Person:

Perrimon, Norbert

The fruit fly Drosophila has contributed significantly to our general understanding of the basic principles of signaling, cell and developmental biology, and neurobiology. However, answers to questions pertaining to energy metabolism have been so far mostly addressed in more complex model organisms such as mice. We review in this article recent studies that show how the genetic tractability and simplicity of Drosophila are being used to identify novel regulatory mechanisms at the organismal level, and to query the co-ordination between energy metabolism and other processes such as neurodegeneration, circadian rhythms, immunity, and tumor biology.

Background: The diversity of metazoan cell shapes is influenced by the dynamic cytoskeletal network. With the advent of RNA-interference (RNAi) technology, it is now possible to screen systematically for genes controlling specific cell-biological processes, including those required to generate distinct morphologies. Results: We adapted existing RNAi technology in Drosophila cell culture for use in high-throughput screens to enable a comprehensive genetic dissection of cell morphogenesis. To identify genes responsible for the characteristic shape of two morphologically distinct cell lines, we performed RNAi screens in each line with a set of double-stranded RNAs (dsRNAs) targeting 994 predicted cell shape regulators. Using automated fluorescence microscopy to visualize actin filaments, microtubules and DNA, we detected morphological phenotypes for 160 genes, one-third of which have not been previously characterized in vivo. Genes with similar phenotypes corresponded to known components of pathways controlling cytoskeletal organization and cell shape, leading us to propose similar functions for previously uncharacterized genes. Furthermore, we were able to uncover genes acting within a specific pathway using a co-RNAi screen to identify dsRNA suppressors of a cell shape change induced by Pten dsRNA. Conclusions: Using RNAi, we identified genes that influence cytoskeletal organization and morphology in two distinct cell types. Some genes exhibited similar RNAi phenotypes in both cell types, while others appeared to have cell-type-specific functions, in part reflecting the different mechanisms used to generate a round or a flat cell morphology.

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.

Intestinal epithelia are maintained by intestinal stem cells (ISCs) that divide to replace dying absorptive and secretory cells that make up this tissue. Lineage labeling studies, both in vertebrates and Drosophila, have revealed the relationships between ISCs and their progeny. In addition, a number of signaling pathways involved in ISC proliferation and differentiation have been identified. Further studies will clarify the signals originating from the ISC niche and determine the processes that control the number and uniform distribution of niches throughout the epithelium.

Phosphate is required for many important cellular processes and having too little phosphate or too much can cause disease and reduce life span in humans. However, the mechanisms underlying homeostatic control of extracellular phosphate levels and cellular effects of phosphate are poorly understood. Here, we establish Drosophila melanogaster as a model system for the study of phosphate effects. We found that Drosophila larval development depends on the availability of phosphate in the medium. Conversely, life span is reduced when adult flies are cultured on high phosphate medium or when hemolymph phosphate is increased in flies with impaired Malpighian tubules. In addition, RNAi-mediated inhibition of MAPK-signaling by knockdown of Ras85D, phl/D-Raf or Dsor1/MEK affects larval development, adult life span and hemolymph phosphate, suggesting that some in vivo effects involve activation of this signaling pathway by phosphate. To identify novel genetic determinants of phosphate responses, we used Drosophila hemocyte-like cultured cells (S2R+) to perform a genome-wide RNAi screen using MAPK activation as the readout. We identified a number of candidate genes potentially important for the cellular response to phosphate. Evaluation of 51 genes in live flies revealed some that affect larval development, adult life span and hemolymph phosphate levels.

Although a large number of actin-binding proteins and their regulators have been identified through classical approaches, gaps in our knowledge remain. Here, we used genome-wide RNA interference as a systematic method to define metazoan actin regulators based on visual phenotype. Using comparative screens in cultured Drosophila and human cells, we generated phenotypic profiles for annotated actin regulators together with proteins bearing predicted actin-binding domains. These phenotypic clusters for the known metazoan "actinome" were used to identify putative new core actin regulators, together with a number of genes with conserved but poorly studied roles in the regulation of the actin cytoskeleton, several of which we studied in detail. This work suggests that although our search for new components of the core actin machinery is nearing saturation, regulation at the level of nuclear actin export, RNA splicing, ubiquitination, and other upstream processes remains an important but unexplored frontier of actin biology.

FlyRNAi (http://www.flyrnai.org), the database and website of the Drosophila RNAi Screening Center (DRSC) at Harvard Medical School, serves a dual role, tracking both production of reagents for RNA interference (RNAi) screening in Drosophila cells and RNAi screen results. The database and website is used as a platform for community availability of protocols, tools, and other resources useful to researchers planning, conducting, analyzing or interpreting the results of Drosophila RNAi screens. Based on our own experience and user feedback, we have made several changes. Specifically, we have restructured the database to accommodate new types of reagents; added information about new RNAi libraries and other reagents; updated the user interface and website; and added new tools of use to the Drosophila community and others. Overall, the result is a more useful, flexible and comprehensive website and database.

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.

Background: The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens. Results: Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using Drosophila embryos [Additional files 1, 2], dataset for cell cycle phase identification using HeLa cells [Additional files 1, 3, 4] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a Drosophila genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms. Conclusion: We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens.

The major facilitator superfamily (MFS) transporter (Pho84) and the type III transporter (Pho84) are responsible for metabolic effects of inorganic phosphate in yeast. While the (Pho84) ortholog Pit1 was also shown to be involved in phosphate-activated MAPK in mammalian cells, it is currently unknown, whether orthologs of (Pho84) have a role in phosphate-sensing in metazoan species. We show here that the activation of MAPK by phosphate observed in mammals is conserved in (Drosophila) cells, and used this assay to characterize the roles of putative phosphate transporters. Surprisingly, while we found that RNAi-mediated knockdown of the fly (Pho84) ortholog dPit had little effect on the activation of MAPK in (Drosophila) S2R+ cells by phosphate, two (Pho84)/SLC17A1–9 MFS orthologs (MFS10 and MFS13) specifically inhibited this response. Further, using a (Xenopus) oocyte assay, we show that MSF13 mediates uptake of [33P]-orthophosphate in a sodium-dependent fashion. Consistent with a role in phosphate physiology, MSF13 is expressed highest in the (Drosophila) crop, midgut, Malpighian tubule, and hindgut. Altogether, our findings provide the first evidence that (Pho84) orthologs mediate cellular effects of phosphate in metazoan cells. Finally, while phosphate is essential for (Drosophila) larval development, loss of MFS13 activity is compatible with viability indicating redundancy at the levels of the transporters.