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Ram A, Pargett M, Choi Y, Murphy D, Teragawa C, Cabel M, Kosaisawe N, Quon G, Albeck JG. Deciphering the history of ERK activity from fixed-cell immunofluorescence measurements. Nat Commun 2025; 16:4721. [PMID: 40399273 DOI: 10.1038/s41467-025-58348-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 03/19/2025] [Indexed: 05/23/2025] Open
Abstract
The RAS/ERK pathway plays a central role in diagnosis and therapy for many cancers. ERK activity is highly dynamic within individual cells and drives cell proliferation, metabolism, and other processes through effector proteins including c-Myc, c-Fos, Fra-1, and Egr-1. These proteins are sensitive to the dynamics of ERK activity, but it is not clear to what extent the pattern of ERK activity in an individual cell determines effector protein expression, or how much information about ERK dynamics is embedded in the pattern of effector expression. Here, we evaluate these relationships using live-cell biosensor measurements of ERK activity, multiplexed with immunofluorescence staining for downstream target proteins of the pathway. Combining these datasets with linear regression, machine learning, and differential equation models, we develop an interpretive framework for immunofluorescence data, wherein Fra-1 and pRb levels imply long-term activation of ERK signaling, while Egr-1 and c-Myc indicate more recent activation. Analysis of multiple cancer cell lines reveals a distorted relationship between ERK activity and cell state in malignant cells. We show that this framework can infer various classes of ERK dynamics from effector protein stains within a heterogeneous population, providing a basis for annotating ERK dynamics within fixed cells.
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Affiliation(s)
- Abhineet Ram
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Yongin Choi
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Devan Murphy
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Carolyn Teragawa
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Markhus Cabel
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Gerald Quon
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA.
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2
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De la Fuente IM, Cortes JM, Malaina I, Pérez-Yarza G, Martinez L, López JI, Fedetz M, Carrasco-Pujante J. The main sources of molecular organization in the cell. Atlas of self-organized and self-regulated dynamic biostructures. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2025; 195:167-191. [PMID: 39805422 DOI: 10.1016/j.pbiomolbio.2025.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2024] [Accepted: 01/10/2025] [Indexed: 01/16/2025]
Abstract
One of the most important goals of contemporary biology is to understand the principles of the molecular order underlying the complex dynamic architecture of cells. Here, we present an overview of the main driving forces involved in the cellular molecular complexity and in the emergent functional dynamic structures, spanning from the most basic molecular organization levels to the complex emergent integrative systemic behaviors. First, we address the molecular information processing which is essential in many complex fundamental mechanisms such as the epigenetic memory, alternative splicing, regulation of transcriptional system, and the adequate self-regulatory adaptation to the extracellular environment. Next, we approach the biochemical self-organization, which is central to understand the emergency of metabolic rhythms, circadian oscillations, and spatial traveling waves. Such a complex behavior is also fundamental to understand the temporal compartmentalization of the cellular metabolism and the dynamic regulation of many physiological activities. Numerous examples of biochemical self-organization are considered here, which show that practically all the main physiological processes in the cell exhibit this type of dynamic molecular organization. Finally, we focus on the biochemical self-assembly which, at a primary level of organization, is a basic but important mechanism for the order in the cell allowing biomolecules in a disorganized state to form complex aggregates necessary for a plethora of essential structures and physiological functions. In total, more than 500 references have been compiled in this review. Due to these main sources of order, systemic functional structures emerge in the cell, driving the metabolic functionality towards the biological complexity.
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Affiliation(s)
- Ildefonso M De la Fuente
- Department of Mathematics, Faculty of Science and Technology, University of the Basque Country, UPV/EHU, Leioa, 48940, Spain.
| | - Jesus M Cortes
- Department of Cell Biology and Histology, Faculty of Medicine and Nursing, University of the Basque Country, UPV/EHU, Leioa, 48940, Spain; Biobizkaia Health Research Institute, Barakaldo, 48903, Spain; IKERBASQUE: The Basque Foundation for Science, Bilbao, Spain
| | - Iker Malaina
- Department of Mathematics, Faculty of Science and Technology, University of the Basque Country, UPV/EHU, Leioa, 48940, Spain
| | - Gorka Pérez-Yarza
- Department of Cell Biology and Histology, Faculty of Medicine and Nursing, University of the Basque Country, UPV/EHU, Leioa, 48940, Spain
| | - Luis Martinez
- Department of Mathematics, Faculty of Science and Technology, University of the Basque Country, UPV/EHU, Leioa, 48940, Spain
| | - José I López
- Biobizkaia Health Research Institute, Barakaldo, 48903, Spain
| | - Maria Fedetz
- Department of Cell Biology and Immunology, Institute of Parasitology and Biomedicine "López-Neyra", CSIC, Granada, 18016, Spain
| | - Jose Carrasco-Pujante
- Department of Cell Biology and Histology, Faculty of Medicine and Nursing, University of the Basque Country, UPV/EHU, Leioa, 48940, Spain
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3
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Nakamura E, Blanchini F, Giordano G, Hoffmann A, Franco E. Temporal dose inversion properties of adaptive biomolecular circuits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.10.636967. [PMID: 39990486 PMCID: PMC11844413 DOI: 10.1101/2025.02.10.636967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/25/2025]
Abstract
Cells have the capacity to encode and decode information in the temporal features of molecular signals. Many pathways, for example, generate either sustained or pulsatile responses depending on the context, and such diverse temporal behaviors have a profound impact on cell fate. Here we focus on how molecular pathways can convert the temporal features of dynamic signals, in particular how they can convert transient signals into persistent downstream events and vice versa. We describe this type of behavior as temporal dose inversion, and we demonstrate that it can be achieved through adaptive molecular circuits. We consider motifs known as incoherent feedforward loop (IFFL) and negative feedback loop (NFL), and identify parametric conditions that enable temporal dose inversion. We next consider more complex versions of these circuits that could be realized using enzymatic signaling and gene regulatory networks, finding that both circuits can exhibit temporal dose inversion. Finally, we consider a generalized IFFL topology, and we find that both the time delay in the inhibition pathway and the relative signal intensities of the activation and inhibition signals are key determinants for temporal dose inversion. Our investigation expands the potential use of adaptive circuits as signal processing units and contributes to our understanding of the role of adaptive circuits in nature.
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Affiliation(s)
- Eiji Nakamura
- Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, USA
| | - Franco Blanchini
- Department of Mathematics, Computer Science and Physics, University of Udine, Italy
| | - Giulia Giordano
- Department of Industrial Engineering, University of Trento, Italy
| | - Alexander Hoffmann
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, USA
| | - Elisa Franco
- Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, USA
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4
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Ferrick KR, Fan Y, Ratnayeke N, Teruel MN, Meyer T. Transient proliferation by reversible YAP and mitogen-control of the cyclin D1/p27 ratio. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.11.617852. [PMID: 39416132 PMCID: PMC11482934 DOI: 10.1101/2024.10.11.617852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
Hippo-YAP signaling orchestrates epithelial tissue repair and is therefore an attractive target in regenerative medicine. Yet it is unresolved how YAP integrates with mitogen signaling and contact inhibition to control the underlying transient proliferative response. Here we show that reduced contact inhibition, increased mitogen signaling, and YAP-TEAD activation converge on increasing the nuclear cyclin D1/p27 protein ratio during G1 phase, towards a threshold ratio that dictates whether individual cells enter or exit the cell cycle. YAP increases this ratio indirectly, in concert with mitogen signaling, by increasing EGFR and other receptors that signal primarily through ERK. After a delay, contact inhibition suppresses YAP activity which gradually downregulates mitogen signaling and the cyclin D1/p27 ratio. Increasing YAP activity by ablating the suppressor Merlin/NF2 reveals a balancing mechanism in which YAP suppression and contact inhibition of proliferation can be recovered but only at higher local cell density. Thus, critical for tissue repair, robust proliferation responses result from the YAP-induced and receptor-mediated prolonged increase in the cyclin D1/p27 ratio, which is only reversed by delayed suppression of receptor signaling after contact inhibition of YAP.
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Affiliation(s)
- Katherine R. Ferrick
- Department of Cell and Developmental Biology, Weill Cornell Medicine, New York, NY, USA
- Department of Chemical and Systems Biology, Stanford Medicine, Stanford, CA, USA
| | - Yilin Fan
- Department of Cell and Developmental Biology, Weill Cornell Medicine, New York, NY, USA
- Department of Chemical and Systems Biology, Stanford Medicine, Stanford, CA, USA
- Current: Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Nalin Ratnayeke
- Department of Cell and Developmental Biology, Weill Cornell Medicine, New York, NY, USA
- Department of Chemical and Systems Biology, Stanford Medicine, Stanford, CA, USA
- Current: Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Mary N. Teruel
- Department of Biochemistry, Weill Cornell Medicine, New York, NY, USA
| | - Tobias Meyer
- Department of Cell and Developmental Biology, Weill Cornell Medicine, New York, NY, USA
- Department of Chemical and Systems Biology, Stanford Medicine, Stanford, CA, USA
- Lead contact
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5
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Luecke S, Guo X, Sheu KM, Singh A, Lowe SC, Han M, Diaz J, Lopes F, Wollman R, Hoffmann A. Dynamical and combinatorial coding by MAPK p38 and NFκB in the inflammatory response of macrophages. Mol Syst Biol 2024; 20:898-932. [PMID: 38872050 PMCID: PMC11297158 DOI: 10.1038/s44320-024-00047-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 05/27/2024] [Accepted: 05/28/2024] [Indexed: 06/15/2024] Open
Abstract
Macrophages sense pathogens and orchestrate specific immune responses. Stimulus specificity is thought to be achieved through combinatorial and dynamical coding by signaling pathways. While NFκB dynamics are known to encode stimulus information, dynamical coding in other signaling pathways and their combinatorial coordination remain unclear. Here, we established live-cell microscopy to investigate how NFκB and p38 dynamics interface in stimulated macrophages. Information theory and machine learning revealed that p38 dynamics distinguish cytokine TNF from pathogen-associated molecular patterns and high doses from low, but contributed little to information-rich NFκB dynamics when both pathways are considered. This suggests that immune response genes benefit from decoding immune signaling dynamics or combinatorics, but not both. We found that the heterogeneity of the two pathways is surprisingly uncorrelated. Mathematical modeling revealed potential sources of uncorrelated heterogeneity in the branched pathway network topology and predicted it to drive gene expression variability. Indeed, genes dependent on both p38 and NFκB showed high scRNAseq variability and bimodality. These results identify combinatorial signaling as a mechanism to restrict NFκB-AND-p38-responsive inflammatory cytokine expression to few cells.
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Affiliation(s)
- Stefanie Luecke
- Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Xiaolu Guo
- Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Katherine M Sheu
- Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Apeksha Singh
- Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Sarina C Lowe
- Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California Los Angeles, Los Angeles, CA, 90095, USA
- Vatche and Tamar Manoukian Division of Digestive Diseases, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Minhao Han
- Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Jessica Diaz
- Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Francisco Lopes
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Grupo de Biologia do Desenvolvimento e Sistemas Dinamicos, Campus Duque de Caxias Professor Geraldo Cidade, Universidade Federal do Rio de Janeiro, Duque de Caxias, 25240-005, Brazil
| | - Roy Wollman
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Department of Integrative Biology and Physiology, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Alexander Hoffmann
- Department of Microbiology, Immunology, and Molecular Genetics (MIMG), University of California Los Angeles, Los Angeles, CA, 90095, USA.
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, 90095, USA.
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Nussinov R, Zhang W, Liu Y, Jang H. Mitogen signaling strength and duration can control cell cycle decisions. SCIENCE ADVANCES 2024; 10:eadm9211. [PMID: 38968359 PMCID: PMC11809619 DOI: 10.1126/sciadv.adm9211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 05/31/2024] [Indexed: 07/07/2024]
Abstract
Decades ago, mitogen-promoted signaling duration and strength were observed to be sensed by the cell and to be critical for its decisions: to proliferate or differentiate. Landmark publications established the importance of mitogen signaling not only in the G1 cell cycle phase but also through the S and the G2/M transition. Despite these early milestones, how mitogen signal duration and strength, short and strong or weaker and sustained, control cell fate has been largely unheeded. Here, we center on cardinal signaling-related questions, including (i) how fluctuating mitogenic signals are converted into cell proliferation-differentiation decisions and (ii) why extended duration of weak signaling is associated with differentiation, while bursts of strong and short induce proliferation but, if too strong and long, induce irreversible senescence. Our innovative broad outlook harnesses cell biology and protein conformational ensembles, helping us to define signaling strength, clarify cell cycle decisions, and thus cell fate.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
| | - Wengang Zhang
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
| | - Yonglan Liu
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
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7
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Andrews SS, Kochen M, Smith L, Feng S, Wiley HS, Sauro HM. Signal integration and integral feedback control with biochemical reaction networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.26.591337. [PMID: 38746178 PMCID: PMC11092504 DOI: 10.1101/2024.04.26.591337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Biochemical reaction networks perform a variety of signal processing functions, one of which is computing the integrals of signal values. This is often used in integral feedback control, where it enables a system's output to respond to changing inputs, but to then return exactly back to some pre-determined setpoint value afterward. To gain a deeper understanding of how biochemical networks are able to both integrate signals and perform integral feedback control, we investigated these abilities for several simple reaction networks. We found imperfect overlap between these categories, with some networks able to perform both tasks, some able to perform integration but not integral feedback control, and some the other way around. Nevertheless, networks that could either integrate or perform integral feedback control shared key elements. In particular, they included a chemical species that was neutrally stable in the open loop system (no feedback), meaning that this species does not have a unique stable steady-state concentration. Neutral stability could arise from zeroth order decay reactions, binding to a partner that was produced at a constant rate (which occurs in antithetic control), or through a long chain of covalent cycles. Mathematically, it arose from rate equations for the reaction network that were underdetermined when evaluated at steady-state.
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8
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DeCuzzi NL, Oberbauer DP, Chmiel KJ, Pargett M, Ferguson JM, Murphy D, Zeki AA, Albeck JG. Spatiotemporal Clusters of ERK Activity Coordinate Cytokine-induced Inflammatory Responses in Human Airway Epithelial Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.03.578773. [PMID: 38352523 PMCID: PMC10862831 DOI: 10.1101/2024.02.03.578773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
RATIONALE Spatially coordinated ERK signaling events ("SPREADs") transmit radially from a central point to adjacent cells via secreted ligands for EGFR and other receptors. SPREADs maintain homeostasis in non-pulmonary epithelia, but it is unknown whether they play a role in the airway epithelium or are dysregulated in inflammatory disease. OBJECTIVES (1) To characterize spatiotemporal ERK activity in response to pro-inflammatory ligands, and (2) to assess pharmacological and metabolic regulation of cytokine-mediated SPREADs. METHODS SPREADs were measured by live-cell ERK biosensors in human bronchial epithelial cell lines (HBE1 and 16HBE) and primary human bronchial epithelial (pHBE) cells, in both submerged and biphasic Air-Liquid Interface (ALI) culture conditions (i.e., differentiated cells). Cells were exposed to pro-inflammatory cytokines relevant to asthma and chronic obstructive pulmonary disease (COPD), and to pharmacological treatments (gefitinib, tocilizumab, hydrocortisone) and metabolic modulators (insulin, 2-deoxyglucose) to probe the airway epithelial mechanisms of SPREADs. Phospho-STAT3 immunofluorescence was used to measure localized inflammatory responses to IL-6. RESULTS Pro-inflammatory cytokines significantly increased the frequency of SPREADs. Notably, differentiated pHBE cells display increased SPREAD frequency that coincides with airway epithelial barrier breakdown. SPREADs correlate with IL-6 peptide secretion and localized pSTAT3. Hydrocortisone, inhibitors of receptor signaling, and suppression of metabolic function decreased SPREAD occurrence. CONCLUSIONS Pro-inflammatory cytokines modulate SPREADs in human airway epithelial cells via both secreted EGFR and IL6R ligands. SPREADs correlate with changes in epithelial barrier permeability, implying a role for spatiotemporal ERK signaling in barrier homeostasis and dysfunction during inflammation. The involvement of SPREADs in airway inflammation suggests a novel signaling mechanism that could be exploited clinically to supplement corticosteroid treatment for asthma and COPD.
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Affiliation(s)
- Nicholaus L. DeCuzzi
- Department of Molecular and Cellular Biology, University of California, Davis
- School of Medicine; Department of Internal Medicine; Division of Pulmonary, Critical Care, and Sleep Medicine; Lung Center; University of California, Davis
| | - Daniel P. Oberbauer
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Kenneth J. Chmiel
- School of Medicine; Department of Internal Medicine; Division of Pulmonary, Critical Care, and Sleep Medicine; Lung Center; University of California, Davis
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Justa M. Ferguson
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Devan Murphy
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Amir A. Zeki
- School of Medicine; Department of Internal Medicine; Division of Pulmonary, Critical Care, and Sleep Medicine; Lung Center; University of California, Davis
- U. C. Davis Reversible Obstructive Airway Disease (ROAD) Center
- Veterans Administration Medical Center, Mather, CA
| | - John G. Albeck
- Department of Molecular and Cellular Biology, University of California, Davis
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9
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Kembro JM, Flesia AG, Acosta-Rodríguez VA, Takahashi JS, Nieto PS. Dietary restriction modulates ultradian rhythms and autocorrelation properties in mice behavior. Commun Biol 2024; 7:303. [PMID: 38461321 PMCID: PMC10925031 DOI: 10.1038/s42003-024-05991-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 02/28/2024] [Indexed: 03/11/2024] Open
Abstract
Animal behavior emerges from integration of many processes with different spatial and temporal scales. Dynamical behavioral patterns, including daily and ultradian rhythms and the dynamical microstructure of behavior (i.e., autocorrelations properties), can be differentially affected by external cues. Identifying these patterns is important for understanding how organisms adapt to their environment, yet unbiased methods to quantify dynamical changes over multiple temporal scales are lacking. Herein, we combine a wavelet approach with Detrended Fluctuation Analysis to identify behavioral patterns and evaluate changes over 42-days in mice subjected to different dietary restriction paradigms. We show that feeding restriction alters dynamical patterns: not only are daily rhythms modulated but also the presence, phase and/or strength of ~12h-rhythms, as well as the nature of autocorrelation properties of feed-intake and wheel running behaviors. These results highlight the underlying complexity of behavioral architecture and offer insights into the multi-scale impact of feeding habits on physiology.
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Affiliation(s)
- Jackelyn Melissa Kembro
- Universidad Nacional de Córdoba (UNC), Facultad de Ciencias Exactas, Físicas y Naturales, Instituto de Ciencia y Tecnología de los Alimentos (ICTA) and Departamento de Química, Cátedra de Química Biológica, Córdoba, Córdoba, X5000HUA, Argentina
- Instituto de Investigaciones Biológicas y Tecnológicas, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)- UNC, Córdoba, Córdoba, X5000HUA, Argentina
| | - Ana Georgina Flesia
- Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, Córdoba, Córdoba, X5000HUA, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Centro de Investigaciones y Estudios de Matemática (CIEM, CONICET-UNC), Córdoba, Córdoba, X5000HUA, Argentina
| | - Victoria América Acosta-Rodríguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, 75390-9111, USA
| | - Joseph S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, 75390-9111, USA
- Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX, 75390-9111, USA
| | - Paula Sofía Nieto
- Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, Córdoba, Córdoba, X5000HUA, Argentina.
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Instituto de Física Enrique Gaviola (IFEG, CONICET-UNC), Universidad Nacional de Córdoba, Córdoba, Córdoba, X5000HUA, Argentina.
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10
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Teague S, Primavera G, Chen B, Liu ZY, Yao L, Freeburne E, Khan H, Jo K, Johnson C, Heemskerk I. Time-integrated BMP signaling determines fate in a stem cell model for early human development. Nat Commun 2024; 15:1471. [PMID: 38368368 PMCID: PMC10874454 DOI: 10.1038/s41467-024-45719-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 02/02/2024] [Indexed: 02/19/2024] Open
Abstract
How paracrine signals are interpreted to yield multiple cell fate decisions in a dynamic context during human development in vivo and in vitro remains poorly understood. Here we report an automated tracking method to follow signaling histories linked to cell fate in large numbers of human pluripotent stem cells (hPSCs). Using an unbiased statistical approach, we discover that measured BMP signaling history correlates strongly with fate in individual cells. We find that BMP response in hPSCs varies more strongly in the duration of signaling than the level. However, both the level and duration of signaling activity control cell fate choices only by changing the time integral. Therefore, signaling duration and level are interchangeable in this context. In a stem cell model for patterning of the human embryo, we show that signaling histories predict the fate pattern and that the integral model correctly predicts changes in cell fate domains when signaling is perturbed. Our data suggest that mechanistically, BMP signaling is integrated by SOX2.
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Affiliation(s)
- Seth Teague
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Gillian Primavera
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Bohan Chen
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Zong-Yuan Liu
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - LiAng Yao
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Emily Freeburne
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Hina Khan
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Kyoung Jo
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Craig Johnson
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Idse Heemskerk
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, USA.
- Center for Cell Plasticity and Organ Design, University of Michigan Medical School, Ann Arbor, MI, USA.
- Department of Physics, University of Michigan, Ann Arbor, MI, USA.
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11
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Ram A, Pargett M, Choi Y, Murphy D, Cabel M, Kosaisawe N, Quon G, Albeck J. Deciphering the History of ERK Activity from Fixed-Cell Immunofluorescence Measurements. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.16.580760. [PMID: 38405841 PMCID: PMC10889026 DOI: 10.1101/2024.02.16.580760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The Ras/ERK pathway drives cell proliferation and other oncogenic behaviors, and quantifying its activity in situ is of high interest in cancer diagnosis and therapy. Pathway activation is often assayed by measuring phosphorylated ERK. However, this form of measurement overlooks dynamic aspects of signaling that can only be observed over time. In this study, we combine a live, single-cell ERK biosensor approach with multiplexed immunofluorescence staining of downstream target proteins to ask how well immunostaining captures the dynamic history of ERK activity. Combining linear regression, machine learning, and differential equation models, we develop an interpretive framework for immunostains, in which Fra-1 and pRb levels imply long term activation of ERK signaling, while Egr-1 and c-Myc indicate recent activation. We show that this framework can distinguish different classes of ERK dynamics within a heterogeneous population, providing a tool for annotating ERK dynamics within fixed tissues.
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Affiliation(s)
- Abhineet Ram
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Yongin Choi
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Devan Murphy
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Markhus Cabel
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Gerald Quon
- Department of Molecular and Cellular Biology, University of California, Davis
| | - John Albeck
- Department of Molecular and Cellular Biology, University of California, Davis
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12
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McAloney CA, Makkawi R, Budhathoki Y, Cannon MV, Franz EM, Gross AC, Cam M, Vetter TA, Duhen R, Davies AE, Roberts RD. Host-derived growth factors drive ERK phosphorylation and MCL1 expression to promote osteosarcoma cell survival during metastatic lung colonization. Cell Oncol (Dordr) 2024; 47:259-282. [PMID: 37676378 PMCID: PMC10899530 DOI: 10.1007/s13402-023-00867-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/23/2023] [Indexed: 09/08/2023] Open
Abstract
PURPOSE For patients with osteosarcoma, disease-related mortality most often results from lung metastasis-a phenomenon shared with many solid tumors. While established metastatic lesions behave aggressively, very few of the tumor cells that reach the lung will survive. By identifying mechanisms that facilitate survival of disseminated tumor cells, we can develop therapeutic strategies that prevent and treat metastasis. METHODS We analyzed single cell RNA-sequencing (scRNAseq) data from murine metastasis-bearing lungs to interrogate changes in both host and tumor cells during colonization. We used these data to elucidate pathways that become activated in cells that survive dissemination and identify candidate host-derived signals that drive activation. We validated these findings through live cell reporter systems, immunocytochemistry, and fluorescent immunohistochemistry. We then validated the functional relevance of key candidates using pharmacologic inhibition in models of metastatic osteosarcoma. RESULTS Expression patterns suggest that the MAPK pathway is significantly elevated in early and established metastases. MAPK activity correlates with expression of anti-apoptotic genes, especially MCL1. Niche cells produce growth factors that increase ERK phosphorylation and MCL1 expression in tumor cells. Both early and established metastases are vulnerable to MCL1 inhibition, but not MEK inhibition in vivo. Combining MCL1 inhibition with chemotherapy both prevented colonization and eliminated established metastases in murine models of osteosarcoma. CONCLUSION Niche-derived growth factors drive MAPK activity and MCL1 expression in osteosarcoma, promoting metastatic colonization. Although later metastases produce less MCL1, they remain dependent on it. MCL1 is a promising target for clinical trials in both human and canine patients.
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Affiliation(s)
- Camille A McAloney
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH, USA
- Center for Childhood Cancers and Blood Diseases, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Rawan Makkawi
- Knight Cancer Institute's, Cancer Early Detection Advanced Research Center, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR, 97239, USA
| | - Yogesh Budhathoki
- Center for Childhood Cancers and Blood Diseases, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
- Molecular, Cellular, and Developmental Biology Program, The Ohio State University, Columbus, OH, USA
| | - Matthew V Cannon
- Center for Childhood Cancers and Blood Diseases, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Emily M Franz
- Center for Childhood Cancers and Blood Diseases, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
- Molecular, Cellular, and Developmental Biology Program, The Ohio State University, Columbus, OH, USA
| | - Amy C Gross
- Center for Childhood Cancers and Blood Diseases, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Maren Cam
- Center for Childhood Cancers and Blood Diseases, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Tatyana A Vetter
- Center for Gene Therapy, Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, OH, USA
- Department of Pediatrics, The Ohio State University, Columbus, OH, USA
| | - Rebekka Duhen
- Knight Cancer Institute's, Cancer Early Detection Advanced Research Center, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR, 97239, USA
| | - Alexander E Davies
- Knight Cancer Institute's, Cancer Early Detection Advanced Research Center, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR, 97239, USA.
| | - Ryan D Roberts
- Center for Childhood Cancers and Blood Diseases, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA.
- Division of Pediatric Hematology, Oncology, and BMT, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH, 43205, USA.
- The Ohio State University James Comprehensive Cancer Center, Columbus, OH, USA.
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13
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Du T, Hu X, Hou Z, Wang W, You S, Wang M, Ji M, Xue N, Chen X. Re-expression of epigenetically silenced PTPRR by histone acetylation sensitizes RAS-mutant lung adenocarcinoma to SHP2 inhibition. Cell Mol Life Sci 2024; 81:64. [PMID: 38280930 PMCID: PMC11073200 DOI: 10.1007/s00018-023-05034-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 10/17/2023] [Accepted: 11/05/2023] [Indexed: 01/29/2024]
Abstract
Silenced protein tyrosine phosphatase receptor type R (PTPRR) participates in mitogen-activated protein kinase (MAPK) signaling cascades during the genesis and development of tumors. Rat sarcoma virus (Ras) genes are frequently mutated in lung adenocarcinoma, thereby resulting in hyperactivation of downstream MAPK signaling. However, the molecular mechanism manipulating the regulation and function of PTPRR in RAS-mutant lung adenocarcinoma is not known. Patient records collected from the Cancer Genome Atlas and Gene Expression Omnibus showed that silenced PTPRR was positively correlated with the prognosis. Exogenous expression of PTPRR suppressed the proliferation and migration of lung cancer cells. PTPRR expression and Src homology 2 containing protein tyrosine phosphatase 2 (SHP2) inhibition acted synergistically to control ERK1/2 phosphorylation in RAS-driven lung cancer cells. Chromatin immunoprecipitation assay revealed that HDAC inhibition induced enriched histone acetylation in the promoter region of PTPRR and recovered PTPRR transcription. The combination of the HDAC inhibitor SAHA and SHP2 inhibitor SHP099 suppressed the progression of lung cancer markedly in vitro and in vivo. Therefore, we revealed the epigenetic silencing mechanism of PTPRR and demonstrated that combination therapy targeting HDAC and SHP2 might represent a novel strategy to treat RAS-mutant lung cancer.
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Affiliation(s)
- Tingting Du
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- Beijing Key Laboratory of Non-Clinical Drug Metabolism and PK/PD Study, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xiaowen Hu
- National Institutes for Food and Drug Control, Beijing, 102629, China
| | - Zhenyan Hou
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Weida Wang
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- Beijing Key Laboratory of Non-Clinical Drug Metabolism and PK/PD Study, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Shen You
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- Beijing Key Laboratory of Non-Clinical Drug Metabolism and PK/PD Study, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Mingjin Wang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- Beijing Key Laboratory of Non-Clinical Drug Metabolism and PK/PD Study, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Ming Ji
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
- Beijing Key Laboratory of Non-Clinical Drug Metabolism and PK/PD Study, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
| | - Nina Xue
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
- Beijing Key Laboratory of Non-Clinical Drug Metabolism and PK/PD Study, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
| | - Xiaoguang Chen
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
- Beijing Key Laboratory of Non-Clinical Drug Metabolism and PK/PD Study, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
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14
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Deschênes-Simard X, Malleshaiah M, Ferbeyre G. Extracellular Signal-Regulated Kinases: One Pathway, Multiple Fates. Cancers (Basel) 2023; 16:95. [PMID: 38201521 PMCID: PMC10778234 DOI: 10.3390/cancers16010095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024] Open
Abstract
This comprehensive review delves into the multifaceted aspects of ERK signaling and the intricate mechanisms underlying distinct cellular fates. ERK1 and ERK2 (ERK) govern proliferation, transformation, epithelial-mesenchymal transition, differentiation, senescence, or cell death, contingent upon activation strength, duration, and context. The biochemical mechanisms underlying these outcomes are inadequately understood, shaped by signaling feedback and the spatial localization of ERK activation. Generally, ERK activation aligns with the Goldilocks principle in cell fate determination. Inadequate or excessive ERK activity hinders cell proliferation, while balanced activation promotes both cell proliferation and survival. Unraveling the intricacies of how the degree of ERK activation dictates cell fate requires deciphering mechanisms encompassing protein stability, transcription factors downstream of ERK, and the chromatin landscape.
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Affiliation(s)
- Xavier Deschênes-Simard
- Montreal University Hospital Center (CHUM), Université de Montréal, Montréal, QC H3T 1J4, Canada;
| | - Mohan Malleshaiah
- Department of Biochemistry and Molecular Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada;
- Montreal Clinical Research Institute (IRCM), Montréal, QC H2W 1R7, Canada
| | - Gerardo Ferbeyre
- Montreal Clinical Research Institute (IRCM), Montréal, QC H2W 1R7, Canada
- Montreal Cancer Institute, CR-CHUM, Université de Montréal, Montréal, QC H3T 1J4, Canada
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15
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Ram A, Murphy D, DeCuzzi N, Patankar M, Hu J, Pargett M, Albeck JG. A guide to ERK dynamics, part 2: downstream decoding. Biochem J 2023; 480:1909-1928. [PMID: 38038975 PMCID: PMC10754290 DOI: 10.1042/bcj20230277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 11/03/2023] [Accepted: 11/09/2023] [Indexed: 12/02/2023]
Abstract
Signaling by the extracellular signal-regulated kinase (ERK) pathway controls many cellular processes, including cell division, death, and differentiation. In this second installment of a two-part review, we address the question of how the ERK pathway exerts distinct and context-specific effects on multiple processes. We discuss how the dynamics of ERK activity induce selective changes in gene expression programs, with insights from both experiments and computational models. With a focus on single-cell biosensor-based studies, we summarize four major functional modes for ERK signaling in tissues: adjusting the size of cell populations, gradient-based patterning, wave propagation of morphological changes, and diversification of cellular gene expression states. These modes of operation are disrupted in cancer and other related diseases and represent potential targets for therapeutic intervention. By understanding the dynamic mechanisms involved in ERK signaling, there is potential for pharmacological strategies that not only simply inhibit ERK, but also restore functional activity patterns and improve disease outcomes.
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Affiliation(s)
- Abhineet Ram
- Department of Molecular and Cellular Biology, University of California, Davis, CA, U.S.A
| | - Devan Murphy
- Department of Molecular and Cellular Biology, University of California, Davis, CA, U.S.A
| | - Nicholaus DeCuzzi
- Department of Molecular and Cellular Biology, University of California, Davis, CA, U.S.A
| | - Madhura Patankar
- Department of Molecular and Cellular Biology, University of California, Davis, CA, U.S.A
| | - Jason Hu
- Department of Molecular and Cellular Biology, University of California, Davis, CA, U.S.A
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, CA, U.S.A
| | - John G. Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, CA, U.S.A
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16
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Ram A, Murphy D, DeCuzzi N, Patankar M, Hu J, Pargett M, Albeck JG. A guide to ERK dynamics, part 1: mechanisms and models. Biochem J 2023; 480:1887-1907. [PMID: 38038974 PMCID: PMC10754288 DOI: 10.1042/bcj20230276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 11/02/2023] [Accepted: 11/06/2023] [Indexed: 12/02/2023]
Abstract
Extracellular signal-regulated kinase (ERK) has long been studied as a key driver of both essential cellular processes and disease. A persistent question has been how this single pathway is able to direct multiple cell behaviors, including growth, proliferation, and death. Modern biosensor studies have revealed that the temporal pattern of ERK activity is highly variable and heterogeneous, and critically, that these dynamic differences modulate cell fate. This two-part review discusses the current understanding of dynamic activity in the ERK pathway, how it regulates cellular decisions, and how these cell fates lead to tissue regulation and pathology. In part 1, we cover the optogenetic and live-cell imaging technologies that first revealed the dynamic nature of ERK, as well as current challenges in biosensor data analysis. We also discuss advances in mathematical models for the mechanisms of ERK dynamics, including receptor-level regulation, negative feedback, cooperativity, and paracrine signaling. While hurdles still remain, it is clear that higher temporal and spatial resolution provide mechanistic insights into pathway circuitry. Exciting new algorithms and advanced computational tools enable quantitative measurements of single-cell ERK activation, which in turn inform better models of pathway behavior. However, the fact that current models still cannot fully recapitulate the diversity of ERK responses calls for a deeper understanding of network structure and signal transduction in general.
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Affiliation(s)
- Abhineet Ram
- Department of Molecular and Cellular Biology, University of California, Davis, U.S.A
| | - Devan Murphy
- Department of Molecular and Cellular Biology, University of California, Davis, U.S.A
| | - Nicholaus DeCuzzi
- Department of Molecular and Cellular Biology, University of California, Davis, U.S.A
| | - Madhura Patankar
- Department of Molecular and Cellular Biology, University of California, Davis, U.S.A
| | - Jason Hu
- Department of Molecular and Cellular Biology, University of California, Davis, U.S.A
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, U.S.A
| | - John G. Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, U.S.A
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17
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Gagliardi PA, Grädel B, Jacques MA, Hinderling L, Ender P, Cohen AR, Kastberger G, Pertz O, Dobrzyński M. Automatic detection of spatio-temporal signaling patterns in cell collectives. J Cell Biol 2023; 222:e202207048. [PMID: 37516918 PMCID: PMC10374943 DOI: 10.1083/jcb.202207048] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 04/24/2023] [Accepted: 06/28/2023] [Indexed: 07/31/2023] Open
Abstract
Increasing experimental evidence points to the physiological importance of space-time correlations in signaling of cell collectives. From wound healing to epithelial homeostasis to morphogenesis, coordinated activation of biomolecules between cells allows the collectives to perform more complex tasks and to better tackle environmental challenges. To capture this information exchange and to advance new theories of emergent phenomena, we created ARCOS, a computational method to detect and quantify collective signaling. We demonstrate ARCOS on cell and organism collectives with space-time correlations on different scales in 2D and 3D. We made a new observation that oncogenic mutations in the MAPK/ERK and PIK3CA/Akt pathways of MCF10A epithelial cells hyperstimulate intercellular ERK activity waves that are largely dependent on matrix metalloproteinase intercellular signaling. ARCOS is open-source and available as R and Python packages. It also includes a plugin for the napari image viewer to interactively quantify collective phenomena without prior programming experience.
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Affiliation(s)
| | - Benjamin Grädel
- Institute of Cell Biology, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Marc-Antoine Jacques
- Institute of Cell Biology, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Lucien Hinderling
- Institute of Cell Biology, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Pascal Ender
- Institute of Cell Biology, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Andrew R. Cohen
- Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, USA
| | | | - Olivier Pertz
- Institute of Cell Biology, University of Bern, Bern, Switzerland
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18
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Al-khayyat W, Pirkkanen J, Dougherty J, Laframboise T, Dickinson N, Khaper N, Lees SJ, Mendonca MS, Boreham DR, Tai TC, Thome C, Tharmalingam S. Overexpression of FRA1 ( FOSL1) Leads to Global Transcriptional Perturbations, Reduced Cellular Adhesion and Altered Cell Cycle Progression. Cells 2023; 12:2344. [PMID: 37830558 PMCID: PMC10571788 DOI: 10.3390/cells12192344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 09/18/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023] Open
Abstract
FRA1 (FOSL1) is a transcription factor and a member of the activator protein-1 superfamily. FRA1 is expressed in most tissues at low levels, and its expression is robustly induced in response to extracellular signals, leading to downstream cellular processes. However, abnormal FRA1 overexpression has been reported in various pathological states, including tumor progression and inflammation. To date, the molecular effects of FRA1 overexpression are still not understood. Therefore, the aim of this study was to investigate the transcriptional and functional effects of FRA1 overexpression using the CGL1 human hybrid cell line. FRA1-overexpressing CGL1 cells were generated using stably integrated CRISPR-mediated transcriptional activation, resulting in a 2-3 fold increase in FRA1 mRNA and protein levels. RNA-sequencing identified 298 differentially expressed genes with FRA1 overexpression. Gene ontology analysis showed numerous molecular networks enriched with FRA1 overexpression, including transcription-factor binding, regulation of the extracellular matrix and adhesion, and a variety of signaling processes, including protein kinase activity and chemokine signaling. In addition, cell functional assays demonstrated reduced cell adherence to fibronectin and collagen with FRA1 overexpression and altered cell cycle progression. Taken together, this study unravels the transcriptional response mediated by FRA1 overexpression and establishes the role of FRA1 in adhesion and cell cycle progression.
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Affiliation(s)
- Wuroud Al-khayyat
- School of Natural Sciences, Laurentian University, Sudbury, ON P3E 2C6, Canada; (W.A.-k.); (N.D.); (D.R.B.); (T.C.T.); (C.T.)
- Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada; (J.P.); (J.D.); (T.L.)
| | - Jake Pirkkanen
- Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada; (J.P.); (J.D.); (T.L.)
| | - Jessica Dougherty
- Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada; (J.P.); (J.D.); (T.L.)
| | - Taylor Laframboise
- Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada; (J.P.); (J.D.); (T.L.)
| | - Noah Dickinson
- School of Natural Sciences, Laurentian University, Sudbury, ON P3E 2C6, Canada; (W.A.-k.); (N.D.); (D.R.B.); (T.C.T.); (C.T.)
| | - Neelam Khaper
- Medical Sciences Division, NOSM University, 955 Oliver Rd., Thunder Bay, ON P7B 5E1, Canada; (N.K.); (S.J.L.)
- Department of Biology, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
| | - Simon J. Lees
- Medical Sciences Division, NOSM University, 955 Oliver Rd., Thunder Bay, ON P7B 5E1, Canada; (N.K.); (S.J.L.)
- Department of Biology, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
| | - Marc S. Mendonca
- Department of Radiation Oncology, Radiation and Cancer Biology Laboratories, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Douglas R. Boreham
- School of Natural Sciences, Laurentian University, Sudbury, ON P3E 2C6, Canada; (W.A.-k.); (N.D.); (D.R.B.); (T.C.T.); (C.T.)
- Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada; (J.P.); (J.D.); (T.L.)
| | - Tze Chun Tai
- School of Natural Sciences, Laurentian University, Sudbury, ON P3E 2C6, Canada; (W.A.-k.); (N.D.); (D.R.B.); (T.C.T.); (C.T.)
- Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada; (J.P.); (J.D.); (T.L.)
- Health Sciences North Research Institute, Sudbury, ON P3E 2H2, Canada
| | - Christopher Thome
- School of Natural Sciences, Laurentian University, Sudbury, ON P3E 2C6, Canada; (W.A.-k.); (N.D.); (D.R.B.); (T.C.T.); (C.T.)
- Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada; (J.P.); (J.D.); (T.L.)
- Health Sciences North Research Institute, Sudbury, ON P3E 2H2, Canada
| | - Sujeenthar Tharmalingam
- School of Natural Sciences, Laurentian University, Sudbury, ON P3E 2C6, Canada; (W.A.-k.); (N.D.); (D.R.B.); (T.C.T.); (C.T.)
- Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada; (J.P.); (J.D.); (T.L.)
- Health Sciences North Research Institute, Sudbury, ON P3E 2H2, Canada
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19
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Sparta B, Kosaisawe N, Pargett M, Patankar M, DeCuzzi N, Albeck JG. Continuous sensing of nutrients and growth factors by the mTORC1-TFEB axis. eLife 2023; 12:e74903. [PMID: 37698461 PMCID: PMC10547473 DOI: 10.7554/elife.74903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 09/11/2023] [Indexed: 09/13/2023] Open
Abstract
mTORC1 senses nutrients and growth factors and phosphorylates downstream targets, including the transcription factor TFEB, to coordinate metabolic supply and demand. These functions position mTORC1 as a central controller of cellular homeostasis, but the behavior of this system in individual cells has not been well characterized. Here, we provide measurements necessary to refine quantitative models for mTORC1 as a metabolic controller. We developed a series of fluorescent protein-TFEB fusions and a multiplexed immunofluorescence approach to investigate how combinations of stimuli jointly regulate mTORC1 signaling at the single-cell level. Live imaging of individual MCF10A cells confirmed that mTORC1-TFEB signaling responds continuously to individual, sequential, or simultaneous treatment with amino acids and the growth factor insulin. Under physiologically relevant concentrations of amino acids, we observe correlated fluctuations in TFEB, AMPK, and AKT signaling that indicate continuous activity adjustments to nutrient availability. Using partial least squares regression modeling, we show that these continuous gradations are connected to protein synthesis rate via a distributed network of mTORC1 effectors, providing quantitative support for the qualitative model of mTORC1 as a homeostatic controller and clarifying its functional behavior within individual cells.
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Affiliation(s)
- Breanne Sparta
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - Madhura Patankar
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - Nicholaus DeCuzzi
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
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20
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Ho EK, Oatman HR, McFann SE, Yang L, Johnson HE, Shvartsman SY, Toettcher JE. Dynamics of an incoherent feedforward loop drive ERK-dependent pattern formation in the early Drosophila embryo. Development 2023; 150:dev201818. [PMID: 37602510 PMCID: PMC10482391 DOI: 10.1242/dev.201818] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 08/11/2023] [Indexed: 08/22/2023]
Abstract
Positional information in development often manifests as stripes of gene expression, but how stripes form remains incompletely understood. Here, we use optogenetics and live-cell biosensors to investigate the posterior brachyenteron (byn) stripe in early Drosophila embryos. This stripe depends on interpretation of an upstream ERK activity gradient and the expression of two target genes, tailless (tll) and huckebein (hkb), that exert antagonistic control over byn. We find that high or low doses of ERK signaling produce transient or sustained byn expression, respectively. Although tll transcription is always rapidly induced, hkb converts graded ERK inputs into a variable time delay. Nuclei thus interpret ERK amplitude through the relative timing of tll and hkb transcription. Antagonistic regulatory paths acting on different timescales are hallmarks of an incoherent feedforward loop, which is sufficient to explain byn dynamics and adds temporal complexity to the steady-state model of byn stripe formation. We further show that 'blurring' of an all-or-none stimulus through intracellular diffusion non-locally produces a byn stripe. Overall, we provide a blueprint for using optogenetics to dissect developmental signal interpretation in space and time.
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Affiliation(s)
- Emily K. Ho
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Harrison R. Oatman
- Program in Quantitative and Computational Biology, Princeton University, Princeton, NJ 08544, USA
| | - Sarah E. McFann
- Department of Chemical & Biological Engineering, Princeton University, Princeton, NJ 08544, USA
| | - Liu Yang
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Heath E. Johnson
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Stanislav Y. Shvartsman
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
- Center for Computational Biology, Flatiron Institute - Simons Foundation, New York, NY 10010, USA
| | - Jared E. Toettcher
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
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21
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Feng S, Sanford JA, Weber T, Hutchinson-Bunch CM, Dakup PP, Paurus VL, Attah K, Sauro HM, Qian WJ, Wiley HS. A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.03.551714. [PMID: 37577496 PMCID: PMC10418157 DOI: 10.1101/2023.08.03.551714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Building mechanistic models of kinase-driven signaling pathways requires quantitative measurements of protein phosphorylation across physiologically relevant conditions, but this is rarely done because of the insensitivity of traditional technologies. By using a multiplexed deep phosphoproteome profiling workflow, we were able to generate a deep phosphoproteomics dataset of the EGFR-MAPK pathway in non-transformed MCF10A cells across physiological ligand concentrations with a time resolution of <12 min and in the presence and absence of multiple kinase inhibitors. An improved phosphosite mapping technique allowed us to reliably identify >46,000 phosphorylation sites on >6600 proteins, of which >4500 sites from 2110 proteins displayed a >2-fold increase in phosphorylation in response to EGF. This data was then placed into a cellular context by linking it to 15 previously published protein databases. We found that our results were consistent with much, but not all previously reported data regarding the activation and negative feedback phosphorylation of core EGFR-ERK pathway proteins. We also found that EGFR signaling is biphasic with substrates downstream of RAS/MAPK activation showing a maximum response at <3ng/ml EGF while direct substrates, such as HGS and STAT5B, showing no saturation. We found that RAS activation is mediated by at least 3 parallel pathways, two of which depend on PTPN11. There appears to be an approximately 4-minute delay in pathway activation at the step between RAS and RAF, but subsequent pathway phosphorylation was extremely rapid. Approximately 80 proteins showed a >2-fold increase in phosphorylation across all experiments and these proteins had a significantly higher median number of phosphorylation sites (~18) relative to total cellular phosphoproteins (~4). Over 60% of EGF-stimulated phosphoproteins were downstream of MAPK and included mediators of cellular processes such as gene transcription, transport, signal transduction and cytoskeletal arrangement. Their phosphorylation was either linear with respect to MAPK activation or biphasic, corresponding to the biphasic signaling seen at the level of the EGFR. This deep, integrated phosphoproteomics data resource should be useful in building mechanistic models of EGFR and MAPK signaling and for understanding how downstream responses are regulated.
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Affiliation(s)
- Song Feng
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | - James A. Sanford
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | - Thomas Weber
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | | | - Panshak P. Dakup
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | - Vanessa L. Paurus
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | - Kwame Attah
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | - Herbert M. Sauro
- Department of Bioengineering, University of Washington, Seattle, WA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | - H. Steven Wiley
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352 USA
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22
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Hoffman TE, Nangia V, Ryland C, Passanisi VJ, Armstrong C, Yang C, Spencer SL. Multiple cancers escape from multiple MAPK pathway inhibitors and use DNA replication stress signaling to tolerate aberrant cell cycles. Sci Signal 2023; 16:eade8744. [PMID: 37527351 PMCID: PMC10704347 DOI: 10.1126/scisignal.ade8744] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 07/13/2023] [Indexed: 08/03/2023]
Abstract
Many cancers harbor pro-proliferative mutations of the mitogen-activated protein kinase (MAPK) pathway. In BRAF-driven melanoma cells treated with BRAF inhibitors, subpopulations of cells escape drug-induced quiescence through a nongenetic manner of adaptation and resume slow proliferation. Here, we found that this phenomenon is common to many cancer types driven by EGFR, KRAS, or BRAF mutations in response to multiple, clinically approved MAPK pathway inhibitors. In 2D cultures and 3D spheroid models of various cancer cell lines, a subset of cells escaped drug-induced quiescence within 4 days to resume proliferation. These "escapee" cells exhibited DNA replication deficits, accumulated DNA lesions, and mounted a stress response that depended on the ataxia telangiectasia and RAD3-related (ATR) kinase. We further identified that components of the Fanconi anemia (FA) DNA repair pathway are recruited to sites of mitotic DNA synthesis (MiDAS) in escapee cells, enabling successful completion of cell division. Analysis of patient tumor samples and clinical data correlated disease progression with an increase in DNA replication stress response factors. Our findings suggest that many MAPK pathway-mutant cancers rapidly escape drug action and that suppressing early stress tolerance pathways may achieve more durable clinical responses to MAPK pathway inhibitors.
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Affiliation(s)
- Timothy E. Hoffman
- Department of Biochemistry and Biofrontiers Institute, University of Colorado Boulder, Boulder, CO, 80303, USA
| | - Varuna Nangia
- Department of Biochemistry and Biofrontiers Institute, University of Colorado Boulder, Boulder, CO, 80303, USA
- Medical Scientist Training Program, University of Colorado-Anschutz Medical School, Aurora, CO, 80045, USA
| | - C. Ryland
- Department of Biochemistry and Biofrontiers Institute, University of Colorado Boulder, Boulder, CO, 80303, USA
| | - Victor J. Passanisi
- Department of Biochemistry and Biofrontiers Institute, University of Colorado Boulder, Boulder, CO, 80303, USA
| | - Claire Armstrong
- Department of Biochemistry and Biofrontiers Institute, University of Colorado Boulder, Boulder, CO, 80303, USA
| | - Chen Yang
- Department of Biochemistry and Biofrontiers Institute, University of Colorado Boulder, Boulder, CO, 80303, USA
- Molecular Cellular and Developmental Biology, University of Colorado Boulder, Boulder, CO, 80303, USA
| | - Sabrina L. Spencer
- Department of Biochemistry and Biofrontiers Institute, University of Colorado Boulder, Boulder, CO, 80303, USA
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23
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Teague S, Primavera G, Chen B, Freeburne E, Khan H, Jo K, Johnson C, Heemskerk I. The time integral of BMP signaling determines fate in a stem cell model for early human development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.10.536068. [PMID: 37090515 PMCID: PMC10120633 DOI: 10.1101/2023.04.10.536068] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
How paracrine signals are interpreted to yield multiple cell fate decisions in a dynamic context during human development in vivo and in vitro remains poorly understood. Here we report an automated tracking method to follow signaling histories linked to cell fate in large numbers of human pluripotent stem cells (hPSCs). Using an unbiased statistical approach, we discovered that measured BMP signaling history correlates strongly with fate in individual cells. We found that BMP response in hPSCs varies more strongly in the duration of signaling than the level. However, we discovered that both the level and duration of signaling activity control cell fate choices only by changing the time integral of signaling and that duration and level are therefore interchangeable in this context. In a stem cell model for patterning of the human embryo, we showed that signaling histories predict the fate pattern and that the integral model correctly predicts changes in cell fate domains when signaling is perturbed. Using an RNA-seq screen we then found that mechanistically, BMP signaling is integrated by SOX2.
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Affiliation(s)
- Seth Teague
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Gillian Primavera
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Bohan Chen
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan
| | - Emily Freeburne
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Hina Khan
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Kyoung Jo
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Craig Johnson
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Idse Heemskerk
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, Michigan
- Center for Cell Plasticity and Organ Design, University of Michigan Medical School, Ann Arbor, Michigan
- Department of Physics, University of Michigan, Ann Arbor, Michigan
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24
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Ho EK, Oatman HR, McFann SE, Yang L, Johnson HE, Shvartsman SY, Toettcher JE. Dynamics of an incoherent feedforward loop drive ERK-dependent pattern formation in the early Drosophila embryo. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.09.531972. [PMID: 36945584 PMCID: PMC10028984 DOI: 10.1101/2023.03.09.531972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Positional information in developing tissues often takes the form of stripes of gene expression that mark the boundaries of a particular cell type or morphogenetic process. How stripes form is still in many cases poorly understood. Here we use optogenetics and live-cell biosensors to investigate one such pattern: the posterior stripe of brachyenteron (byn) expression in the early Drosophila embryo. This byn stripe depends on interpretation of an upstream signal - a gradient of ERK kinase activity - and the expression of two target genes tailless (tll) and huckebein (hkb) that exert antagonistic control over byn . We find that high or low doses of ERK signaling produce either transient or sustained byn expression, respectively. These ERK stimuli also regulate tll and hkb expression with distinct dynamics: tll transcription is rapidly induced under both low and high stimuli, whereas hkb transcription converts graded ERK inputs into an output switch with a variable time delay. Antagonistic regulatory paths acting on different timescales are hallmarks of an incoherent feedforward loop architecture, which is sufficient to explain transient or sustained byn dynamics and adds temporal complexity to the steady-state model of byn stripe formation. We further show that an all-or-none stimulus can be 'blurred' through intracellular diffusion to non-locally produce a stripe of byn gene expression. Overall, our study provides a blueprint for using optogenetic inputs to dissect developmental signal interpretation in space and time.
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Affiliation(s)
- Emily K Ho
- Department of Molecular Biology Princeton University, Princeton NJ 08544
| | - Harrison R Oatman
- Program in Quantitative and Computational Biology Princeton University, Princeton NJ 08544
| | - Sarah E McFann
- Department of Chemical & Biological Engineering Princeton University, Princeton NJ 08544
| | - Liu Yang
- Lewis Sigler Institute for Integrative Genomics Princeton University, Princeton NJ 08544
| | - Heath E Johnson
- Department of Molecular Biology Princeton University, Princeton NJ 08544
| | - Stanislav Y Shvartsman
- Department of Molecular Biology Princeton University, Princeton NJ 08544
- Lewis Sigler Institute for Integrative Genomics Princeton University, Princeton NJ 08544
- Flatiron Institute, New York, NY 10010
| | - Jared E Toettcher
- Department of Molecular Biology Princeton University, Princeton NJ 08544
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25
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Tran AP, Tralie CJ, Reyes J, Moosmüller C, Belkhatir Z, Kevrekidis IG, Levine AJ, Deasy JO, Tannenbaum AR. Long-term p21 and p53 dynamics regulate the frequency of mitosis events and cell cycle arrest following radiation damage. Cell Death Differ 2023; 30:660-672. [PMID: 36182991 PMCID: PMC9984379 DOI: 10.1038/s41418-022-01069-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 09/12/2022] [Accepted: 09/14/2022] [Indexed: 11/07/2022] Open
Abstract
Radiation exposure of healthy cells can halt cell cycle temporarily or permanently. In this work, we analyze the time evolution of p21 and p53 from two single cell datasets of retinal pigment epithelial cells exposed to several levels of radiation, and in particular, the effect of radiation on cell cycle arrest. Employing various quantification methods from signal processing, we show how p21 levels, and to a lesser extent p53 levels, dictate whether the cells are arrested in their cell cycle and how frequently these mitosis events are likely to occur. We observed that single cells exposed to the same dose of DNA damage exhibit heterogeneity in cellular outcomes and that the frequency of cell division is a more accurate monitor of cell damage rather than just radiation level. Finally, we show how heterogeneity in DNA damage signaling is manifested early in the response to radiation exposure level and has potential to predict long-term fate.
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Affiliation(s)
- Anh Phong Tran
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Christopher J Tralie
- Department of Mathematics and Computer Science, Ursinus College, Collegeville, PA, USA
| | - José Reyes
- Cancer Biology and Genetics Program and Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Caroline Moosmüller
- Department of Mathematics, University of California, San Diego, La Jolla, CA, USA
| | - Zehor Belkhatir
- School of Engineering and Sustainable Development, De Montfort University, Leicester, UK
| | - Ioannis G Kevrekidis
- Department of Chemical and Biological Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Arnold J Levine
- Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ, USA
| | - Joseph O Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Allen R Tannenbaum
- Departments of Computer Science and Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY, USA.
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26
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Pargett M, Ram AR, Murthy V, Davies AE. Live-Cell Sender-Receiver Co-cultures for Quantitative Measurement of Paracrine Signaling Dynamics, Gene Expression, and Drug Response. Methods Mol Biol 2023; 2634:285-314. [PMID: 37074584 DOI: 10.1007/978-1-0716-3008-2_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Abstract
Paracrine signaling is a fundamental process regulating tissue development, repair, and pathogenesis of diseases such as cancer. Herein we describe a method for quantitatively measuring paracrine signaling dynamics, and resultant gene expression changes, in living cells using genetically encoded signaling reporters and fluorescently tagged gene loci. We discuss considerations for selecting paracrine "sender-receiver" cell pairs, appropriate reporters, the use of this system to ask diverse experimental questions and screen drugs blocking intracellular communication, data collection, and the use of computational approaches to model and interpret these experiments.
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Affiliation(s)
- Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA, USA
| | - Abhineet R Ram
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA, USA
| | - Vaibhav Murthy
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH, USA
- Knight Cancer Institute, Cancer Early Detection Advanced Research Center, Oregon Health & Science University, Portland, OR, USA
| | - Alexander E Davies
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH, USA.
- Knight Cancer Institute, Cancer Early Detection Advanced Research Center, Oregon Health & Science University, Portland, OR, USA.
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27
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Abstract
Ultradian rhythms in metabolism and physiology have been described previously in mammals. However, the underlying mechanisms for these rhythms are still elusive. Here, we report the discovery of temperature-sensitive ultradian rhythms in mammalian fibroblasts that are independent of both the cell cycle and the circadian clock. The period in each culture is stable over time but varies in different cultures (ranging from 3 to 24 h). We show that transient, single-cell metabolic pulses are synchronized into stable ultradian rhythms across contacting cells in culture by gap junction-mediated coupling. Coordinated rhythms are also apparent for other metabolic and physiological measures, including plasma membrane potential (Δψp), intracellular glutamine, α-ketoglutarate, intracellular adenosine triphosphate (ATP), cytosolic pH, and intracellular calcium. Moreover, these ultradian rhythms require extracellular glutamine, several different ion channels, and the suppression of mitochondrial ATP synthase by α-ketoglutarate, which provides a key feedback mechanism. We hypothesize that cellular coupling and metabolic feedback can be used by cells to balance energy demands for survival.
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28
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Gross SM, Dane MA, Smith RL, Devlin KL, McLean IC, Derrick DS, Mills CE, Subramanian K, London AB, Torre D, Evangelista JE, Clarke DJB, Xie Z, Erdem C, Lyons N, Natoli T, Pessa S, Lu X, Mullahoo J, Li J, Adam M, Wassie B, Liu M, Kilburn DF, Liby TA, Bucher E, Sanchez-Aguila C, Daily K, Omberg L, Wang Y, Jacobson C, Yapp C, Chung M, Vidovic D, Lu Y, Schurer S, Lee A, Pillai A, Subramanian A, Papanastasiou M, Fraenkel E, Feiler HS, Mills GB, Jaffe JD, Ma’ayan A, Birtwistle MR, Sorger PK, Korkola JE, Gray JW, Heiser LM. A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses. Commun Biol 2022; 5:1066. [PMID: 36207580 PMCID: PMC9546880 DOI: 10.1038/s42003-022-03975-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 09/12/2022] [Indexed: 02/01/2023] Open
Abstract
The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.
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Affiliation(s)
- Sean M. Gross
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Mark A. Dane
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Rebecca L. Smith
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Kaylyn L. Devlin
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Ian C. McLean
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Daniel S. Derrick
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Caitlin E. Mills
- grid.38142.3c000000041936754XLaboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, MA USA
| | - Kartik Subramanian
- grid.38142.3c000000041936754XLaboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, MA USA
| | - Alexandra B. London
- grid.59734.3c0000 0001 0670 2351Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Denis Torre
- grid.59734.3c0000 0001 0670 2351Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - John Erol Evangelista
- grid.59734.3c0000 0001 0670 2351Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Daniel J. B. Clarke
- grid.59734.3c0000 0001 0670 2351Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Zhuorui Xie
- grid.59734.3c0000 0001 0670 2351Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Cemal Erdem
- grid.26090.3d0000 0001 0665 0280Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, SC USA
| | - Nicholas Lyons
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Ted Natoli
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Sarah Pessa
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Xiaodong Lu
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - James Mullahoo
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Jonathan Li
- grid.116068.80000 0001 2341 2786Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Miriam Adam
- grid.116068.80000 0001 2341 2786Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Brook Wassie
- grid.116068.80000 0001 2341 2786Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Moqing Liu
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - David F. Kilburn
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Tiera A. Liby
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Elmar Bucher
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Crystal Sanchez-Aguila
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA
| | - Kenneth Daily
- grid.430406.50000 0004 6023 5303Sage Bionetworks, Seattle, WA USA
| | - Larsson Omberg
- grid.430406.50000 0004 6023 5303Sage Bionetworks, Seattle, WA USA
| | - Yunguan Wang
- grid.38142.3c000000041936754XLaboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, MA USA
| | - Connor Jacobson
- grid.38142.3c000000041936754XLaboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, MA USA
| | - Clarence Yapp
- grid.38142.3c000000041936754XLaboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, MA USA
| | - Mirra Chung
- grid.38142.3c000000041936754XLaboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, MA USA
| | - Dusica Vidovic
- grid.26790.3a0000 0004 1936 8606Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Institute for Data Science & Computing, University of Miami, Miami, FL 33136 USA
| | - Yiling Lu
- grid.240145.60000 0001 2291 4776Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Stephan Schurer
- grid.26790.3a0000 0004 1936 8606Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Institute for Data Science & Computing, University of Miami, Miami, FL 33136 USA
| | - Albert Lee
- grid.94365.3d0000 0001 2297 5165Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, USA
| | - Ajay Pillai
- grid.94365.3d0000 0001 2297 5165Human Genome Research Institute, National Institutes of Health, Bethesda, USA
| | - Aravind Subramanian
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Malvina Papanastasiou
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Ernest Fraenkel
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.116068.80000 0001 2341 2786Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Heidi S. Feiler
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA ,grid.5288.70000 0000 9758 5690Knight Cancer Institute, OHSU, Portland, OR USA
| | - Gordon B. Mills
- grid.5288.70000 0000 9758 5690Knight Cancer Institute, OHSU, Portland, OR USA ,grid.5288.70000 0000 9758 5690Division of Oncological Sciences, OHSU, Portland, OR USA
| | - Jake D. Jaffe
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Avi Ma’ayan
- grid.59734.3c0000 0001 0670 2351Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Marc R. Birtwistle
- grid.26090.3d0000 0001 0665 0280Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, SC USA
| | - Peter K. Sorger
- grid.38142.3c000000041936754XLaboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, MA USA
| | - James E. Korkola
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA ,grid.5288.70000 0000 9758 5690Knight Cancer Institute, OHSU, Portland, OR USA
| | - Joe W. Gray
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA ,grid.5288.70000 0000 9758 5690Knight Cancer Institute, OHSU, Portland, OR USA
| | - Laura M. Heiser
- grid.5288.70000 0000 9758 5690Department of Biomedical Engineering, OHSU, Portland, OR USA ,grid.5288.70000 0000 9758 5690Knight Cancer Institute, OHSU, Portland, OR USA
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29
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Ender P, Gagliardi PA, Dobrzyński M, Frismantiene A, Dessauges C, Höhener T, Jacques MA, Cohen AR, Pertz O. Spatiotemporal control of ERK pulse frequency coordinates fate decisions during mammary acinar morphogenesis. Dev Cell 2022; 57:2153-2167.e6. [PMID: 36113484 DOI: 10.1016/j.devcel.2022.08.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 07/06/2022] [Accepted: 08/20/2022] [Indexed: 12/30/2022]
Abstract
The signaling events controlling proliferation, survival, and apoptosis during mammary epithelial acinar morphogenesis remain poorly characterized. By imaging single-cell ERK activity dynamics in MCF10A acini, we find that these fates depend on the average frequency of non-periodic ERK pulses. High pulse frequency is observed during initial acinus growth, correlating with rapid cell motility and proliferation. Subsequent decrease in motility correlates with lower ERK pulse frequency and quiescence. Later, during lumen formation, coordinated multicellular ERK waves emerge, correlating with high and low ERK pulse frequencies in outer surviving and inner dying cells, respectively. Optogenetic entrainment of ERK pulses causally connects high ERK pulse frequency with inner cell survival. Acini harboring the PIK3CA H1047R mutation display increased ERK pulse frequency and inner cell survival. Thus, fate decisions during acinar morphogenesis are coordinated by different spatiotemporal modalities of ERK pulse frequency.
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Affiliation(s)
- Pascal Ender
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | | | - Maciej Dobrzyński
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Agne Frismantiene
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Coralie Dessauges
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Thomas Höhener
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Marc-Antoine Jacques
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Andrew R Cohen
- Department of Electrical and Computer Engineering, Drexel University, 3120-40 Market Street, Suite 313, Philadelphia, PA 19104, USA
| | - Olivier Pertz
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland.
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30
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Comandante-Lou N, Baumann DG, Fallahi-Sichani M. AP-1 transcription factor network explains diverse patterns of cellular plasticity in melanoma cells. Cell Rep 2022; 40:111147. [PMID: 35926467 DOI: 10.1016/j.celrep.2022.111147] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 06/04/2022] [Accepted: 07/07/2022] [Indexed: 12/28/2022] Open
Abstract
Cellular plasticity associated with fluctuations in transcriptional programs allows individual cells in a tumor to adopt heterogeneous differentiation states and switch phenotype during their adaptive responses to therapies. Despite increasing knowledge of such transcriptional programs, the molecular basis of cellular plasticity remains poorly understood. Here, we combine multiplexed transcriptional and protein measurements at population and single-cell levels with multivariate statistical modeling to show that the state of AP-1 transcription factor network plays a unifying role in explaining diverse patterns of plasticity in melanoma. We find that a regulated balance among AP-1 factors cJUN, JUND, FRA2, FRA1, and cFOS determines the intrinsic diversity of differentiation states and adaptive responses to MAPK inhibitors in melanoma cells. Perturbing this balance through genetic depletion of specific AP-1 proteins, or by MAPK inhibitors, shifts cellular heterogeneity in a predictable fashion. Thus, AP-1 may serve as a critical node for manipulating cellular plasticity with potential therapeutic implications.
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Affiliation(s)
- Natacha Comandante-Lou
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Douglas G Baumann
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Mohammad Fallahi-Sichani
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; UVA Cancer Center, University of Virginia, Charlottesville, VA 22908, USA.
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31
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Cui H, Wei W, Qian M, Tian R, Fu X, Li H, Nan G, Yang T, Lin P, Chen X, Zhu Y, Wang B, Sun X, Dou J, Jiang J, Li L, Wang S, Chen Z. PDGFA-associated protein 1 is a novel target of c-Myc and contributes to colorectal cancer initiation and progression. Cancer Commun (Lond) 2022; 42:750-767. [PMID: 35716012 PMCID: PMC9395323 DOI: 10.1002/cac2.12322] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 04/26/2022] [Accepted: 06/06/2022] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The mechanism underlying colorectal cancer (CRC) initiation and progression remains elusive, and overall survival is far from satisfactory. Previous studies have shown that PDGFA-associated protein 1 (PDAP1) is upregulated in several cancers including CRC. Here, we aimed to identify the cause and consequence of PDAP1 dysregulation in CRC and evaluate its role as a potential therapeutic target. METHODS Multi-omics data analysis was performed to identify potential key players in CRC initiation and progression. Immunohistochemistry (IHC) staining was applied to determine the expression pattern of PDAP1 in CRC tissues. Pdap1 conditional knockout mice were used to establish colitis and CRC mouse models. RNA sequencing, a phosphoprotein antibody array, western blotting, histological analysis, 5-bromo-2'-deoxyuridine (BrdU) incorporation assay, and interactome analysis were applied to identify the underlying mechanisms of PDAP1. A human patient-derived xenograft (PDX) model was used to assess the potential of PDAP1 as a therapeutic target. RESULTS PDAP1 was identified as a potential key player in CRC development using multi-omics data analysis. PDAP1 was overexpressed in CRC cells and correlated with reduced overall survival. Further investigation showed that PDAP1 was critical for the regulation of cell proliferation, migration, invasion, and metastasis. Significantly, depletion of Pdap1 in intestinal epithelial cells impaired mucosal restitution in dextran sulfate sodium salt-induced colitis and inhibited tumor initiation and growth in colitis-associated cancers. Mechanistic studies showed that c-Myc directly transactivated PDAP1, which contributed to the high PDAP1 expression in CRC cells. PDAP1 interacted with the juxtamembrane domain of epidermal growth factor receptor (EGFR) and facilitated EGFR-mitogen-activated protein kinase (MAPK) signaling activation, which resulted in FOS-related antigen 1 (FRA-1) expression, thereby facilitating CRC progression. Notably, silencing of PDAP1 could hinder the growth of patient-derived xenografts that sustain high PDAP1 levels. CONCLUSIONS PDAP1 facilitates mucosal restitution and carcinogenesis in colitis-associated cancer. c-Myc-driven upregulation of PDAP1 promotes proliferation, migration, invasion, and metastasis of CRC cells via the EGFR-MAPK-FRA-1 signaling axis. These findings indicated that PDAP1 inhibition is warranted for CRC patients with PDAP1 overexpression.
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Affiliation(s)
- Hong‐Yong Cui
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Wei Wei
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Mei‐Rui Qian
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Ruo‐Fei Tian
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Xin Fu
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Hong‐Wei Li
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive DiseasesXijing Hospital of Digestive DiseasesFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Gang Nan
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Ting Yang
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
- Department of Clinical MedicineMedical College of Yan'an UniversityYan'anShaanxi716000P. R. China
| | - Peng Lin
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Xi Chen
- Key Laboratory of Synthetic and Natural Functional Molecule of the Ministry of EducationCollege of Chemistry and Materials ScienceNorthwest UniversityXi'anShaanxi710127P. R. China
| | - Yu‐Meng Zhu
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Bin Wang
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Xiu‐Xuan Sun
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Jian‐Hua Dou
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive DiseasesXijing Hospital of Digestive DiseasesFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Jian‐Li Jiang
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Ling Li
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Shi‐Jie Wang
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
| | - Zhi‐Nan Chen
- National Translational Science Center for Molecular Medicine & Department of Cell BiologyFourth Military Medical UniversityXi'anShaanxi710032P. R. China
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Ku BM, Heo JY, Kim J, Sun JM, Lee SH, Ahn JS, Park K, Ahn MJ. ERK inhibitor ASN007 effectively overcomes acquired resistance to EGFR inhibitor in non-small cell lung cancer. Invest New Drugs 2022; 40:265-273. [PMID: 34973117 PMCID: PMC8993753 DOI: 10.1007/s10637-021-01121-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 04/21/2021] [Indexed: 11/20/2022]
Abstract
The emergence of acquired resistance limits the long-term efficacy of EGFR tyrosine kinase inhibitors (EGFR TKIs). Thus, development of effective strategies to overcome resistance to EGFR TKI is urgently needed. Multiple mechanisms to reactivate ERK signaling have been successfully demonstrated in acquired resistance models. We found that in EGFR mutant non-small cell lung cancer (NSCLC) patients, acquired resistance to EGFR TKIs was accompanied by increased activation of ERK. Increased ERK activation was also found in in vitro models of acquired EGFR TKI resistance. ASN007 is a potent selective ERK1/2 inhibitor with promising antitumor activity in cancers with BRAF and RAS mutations. ASN007 treatment impeded tumor cell growth and the cell cycle in EGFR TKI-resistant cells. In addition, combination treatment with ASN007 and EGFR TKIs significantly decreased the survival of resistant cells, enhanced induction of apoptosis, and effectively inhibited the growth of erlotinib-resistant xenografts, providing the preclinical rationale for testing combinations of ASN007 and EGFR TKIs in EGFR-mutated NSCLC patients. This study emphasizes the importance of targeting ERK signaling in maintaining the long-term benefits of EGFR TKIs by overcoming acquired resistance.
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Affiliation(s)
- Bo Mi Ku
- Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jae Yeong Heo
- Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jinchul Kim
- Division of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
| | - Jong-Mu Sun
- Division of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
| | - Se-Hoon Lee
- Division of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
| | - Jin Seok Ahn
- Division of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
| | - Keunchil Park
- Division of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea
| | - Myung-Ju Ahn
- Division of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
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33
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Valls PO, Esposito A. Signalling dynamics, cell decisions, and homeostatic control in health and disease. Curr Opin Cell Biol 2022; 75:102066. [PMID: 35245783 PMCID: PMC9097822 DOI: 10.1016/j.ceb.2022.01.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 01/27/2022] [Accepted: 01/28/2022] [Indexed: 11/13/2022]
Abstract
Cell signalling engenders cells with the capability to receive and process information from the intracellular and extracellular environments, trigger and execute biological responses, and communicate with each other. Ultimately, cell signalling is responsible for maintaining homeostasis at the cellular, tissue and systemic level. For this reason, cell signalling is a topic of intense research efforts aimed to elucidate how cells coordinate transitions between states in developing and adult organisms in physiological and pathological conditions. Here, we review current knowledge of how cell signalling operates at multiple spatial and temporal scales, focusing on how single-cell analytical techniques reveal mechanisms underpinning cell-to-cell variability, signalling plasticity, and collective cellular responses.
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Affiliation(s)
- Pablo Oriol Valls
- MRC Cancer Unit, University of Cambridge, Cambridge, CB2 0XZ, United Kingdom
| | - Alessandro Esposito
- MRC Cancer Unit, University of Cambridge, Cambridge, CB2 0XZ, United Kingdom; Centre for Genome Engineering and Maintenance, College of Health, Medicine and Life Sciences, Brunel University London, Uxbridge, UB8 3PH, United Kingdom.
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34
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Jiménez A, Lu D, Kalocsay M, Berberich MJ, Balbi P, Jambhekar A, Lahav G. Time‐series transcriptomics and proteomics reveal alternative modes to decode p53 oscillations. Mol Syst Biol 2022; 18:e10588. [PMID: 35285572 PMCID: PMC8919251 DOI: 10.15252/msb.202110588] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 02/16/2022] [Accepted: 02/19/2022] [Indexed: 12/21/2022] Open
Affiliation(s)
- Alba Jiménez
- Department of Systems Biology Blavatnik Institute at Harvard Medical School Boston MA USA
| | - Dan Lu
- Department of Systems Biology Blavatnik Institute at Harvard Medical School Boston MA USA
| | - Marian Kalocsay
- Department of Systems Biology Blavatnik Institute at Harvard Medical School Boston MA USA
- Laboratory of Systems Pharmacology Blavatnik Institute at Harvard Medical School Boston MA USA
| | - Matthew J Berberich
- Laboratory of Systems Pharmacology Blavatnik Institute at Harvard Medical School Boston MA USA
- Center for Protein Degradation Dana‐Farber Cancer Institute Boston MA USA
| | - Petra Balbi
- Department of Systems Biology Blavatnik Institute at Harvard Medical School Boston MA USA
| | - Ashwini Jambhekar
- Department of Systems Biology Blavatnik Institute at Harvard Medical School Boston MA USA
- Ludwig Center at Harvard Medical School Boston MA USA
| | - Galit Lahav
- Department of Systems Biology Blavatnik Institute at Harvard Medical School Boston MA USA
- Ludwig Center at Harvard Medical School Boston MA USA
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35
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Phillips SMB, Bergstrom C, Walker B, Wang G, Alfaro T, Stromberg ZR, Hess BM. Engineered Cell Line Imaging Assay Differentiates Pathogenic from Non-Pathogenic Bacteria. Pathogens 2022; 11:pathogens11020209. [PMID: 35215152 PMCID: PMC8874627 DOI: 10.3390/pathogens11020209] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/31/2022] [Accepted: 02/02/2022] [Indexed: 01/27/2023] Open
Abstract
Cell culture systems have greatly expanded our understanding of how bacterial pathogens target signaling pathways to manipulate the host and cause infection. Advances in genetic engineering have allowed for the creation of fluorescent protein readouts within signaling pathways, but these techniques have been underutilized in pathogen biology. Here, we genetically engineered a lung cell line with fluorescent reporters for extracellular signal-related kinase (ERK) and the downstream transcription factor FOS-related antigen 1 (Fra1) and evaluated signaling after inoculation with pathogenic and non-pathogenic bacteria. Cells were inoculated with 100 colony-forming units of Acinetobacter baylyi, Klebsiella pneumoniae, Pseudomonas aeruginosa, Streptococcus agalactiae, or Staphylococcus epidermidis and imaged in a multi-mode reader. The alamarBlue cell viability assay was used as a reference test and showed that pathogenic P. aeruginosa induced significant (p < 0.05) cell death after 8 h in both wild-type and engineered cell lines compared to non-pathogenic S. epidermidis. In engineered cells, we found that Fra1 signaling was disrupted in as little as 4 h after inoculation with bacterial pathogens compared to delayed disruption in signaling by non-pathogenic S. epidermidis. Overall, we demonstrate that low levels of pathogenic versus non-pathogenic bacteria can be rapidly and sensitively screened based on ERK-Fra1 signaling.
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36
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Loewith R, Roux A, Pertz O. Chemical-Biology-derived in vivo Sensors: Past, Present, and Future. Chimia (Aarau) 2021; 75:1017-1021. [PMID: 34920770 DOI: 10.2533/chimia.2021.1017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
To understand the complex biochemistry and biophysics of biological systems, one needs to be able to monitor local concentrations of molecules, physical properties of macromolecular assemblies and activation status of signaling pathways, in real time, within single cells, and at high spatio-temporal resolution. Here we look at the tools that have been / are being / need to be provided by chemical biology to address these challenges. In particular, we highlight the utility of molecular probes that help to better measure mechanical forces and flux through key signalling pathways. Chemical biology can be used to both build biosensors to visualize, but also actuators to perturb biological processes. An emergent theme is the possibility to multiplex measurements of multiple cellular processes. Advances in microscopy automation now allow us to acquire datasets for 1000's of cells. This produces high dimensional datasets that require computer vision approaches that automate image analysis. The high dimensionality of these datasets are often not immediately accessible to human intuition, and, similarly to 'omics technologies, require statistical approaches for their exploitation. The field of biosensor imaging is therefore experiencing a multidisciplinary transition that will enable it to realize its full potential as a tool to provide a deeper appreciation of cell physiology.
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Affiliation(s)
- Robbie Loewith
- National Centre for Competence in Research in Chemical Biology; Department of Molecular Biology, University of Geneva;,
| | - Aurélien Roux
- National Centre for Competence in Research in Chemical Biology; Department of Biochemistry, University of Geneva; Auré,
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37
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Krause HB, Bondarowicz H, Karls AL, McClean MN, Kreeger PK. Design and implementation of a microfluidic device capable of temporal growth factor delivery reveal filtering capabilities of the EGFR/ERK pathway. APL Bioeng 2021; 5:046101. [PMID: 34765858 PMCID: PMC8566012 DOI: 10.1063/5.0059011] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 10/15/2021] [Indexed: 12/30/2022] Open
Abstract
Utilizing microfluidics to mimic the dynamic temporal changes of growth factor and cytokine concentrations in vivo has greatly increased our understanding of how signal transduction pathways are structured to encode extracellular stimuli. To date, these devices have focused on delivering pulses of varying frequency, and there are limited cell culture models for delivering slowly increasing concentrations of stimuli that cells may experience in vivo. To examine this setting, we developed and validated a microfluidic device that can deliver increasing concentrations of growth factor over periods ranging from 6 to 24 h. Using this device and a fluorescent biosensor of extracellular-regulated kinase (ERK) activity, we delivered a slowly increasing concentration of epidermal growth factor (EGF) to human mammary epithelial cells and surprisingly observed minimal ERK activation, even at concentrations that stimulate robust activity in bolus delivery. The cells remained unresponsive to subsequent challenges with EGF, and immunocytochemistry suggested that the loss of an epidermal growth factor receptor was responsible. Cells were then challenged with faster rates of change of EGF, revealing an increased ERK activity as a function of rate of change. Specifically, both the fraction of cells that responded and the length of ERK activation time increased with the rate of change. This microfluidic device fills a gap in the current repertoire of in vitro microfluidic devices and demonstrates that slower, more physiological changes in growth factor presentation can reveal new regulatory mechanisms for how signal transduction pathways encode changes in the extracellular growth factor milieu.
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Affiliation(s)
- Harris B Krause
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Hanna Bondarowicz
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Alexis L Karls
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
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38
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Liu Y, Lin J, Chen Y, Li Z, Zhou J, Lu X, Chen Z, Zuo D. Omega‑3 polyunsaturated fatty acids inhibit IL‑11/STAT3 signaling in hepatocytes during acetaminophen hepatotoxicity. Int J Mol Med 2021; 48:190. [PMID: 34414450 PMCID: PMC8416141 DOI: 10.3892/ijmm.2021.5023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/02/2021] [Indexed: 01/11/2023] Open
Abstract
Omega-3 polyunsaturated fatty acids (n-3 PUFAs) exert a negative effect on IL-6 production in several liver disorders, including cirrhosis, acute liver failure and fatty liver disease. However, its effect on the production of IL-11, another important IL-6 family cytokine, remains unclear. IL-11 was found to be significantly elevated in acetaminophen (APAP)-induced liver damage. The aim of the present study was to investigate whether and how n-3 PUFAs modulate IL-11 production during APAP-induced liver injury. For that purpose, wild-type (WT) and fat-1 transgenic mice were intraperitoneally injected with APAP to induce liver injury. Serum was collected for ELISA and alanine aminotransferase assay. The hepatocytes of APAP-injected mice were isolated for reverse transcription-quantitative PCR and western blot analyses. For the in vitro study, primary hepatocytes isolated from WT or fat-1 mice were stimulated with APAP. The results revealed that both endogenous and exogenous n-3 PUFAs significantly aggravated APAP-induced liver damage via the downregulation of STAT3 signaling. Notably, n-3 PUFAs inhibited IL-11 expression, but not IL-6 expression in hepatocytes during the APAP challenge. Furthermore, it was demonstrated that limited phosphorylation of ERK1/2 and Fos-like-1 (Fra-1) expression are responsible for the n-3 PUFA-mediated inhibitory effect on IL-11 production in APAP-treated hepatocytes. It was concluded that n-3 PUFAs inhibit IL-11 production and further STAT3 activation in hepatocytes during APAP-induced liver injury. Therefore, ERK1/2-mediated Fra-1 expression is responsible for the effect of n-3 PUFAs on IL-11 expression.
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Affiliation(s)
- Yunzhi Liu
- Department of Medical Laboratory, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Jingmin Lin
- Guangdong Province Key Laboratory of Proteomics, Department of Immunology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Yu Chen
- Department of Medical Laboratory, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Zhuonan Li
- College of Marine Life Sciences, Ocean University of China, Qingdao, Shandong 266003, P.R. China
| | - Jia Zhou
- Guangdong Province Key Laboratory of Proteomics, Department of Immunology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Xiao Lu
- Guangdong Province Key Laboratory of Proteomics, Department of Immunology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Zhengliang Chen
- Guangdong Province Key Laboratory of Proteomics, Department of Immunology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Daming Zuo
- Department of Medical Laboratory, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
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39
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Gillies TE, Pargett M, Silva JM, Teragawa CK, McCormick F, Albeck JG. Oncogenic mutant RAS signaling activity is rescaled by the ERK/MAPK pathway. Mol Syst Biol 2021; 16:e9518. [PMID: 33073539 PMCID: PMC7569415 DOI: 10.15252/msb.20209518] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 09/02/2020] [Accepted: 09/21/2020] [Indexed: 12/22/2022] Open
Abstract
Activating mutations in RAS are present in ~ 30% of human tumors, and the resulting aberrations in ERK/MAPK signaling play a central role in oncogenesis. However, the form of these signaling changes is uncertain, with activating RAS mutants linked to both increased and decreased ERK activation in vivo. Rationally targeting the kinase activity of this pathway requires clarification of the quantitative effects of RAS mutations. Here, we use live‐cell imaging in cells expressing only one RAS isoform to quantify ERK activity with a new level of accuracy. We find that despite large differences in their biochemical activity, mutant KRAS isoforms within cells have similar ranges of ERK output. We identify roles for pathway‐level effects, including variation in feedback strength and feedforward modulation of phosphatase activity, that act to rescale pathway sensitivity, ultimately resisting changes in the dynamic range of ERK activity while preserving responsiveness to growth factor stimuli. Our results reconcile seemingly inconsistent reports within the literature and imply that the signaling changes induced by RAS mutations early in oncogenesis are subtle.
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Affiliation(s)
- Taryn E Gillies
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Jillian M Silva
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA
| | - Carolyn K Teragawa
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
| | - Frank McCormick
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA.,Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, CA, USA
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40
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Gagliardi PA, Dobrzyński M, Jacques MA, Dessauges C, Ender P, Blum Y, Hughes RM, Cohen AR, Pertz O. Collective ERK/Akt activity waves orchestrate epithelial homeostasis by driving apoptosis-induced survival. Dev Cell 2021; 56:1712-1726.e6. [PMID: 34081908 DOI: 10.1016/j.devcel.2021.05.007] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 02/16/2021] [Accepted: 05/09/2021] [Indexed: 12/20/2022]
Abstract
Cell death events continuously challenge epithelial barrier function yet are crucial to eliminate old or critically damaged cells. How such apoptotic events are spatio-temporally organized to maintain epithelial homeostasis remains unclear. We observe waves of extracellular-signal-regulated kinase (ERK) and AKT serine/threonine kinase (Akt) activity pulses that originate from apoptotic cells and propagate radially to healthy surrounding cells. This requires epidermal growth factor receptor (EGFR) and matrix metalloproteinase (MMP) signaling. At the single-cell level, ERK/Akt waves act as spatial survival signals that locally protect cells in the vicinity of the epithelial injury from apoptosis for a period of 3-4 h. At the cell population level, ERK/Akt waves maintain epithelial homeostasis (EH) in response to mild or intense environmental insults. Disruption of this spatial signaling system results in the inability of a model epithelial tissue to ensure barrier function in response to environmental insults.
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Affiliation(s)
| | - Maciej Dobrzyński
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Marc-Antoine Jacques
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Coralie Dessauges
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Pascal Ender
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Yannick Blum
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland
| | - Robert M Hughes
- Department of Chemistry, East Carolina University, 300 Science and Technology Building, Greenville, NC 27858-4353, USA
| | - Andrew R Cohen
- Department of Electrical and Computer Engineering, Drexel University, 3120-40 Market Street, Suite 313, Philadelphia, PA 19104, USA
| | - Olivier Pertz
- Institute of Cell Biology, University of Bern, Baltzerstrasse 4, 3012 Bern, Switzerland.
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41
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Li S, Counter CM. Signaling levels mold the RAS mutation tropism of urethane. eLife 2021; 10:67172. [PMID: 33998997 PMCID: PMC8128437 DOI: 10.7554/elife.67172] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 04/01/2021] [Indexed: 12/29/2022] Open
Abstract
RAS genes are commonly mutated in human cancer. Despite many possible mutations, individual cancer types often have a 'tropism' towards a specific subset of RAS mutations. As driver mutations, these patterns ostensibly originate from normal cells. High oncogenic RAS activity causes oncogenic stress and different oncogenic mutations can impart different levels of activity, suggesting a relationship between oncoprotein activity and RAS mutation tropism. Here, we show that changing rare codons to common in the murine Kras gene to increase protein expression shifts tumors induced by the carcinogen urethane from arising from canonical Q61 to biochemically less active G12 Kras driver mutations, despite the carcinogen still being biased towards generating Q61 mutations. Conversely, inactivating the tumor suppressor p53 to blunt oncogenic stress partially reversed this effect, restoring Q61 mutations. One interpretation of these findings is that the RAS mutation tropism of urethane arises from selection in normal cells for specific mutations that impart a narrow window of signaling that promotes proliferation without causing oncogenic stress.
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Affiliation(s)
- Siqi Li
- Pharmacology and Cancer Biology, Duke University, Durham, United States
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42
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Tian C, Yang C, Spencer SL. EllipTrack: A Global-Local Cell-Tracking Pipeline for 2D Fluorescence Time-Lapse Microscopy. Cell Rep 2021; 32:107984. [PMID: 32755578 DOI: 10.1016/j.celrep.2020.107984] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 05/29/2020] [Accepted: 07/09/2020] [Indexed: 12/12/2022] Open
Abstract
Time-lapse microscopy provides an unprecedented opportunity to monitor single-cell dynamics. However, tracking cells for long periods remains a technical challenge, especially for multi-day, large-scale movies with rapid cell migration, high cell density, and drug treatments that alter cell morphology/behavior. Here, we present EllipTrack, a global-local cell-tracking pipeline optimized for tracking such movies. EllipTrack first implements a global track-linking algorithm to construct tracks that maximize the probability of cell lineages. Tracking mistakes are then corrected with a local track-correction module in which tracks generated by the global algorithm are systematically examined and amended if a more probable alternative can be found. Through benchmarking, we show that EllipTrack outperforms state-of-the-art cell trackers and generates nearly error-free cell lineages for multiple large-scale movies. In addition, EllipTrack can adapt to time- and cell-density-dependent changes in cell migration speeds and requires minimal training datasets. EllipTrack is available at https://github.com/tianchengzhe/EllipTrack.
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Affiliation(s)
- Chengzhe Tian
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80303, USA; BioFrontiers Institute, University of Colorado Boulder, Boulder, CO 80303, USA.
| | - Chen Yang
- Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, Boulder, CO 80303, USA; BioFrontiers Institute, University of Colorado Boulder, Boulder, CO 80303, USA
| | - Sabrina L Spencer
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80303, USA; BioFrontiers Institute, University of Colorado Boulder, Boulder, CO 80303, USA.
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43
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Benary M, Bohn S, Lüthen M, Nolis IK, Blüthgen N, Loewer A. Disentangling Pro-mitotic Signaling during Cell Cycle Progression using Time-Resolved Single-Cell Imaging. Cell Rep 2021; 31:107514. [PMID: 32294432 DOI: 10.1016/j.celrep.2020.03.078] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 02/19/2020] [Accepted: 03/23/2020] [Indexed: 11/26/2022] Open
Abstract
Cells rely on input from extracellular growth factors to control their proliferation during development and adult homeostasis. Such mitogenic inputs are transmitted through multiple signaling pathways that synergize to precisely regulate cell cycle entry and progression. Although the architecture of these signaling networks has been characterized in molecular detail, their relative contribution, especially at later cell cycle stages, remains largely unexplored. By combining quantitative time-resolved measurements of fluorescent reporters in untransformed human cells with targeted pharmacological inhibitors and statistical analysis, we quantify epidermal growth factor (EGF)-induced signal processing in individual cells over time and dissect the dynamic contribution of downstream pathways. We define signaling features that encode information about extracellular ligand concentrations and critical time windows for inducing cell cycle transitions. We show that both extracellular signal-regulated kinase (ERK) and phosphatidylinositol 3-kinase (PI3K) activity are necessary for initial cell cycle entry, whereas only PI3K affects the duration of S phase at later stages of mitogenic signaling.
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Affiliation(s)
- Manuela Benary
- Institute of Pathology, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany; Institute for Theoretical Biology, Charité-Universitätsmedizin Berlin, 10115 Berlin, Germany; Integrative Research Institute Life Sciences, Humboldt University Berlin, 10115 Berlin, Germany
| | - Stefan Bohn
- Department of Biology, Technische Universität Darmstadt, 64287 Darmstadt, Germany
| | - Mareen Lüthen
- Institute of Pathology, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Ilias K Nolis
- Berlin Institute for Medical Systems Biology, Max Delbrueck Center in the Helmholtz Association, 13125 Berlin, Germany
| | - Nils Blüthgen
- Institute of Pathology, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany; Institute for Theoretical Biology, Charité-Universitätsmedizin Berlin, 10115 Berlin, Germany; Integrative Research Institute Life Sciences, Humboldt University Berlin, 10115 Berlin, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
| | - Alexander Loewer
- Department of Biology, Technische Universität Darmstadt, 64287 Darmstadt, Germany; Berlin Institute for Medical Systems Biology, Max Delbrueck Center in the Helmholtz Association, 13125 Berlin, Germany.
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44
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Quantifying single-cell ERK dynamics in colorectal cancer organoids reveals EGFR as an amplifier of oncogenic MAPK pathway signalling. Nat Cell Biol 2021; 23:377-390. [PMID: 33795873 PMCID: PMC7610573 DOI: 10.1038/s41556-021-00654-5] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 02/24/2021] [Indexed: 02/07/2023]
Abstract
Direct targeting of the downstream mitogen-activated protein kinase (MAPK) pathway to suppress extracellular-regulated kinase (ERK) activation in KRAS and BRAF mutant colorectal cancer (CRC) has proven clinically unsuccessful, but promising results have been obtained with combination therapies including epidermal growth factor receptor (EGFR) inhibition. To elucidate the interplay between EGF signalling and ERK activation in tumours, we used patient-derived organoids (PDOs) from KRAS and BRAF mutant CRCs. PDOs resemble in vivo tumours, model treatment response and are compatible with live-cell microscopy. We established real-time, quantitative drug response assessment in PDOs with single-cell resolution, using our improved fluorescence resonance energy transfer (FRET)-based ERK biosensor EKAREN5. We show that oncogene-driven signalling is strikingly limited without EGFR activity and insufficient to sustain full proliferative potential. In PDOs and in vivo, upstream EGFR activity rigorously amplifies signal transduction efficiency in KRAS or BRAF mutant MAPK pathways. Our data provide a mechanistic understanding of the effectivity of EGFR inhibitors within combination therapies against KRAS and BRAF mutant CRC.
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45
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Jacques M, Dobrzyński M, Gagliardi PA, Sznitman R, Pertz O. CODEX, a neural network approach to explore signaling dynamics landscapes. Mol Syst Biol 2021; 17:e10026. [PMID: 33835701 PMCID: PMC8034356 DOI: 10.15252/msb.202010026] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 03/01/2021] [Accepted: 03/03/2021] [Indexed: 12/19/2022] Open
Abstract
Current studies of cell signaling dynamics that use live cell fluorescent biosensors routinely yield thousands of single-cell, heterogeneous, multi-dimensional trajectories. Typically, the extraction of relevant information from time series data relies on predefined, human-interpretable features. Without a priori knowledge of the system, the predefined features may fail to cover the entire spectrum of dynamics. Here we present CODEX, a data-driven approach based on convolutional neural networks (CNNs) that identifies patterns in time series. It does not require a priori information about the biological system and the insights into the data are built through explanations of the CNNs' predictions. CODEX provides several views of the data: visualization of all the single-cell trajectories in a low-dimensional space, identification of prototypic trajectories, and extraction of distinctive motifs. We demonstrate how CODEX can provide new insights into ERK and Akt signaling in response to various growth factors, and we recapitulate findings in p53 and TGFβ-SMAD2 signaling.
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Affiliation(s)
| | | | | | - Raphael Sznitman
- ARTORG Center for Biomedical Engineering ResearchUniversity of BernBernSwitzerland
| | - Olivier Pertz
- Institute of Cell BiologyUniversity of BernBernSwitzerland
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46
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Lormeau C, Rudolf F, Stelling J. A rationally engineered decoder of transient intracellular signals. Nat Commun 2021; 12:1886. [PMID: 33767179 PMCID: PMC7994635 DOI: 10.1038/s41467-021-22190-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 03/05/2021] [Indexed: 12/20/2022] Open
Abstract
Cells can encode information about their environment by modulating signaling dynamics and responding accordingly. Yet, the mechanisms cells use to decode these dynamics remain unknown when cells respond exclusively to transient signals. Here, we approach design principles underlying such decoding by rationally engineering a synthetic short-pulse decoder in budding yeast. A computational method for rapid prototyping, TopoDesign, allowed us to explore 4122 possible circuit architectures, design targeted experiments, and then rationally select a single circuit for implementation. This circuit demonstrates short-pulse decoding through incoherent feedforward and positive feedback. We predict incoherent feedforward to be essential for decoding transient signals, thereby complementing proposed design principles of temporal filtering, the ability to respond to sustained signals, but not to transient signals. More generally, we anticipate TopoDesign to help designing other synthetic circuits with non-intuitive dynamics, simply by assembling available biological components.
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Affiliation(s)
- Claude Lormeau
- Department of Biosystems Science and Engineering and SIB Swiss Institute of Bioinformatics, ETH Zurich, Mattenstrasse 26, CH 4058, Basel, Switzerland
- Life Science Zurich Graduate School, Interdisciplinary PhD Program Systems Biology, Zurich, Switzerland
| | - Fabian Rudolf
- Department of Biosystems Science and Engineering and SIB Swiss Institute of Bioinformatics, ETH Zurich, Mattenstrasse 26, CH 4058, Basel, Switzerland
| | - Jörg Stelling
- Department of Biosystems Science and Engineering and SIB Swiss Institute of Bioinformatics, ETH Zurich, Mattenstrasse 26, CH 4058, Basel, Switzerland.
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47
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Ebata K, Yamashiro S, Iida K, Okada M. Building patient-specific models for receptor tyrosine kinase signaling networks. FEBS J 2021; 289:90-101. [PMID: 33755310 DOI: 10.1111/febs.15831] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 02/26/2021] [Accepted: 03/19/2021] [Indexed: 12/16/2022]
Abstract
Cancer progresses due to changes in the dynamic interactions of multidimensional factors associated with gene mutations. Cancer research has actively adopted computational methods, including data-driven and mathematical model-driven approaches, to identify causative factors and regulatory rules that can explain the complexity and diversity of cancers. A data-driven, statistics-based approach revealed correlations between gene alterations and clinical outcomes in many types of cancers. A model-driven mathematical approach has elucidated the dynamic features of cancer networks and identified the mechanisms of drug efficacy and resistance. More recently, machine learning methods have emerged that can be used for mining omics data and classifying patient. However, as the strengths and weaknesses of each method becoming apparent, new analytical tools are emerging to combine and improve the methodologies and maximize their predictive power for classifying cancer subtypes and prognosis. Here, we introduce recent advances in cancer systems biology aimed at personalized medicine, with focus on the receptor tyrosine kinase signaling network.
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Affiliation(s)
- Kyoichi Ebata
- Institute for Protein Research, Osaka University, Suita, Japan
| | - Sawa Yamashiro
- Institute for Protein Research, Osaka University, Suita, Japan
| | - Keita Iida
- Institute for Protein Research, Osaka University, Suita, Japan
| | - Mariko Okada
- Institute for Protein Research, Osaka University, Suita, Japan.,Center for Drug Design and Research, National Institutes of Biomedical Innovation, Health and Nutrition, Ibaraki, Japan.,Institute for Chemical Research, Kyoto University, Japan
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48
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Kosaisawe N, Sparta B, Pargett M, Teragawa CK, Albeck JG. Transient phases of OXPHOS inhibitor resistance reveal underlying metabolic heterogeneity in single cells. Cell Metab 2021; 33:649-665.e8. [PMID: 33561427 PMCID: PMC8005262 DOI: 10.1016/j.cmet.2021.01.014] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 10/13/2020] [Accepted: 01/13/2021] [Indexed: 12/16/2022]
Abstract
Cell-to-cell heterogeneity in metabolism plays an unknown role in physiology and pharmacology. To functionally characterize cellular variability in metabolism, we treated cells with inhibitors of oxidative phosphorylation (OXPHOS) and monitored their responses with live-cell reporters for ATP, ADP/ATP, or activity of the energy-sensing kinase AMPK. Across multiple OXPHOS inhibitors and cell types, we identified a subpopulation of cells resistant to activation of AMPK and reduction of ADP/ATP ratio. This resistant state persists transiently for at least several hours and can be inherited during cell divisions. OXPHOS inhibition suppresses the mTORC1 and ERK growth signaling pathways in sensitive cells, but not in resistant cells. Resistance is linked to a multi-factorial combination of increased glucose uptake, reduced protein biosynthesis, and G0/G1 cell-cycle status. Our results reveal dynamic fluctuations in cellular energetic balance and provide a basis for measuring and predicting the distribution of cellular responses to OXPHOS inhibition.
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Affiliation(s)
- Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Breanne Sparta
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Carolyn K Teragawa
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA.
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49
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The ERK mitogen-activated protein kinase signaling network: the final frontier in RAS signal transduction. Biochem Soc Trans 2021; 49:253-267. [PMID: 33544118 DOI: 10.1042/bst20200507] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 12/30/2020] [Accepted: 01/08/2021] [Indexed: 12/11/2022]
Abstract
The RAF-MEK-ERK mitogen-activated protein kinase (MAPK) cascade is aberrantly activated in a diverse set of human cancers and the RASopathy group of genetic developmental disorders. This protein kinase cascade is one of the most intensely studied cellular signaling networks and has been frequently targeted by the pharmaceutical industry, with more than 30 inhibitors either approved or under clinical evaluation. The ERK-MAPK cascade was originally depicted as a serial and linear, unidirectional pathway that relays extracellular signals, such as mitogenic stimuli, through the cytoplasm to the nucleus. However, we now appreciate that this three-tiered protein kinase cascade is a central core of a complex network with dynamic signaling inputs and outputs and autoregulatory loops. Despite our considerable advances in understanding the ERK-MAPK network, the ability of cancer cells to adapt to the inhibition of key nodes reveals a level of complexity that remains to be fully understood. In this review, we summarize important developments in our understanding of the ERK-MAPK network and identify unresolved issues for ongoing and future study.
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50
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Haggerty RA, Purvis JE. Inferring the structures of signaling motifs from paired dynamic traces of single cells. PLoS Comput Biol 2021; 17:e1008657. [PMID: 33539338 PMCID: PMC7889133 DOI: 10.1371/journal.pcbi.1008657] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 02/17/2021] [Accepted: 12/26/2020] [Indexed: 11/18/2022] Open
Abstract
Individual cells show variability in their signaling dynamics that often correlates with phenotypic responses, indicating that cell-to-cell variability is not merely noise but can have functional consequences. Based on this observation, we reasoned that cell-to-cell variability under the same treatment condition could be explained in part by a single signaling motif that maps different upstream signals into a corresponding set of downstream responses. If this assumption holds, then repeated measurements of upstream and downstream signaling dynamics in a population of cells could provide information about the underlying signaling motif for a given pathway, even when no prior knowledge of that motif exists. To test these two hypotheses, we developed a computer algorithm called MISC (Motif Inference from Single Cells) that infers the underlying signaling motif from paired time-series measurements from individual cells. When applied to measurements of transcription factor and reporter gene expression in the yeast stress response, MISC predicted signaling motifs that were consistent with previous mechanistic models of transcription. The ability to detect the underlying mechanism became less certain when a cell's upstream signal was randomly paired with another cell's downstream response, demonstrating how averaging time-series measurements across a population obscures information about the underlying signaling mechanism. In some cases, motif predictions improved as more cells were added to the analysis. These results provide evidence that mechanistic information about cellular signaling networks can be systematically extracted from the dynamical patterns of single cells.
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Affiliation(s)
- Raymond A. Haggerty
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Computational Medicine Program, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Curriculum for Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Jeremy E. Purvis
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Computational Medicine Program, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Curriculum for Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America
- * E-mail:
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