Professor Chris Bakal
Group Leader: Dynamical Cell Systems
Biography
Professor Chris Bakal studies the biological switches that cause cells to change shape, become cancerous and spread around the body. By understanding how these switches work, scientists may one day find a way to control them through drugs or other therapies. He is Leader of the Dynamical Cell Systems Group within the Division of Cancer Biology at The Institute of Cancer Research, London.
Cells are able to assume a wide variety of complex shapes in order to carry out different roles and Professor Bakal’s group examines the genetic and biochemical mechanisms that underpin these shape changes.
Their research covers how both environmental and genetic variation affects cell shape. Ultimately, he aims to understand how normal and cancerous cells can adopt different shapes and why metastatic cancer develops in some people but not others.
“I am fascinated by the fact that our cells have the ability to take so many different shapes,” Professor Bakal says. “How is it that one cell can become a thin-branched neuron that is many feet long, whereas others become flat, large skin cells? Understanding the ability of cells to assume different shapes is key to understanding cancer, since metastatic cells have to change their shape in order to move to different parts of the body.”
Professor Bakal received his undergraduate degree in Biochemistry at the University of British Columbia and his PhD in Medical Biophysics at the University of Toronto and the Ontario Cancer Institute.
He joined Harvard Medical School and the Howard Hughes Medical Institute as a postdoctoral fellow in 2004. In 2006, he also became an affiliate of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology, as well as an affiliate of the Broad Institute.
While at Harvard Medical School, Professor Bakal developed his interest in the communication networks between cells that control their migration around the body and are therefore involved in cancer spread.
He also devised an automated computer programme used to recognise the shape of cells and infer the corresponding genetic alterations that have occurred in the cell. The new technology can be used to predict if a cell is cancerous or non-cancerous, a previously time-consuming job performed by human pathologists.
In 2009, Professor Bakal started his own research group at the ICR on a Wellcome Trust Research Career Development Fellowship. His group is part of the integrative network biology initiative, which is a collaborative research effort between scientists of different disciplines to study the biological processes involved in cancer metastasis.
“The ICR was the only place in the world where I could work in an integrative fashion to develop new experimental and computational technologies to study signalling networks regulating cell shape,” Professor Bakal says.
“I hope that we can use many of the technologies that I have developed to gain a holistic and systems-level understanding into how cancer cells metastasise. If we can do this it will open the door for effective personalised treatment and, importantly, allow us to make full use of all the sequencing information that is available.”
Professor Bakal has received several awards including the Dorsett L. Spurgeon Award in 2007 as the top postdoctoral fellow at Harvard Medical School. In 2009, he received an Outstanding Research Award from Nature Biotechnology. While on a Leukaemia and Lymphoma Society Fellowship from 2005 to 2009, he was twice honoured by the society’s volunteers for his research efforts.
Outside work, Professor Bakal was a former world-ranked downhill ski racer who specialised in the super-giant slalom event. He is also a former track and field athlete who finished in the top eight three times at the Canadian National Championships 1500m event and has also run a mile in 4 minutes and 3 seconds.
In 2016, he was awarded the title of Reader at the ICR.
Professor Bakal is a member of the Cancer Research UK Convergence Science Centre, which brings together leading researchers in engineering, physical sciences, life sciences and medicine to develop innovative ways to address challenges in cancer.
Bsc Biochemistry, University of British Columbia.
Postdoctoral Fellow, Harvard Medical School.
PhD Medical Biophysics, University of Toronto.
Award for Outstanding Research Achievement, Nature Biotechnology, 2009.
Keystone Scholarship, Keystone Symposia, 2006.
Lilly Singapore Centre for Drug Discovery Keystone Scholarship, Lilly Singapore Centre for Drug Discovery, 2009.
Dorsett L. Spurgeon Distinguished Research Award, Harvard Medical School, 2007.
Allison Gurnitz Leukemia and Lymphoma Society Sponsorship, Leukemia and Lymphoma Society, 2007.
Citrix Leukemia and Lymphoma Society Sponsorship, Leukemia and Lymphoma Society, 2009.
EACR Cancer Researcher Highly Commended Award, European Association for Cancer Research, 2011.
Emerging Investigator, Molecular Biosystems Journal, 2012.
AstraZeneca Young Scientist Frank Rose Award, British Association for Cancer Research, 2013.
Merrimack Pharmaceuticals Prize in Systems Biology, Council for Systems Biology in Boston, 2015.
Future Leaders in Cancer Research Prize, Cancer Research UK, 2015.
Editorial Boards
Molecular Omics, 2019.
“Interdisciplinary PhDs” and “Transition Postdoctoral Fellowships”, Member, Swiss National Science Foundation (SNSF), 2013.
Pioneer Award, Member, Cancer Research UK, 2015.
UKRI Physics of Life External Programme Advisory Board, Member, UKRI, 2019.
British Society for Cell Biology Committee, Member, British Society for Cell Biology, 2019.
BBSRC Committee Pool of Experts, Member, BBSRC, 2018.
Related pages
Types of Publications
Journal articles
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
A report of the Wellcome Trust Functional Genomics and Systems Biology Conference, Hinxton, UK, 29 November to 1 December 2011.
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.
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.
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.
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.
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.
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.
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.
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.
Bakal studies the signaling networks that control cell shape.
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.
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.
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.
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.
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.
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.
Types of Publications
Journal articles
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
A report of the Wellcome Trust Functional Genomics and Systems Biology Conference, Hinxton, UK, 29 November to 1 December 2011.
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.
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.
<h4>Background</h4>The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.<h4>Methods and findings</h4>We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D) in solid tumors, termed the tumor ecosystem diversity index (EDI), using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3) breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2) breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of TP53 mutation status (multivariate analysis test set, p = 9 × 10-4, hazard ratio = 1.47, 95% CI 1.17-1.84; validation set, p = 0.0011, hazard ratio = 1.78, 95% CI 1.26-2.52). Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.<h4>Conclusions</h4>To our knowledge, this is the first study to couple unbiased measures of microenvironmental heterogeneity with genomic alterations to predict breast cancer clinical outcome. We propose a clinically relevant role of microenvironmental heterogeneity for advanced breast tumors, and highlight that ecological statistics can be translated into medical advances for identifying a new type of biomarker and, furthermore, for understanding the synergistic interplay of microenvironmental heterogeneity with genomic alterations in cancer cells.
Inositol Requiring Enzyme-1 (IRE1) is the most conserved transducer of the Unfolded Protein Response (UPR), a surveillance mechanism that ensures homeostasis of the endoplasmic reticulum (ER) in eukaryotes. IRE1 activation orchestrates adaptive responses, including lipid anabolism, metabolic reprogramming, increases in protein folding competency, and ER expansion/remodeling. However, we still know surprisingly little regarding the principles by which this ER transducer is deactivated upon ER stress clearance. Here we show that Protein Kinase B-mechanistic Target of Rapamycin (PKB/AKT-mTOR) signaling controls the dynamics of IRE1 deactivation by regulating ER-mitochondria physical contacts and the autophosphorylation state of IRE1. AKT-mTOR-mediated attenuation of IRE1 activity is important for ER remodelling dynamics and cell survival in the face of recursive, transient ER stress. Our observations suggest that IRE1 attenuation is an integral component of anabolic programmes regulated by AKT-mTOR. We suggest that AKT-mTOR activity is part of a 'timing mechanism' to deactivate IRE1 immediately following engagement of the UPR, in order to limit prolonged IRE1 RNAse activity that could lead to damaging inflammation or apoptosis.
Human cells that suffer mild DNA damage can enter a reversible state of growth arrest known as quiescence. This decision to temporarily exit the cell cycle is essential to prevent the propagation of mutations, and most cancer cells harbor defects in the underlying control system. Here we present a mechanistic mathematical model to study the proliferation-quiescence decision in nontransformed human cells. We show that two bistable switches, the restriction point (RP) and the G1/S transition, mediate this decision by integrating DNA damage and mitogen signals. In particular, our data suggest that the cyclin-dependent kinase inhibitor p21 (Cip1/Waf1), which is expressed in response to DNA damage, promotes quiescence by blocking positive feedback loops that facilitate G1 progression downstream of serum stimulation. Intriguingly, cells exploit bistability in the RP to convert graded p21 and mitogen signals into an all-or-nothing cell-cycle response. The same mechanism creates a window of opportunity where G1 cells that have passed the RP can revert to quiescence if exposed to DNA damage. We present experimental evidence that cells gradually lose this ability to revert to quiescence as they progress through G1 and that the onset of rapid p21 degradation at the G1/S transition prevents this response altogether, insulating S phase from mild, endogenous DNA damage. Thus, two bistable switches conspire in the early cell cycle to provide both sensitivity and robustness to external stimuli.
Spiradenoma and cylindroma are distinctive skin adnexal tumors with sweat gland differentiation and potential for malignant transformation and aggressive behaviour. We present the genomic analysis of 75 samples from 57 representative patients including 15 cylindromas, 17 spiradenomas, 2 cylindroma-spiradenoma hybrid tumors, and 24 low- and high-grade spiradenocarcinoma cases, together with morphologically benign precursor regions of these cancers. We reveal somatic or germline alterations of the CYLD gene in 15/15 cylindromas and 5/17 spiradenomas, yet only 2/24 spiradenocarcinomas. Notably, we find a recurrent missense mutation in the kinase domain of the ALPK1 gene in spiradenomas and spiradenocarcinomas, which is mutually exclusive from mutation of CYLD and can activate the NF-κB pathway in reporter assays. In addition, we show that high-grade spiradenocarcinomas carry loss-of-function TP53 mutations, while cylindromas may have disruptive mutations in DNMT3A. Thus, we reveal the genomic landscape of adnexal tumors and therapeutic targets.
Mechanics and biochemical signaling are both often deregulated in cancer, leading toincreased cell invasiveness, proliferation, and survival. The dynamics and interactions of cytoskeletal components control basic mechanical properties, such as cell tension, stiffness, and engagement with the extracellular environment, which can lead to extracellular matrix remodeling. Intracellular mechanics can alter signaling and transcription factors, impacting cell decision making. Additionally, signaling from soluble and mechanical factors in the extracellular environment, such as substrate stiffness and ligand density, can modulate cytoskeletal dynamics. Computational models closely integrated with experimental support, incorporating cancer-specific parameters, can provide quantitative assessments and serve as predictive tools toward dissecting the feedback between signaling and mechanics and across multiple scales and domains in tumor progression.
Biomaterial substrates can be engineered to present topographical signals to cells which, through interactions between the material and active components of the cell membrane, regulate key cellular processes and guide cell fate decisions. However, targeting mechanoresponsive elements that reside within the intracellular domain is a concept that has only recently emerged. Here, we show that mesoporous silicon nanoneedle arrays interact simultaneously with the cell membrane, cytoskeleton, and nucleus of primary human cells, generating distinct responses at each of these cellular compartments. Specifically, nanoneedles inhibit focal adhesion maturation at the membrane, reduce tension in the cytoskeleton, and lead to remodeling of the nuclear envelope at sites of impingement. The combined changes in actin cytoskeleton assembly, expression and segregation of the nuclear lamina, and localization of Yes-associated protein (YAP) correlate differently from what is canonically observed upon stimulation at the cell membrane, revealing that biophysical cues directed to the intracellular space can generate heretofore unobserved mechanosensory responses. These findings highlight the ability of nanoneedles to study and direct the phenotype of large cell populations simultaneously, through biophysical interactions with multiple mechanoresponsive components.
Differentiated cells are epigenetically stable, but can be reprogrammed to pluripotency by expression of the OSKM transcription factors. Despite significant effort, relatively little is known about the cellular requirements for reprogramming and how they affect the properties of induced pluripotent stem cells. We have performed high-content screening with small interfering RNAs targeting 300 chromatin-associated factors and extracted colony-level quantitative features. This revealed five morphological phenotypes in early reprogramming, including one displaying large round colonies exhibiting an early block of reprogramming. Using RNA sequencing, we identified transcriptional changes associated with these phenotypes. Furthermore, double knockdown epistasis experiments revealed that BRCA1, BARD1, and WDR5 functionally interact and are required for the DNA damage response. In addition, the mesenchymal-to-epithelial transition is affected in Brca1, Bard1, and Wdr5 knockdowns. Our data provide a resource of chromatin-associated factors in early reprogramming and underline colony morphology as an important high-dimensional readout for reprogramming quality.
Loss-of-function (LOF) methods such as RNA interference (RNAi), antisense oligonucleotides or CRISPR-based genome editing provide unparalleled power for studying the biological function of genes of interest. However, a major concern is non-specific targeting, which involves depletion of transcripts other than those intended. Little work has been performed to characterize the off-target effects of these common LOF methods at the whole-transcriptome level. Here, we experimentally compared the non-specific activity of RNAi, antisense oligonucleotides and CRISPR interference (CRISPRi). All three methods yielded non-negligible off-target effects in gene expression, with CRISPRi also exhibiting strong clonal effects. As an illustrative example, we evaluated the performance of each method for determining the role of an uncharacterized long noncoding RNA (lncRNA). Several LOF methods successfully depleted the candidate lncRNA but yielded different sets of differentially expressed genes as well as a different cellular phenotype upon depletion. Similar discrepancies between methods were observed with a protein-coding gene (Ch-TOG/CKAP5) and another lncRNA (MALAT1). We suggest that the differences between methods arise due to method-specific off-target effects and provide guidelines for mitigating such effects in functional studies. Our recommendations provide a framework with which off-target effects can be managed to improve functional characterization of genes of interest.
<h4>Summary</h4>Live imaging studies give unparalleled insight into dynamic single cell behaviours and fate decisions. However, the challenge of reliably tracking single cells over long periods of time limits both the throughput and ease with which such studies can be performed. Here, we present NucliTrack, a cross platform solution for automatically segmenting, tracking and extracting features from fluorescently labelled nuclei. NucliTrack performs similarly to other state-of-the-art cell tracking algorithms, but NucliTrack's interactive, graphical interface makes it significantly more user friendly.<h4>Availability and implementation</h4>NucliTrack is available as a free, cross platform application and open source Python package. Installation details and documentation are at: http://nuclitrack.readthedocs.io/en/latest/ A video guide can be viewed online: https://www.youtube.com/watch?v=J6e0D9F-qSU Source code is available through Github: https://github.com/samocooper/nuclitrack. A Matlab toolbox is also available at: https://uk.mathworks.com/matlabcentral/fileexchange/61479-samocooper-nuclitrack-matlab.<h4>Contact</h4>[email protected].<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online.
<b>Purpose:</b> Triple-negative breast cancer (TNBC) is a heterogeneous subgroup of breast cancer that is associated with a poor prognosis. We evaluated the activity of CDK4/6 inhibitors across the TNBC subtypes and investigated mechanisms of sensitivity.<b>Experimental Design:</b> A panel of cell lines representative of TNBC was tested for <i>in vitro</i> and <i>in vivo</i> sensitivity to CDK4/6 inhibition. A fluorescent CDK2 activity reporter was used for single-cell analysis in conjunction with time-lapse imaging.<b>Results:</b> The luminal androgen receptor (LAR) subtype of TNBC was highly sensitive to CDK4/6 inhibition both <i>in vitro</i> (<i>P</i> < 0.001 LAR vs. basal-like) and <i>in vivo</i> in MDA-MB-453 LAR cell line xenografts. Single-cell analysis of CDK2 activity demonstrated differences in cell-cycle dynamics between LAR and basal-like cells. Palbociclib-sensitive LAR cells exit mitosis with low levels of CDK2 activity, into a quiescent state that requires CDK4/6 activity for cell-cycle reentry. Palbociclib-resistant basal-like cells exit mitosis directly into a proliferative state, with high levels of CDK2 activity, bypassing the restriction point and the requirement for CDK4/6 activity. High CDK2 activity after mitosis is driven by temporal deregulation of cyclin E1 expression. CDK4/6 inhibitors were synergistic with PI3 kinase inhibitors in <i>PIK3CA</i>-mutant TNBC cell lines, extending CDK4/6 inhibitor sensitivity to additional TNBC subtypes.<b>Conclusions:</b> Cell-cycle dynamics determine the response to CDK4/6 inhibition in TNBC. CDK4/6 inhibitors, alone and in combination, are a novel therapeutic strategy for specific subgroups of TNBC. <i>Clin Cancer Res; 23(18); 5561-72. ©2017 AACR</i>.
The dynamics of signalling networks that couple environmental conditions with cellular behaviour can now be characterised in exquisite detail using live single-cell imaging experiments. Recent improvements in our abilities to introduce fluorescent sensors into cells, coupled with advances in pipelines for quantifying and extracting single-cell data, mean that high-throughput systematic analyses of signalling dynamics are becoming possible. In this review, we consider current technologies that are driving progress in the scale and range of such studies. Moreover, we discuss novel approaches that are allowing us to explore how pathways respond to changes in inputs and even predict the fate of a cell based upon its signalling history and state.
Following DNA damage caused by exogenous sources, such as ionizing radiation, the tumour suppressor p53 mediates cell cycle arrest via expression of the CDK inhibitor, p21. However, the role of p21 in maintaining genomic stability in the absence of exogenous DNA-damaging agents is unclear. Here, using live single-cell measurements of p21 protein in proliferating cultures, we show that naturally occurring DNA damage incurred over S-phase causes p53-dependent accumulation of p21 during mother G2- and daughter G1-phases. High p21 levels mediate G1 arrest via CDK inhibition, yet lower levels have no impact on G1 progression, and the ubiquitin ligases CRL4<sup>Cdt2</sup> and SCF<sup>Skp2</sup> couple to degrade p21 prior to the G1/S transition. Mathematical modelling reveals that a bistable switch, created by CRL4<sup>Cdt2</sup>, promotes irreversible S-phase entry by keeping p21 levels low, preventing premature S-phase exit upon DNA damage. Thus, we characterize how p21 regulates the proliferation-quiescence decision to maintain genomic stability.
In order to metastasise, triple negative breast cancer (TNBC) must make dynamic changes in cell shape. The shape of all eukaryotic cells is regulated by Rho Guanine Nucleotide Exchange Factors (RhoGEFs), which activate Rho-family GTPases in response to mechanical and informational cues. In contrast, Rho GTPase-activating proteins (RhoGAPs) inhibit Rho GTPases. However, which RhoGEFs and RhoGAPS couple TNBC cell shape to changes in their environment is very poorly understood. Moreover, whether the activity of particular RhoGEFs and RhoGAPs become dysregulated as cells evolve the ability to metastasise is not clear. Towards the ultimate goal of identifying RhoGEFs and RhoGAPs that are essential for TNBC metastasis, we performed an RNAi screen to isolate RhoGEFs and RhoGAPs that contribute to the morphogenesis of the highly metastatic TNBC cell line LM2, and its less-metastatic parental cell line MDA-MB-231. For ~6 million cells from each cell line, we measured 127 different features following the depletion of 142 genes. Using a linear classifier scheme we also describe the morphological heterogeneity of each gene-depleted population.
The associations between clinical phenotypes (tumor grade, survival) and cell phenotypes, such as shape, signaling activity, and gene expression, are the basis for cancer pathology, but the mechanisms explaining these relationships are not always clear. The generation of large data sets containing information regarding cell phenotypes and clinical data provides an opportunity to describe these mechanisms. Here, we develop an image-omics approach to integrate quantitative cell imaging data, gene expression, and protein-protein interaction data to systematically describe a "shape-gene network" that couples specific aspects of breast cancer cell shape to signaling and transcriptional events. The actions of this network converge on NF-κB, and support the idea that NF-κB is responsive to mechanical stimuli. By integrating RNAi screening data, we identify components of the shape-gene network that regulate NF-κB in response to cell shape changes. This network was also used to generate metagene models that predict NF-κB activity and aspects of morphology such as cell area, elongation, and protrusiveness. Critically, these metagenes also have predictive value regarding tumor grade and patient outcomes. Taken together, these data strongly suggest that changes in cell shape, driven by gene expression and/or mechanical forces, can promote breast cancer progression by modulating NF-κB activation. Our findings highlight the importance of integrating phenotypic data at the molecular level (signaling and gene expression) with those at the cellular and tissue levels to better understand breast cancer oncogenesis.
Localisation and protein function are intimately linked in eukaryotes, as proteins are localised to specific compartments where they come into proximity of other functionally relevant proteins. Significant co-localisation of two proteins can therefore be indicative of their functional association. We here present COLA, a proteomics based strategy coupled with a bioinformatics framework to detect protein-protein co-localisations on a global scale. COLA reveals functional interactions by matching proteins with significant similarity in their subcellular localisation signatures. The rapid nature of COLA allows mapping of interactome dynamics across different conditions or treatments with high precision.
Mechanical signals from the extracellular matrix (ECM) and cellular geometry regulate the nuclear translocation of transcriptional regulators such as Yes-associated protein (YAP). Elucidating how physical signals control the activity of mechanosensitive proteins poses a technical challenge, because perturbations that affect cell shape may also affect protein localization indirectly. Here, we present an approach that mitigates confounding effects of cell-shape changes, allowing us to identify direct regulators of YAP localization. This method uses single-cell image analysis and statistical models that exploit the naturally occurring heterogeneity of cellular populations. Through systematic depletion of all human kinases, Rho family GTPases, GEFs, and GTPase activating proteins (GAPs), together with targeted chemical perturbations, we found that β-PIX, a Rac1/Ccd42 GEF, and PAK2, a Rac1/Cdc42 effector, drive both YAP activation and cell-ECM adhesion turnover during cell spreading. Our observations suggest that coupling YAP to adhesion dynamics acts as a mechano-timer, allowing cells to rapidly tune gene expression in response to physical signals.
Genome stability relies on proper coordination of mitosis and cytokinesis, where dynamic microtubules capture and faithfully segregate chromosomes into daughter cells. With a high-content RNAi imaging screen targeting more than 2,000 human lncRNAs, we identify numerous lncRNAs involved in key steps of cell division such as chromosome segregation, mitotic duration and cytokinesis. Here, we provide evidence that the chromatin-associated lncRNA, linc00899, leads to robust mitotic delay upon its depletion in multiple cell types. We perform transcriptome analysis of linc00899-depleted cells and identify the neuronal microtubule-binding protein, TPPP/p25, as a target of linc00899. We further show that linc00899 binds TPPP/p25 and suppresses its transcription. In cells depleted of linc00899, upregulation of TPPP/p25 alters microtubule dynamics and delays mitosis. Overall, our comprehensive screen uncovers several lncRNAs involved in genome stability and reveals a lncRNA that controls microtubule behaviour with functional implications beyond cell division.
Two mitotic cyclin types, cyclin A and B, exist in higher eukaryotes, but their specialised functions in mitosis are incompletely understood. Using degron tags for rapid inducible protein removal, we analyse how acute depletion of these proteins affects mitosis. Loss of cyclin A in G2-phase prevents mitotic entry. Cells lacking cyclin B can enter mitosis and phosphorylate most mitotic proteins, because of parallel PP2A:B55 phosphatase inactivation by Greatwall kinase. The final barrier to mitotic establishment corresponds to nuclear envelope breakdown, which requires a decisive shift in the balance of cyclin-dependent kinase Cdk1 and PP2A:B55 activity. Beyond this point, cyclin B/Cdk1 is essential for phosphorylation of a distinct subset of mitotic Cdk1 substrates that are essential to complete cell division. Our results identify how cyclin A, cyclin B and Greatwall kinase coordinate mitotic progression by increasing levels of Cdk1-dependent substrate phosphorylation.
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.
Data visualization is a fundamental aspect of science. In the context of microscopy-based studies, visualization typically involves presentation of the images themselves. However, data visualization is challenging when microscopy experiments entail imaging of millions of cells, and complex cellular phenotypes are quantified in a high-content manner. Most well-established visualization tools are inappropriate for displaying high-content data, which has driven the development of new visualization methodology. In this review, we discuss how data has been visualized in both classical and high-content microscopy studies; as well as the advantages, and disadvantages, of different visualization methods.
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.
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.
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.
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.
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.
Bakal studies the signaling networks that control cell shape.
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.
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.
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.
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.
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.
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.
Rho GTPases are central regulators of the cytoskeleton and, in humans, are controlled by 145 multidomain guanine nucleotide exchange factors (RhoGEFs) and GTPase-activating proteins (RhoGAPs). How Rho signalling patterns are established in dynamic cell spaces to control cellular morphogenesis is unclear. Through a family-wide characterization of substrate specificities, interactomes and localization, we reveal at the systems level how RhoGEFs and RhoGAPs contextualize and spatiotemporally control Rho signalling. These proteins are widely autoinhibited to allow local regulation, form complexes to jointly coordinate their networks and provide positional information for signalling. RhoGAPs are more promiscuous than RhoGEFs to confine Rho activity gradients. Our resource enabled us to uncover a multi-RhoGEF complex downstream of G-protein-coupled receptors controlling CDC42-RHOA crosstalk. Moreover, we show that integrin adhesions spatially segregate GEFs and GAPs to shape RAC1 activity zones in response to mechanical cues. This mechanism controls the protrusion and contraction dynamics fundamental to cell motility. Our systems analysis of Rho regulators is key to revealing emergent organization principles of Rho signalling.
During metastasis, tumour cells navigating the vascular circulatory system-circulating tumour cells (CTCs)-encounter capillary beds, where they start the process of extravasation. Biomechanical constriction forces exerted by the microcirculation compromise the survival of tumour cells within capillaries, but a proportion of CTCs manage to successfully extravasate and colonise distant sites. Despite the profound importance of this step in the progression of metastatic cancers, the factors about this deadly minority of cells remain elusive. Growing evidence suggests that mechanical forces exerted by the capillaries might induce adaptive mechanisms in CTCs, enhancing their survival and metastatic potency. Advances in microfluidics have enabled a better understanding of the cell-survival capabilities adopted in capillary-mimicking constrictions. In this review, we will highlight adaptations developed by CTCs to endure mechanical constraints in the microvasculature and outline how these mechanical forces might trigger dynamic changes towards a more invasive phenotype. A better understanding of the dynamic mechanisms adopted by CTCs within the microcirculation that ultimately lead to metastasis could open up novel therapeutic avenues.
Clustering of the enteropathogenic Escherichia coli (EPEC) type III secretion system (T3SS) effector translocated intimin receptor (Tir) by intimin leads to actin polymerisation and pyroptotic cell death in macrophages. The effect of Tir clustering on the viability of EPEC-infected intestinal epithelial cells (IECs) is unknown. We show that EPEC induces pyroptosis in IECs in a Tir-dependent but actin polymerisation-independent manner, which was enhanced by priming with interferon gamma (IFNγ). Mechanistically, Tir clustering triggers rapid Ca2+ influx, which induces lipopolysaccharide (LPS) internalisation, followed by activation of caspase-4 and pyroptosis. Knockdown of caspase-4 or gasdermin D (GSDMD), translocation of NleF, which blocks caspase-4 or chelation of extracellular Ca2+, inhibited EPEC-induced cell death. IEC lines with low endogenous abundance of GSDMD were resistant to Tir-induced cell death. Conversely, ATP-induced extracellular Ca2+ influx enhanced cell death, which confirmed the key regulatory role of Ca2+ in EPEC-induced pyroptosis. We reveal a novel mechanism through which infection with an extracellular pathogen leads to pyroptosis in IECs.
We present a new folded dual-view oblique plane microscopy (OPM) technique termed dOPM that enables two orthogonal views of the sample to be obtained by translating a pair of tilted mirrors in refocussing space. Using a water immersion 40× 1.15 NA primary objective, deconvolved image volumes of 200 nm beads were measured to have full width at half maxima (FWHM) of 0.35 ± 0.04 µm and 0.39 ± 0.02 µm laterally and 0.81 ± 0.07 µm axially. The measured z-sectioning value was 1.33 ± 0.45 µm using light-sheet FWHM in the frames of the two views of 4.99 ± 0.58 µm and 4.89 ± 0.63 µm. To qualitatively demonstrate that the system can reduce shadow artefacts while providing a more isotropic resolution, a multi-cellular spheroid approximately 100 µm in diameter was imaged.
We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, for example due to changes in temperature or mechanical drift. It is also useful for automated slide scanning or multiwell plate imaging where the sample(s) to be imaged may not be in the same horizontal plane throughout the image data acquisition. To address the impact of (thermal or mechanical) fluctuations over time in the optical autofocus system itself, we utilize a convolutional neural network (CNN) that is trained over multiple days to account for such fluctuations. To address the trade-off between axial precision and range of the autofocus, we implement orthogonal optical readouts with separate CNN training data, thereby achieving an accuracy well within the 600 nm depth of field of our 1.3 numerical aperture objective lens over a defocus range of up to approximately +/-100 μm. We characterize the performance of this autofocus system and demonstrate its application to automated multiwell plate single molecule localization microscopy.
The morphology of breast cancer cells is often used as an indicator of tumor severity and prognosis. Additionally, morphology can be used to identify more fine-grained, molecular developments within a cancer cell, such as transcriptomic changes and signaling pathway activity. Delineating the interface between morphology and signaling is important to understand the mechanical cues that a cell processes in order to undergo epithelial-to-mesenchymal transition and consequently metastasize. However, the exact regulatory systems that define these changes remain poorly characterized. In this study, we used a network-systems approach to integrate imaging data and RNA-seq expression data. Our workflow allowed the discovery of unbiased and context-specific gene expression signatures and cell signaling subnetworks relevant to the regulation of cell shape, rather than focusing on the identification of previously known, but not always representative, pathways. By constructing a cell-shape signaling network from shape-correlated gene expression modules and their upstream regulators, we found central roles for developmental pathways such as WNT and Notch, as well as evidence for the fine control of NF-kB signaling by numerous kinase and transcriptional regulators. Further analysis of our network implicates a gene expression module enriched in the RAP1 signaling pathway as a mediator between the sensing of mechanical stimuli and regulation of NF-kB activity, with specific relevance to cell shape in breast cancer.
In contrast to hypertrophic cardiomyopathy, there has been reported no specific pattern of cardiomyocyte array in dilated cardiomyopathy (DCM), partially because lack of alignment assessment in a three-dimensional (3D) manner. Here we have established a novel method to evaluate cardiomyocyte alignment in 3D using intravital heart imaging and demonstrated homogeneous alignment in DCM mice. Whilst cardiomyocytes of control mice changed their alignment by every layer in 3D and position twistedly even in a single layer, termed myocyte twist, cardiomyocytes of DCM mice aligned homogeneously both in two-dimensional (2D) and in 3D and lost myocyte twist. Manipulation of cultured cardiomyocyte toward homogeneously aligned increased their contractility, suggesting that homogeneous alignment in DCM mice is due to a sort of alignment remodelling as a way to compensate cardiac dysfunction. Our findings provide the first intravital evidence of cardiomyocyte alignment and will bring new insights into understanding the mechanism of heart failure.
The behaviour of circulating tumour cells in the microcirculation remains poorly understood. Growing evidence suggests that biomechanical adaptations and interactions with blood components, i.e. immune cells and platelets within capillary beds, may add more complexity to CTCs journey towards metastasis. Revisiting how these mediators impact the ability of circulating tumour cells to survive and metastasise, will be vital to understand the role of microcirculation and advance our knowledge on metastasis.
When used in combination with hormone treatment, Palbociclib prolongs progression-free survival of patients with hormone receptor positive breast cancer. Mechanistically, Palbociclib inhibits CDK4/6 activity but the basis for differing sensitivity of cancer to Palbociclib is poorly understood. A common observation in a subset of Triple Negative Breast Cancers (TNBCs) is that prolonged CDK4/6 inhibition can engage a senescence-like state where cells exit the cell cycle, whilst, remaining metabolically active. To better understand the senescence-like cell state which arises after Palbociclib treatment we used mass spectrometry to quantify the proteome, phosphoproteome, and secretome of Palbociclib-treated MDA-MB-231 TNBC cells. We observed altered levels of cell cycle regulators, immune response, and key senescence markers upon Palbociclib treatment. These datasets provide a starting point for the derivation of biomarkers which could inform the future use CDK4/6 inhibitors in TNBC subtypes and guide the development of potential combination therapies.
Rho GTP Exchange Factors (RhoGEFs) and Rho GTPase Activating Proteins (RhoGAPs) are large families of molecules that regulate shape determination in all eukaryotes. In pathologies such as melanoma, RhoGEF and RhoGAP activity underpins the ability of cells to invade tissues of varying elasticity. To identify RhoGEFs and RhoGAPs that regulate melanoma cell shape on soft and/or stiff materials, we performed genetic screens, in tandem with single-cell quantitative morphological analysis. We show that ARHGEF9/Collybistin (Cb) is essential for cell shape determination on both soft and stiff materials, and in cells embedded in 3D soft hydrogel. ARHGEF9 is required for melanoma cells to invade 3D matrices. Depletion of ARHGEF9 results in loss of tension at focal adhesions decreased cell-wide contractility, and the inability to stabilize protrusions. Taken together we show that ARHGEF9 promotes the formation of actin-rich filopodia, which serves to establish and stabilize adhesions and determine melanoma cell shape.
Cancer cells feature a resting membrane potential (V<sub>m</sub>) that is depolarized compared to normal cells, and express active ionic conductances, which factor directly in their pathophysiological behavior. Despite similarities to 'excitable' tissues, relatively little is known about cancer cell V<sub>m</sub> dynamics. Here high-throughput, cellular-resolution V<sub>m</sub> imaging reveals that V<sub>m</sub> fluctuates dynamically in several breast cancer cell lines compared to non-cancerous MCF-10A cells. We characterize V<sub>m</sub> fluctuations of hundreds of human triple-negative breast cancer MDA-MB-231 cells. By quantifying their Dynamic Electrical Signatures (DESs) through an unsupervised machine-learning protocol, we identify four classes ranging from "noisy" to "blinking/waving". The V<sub>m</sub> of MDA-MB-231 cells exhibits spontaneous, transient hyperpolarizations inhibited by the voltage-gated sodium channel blocker tetrodotoxin, and by calcium-activated potassium channel inhibitors apamin and iberiotoxin. The V<sub>m</sub> of MCF-10A cells is comparatively static, but fluctuations increase following treatment with transforming growth factor-β1, a canonical inducer of the epithelial-to-mesenchymal transition. These data suggest that the ability to generate V<sub>m</sub> fluctuations may be a property of hybrid epithelial-mesenchymal cells or those originated from luminal progenitors.
Small interfering RNA (siRNA) screening approaches used with quantitative single-cell analysis can uncover the roles of genes in cell morphogenesis. Here, we present a high-throughput automated phenotypic screening technique to quantify a single cell shape in cancer cells cultured on top of soft 3D hydrogels. We describe reverse transfection of cells with siRNAs and seeding of these cells on top of collagen, followed by image analysis to quantify morphology of a single cell and population levels in low-elasticity matrices. For complete details on the use and execution of this protocol, please refer to Bousgouni et al. (2022).<sup>1</sup>.
Almost all living cells maintain size uniformity through successive divisions. Proteins that over and underscale with size can act as rheostats, which regulate cell cycle progression. Using a multiomic strategy, we leveraged the heterogeneity of melanoma cell lines to identify peptides, transcripts, and phosphorylation events that differentially scale with cell size. Subscaling proteins are enriched in regulators of the DNA damage response and cell cycle progression, whereas super-scaling proteins included regulators of the cytoskeleton, extracellular matrix, and inflammatory response. Mathematical modeling suggested that decoupling growth and proliferative signaling may facilitate cell cycle entry over senescence in large cells when mitogenic signaling is decreased. Regression analysis reveals that up-regulation of TP53 or CDKN1A/p21CIP1 is characteristic of proliferative cancer cells with senescent-like sizes/proteomes. This study provides one of the first demonstrations of size-scaling phenomena in cancer and how morphology influences the chemistry of the cell.
Accurate genome replication is essential for all life and a key mechanism of disease prevention, underpinned by the ability of cells to respond to replicative stress (RS) and protect replication forks. These responses rely on the formation of Replication Protein A (RPA)-single stranded (ss) DNA complexes, yet this process remains largely uncharacterized. Here, we establish that actin nucleation-promoting factors (NPFs) associate with replication forks, promote efficient DNA replication and facilitate association of RPA with ssDNA at sites of RS. Accordingly, their loss leads to deprotection of ssDNA at perturbed forks, impaired ATR activation, global replication defects and fork collapse. Supplying an excess of RPA restores RPA foci formation and fork protection, suggesting a chaperoning role for actin nucleators (ANs) (i.e. Arp2/3, DIAPH1) and NPFs (i.e, WASp, N-WASp) in regulating RPA availability upon RS. We also discover that β-actin interacts with RPA directly in vitro, and in vivo a hyper-depolymerizing β-actin mutant displays a heightened association with RPA and the same dysfunctional replication phenotypes as loss of ANs/NPFs, which contrasts with the phenotype of a hyper-polymerizing β-actin mutant. Thus, we identify components of actin polymerization pathways that are essential for preventing ectopic nucleolytic degradation of perturbed forks by modulating RPA activity.
How cancer cells determine their shape in response to three-dimensional (3D) geometric and mechanical cues is unclear. We develop an approach to quantify the 3D cell shape of over 60,000 melanoma cells in collagen hydrogels using high-throughput stage-scanning oblique plane microscopy (ssOPM). We identify stereotypic and environmentally dependent changes in shape and protrusivity depending on whether a cell is proximal to a flat and rigid surface or is embedded in a soft environment. Environmental sensitivity metrics calculated for small molecules and gene knockdowns identify interactions between the environment and cellular factors that are important for morphogenesis. We show that the Rho guanine nucleotide exchange factor (RhoGEF) TIAM2 contributes to shape determination in environmentally independent ways but that non-muscle myosin II, microtubules, and the RhoGEF FARP1 regulate shape in ways dependent on the microenvironment. Thus, changes in cancer cell shape in response to 3D geometric and mechanical cues are modulated in both an environmentally dependent and independent fashion.
Lab-on-Chip electrochemical sensors, such as Ion-Sensitive Field-Effect Transistors (ISFETs), are being developed for use in point-of-care diagnostics, such as pH detection of tumour microenvironments, due to their integration with standard Complementary Metal Oxide Semiconductor (CMOS) technology. With this approach, the passivation of the CMOS process is used as a sensing layer to minimise post-processing, and Silicon Nitride (Si<sub>3</sub>N<sub>4</sub>) is the most common material at the microchip surface. ISFETs have the potential to be used for cell-based assays however, there is a poor understanding of the biocompatibility of microchip surfaces. Here, we quantitatively evaluated cell adhesion, morphogenesis, proliferation and mechano-responsiveness of both normal and cancer cells cultured on a Si<sub>3</sub>N<sub>4</sub>, sensor surface. We demonstrate that both normal and cancer cell adhesion decreased on Si<sub>3</sub>N<sub>4</sub>. Activation of the mechano-responsive transcription regulators, YAP/TAZ, are significantly decreased in cancer cells on Si<sub>3</sub>N<sub>4</sub> in comparison to standard cell culture plastic, whilst proliferation marker, Ki67, expression markedly increased. Non-tumorigenic cells on chip showed less sensitivity to culture on Si<sub>3</sub>N<sub>4</sub> than cancer cells. Treatment with extracellular matrix components increased cell adhesion in normal and cancer cell cultures, surpassing the adhesiveness of plastic alone. Moreover, poly-l-ornithine and laminin treatment restored YAP/TAZ levels in both non-tumorigenic and cancer cells to levels comparable to those observed on plastic. Thus, engineering the electrochemical sensor surface with treatments will provide a more physiologically relevant environment for future cell-based assay development on chip.
Solid tumours have abnormally high intracellular [Na<sup>+</sup>]. The activity of various Na<sup>+</sup> channels may underlie this Na<sup>+</sup> accumulation. Voltage-gated Na<sup>+</sup> channels (VGSCs) have been shown to be functionally active in cancer cell lines, where they promote invasion. However, the mechanisms involved, and clinical relevance, are incompletely understood. Here, we show that protein expression of the Na<sub>v</sub>1.5 VGSC subtype strongly correlates with increased metastasis and shortened cancer-specific survival in breast cancer patients. In addition, VGSCs are functionally active in patient-derived breast tumour cells, cell lines, and cancer-associated fibroblasts. Knockdown of Na<sub>v</sub>1.5 in a mouse model of breast cancer suppresses expression of invasion-regulating genes. Na<sub>v</sub>1.5 activity increases ATP demand and glycolysis in breast cancer cells, likely by upregulating activity of the Na<sup>+</sup>/K<sup>+</sup> ATPase, thus promoting H<sup>+</sup> production and extracellular acidification. The pH of murine xenograft tumours is lower at the periphery than in the core, in regions of higher proliferation and lower apoptosis. In turn, acidic extracellular pH elevates persistent Na<sup>+</sup> influx through Na<sub>v</sub>1.5 into breast cancer cells. Together, these findings show positive feedback between extracellular acidification and the movement of Na<sup>+</sup> into cancer cells which can facilitate invasion. These results highlight the clinical significance of Na<sub>v</sub>1.5 activity as a potentiator of breast cancer metastasis and provide further evidence supporting the use of VGSC inhibitors in cancer treatment.
During metastatic dissemination, circulating tumour cells (CTCs) enter capillary beds, where they experience mechanical constriction forces. The transient and persistent effects of these forces on CTCs behaviour remain poorly understood. Here, we developed a high-throughput microfluidic platform mimicking human capillaries to investigate the impact of mechanical constriction forces on malignant and normal breast cell lines. We observed that capillary constrictions induced nuclear envelope rupture in both cancer and normal cells, leading to transient changes in nuclear and cytoplasmic area. Constriction forces transiently activated cGAS/STING and pathways involved in inflammation (NF-κB, STAT and IRF3), especially in the non-malignant cell line. Furthermore, the non-malignant cell line experienced transcriptional changes, particularly downregulation of epithelial markers, while the metastatic cell lines showed minimal alterations. These findings suggest that mechanical constriction forces within capillaries may promote differential effects in malignant and normal cell lines.
Xeroderma pigmentosum (XP) is caused by defective nucleotide excision repair of DNA damage. This results in hypersensitivity to ultraviolet light and increased skin cancer risk, as sunlight-induced photoproducts remain unrepaired. However, many XP patients also display early-onset neurodegeneration, which leads to premature death. The mechanism of neurodegeneration is unknown. Here, we investigate XP neurodegeneration using pluripotent stem cells derived from XP patients and healthy relatives, performing functional multi-omics on samples during neuronal differentiation. We show substantially increased levels of 5',8-cyclopurine and 8-oxopurine in XP neuronal DNA secondary to marked oxidative stress. Furthermore, we find that the endoplasmic reticulum stress response is upregulated and reversal of the mutant genotype is associated with phenotypic rescue. Critically, XP neurons exhibit inappropriate downregulation of the protein clearance ubiquitin-proteasome system (UPS). Chemical enhancement of UPS activity in XP neuronal models improves phenotypes, albeit inadequately. Although more work is required, this study presents insights with intervention potential.
The canonical NF-κB transcription factor RELA is a master regulator of immune and stress responses and is upregulated in pancreatic ductal adenocardinoma (PDAC) tumours. In this study, we characterised previously unexplored endogenous RELA-GFP dynamics in PDAC cell lines through live single-cell imaging. Our observations revealed that TNFα stimulation induces rapid, sustained, and non-oscillatory nuclear translocation of RELA. Through Bayesian analysis of single-cell datasets with variation in nuclear RELA, we predicted that RELA heterogeneity in PDAC cell lines is dependent on F-actin dynamics. RNA-seq analysis identified distinct clusters of RELA-regulated gene expression in PDAC cells, including TNFα-induced RELA upregulation of the actin regulators NUAK2 and ARHGAP31. Further, siRNA-mediated depletion of ARHGAP31 and NUAK2 altered TNFα-stimulated nuclear RELA dynamics in PDAC cells, establishing a novel negative feedback loop that regulates RELA activation by TNFα. Additionally, we characterised the NF-κB pathway in PDAC cells, identifying how NF-κB/IκB proteins genetically and physically interact with RELA in the absence or presence of TNFα. Taken together, we provide computational and experimental support for interdependence between the F-actin network and the NF-κB pathway with RELA translocation dynamics in PDAC.
The concentration of many transcription factors exhibits high cell-to-cell variability due to differences in synthesis, degradation, and cell size. Whether the functions of these factors are robust to fluctuations in concentration, and how this may be achieved, is poorly understood. Across two independent panels of breast cancer cells, we show that the average whole cell concentration of YAP decreases as a function of cell area. However, the nuclear concentration distribution remains constant across cells grouped by size, across a 4-8 fold size range, implying unperturbed nuclear translocation despite the falling cell wide concentration. Both the whole cell and nuclear concentration was higher in cells with more DNA and CycA/PCNA expression suggesting periodic synthesis of YAP across the cell cycle offsets dilution due to cell growth and/or cell spreading. The cell area - YAP scaling relationship extended to melanoma and RPE cells. Integrative analysis of imaging and phospho-proteomic data showed the average nuclear YAP concentration across cell lines was predicted by differences in RAS/MAPK signalling, focal adhesion maturation, and nuclear transport processes. Validating the idea that RAS/MAPK and cell cycle regulate YAP translocation, chemical inhibition of MEK or CDK4/6 increased the average nuclear YAP concentration. Together, this study provides an example case, where cytoplasmic dilution of a protein, for example through cell growth, does not limit a cognate cellular function. Here, that same proteins translocation into the nucleus.