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1.  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
2.  Systematic analysis of RNAi reports identifies dismal commonality at gene-level & reveals an unprecedented enrichment in pooled shRNA screens 
RNA interference (RNAi) has opened promising avenues to better understand gene function. Though many RNAi screens report on the identification of genes, very few, if any, have been further studied and validated. Data discrepancy is emerging as one of RNAi main pitfalls. We reasoned that a systematic analysis of lethality-based screens, since they score for cell death, would examine the extent of hit discordance at inter-screen level. To this end, we developed a methodology for literature mining and overlap analysis of several screens using both siRNA and shRNA flavors, and obtained 64 gene lists censoring an initial list of 7,430 nominated genes. We further performed a comparative analysis first at a global level followed by hit re-assessment under much more stringent conditions. To our surprise, none of the hits overlapped across the board even for PLK1, which emerged as a strong candidate in siRNA screens; but only marginally in the shRNA ones. Furthermore, EIF5B emerges as the most common hit only in the shRNA screens. A highly unusual and unprecedented result was the observation that 5,269 out of 6,664 nominated genes (~80%) in the shRNA screens were exclusive to the pooled format, raising concerns as to the merits of pooled screens which qualify hits based on relative depletions, possibly due to multiple integrations per cell, data deconvolution or inaccuracies in intracellular processing causing off-target effects. Without golden standards in place, we would encourage the community to pay more attention to RNAi screening data analysis practices, bearing in mind that it is combinatorial in nature and one active siRNA duplex or shRNA hairpin per gene does not suffice credible hit nomination. Finally, we also would like to caution interpretation of pooled shRNA screening outcomes.
PMCID: PMC3885821  PMID: 23848309
RNAi; shRNA; siRNA; Gene; screening; bioinformatics; analysis; overlap; lethality; essential; PLK1
3.  A Genome-Wide siRNA Screen to Identify Modulators of Insulin Sensitivity and Gluconeogenesis 
PLoS ONE  2012;7(5):e36384.
Background
Hepatic insulin resistance impairs insulin’s ability to suppress hepatic glucose production (HGP) and contributes to the development of type 2 diabetes (T2D). Although the interests to discover novel genes that modulate insulin sensitivity and HGP are high, it remains challenging to have a human cell based system to identify novel genes.
Methodology/Principal Findings
To identify genes that modulate hepatic insulin signaling and HGP, we generated a human cell line stably expressing beta-lactamase under the control of the human glucose-6-phosphatase (G6PC) promoter (AH-G6PC cells). Both beta-lactamase activity and endogenous G6PC mRNA were increased in AH-G6PC cells by a combination of dexamethasone and pCPT-cAMP, and reduced by insulin. A 4-gene High-Throughput-Genomics assay was developed to concomitantly measure G6PC and pyruvate-dehydrogenase-kinase-4 (PDK4) mRNA levels. Using this assay, we screened an siRNA library containing pooled siRNA targeting 6650 druggable genes and identified 614 hits that lowered G6PC expression without increasing PDK4 mRNA levels. Pathway analysis indicated that siRNA-mediated knockdown (KD) of genes known to positively or negatively affect insulin signaling increased or decreased G6PC mRNA expression, respectively, thus validating our screening platform. A subset of 270 primary screen hits was selected and 149 hits were confirmed by target gene KD by pooled siRNA and 7 single siRNA for each gene to reduce G6PC expression in 4-gene HTG assay. Subsequently, pooled siRNA KD of 113 genes decreased PEPCK and/or PGC1alpha mRNA expression thereby demonstrating their role in regulating key gluconeogenic genes in addition to G6PC. Last, KD of 61 of the above 113 genes potentiated insulin-stimulated Akt phosphorylation, suggesting that they suppress gluconeogenic gene by enhancing insulin signaling.
Conclusions/Significance
These results support the proposition that the proteins encoded by the genes identified in our cell-based druggable genome siRNA screen hold the potential to serve as novel pharmacological targets for the treatment of T2D.
doi:10.1371/journal.pone.0036384
PMCID: PMC3348929  PMID: 22590537
4.  A Whole-Genome RNA Interference Screen for Human Cell Factors Affecting Myxoma Virus Replication 
Journal of Virology  2013;87(8):4623-4641.
Myxoma virus (MYXV) provides an important model for investigating host-pathogen interactions. Recent studies have also highlighted how mutations in transformed human cells can expand the host range of this rabbit virus. Although virus growth depends upon interactions between virus and host proteins, the nature of these interactions is poorly understood. To address this matter, we performed small interfering RNA (siRNA) screens for genes affecting MYXV growth in human MDA-MB-231 cells. By using siRNAs targeting the whole human genome (21,585 genes), a subset of human phosphatases and kinases (986 genes), and also a custom siRNA library targeting selected statistically significant genes (“hits”) and nonsignificant genes (“nonhits”) of the whole human genome screens (88 genes), we identified 711 siRNA pools that promoted MYXV growth and 333 that were inhibitory. Another 32 siRNA pools (mostly targeting the proteasome) were toxic. The overall overlap in the results was about 25% for the hits and 75% for the nonhits. These pro- and antiviral genes can be clustered into pathways and related groups, including well-established inflammatory and mitogen-activated protein kinase pathways, as well as clusters relating to β-catenin and the Wnt signaling cascade, the cell cycle, and cellular metabolism. The validity of a subset of these hits was independently confirmed. For example, treating cells with siRNAs that might stabilize cells in G1, or inhibit passage into S phase, stimulated MYXV growth, and these effects were reproduced by trapping cells at the G1/S boundary with an inhibitor of cyclin-dependent kinases 4/6. By using 2-deoxy-d-glucose and plasmids carrying the gene for phosphofructokinase, we also confirmed that infection is favored by aerobic glycolytic metabolism. These studies provide insights into how the growth state and structure of cells affect MYXV growth and how these factors might be manipulated to advantage in oncolytic virus therapy.
doi:10.1128/JVI.02617-12
PMCID: PMC3624348  PMID: 23408614
5.  Simultaneous analysis of large-scale RNAi screens for pathogen entry 
BMC Genomics  2014;15(1):1162.
Background
Large-scale RNAi screening has become an important technology for identifying genes involved in biological processes of interest. However, the quality of large-scale RNAi screening is often deteriorated by off-targets effects. In order to find statistically significant effector genes for pathogen entry, we systematically analyzed entry pathways in human host cells for eight pathogens using image-based kinome-wide siRNA screens with siRNAs from three vendors. We propose a Parallel Mixed Model (PMM) approach that simultaneously analyzes several non-identical screens performed with the same RNAi libraries.
Results
We show that PMM gains statistical power for hit detection due to parallel screening. PMM allows incorporating siRNA weights that can be assigned according to available information on RNAi quality. Moreover, PMM is able to estimate a sharedness score that can be used to focus follow-up efforts on generic or specific gene regulators. By fitting a PMM model to our data, we found several novel hit genes for most of the pathogens studied.
Conclusions
Our results show parallel RNAi screening can improve the results of individual screens. This is currently particularly interesting when large-scale parallel datasets are becoming more and more publicly available. Our comprehensive siRNA dataset provides a public, freely available resource for further statistical and biological analyses in the high-content, high-throughput siRNA screening field.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-1162) contains supplementary material, which is available to authorized users.
doi:10.1186/1471-2164-15-1162
PMCID: PMC4326433  PMID: 25534632
High-throughput high-content RNAi screening; Pathogen entry; Linear mixed model; Hit detection
6.  Comparative analysis of RNAi screening technologies at genome-scale reveals an inherent processing inefficiency of the plasmid-based shRNA hairpin 
RNAi screening in combination with the genome-sequencing projects would constitute the Holy Grail of modern genetics; enabling discovery and validation towards a better understanding of fundamental biology leading to novel targets to combat disease. Hit discordance at inter-screen level together with the lack of reproducibility is emerging as the technology's main pitfalls. To examine some of the underlining factors leading to such discrepancies, we reasoned that perhaps there is an inherent difference in knockdown efficiency of the various RNAi technologies. For this purpose, we utilized the two most popular ones, chemically synthesized siRNA duplex and plasmid-based shRNA hairpin, in order to perform a head to head comparison. Using a previously developed gain-of-function assay probing modulators of the miRNA biogenesis pathway, we first executed on a siRNA screen against the Silencer Select V4.0 library (AMB) nominating 1,273, followed by an shRNA screen against the TRC1 library (TRC1) nominating 497 gene candidates. We observed a poor overlap of only 29 hits given that there are 15,068 overlapping genes between the two libraries; with DROSHA as the only common hit out of the seven known core miRNA biogenesis genes. Distinct genes interacting with the same biogenesis regulators were observed in both screens, with a dismal cross-network overlap of only 3 genes (DROSHA, TGFBR1, and DIS3). Taken together, our study demonstrates differential knockdown activities between the two technologies, possibly due to the inefficient intracellular processing and potential cell-type specificity determinants in generating intended targeting sequences for the plasmid-based shRNA hairpins; and suggests this observed inefficiency as potential culprit in addressing the lack of reproducibility.
PMCID: PMC4007059  PMID: 24433414
7.  An Arrayed Genome-Scale Lentiviral-Enabled Short Hairpin RNA Screen Identifies Lethal and Rescuer Gene Candidates 
Abstract
RNA interference technology is becoming an integral tool for target discovery and validation.; With perhaps the exception of only few studies published using arrayed short hairpin RNA (shRNA) libraries, most of the reports have been either against pooled siRNA or shRNA, or arrayed siRNA libraries. For this purpose, we have developed a workflow and performed an arrayed genome-scale shRNA lethality screen against the TRC1 library in HeLa cells. The resulting targets would be a valuable resource of candidates toward a better understanding of cellular homeostasis. Using a high-stringency hit nomination method encompassing criteria of at least three active hairpins per gene and filtered for potential off-target effects (OTEs), referred to as the Bhinder–Djaballah analysis method, we identified 1,252 lethal and 6 rescuer gene candidates, knockdown of which resulted in severe cell death or enhanced growth, respectively. Cross referencing individual hairpins with the TRC1 validated clone database, 239 of the 1,252 candidates were deemed independently validated with at least three validated clones. Through our systematic OTE analysis, we have identified 31 microRNAs (miRNAs) in lethal and 2 in rescuer genes; all having a seed heptamer mimic in the corresponding shRNA hairpins and likely cause of the OTE observed in our screen, perhaps unraveling a previously unknown plausible essentiality of these miRNAs in cellular viability. Taken together, we report on a methodology for performing large-scale arrayed shRNA screens, a comprehensive analysis method to nominate high-confidence hits, and a performance assessment of the TRC1 library highlighting the intracellular inefficiencies of shRNA processing in general.
doi:10.1089/adt.2012.475
PMCID: PMC3619155  PMID: 23198867
8.  TOPS: a versatile software tool for statistical analysis and visualization of combinatorial gene-gene and gene-drug interaction screens 
BMC Bioinformatics  2014;15:98.
Background
Measuring the impact of combinations of genetic or chemical perturbations on cellular fitness, sometimes referred to as synthetic lethal screening, is a powerful method for obtaining novel insights into gene function and drug action. Especially when performed at large scales, gene-gene or gene-drug interaction screens can reveal complex genetic interactions or drug mechanism of action or even identify novel therapeutics for the treatment of diseases.
The result of such large-scale screen results can be represented as a matrix with a numeric score indicating the cellular fitness (e.g. viability or doubling time) for each double perturbation. In a typical screen, the majority of combinations do not impact the cellular fitness. Thus, it is critical to first discern true "hits" from noise. Subsequent data exploration and visualization methods can assist to extract meaningful biological information from the data. However, despite the increasing interest in combination perturbation screens, no user friendly open-source program exists that combines statistical analysis, data exploration tools and visualization.
Results
We developed TOPS (Tool for Combination Perturbation Screen Analysis), a Java and R-based software tool with a simple graphical user interface that allows the user to import, analyze, filter and plot data from double perturbation screens as well as other compatible data. TOPS was designed in a modular fashion to allow the user to add alternative importers for data formats or custom analysis scripts not covered by the original release.
We demonstrate the utility of TOPS on two datasets derived from functional genetic screens using different methods. Dataset 1 is a gene-drug interaction screen and is based on Luminex xMAP technology. Dataset 2 is a gene-gene short hairpin (sh)RNAi screen exploring the interactions between deubiquitinating enzymes and a number of prominent oncogenes using massive parallel sequencing (MPS).
Conclusions
TOPS provides the benchtop scientist with a free toolset to analyze, filter and visualize data from functional genomic gene-gene and gene-drug interaction screens with a flexible interface to accommodate different technologies and analysis algorithms in addition to those already provided here. TOPS is freely available for academic and non-academic users and is released as open source.
doi:10.1186/1471-2105-15-98
PMCID: PMC4077039  PMID: 24712852
Double perturbation screens; Synthetic lethality; Functional genetics; Massive parallel sequencing; Luminex xMAP; Drug screens; Synergy; Epistasis
9.  Genome-Wide Small Interfering RNA Screens Reveal VAMP3 as a Novel Host Factor Required for Uukuniemi Virus Late Penetration 
Journal of Virology  2014;88(15):8565-8578.
ABSTRACT
The Bunyaviridae constitute a large family of enveloped animal viruses, many of which are important emerging pathogens. How bunyaviruses enter and infect mammalian cells remains largely uncharacterized. We used two genome-wide silencing screens with distinct small interfering RNA (siRNA) libraries to investigate host proteins required during infection of human cells by the bunyavirus Uukuniemi virus (UUKV), a late-penetrating virus. Sequence analysis of the libraries revealed that many siRNAs in the screens inhibited infection by silencing not only the intended targets but additional genes in a microRNA (miRNA)-like manner. That the 7-nucleotide seed regions in the siRNAs can cause a perturbation in infection was confirmed by using synthetic miRNAs (miRs). One of the miRs tested, miR-142-3p, was shown to interfere with the intracellular trafficking of incoming viruses by regulating the v-SNARE VAMP3, a strong hit shared by both siRNA screens. Inactivation of VAMP3 by the tetanus toxin led to a block in infection. Using fluorescence-based techniques in fixed and live cells, we found that the viruses enter VAMP3+ endosomal vesicles 5 min after internalization and that colocalization was maximal 15 min thereafter. At this time, LAMP1 was associated with the VAMP3+ virus-containing endosomes. In cells depleted of VAMP3, viruses were mainly trapped in LAMP1-negative compartments. Together, our results indicated that UUKV relies on VAMP3 for penetration, providing an indication of added complexity in the trafficking of viruses through the endocytic network.
IMPORTANCE Bunyaviruses represent a growing threat to humans and livestock globally. Unfortunately, relatively little is known about these emerging pathogens. We report here the first human genome-wide siRNA screens for a bunyavirus. The screens resulted in the identification of 562 host cell factors with a potential role in cell entry and virus replication. To demonstrate the robustness of our approach, we confirmed and analyzed the role of the v-SNARE VAMP3 in Uukuniemi virus entry and infection. The information gained lays the basis for future research into the cell biology of bunyavirus infection and new antiviral strategies. In addition, by shedding light on serious caveats in large-scale siRNA screening, our experimental and bioinformatics procedures will be valuable in the comprehensive analysis of past and future high-content screening data.
doi:10.1128/JVI.00388-14
PMCID: PMC4135934  PMID: 24850728
10.  Knowledge based identification of essential signaling from genome-scale siRNA experiments 
BMC Systems Biology  2009;3:80.
Background
A systems biology interpretation of genome-scale RNA interference (RNAi) experiments is complicated by scope, experimental variability and network signaling robustness. Over representation approaches (ORA), such as the Hypergeometric or z-score, are an established statistical framework used to associate RNA interference effectors to biologically annotated gene sets or pathways. These methods, however, do not directly take advantage of our growing understanding of the interactome. Furthermore, these methods can miss partial pathway activation and may be biased by protein complexes. Here we present a novel ORA, protein interaction permutation analysis (PIPA), that takes advantage of canonical pathways and established protein interactions to identify pathways enriched for protein interactions connecting RNAi hits.
Results
We use PIPA to analyze genome-scale siRNA cell growth screens performed in HeLa and TOV cell lines. First we show that interacting gene pair siRNA hits are more reproducible than single gene hits. Using protein interactions, PIPA identifies enriched pathways not found using the standard Hypergeometric analysis including the FAK cytoskeletal remodeling pathway. Different branches of the FAK pathway are distinctly essential in HeLa versus TOV cell lines while other portions are uneffected by siRNA perturbations. Enriched hits belong to protein interactions associated with cell cycle regulation, anti-apoptosis, and signal transduction.
Conclusion
PIPA provides an analytical framework to interpret siRNA screen data by merging biologically annotated gene sets with the human interactome. As a result we identify pathways and signaling hypotheses that are statistically enriched to effect cell growth in human cell lines. This method provides a complementary approach to standard gene set enrichment that utilizes the additional knowledge of specific interactions within biological gene sets.
doi:10.1186/1752-0509-3-80
PMCID: PMC2731733  PMID: 19653913
11.  mRNA turnover rate limits siRNA and microRNA efficacy 
Based on a simple model of the mRNA life cycle, we predict that mRNAs with high turnover rates in the cell are more difficult to perturb with RNAi.We test this hypothesis using a luciferase reporter system and obtain additional evidence from a variety of large-scale data sets, including microRNA overexpression experiments and RT–qPCR-based efficacy measurements for thousands of siRNAs.Our results suggest that mRNA half-lives will influence how mRNAs are differentially perturbed whenever small RNA levels change in the cell, not only after transfection but also during differentiation, pathogenesis and normal cell physiology.
What determines how strongly an mRNA responds to a microRNA or an siRNA? We know that properties of the sequence match between the small RNA and the mRNA are crucial. However, large-scale validations of siRNA efficacies have shown that certain transcripts remain recalcitrant to perturbation even after repeated redesign of the siRNA (Krueger et al, 2007). Weak response to RNAi may thus be an inherent property of the mRNA, but the underlying factors have proven difficult to uncover.
siRNAs induce degradation by sequence-specific cleavage of their target mRNAs (Elbashir et al, 2001). MicroRNAs, too, induce mRNA degradation, and ∼80% of their effect on protein levels can be explained by changes in transcript abundance (Hendrickson et al, 2009; Guo et al, 2010). Given that multiple factors act simultaneously to degrade individual mRNAs, we here consider whether variable responses to micro/siRNA regulation may, in part, be explained simply by the basic dynamics of mRNA turnover. If a transcript is already under strong destabilizing regulation, it is theoretically possible that the relative change in abundance after the addition of a novel degrading factor would be less pronounced compared with a stable transcript (Figure 1). mRNA turnover is achieved by a multitude of factors, and the influence of such factors on targetability can be explored. However, their combined action, including yet unknown factors, is summarized into a single property: the mRNA decay rate.
First, we explored the theoretical relationship between the pre-existing turnover rate of an mRNA, and its expected susceptibility to perturbation by a small RNA. We assumed a basic model of the mRNA life cycle, in which the rate of transcription is constant and the rate of degradation is described by first-order kinetics. Under this model, the relative change in steady-state expression level will become smaller as the pre-existing decay rate grows larger, independent of the transcription rate. This relationship persists also if we assume various degrees of synergy and antagonism between the pre-existing factors and the external factor, with increasing synergism leading to transcripts being more equally targetable, regardless of their pre-existing decay rate.
We next generated a series of four luciferase reporter constructs with destabilizing AU-rich elements (AREs) of various strengths incorporated into their 3′ UTRs. To evaluate how the different constructs would respond to perturbation, we performed co-transfections with an siRNA targeted at the coding region of the luciferase gene. This reduced the signal of the non-destabilized construct to 26% compared with a control siRNA. In contrast, the most destabilized construct showed 42% remaining reporter activity, and we could observe a dose–response relationship across the series.
The reporter experiment encouraged an investigation of this effect on real-world mRNAs. We analyzed a set of 2622 siRNAs, for which individual efficacies were determined using RT–qPCR 48 h post-transfection in HeLa cells (www.appliedbiosystems.com). Of these, 1778 could be associated with an experimentally determined decay rate (Figure 4A). Although the overall correlation between the two variables was modest (Spearman's rank correlation rs=0.22, P<1e−20), we found that siRNAs directed at high-turnover (t1/2<200 min) and medium-turnover (2001000 min) transcripts (P<8e−11 and 4e−9, respectively, two-tailed KS-test, Figure 4B). While 41.6% (498/1196) of the siRNAs directed at low-turnover transcripts reached 10% remaining expression or better, only 16.7% (31/186) of the siRNAs that targeted high-turnover mRNAs reached this high degree of silencing (Figure 4B). Reduced targetability (25.2%, 100/396) was also seen for transcripts with medium-turnover rate.
Our results based on siRNA data suggested that turnover rates could also influence microRNA targeting. By assembling genome-wide mRNA expression data from 20 published microRNA transfections in HeLa cells, we found that predicted target mRNAs with short and medium half-life were significantly less repressed after transfection than their long-lived counterparts (P<8e−5 and P<0.03, respectively, two-tailed KS-test). Specifically, 10.2% (293/2874) of long-lived targets versus 4.4% (41/942) of short-lived targets were strongly (z-score <−3) repressed. siRNAs are known to cause off-target effects that are mediated, in part, by microRNA-like seed complementarity (Jackson et al, 2006). We analyzed changes in transcript levels after transfection of seven different siRNAs, each with a unique seed region (Jackson et al, 2006). Putative ‘off-targets' were identified by mapping of non-conserved seed matches in 3′ UTRs. We found that low-turnover mRNAs (t1/2 >1000 min) were more affected by seed-mediated off-target silencing than high-turnover mRNAs (t1/2 <200 min), with twice as many long-lived seed-containing transcripts (3.8 versus 1.9%) being strongly (z-score <−3) repressed.
In summary, mRNA turnover rates have an important influence on the changes exerted by small RNAs on mRNA levels. It can be assumed that mRNA half-lives will influence how mRNAs are differentially perturbed whenever small RNA levels change in the cell, not only after transfection but also during differentiation, pathogenesis and normal cell physiology.
The microRNA pathway participates in basic cellular processes and its discovery has enabled the development of si/shRNAs as powerful investigational tools and potential therapeutics. Based on a simple kinetic model of the mRNA life cycle, we hypothesized that mRNAs with high turnover rates may be more resistant to RNAi-mediated silencing. The results of a simple reporter experiment strongly supported this hypothesis. We followed this with a genome-wide scale analysis of a rich corpus of experiments, including RT–qPCR validation data for thousands of siRNAs, siRNA/microRNA overexpression data and mRNA stability data. We find that short-lived transcripts are less affected by microRNA overexpression, suggesting that microRNA target prediction would be improved if mRNA turnover rates were considered. Similarly, short-lived transcripts are more difficult to silence using siRNAs, and our results may explain why certain transcripts are inherently recalcitrant to perturbation by small RNAs.
doi:10.1038/msb.2010.89
PMCID: PMC3010119  PMID: 21081925
microRNA; mRNA decay; RNAi; siRNA
12.  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
13.  The phosphoproteome of toll-like receptor-activated macrophages 
First global and quantitative analysis of phosphorylation cascades induced by toll-like receptor (TLR) stimulation in macrophages identifies nearly 7000 phosphorylation sites and shows extensive and dynamic up-regulation and down-regulation after lipopolysaccharide (LPS).In addition to the canonical TLR-associated pathways, mining of the phosphorylation data suggests an involvement of ATM/ATR kinases in signalling and shows that the cytoskeleton is a hotspot of TLR-induced phosphorylation.Intersecting transcription factor phosphorylation with bioinformatic promoter analysis of genes induced by LPS identified several candidate transcriptional regulators that were previously not implicated in TLR-induced transcriptional control.
Toll-like receptors (TLR) are a family of pattern recognition receptors that enable innate immune cells to sense infectious danger. Recognition of microbial structures, like lipopolysaccharide (LPS) of Gram-negative bacteria by TLR4, causes within hours substantial re-programming of macrophage gene expression, including up-regulation of chemokines driving inflammation, anti-microbial effector molecules and cytokines directing adaptive immune responses. TLR signalling is initiated by the adapter protein Myd88 and leads to the activation of kinase cascades that result in activation of the MAPK and NFkB pathways. Phosphorylation has an essential role in these early steps of TLR signalling, and in addition regulates critical transcription factors (TFs). Although TLR signalling has been extensively studied, a comprehensive analysis of phosphorylation events in TLR-activated macrophages is lacking. It is therefore unknown whether the canonical MAPK and NFkB pathways comprise the main phosphorylation events and which other molecular functions and processes are regulated by phosphorylation after stimulation with LPS.
Recent progress in mass spectrometry-based proteomics has opened the possibility to quantitatively investigate global changes in protein abundance and post-translational modifications. Stable isotope labelling with amino acids in cell culture (SILAC) allows highly accurate quantification, and has proved especially useful for direct comparison of phosphopeptide abundance in time-course or treatment analyses.
Here, we adapted SILAC to primary mouse macrophages, and performed a global, quantitative and kinetic analysis of the macrophage phosphoproteome after LPS stimulation. Bioinformatic analyses were used to identify kinases, pathways and biological processes enriched in the LPS-regulated phosphoproteome. To connect TF phosphorylation with transcription, we generated a parallel dataset of nascent RNA and used in silico promoter analysis to identify transcriptional regulators with binding site enrichment among the LPS-regulated gene set.
After establishing SILAC conditions for efficient labelling of primary bone marrow-derived macrophages in two independent experiments 1850 phosphoproteins with a total of 6956 phosphorylation sites were reproducibly identified. Phosphoproteins were detected from all cellular compartments, with a clear enrichment for nuclear and cytoskeleton-associated proteins. LPS caused major regulation of a large fraction of phosphopeptides, with 24% of all sites up-regulated and 9% down-regulated after stimulation (Figure 3A and B). These changes were highly dynamic, as the majority of the regulated phosphopeptides were up-regulated or down-regulated transiently or in a delayed manner (Figure 3C). Overall, the extent of changes in the phosphoproteome was comparable to the transcriptional re-programming, underscoring the importance of phosphorylation cascades in TLR signalling. Our parallel transcriptome data also showed that widespread phosphorylation precedes massive transcriptional changes.
To obtain footprints of kinase activation in response to TLR ligation, we searched phosphopeptide sequences for known linear sequence motifs of 33 kinases and identified kinase motifs enriched among LPS-regulated phosphorylation sites (compared to non-regulated phosphorylation sites) (Table I). Motif ERK/MAPK was highly enriched, in accordance with the essential role of the MAPK module in TLR signalling. Other kinases with motif enrichment have also recently been linked to TLR signalling (e.g. PKD; AKT and its targets GSK3 and mTOR). However, the DNA damage-actviated kinases ATM/ATR and the cell cycle-associated kinases AURORA and CHK1/2 have not been associated with the macrophage response to TLR activation yet. These finding shed new light on older data on the effect of TLR on macrophage proliferation in response to macrophage colony stimulating factor. Of interest, in follow-up experiments using pharmacological inhibitors of the kinases with motif enrichment, we observed that inhibition of ATM kinase activity caused increased LPS-induced expression of several cytokines and chemokines, suggesting that this pathway regulates inflammatory responses.
In further bioinformatic analyses, the Gene Ontology and signalling pathway annotations of phosphoproteins were used to identify signalling pathways and cellular processes targeted by TLR4-controlled phosphorylation (Table II). Among the expected hits, based on the known TLR pathways, were TLR signalling, MAPK and AKT as well as mTOR signalling. Of interest, the annotation terms ‘Rho GTPase cycle' and ‘cytoskeleton' were significantly enriched among LPS-regulated phosphoproteins, indicating a more prominent role for cytoskeletal proteins in the transduction of TLR signals or in the biological response to it.
We were especially interested in the phosphorylation of TFs and its regulation by LPS (Figure 6A). We hypothesised that functionally important TFs should have an increased frequency of binding sites in the promoters of LPS-regulated genes (Figure 6B). To identify transcriptionally regulated genes with high sensitivity, we isolated nascent RNA after metabolic labelling (Figure 6C–E). In silico promoter scanning using Genomatix software for binding sites for all 50 TF families with phosphorylated members was used to test for enrichment in transciptionally induced genes (Figure 6F). At the early time point, binding site enrichment for the canonical TLR-associated TF NFkB was detected, and in addition we found that several other TF families with an established role in the transcription of individual LPS-target genes showed binding site enrichment (CEBP, MEF2, NFAT and HEAT). In addition, enrichment for OCT and HOXC binding sites at the early time point and SORY matrices later after stimulation indicated an involvement of the phosphorylated members of the respective TF families in the execution of TLR-induced transcriptional responses. An initial test of the function for a few of these candidate transcriptional regulators was performed using siRNA knockdown in primary macrophages. These experiments suggested that knock down of the SORY binding phosphoprotein Capicua homolog (Cic) and to a lesser extent of the CREB family member Atf7 selectively attenuates LPS-induced expression of Il1a and Il1b.
In summary, this study provides a novel and global perspective on innate immune activation by TLR signalling (Figure 5). We quantitatively detected a large number of previously unknown site-specific phosphorylation events, which are now publicly available through the Phosida database. By combining different data mining approaches, we consistently identified canonical and newly implicated TLR-activated signalling modules. In particular, the PI3K/AKT and the related mTOR pathway were highlighted; furthermore, DNA damage–response associated ATM/ATR kinases and the cytoskeleton emerged as unexpected hotspots for phosphorylation. Finally, weaving together corresponding phophoproteome and nascent transcriptome datasets through the loom of in silico promoter analysis we identified TFs with a likely role in mediating TLR-induced gene expression programmes.
Recognition of microbial danger signals by toll-like receptors (TLR) causes re-programming of macrophages. To investigate kinase cascades triggered by the TLR4 ligand lipopolysaccharide (LPS) on systems level, we performed a global, quantitative and kinetic analysis of the phosphoproteome of primary macrophages using stable isotope labelling with amino acids in cell culture, phosphopeptide enrichment and high-resolution mass spectrometry. In parallel, nascent RNA was profiled to link transcription factor (TF) phosphorylation to TLR4-induced transcriptional activation. We reproducibly identified 1850 phosphoproteins with 6956 phosphorylation sites, two thirds of which were not reported earlier. LPS caused major dynamic changes in the phosphoproteome (24% up-regulation and 9% down-regulation). Functional bioinformatic analyses confirmed canonical players of the TLR pathway and highlighted other signalling modules (e.g. mTOR, ATM/ATR kinases) and the cytoskeleton as hotspots of LPS-regulated phosphorylation. Finally, weaving together phosphoproteome and nascent transcriptome data by in silico promoter analysis, we implicated several phosphorylated TFs in primary LPS-controlled gene expression.
doi:10.1038/msb.2010.29
PMCID: PMC2913394  PMID: 20531401
macrophage; nascent RNA; phosphoproteome; SILAC; toll-like receptors
14.  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
15.  Small Interfering RNA Screens Reveal Enhanced Cisplatin Cytotoxicity in Tumor Cells Having both BRCA Network and TP53 Disruptions▿ ‡  
Molecular and Cellular Biology  2006;26(24):9377-9386.
RNA interference technology allows the systematic genetic analysis of the molecular alterations in cancer cells and how these alterations affect response to therapies. Here we used small interfering RNA (siRNA) screens to identify genes that enhance the cytotoxicity (enhancers) of established anticancer chemotherapeutics. Hits identified in drug enhancer screens of cisplatin, gemcitabine, and paclitaxel were largely unique to the drug being tested and could be linked to the drug's mechanism of action. Hits identified by screening of a genome-scale siRNA library for cisplatin enhancers in TP53-deficient HeLa cells were significantly enriched for genes with annotated functions in DNA damage repair as well as poorly characterized genes likely having novel functions in this process. We followed up on a subset of the hits from the cisplatin enhancer screen and validated a number of enhancers whose products interact with BRCA1 and/or BRCA2. TP53+/− matched-pair cell lines were used to determine if knockdown of BRCA1, BRCA2, or validated hits that associate with BRCA1 and BRCA2 selectively enhances cisplatin cytotoxicity in TP53-deficient cells. Silencing of BRCA1, BRCA2, or BRCA1/2-associated genes enhanced cisplatin cytotoxicity ∼4- to 7-fold more in TP53-deficient cells than in matched TP53 wild-type cells. Thus, tumor cells having disruptions in BRCA1/2 network genes and TP53 together are more sensitive to cisplatin than cells with either disruption alone.
doi:10.1128/MCB.01229-06
PMCID: PMC1698535  PMID: 17000754
16.  Kinome-Wide RNAi Screen Implicates at Least 5 Host Hepatocyte Kinases in Plasmodium Sporozoite Infection 
PLoS Pathogens  2008;4(11):e1000201.
Plasmodium sporozoites, the causative agent of malaria, are injected into their vertebrate host through the bite of an infected Anopheles mosquito, homing to the liver where they invade hepatocytes to proliferate and develop into merozoites that, upon reaching the bloodstream, give rise to the clinical phase of infection. To investigate how host cell signal transduction pathways affect hepatocyte infection, we used RNAi to systematically test the entire kinome and associated genes in human Huh7 hepatoma cells for their potential roles during infection by P. berghei sporozoites. The three-phase screen covered 727 genes, which were tested with a total of 2,307 individual siRNAs using an automated microscopy assay to quantify infection rates and qRT-PCR to assess silencing levels. Five protein kinases thereby emerged as top hits, all of which caused significant reductions in infection when silenced by RNAi. Follow-up validation experiments on one of these hits, PKCς (PKCzeta), confirmed the physiological relevance of our findings by reproducing the inhibitory effect on P. berghei infection in adult mice treated systemically with liposome-formulated PKCς-targeting siRNAs. Additional cell-based analyses using a pseudo-substrate inhibitor of PKCς added further RNAi-independent support, indicating a role for host PKCς on the invasion of hepatocytes by sporozoites. This study represents the first comprehensive, functional genomics-driven identification of novel host factors involved in Plasmodium sporozoite infection.
Author Summary
During a mammalian malaria infection, Plasmodium sporozoites injected by an infected mosquito travel to the liver where they invade hepatocytes and multiply into thousands of new parasites. These newly formed merozoites are then released into the bloodstream where they infect red blood cells and cause the symptoms of the disease. Although asymptomatic, the liver stage of malaria is an obligatory step in the parasite's lifecycle and constitutes an appealing target for prophylatic intervention. The marked tropism of sporozoites for hepatocytes suggests the latter may provide the parasite with a molecular environment that it can exploit to its own benefit. The identification of host factors that influence hepatic infection can thus provide clues for potential anti-malarial strategies. To this end, we carried out an RNA interference screen of the entire human kinome and associated signaling molecules and assessed the effect of knockdown of their expression in the infection of a human hepatoma cell line by Plasmodium. This strategy identified at least 5 kinases whose down-regulation leads to a marked decrease in infection. Further characterisation of one of these proteins, PKCζ, confirmed that it plays a role in infection by influencing the parasite's invasion of the host liver cells.
doi:10.1371/journal.ppat.1000201
PMCID: PMC2574010  PMID: 18989463
17.  Visual Genome-Wide RNAi Screening to Identify Human Host Factors Required for Trypanosoma cruzi Infection 
PLoS ONE  2011;6(5):e19733.
The protozoan parasite Trypanosoma cruzi is the etiologic agent of Chagas disease, a neglected tropical infection that affects millions of people in the Americas. Current chemotherapy relies on only two drugs that have limited efficacy and considerable side effects. Therefore, the development of new and more effective drugs is of paramount importance. Although some host cellular factors that play a role in T. cruzi infection have been uncovered, the molecular requirements for intracellular parasite growth and persistence are still not well understood. To further study these host-parasite interactions and identify human host factors required for T. cruzi infection, we performed a genome-wide RNAi screen using cellular microarrays of a printed siRNA library that spanned the whole human genome. The screening was reproduced 6 times and a customized algorithm was used to select as hits those genes whose silencing visually impaired parasite infection. The 162 strongest hits were subjected to a secondary screening and subsequently validated in two different cell lines. Among the fourteen hits confirmed, we recognized some cellular membrane proteins that might function as cell receptors for parasite entry and others that may be related to calcium release triggered by parasites during cell invasion. In addition, two of the hits are related to the TGF-beta signaling pathway, whose inhibition is already known to diminish levels of T. cruzi infection. This study represents a significant step toward unveiling the key molecular requirements for host cell invasion and revealing new potential targets for antiparasitic therapy.
doi:10.1371/journal.pone.0019733
PMCID: PMC3098829  PMID: 21625474
18.  An integrative approach for a network based meta-analysis of viral RNAi screens 
Background
Big data is becoming ubiquitous in biology, and poses significant challenges in data analysis and interpretation. RNAi screening has become a workhorse of functional genomics, and has been applied, for example, to identify host factors involved in infection for a panel of different viruses. However, the analysis of data resulting from such screens is difficult, with often low overlap between hit lists, even when comparing screens targeting the same virus. This makes it a major challenge to select interesting candidates for further detailed, mechanistic experimental characterization.
Results
To address this problem we propose an integrative bioinformatics pipeline that allows for a network based meta-analysis of viral high-throughput RNAi screens. Initially, we collate a human protein interaction network from various public repositories, which is then subjected to unsupervised clustering to determine functional modules. Modules that are significantly enriched with host dependency factors (HDFs) and/or host restriction factors (HRFs) are then filtered based on network topology and semantic similarity measures. Modules passing all these criteria are finally interpreted for their biological significance using enrichment analysis, and interesting candidate genes can be selected from the modules.
Conclusions
We apply our approach to seven screens targeting three different viruses, and compare results with other published meta-analyses of viral RNAi screens. We recover key hit genes, and identify additional candidates from the screens. While we demonstrate the application of the approach using viral RNAi data, the method is generally applicable to identify underlying mechanisms from hit lists derived from high-throughput experimental data, and to select a small number of most promising genes for further mechanistic studies.
Electronic supplementary material
The online version of this article (doi:10.1186/s13015-015-0035-7) contains supplementary material, which is available to authorized users.
doi:10.1186/s13015-015-0035-7
PMCID: PMC4331137
Network analysis; RNAi screening; Virus-host interactions
19.  HTS-DB: an online resource to publish and query data from functional genomics high-throughput siRNA screening projects 
High-throughput screening (HTS) uses technologies such as RNA interference to generate loss-of-function phenotypes on a genomic scale. As these technologies become more popular, many research institutes have established core facilities of expertise to deal with the challenges of large-scale HTS experiments. As the efforts of core facility screening projects come to fruition, focus has shifted towards managing the results of these experiments and making them available in a useful format that can be further mined for phenotypic discovery. The HTS-DB database provides a public view of data from screening projects undertaken by the HTS core facility at the CRUK London Research Institute. All projects and screens are described with comprehensive assay protocols, and datasets are provided with complete descriptions of analysis techniques. This format allows users to browse and search data from large-scale studies in an informative and intuitive way. It also provides a repository for additional measurements obtained from screens that were not the focus of the project, such as cell viability, and groups these data so that it can provide a gene-centric summary across several different cell lines and conditions. All datasets from our screens that can be made available can be viewed interactively and mined for further hit lists. We believe that in this format, the database provides researchers with rapid access to results of large-scale experiments that might facilitate their understanding of genes/compounds identified in their own research.
Database URL: http://hts.cancerresearchuk.org/db/public
doi:10.1093/database/bat072
PMCID: PMC3796064  PMID: 24122843
20.  Integrative genome-scale metabolic analysis of Vibrio vulnificus for drug targeting and discovery 
Chromosome 1 of Vibrio vulnificus tends to contain larger portion of essential or housekeeping genes on the basis of the genomic analysis and gene knockout experiments performed in this study, while its chromosome 2 seems to have originated and evolved from a plasmid.The genome-scale metabolic network model of V. vulnificus was reconstructed based on databases and literature, and was used to identify 193 essential metabolites.Five essential metabolites finally selected after the filtering process are 2-amino-4-hydroxy-6-hydroxymethyl-7,8-dihydropteridine (AHHMP), D-glutamate (DGLU), 2,3-dihydrodipicolinate (DHDP), 1-deoxy-D-xylulose 5-phosphate (DX5P), and 4-aminobenzoate (PABA), which were predicted to be essential in V. vulnificus, absent in human, and are consumed by multiple reactions.Chemical analogs of the five essential metabolites were screened and a hit compound showing the minimal inhibitory concentration (MIC) of 2 μg/ml and the minimal bactericidal concentration (MBC) of 4 μg/ml against V. vulnificus was identified.
Discovering new antimicrobial targets and consequently new antimicrobials is important as drug resistance of pathogenic microorganisms is becoming an increasingly serious problem in human healthcare management (Fischbach and Walsh, 2009). There clearly exists a gap between genomic studies and drug discovery as the accumulation of knowledge on pathogens at genome level has not successfully transformed into the development of effective drugs (Mills, 2006; Payne et al, 2007). In this study, we dissected the genome of a microbial pathogen in detail, and subsequently developed a systems biological strategy of employing genome-scale metabolic modeling and simulation together with metabolite essentiality analysis for effective drug targeting and discovery. This strategy was used for identifying new drug targets in an opportunistic pathogen Vibrio vulnificus CMCP6 as a model.
V. vulnificus is a Gram-negative halophilic bacterium that is found in estuarine waters, brackish ponds, or coastal areas, and its Biotype 1 is an opportunistic human pathogen that can attack immune-compromised patients, and causes primary septicemia, necrotized wound infections, and gastroenteritis. We previously found that many metabolic genes were specifically induced in vivo, suggesting that specific metabolic pathways are essential for in vivo survival and virulence of this pathogen (Kim et al, 2003; Lee et al, 2007). These results motivated us to carry out systems biological analysis of the genome and the metabolic network for new drug target discovery.
V. vulnificus CMCP6 has two chromosomes. We first re-sequenced genomic regions assembled in low quality and low depth, and subsequently re-annotated the whole genome of V. vulnificus. Horizontal gene transfer was suspected to be responsible for the diversification of each chromosome of V. vulnificus, and the presence of metabolic genes was more biased to chromosome 1 than chromosome 2. Further studies on V. vulnificus genome revealed that chromosome 2 is more prone to diversification for better adaptation to the environment than its chromosome 1, while chromosome 1 tends to expand their genetic repertoire while maintaining the core genes at a constant level.
Next, a genome-scale metabolic network VvuMBEL943 was reconstructed based on literature, databases and experiments for systematic studies on the metabolism of this pathogen and prediction of drug targets. The VvuMBEL943 model is composed of 943 reactions and 765 metabolites, and covers 673 genes. The model was validated by comparing its simulated cell growth phenotype obtained by constraints-based flux analysis with the V. vulnificus-specific experimental data previously reported in the literature. In this study, constraints-based flux analysis is an optimization-based simulation method that calculates intracellular fluxes under the specific genetic and environmental condition (Kim et al, 2008). As a result, 17 growth phenotypes were correctly predicted out of 18 cases, which demonstrate the validity of VvuMBEL943.
The main objective of constructing VvuMBEL943 in this study is to predict potential drug targets by system-wide analysis of the metabolic network for the effective treatment of V. vulnificus. To achieve this goal, a set of drug target candidates was predicted by taking a metabolite-centric approach. Metabolite essentiality analysis is a concept recently introduced for the study of cellular robustness to complement conventional reaction or gene-centric approach (Kim et al, 2007b). Metabolite essentiality analysis observes changes in flux distribution by removing each metabolite from the in silico metabolic network. Hence, metabolite essentiality predicts essential metabolites whose absence causes cell death. By selecting essential metabolites, it is possible to directly screen only their structural analogs, which substantially reduces the number of chemical compounds to screen from the chemical compound library. As a result of implementing this approach, 193 metabolites were initially identified to be essential to the cell. These essential metabolites were then further filtered based on the predetermined criteria, mainly organism specificity and multiple connectivity associated with each metabolite, in order to reduce the number of initial target candidates towards identifying the most effective ones.
Five essential metabolites finally selected are 2-amino-4-hydroxy-6-hydroxymethyl-7,8-dihydropteridine (AHHMP), D-glutamate (DGLU), 2,3-dihydrodipicolinate (DHDP), 1-deoxy-D-xylulose 5-phosphate (DX5P), and 4-aminobenzoate (PABA). Enzymes that consume these essential metabolites were experimentally verified to be essential, which indeed demonstrates the essentiality of these five metabolites. On the basis of the structural information of these five essential metabolites, whole-cell screening assay was performed using their analogs for possible antibacterial discovery. We screened 352 chemical analogs of the essential metabolites selected from the chemical compound library, and found a hit compound 24837, which shows the minimal inhibitory concentration (MIC) of 2 μg/ml and minimal bactericidal concentration (MBC) of 4 μg/ml, showing good antibacterial activity without further structural modification. Although this study demonstrates a proof-of-concept, the approaches and their rationale taken here should serve as a general strategy for discovering novel antibiotics and drugs based on systems-level analysis of metabolic networks.
Although the genomes of many microbial pathogens have been studied to help identify effective drug targets and novel drugs, such efforts have not yet reached full fruition. In this study, we report a systems biological approach that efficiently utilizes genomic information for drug targeting and discovery, and apply this approach to the opportunistic pathogen Vibrio vulnificus CMCP6. First, we partially re-sequenced and fully re-annotated the V. vulnificus CMCP6 genome, and accordingly reconstructed its genome-scale metabolic network, VvuMBEL943. The validated network model was employed to systematically predict drug targets using the concept of metabolite essentiality, along with additional filtering criteria. Target genes encoding enzymes that interact with the five essential metabolites finally selected were experimentally validated. These five essential metabolites are critical to the survival of the cell, and hence were used to guide the cost-effective selection of chemical analogs, which were then screened for antimicrobial activity in a whole-cell assay. This approach is expected to help fill the existing gap between genomics and drug discovery.
doi:10.1038/msb.2010.115
PMCID: PMC3049409  PMID: 21245845
drug discovery; drug targeting; genome analysis; metabolic network; Vibrio vulnificus
21.  The Role of Abcb5 Alleles in Susceptibility to Haloperidol-Induced Toxicity in Mice and Humans 
PLoS Medicine  2015;12(2):e1001782.
Background
We know very little about the genetic factors affecting susceptibility to drug-induced central nervous system (CNS) toxicities, and this has limited our ability to optimally utilize existing drugs or to develop new drugs for CNS disorders. For example, haloperidol is a potent dopamine antagonist that is used to treat psychotic disorders, but 50% of treated patients develop characteristic extrapyramidal symptoms caused by haloperidol-induced toxicity (HIT), which limits its clinical utility. We do not have any information about the genetic factors affecting this drug-induced toxicity. HIT in humans is directly mirrored in a murine genetic model, where inbred mouse strains are differentially susceptible to HIT. Therefore, we genetically analyzed this murine model and performed a translational human genetic association study.
Methods and Findings
A whole genome SNP database and computational genetic mapping were used to analyze the murine genetic model of HIT. Guided by the mouse genetic analysis, we demonstrate that genetic variation within an ABC-drug efflux transporter (Abcb5) affected susceptibility to HIT. In situ hybridization results reveal that Abcb5 is expressed in brain capillaries, and by cerebellar Purkinje cells. We also analyzed chromosome substitution strains, imaged haloperidol abundance in brain tissue sections and directly measured haloperidol (and its metabolite) levels in brain, and characterized Abcb5 knockout mice. Our results demonstrate that Abcb5 is part of the blood-brain barrier; it affects susceptibility to HIT by altering the brain concentration of haloperidol. Moreover, a genetic association study in a haloperidol-treated human cohort indicates that human ABCB5 alleles had a time-dependent effect on susceptibility to individual and combined measures of HIT. Abcb5 alleles are pharmacogenetic factors that affect susceptibility to HIT, but it is likely that additional pharmacogenetic susceptibility factors will be discovered.
Conclusions
ABCB5 alleles alter susceptibility to HIT in mouse and humans. This discovery leads to a new model that (at least in part) explains inter-individual differences in susceptibility to a drug-induced CNS toxicity.
Gary Peltz and colleagues examine the role of ABCB5 alleles in haloperidol-induced toxicity in a murine genetic model and humans treated with haloperidol.
Editors' Summary
Background
The brain is the control center of the human body. This complex organ controls thoughts, memory, speech, and movement, it is the seat of intelligence, and it regulates the function of many organs. The brain comprises many different parts, all of which work together but all of which have their own special functions. For example, the forebrain is involved in intellectual activities such as thinking whereas the hindbrain controls the body’s vital functions and movements. Messages are passed between the various regions of the brain and to other parts of the body by specialized cells called neurons, which release and receive signal molecules known as neurotransmitters. Like all the organs in the body, blood vessels supply the brain with the oxygen, water, and nutrients it needs to function. Importantly, however, the brain is protected from infectious agents and other potentially dangerous substances circulating in the blood by the “blood-brain barrier,” a highly selective permeability barrier that is formed by the cells lining the fine blood vessels (capillaries) within the brain.
Why Was This Study Done?
Although drugs have been developed to treat various brain disorders, more active and less toxic drugs are needed to improve the treatment of many if not most of these conditions. Unfortunately, relatively little is known about how the blood-brain barrier regulates the entry of drugs into the brain or about the genetic factors that affect the brain’s susceptibility to drug-induced toxicities. It is not known, for example, why about half of patients given haloperidol—a drug used to treat psychotic disorders (conditions that affect how people think, feel, or behave)—develop tremors and other symptoms caused by alterations in the brain region that controls voluntary movements. Here, to improve our understanding of how drugs enter the brain and impact its function, the researchers investigate the genetic factors that affect haloperidol-induced toxicity by genetically analyzing several inbred mouse strains (every individual in an inbred mouse strain is genetically identical) with different susceptibilities to haloperidol-induced toxicity and by undertaking a human genetic association study (a study that looks for non-chance associations between specific traits and genetic variants).
What Did the Researchers Do and Find?
The researchers used a database of genetic variants called single nucleotide polymorphisms (SNPs) and a computational genetic mapping approach to show first that variations within the gene encoding Abcb5 affected susceptibility to haloperidol-induced toxicity (indicated by changes in the length of time taken by mice to move their paws when placed on an inclined wire-mesh screen) among inbred mouse strains. Abcb5 is an ATP-binding cassette transporter, a type of protein that moves molecules across cell membranes. The researchers next showed that Abcb5 is expressed in brain capillaries, which is the location of the blood-brain barrier. Abcb5 was also expressed in cerebellar Purkinje cells, which help to control motor (intentional) movements. They also measured the measured the effect of haloperidol and the haloperidol concentration in brain tissue sections in mice that were genetically engineered to make no Abcb5 (Abcb5 knockout mice). Finally, the researchers investigated whether specific alleles (alternative versions) of ABCB5 are associated with haloperidol-induced toxicity in people. Among a group of 85 patients treated with haloperidol for a psychotic illness, one specific ABCB5 allele was associated with haloperidol-induced toxicity during the first few days of treatment.
What Do These Findings Mean?
These findings indicate that Abcb5 is a component of the blood-brain barrier in mice and suggest that genetic variants in the gene encoding this protein underlie, at least in part, the differences in susceptibility to haloperidol-induced toxicity seen among inbred mice strains. Moreover, the human genetic association study indicates that a specific ABCB5 allele also affects the susceptibility of people to haloperidol-induced toxicity. The researchers note that other ABCB5 alleles or other genetic factors that affect haloperidol-induced toxicity in people might emerge if larger groups of patients were studied. However, based on their findings, the researchers propose a new model for the genetic mechanisms that underlie inter-individual and cell type-specific differences in susceptibility to haloperidol-induced brain toxicity. If confirmed in future studies, this model might facilitate the development of more effective and less toxic drugs to treat a range of brain disorders.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001782.
The US National Institute of Neurological Disorders and Stroke provides information about a wide range of brain diseases (in English and Spanish); its fact sheet “Brain Basics: Know Your Brain” is a simple introduction to the human brain; its “Blueprint Neurotherapeutics Network” was established to develop new drugs for disorders affecting the brain and other parts of the nervous system
MedlinePlus provides links to additional resources about brain diseases and their treatment (in English and Spanish)
Wikipedia provides information about haloperidol, about ATP-binding cassette transporters and about genetic association (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001782
PMCID: PMC4315575  PMID: 25647612
22.  GUItars: A GUI Tool for Analysis of High-Throughput RNA Interference Screening Data 
PLoS ONE  2012;7(11):e49386.
Background
High-throughput RNA interference (RNAi) screening has become a widely used approach to elucidating gene functions. However, analysis and annotation of large data sets generated from these screens has been a challenge for researchers without a programming background. Over the years, numerous data analysis methods were produced for plate quality control and hit selection and implemented by a few open-access software packages. Recently, strictly standardized mean difference (SSMD) has become a widely used method for RNAi screening analysis mainly due to its better control of false negative and false positive rates and its ability to quantify RNAi effects with a statistical basis. We have developed GUItars to enable researchers without a programming background to use SSMD as both a plate quality and a hit selection metric to analyze large data sets.
Results
The software is accompanied by an intuitive graphical user interface for easy and rapid analysis workflow. SSMD analysis methods have been provided to the users along with traditionally-used z-score, normalized percent activity, and t-test methods for hit selection. GUItars is capable of analyzing large-scale data sets from screens with or without replicates. The software is designed to automatically generate and save numerous graphical outputs known to be among the most informative high-throughput data visualization tools capturing plate-wise and screen-wise performances. Graphical outputs are also written in HTML format for easy access, and a comprehensive summary of screening results is written into tab-delimited output files.
Conclusion
With GUItars, we demonstrated robust SSMD-based analysis workflow on a 3840-gene small interfering RNA (siRNA) library and identified 200 siRNAs that increased and 150 siRNAs that decreased the assay activities with moderate to stronger effects. GUItars enables rapid analysis and illustration of data from large- or small-scale RNAi screens using SSMD and other traditional analysis methods. The software is freely available at http://sourceforge.net/projects/guitars/.
doi:10.1371/journal.pone.0049386
PMCID: PMC3502531  PMID: 23185323
23.  siRNA-mediated off-target gene silencing triggered by a 7 nt complementation 
Nucleic Acids Research  2005;33(14):4527-4535.
A growing body of evidence suggests that siRNA could generate off-target effects through different mechanisms. However, the full impact of off-target gene regulation on phenotypic induction and accordingly on data interpretation in the context of large-scale siRNA library screen has not been reported. Here we report on off-target gene silencing effects observed in a large-scale knockdown experiment designed to identify novel regulators of the HIF-1 pathway. All of the three ‘top hits’ from our screen have been demonstrated to result from off-target gene silencing. Two of the three ‘siRNA hits’ were found to directly trigger down-regulation of hif-1α mRNA through a 7 nt motif, AGGCAGT, that is present in both the hif-1α mRNA and the siRNAs. Further analysis revealed that the generation of off-target gene silencing via this 7 nt motif depends on the characteristics of the target mRNA, including the sequence context surrounding the complementary region, the position of the complementary region in the mRNA and the copy number of the complementary region. Interestingly, the off-target siRNA against hif-1α was also shown to trigger mRNA degradation with high probability of other genes that possess multiple copies of the AGGCAGT motif in the 3′-untranslated region. Lessons learned from this study will be a valuable asset to aid in designing siRNAs with more stringent target selectivity and improving ‘hits-follow-up’ strategies for future large-scale knockdown experiments.
doi:10.1093/nar/gki762
PMCID: PMC1184219  PMID: 16091630
24.  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
25.  Revealing Molecular Mechanisms by Integrating High-Dimensional Functional Screens with Protein Interaction Data 
PLoS Computational Biology  2014;10(9):e1003801.
Functional genomics screens using multi-parametric assays are powerful approaches for identifying genes involved in particular cellular processes. However, they suffer from problems like noise, and often provide little insight into molecular mechanisms. A bottleneck for addressing these issues is the lack of computational methods for the systematic integration of multi-parametric phenotypic datasets with molecular interactions. Here, we present Integrative Multi Profile Analysis of Cellular Traits (IMPACT). The main goal of IMPACT is to identify the most consistent phenotypic profile among interacting genes. This approach utilizes two types of external information: sets of related genes (IMPACT-sets) and network information (IMPACT-modules). Based on the notion that interacting genes are more likely to be involved in similar functions than non-interacting genes, this data is used as a prior to inform the filtering of phenotypic profiles that are similar among interacting genes. IMPACT-sets selects the most frequent profile among a set of related genes. IMPACT-modules identifies sub-networks containing genes with similar phenotype profiles. The statistical significance of these selections is subsequently quantified via permutations of the data. IMPACT (1) handles multiple profiles per gene, (2) rescues genes with weak phenotypes and (3) accounts for multiple biases e.g. caused by the network topology. Application to a genome-wide RNAi screen on endocytosis showed that IMPACT improved the recovery of known endocytosis-related genes, decreased off-target effects, and detected consistent phenotypes. Those findings were confirmed by rescreening 468 genes. Additionally we validated an unexpected influence of the IGF-receptor on EGF-endocytosis. IMPACT facilitates the selection of high-quality phenotypic profiles using different types of independent information, thereby supporting the molecular interpretation of functional screens.
Author Summary
Genome-scale functional genomics screens are important tools for investigating the function of genes. Technological progress allows for the simultaneous measurement of multiple parameters quantifying the response of cells to gene perturbations such as RNA interference. Such multi-dimensional screens provide rich data, but there is a lack of computational methods for interpreting these complex measurements. We have developed two computational methods that combine the data from multi-dimensional functional genomics screens with protein interaction information. These methods search for phenotype patterns that are consistent among interacting genes. Thereby, we could reduce the noise in the data and facilitate the mechanistic interpretation of the findings. The performance of the methods was demonstrated through application to a genome-wide screen studying endocytosis. Subsequent experimental validation demonstrated the improved detection of phenotypic profiles through the use of protein interaction data. Our analysis revealed unexpected roles of specific network modules and protein complexes with respect to endocytosis. Detailed follow-up experiments investigating the dynamics of endocytosis uncovered crosstalk between the cancer-related EGF and IGF pathways with so far unknown effects on endocytosis and cargo trafficking.
doi:10.1371/journal.pcbi.1003801
PMCID: PMC4154648  PMID: 25188415

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