity.
The pathogen Salmonella Typhimurium is a common cause of diarrhea and invades the gut tissue by injecting a cocktail of virulence factors into epithelial cells, triggering actin rearrangements, membrane ruffling and pathogen entry. One of these factors is SopE, a G-nucleotide exchange factor for the host cellular Rho GTPases Rac1 and Cdc42. How SopE mediates cellular invasion is incompletely understood. Using genome-scale RNAi screening we identified 72 known and novel host cell proteins affecting SopE-mediated entry. Follow-up assays assigned these ‘hits' to particular steps of the invasion process; i.e., binding, effector injection, membrane ruffling, membrane closure and maturation of the Salmonella-containing vacuole. Depletion of the COPI complex revealed a unique effect on virulence factor injection and membrane ruffling. Both effects are attributable to mislocalization of cholesterol, sphingolipids, Rac1 and Cdc42 away from the plasma membrane into a large intracellular compartment. Equivalent results were obtained with the vesicular stomatitis virus. Therefore, COPI-facilitated maintenance of lipids may represent a novel, unifying mechanism essential for a wide range of pathogens, offering opportunities for designing new drugs.
doi:10.1038/msb.2011.7
PMCID: PMC3094068  PMID: 21407211
coatomer; HeLa; Salmonella; siRNA; systems biology
5.  A network-based integrative approach to prioritize reliable hits from multiple genome-wide RNAi screens in Drosophila 
BMC Genomics  2009;10:220.
Background
The recently developed RNA interference (RNAi) technology has created an unprecedented opportunity which allows the function of individual genes in whole organisms or cell lines to be interrogated at genome-wide scale. However, multiple issues, such as off-target effects or low efficacies in knocking down certain genes, have produced RNAi screening results that are often noisy and that potentially yield both high rates of false positives and false negatives. Therefore, integrating RNAi screening results with other information, such as protein-protein interaction (PPI), may help to address these issues.
Results
By analyzing 24 genome-wide RNAi screens interrogating various biological processes in Drosophila, we found that RNAi positive hits were significantly more connected to each other when analyzed within a protein-protein interaction network, as opposed to random cases, for nearly all screens. Based on this finding, we developed a network-based approach to identify false positives (FPs) and false negatives (FNs) in these screening results. This approach relied on a scoring function, which we termed NePhe, to integrate information obtained from both PPI network and RNAi screening results. Using a novel rank-based test, we compared the performance of different NePhe scoring functions and found that diffusion kernel-based methods generally outperformed others, such as direct neighbor-based methods. Using two genome-wide RNAi screens as examples, we validated our approach extensively from multiple aspects. We prioritized hits in the original screens that were more likely to be reproduced by the validation screen and recovered potential FNs whose involvements in the biological process were suggested by previous knowledge and mutant phenotypes. Finally, we demonstrated that the NePhe scoring system helped to biologically interpret RNAi results at the module level.
Conclusion
By comprehensively analyzing multiple genome-wide RNAi screens, we conclude that network information can be effectively integrated with RNAi results to produce suggestive FPs and FNs, and to bring biological insight to the screening results.
doi:10.1186/1471-2164-10-220
PMCID: PMC2697172  PMID: 19435510
6.  High Content Screening of a Kinase-Focused Library Reveals Compounds Broadly-Active against Dengue Viruses 
Dengue virus is a mosquito-borne flavivirus that has a large impact in global health. It is considered as one of the medically important arboviruses, and developing a preventive or therapeutic solution remains a top priority in the medical and scientific community. Drug discovery programs for potential dengue antivirals have increased dramatically over the last decade, largely in part to the introduction of high-throughput assays. In this study, we have developed an image-based dengue high-throughput/high-content assay (HT/HCA) using an innovative computer vision approach to screen a kinase-focused library for anti-dengue compounds. Using this dengue HT/HCA, we identified a group of compounds with a 4-(1-aminoethyl)-N-methylthiazol-2-amine as a common core structure that inhibits dengue viral infection in a human liver-derived cell line (Huh-7.5 cells). Compounds CND1201, CND1203 and CND1243 exhibited strong antiviral activities against all four dengue serotypes. Plaque reduction and time-of-addition assays suggests that these compounds interfere with the late stage of viral infection cycle. These findings demonstrate that our image-based dengue HT/HCA is a reliable tool that can be used to screen various chemical libraries for potential dengue antiviral candidates.
Author Summary
Dengue, a re-emergent human disease that places nearly half of the world's population at risk, threatens to further expand in geographical distribution. The lack of an available effective dengue vaccine has encouraged the search for antiviral drugs as an alternative approach. In recent years, drug discovery through high-throughput screening has become a trend in the search for dengue antivirals. In this study, we developed an image-based dengue high-throughput/high-content assay using prevalent viral strains of three dengue serotypes (DENV1, DENV2 and DENV3) isolated from dengue outbreaks in South America and a laboratory-adapted strain of DENV4. We demonstrated the usefulness of our image-based dengue HT/HCA in identifying potential dengue antivirals by screening a small subset of chemical compounds for inhibition of dengue virus infection in a human-derived host cell line (Huh-7.5), and partially characterized their activities against dengue infection in a mosquito host cell line (C6/36), a distantly-related virus (hepatitis C virus), and an unrelated virus that is transmitted by the same mosquito vector (chikungunya virus).
doi:10.1371/journal.pntd.0002073
PMCID: PMC3578765  PMID: 23437413
7.  Flow cytometry-based functional selection of RNA interference triggers for efficient epi-allelic analysis of therapeutic targets 
BMC Biotechnology  2014;14:57.
Background
The dose-response relationship is a fundamental pharmacological parameter necessary to determine therapeutic thresholds. Epi-allelic hypomorphic analysis using RNA interference (RNAi) can similarly correlate target gene dosage with cellular phenotypes. This however requires a set of RNAi triggers empirically determined to attenuate target gene expression to different levels.
Results
In order to improve our ability to incorporate epi-allelic analysis into target validation studies, we developed a novel flow cytometry-based functional screening approach (CellSelectRNAi) to achieve unbiased selection of shRNAs from high-coverage libraries that knockdown target gene expression to predetermined levels. Employing a Gaussian probability model we calculated that knockdown efficiency is inferred from shRNA sequence frequency profiles derived from sorted hypomorphic cell populations. We used this approach to generate a hypomorphic epi-allelic cell series of shRNAs to reveal a functional threshold for the tumor suppressor p53 in normal and transformed cells.
Conclusion
The unbiased CellSelectRNAi flow cytometry-based functional screening approach readily provides an epi-allelic series of shRNAs for graded reduction of target gene expression and improved phenotypic validation.
doi:10.1186/1472-6750-14-57
PMCID: PMC4074332  PMID: 24952598
8.  Adenovirus Delivered Short Hairpin RNA Targeting a Conserved Site in the 5′ Non-Translated Region Inhibits All Four Serotypes of Dengue Viruses 
Background
Dengue is a mosquito-borne viral disease caused by four closely related serotypes of Dengue viruses (DENVs). This disease whose symptoms range from mild fever to potentially fatal haemorrhagic fever and hypovolemic shock, threatens nearly half the global population. There is neither a preventive vaccine nor an effective antiviral therapy against dengue disease. The difference between severe and mild disease appears to be dependent on the viral load. Early diagnosis may enable timely therapeutic intervention to blunt disease severity by reducing the viral load. Harnessing the therapeutic potential of RNA interference (RNAi) to attenuate DENV replication may offer one approach to dengue therapy.
Methodology/Principal Findings
We screened the non-translated regions (NTRs) of the RNA genomes of representative members of the four DENV serotypes for putative siRNA targets mapping to known transcription/translation regulatory elements. We identified a target site in the 5′ NTR that maps to the 5′ upstream AUG region, a highly conserved cis-acting element essential for viral replication. We used a replication-defective human adenovirus type 5 (AdV5) vector to deliver a short-hairpin RNA (shRNA) targeting this site into cells. We show that this shRNA matures to the cognate siRNA and is able to inhibit effectively antigen secretion, viral RNA replication and infectious virus production by all four DENV serotypes.
Conclusion/Significance
The data demonstrate the feasibility of using AdV5-mediated delivery of shRNAs targeting conserved sites in the viral genome to achieve inhibition of all four DENV serotypes. This paves the way towards exploration of RNAi as a possible therapeutic strategy to curtail DENV infection.
Author Summary
Dengue is a mosquito-borne viral disease that threatens nearly half the global population. The symptoms of this disease, caused by four closely related Dengue viruses, range from mild fever to potentially fatal haemorrhagic fever and shock. There is neither a preventive vaccine nor an effective antiviral therapy against the disease. The difference between severe and mild disease appears to be dependent on the viral load. Reducing the virus levels in the bloodstream through therapeutic intervention may be associated with favourable prognosis. We investigated the feasibility of destroying dengue virus genomic RNA using a phenomenon known as RNA interference, in which the RNA-cleaving activity of a cellular enzyme complex is directed to a site in the target RNA, using a short complementary RNA known as small interfering RNA. We used adenovirus, a common cold virus, to deliver a small interfering RNA complementary to a conserved region just adjacent to the initiator codon in the dengue virus RNA. We found that this could inhibit viral RNA multiplication, expression of viral proteins and the secretion of infectious virus. Importantly, our results showed that the adenovirus delivered small interfering RNA which could inhibit all four types of dengue viruses.
doi:10.1371/journal.pntd.0001735
PMCID: PMC3404111  PMID: 22848770
9.  Main Report 
Genetics in Medicine  2006;8(Suppl 1):12S-252S.
Background:
States vary widely in their use of newborn screening tests, with some mandating screening for as few as three conditions and others mandating as many as 43 conditions, including varying numbers of the 40+ conditions that can be detected by tandem mass spectrometry (MS/MS). There has been no national guidance on the best candidate conditions for newborn screening since the National Academy of Sciences report of 19751 and the United States Congress Office of Technology Assessment report of 1988,2 despite rapid developments since then in genetics, in screening technologies, and in some treatments.
Objectives:
In 2002, the Maternal and Child Health Bureau (MCHB) of the Health Resources and Services Administration (HRSA) of the United States Department of Health and Human Services (DHHS) commissioned the American College of Medical Genetics (ACMG) to: Conduct an analysis of the scientific literature on the effectiveness of newborn screening.Gather expert opinion to delineate the best evidence for screening for specified conditions and develop recommendations focused on newborn screening, including but not limited to the development of a uniform condition panel.Consider other components of the newborn screening system that are critical to achieving the expected outcomes in those screened.
Methods:
A group of experts in various areas of subspecialty medicine and primary care, health policy, law, public health, and consumers worked with a steering committee and several expert work groups, using a two-tiered approach to assess and rank conditions. A first step was developing a set of principles to guide the analysis. This was followed by developing criteria by which conditions could be evaluated, and then identifying the conditions to be evaluated. A large and broadly representative group of experts was asked to provide their opinions on the extent to which particular conditions met the selected criteria, relying on supporting evidence and references from the scientific literature. The criteria were distributed among three main categories for each condition: The availability and characteristics of the screening test;The availability and complexity of diagnostic services; andThe availability and efficacy of treatments related to the conditions. A survey process utilizing a data collection instrument was used to gather expert opinion on the conditions in the first tier of the assessment. The data collection format and survey provided the opportunity to quantify expert opinion and to obtain the views of a diverse set of interest groups (necessary due to the subjective nature of some of the criteria). Statistical analysis of data produced a score for each condition, which determined its ranking and initial placement in one of three categories (high scoring, moderately scoring, or low scoring/absence of a newborn screening test). In the second tier of these analyses, the evidence base related to each condition was assessed in depth (e.g., via systematic reviews of reference lists including MedLine, PubMed and others; books; Internet searches; professional guidelines; clinical evidence; and cost/economic evidence and modeling). The fact sheets reflecting these analyses were evaluated by at least two acknowledged experts for each condition. These experts assessed the data and the associated references related to each criterion and provided corrections where appropriate, assigned a value to the level of evidence and the quality of the studies that established the evidence base, and determined whether there were significant variances from the survey data. Survey results were subsequently realigned with the evidence obtained from the scientific literature during the second-tier analysis for all objective criteria, based on input from at least three acknowledged experts in each condition. The information from these two tiers of assessment was then considered with regard to the overriding principles and other technology or condition-specific recommendations. On the basis of this information, conditions were assigned to one of three categories as described above:Core Panel;Secondary Targets (conditions that are part of the differential diagnosis of a core panel condition.); andNot Appropriate for Newborn Screening (either no newborn screening test is available or there is poor performance with regard to multiple other evaluation criteria).
ACMG also considered features of optimal newborn screening programs beyond the tests themselves by assessing the degree to which programs met certain goals (e.g., availability of educational programs, proportions of newborns screened and followed up). Assessments were based on the input of experts serving in various capacities in newborn screening programs and on 2002 data provided by the programs of the National Newborn Screening and Genetics Resource Center (NNSGRC). In addition, a brief cost-effectiveness assessment of newborn screening was conducted.
Results:
Uniform panel
A total of 292 individuals determined to be generally representative of the regional distribution of the United States population and of areas of expertise or involvement in newborn screening provided a total of 3,949 evaluations of 84 conditions. For each condition, the responses of at least three experts in that condition were compared with those of all respondents for that condition and found to be consistent. A score of 1,200 on the data collection instrument provided a logical separation point between high scoring conditions (1,200–1,799 of a possible 2,100) and low scoring (<1,000) conditions. A group of conditions with intermediate scores (1,000–1,199) was identified, all of which were part of the differential diagnosis of a high scoring condition or apparent in the result of the multiplex assay. Some are identified by screening laboratories and others by diagnostic laboratories. This group was designated as a “secondary target” category for which the program must report the diagnostic result.
Using the validated evidence base and expert opinion, each condition that had previously been assigned to a category based on scores gathered through the data collection instrument was reconsidered. Again, the factors taken into consideration were: 1) available scientific evidence; 2) availability of a screening test; 3) presence of an efficacious treatment; 4) adequate understanding of the natural history of the condition; and 5) whether the condition was either part of the differential diagnosis of another condition or whether the screening test results related to a clinically significant condition.
The conditions were then assigned to one of three categories as previously described (core panel, secondary targets, or not appropriate for Newborn Screening).
Among the 29 conditions assigned to the core panel are three hemoglobinopathies associated with a Hb/S allele, six amino acidurias, five disorders of fatty oxidation, nine organic acidurias, and six unrelated conditions (congenital hypothyroidism (CH), biotinidase deficiency (BIOT), congenital adrenal hyperplasia (CAH), classical galactosemia (GALT), hearing loss (HEAR) and cystic fibrosis (CF)). Twenty-three of the 29 conditions in the core panel are identified with multiplex technologies such as tandem mass spectrometry (MS/MS) or high pressure liquid chromatography (HPLC). On the basis of the evidence, six of the 35 conditions initially placed in the core panel were moved into the secondary target category, which expanded to 25 conditions. Test results not associated with potential disease in the infant (e.g., carriers) were also placed in the secondary target category. When newborn screening laboratory results definitively establish carrier status, the result should be made available to the health care professional community and families. Twenty-seven conditions were determined to be inappropriate for newborn screening at this time.
Conditions with limited evidence reported in the scientific literature were more difficult to evaluate, quantify and place in one of the three categories. In addition, many conditions were found to occur in multiple forms distinguished by age-of-onset, severity, or other features. Further, unless a condition was already included in newborn screening programs, there was a potential for bias in the information related to some criteria. In such circumstances, the quality of the studies underlying the data such as expert opinion that considered case reports and reasoning from first principles determined the placement of the conditions into particular categories.
Newborn screening program optimization
– Assessment of the activities of newborn screening programs, based on program reports, was done for the six program components: education; screening; follow-up; diagnostic confirmation; management; and program evaluation. Considerable variation was found between programs with regard to whether particular aspects (e.g., prenatal education program availability, tracking of specimen collection and delivery) were included and the degree to which they are provided. Newborn screening program evaluation systems also were assessed in order to determine their adequacy and uniformity with the goal being to improve interprogram evaluation and comparison to ensure that the expected outcomes from having been identified in screening are realized.
Conclusions:
The state of the published evidence in the fast-moving worlds of newborn screening and medical genetics has not kept up with the implementation of new technologies, thus requiring the considerable use of expert opinion to develop recommendations about a core panel of conditions for newborn screening. Twenty-nine conditions were identified as primary targets for screening from which all components of the newborn screening system should be maximized. An additional 25 conditions were listed that could be identified in the course of screening for core panel conditions. Programs are obligated to establish a diagnosis and communicate the result to the health care provider and family. It is recognized that screening may not have been maximized for the detection of these secondary conditions but that some proportion of such cases may be found among those screened for core panel conditions. With additional screening, greater training of primary care health care professionals and subspecialists will be needed, as will the development of an infrastructure for appropriate follow-up and management throughout the lives of children who have been identified as having one of these rare conditions. Recommended actions to overcome barriers to an optimal newborn screening system include: The establishment of a national role in the scientific evaluation of conditions and the technologies by which they are screened;Standardization of case definitions and reporting procedures;Enhanced oversight of hospital-based screening activities;Long-term data collection and surveillance; andConsideration of the financial needs of programs to allow them to deliver the appropriate services to the screened population.
doi:10.1097/01.gim.0000223467.60151.02
PMCID: PMC3109899
10.  An image score inference system for RNAi genome-wide screening based on fuzzy mixture regression modeling 
With recent advances in fluorescence microscopy imaging techniques and methods of gene knock down by RNA interference (RNAi), genome-scale high-content screening (HCS) has emerged as a powerful approach to systematically identify all parts of complex biological processes. However, a critical barrier preventing fulfillment of the success is the lack of efficient and robust methods for automating RNAi image analysis and quantitative evaluation of the gene knock down effects on huge volume of HCS data. Facing such opportunities and challenges, we have started investigation of automatic methods towards the development of a fully automatic RNAi-HCS system. Particularly important are reliable approaches to cellular phenotype classification and image-based gene function estimation.
We have developed a HCS analysis platform that consists of two main components: fluorescence image analysis and image scoring. For image analysis, we used a two-step enhanced watershed method to extract cellular boundaries from HCS images. Segmented cells were classified into several predefined phenotypes based on morphological and appearance features. Using statistical characteristics of the identified phenotypes as a quantitative description of the image, a score is generated that reflects gene function. Our scoring model integrates fuzzy gene class estimation and single regression models. The final functional score of an image was derived using the weighted combination of the inference from several support vector-based regression models. We validated our phenotype classification method and scoring system on our cellular phenotype and gene database with expert ground truth labeling.
We built a database of high-content, 3-channel, fluorescence microscopy images of Drosophila Kc167 cultured cells that were treated with RNAi to perturb gene function. The proposed informatics system for microscopy image analysis is tested on this database. Both of the two main components, automated phenotype classification and image scoring system, were evaluated. The robustness and efficiency of our system were validated in quantitatively predicting the biological relevance of genes.
doi:10.1016/j.jbi.2008.04.007
PMCID: PMC2763194  PMID: 18547870
High-content screening; Image score inference
11.  Identification of Drosophila Mitotic Genes by Combining Co-Expression Analysis and RNA Interference 
PLoS Genetics  2008;4(7):e1000126.
RNAi screens have, to date, identified many genes required for mitotic divisions of Drosophila tissue culture cells. However, the inventory of such genes remains incomplete. We have combined the powers of bioinformatics and RNAi technology to detect novel mitotic genes. We found that Drosophila genes involved in mitosis tend to be transcriptionally co-expressed. We thus constructed a co-expression–based list of 1,000 genes that are highly enriched in mitotic functions, and we performed RNAi for each of these genes. By limiting the number of genes to be examined, we were able to perform a very detailed phenotypic analysis of RNAi cells. We examined dsRNA-treated cells for possible abnormalities in both chromosome structure and spindle organization. This analysis allowed the identification of 142 mitotic genes, which were subdivided into 18 phenoclusters. Seventy of these genes have not previously been associated with mitotic defects; 30 of them are required for spindle assembly and/or chromosome segregation, and 40 are required to prevent spontaneous chromosome breakage. We note that the latter type of genes has never been detected in previous RNAi screens in any system. Finally, we found that RNAi against genes encoding kinetochore components or highly conserved splicing factors results in identical defects in chromosome segregation, highlighting an unanticipated role of splicing factors in centromere function. These findings indicate that our co-expression–based method for the detection of mitotic functions works remarkably well. We can foresee that elaboration of co-expression lists using genes in the same phenocluster will provide many candidate genes for small-scale RNAi screens aimed at completing the inventory of mitotic proteins.
Author Summary
Mitosis is the evolutionarily conserved process that enables a dividing cell to equally partition its genetic material between the two daughter cells. The fidelity of mitotic division is crucial for normal development of multicellular organisms and to prevent cancer or birth defects. Understanding the molecular mechanisms of mitosis requires the identification of genes involved in this process. Previous studies have shown that such genes can be readily identified by RNA interference (RNAi) in Drosophila tissue culture cells. Because the inventory of mitotic genes is still incomplete, we have undertaken an RNAi screen using a novel approach. We used a co-expression–based bioinformatic procedure to select a group of 1,000 genes enriched in mitotic functions from a dataset of 13,166 Drosophila genes. This group includes roughly half of the known mitotic genes, implying that it should contain half of all mitotic genes, including those that are currently unknown. We performed RNAi against each of the 1,000 genes in the group. By limiting the number of genes to be examined, we were able to perform a very detailed phenotypic analysis of RNAi cells. This analysis allowed the identification of 70 genes whose mitotic role was previously unknown; 30 are required for proper chromosome segregation and 40 are required to maintain chromosome integrity.
doi:10.1371/journal.pgen.1000126
PMCID: PMC2537813  PMID: 18797514
12.  Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble 
BMC Bioinformatics  2011;12:128.
Background
Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA interference (RNAi) or small-molecule screens. As such, efficient computational methods are required for automatic cellular phenotype identification capable of dealing with large image data sets. In this paper we investigated an efficient method for the extraction of quantitative features from images by combining second order statistics, or Haralick features, with curvelet transform. A random subspace based classifier ensemble with multiple layer perceptron (MLP) as the base classifier was then exploited for classification. Haralick features estimate image properties related to second-order statistics based on the grey level co-occurrence matrix (GLCM), which has been extensively used for various image processing applications. The curvelet transform has a more sparse representation of the image than wavelet, thus offering a description with higher time frequency resolution and high degree of directionality and anisotropy, which is particularly appropriate for many images rich with edges and curves. A combined feature description from Haralick feature and curvelet transform can further increase the accuracy of classification by taking their complementary information. We then investigate the applicability of the random subspace (RS) ensemble method for phenotype classification based on microscopy images. A base classifier is trained with a RS sampled subset of the original feature set and the ensemble assigns a class label by majority voting.
Results
Experimental results on the phenotype recognition from three benchmarking image sets including HeLa, CHO and RNAi show the effectiveness of the proposed approach. The combined feature is better than any individual one in the classification accuracy. The ensemble model produces better classification performance compared to the component neural networks trained. For the three images sets HeLa, CHO and RNAi, the Random Subspace Ensembles offers the classification rates 91.20%, 98.86% and 91.03% respectively, which compares sharply with the published result 84%, 93% and 82% from a multi-purpose image classifier WND-CHARM which applied wavelet transforms and other feature extraction methods. We investigated the problem of estimation of ensemble parameters and found that satisfactory performance improvement could be brought by a relative medium dimensionality of feature subsets and small ensemble size.
Conclusions
The characteristics of curvelet transform of being multiscale and multidirectional suit the description of microscopy images very well. It is empirically demonstrated that the curvelet-based feature is clearly preferred to wavelet-based feature for bioimage descriptions. The random subspace ensemble of MLPs is much better than a number of commonly applied multi-class classifiers in the investigated application of phenotype recognition.
doi:10.1186/1471-2105-12-128
PMCID: PMC3098787  PMID: 21529372
13.  Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets 
BMC Systems Biology  2010;4:84.
Background
RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis.
Results
In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes.
Conclusions
We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.
doi:10.1186/1752-0509-4-84
PMCID: PMC2904735  PMID: 20550706
14.  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.
Author Summary
RNA interference (RNAi) is a technique to selectively suppress mRNA of individual genes and, consequently, their cognate proteins. RNAi using double-stranded (ds) RNA has been used to interrogate the function of mainly single genes in the flatworm, Schistosoma mansoni, one of a number of schistosome species causing schistosomiasis. In consideration of large-scale screens to identify candidate drug targets, we examined the selectivity and sensitivity (the degree of suppression) of RNAi for 11 genes produced in different tissues of the parasite: the gut, tegument (surface) and otherwise. We used the schistosomulum stage prepared from infective cercariae larvae which are accessible in large numbers and adaptable to automated screening platforms. We found that RNAi suppresses transcripts selectively, however, the sensitivity of suppression varies (40%–>75%). No obvious changes in the parasite occurred post-RNAi, including after targeting the mRNA of genes that had been computationally predicted to be essential for survival. Additionally, we defined operational parameters to facilitate large-scale RNAi, including choice of culture medium, transfection strategy to deliver dsRNA, dose- and time-dependency, and dosing limits. Finally, using fluorescent probes, we show that the developing gut allows rapid entrance of dsRNA into the parasite to initiate RNAi.
doi:10.1371/journal.pntd.0000850
PMCID: PMC2957409  PMID: 20976050
15.  RNAi–Based Functional Profiling of Loci from Blood Lipid Genome-Wide Association Studies Identifies Genes with Cholesterol-Regulatory Function 
PLoS Genetics  2013;9(2):e1003338.
Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease. However, GWAS only rarely reveal information on the exact genetic elements and pathogenic events underlying an association. In order to extract functional information from genomic data, strategies for systematic follow-up studies on a phenotypic level are required. Here we address these limitations by applying RNA interference (RNAi) to analyze 133 candidate genes within 56 loci identified by GWAS as associated with blood lipid levels, coronary artery disease, and/or myocardial infarction for a function in regulating cholesterol levels in cells. Knockdown of a surprisingly high number (41%) of trait-associated genes affected low-density lipoprotein (LDL) internalization and/or cellular levels of free cholesterol. Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions. Using a set of secondary assays we demonstrate for a number of genes without previously known lipid-regulatory roles (e.g. CXCL12, FAM174A, PAFAH1B1, SEZ6L, TBL2, WDR12) that knockdown correlates with altered LDL–receptor levels and/or that overexpression as GFP–tagged fusion proteins inversely modifies cellular cholesterol levels. By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci.
Author Summary
Complex traits and diseases are assumed to result from interactions between multiple genes in relevant biological processes. Recent genome-wide association studies have uncovered many novel genomic loci where genes with functional significance are expected. However, functional validation of such genes has thus far remained confined to single gene approaches. Here, we use RNA interference and high-content screening microscopy to profile 133 genes at 56 loci associated with blood lipid traits, cardiovascular disease, and/or myocardial infarction for a function in regulating cellular free cholesterol levels and the efficiency of low-density lipoprotein uptake. Our results suggest that a high number of trait-associated genes have conserved cholesterol-regulatory functions in cells, with several GWAS loci harboring more than one gene of likely functional significance. For a number of genes without previously known lipid-regulatory functions, consequences upon siRNA knockdown positively correlated with cellular levels of LDL receptor, a major determinant of blood LDL levels. Moreover, GFP–tagged fusion proteins of several candidates shifted cellular cholesterol levels to inverse directions than knockdown, and subcellular localization of some candidates was sterol-dependent. Our study generates a valuable resource for prioritization of lipid-trait/CAD/MI-associated genes for future in-depth mechanistic analyses and introduces cell-based RNAi as a scalable and unbiased tool for functional follow-up of GWAS loci.
doi:10.1371/journal.pgen.1003338
PMCID: PMC3585126  PMID: 23468663
16.  A novel phenotypic dissimilarity method for image-based high-throughput screens 
BMC Bioinformatics  2013;14:336.
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.
doi:10.1186/1471-2105-14-336
PMCID: PMC4225524  PMID: 24256072
Phenotypic dissimilarity; Image-based high-throughput screening; High-content screening; RNAi; Gene networks
17.  Characterizing Protein Interactions Employing a Genome-Wide siRNA Cellular Phenotyping Screen 
PLoS Computational Biology  2014;10(9):e1003814.
Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest.
Author Summary
Mathematical models which aim to describe cellular signaling start from constructing an interaction network of effectors, mediators and their effected target proteins. Several developments came up making it easier to put these links together. Besides tediously assembling knowledge from textbooks and research articles, experimental high-throughput methods were established like Yeast-2-Hybrid assays or Fluorescence Emission Resonance Transfer. However, these methods do not elucidate the effect of such interactions. We aimed inferring if an interaction in a specific cellular context is rather activating or inhibiting. We used cellular phenotypes of a genome-wide RNAi knockdown screen of live cells to identify such activating and inhibiting effects of protein interactions. The rationale behind it is that activating protein interactions should lead to similar phenotypes when their respective genes are knocked down, whereas an inhibiting protein interaction should lead to dissimilar phenotypes. Exemplarily, we applied our method to a phenotype screen of perturbed HeLa cells. Our predictions effectively reproduced textbook relationships between proteins or domains when comparing the predicted effects with pairs of effectors, receptors, kinases, phosphatases and of general signalling modules. The presented computational approach is generic and may enable elucidating the effects of studied interactions also of other cellular systems under more specific conditions.
doi:10.1371/journal.pcbi.1003814
PMCID: PMC4178005  PMID: 25255318
18.  Feasibility, Yield, and Cost of Active Tuberculosis Case Finding Linked to a Mobile HIV Service in Cape Town, South Africa: A Cross-sectional Study 
PLoS Medicine  2012;9(8):e1001281.
Katharina Kranzer and colleagues investigate the operational characteristics of an active tuberculosis case-finding service linked to a mobile HIV testing unit that operates in underserviced areas in Cape Town, South Africa.
Background
The World Health Organization is currently developing guidelines on screening for tuberculosis disease to inform national screening strategies. This process is complicated by significant gaps in knowledge regarding mass screening. This study aimed to assess feasibility, uptake, yield, treatment outcomes, and costs of adding an active tuberculosis case-finding program to an existing mobile HIV testing service.
Methods and Findings
The study was conducted at a mobile HIV testing service operating in deprived communities in Cape Town, South Africa. All HIV-negative individuals with symptoms suggestive of tuberculosis, and all HIV-positive individuals regardless of symptoms were eligible for participation and referred for sputum induction. Samples were examined by microscopy and culture. Active tuberculosis case finding was conducted on 181 days at 58 different sites. Of the 6,309 adults who accessed the mobile clinic, 1,385 were eligible and 1,130 (81.6%) were enrolled. The prevalence of smear-positive tuberculosis was 2.2% (95% CI 1.1–4.0), 3.3% (95% CI 1.4–6.4), and 0.4% (95% CI 1.4 015–6.4) in HIV-negative individuals, individuals newly diagnosed with HIV, and known HIV, respectively. The corresponding prevalence of culture-positive tuberculosis was 5.3% (95% CI 3.5–7.7), 7.4% (95% CI 4.5–11.5), 4.3% (95% CI 2.3–7.4), respectively. Of the 56 new tuberculosis cases detected, 42 started tuberculosis treatment and 34 (81.0%) completed treatment. The cost of the intervention was US$1,117 per tuberculosis case detected and US$2,458 per tuberculosis case cured. The generalisability of the study is limited to similar settings with comparable levels of deprivation and TB and HIV prevalence.
Conclusions
Mobile active tuberculosis case finding in deprived populations with a high burden of HIV and tuberculosis is feasible, has a high uptake, yield, and treatment success. Further work is now required to examine cost-effectiveness and affordability and whether and how the same results may be achieved at scale.
Editors' Summary
Background
In 2010, 8.8 million people developed active tuberculosis—a contagious bacterial infection—and 1.4 million people died from the disease. Most of these deaths were in low- and middle-income countries and a quarter were in HIV-positive individuals—people who are infected with HIV, the virus that causes AIDS, are particularly susceptible to tuberculosis because of their weakened immune system. Tuberculosis is caused by Mycobacterium tuberculosis, which is spread in airborne droplets when people with the disease cough or sneeze. Its characteristic symptoms are a persistent cough, unintentional weight loss, hemoptysis (coughing up blood from the lungs), fever, and night sweats. Diagnostic tests for tuberculosis include sputum smear microscopy (microscopic analysis of mucus brought up from the lungs by coughing) and culture (growth) of M. tuberculosis from sputum samples. Tuberculosis can be cured by taking several powerful antibiotics daily for at least 6 months.
Why Was This Study Done?
To improve tuberculosis control, active disease must be diagnosed quickly and treated immediately. Passive tuberculosis case finding, which relies on people seeking medical help because they feel unwell, delays the diagnosis and treatment of tuberculosis and increases M. tuberculosis transmission. By contrast, active tuberculosis case finding—where health workers seek out and diagnose individuals with TB who have not sought care on their own initiative—has the potential to reduce tuberculosis transmission by improving case detection. The World Health Organization (WHO), which already recommends active tuberculosis case finding in HIV-infected individuals as part of its HIV/TB “Three I's” strategy, is currently developing guidelines to inform the design of national tuberculosis screening strategies based on the local prevalence of HIV and TB and other context-specific factors that affect how many individuals need to be screened to identify each additional new tuberculosis case (the “yield” of active case finding). Large gaps in our knowledge about mass-screening strategies are complicating the development of these guidelines so, in this observational prospective study, the researchers assess the feasibility, uptake, yield, treatment outcomes, and costs of adding an active tuberculosis case-finding program to an existing mobile HIV testing service in South Africa.
What Did the Researchers Do and Find?
All HIVnegative adults with symptoms characteristic of tuberculosis and all HIV-positive adults regardless of symptoms who attended a mobile HIV testing service operating in deprived communities in ape Town, South Africa between May 2009 and February 2011 were eligible for inclusion in the study. Of the 6,309 adults who accessed the mobile clinic during this period, 1,385 met these eligibility criteria, and 1,130 were enrolled and referred for the collection of sputum samples, which were analyzed by microscopy and culture. The prevalence of smear-positive tuberculosis was 2.2%, 3.3%, and 0.4% among HIV-negative study participants, newly diagnosed HIV-positive participants, and people already known to have HIV, respectively. The corresponding prevalences for smear-negative/culture-positive tuberculosis were 5.3%, 7.4%, and 4.3%, respectively (culture detects more tuberculosis cases than microscopy but, whereas microscopy can provide a result within 1–2 days, culture can take several weeks). Fifty-six new tuberculosis cases were identified, 42 people started tuberculosis treatment, and 34 completed treatment (a treatment success rate of 81%). Finally, the incremental cost of the intervention was US$1,117 per tuberculosis case detected and US$2,458 per tuberculosis case cured.
What Do These Findings Mean?
These findings show that active case finding for tuberculosis delivered through a mobile HIV testing service is feasible and has a high uptake, yield and treatment success in deprived communities with a high prevalence of HIV and tuberculosis. The findings also highlight the challenges faced by mobile population-based services such as losses between tuberculosis diagnosis and treatment, which were greatest for smear-negative/culture-positive people who were more difficult to contact than smear-positive people because of the greater time lag between sputum collection and diagnosis. Because the study was done in a single city, these findings need to be confirmed in other settings—the yield of active tuberculosis case finding reported here, for example, is not likely to be generalizable to countries that rely on sputum smears for tuberculosis diagnosis. Finally, given that the incremental cost per case treated in this study is 3-fold higher than the incremental cost per case treated under passive case detection in South Africa, further studies are needed to determine the cost-effectiveness and affordability of population-based tuberculosis screening.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001281.
The World Health Organization provides information on all aspects of tuberculosis, including information on tuberculosis and HIV, and on the Three I?s for HIV/TB (some information is in several languages); details of a 2011 meeting on the development of guidelines on screening for active tuberculosis are available
The Stop TB partnership is working towards tuberculosis elimination; patient stories about tuberculosis/HIV coinfection are available
The US Centers for Disease Control and Prevention has information about tuberculosis, about tuberculosis and HIV co-infection, and about the diagnosis of tuberculosis disease
The US National Institute of Allergy and Infectious Diseases also has detailed information on all aspects of tuberculosis
MedlinePlus has links to further information about tuberculosis (in English and Spanish)
The Tuberculosis Survival Project, which aims to raise awareness of tuberculosis and provide support for people with tuberculosis, provides personal stories about treatment for tuberculosis; the Tuberculosis Vaccine Initiative also provides personal stories about dealing with tuberculosis
doi:10.1371/journal.pmed.1001281
PMCID: PMC3413719  PMID: 22879816
19.  IFN-γ production in response to in vitro stimulation with collagen type II in rheumatoid arthritis is associated with HLA-DRB1*0401 and HLA-DQ8 
Arthritis Research  1999;2(1):75-84.
IFN-γ was measured in supernatants after in vitro stimulation of peripheral blood mononuclear cells with collagen type II (CII), purified protein derivative or influenza virus. IFN-γ production in response to CII was similar in rheumatoid arthritis (RA) patients and healthy control individuals. The IFN-γ response to purified protein derivative and influenza virus was lower in RA patients, reflecting a general T-cell hyporesponsiveness in RA. After recalculating the response to CII taking this hyporesponsiveness into account the CII response was higher in RA patients, and was associated with human leucocyte antigen (HLA)-DRB1*0401 and HLA-DQA1*0301-DQB1*0302 (HLA-DQ8). Rheumatoid arthritis patients with elevated serum levels of immunoglobulin (Ig)G anti-CII antibodies had lower CII-induced IFN-γ production than patients with low anti-CII levels. The relative increase in CII-reactivity in RA patients as compared with healthy control individuals, and the association of a higher response with RA-associated HLA haplotypes, suggest the existence of a potentially pathogenic cellular reactivity against CII in RA.
Introduction:
Despite much work over past decades, whether antigen-specific immune reactions occur in rheumatoid arthritis (RA) and to what extent such reactions are directed towards joint-specific autoantigens is still questionable. One strong indicator for antigenic involvement in RA is the fact that certain major histocompatibility complex (MHC) class II genotypes [human leucocyte antigen (HLA)-DR4 and HLA-DR1] predispose for the development of the disease [1]. In the present report, collagen type II (CII) was studied as a putative autoantigen on the basis of both clinical and experimental data that show an increased frequency of antibodies to CII in RA patients [2,3,4] and that show that CII can induce experimental arthritis [5].
It is evident from the literature that RA peripheral blood mononuclear cells (PBMCs) respond poorly to antigenic stimulation [6,7,8], and in particular evidence for a partial tolerization to CII has been presented [9]. The strategy of the present work has accordingly been to reinvestigate T-cell reactivity to CII in RA patients, to relate it to the response to commonly used recall antigens and to analyze IFN-γ responses as an alternative to proliferative responses.
Aims:
To study cellular immune reactivity to CII in patients with RA and in healthy control individuals and to correlate this reactivity to HLA class II genotypes and to the presence of antibodies to CII in serum.
Methods:
Forty-five patients who met the 1987 American College of Rheumatology classification criteria for RA [10] and 25 healthy control individuals of similar age and sex were included. Twenty-six of these patients who had low levels of anti-CII in serum were randomly chosen, whereas 19 patients with high anti-CII levels were identified by enzyme-linked immunosorbent assay (ELISA)-screening of 400 RA sera.
Heparinized blood was density gradient separated and PBMCs were cultured at 1 × 106/ml in RPMI-10% fetal calf serum with or without antigenic stimulation: native or denatured CII (100 μ g/ml), killed influenza virus (Vaxigrip, Pasteur Mérieux, Lyon, France; diluted 1 : 1000) or purified protein derivative (PPD; 10 μ g/ml). CII was heat-denatured in 56°C for 30 min.
Cell supernatants were collected after 7days and IFN-γ contents were analyzed using ELISA. HLA-DR and HLA-DQ genotyping was performed utilizing a polymerase chain reaction-based technique with sequence-specific oligonucleotide probe hybridization. Nonparametric statistical analyses were utilized throughout the study.
Results:
PBMCs from both RA patients and healthy control individuals responded with inteferon-γ production to the same degree to stimulation with native and denatured CII (Fig. 1a), giving median stimulation indexes with native CII of 4.6 for RA patients and 5.4 for healthy control individuals, and with denatured CII of 2.9 for RA patients and 2.6 for healthy control individuals. RA patients with elevated levels of anti-CII had a weaker IFN-γ response to both native and denatured CII than did healthy control individuals (P = 0.02 and 0.04, respectively).
Stimulation with the standard recall antigens PPD and killed influenza virus yielded a median stimulation index with PPD of 10.0 for RA patients and 51.3 for healthy control individuals and with influenza of 12.3 for RA patients and 25.7 for healthy, control individuals. The RA patients displayed markedly lower responsiveness to both PPD and killed influenza virus than did healthy control individuals (Fig. 1b). IFN-γ responses to all antigens were abrogated when coincubating with antibodies blocking MHC class II.
The low response to PPD and killed influenza virus in RA patients relative to that of healthy control individuals reflects a general downregulation of antigen-induced responsiveness of T cells from RA patients [6,7,8]. That no difference between the RA group and the control group was recorded in CII-induced IFN-γ production therefore indicates that there may be an underlying increased responsiveness to CII in RA patients, which is obscured by the general downregulation of T-cell responsiveness in these patients. In order to address this possibility, we calculated the fraction between individual values for the CII-induced IFN-γ production and the PPD-induced and killed influenza virus-induced IFN-γ production, and compared these fractions. A highly significant difference between the RA and healthy control groups was apparent after stimulation with both native CII and denatured CII when expressing the response as a fraction of that with PPD (Fig. 2a). Similar data were obtained using killed influenza virus-stimulated IFN-γ values as the denominator (Fig. 2b).
When comparing the compensated IFN-γ response to denatured CII stimulation between RA patients with different HLA genotypes, highly significant differences were evident, with HLA-DRB1*0401 patients having greater CII responsiveness than patients who lacked this genotype (Fig. 3a). HLA-DQ8 positive patients also displayed a high responsiveness to CII as compared with HLA-DQ8 negative RA patients (Fig. 3b). These associations between the relative T-cell reactivity to denatured CII and HLA class II genotypes were not seen in healthy control individuals. Similar results were achieved using influenza as denominator (P = 0.02 for HLA-DRB1*0401 and P = 0.01 for HLA-DQ8).
Discussion:
No reports have previously systematically taken the general T-cell hyporesponsiveness in RA into account when investigating specific T-cell responses in this disease. In order to address this issue we used the T-cell responses to PPD and killed influenza virus as reference antigens. This was made on the assumption that exposure to these antigens is similar in age-matched and sex-matched groups of RA patients and healthy control individuals. The concept of a general hyporesponsiveness in RA T cells has been documented in several previous reports, in which both nominal antigens [6,7,8] and mitogens [11,12,13] have been used. The fact that a similar functional downregulation in RA PBMCs was obtained with both PPD and killed influenza virus as reference antigens strengthens the validity of our approach.
We identified an association between the IFN-γ response to CII and HLA-DRB1*0401 and HLA-DQ8 in the RA patient group, which is of obvious interest because both these MHC class II alleles have been associated with high responsiveness to CII in transgenic mice that express these human MHC class II molecules [14,15]. There was no association between high anti-CII levels and shared epitope (HLA-DRB1*0401 or HLA-DRB1*0404).
Conclusion:
CII, a major autoantigen candidate in RA, can elicit an IFN-γ response in vitro that is associated with HLA-DRB1*0401 and HLA-DQ8 in RA patients. This study, with a partly new methodological approach to a classical problem in RA, has provided some additional support to the notion that CII may be a target autoantigen of importance for a substantial group of RA patients. Continued efforts to identify mechanisms behind the general hyporesponsiveness to antigens in RA, as well as the mechanisms behind the potential partial anergy to CII, may provide us with better opportunities to study the specificity and pathophysiological relevance of anti-CII reactivity in RA.
PMCID: PMC17806  PMID: 11219392
collagen type II; human leucocyte antigen-DR; IFN-γ; rheumatoid arthritis; T cell
20.  Lyapunov exponents and phase diagrams reveal multi-factorial control over TRAIL-induced apoptosis 
Kinetic modeling, phase diagrams analysis, and quantitative single-cell experiments are combined to investigate how multiple factors, including the XIAP:caspase-3 ratio and ligand concentration, regulate receptor-mediated apoptosis.
Based on protein expression levels, Lyapunov-based phase diagrams predict which pathways are required for a cell to undergo receptor-mediated cell death.Multiple inter-dependent factors, including the XIAP:caspase-3 ratio and ligand concentration, regulate the requirement for mitochondrial outer membrane permeabilization during receptor-mediated apoptosis.The E3 ubiquitin ligase activity of XIAP is essential for maintaining the ‘snap-action' regulation of effector caspase activity.Cell-to-cell variability in protein expression gives rise to mixed phenotypes in cell lines that map close to boundaries (separatrices) identified by Lyapunov exponent analysis.
In mammalian cells, extrinsic (receptor-mediated) apoptosis is triggered by binding of extracellular death ligands such as tumor necrosis factor (TNF) and TRAIL (TNF-related apoptosis-inducing ligand) to cognate receptors. When death receptors are activated, death inducing signaling complexes (DISCs) assemble causing activation and cleavage of initiator pro-caspases-8 and -10, which then cleave effector pro-caspases-3 and -7 in a multi-enzyme cascade (Riedl and Shi, 2004). Active effector caspases digest essential cellular proteins and activate the CAD nucleases that cleave genomic DNA, thereby killing cells. This cascade of DISC assembly followed by initiator and then effector caspase activation is sufficient to kill so-called type I cells (e.g. B lymphocytes), but most cell types exhibit a type II behavior in which mitochondrial outer membrane permeabilization (MOMP) is an essential step in the march to death (Scaffidi et al, 1998; Barnhart et al, 2003; Letai, 2008). Identifying factors that determine whether cells are type I or II is of practical and theoretical interest. From a practical perspective, whether a cell requires MOMP for apoptosis determines the potency of Bcl2 and similar oncogenes, the efficacy of anti-Bcl2 drugs such as navitoclax (ABT-263), and the sensitivity of cells to TRAIL and anti-TRAIL receptor antibodies, which are also investigational anti-cancer drugs (Newsom-Davis et al, 2009). From a theoretical perspective, the type I versus II choice exemplifies a common situation in mammalian cells in which overlapping signaling pathways play a greater or lesser role in controlling cell fate depending on cell type: it is remarkable that a simple three-step (receptor→initiator caspase→effector caspase) process is sufficient to trigger apoptosis in some cell types but that a much more complex route involving MOMP is required in others.
Attempts to understand why some cells require MOMP for cell death and others do not have identified differences in the oligomeric state of death ligand receptors and the efficiency of DISC formation as important variables. In cells in which DISCs form efficiently, initiator caspases are cleaved rapidly and sufficient effector pro-caspases are processed into their active forms to kill cells (type I cells; Scaffidi et al, 1999b). In type II cells, DISC formation seems to be less efficient, and it has been proposed that MOMP is required to amplify weak initiator caspase signals and thereby generate lethal effector caspase levels (Barnhart et al, 2003). However, it has recently become apparent that XIAP also plays a role in type I versus II choice: in XIAP knockout mice, liver cells switch from a type II to a type I phenotype (Jost et al, 2009) and XIAP is observed to be involved in the survival of type I cells treated with death ligands in culture (Maas et al, 2010).
In this paper, we attempt to place these observations in a quantitative context by analyzing a computational model of extrinsic cell death using a method drawn from dynamical system analysis, direct finite-time Lyapunov exponent (DLE) analysis. Our implementation of DLE analysis relates changes in the concentrations of protein in a model to an outcome several hours later. We computed DLEs for six regulators of apoptosis over a range of concentrations determined experimentally to represent a natural range of variation in parental or genetically modified tumor cell lines. This generated a phase space onto which individual cell lines could be mapped using quantitative immunoblotting data. Cell-to-cell variation was estimated by flow cytometry and also mapped onto the phase space. The most interesting regions of the space were those in which a small change in one or more initial protein concentration resulted in a dramatic change in phenotype. Such a boundary or separatrix was observed in slices of phase space corresponding XIAP versus pro-caspase-3 concentration (the [XIAP]:[caspase-3] ratio). In cells in which the ratio is low, a type I phenotype is predicted to occur; when the ratio is high, a type II phenotype is favored; and in cell lines that lie close to the separatrix, cell-to-cell variability is expected, with some cells exhibiting a type I phenotype and others a type II behavior. DLE analysis shows that the [XIAP]:[caspase-3] ratio is not the only controlling factor in type I versus II control: as receptor activity or ligand concentration increase, the position of the separatrix changes so as to expand the region in which the type I phenotype is favored.
We tested these predictions by manipulating XIAP and ligand levels in multiple cell lines and then followed cell death by imaging, flow cytometry, or clonogenic assays. We observed that when XIAP was knocked out (by homologous recombination) in the HCT116 colorectal cancer line, cells shifted from a pure type II to a type I phenotype, as predicted from the DLE phase diagram. SKW6.4 B-cell lymphoma cells were predicted to lie at a position in phase space that is insensitive to XIAP levels (within the range achievable by over-expression) and we confirmed this experimentally. Finally, T47D breast cancer cells were predicted—and observed—to straddle the separatrix and to exhibit cell-to-cell variability in fate, with some cells showing a type I and others a type II phenotype. As the concentration of TRAIL was increased, the ratio of type I to type II T47D cells increased, confirming the prediction that this ratio is controlled in a multi-factorial manner.
To extend our approach to mutations that change protein activity rather than protein level, we simulated the effects of changing rate constants that control ubiquitylation of caspase-3 following its binding to XIAP. We generated cells carrying a truncated form of XIAP that lacks the RING domain (XIAPΔRING) and cannot mediate the ubiquitylation of caspase-3 (this truncation leaves the affinity of XIAP for caspase-3 unchanged). We predicted and demonstrated experimentally that expression of XIAPΔRING disrupts normal snap-action control over caspase-3 activation. Our findings not only advance understanding of extrinsic apoptosis but also constitute a proof of principle for an approach to quantitative modeling of dynamic regulatory processes in diverse cell types.
Receptor-mediated apoptosis proceeds via two pathways: one requiring only a cascade of initiator and effector caspases (type I behavior) and the second requiring an initiator–effector caspase cascade and mitochondrial outer membrane permeabilization (type II behavior). Here, we investigate factors controlling type I versus II phenotypes by performing Lyapunov exponent analysis of an ODE-based model of cell death. The resulting phase diagrams predict that the ratio of XIAP to pro-caspase-3 concentrations plays a key regulatory role: type I behavior predominates when the ratio is low and type II behavior when the ratio is high. Cell-to-cell variability in phenotype is observed when the ratio is close to the type I versus II boundary. By positioning multiple tumor cell lines on the phase diagram we confirm these predictions. We also extend phase space analysis to mutations affecting the rate of caspase-3 ubiquitylation by XIAP, predicting and showing that such mutations abolish all-or-none control over activation of effector caspases. Thus, phase diagrams derived from Lyapunov exponent analysis represent a means to study multi-factorial control over a complex biochemical pathway.
doi:10.1038/msb.2011.85
PMCID: PMC3261706  PMID: 22108795
apoptosis; caspases; dynamical systems analysis; kinetic modeling; XIAP
21.  A Systematic Analysis of Host Factors Reveals a Med23-Interferon-λ Regulatory Axis against Herpes Simplex Virus Type 1 Replication 
PLoS Pathogens  2013;9(8):e1003514.
Herpes simplex virus type 1 (HSV-1) is a neurotropic virus causing vesicular oral or genital skin lesions, meningitis and other diseases particularly harmful in immunocompromised individuals. To comprehensively investigate the complex interaction between HSV-1 and its host we combined two genome-scale screens for host factors (HFs) involved in virus replication. A yeast two-hybrid screen for protein interactions and a RNA interference (RNAi) screen with a druggable genome small interfering RNA (siRNA) library confirmed existing and identified novel HFs which functionally influence HSV-1 infection. Bioinformatic analyses found the 358 HFs were enriched for several pathways and multi-protein complexes. Of particular interest was the identification of Med23 as a strongly anti-viral component of the largely pro-viral Mediator complex, which links specific transcription factors to RNA polymerase II. The anti-viral effect of Med23 on HSV-1 replication was confirmed in gain-of-function gene overexpression experiments, and this inhibitory effect was specific to HSV-1, as a range of other viruses including Vaccinia virus and Semliki Forest virus were unaffected by Med23 depletion. We found Med23 significantly upregulated expression of the type III interferon family (IFN-λ) at the mRNA and protein level by directly interacting with the transcription factor IRF7. The synergistic effect of Med23 and IRF7 on IFN-λ induction suggests this is the major transcription factor for IFN-λ expression. Genotypic analysis of patients suffering recurrent orofacial HSV-1 outbreaks, previously shown to be deficient in IFN-λ secretion, found a significant correlation with a single nucleotide polymorphism in the IFN-λ3 (IL28b) promoter strongly linked to Hepatitis C disease and treatment outcome. This paper describes a link between Med23 and IFN-λ, provides evidence for the crucial role of IFN-λ in HSV-1 immune control, and highlights the power of integrative genome-scale approaches to identify HFs critical for disease progression and outcome.
Author Summary
Herpes simplex virus type 1 (HSV-1) infects the vast majority of the global population. Whilst most people experience the relatively mild symptoms of cold sores, some individuals suffer more serious diseases like viral meningitis and encephalitis. HSV-1 is also becoming more common as a cause of genital herpes, traditionally associated with HSV-2 infection. Co-infection with HSV-2 is a major contributor to HIV transmission, so a better understanding of HSV-1/HSV-2 disease has wide implications for global healthcare. After initial infection, all herpesviruses have the ability to remain dormant, and can awaken to cause a symptomatic infection at any stage. Whether the virus remains dormant or active is the result of a finely tuned balance between our immune system and evasion techniques developed by the virus. In this study we have found a new method by which the replication of the virus is counteracted. The cellular protein Med23 was found to actively induce an innate anti-viral immune response in the form of the Type III interferons (IFN-lambda), by binding IRF7, a key regulator of interferons, and modulating its activity. Interferon lambda is well known to be important in the control of Hepatitis C infection, and a genetic mutation correlating to an increase in interferon lambda levels is strongly linked to clearance of infection. Here we find the same association between this genetic mutation and the clinical severity of recurrent cases of HSV-1 infection (coldsores). These data identify a Med23-interferon lambda regulatory axis of innate immunity, show that interferon lambda plays a significant role in HSV-1 infection, and contribute to the expanding evidence for interferon lambda in disease control.
doi:10.1371/journal.ppat.1003514
PMCID: PMC3738494  PMID: 23950709
22.  A protein network-guided screen for cell cycle regulators in Drosophila 
BMC Systems Biology  2011;5:65.
Background
Large-scale RNAi-based screens are playing a critical role in defining sets of genes that regulate specific cellular processes. Numerous screens have been completed and in some cases more than one screen has examined the same cellular process, enabling a direct comparison of the genes identified in separate screens. Surprisingly, the overlap observed between the results of similar screens is low, suggesting that RNAi screens have relatively high levels of false positives, false negatives, or both.
Results
We re-examined genes that were identified in two previous RNAi-based cell cycle screens to identify potential false positives and false negatives. We were able to confirm many of the originally observed phenotypes and to reveal many likely false positives. To identify potential false negatives from the previous screens, we used protein interaction networks to select genes for re-screening. We demonstrate cell cycle phenotypes for a significant number of these genes and show that the protein interaction network is an efficient predictor of new cell cycle regulators. Combining our results with the results of the previous screens identified a group of validated, high-confidence cell cycle/cell survival regulators. Examination of the subset of genes from this group that regulate the G1/S cell cycle transition revealed the presence of multiple members of three structurally related protein complexes: the eukaryotic translation initiation factor 3 (eIF3) complex, the COP9 signalosome, and the proteasome lid. Using a combinatorial RNAi approach, we show that while all three of these complexes are required for Cdk2/Cyclin E activity, the eIF3 complex is specifically required for some other step that limits the G1/S cell cycle transition.
Conclusions
Our results show that false positives and false negatives each play a significant role in the lack of overlap that is observed between similar large-scale RNAi-based screens. Our results also show that protein network data can be used to minimize false negatives and false positives and to more efficiently identify comprehensive sets of regulators for a process. Finally, our data provides a high confidence set of genes that are likely to play key roles in regulating the cell cycle or cell survival.
doi:10.1186/1752-0509-5-65
PMCID: PMC3113730  PMID: 21548953
23.  High-throughput RNA interference screens integrative analysis: Towards a comprehensive understanding of the virus-host interplay 
World Journal of Virology  2013;2(2):18-31.
Viruses are extremely heterogeneous entities; the size and the nature of their genetic information, as well as the strategies employed to amplify and propagate their genomes, are highly variable. However, as obligatory intracellular parasites, replication of all viruses relies on the host cell. Having co-evolved with their host for several million years, viruses have developed very sophisticated strategies to hijack cellular factors that promote virus uptake, replication, and spread. Identification of host cell factors (HCFs) required for these processes is a major challenge for researchers, but it enables the identification of new, highly selective targets for anti viral therapeutics. To this end, the establishment of platforms enabling genome-wide high-throughput RNA interference (HT-RNAi) screens has led to the identification of several key factors involved in the viral life cycle. A number of genome-wide HT-RNAi screens have been performed for major human pathogens. These studies enable first inter-viral comparisons related to HCF requirements. Although several cellular functions appear to be uniformly required for the life cycle of most viruses tested (such as the proteasome and the Golgi-mediated secretory pathways), some factors, like the lipid kinase Phosphatidylinositol 4-kinase IIIα in the case of hepatitis C virus, are selectively required for individual viruses. However, despite the amount of data available, we are still far away from a comprehensive understanding of the interplay between viruses and host factors. Major limitations towards this goal are the low sensitivity and specificity of such screens, resulting in limited overlap between different screens performed with the same virus. This review focuses on how statistical and bioinformatic analysis methods applied to HT-RNAi screens can help overcoming these issues thus increasing the reliability and impact of such studies.
doi:10.5501/wjv.v2.i2.18
PMCID: PMC3785050  PMID: 24175227
RNA interference; High-throughput; Cell population; Dependency factors; Bioinformatics; Human immunodeficiency virus; Hepatitis C virus; Dengue virus; Viral infection; Virus-host interactions
24.  RNAi Screening: New Approaches, Understandings and Organisms 
RNA interference (RNAi) leads to sequence-specific knockdown of gene function. The approach can be used in large-scale screens to interrogate function in various model organisms and an increasing number of other species. Genome-scale RNAi screens are routinely performed in cultured or primary cells or in vivo in organisms such as C. elegans. High-throughput RNAi screening is benefitting from the development of sophisticated new instrumentation and software tools for collecting and analyzing data, including high-content image data. The results of large-scale RNAi screens have already proved useful, leading to new understandings of gene function relevant to topics such as infection, cancer, obesity and aging. Nevertheless, important caveats apply and should be taken into consideration when developing or interpreting RNAi screens. Some level of false discovery is inherent to high-throughput approaches and specific to RNAi screens, false discovery due to off-target effects (OTEs) of RNAi reagents remains a problem. The need to improve our ability to use RNAi to elucidate gene function at large scale and in additional systems continues to be addressed through improved RNAi library design, development of innovative computational and analysis tools and other approaches.
doi:10.1002/wrna.110
PMCID: PMC3249004  PMID: 21953743
RNAi; high-throughput screens; high-content imaging; cell-based assays
25.  A Direct Phenotypic Comparison of siRNA Pools and Multiple Individual Duplexes in a Functional Assay 
PLoS ONE  2009;4(12):e8471.
Background
RNAi is a prominent tool for the identification of novel regulatory elements within complex cellular pathways. In invertebrates, RNAi is a relatively straightforward process, where large double-stranded RNA molecules initiate sequence-specific transcript destruction in target cells. In contrast, RNAi in mammalian cell culture assays requires the delivery of short interfering RNA duplexes to target cells. Due to concerns over off-target phenotypes and extreme variability in duplex efficiency, investigators typically deliver and analyze multiple duplexes per target. Currently, duplexes are delivered and analyzed either individually or as a pool of several independent duplexes. A choice between experiments based on siRNA pools or multiple individual duplexes has considerable implications for throughput, reagent requirements and data analysis in genome-wide surveys, yet there are relatively few data that directly compare the efficiency of the two approaches.
Methodology/Principal Findings
To address this critical issue, we conducted a direct comparison of siRNA pools and multiple single siRNAs that target all human phosphatases in a robust functional assay. We determined the frequency with which both approaches uncover loss-of-function phenotypes and compared the phenotypic severity for siRNA pools and the constituent individual duplexes.
Conclusions/Significance
Our survey indicates that screens with siRNA pools have several significant advantages over identical screens with the corresponding individual siRNA duplexes. Of note, we frequently observed greater phenotypic penetrance for siRNA pools than for the parental individual duplexes. Thus, our data indicate that experiments with siRNA pools have a greater likelihood of generating loss-of-function phenotypes than individual siRNA duplexes.
doi:10.1371/journal.pone.0008471
PMCID: PMC2793519  PMID: 20041186

Results 1-25 (1622678)