Accepted Manuscript Functional genomic analysis of the Drosophila immune response Susanna Valanne PII: DOI: Reference:
S0145-305X(13)00134-1 http://dx.doi.org/10.1016/j.dci.2013.05.007 DCI 1954
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Developmental & Comparative Immunology
Please cite this article as: Valanne, S., Functional genomic analysis of the Drosophila immune response, Developmental & Comparative Immunology (2013), doi: http://dx.doi.org/10.1016/j.dci.2013.05.007
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Functional genomic analysis of the Drosophila immune response Susanna Valanne1 1
Institute of Biomedical Technology and BioMediTech, Tampere University, 33520 Tampere, Finland.
[email protected] , tel. +35840 1909728. Abstract Drosophila melanogaster has been widely used as a model organism for over a century now, and also as an immunological research model for over 20 years. With the emergence of RNA interference (RNAi) in Drosophila as a robust tool to silence genes of interest, large‐scale or genome‐wide functional analysis has become a popular way of studying the Drosophila immune response in cell culture. Drosophila immunity is composed of cellular and humoral immunity mechanisms, and especially the systemic, humoral response pathways have been extensively dissected using the functional genomic approach. Although most components of the main immune pathways had already been found using traditional genetic screening techniques, important findings including pathway components, positive and negative regulators and modifiers have been made with RNAi screening. Additionally, RNAi screening has produced new information on host‐pathogen interactions related to the pathogenesis of many microbial species.
Keywords Drosophila; immune response; RNA interference; host‐pathogen interactions; NF‐kappaB signaling; JAK/STAT signaling Abbreviations RNAi, RNA interference; AMP, antimicrobial peptide; imd, immune deficiency; Jak‐STAT pathway, Janus kinase ‐ Signal Transducer and Activator of Transcription pathway; dsRNA, double‐stranded RNA; RNAi, RNA interference; siRNA, small interfering RNA; TLR, Toll‐Like Receptor; I B, Inhibitor of B; PGRP, peptidoglycan recognition protein; UAS, upstream activating sequence
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Contents Abstract Introduction 1. RNAi methodology for large‐scale screening 2. Functional analysis of the Drosophila immune response 2.1. Drosophila cellular response 2.1.1. Phagocytosis 2.2. Drosophila humoral immune response 2.2.1. Drosophila Imd pathway 2.2.2. Drosophila Toll pathway 2.2.3. Drosophila JAK/STAT pathway 2.2.4. Drosophila RNAi pathway 2.3. RNAi screening in Drosophila as a tool to study host‐pathogen interactions 3. Concluding remarks Acknowledgements Conflict of Interest References
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Introduction The fruitfly, Drosophila melanogaster, has been successfully used as a model organism for over a hundred years now. As invertebrates flies are ethically ideal for use in research. Possibilities for genetically manipulating them are excellent, and many sophisticated and powerful tools for fly research are available. Importantly, many biological processes are conserved between flies and vertebrates. Drosophila is a remarkable tool for making large genetic mutation screens (St Johnston, 2002), but it is also increasingly used in high‐throughput RNAi screening for functional genomic analyses (Valanne et al., 2012). Insects and microbes partially share the same environment, since insects, including Drosophila, often feed on rotting fruit containing a rich collection of microorganisms. As a result, Drosophila has evolved sensitive mechanisms for pathogen recognition and many strategies to defend itself against bacteria, fungi, parasites, and viruses (Lemaitre and Hoffmann, 2007). To combat infection Drosophila relies on several innate immunity reactions, many of which are shared with higher organisms. Therefore, Drosophila was developed as a model system to study innate immunity in the early 1990s, e.g. (Kylsten et al., 1990, Samakovlis et al., 1991, Wicker et al., 1990, Reichhart et al., 1992). Work on insects and other invertebrates has played an important role in understanding innate immune mechanisms in general (Hultmark, 1993, Hultmark, 1994, Hultmark, 2003, Lemaitre and Hoffmann, 2007). Drosophila lacks the adaptive immune response. This too makes it a good model for innate immunity studies, since results are easier to interpret. 1. RNAi methodology for large‐scale screening RNA interference (RNAi) is an ancient gene silencing mechanism for host defense against invading genetic material. In 1998 future Nobel laureates Fire and Mello (Fire et al., 1998) showed that target gene expression is silenced in Caenorhabditis elegans by the RNAi mechanism. Soon it became clear that this phenomenon is a very useful tool in research. And when it was shown that RNAi works efficiently also in Drosophila (Hammond et al., 2000), large scale gene silencing applications for Drosophila cells were developed (Rämet et al., 2002, Lum et al., 2003, Kiger et al., 2003, Boutros et al., 2004). Drosophila cells are optimal for large‐scale screening, because they can bind and internalize long double‐stranded RNA (dsRNA) fragments through receptor‐mediated endocytosis (Saleh et al., 2006, Ulvila et al., 2006), reviewed in (Valanne et al., 2012). Long dsRNA fragments are then diced into small interfering RNA (siRNA) fragments inside the cell by its intact RNAi machinery. siRNA fragments result in silencing of the gene in a sequence‐ specific way. Although off‐target effects have been shown for short homology stretches (Kulkarni et al.,
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2006, Ma et al., 2006), the silencing effect can be totally specific as shown for a chitinase‐like protein CG5210 in a microarray (Kleino et al., 2005, Fig. 1A). A schematic drawing of RNAi screening in Drosophila cells is shown in Figure 1. In the past few years RNAi screening in Drosophila in vivo has also become widely used because of the availability of many RNAi fly line collections, such as the Vienna collection in Austria (Dietzl et al., 2007), the collection in the National Institute of Genetics Fly Stock Center, Kyoto, Japan and the TRiP collections in Harvard, USA (Ni et al., 2008, Ni et al., 2011). Drosophila in vivo RNAi is based on the binary UAS‐GAL4 system (Brand and Perrimon, 1993), adapted from yeast. With this approach, a single cross between flies carrying an Upstream Activating Sequence coupled to a transgene of choice (UAS‐Gene X) and flies carrying a tissue‐specific GAL4 driver, results in the overexpression of the transgene in the chosen tissue in the F1 progeny flies (Brand and Perrimon, 1993, Duffy, 2002). RNAi lines contain an inverted repeat sequence of the targeted gene under the UAS, so overexpression of that sequence results in silencing of the corresponding gene in the tissue where GAL4 is expressed. Gene silencing with this method is usually very effective and RNAi phenotypes compare well with chromosomal mutations (Dietzl et al., 2007, Ni et al., 2008, Ni et al., 2011). The original method for generating UAS‐driven RNAi fly line collections was to insert a UAS‐construct containing the inverted repeat sequence of the targeted gene into the fly genome randomly using P‐ element‐mediated transformation (Dietzl et al., 2007). However, this sometimes resulted in false negatives due to variable expression because of the random landing site of the RNAi hairpin construct. Therefore, improvements were made to the second generation of RNAi lines by cloning the RNAi constructs into a vector with a phiC31 site for site‐specific integration into the Drosophila genome (Ni et al., 2008). The biggest advantage of this method is that the random integration of the RNAi construct into poorly expressed loci is eliminated and the construct is inserted into an optimal target site (Ni et al., 2008). Furthermore, in 2011, a growing resource of Drosophila RNAi lines with constructs specifically tested to be effective in the female germline was published. In these Drosophila lines silencing is generated using articifial micro‐RNAs, so‐called short hairpin (sh)RNAs (Ni et al., 2011). With additional tools, such as the temperature‐specific allele of the GAL4 repressor GAL80 or the hormone‐ inducible GAL4‐progesterone receptor chimera, RNAi silencing can be spatially or temporally controlled (McGuire et al., 2004). Turning on the UAS‐GAL4 system for gene silencing at a chosen time overcomes lethality issues of silencing genes essential for development. Moreover, tissue‐specific silencing is possible using a vast collection of GAL4 lines with differing expression patterns, meaning that genes can be silenced
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e.g. only in immune tissues such as the fatbody or hemocytes. This way the silencing effects in other tissues, where the gene of interest may have a non‐immune role, can be avoided. A schematic drawing of Drosophila in vivo screening is shown in Figure 1. 2. Functional analysis of the Drosophila immune response Most Drosophila immune response genes had been found in mutation screens before the RNAi screening era, e.g. the Toll‐Dorsal pathway core components (Belvin & Anderson, 1996), imd (Lemaitre et al., 1995), DIF (Rutschmann et al., 2000a) and IKK gamma (Rutschmann et al., 2000b). However, when RNAi became available, allowing individual genes to be easily knocked down in cell culture systems or whole organisms to identify genes related to loss‐of‐function genotypes, this reverse genetics method was also applied to the search for immune related genes. The first such screen was a phagocytosis screen, which resulted in the identification of the Imd pathway receptor peptidoglycan recognition protein LC (PGRP‐LC; Rämet et al., 2002). Thereafter, this functional analysis approach has been utilized extensively to find new components of many immune‐related mechanisms in Drosophila. The main findings from Drosophila RNAi screens regarding immunological mechanisms are summarized in Table I. To combat infections Drosophila relies on cellular and humoral immune responses. Both these mechanisms are important, and the balance between them depends on the invading pathogen (Nehme et al., 2011). 2.1. Drosophila cellular response Drosophila lacks a closed circulatory system, and the hemolymph i.e. the Drosophila blood, floats freely in its body cavity. Drosophila blood cells, or hemocytes, are present in the hemolymph ready to combat infections and participate in wound healing. There are three classes of hemocytes in Drosophila: plasmatocytes, lamellocytes and crystal cells. Plasmatocytes are professional phagocytes and make up about 95% of the hemocytes in a healthy Drosophila larva, and the remaining 5% is composed of crystal cells that are responsible for melanization and wound repair (Williams, 2007). Cells of the third class, lamellocytes, are not present in a healthy animal, but are induced by for example the parasitic wasp, Leptopilina boulardi (Williams et al., 2005). The most important mechanisms of the Drosophila cellular response are phagocytosis and encapsulation, of which the former has been substantially analyzed by RNAi screening. 2.1.1. Phagocytosis
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Phagocytosis probably originates from the engulfment of nutrients by unicellular organisms, and it is one of the oldest forms of host defense (reviewed in (Ulvila et al., 2011)). In Drosophila, the phagocytic activity of plasmatocytes has been shown to be important for immunity, although antimicrobial peptides (AMPs) produced via NF‐ B signaling pathways play a much more prominent role. Also, communication between Drosophila phagocytes and the fatbody tissue, which is involved in AMP production, has been shown at least in larval stages (Basset et al., 2000, Brennan et al., 2007, Charroux and Royet, 2009, Defaye et al., 2009), reviewed in (Ulvila et al., 2011). Drosophila can be used as a phagocytosis model, because phagocytic mechanisms have been well conserved in evolution. Moreover, Drosophila S2 cells are well suited for phagocytosis RNAi screening: Firstly, they recognize and engulf bacteria in a manner comparable to plasmatocytes (Rämet et al., 2001) and secondly, they internalize dsRNA directly from the cell culture medium via receptor‐mediated endocytosis (Ulvila et al., 2006). The genes important for the phagocytosis of several different micro‐organisms, such as Escherichia coli (Rämet et al., 2002, Ulvila et al., 2011), mycobacteria (Philips et al., 2005), Listeria monocytogenes (Agaisse et al., 2005), Candida albicans (Stroschein‐Stevenson et al., 2006) and Leishmania donovani (Peltan et al., 2012) have been screened for in Drosophila cells. The identified genes include microbe‐specific host factors (reviewed in section 2.3.) as well as components needed for general phagocytic mechanisms, including mainly actin‐related proteins and genes important for endocytosis and intracellular vesicle trafficking (reviewed in (Ulvila et al., 2011)). 2.2. Drosophila humoral immune response Microbes that manage to escape local and cellular defenses are faced with the humoral immune response, which includes the expression of a spectrum of antimicrobial peptides (AMPs). At least 34 AMPs in eight families have been found in Drosophila (Hultmark, 2003). AMPs are produced mostly in the fatbody, the functional equivalent of the human liver, and thereafter secreted into the hemolymph, the insect blood. They can act on invading micro‐organisms in various ways, for example by permeabilizing and disrupting the microbial cell membranes. AMPs can be broad spectrum effectors such as cecropins that kill both Gram‐negative and Gram‐positive bacteria and also fungi. Other AMPs such as diptericins, attacins and drosomycin, are more specialized (Hultmark, 2003). Two highly conserved pathways, namely the Toll and Imd pathways, control these responses by initiating the activation of NF‐ B‐like transcription factors and the subsequent transcription of AMPs (reviewed in (Valanne et al., 2012)). Also the JAK/STAT pathway regulates some immune response genes whose functions are still unclear. In anti‐viral defense, the Drosophila RNAi pathway is an important humoral immunity mechanism. 2.2.1. Drosophila Imd pathway
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The Drosophila Imd pathway is a dedicated signaling pathway for generating a systemic immune response against invading micro‐organisms. Initially, the pathway’s key component, imd, was found by analyzing a Black cell mutant fly line, whose ability to express AMPs was shown to be severely compromised. Further analysis revealed a mutation independent of the black cell phenotype in a nearby gene that turned out to be imd (immune deficiency) (Lemaitre et al., 1995). For a number of years the pathway receptor remained unknown until in 2002 PGRP‐LC was identified by three groups at the same time (Choe et al., 2002, Gottar et al., 2002, Rämet et al., 2002). The study by Rämet et al. (2002) was the first large‐scale RNAi screen carried out in Drosophila S2 cells, and it immediately showed the power of this screening approach. Upon binding a DAP‐type peptidoglycan PGRP‐LC receptors dimerize and the pathway is activated (Kaneko et al., 2004, Leulier et al., 2003). Another peptidoglycan recognition protein, namely PGRP‐LE, has also a role in binding peptidoglycan (Kaneko et al., 2006, Lim et al., 2006, Takehana et al., 2004), especially in the gut, as was shown recently (Bosco‐Drayon et al., 2012, Neyen et al., 2012). Activation of the pathway leads to the binding of Imd, which recruits Fas‐associated death domain (FADD), and FADD in turn recruits a caspase called death‐related ced‐3/Nedd2‐like protein (Dredd) into the complex. The signal propagates in a sequential way ultimately resulting in the activation and nuclear translocation of the NF‐ B factor Relish and the transcription of immune effector genes, as reviewed in (Valanne et al., 2012)). The importance of large‐scale RNAi screens in Drosophila NF‐ B signaling research has been reviewed in great detail recently (Valanne et al., 2012), and therefore this subject is described relatively briefly here. To summarize the screens of recent years: The first large‐scale RNAi screen for Imd pathway components was published by Foley & O’Farrell (2004), the main finding of which was the identification of Dnr1 as an inhibitor of Dredd. This screen was soon followed by two screens, both of which identified Inhibitor of apoptosis 2 (Iap2) and TAK1‐associated binding protein 2 (Tab2/TAB/CG7417) as essential components of the Imd pathway (Gesellchen et al., 2005, Kleino et al., 2005). Later on, based on the Gesellchen et al. (2005) screen, an evolutionarily conserved nuclear factor Akirin was identified as essential for the normal function of the Imd pathway (Goto et al., 2008). An RNAi screening approach has been taken to study also the negative regulation of the Imd pathway. In a follow‐up study to Gesellchen et al. (2005) it was shown that Ras/MAPK signaling attenuates the Imd signaling response (Ragab et al., 2011) via Pirk, a negative regulator of the Imd pathway identified earlier (Aggarwal et al., 2008, Kallio et al., 2005, Kleino et al., 2008, Lhocine et al., 2008). Ras/MAPK signaling downregulates the transcription of Pirk when activated via the PDGF/VEGF receptor (PVR)(Ragab et al., 2011). PVR has been shown to be a negative regulator of the Imd pathway also in the Kleino and coworkers’
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screen (2005) as well as in a screen for components of the JNK arm of the Imd pathway (Bond and Foley, 2009). More recently, Myllymäki and Rämet (2012) demonstrated that another Imd pathway inhibitor identified earlier in their screen, zfh1 (Kleino et al., 2005), acts at a transcriptional level in Drosophila S2 cells and that its human homologue ZEB1 positively regulates TNFR signaling in HeLa cells (Myllymäki and Rämet, 2012). Of note, Pirk (CG15678) was never found with the RNAi in vitro screening approach, which points out some of the limitations of this method. Pirk was identified in microarray studies for genes induced by Escherichia coli (Kallio et al., 2005, Valanne et al., 2007), and upon pirk RNAi Attacin reporter activity was elevated in E. coli ‐induced S2 cells (Kallio et al., 2005). Reasons that Pirk was never identified in the RNAi screens could be that the elevated reporter activity was below the chosen threshold in large‐scale screens, pirk dsRNA may not have been present in the libraries used or the library dsRNA did not silence the gene sufficiently. On the other hand, when genes identified in microarray studies have been studied in detail with the RNAi approach, sometimes the clear function has been difficult to find, like in the case of Edin (CG32185): edin was among one of the most induced genes in a microarray of E. coli activated S2 cells (Valanne et al., 2007), but despite an extensive study, edin RNAi or overexpression was found to have little effect on immune response related phenomena (Vanha‐aho et al., 2012). Edin appears to be involved in Enterococcus faecalis (Vanha‐aho et al., 2012) and Listeria monocytogenes resistance (Gordon et al., 2008), but further studies are required to find out the mechanism for how Edin affects the Drosophila immune response. 2.2.2. Drosophila Toll pathway The Drosophila Toll pathway was originally identified in a genetic saturation mutagenesis screen developed by C. Nüsslein‐Volhard and E. Wieschaus to look for genes important for the dorsal‐ventral patterning of the embryo (Belvin and Anderson, 1996, Anderson et al., 1985a, Anderson et al., 1985b). Later on it was demonstrated that in Drosophila the same signaling pathway was important both in embryo development and immunity, when the Toll receptor was shown to be an immune activator in a cell line (Rosetto et al., 1995). In 2011 the Nobel Prize in Physiology and Medicine was in part rewarded for the research demonstrating that the Drosophila Toll receptor is important for antifungal resistance in vivo (Lemaitre et al., 1996), a finding which facilitated the discovery of mammalian Toll‐like receptors (TLRs) (Medzhitov et al., 1997). Albeit strikingly similar, the fly and mammalian Toll/TLR pathways have important differences as well: in contrast to the mammalian TLRs, the Drosophila Toll is not a pattern recognition receptor but a cytokine receptor, which is activated via a cascade of proteolytic events and the binding of an activated ligand (reviewed in (Valanne et al., 2011). The most important group of pattern recognition proteins in the fly are the Peptidoglycan recognition proteins (PGRPs), reviewed in (Charroux et al., 2009), which function in pathogen recognition in both the Imd and the Toll pathways. 8
To this point, nine genes encoding Drosophila Toll receptors and at least 13 genes coding for human TLR receptors (Roach et al., 2005) have been identified. All Drosophila Tolls share the same molecular structure, but except for Toll (Toll‐1) the roles of the Drosophila Tolls in immunity have remained elusive. Since all identified mammalian TLRs are involved in the immune response, immune‐related functions for the remaining eight Drosophila Tolls have been actively searched for. Indeed, some reports for the roles of Toll‐ 5 and Toll‐9 in AMP induction exist (Bettencourt et al., 2004, Luo et al., 2001, Tauszig et al., 2000). Furthermore, a role for Toll‐7 in viral recognition and autophagy has been recently proposed (Nakamoto et al., 2012), suggesting that other Tolls may be involved in the recognition of specific, yet to be tested pathogens. The canonical Toll pathway has been reviewed in detail in (Valanne et al., 2011) and (Valanne et al., 2012). Briefly, upon pathway activation, binding of the active Spätzle ligand causes Toll receptors to dimerize. The dimerized receptor binds a heterotrimeric complex composed of dimers of MyD88 and Tube adaptor proteins as well as a Pelle kinase dimer (Moncrieffe et al., 2008, Sun et al., 2002). Activation of the MyD88‐ Tube‐Pelle complex leads to the phosphorylation and degradation of the Drosophila inhibitor of B (I B) factor Cactus, and thereby the activation and subsequent translocation of the NF‐ B factor Dorsal and/or DIF (Dorsal related immunity factor) to the nucleus. Binding of NF‐ B to responsive sites in the genome induces the transcription of the pathway target genes such as Drosomycin, immune induced molecule 1 (IM1) and IM2. Large‐scale or genome‐wide in vitro RNAi screening has revealed new modifiers of the Toll pathway, although most of the core pathway components were already discovered before the RNAi screens started. In a screen for 1033 transcription factors from a genome‐wide RNAi library described in (Boutros et al., 2004), the authors identified Deformed epidermal growth factor (Deaf‐1) as essential for full Drosomycin expression (Kuttenkeuler et al., 2010). Moreover, a targeted screen for kinases and phosphatases identified the endocytic pathway and its component Myopic as important for Toll signaling (Huang et al., 2010). This finding is supported by another study, where the endocytic pathway was shown to be needed for the Toll pathway function in embryogenesis as well (Lund et al., 2010). In a genome‐wide RNAi screen around the same time Valanne et al. (2010) identified an evolutionarily conserved G‐protein coupled receptor kinase 2 (Gprk2) as an important modifier of the Toll pathway that interacts with the NF‐ B inhibitor Cactus. Silencing of the Gprk2 ortholog in zebrafish embryos or the human ortholog GRK5 in HeLa cells caused impaired expression of cytokines indicating a functional immunological role also in these systems. This is further supported by a study by Patial et al. (2010) who showed that GRK5 mutant mice have an attenuated
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cytokine response to LPS and that GRK5 interacts with I B (Patial et al., 2010). However, the exact mechanism of Gprk2 action on the Toll pathway remains to be examined. 2.2.3. Drosophila JAK/STAT pathway The Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway mediates cytokine signaling to transcriptionally activate various genes (Aaronson and Horvath, 2002). In mammals, the JAK/STAT pathway is important for the regulation and maintenance of hematopoietic cells, and thus a malfunction in the pathway can lead to various pathological stages such as tumorigenesis. In Drosophila, the JAK/STAT pathway is involved in many processes in development, cell fate determination and immunity, particularly the antiviral response (Agaisse et al., 2005, Dostert et al., 2005, Hou et al., 2002, Souza‐Neto et al., 2009). JAK/STAT signaling begins when an extracellular cytokine ligand binds to a hetero‐ or homodimeric receptor complex thereby triggering autophosphorylation and the activation of associated JAKs (Fisher et al., 2013). Activated JAKs phosphorylate the C‐terminal tails of the receptors they bind to, generating docking sites and thereby recruiting the STAT proteins. STATs are bound to the receptors and phosphorylated by JAKs, which causes STATs to dissociate, dimerize and translocate to the nucleus where they induce the transcription of their target genes (Arbouzova and Zeidler, 2006, Ihle, 2001). In mammals, over fifty cytokines can activate seven STATs and four JAKs (Kisseleva et al., 2002) via many hetero‐ or homodimeric combinations of cytokine receptors that are thought to offer tissue specificity (Fisher et al., 2013). In Drosophila, there are only three ligands (Upd, Upd2 and Upd3) that activate one receptor (Dome), from where the signal is propagated via one JAK (hopscotch; hop) and one STAT (Stat92E). Upon an immune challenge, JAK/STAT pathway target genes such as the Turandot (Tot) genes and the thioester‐containing protein 2 (Tep2) are induced. Several functional genomic analyses have been carried out for the Drosophila JAK/STAT pathway. By 2010, three genome‐wide screens for JAK/STAT pathway components/regulators in Drosophila cells in culture had been completed (Baeg et al., 2005, Kallio et al., 2010, Muller et al., 2005). Although all these screens identified the central pathway components, there is little overlap in the novel genes found in the different studies. This has been explained at least in part by differences in set‐ups regarding cells, pathway inducers and readouts. For example, in the Baeg et al. screen over 75% of the findings involved negative regulators of the pathway, whereas the Muller et al. screen identified mainly positive regulators, probably partly as a 10
result of the level of pathway stimulation (Muller et al., 2008). The quality of the RNAi library is also an issue. To explore the differences between first and second generation RNAi libraries, another JAK/STAT screen, biologically very similar to the Muller et al. (2005) screen, was carried out recently, (Fisher et al., 2012). The authors also reanalyzed the Muller et al. (2005) screen with newer bioinformatics methods, and compared it to their screen. However, even in these biologically very similar screens the overlap in identified genes was surprisingly small (29%). Although the authors discuss the role of off target effects and related improvements in the new RNAi library design, the poor overlap is not fully explained by differences in libraries. Even the best screening approaches are only a tool for identifying genes important for a chosen pathway, and ultimately, downstream validation and secondary assays to confirm the findings are required (Fisher et al., 2012). The screening set‐up also affects the findings greatly, as is demonstrated in Kallio et al. (2010). The authors used a mutant form of the hop kinase, hopTum‐l, as an inducer of the JAK/STAT pathway, since they wanted to screen for components important for the conserved intracellular part of the signaling cascade (Kallio et al., 2010). With this set‐up they identified eye transformer (ET) first as a positive regulator. Later it was shown that in a more physiological context, ET RNAi enhances the JAK/STAT phenotypes both in vitro and in vivo, identifying ET as a negative regulator of the JAK/STAT pathway. It was shown that ET is an intrinsic component of the Dome receptor complex as it interacts with both Dome and hop, and it functions in regulating Stat92E phosphorylation (Kallio et al., 2010). Around the same time Makki et al. (2010) demonstrated that ET/CG14225/Latran acts as an inhibitor of the JAK/STAT pathway also in the lymph gland, where it induces massive differentiation of lamellocytes upon wasp parasitization (Makki et al., 2010). Other important findings from genome‐wide JAK/STAT screens include the dBRWD3 and Ptp61F genes: disrupted dBRWD3 expression and overexpression of Ptp61F suppressed the hopTum‐l‐induced leukemia‐like blood cell tumors, bringing insights into a pathway relevant for human cancer mechanisms (Muller et al., 2005). Ptp61F was also identified in the Baeg et al. (2005) screen, as were RanBP3 and RanBP10, two other putative negative regulators of the pathway (Baeg et al., 2005). Moreover, Cnot4/CG31716 was identified in the Kallio et al. screen (2010) and was later shown to be an evolutionarily conserved positive regulator of the JAK/STAT pathway (Grönholm et al., 2012). Also, in a genome‐wide in vivo RNAi screen the JAK/STAT pathway was shown to negatively regulate survival during an intestinal Serratia marcescens infection (Cronin et al., 2009). This study was the first in vivo RNAi screen of such scale and it utilized the genome‐wide collection of RNAi lines available in the Vienna Drosophila RNAi Center (Dietzl et al., 2007). On the other hand, others have shown that enhanced JAK/STAT signaling is protective in the guts of S. marcescens infected flies (Jiang et al., 2009, Kallio et al., 2010), possibly indicating that the JAK/STAT pathway activity level needs to be particularly delicately regulated and balanced for proper function and homeostasis. 11
2.2.4. Drosophila RNAi pathway Although RNAi has been used as a method in Drosophila RNAi screening research for silencing specific genes (see section 1), RNAi first evolved as an innate immune mechanism particularly against viruses (Cherry & Silverman, 2006). The Drosophila RNAi pathway uses viral dsRNA to induce host‐mediated degradation of viral RNA, and this essential antiviral function of RNAi in flies has been demonstrated in many studies (Galiana‐Arnoux et al., 2006, Wang et al., 2006, Zambon et al., 2006). RNAi screening for components of the RNAi pathway revealed the importance of the endocytic pathway in dsRNA internalization in S2 cells (Ulvila et al., 2006, Saleh et al., 2006). The RNAi pathway is reviewed in detail in this issue of Developmental and Comparative immunology. 2.3. RNAi screening in Drosophila as a tool to study host‐pathogen interactions Because of the ease and affectivity of Drosophila RNAi in cell culture, in recent years this model has been adapted to study host factors in response to multiple pathogens. This approach can potentially identify novel therapeutic targets and aid in understanding the complex interactions between pathogens and their host cells (Cherry, 2008). One of the first genome wide screens for host‐pathogen interactions identified a specific requirement for high levels of the host translation machinery for picorna‐like viruses both in insects and mammals (Cherry et al., 2005). In a follow‐up study it was shown that these viruses require at least two host encoded mechanisms for their lifecycle: the coat protein complex I (COPI) activity and fatty acid biosynthesis (Cherry et al., 2006). Other genome‐wide screens published around the same time identified factors needed for the entry and survival of intracellular bacteria: one important finding was Peste, a member of the CD36 family of scavenger receptors. Peste was identified as required for the uptake of both Listeria monocytogenes (Agaisse et al., 2005) and Mycobacterium fortuitum (Philips et al., 2005). Also, serine palmitoyltransferase and genes important for vacuolar trafficking were shown to play a role in L. monocytogenes pathogenesis (Cheng et al., 2005). As a follow‐up to the mycobacterial work Philips et al. (2008) compared an infection with M. fortuitum to an infection with the non‐pathogenic mycobacterial species M. smegmatis upon the silencing of 86 selected genes, and showed that the ESCRT machinery modulates a mycobacterial phagosome in Drosophila S2 cells (Philips et al., 2008). Moreover, beta‐ hexosaminidase has been shown to control mycobacterial growth in a small screen of about 1000 dsRNAs (Koo et al., 2008). Host factors needed for infection by other intracellular bacteria, namely Francicella tularensis and Chlamydia spp. have been screened using genome‐wide dsRNA libraries in Drosophila cells, identifying 12
evolutionarily conserved components involved for example in phagosome maturation and actin remodeling (Akimana et al., 2010, Derre et al., 2007). Also, host factors in viral infections have been studied using this method. Firstly, a genome‐wide study with the influenza virus identified three Drosophila genes with human homologues ATP6V0D1, COX6A1 and NXF1 as important for virus replication (Hao et al., 2008). Secondly, Dengue virus host factors were studied in a genome‐wide screen in Drosophila cells. After this a targeted siRNA screen in human cells with homologues of identified Drosophila genes fished out 42 human host factors important for the dengue virus infection (Sessions et al., 2009). Also, a smaller targeted kinome screen was carried out for the Vaccinia virus, identifying an AMP‐activated kinase complex needed for viral entry into Drosophila cells as well as mammalian cells (Moser et al., 2010). Other small targeted screens have been carried out for host factors needed for at least for a Cryptococcus neoformans, Pseudomonas aeruginosa, Brucella and Rickettsia infection. These studies reveal new information on specific host‐ pathogen interaction mechanisms for each pathogen (Pielage et al., 2008, Qin et al., 2008, Qin et al., 2011, Reed et al., 2012, Serio et al., 2010). 3. Concluding remarks Large‐scale RNAi screening is a powerful method to dissect signaling pathways or specific interactions. The last ten years have shown the potential and applicability of this approach to many functions of interest in Drosophila. Many genes or processes relevant to human disease can be found using the Drosophila RNAi screening approach, demonstrating the evolutionary conservation of many mechanisms from flies to humans. On one hand, the emergence of mammalian siRNA libraries and the possibility to carry out genome‐wide studies in mammalian cell culture will undoubtedly bring another level of understanding to the mechanisms studied. On the other hand, the genome‐wide RNAi libraries of flies in vivo will bring about an increasing number of studies where, depending on the set‐up, genes are silenced in a chosen tissue at a chosen time in development. Drosophila in vivo screens will most likely reveal cell‐autonomous mechanisms that cannot be found in cell culture assays. Additionally, Drosophila RNAi lines can be utilized to validate in vitro findings on the organismal scale. However, all screening approaches produce a vast amount of data that need to be analyzed critically. Data validation is an important step in screening, since even the best screens are only a starting point for further validation of the hits and for functional studies. Acknowledgements SV was funded by “Provision of support to research career development in biocenters” grant from Biocenter Finland.
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Conflict of Interest None to declare.
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Figure legends Figure 1: Drosophila RNAi screening in vitro and in vivo. Left: Drosophila cells are cultured in multiwell cell culture plates. dsRNAs from a large‐scale or genome‐wide library are added to the cells. If needed, reporter plasmids and pathway inducers are transfected. After assaying reporter activities (or using other assays, e.g. microscopy), interesting hit genes are selected. Thereafter, initial findings need to be confirmed and validated, and then analyzed for their function. Right: Drosophila in vivo RNAi screening. A collection of UAS‐RNAi fly lines are crossed with the GAL4 driver line to silence genes in a chosen tissue (or ubiquitously). After an initial assay interesting genes are identified and validated with repeats and independent RNAi lines. Functional assays are carried out for example with different GAL4 driver lines to identify for which tissue the selected genes are important.
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Table I: Most important findings from Drosophila immune response RNAi screens. Main findings
Reference
Imd pathway PGRP‐LC
Rämet et al., 2002
Dnr1
Foley & O’Farrell, 2004
Iap2, Tab2 (TAB)
Kleino et al., 2005
Iap2, Tab2 (CG7417)
Gesellchen et al., 2005
Akirin
Goto et al., 2008
Ras/MAPK signaling
Ragab et al., 2011
PVR
Bond & Foley, 2009
zfh1
Myllymäki & Rämet, 2012
Toll pathway Deaf‐1
Kuttenkeuler et al., 2010
Gprk2, (ush, pnr, wispy/TAMP)
Valanne et al., 2010
endocytic pathway (Myopic)
Huang et al., 2010
JAK/STAT pathway Ptp61F, dBRWD3
Muller et al., 2005
Ptp61F, RanBP3, RanBP10
Baeg et al., 2005
ET, (Not4/CG31716)
Kallio et al., 2010, Grönholm et al., 2012
Ptp61F, Tbp, CG40121
Fisher et al., 2012
Phagocytosis (general) PGRP‐LC
Rämet et al., 2002
14‐3‐3 , (Abi, cpa)
Ulvila et al., 2011
Specific host‐pathogen interactions (pathogen in brackets) Translation machinery (picorna‐like viruses)
Cherry et al., 2005
Peste (Mycobacteria, Listeria)
Agaisse et al., 2005, Philips et al., 2005
Vacuolar trafficking, serine palmitoyltransferase (Listeria monocytogenes)
Cheng et al., 2005
COPI activity, fatty acid biosynthesis (picorna‐like viruses)
Cherry et al., 2006
Tom complex (Chlamydia)
Derre et al., 2007
ESCRT machinery (Mycobacteria)
Philips et al., 2008
beta‐hexosaminidase (Mycobacteria)
Koo et al., 2008
ATP6V0D1, COX6A1 and NXF1 (influenza virus)
Hao et al., 2008
IRE1 (Brucella)
Qin et al., 2008
42 human homologs (Dengue virus)
Sessions et al., 2009
PI4KCA, USP22, CDC27 (Francicella tularensis)
Akimana et al., 2010
AMP‐activated kinase complex (Vaccinia virus)
Moser et al., 2010
Abl tyrosine kinase, Crk, Rac1, Cdc42, p21‐activated kinase
Pielage et al., 2010
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(Pseudomonas aeruginosa) profilin, fimbrin/T‐plastin, capping protein, cofilin (Rickettsia)
Serio et al., 2010
Autophagy proteins (Cryptococcus neoformans)
Qin et al., 2011
WAVE and Arp2/3 complexes (Rickettsia)
Reed et al., 2012
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Functional genomic analysis of the Drosophila immune response Susanna Valanne Abstract Drosophila melanogaster has been widely used as a model organism for over a century now, and also as an immunological research model for over 20 years. With the emergence of RNA interference (RNAi) in Drosophila as a robust tool to silence genes of interest, large‐scale or genome‐wide functional analysis has become a popular way of studying the Drosophila immune response in cell culture. Drosophila immunity is composed of cellular and humoral immunity mechanisms, and especially the systemic, humoral response pathways have been extensively dissected using the functional genomic approach. Although most components of the main immune pathways had already been found using traditional genetic screening techniques, important findings including pathway components, positive and negative regulators and modifiers have been made with RNAi screening. Additionally, RNAi screening has produced new information on host‐pathogen interactions related to the pathogenesis of many microbial species.
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Functional genomic analysis of the Drosophila immune response Susanna Valanne Highlights ‐ ‐ ‐ ‐
Drosophila is an excellent research model for innate immunity Many immune mechanisms are conserved in evolution from flies to humans RNAi is a robust tool for gene silencing in Drosophila in vitro and in vivo RNAi screening approach has yielded many important findings in Drosophila immunity
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