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.
Drosophila larval skeletal muscles are single, multinucleated cells of different sizes that undergo tremendous growth within a few days. The mechanisms underlying this growth in concert with overall body growth are unknown. We find that the size of individual muscles correlates with the number of nuclei per muscle cell and with increasing nuclear ploidy during development. Inhibition of Insulin receptor (InR; Insulin-like receptor) signaling in muscles autonomously reduces muscle size and systemically affects the size of other tissues, organs and indeed the entire body, most likely by regulating feeding behavior. In muscles, InR/Tor signaling, Foxo and dMyc (Diminutive) are key regulators of endoreplication, which is necessary but not sufficient to induce growth. Mechanistically, InR/Foxo signaling controls cell cycle progression by modulating dmyc expression and dMyc transcriptional activity. Thus, maximal dMyc transcriptional activity depends on InR to control muscle mass, which in turn induces a systemic behavioral response to allocate body size and proportions.
In Drosophila melanogaster, widely used mitotic recombination-based strategies generate mosaic flies with positive readout for only one daughter cell after division. To differentially label both daughter cells, we developed the twin spot generator (TSG) technique, which through mitotic recombination generates green and red twin spots that are detectable after the first cell division as single cells. We propose wide applications of TSG to lineage and genetic mosaic studies.
A label-free quantification strategy including the development of in-house software (NakedQuant) to calculate the average TIC across all spectral counts in tandem affinity purification (TAP)-tagging liquid chromatography-mass spectrometry MS/MS (LC/MS/MS) experiments was applied to a large-scale study of protein complexes in the MAPK portion of the insulin signaling pathway from Drosophila cells. Dynamics were calculated under basal and stimulating conditions as fold changes. These experiments were performed in the context of a core service model with the user performing the TAP immunoprecipitation and the MS core performing the MS and informatics stops. The MS strategy showed excellent coverage of known components in addition to potentially novel interactions.
Genome-wide, cell-based screens using high-content screening (HCS) techniques and automated fluorescence microscopy generate thousands of high-content images that contain an enormous wealth of cell biological information. Such screens are key to the analysis of basic cell biological principles, such as control of cell cycle and cell morphology. However, these screens will ultimately only shed light on human disease mechanisms and potential cures if the analysis can keep up with the generation of data. A fundamental step toward automated analysis of high-content screening is to construct a robust platform for automatic cellular phenotype identification. The authors present a framework, consisting of microscopic image segmentation and analysis components, for automatic recognition of cellular phenotypes in the context of the Rho family of small GTPases. To implicate genes involved in Rac signaling, RNA interference (RNAi) was used to perturb gene functions, and the corresponding cellular phenotypes were analyzed for changes. The data used in the experiments are high-content, 3-channel, fluorescence microscopy images of Drosophila Kc167 cultured cells stained with markers that allow visualization of DNA, polymerized actin filaments, and the constitutively activated Rho protein Rac(V12). The performance of this approach was tested using a cellular database that contained more than 1000 samples of 3 predefined cellular phenotypes, and the generalization error was estimated using a cross-validation technique. Moreover, the authors applied this approach to analyze the whole high-content fluorescence images of Drosophila cells for further HCS-based gene function analysis.
The specificity of RNAi pathways is determined by several classes of small RNAs, which include siRNAs, piRNAs, endo-siRNAs, and microRNAs (miRNAs). These small RNAs are invariably incorporated into large Argonaute (Ago)-containing effector complexes known as RNA-induced silencing complexes (RISCs), which they guide to silencing targets. Both genetic and biochemical strategies have yielded conserved molecular components of small RNA biogenesis and effector machineries. However, given the complexity of these pathways, there are likely to be additional components and regulators that remain to be uncovered. We have undertaken a comparative and comprehensive RNAi screen to identify genes that impact three major Ago-dependent small RNA pathways that operate in Drosophila S2 cells. We identify subsets of candidates that act positively or negatively in siRNA, endo-siRNA, and miRNA pathways. Our studies indicate that many components are shared among all three Argonaute-dependent silencing pathways, though each is also impacted by discrete sets of genes.
Drosophila endogenous small RNAs are categorized according to their mechanisms of biogenesis and the Argonaute protein to which they bind. MicroRNAs are a class of ubiquitously expressed RNAs of approximately 22 nucleotides in length, which arise from structured precursors through the action of Drosha-Pasha and Dicer-1-Loquacious complexes. These join Argonaute-1 to regulate gene expression. A second endogenous small RNA class, the Piwi-interacting RNAs, bind Piwi proteins and suppress transposons. Piwi-interacting RNAs are restricted to the gonad, and at least a subset of these arises by Piwi-catalysed cleavage of single-stranded RNAs. Here we show that Drosophila generates a third small RNA class, endogenous small interfering RNAs, in both gonadal and somatic tissues. Production of these RNAs requires Dicer-2, but a subset depends preferentially on Loquacious rather than the canonical Dicer-2 partner, R2D2 (ref. 14). Endogenous small interfering RNAs arise both from convergent transcription units and from structured genomic loci in a tissue-specific fashion. They predominantly join Argonaute-2 and have the capacity, as a class, to target both protein-coding genes and mobile elements. These observations expand the repertoire of small RNAs in Drosophila, adding a class that blurs distinctions based on known biogenesis mechanisms and functional roles.
A major obstacle to creating precisely expressed transgenes lies in the epigenetic effects of the host chromatin that surrounds them. Here we present a strategy to overcome this problem, employing a Gal4-inducible luciferase assay to systematically quantify position effects of host chromatin and the ability of insulators to counteract these effects at phiC31 integration loci randomly distributed throughout the Drosophila genome. We identify loci that can be exploited to deliver precise doses of transgene expression to specific tissues. Moreover, we uncover a previously unrecognized property of the gypsy retrovirus insulator to boost gene expression to levels severalfold greater than at most or possibly all un-insulated loci, in every tissue tested. These findings provide the first opportunity to create a battery of transgenes that can be reliably expressed at high levels in virtually any tissue by integration at a single locus, and conversely, to engineer a controlled phenotypic allelic series by exploiting several loci. The generality of our approach makes it adaptable to other model systems to identify and modify loci for optimal transgene expression.
A fundamental concept in development is that secreted molecules such as Wingless (Wg) and Hedgehog (Hh) generate pattern by inducing cell fate. By following markers of cellular identity posterior to the Wg- and Hh-expressing cells in the Drosophila dorsal embryonic epidermis, we provide evidence that neither Wg nor Hh specifies the identity of the cell types they pattern. Rather, they maintain pre-existing cellular identities that are otherwise unstable and progress stepwise towards a default fate. Wg and Hh therefore generate pattern by inhibiting specific switches in cell identity, showing that the specification and the patterning of a given cell are uncoupled. Sequential binary decisions without induction of cell identity give rise to both the groove cells and their posterior neighbors. The combination of independent progression of cell identity and arrest of progression by signals facilitates accurate patterning of an extremely plastic developing epidermis.
While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi) on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new genes that have important functions in the nervous system.