Publications

The transition from G1 into DNA replication (S phase) is an emergent behavior resulting from dynamic and complex interactions between cyclin-dependent kinases (Cdks), Cdk inhibitors (CKIs), and the anaphase-promoting complex/cyclosome (APC/C). Understanding the cellular decision to commit to S phase requires a quantitative description of these interactions. We apply quantitative imaging of single human cells to track the expression of G1/S regulators and use these data to parametrize a stochastic mathematical model of the G1/S transition. We show that a rapid, proteolytic, double-negative feedback loop between Cdk2:Cyclin and the Cdk inhibitor p27(Kip1) drives a switch-like entry into S phase. Furthermore, our model predicts that increasing Emi1 levels throughout S phase are critical in maintaining irreversibility of the G1/S transition, which we validate using Emi1 knockdown and live imaging of G1/S reporters. This work provides insight into the general design principles of the signaling networks governing the temporally abrupt transitions between cell-cycle phases..

Although a great deal is known about the signaling events that promote nuclear translocation of NF-κB, how cellular biophysics and the microenvironment might regulate the dynamics of this pathway is poorly understood. In this study, we used high-content image analysis and Bayesian network modeling to ask whether cell shape and context features influence NF-κB activation using the inherent variability present in unperturbed populations of breast tumor and non-tumor cell lines. Cell–cell contact, cell and nuclear area, and protrusiveness all contributed to variability in NF-κB localization in the absence and presence of TNFα. Higher levels of nuclear NF-κB were associated with mesenchymal-like versus epithelial-like morphologies, and RhoA-ROCK-myosin II signaling was critical for mediating shape-based differences in NF-κB localization and oscillations. Thus, mechanical factors such as cell shape and the microenvironment can influence NF-κB signaling and may in part explain how different phenotypic outcomes can arise from the same chemical cues..

How multiple spindle assembly pathways are integrated to drive bipolar spindle assembly is poorly understood. We performed an image-based double RNAi screen to identify genes encoding Microtubule-Associated Proteins (MAPs) that interact with the highly conserved ch-TOG gene to regulate bipolar spindle assembly in human cells. We identified a ch-TOG centred network of genetic interactions which promotes centrosome-mediated microtubule polymerisation, leading to the incorporation of microtubules polymerised by all pathways into a bipolar structure [corrected]. Our genetic screen also reveals that ch-TOG maintains a dynamic microtubule population, in part, through modulating HSET activity. ch-TOG ensures that spindle assembly is robust to perturbation but sufficiently dynamic such that spindles can explore a diverse shape space in search of structures that can align chromosomes..

Melanoma cells can adopt two functionally distinct forms, amoeboid and mesenchymal, which facilitates their ability to invade and colonize diverse environments during the metastatic process. Using quantitative imaging of single living tumor cells invading three-dimensional collagen matrices, in tandem with unsupervised computational analysis, we found that melanoma cells can switch between amoeboid and mesenchymal forms via two different routes in shape space--an apolar and polar route. We show that whereas particular Rho-family GTPases are required for the morphogenesis of amoeboid and mesenchymal forms, others are required for transitions via the apolar or polar route and not amoeboid or mesenchymal morphogenesis per se. Altering the transition rates between particular routes by depleting Rho-family GTPases can change the morphological heterogeneity of cell populations. The apolar and polar routes may have evolved in order to facilitate conversion between amoeboid and mesenchymal forms, as cells are either searching for, or attracted to, particular migratory cues, respectively..

Visualization is essential for data interpretation, hypothesis formulation and communication of results. However, there is a paucity of visualization methods for image-derived data sets generated by high-content analysis in which complex cellular phenotypes are described as high-dimensional vectors of features. Here we present a visualization tool, PhenoPlot, which represents quantitative high-content imaging data as easily interpretable glyphs, and we illustrate how PhenoPlot can be used to improve the exploration and interpretation of complex breast cancer cell phenotypes..

We show that phospholipid anabolism does not occur uniformly during the metazoan cell cycle. Transition to S-phase is required for optimal mobilization of lipid precursors, synthesis of specific phospholipid species and endoplasmic reticulum (ER) homeostasis. Average changes observed in whole-cell phospholipid composition, and total ER lipid content, upon stimulation of cell growth can be explained by the cell cycle distribution of the population. TORC1 promotes phospholipid anabolism by slowing S/G2 progression. The cell cycle stage-specific nature of lipid biogenesis is dependent on p53. We propose that coupling lipid metabolism to cell cycle progression is a means by which cells have evolved to coordinate proliferation with cell and organelle growth..

Through statistical analysis of datasets describing single cell shape following systematic gene depletion, we have found that the morphological landscapes explored by cells are composed of a small number of attractor states. We propose that the topology of these landscapes is in large part determined by cell-intrinsic factors, such as biophysical constraints on cytoskeletal organization, and reflects different stable signaling and/or transcriptional states. Cell-extrinsic factors act to determine how cells explore these landscapes, and the topology of the landscapes themselves. Informational stimuli primarily drive transitions between stable states by engaging signaling networks, while mechanical stimuli tune, or even radically alter, the topology of these landscapes. As environments fluctuate, the topology of morphological landscapes explored by cells dynamically adapts to these fluctuations. Finally we hypothesize how complex cellular and tissue morphologies can be generated from a limited number of simple cell shapes..

One goal of cell biology is to understand how cells adopt different shapes in response to varying environmental and cellular conditions. Achieving a comprehensive understanding of the relationship between cell shape and environment requires a systems-level understanding of the signalling networks that respond to external cues and regulate the cytoskeleton. Classical biochemical and genetic approaches have identified thousands of individual components that contribute to cell shape, but it remains difficult to predict how cell shape is generated by the activity of these components using bottom-up approaches because of the complex nature of their interactions in space and time. Here, we describe the regulation of cellular shape by signalling systems using a top-down approach. We first exploit the shape diversity generated by systematic RNAi screening and comprehensively define the shape space a migratory cell explores. We suggest a simple Boolean model involving the activation of Rac and Rho GTPases in two compartments to explain the basis for all cell shapes in the dataset. Critically, we also generate a probabilistic graphical model to show how cells explore this space in a deterministic, rather than a stochastic, fashion. We validate the predictions made by our model using live-cell imaging. Our work explains how cross-talk between Rho and Rac can generate different cell shapes, and thus morphological heterogeneity, in genetically identical populations..

The function and capacity of the endoplasmic reticulum (ER) is determined by multiple processes ranging from the local regulation of peptide translation, translocation, and folding, to global changes in lipid composition. ER homeostasis thus requires complex interactions amongst numerous cellular components. However, describing the networks that maintain ER function during changes in cell behavior and environmental fluctuations has, to date, proven difficult. Here we perform a systems-level analysis of ER homeostasis, and find that although signaling networks that regulate ER function have a largely modular architecture, the TORC1-SREBP signaling axis is a central node that integrates signals emanating from different sub-networks. TORC1-SREBP promotes ER homeostasis by regulating phospholipid biosynthesis and driving changes in ER morphology. In particular, our network model shows TORC1-SREBP serves to integrate signals promoting growth and G1-S progression in order to maintain ER function during cell proliferation..

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The mapping of signalling networks is one of biology's most important goals. However, given their size, complexity and dynamic nature, obtaining comprehensive descriptions of these networks has proven extremely challenging. A fast and cost-effective means to infer connectivity between genes on a systems-level is by quantifying the similarity between high-dimensional cellular phenotypes following systematic gene depletion. This review describes the methodology used to map signalling networks using data generated in the context of RNAi screens..

Bakal studies the signaling networks that control cell shape..

Actin-based stress fiber formation is coupled to microtubule depolymerization through the local activation of RhoA. While the RhoGEF Lfc has been implicated in this cytoskeleton coupling process, it has remained elusive how Lfc is recruited to microtubules and how microtubule recruitment moderates Lfc activity. Here, we demonstrate that the dynein light chain protein Tctex-1 is required for localization of Lfc to microtubules. Lfc residues 139-161 interact with Tctex-1 at a site distinct from the cleft that binds dynein intermediate chain. An NMR-based GEF assay revealed that interaction with Tctex-1 represses Lfc nucleotide exchange activity in an indirect manner that requires both polymerized microtubules and phosphorylation of S885 by PKA. We show that inhibition of Lfc by Tctex-1 is dynein dependent. These studies demonstrate a pivotal role of Tctex-1 as a negative regulator of actin filament organization through its control of Lfc in the crosstalk between microtubule and actin cytoskeletons..

Reactive Oxygen Species (ROS) are a natural by-product of cellular growth and proliferation, and are required for fundamental processes such as protein-folding and signal transduction. However, ROS accumulation, and the onset of oxidative stress, can negatively impact cellular and genomic integrity. Signalling networks have evolved to respond to oxidative stress by engaging diverse enzymatic and non-enzymatic antioxidant mechanisms to restore redox homeostasis. The architecture of oxidative stress response networks during periods of normal growth, and how increased ROS levels dynamically reconfigure these networks are largely unknown. In order to gain insight into the structure of signalling networks that promote redox homeostasis we first performed genome-scale RNAi screens to identify novel suppressors of superoxide accumulation. We then infer relationships between redox regulators by hierarchical clustering of phenotypic signatures describing how gene inhibition affects superoxide levels, cellular viability, and morphology across different genetic backgrounds. Genes that cluster together are likely to act in the same signalling pathway/complex and thus make "functional interactions". Moreover we also calculate differential phenotypic signatures describing the difference in cellular phenotypes following RNAi between untreated cells and cells submitted to oxidative stress. Using both phenotypic signatures and differential signatures we construct a network model of functional interactions that occur between components of the redox homeostasis network, and how such interactions become rewired in the presence of oxidative stress. This network model predicts a functional interaction between the transcription factor Jun and the IRE1 kinase, which we validate in an orthogonal assay. We thus demonstrate the ability of systems-biology approaches to identify novel signalling events..

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A report of the Wellcome Trust Functional Genomics and Systems Biology Conference, Hinxton, UK, 29 November to 1 December 2011..

Drosophila melanogaster has a long history as a model organism with several unique features that make it an ideal research tool for the study of the relationship between genotype and phenotype. Importantly fundamental genetic principles as well as key human disease genes have been uncovered through the use of Drosophila. The contribution of the fruit fly to science and medicine continues in the postgenomic era as cell-based Drosophila RNAi screens are a cost-effective and scalable enabling technology that can be used to quantify the contribution of different genes to diverse cellular processes. Drosophila high-throughput screens can also be used as integral part of systems-level approaches to describe the architecture and dynamics of cellular networks..

Physical interactions between cells and the extracellular matrix (ECM) guide directional migration by spatially controlling where cells form focal adhesions (FAs), which in turn regulate the extension of motile processes. Here we show that physical control of directional migration requires the FA scaffold protein paxillin. Using single-cell sized ECM islands to constrain cell shape, we found that fibroblasts cultured on square islands preferentially activated Rac and extended lamellipodia from corner, rather than side regions after 30 min stimulation with PDGF, but that cells lacking paxillin failed to restrict Rac activity to corners and formed small lamellipodia along their entire peripheries. This spatial preference was preceded by non-spatially constrained formation of both dorsal and lateral membrane ruffles from 5-10 min. Expression of paxillin N-terminal (paxN) or C-terminal (paxC) truncation mutants produced opposite, but complementary, effects on lamellipodia formation. Surprisingly, pax-/- and paxN cells also formed more circular dorsal ruffles (CDRs) than pax+ cells, while paxC cells formed fewer CDRs and extended larger lamellipodia even in the absence of PDGF. In a two-dimensional (2D) wound assay, pax-/- cells migrated at similar speeds to controls but lost directional persistence. Directional motility was rescued by expressing full-length paxillin or the N-terminus alone, but paxN cells migrated more slowly. In contrast, pax-/- and paxN cells exhibited increased migration in a three-dimensional (3D) invasion assay, with paxN cells invading Matrigel even in the absence of PDGF. These studies indicate that paxillin integrates physical and chemical motility signals by spatially constraining where cells will form motile processes, and thereby regulates directional migration both in 2D and 3D. These findings also suggest that CDRs may correspond to invasive protrusions that drive cell migration through 3D extracellular matrices..

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..

Recently reporting in Nature, Collinet et al. describes the application of quantitative multiparametric methods to a genome-wide RNAi screen for regulators of endocytosis. The study illustrates the power of this approach beyond the identification of new endocytic components to providing insights into the design principles of the endocytic system..

RNA interference (RNAi) is an effective tool for genome-scale, high-throughput analysis of gene function. In the past five years, a number of genome-scale RNAi high-throughput screens (HTSs) have been done in both Drosophila and mammalian cultured cells to study diverse biological processes, including signal transduction, cancer biology, and host cell responses to infection. Results from these screens have led to the identification of new components of these processes and, importantly, have also provided insights into the complexity of biological systems, forcing new and innovative approaches to understanding functional networks in cells. Here, we review the main findings that have emerged from RNAi HTS and discuss technical issues that remain to be improved, in particular the verification of RNAi results and validation of their biological relevance. Furthermore, we discuss the importance of multiplexed and integrated experimental data analysis pipelines to RNAi HTS..

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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..

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..

Cellular signaling networks have evolved to enable swift and accurate responses, even in the face of genetic or environmental perturbation. Thus, genetic screens may not identify all the genes that regulate different biological processes. Moreover, although classical screening approaches have succeeded in providing parts lists of the essential components of signaling networks, they typically do not provide much insight into the hierarchical and functional relations that exist among these components. We describe a high-throughput screen in which we used RNA interference to systematically inhibit two genes simultaneously in 17,724 combinations to identify regulators of Drosophila JUN NH(2)-terminal kinase (JNK). Using both genetic and phosphoproteomics data, we then implemented an integrative network algorithm to construct a JNK phosphorylation network, which provides structural and mechanistic insights into the systems architecture of JNK signaling..

Although classical genetic and biochemical approaches have identified hundreds of proteins that function in the dynamic remodeling of cell shape in response to upstream signals, there is currently little systems-level understanding of the organization and composition of signaling networks that regulate cell morphology. We have developed quantitative morphological profiling methods to systematically investigate the role of individual genes in the regulation of cell morphology in a fast, robust, and cost-efficient manner. We analyzed a compendium of quantitative morphological signatures and described the existence of local signaling networks that act to regulate cell protrusion, adhesion, and tension..

We used DNA microarray screening to identify Ckap2 (cytoskeleton associated protein 2) as a novel p53 target gene in a mouse erythroleukemia cell line. DNA damage induces human and mouse CKAP2 expression in a p53-dependent manner and p53 activates the Ckap2 promoter. Overexpressed Ckap2 colocalizes with and stabilizes microtubules. In p53-null cells, overexpression of Ckap2 induces tetraploidy with aberrant centrosome numbers, suggesting disturbed mitosis and cytokinesis. In p53-competent cells, Ckap2 does not induce tetraploidy but activates p53-mediated cell cycle arrest and apoptosis. Our data suggest the existence of a functional positive feedback loop in which Ckap2 activates the G1 tetraploidy checkpoint and prevents aneuploidy..

Rho GTPases regulate reorganization of actin and microtubule cytoskeletal structures during both interphase and mitosis. The timing and subcellular compartment in which Rho GTPases are activated is controlled by the large family of Rho GTP exchange factors (RhoGEFs). Here, we show that the microtubule-associated RhoGEF Lfc is required for the formation of the mitotic spindle during prophase/prometaphase. The inability of cells to assemble a functioning spindle after Lfc inhibition resulted in a delay in mitosis and an accumulation of prometaphase cells. Inhibition of Lfc's primary target Rho GTPase during prophase/prometaphase, or expression of a catalytically inactive mutant of Lfc, also prevented normal spindle assembly and resulted in delays in mitotic progression. Coinjection of constitutively active Rho GTPase rescued the spindle defects caused by Lfc inhibition, suggesting the requirement of RhoGTP in regulating spindle assembly. Lastly, we implicate mDia1 as an important effector of Lfc signaling. These findings demonstrate a role for Lfc, Rho, and mDia1 during mitosis..

Carma1 (also known as caspase recruitment domain [CARD]11, Bimp3) is a CARD-containing membrane-associated guanylate kinase family protein that plays an essential role in antigen receptor-induced nuclear factor kappaB activation. We investigated the role of Carma1 in the assembly of signaling molecules at the immune synapse using a peptide-specific system. We report that Carma1 is essential for peptide-induced interleukin 2 and interferon gamma production, but dispensable for proliferation in T cells. Recruitment and distribution of T cell receptor, lymphocyte function associated 1, lipid rafts, and protein kinase C (PKC)theta; to central and peripheral immune synapse regions occur normally in Carma1-/- T cells. Carma1 controls entry of IkappaB kinase (IKK) into lipid raft aggregates and the central region of the immune synapse, as well as activation of IKK downstream of PKC. Our data provide the first genetic evidence on a new class of molecular scaffold that controls entry of defined signaling components, IKK, into the central supramolecular activation cluster at T cell-antigen-presenting cell interfaces without having any apparent effect on the overall organization and formation of immune synapses..

Because survivin-null embryos die at an early embryonic stage, the role of survivin in thymocyte development is unknown. We have investigated the role by deleting the survivin gene only in the T lineage and show here that loss of survivin blocks the transition from CD4- CD8- double negative (DN) thymocytes to CD4+ CD8+ double positive cells. Although the pre-T cell receptor signaling pathway is intact in survivin-deficient thymocytes, the cells cannot respond to its signals. In response to proliferative stimuli, cycling survivin-deficient DN cells exhibit cell cycle arrest, a spindle formation defect, and increased cell death. Strikingly, loss of survivin activates the tumor suppressor p53. However, the developmental defects caused by survivin deficiency cannot be rescued by p53 inactivation or introduction of Bcl-2. These lines of evidence indicate that developing thymocytes depend on the cytoprotective function of survivin and that this function is tightly coupled to cell proliferation but independent of p53 and Bcl-2. Thus, survivin plays a critical role in early thymocyte development..

Members of the MAGUK family proteins cluster receptors and intracellular signaling molecules at the neuronal synapse. We report that genetic inactivation of the MAGUK family protein CARD11/Carma1/Bimp3 results in a complete block in T and B cell immunity. CARD11 is essential for antigen receptor- and PKC-mediated proliferation and cytokine production in T and B cells due to a selective defect in JNK and NFkappaB activation. Moreover, B cell proliferation and JNK activation were impaired upon stimulation of TLR4 with lipopolysaccharide, indicating that CARD11 is involved in both the innate and adaptive immune systems. Our results show that the same family of molecules are critical regulators of neuronal synapses and immune receptor signaling..

Reversible phosphorylation of serine, threonine and tyrosine residues by the interplay of protein kinases and phosphatases plays a key role in regulating many different cellular processes in eukaryotic organisms. A diversity of control mechanisms exists to influence the activity of these enzymes and choreograph the correct concert of protein modifications to achieve distinct biological responses. Such enzymes and their adaptor molecules were long thought to be specific to eukaryotic cellular processes. However, there is increasing evidence that many prokaryotes achieve regulation of key components of cellular function through similar mechanisms..