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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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2
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McNamara HM, Ramm B, Toettcher JE. Synthetic developmental biology: New tools to deconstruct and rebuild developmental systems. Semin Cell Dev Biol 2023; 141:33-42. [PMID: 35484026 PMCID: PMC10332110 DOI: 10.1016/j.semcdb.2022.04.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 04/13/2022] [Indexed: 11/16/2022]
Abstract
Technological advances have driven many recent advances in developmental biology. Light sheet imaging can reveal single-cell dynamics in living three-dimensional tissues, whereas single-cell genomic methods open the door to a complete catalogue of cell types and gene expression states. An equally powerful but complementary set of approaches are also becoming available to define development processes from the bottom up. These synthetic approaches aim to reconstruct the minimal developmental patterns, signaling processes, and gene networks that produce the basic set of developmental operations: spatial polarization, morphogen interpretation, tissue movement, and cellular memory. In this review we discuss recent approaches at the intersection of synthetic biology and development, including synthetic circuits to deliver and record signaling stimuli and synthetic reconstitution of pattern formation on multicellular scales.
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Affiliation(s)
- Harold M McNamara
- Lewis Sigler Institute, Princeton University, Princeton, NJ 08544, USA; Department of Physics, Princeton University, Princeton, NJ 08544, USA; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Beatrice Ramm
- Department of Physics, Princeton University, Princeton, NJ 08544, USA; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Jared E Toettcher
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
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3
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Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression. Cell Syst 2022; 13:353-364.e6. [PMID: 35298924 DOI: 10.1016/j.cels.2022.02.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 11/18/2021] [Accepted: 02/17/2022] [Indexed: 12/27/2022]
Abstract
Cells live in constantly changing environments and employ dynamic signaling pathways to transduce information about the signals they encounter. However, the mechanisms by which dynamic signals are decoded into appropriate gene expression patterns remain poorly understood. Here, we devise networked optogenetic pathways that achieve dynamic signal processing functions that recapitulate cellular information processing. Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling edge pulse detector and show that this circuit can be employed to demultiplex dynamically encoded signals. We combine this demultiplexer with dCas9-based gene networks to construct pulsatile signal filters and decoders. Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state. Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway. Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
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4
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A synthetic gene circuit for imaging-free detection of signaling pulses. Cell Syst 2022; 13:131-142.e13. [PMID: 34739875 PMCID: PMC8857027 DOI: 10.1016/j.cels.2021.10.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 07/20/2021] [Accepted: 10/14/2021] [Indexed: 12/24/2022]
Abstract
Cells employ intracellular signaling pathways to sense and respond to changes in their external environment. In recent years, live-cell biosensors have revealed complex pulsatile dynamics in many pathways, but studies of these signaling dynamics are limited by the necessity of live-cell imaging at high spatiotemporal resolution. Here, we describe an approach to infer pulsatile signaling dynamics from a single measurement in fixed cells using a pulse-detecting gene circuit. We computationally screened for circuits with the capability to selectively detect signaling pulses, revealing an incoherent feedforward topology that robustly performs this computation. We implemented the motif experimentally for the Erk signaling pathway using a single engineered transcription factor and fluorescent protein reporter. Our "recorder of Erk activity dynamics" (READer) responds sensitively to spontaneous and stimulus-driven Erk pulses. READer circuits open the door to permanently labeling transient, dynamic cell populations to elucidate the mechanistic underpinnings and biological consequences of signaling dynamics.
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5
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Basta LP, Hill-Oliva M, Paramore SV, Sharan R, Goh A, Biswas A, Cortez M, Little KA, Posfai E, Devenport D. New mouse models for high resolution and live imaging of planar cell polarity proteins in vivo. Development 2021; 148:271988. [PMID: 34463728 DOI: 10.1242/dev.199695] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 08/24/2021] [Indexed: 01/10/2023]
Abstract
The collective polarization of cellular structures and behaviors across a tissue plane is a near universal feature of epithelia known as planar cell polarity (PCP). This property is controlled by the core PCP pathway, which consists of highly conserved membrane-associated protein complexes that localize asymmetrically at cell junctions. Here, we introduce three new mouse models for investigating the localization and dynamics of transmembrane PCP proteins: Celsr1, Fz6 and Vangl2. Using the skin epidermis as a model, we characterize and verify the expression, localization and function of endogenously tagged Celsr1-3xGFP, Fz6-3xGFP and tdTomato-Vangl2 fusion proteins. Live imaging of Fz6-3xGFP in basal epidermal progenitors reveals that the polarity of the tissue is not fixed through time. Rather, asymmetry dynamically shifts during cell rearrangements and divisions, while global, average polarity of the tissue is preserved. We show using super-resolution STED imaging that Fz6-3xGFP and tdTomato-Vangl2 can be resolved, enabling us to observe their complex localization along junctions. We further explore PCP fusion protein localization in the trachea and neural tube, and discover new patterns of PCP expression and localization throughout the mouse embryo.
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Affiliation(s)
- Lena P Basta
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA
| | - Michael Hill-Oliva
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA.,Department of Medicine, Columbia University, New York, NY 10032USA
| | - Sarah V Paramore
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA
| | - Rishabh Sharan
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA
| | - Audrey Goh
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA
| | - Abhishek Biswas
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA.,Research Computing, Office of Information Technology, Princeton University, Princeton, NJ 08544, USA
| | - Marvin Cortez
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA
| | - Katherine A Little
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA
| | - Eszter Posfai
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA
| | - Danelle Devenport
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544USA
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6
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Beitz AM, Oakes CG, Galloway KE. Synthetic gene circuits as tools for drug discovery. Trends Biotechnol 2021; 40:210-225. [PMID: 34364685 DOI: 10.1016/j.tibtech.2021.06.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/24/2021] [Accepted: 06/25/2021] [Indexed: 12/19/2022]
Abstract
Within mammalian systems, there exists enormous opportunity to use synthetic gene circuits to enhance phenotype-based drug discovery, to map the molecular origins of disease, and to validate therapeutics in complex cellular systems. While drug discovery has relied on marker staining and high-content imaging in cell-based assays, synthetic gene circuits expand the potential for precision and speed. Here we present a vision of how circuits can improve the speed and accuracy of drug discovery by enhancing the efficiency of hit triage, capturing disease-relevant dynamics in cell-based assays, and simplifying validation and readouts from organoids and microphysiological systems (MPS). By tracking events and cellular states across multiple length and time scales, circuits will transform how we decipher the causal link between molecular events and phenotypes to improve the selectivity and sensitivity of cell-based assays.
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Affiliation(s)
- Adam M Beitz
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Conrad G Oakes
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Kate E Galloway
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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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: 6] [Impact Index Per Article: 2.0] [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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