Characterizing the extent and logic of signaling networks is essential to understanding specificity in such physiological and pathophysiological contexts as cell fate decisions and mechanisms of oncogenesis and resistance to chemotherapy. Cell-based RNA interference (RNAi) screens enable the inference of large numbers of genes that regulate signaling pathways, but these screens cannot provide network structure directly. We describe an integrated network around the canonical receptor tyrosine kinase (RTK)-Ras-extracellular signal-regulated kinase (ERK) signaling pathway, generated by combining parallel genome-wide RNAi screens with protein-protein interaction (PPI) mapping by tandem affinity purification-mass spectrometry. We found that only a small fraction of the total number of PPI or RNAi screen hits was isolated under all conditions tested and that most of these represented the known canonical pathway components, suggesting that much of the core canonical ERK pathway is known. Because most of the newly identified regulators are likely cell type- and RTK-specific, our analysis provides a resource for understanding how output through this clinically relevant pathway is regulated in different contexts. We report in vivo roles for several of the previously unknown regulators, including CG10289 and PpV, the Drosophila orthologs of two components of the serine/threonine-protein phosphatase 6 complex; the Drosophila ortholog of TepIV, a glycophosphatidylinositol-linked protein mutated in human cancers; CG6453, a noncatalytic subunit of glucosidase II; and Rtf1, a histone methyltransferase.
To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.
MicroRNAs (miRNAs) are a class of short noncoding RNAs that regulate protein-coding genes posttranscriptionally. In animals, most known miRNA targeting occurs within the 3'UTR of mRNAs, but the extent of biologically relevant targeting in the ORF or 5'UTR of mRNAs remains unknown. Here, we develop an algorithm (MinoTar-miRNA ORF Targets) to identify conserved regulatory motifs within protein-coding regions and use it to estimate the number of preferentially conserved miRNA-target sites in ORFs. We show that, in Drosophila, preferentially conserved miRNA targeting in ORFs is as widespread as it is in 3'UTRs and that, while far less abundant, conserved targets in Drosophila 5'UTRs number in the hundreds. Using our algorithm, we predicted a set of high-confidence ORF targets and selected seven miRNA-target pairs from among these for experimental validation. We observed down-regulation by the miRNA in five out of seven cases, indicating our approach can recover functional sites with high confidence. Additionally, we observed additive targeting by multiple sites within a single ORF. Altogether, our results demonstrate that the scale of biologically important miRNA targeting in ORFs is extensive and that computational tools such as ours can aid in the identification of such targets. Further evidence suggests that our results extend to mammals, but that the extent of ORF and 5'UTR targeting relative to 3'UTR targeting may be greater in Drosophila.
Adult structures in holometabolous insects such as Drosophila are generated by groups of imaginal cells dedicated to the formation of different organs. Imaginal cells are specified in the embryo and remain quiescent until the larval stages, when they proliferate and differentiate to form organs. The Drosophila tracheal system is extensively remodeled during metamorphosis by a small number of airway progenitors. Among these, the spiracular branch tracheoblasts are responsible for the generation of the pupal and adult abdominal airways. To understand the coordination of proliferation and differentiation during organogenesis of tubular organs, we analyzed the remodeling of Drosophila airways during metamorphosis. We show that the embryonic spiracular branch tracheoblasts are multipotent cells that express the homeobox transcription factor Cut, which is necessary for their survival and normal development. They give rise to three distinct cell populations at the end of larval development, which generate the adult tracheal tubes, the spiracle and the epidermis surrounding the spiracle. Our study establishes the series of events that lead to the formation of an adult tubular structure in Drosophila.
Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations.
Protein aggregates are a common pathological feature of most neurodegenerative diseases (NDs). Understanding their formation and regulation will help clarify their controversial roles in disease pathogenesis. To date, there have been few systematic studies of aggregates formation in Drosophila, a model organism that has been applied extensively in modeling NDs and screening for toxicity modifiers. We generated transgenic fly lines that express enhanced-GFP-tagged mutant Huntingtin (Htt) fragments with different lengths of polyglutamine (polyQ) tract and showed that these Htt mutants develop protein aggregates in a polyQ-length- and age-dependent manner in Drosophila. To identify central regulators of protein aggregation, we further generated stable Drosophila cell lines expressing these Htt mutants and also established a cell-based quantitative assay that allows automated measurement of aggregates within cells. We then performed a genomewide RNA interference screen for regulators of mutant Htt aggregation and isolated 126 genes involved in diverse cellular processes. Interestingly, although our screen focused only on mutant Htt aggregation, several of the identified candidates were known previously as toxicity modifiers of NDs. Moreover, modulating the in vivo activity of hsp110 (CG6603) or tra1, two hits from the screen, affects neurodegeneration in a dose-dependent manner in a Drosophila model of Huntington's disease. Thus, other aggregates regulators isolated in our screen may identify additional genes involved in the protein-folding pathway and neurotoxicity.
Identification of the signaling pathways that control the proliferation of stem cells (SCs), and whether they act in a cell or non-cell autonomous manner, is key to our understanding of tissue homeostasis and cancer. In the adult Drosophila midgut, the Jun N-Terminal Kinase (JNK) pathway is activated in damaged enterocyte cells (ECs) following injury. This leads to the production of Upd cytokines from ECs, which in turn activate the Janus kinase (JAK)/Signal transducer and activator of transcription (STAT) pathway in Intestinal SCs (ISCs), stimulating their proliferation. In addition, the Hippo pathway has been recently implicated in the regulation of Upd production from the ECs. Here, we show that the Hippo pathway target, Yorkie (Yki), also plays a crucial and cell-autonomous role in ISCs. Activation of Yki in ISCs is sufficient to increase ISC proliferation, a process involving Yki target genes that promote division, survival and the Upd cytokines. We further show that prior to injury, Yki activity is constitutively repressed by the upstream Hippo pathway members Fat and Dachsous (Ds). These findings demonstrate a cell-autonomous role for the Hippo pathway in SCs, and have implications for understanding the role of this pathway in tumorigenesis and cancer stem cells.
Biological networks are highly complex systems, consisting largely of enzymes that act as molecular switches to activate/inhibit downstream targets via post-translational modification. Computational techniques have been developed to perform signaling network inference using some high-throughput data sources, such as those generated from transcriptional and proteomic studies, but comparable methods have not been developed to use high-content morphological data, which are emerging principally from large-scale RNAi screens, to these ends. Here, we describe a systematic computational framework based on a classification model for identifying genetic interactions using high-dimensional single-cell morphological data from genetic screens, apply it to RhoGAP/GTPase regulation in Drosophila, and evaluate its efficacy. Augmented by knowledge of the basic structure of RhoGAP/GTPase signaling, namely, that GAPs act directly upstream of GTPases, we apply our framework for identifying genetic interactions to predict signaling relationships between these proteins. We find that our method makes mediocre predictions using only RhoGAP single-knockdown morphological data, yet achieves vastly improved accuracy by including original data from a double-knockdown RhoGAP genetic screen, which likely reflects the redundant network structure of RhoGAP/GTPase signaling. We consider other possible methods for inference and show that our primary model outperforms the alternatives. This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations.
Akt represents a nodal point between the Insulin receptor and TOR signaling, and its activation by phosphorylation controls cell proliferation, cell size, and metabolism. The activity of Akt must be carefully balanced, as increased Akt signaling is frequently associated with cancer and as insufficient Akt signaling is linked to metabolic disease and diabetes mellitus. Using a genome-wide RNAi screen in Drosophila cells in culture, and in vivo analyses in the third instar wing imaginal disc, we studied the regulatory circuitries that define dAkt activation. We provide evidence that negative feedback regulation of dAkt occurs during normal Drosophila development in vivo. Whereas in cell culture dAkt is regulated by S6 Kinase (S6K)-dependent negative feedback, this feedback inhibition only plays a minor role in vivo. In contrast, dAkt activation under wild-type conditions is defined by feedback inhibition that depends on TOR Complex 1 (TORC1), but is S6K-independent. This feedback inhibition is switched from TORC1 to S6K only in the context of enhanced TORC1 activity, as triggered by mutations in tsc2. These results illustrate how the Akt-TOR pathway dynamically adapts the routing of negative feedback in response to the activity load of its signaling circuit in vivo.
The progressive loss of muscle strength during aging is a common degenerative event of unclear pathogenesis. Although muscle functional decline precedes age-related changes in other tissues, its contribution to systemic aging is unknown. Here, we show that muscle aging is characterized in Drosophila by the progressive accumulation of protein aggregates that associate with impaired muscle function. The transcription factor FOXO and its target 4E-BP remove damaged proteins at least in part via the autophagy/lysosome system, whereas foxo mutants have dysfunctional proteostasis. Both FOXO and 4E-BP delay muscle functional decay and extend life span. Moreover, FOXO/4E-BP signaling in muscles decreases feeding behavior and the release of insulin from producing cells, which in turn delays the age-related accumulation of protein aggregates in other tissues. These findings reveal an organism-wide regulation of proteostasis in response to muscle aging and a key role of FOXO/4E-BP signaling in the coordination of organismal and tissue aging.
The stereotyped striation of myofibrils is a conserved feature of muscle organization that is critical to its function. Although most components that constitute the basic myofibrils are well-characterized biochemically and are conserved across the animal kingdom, the mechanisms leading to the precise assembly of sarcomeres, the basic units of myofibrils, are poorly understood. To gain insights into this process, we investigated the functional relationships of sarcomeric protein complexes. Specifically, we systematically analyzed, using either RNAi in primary muscle cells or available genetic mutations, the organization of myofibrils in Drosophila muscles that lack one or more sarcomeric proteins. Our study reveals that the thin and thick filaments are mutually dependent on each other for striation. Further, the tension sensor complex comprised of zipper/Zasp/α-actinin is involved in stabilizing the sarcomere but not in its initial formation. Finally, integrins appear essential for the interdigitation of thin and thick filaments that occurs prior to striation. Thus, sarcomere formation occurs by the coordinated assembly of multiple latent protein complexes, as opposed to sequential assembly.
RNAi-mediated gene knockdown in Drosophila melanogaster is a powerful method to analyze loss-of-function phenotypes both in cell culture and in vivo. However, it has also become clear that false positives caused by off-target effects are prevalent, requiring careful validation of RNAi-induced phenotypes. The most rigorous proof that an RNAi-induced phenotype is due to loss of its intended target is to rescue the phenotype by a transgene impervious to RNAi. For large-scale validations in the mouse and Caenorhabditis elegans, this has been accomplished by using bacterial artificial chromosomes (BACs) of related species. However, in Drosophila, this approach is not feasible because transformation of large BACs is inefficient. We have therefore developed a general RNAi rescue approach for Drosophila that employs Cre/loxP-mediated recombination to rapidly retrofit existing fosmid clones into rescue constructs. Retrofitted fosmid clones carry a selection marker and a phiC31 attB site, which facilitates the production of transgenic animals. Here, we describe our approach and demonstrate proof-of-principle experiments showing that D. pseudoobscura fosmids can successfully rescue RNAi-induced phenotypes in D. melanogaster, both in cell culture and in vivo. Altogether, the tools and method that we have developed provide a gold standard for validation of Drosophila RNAi experiments.
We present a droplet-based microfluidic technology that enables high-throughput screening of single mammalian cells. This integrated platform allows for the encapsulation of single cells and reagents in independent aqueous microdroplets (1 pL to 10 nL volumes) dispersed in an immiscible carrier oil and enables the digital manipulation of these reactors at a very high-throughput. Here, we validate a full droplet screening workflow by conducting a droplet-based cytotoxicity screen. To perform this screen, we first developed a droplet viability assay that permits the quantitative scoring of cell viability and growth within intact droplets. Next, we demonstrated the high viability of encapsulated human monocytic U937 cells over a period of 4 days. Finally, we developed an optically-coded droplet library enabling the identification of the droplets composition during the assay read-out. Using the integrated droplet technology, we screened a drug library for its cytotoxic effect against U937 cells. Taken together our droplet microfluidic platform is modular, robust, uses no moving parts, and has a wide range of potential applications including high-throughput single-cell analyses, combinatorial screening, and facilitating small sample analyses.
Drosophila Argonaute-1 and Argonaute-2 differ in function and small RNA content. AGO2 binds to siRNAs, whereas AGO1 is almost exclusively occupied by microRNAs. MicroRNA duplexes are intrinsically asymmetric, with one strand, the miR strand, preferentially entering AGO1 to recognize and regulate the expression of target mRNAs. The other strand, miR*, has been viewed as a byproduct of microRNA biogenesis. Here, we show that miR*s are often loaded as functional species into AGO2. This indicates that each microRNA precursor can potentially produce two mature small RNA strands that are differentially sorted within the RNAi pathway. miR* biogenesis depends upon the canonical microRNA pathway, but loading into AGO2 is mediated by factors traditionally dedicated to siRNAs. By inferring and validating hierarchical rules that predict differential AGO loading, we find that intrinsic determinants, including structural and thermodynamic properties of the processed duplex, regulate the fate of each RNA strand within the RNAi pathway.
With recent advances in fluorescence microscopy imaging techniques and methods of gene knock down by RNA interference (RNAi), genome-scale high-content screening (HCS) has emerged as a powerful approach to systematically identify all parts of complex biological processes. However, a critical barrier preventing fulfillment of the success is the lack of efficient and robust methods for automating RNAi image analysis and quantitative evaluation of the gene knock down effects on huge volume of HCS data. Facing such opportunities and challenges, we have started investigation of automatic methods towards the development of a fully automatic RNAi-HCS system. Particularly important are reliable approaches to cellular phenotype classification and image-based gene function estimation. We have developed a HCS analysis platform that consists of two main components: fluorescence image analysis and image scoring. For image analysis, we used a two-step enhanced watershed method to extract cellular boundaries from HCS images. Segmented cells were classified into several predefined phenotypes based on morphological and appearance features. Using statistical characteristics of the identified phenotypes as a quantitative description of the image, a score is generated that reflects gene function. Our scoring model integrates fuzzy gene class estimation and single regression models. The final functional score of an image was derived using the weighted combination of the inference from several support vector-based regression models. We validated our phenotype classification method and scoring system on our cellular phenotype and gene database with expert ground truth labeling. We built a database of high-content, 3-channel, fluorescence microscopy images of Drosophila Kc(167) cultured cells that were treated with RNAi to perturb gene function. The proposed informatics system for microscopy image analysis is tested on this database. Both of the two main components, automated phenotype classification and image scoring system, were evaluated. The robustness and efficiency of our system were validated in quantitatively predicting the biological relevance of genes.
A polyglutamine expansion in the huntingtin (HTT) gene causes neurodegeneration in Huntington's disease (HD), but the in vivo function of the native protein (Htt) is largely unknown. Numerous biochemical and in vitro studies have suggested a role for Htt in neuronal development, synaptic function and axonal trafficking. To test these models, we generated a null mutant in the putative Drosophila HTT homolog (htt, hereafter referred to asdhtt) and, surprisingly, found that dhtt mutant animals are viable with no obvious developmental defects. Instead, dhtt is required for maintaining the mobility and long-term survival of adult animals, and for modulating axonal terminal complexity in the adult brain. Furthermore, removing endogenous dhtt significantly accelerates the neurodegenerative phenotype associated with a Drosophila model of polyglutamine Htt toxicity (HD-Q93), providing in vivo evidence that disrupting the normal function of Htt might contribute to HD pathogenesis.
Drosophila melanogaster expresses three classes of small RNAs, which are classified according to their mechanisms of biogenesis. MicroRNAs are approximately 22-23 nucleotides (nt), ubiquitously expressed small RNAs that are sequentially processed from hairpin-like precursors by Drosha/Pasha and Dcr-1/Loquacious complexes. MicroRNAs usually associate with AGO1 and regulate the expression of protein-coding genes. Piwi-interacting RNAs (piRNAs) of approximately 24-28 nt associate with Piwi-family proteins and can arise from single-stranded precursors. piRNAs function in transposon silencing and are mainly restricted to gonadal tissues. Endo-siRNAs are found in both germline and somatic tissues. These approximately 21-nt RNAs are produced by a distinct Dicer, Dcr-2, and do not depend on Drosha/Pasha complexes. They predominantly bind to AGO2 and target both mobile elements and protein-coding genes. Surprisingly, a subset of endo-siRNAs strongly depend for their production on the dsRNA-binding protein Loquacious (Loqs), thought generally to be a partner for Dcr-1 and a cofactor for miRNA biogenesis. Endo-siRNA production depends on a specific Loqs isoform, Loqs-PD, which is distinct from the one, Loqs-PB, required for the production of microRNAs. Paralleling their roles in the biogenesis of distinct small RNA classes, Loqs-PD and Loqs-PB bind to different Dicer proteins, with Dcr-1/Loqs-PB complexes and Dcr-2/Loqs-PD complexes driving microRNA and endo-siRNA biogenesis, respectively.
Accumulating evidence suggests that hyperproliferating intestinal stem cells (SCs) and progenitors drive cancer initiation, maintenance, and metastasis. In addition, chronic inflammation and infection have been increasingly recognized for their roles in cancer. Nevertheless, the mechanisms by which bacterial infections can initiate SC-mediated tumorigenesis remain elusive. Using a Drosophila model of gut pathogenesis, we show that intestinal infection with Pseudomonas aeruginosa, a human opportunistic bacterial pathogen, activates the c-Jun N-terminal kinase (JNK) pathway, a hallmark of the host stress response. This, in turn, causes apoptosis of enterocytes, the largest class of differentiated intestinal cells, and promotes a dramatic proliferation of SCs and progenitors that serves as a homeostatic compensatory mechanism to replenish the apoptotic enterocytes. However, we find that this homeostatic mechanism can lead to massive over-proliferation of intestinal cells when infection occurs in animals with a latent oncogenic form of the Ras1 oncogene. The affected intestines develop excess layers of cells with altered apicobasal polarity reminiscent of dysplasia, suggesting that infection can directly synergize with the genetic background in predisposed individuals to initiate SC-mediated tumorigenesis. Our results provide a framework for the study of intestinal bacterial infections and their effects on undifferentiated and mature enteric epithelial cells in the initial stages of intestinal cancer. Assessment of progenitor cell responses to pathogenic intestinal bacteria could provide a measure of predisposition for apoptotic enterocyte-assisted intestinal dysplasias in humans.
Conditional expression of hairpin constructs in Drosophila is a powerful method to disrupt the activity of single genes with a spatial and temporal resolution that is impossible, or exceedingly difficult, using classical genetic methods. We previously described a method (Ni et al. 2008) whereby RNAi constructs are targeted into the genome by the phiC31-mediated integration approach using Vermilion-AttB-Loxp-Intron-UAS-MCS (VALIUM), a vector that contains vermilion as a selectable marker, an attB sequence to allow for phiC31-targeted integration at genomic attP landing sites, two pentamers of UAS, the hsp70 core promoter, a multiple cloning site, and two introns. As the level of gene activity knockdown associated with transgenic RNAi depends on the level of expression of the hairpin constructs, we generated a number of derivatives of our initial vector, called the "VALIUM" series, to improve the efficiency of the method. Here, we report the results from the systematic analysis of these derivatives and characterize VALIUM10 as the most optimal vector of this series. A critical feature of VALIUM10 is the presence of gypsy insulator sequences that boost dramatically the level of knockdown. We document the efficacy of VALIUM as a vector to analyze the phenotype of genes expressed in the nervous system and have generated a library of 2282 constructs targeting 2043 genes that will be particularly useful for studies of the nervous system as they target, in particular, transcription factors, ion channels, and transporters.