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Andrews SS, Wiley HS, Sauro HM. Design patterns of biological cells. Bioessays 2024; 46:e2300188. [PMID: 38247191 PMCID: PMC10922931 DOI: 10.1002/bies.202300188] [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: 09/30/2023] [Revised: 12/03/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024]
Abstract
Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.
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Affiliation(s)
- Steven S. Andrews
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - H. Steven Wiley
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Herbert M. Sauro
- Department of Bioengineering, University of Washington, Seattle, WA, USA
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2
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A focus on yeast mating: From pheromone signaling to cell-cell fusion. Semin Cell Dev Biol 2023; 133:83-95. [PMID: 35148940 DOI: 10.1016/j.semcdb.2022.02.003] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/31/2022] [Accepted: 02/02/2022] [Indexed: 12/14/2022]
Abstract
Cells live in a chemical environment and are able to orient towards chemical cues. Unicellular haploid fungal cells communicate by secreting pheromones to reproduce sexually. In the yeast models Saccharomyces cerevisiae and Schizosaccharomyces pombe, pheromonal communication activates similar pathways composed of cognate G-protein-coupled receptors and downstream small GTPase Cdc42 and MAP kinase cascades. Local pheromone release and sensing, at a mobile surface polarity patch, underlie spatial gradient interpretation to form pairs between two cells of distinct mating types. Concentration of secretion at the point of cell-cell contact then leads to local cell wall digestion for cell fusion, forming a diploid zygote that prevents further fusion attempts. A number of asymmetries between mating types may promote efficiency of the system. In this review, we present our current knowledge of pheromone signaling in the two model yeasts, with an emphasis on how cells decode the pheromone signal spatially and ultimately fuse together. Though overall pathway architectures are similar in the two species, their large evolutionary distance allows to explore how conceptually similar solutions to a general biological problem can arise from divergent molecular components.
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3
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Abstract
Accurate decoding of spatial chemical landscapes is critical for many cell functions. Eukaryotic cells decode local chemical gradients to orient growth or movement in productive directions. Recent work on yeast model systems, whose gradient sensing pathways display much less complexity than those in animal cells, has suggested new paradigms for how these very small cells successfully exploit information in noisy and dynamic pheromone gradients to identify their mates. Pheromone receptors regulate a polarity circuit centered on the conserved Rho-family GTPase, Cdc42. The polarity circuit contains both positive and negative feedback pathways, allowing spontaneous symmetry breaking and also polarity site disassembly and relocation. Cdc42 orients the actin cytoskeleton, leading to focused vesicle traffic that promotes movement of the polarity site and also reshapes the cortical distribution of receptors at the cell surface. In this article, we review the advances from work on yeasts and compare them with the excitable signaling pathways that have been revealed in chemotactic animal cells. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Debraj Ghose
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA;
| | - Timothy Elston
- Department of Pharmacology, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Daniel Lew
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA;
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4
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Ren S, Hu P, Jia J, Ni J, Jiang T, Yang H, Bai J, Tian C, Chen L, Huang Q, Lv B, Feng X, Li C. Engineering of Saccharomyces cerevisiae for sensing sweetness. Biochem Eng J 2022. [DOI: 10.1016/j.bej.2021.108239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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5
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Xu X, Quan W, Zhang F, Jin T. A systems approach to investigate GPCR-mediated Ras signaling network in chemoattractant sensing. Mol Biol Cell 2021; 33:ar23. [PMID: 34910560 PMCID: PMC9250378 DOI: 10.1091/mbc.e20-08-0545] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
A GPCR-mediated signaling network enables a chemotactic cell to generate adaptative Ras signaling in response to a large range of concentrations of a chemoattractant. To explore potential regulatory mechanisms of GPCR-controlled Ras signaling in chemosensing, we applied a software package, Simmune, to construct detailed spatiotemporal models simulating responses of the cAR1-mediated Ras signaling network. We first determined the dynamics of G-protein activation and Ras signaling in Dictyostelium cells in response to cAMP stimulations using live-cell imaging and then constructed computation models by incorporating potential mechanisms. Using simulations, we validated the dynamics of signaling events and predicted the dynamic profiles of those events in the cAR1-mediated Ras signaling networks with defective Ras inhibitory mechanisms, such as without RasGAP, with RasGAP overexpression, or with RasGAP hyperactivation. We describe a method of using Simmune to construct spatiotemporal models of a signaling network and run computational simulations without writing mathematical equations. This approach will help biologists to develop and analyze computational models that parallel live-cell experiments.
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Affiliation(s)
- Xuehua Xu
- Chemotaxis Signal Section, Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD 20852, USA
| | - Wei Quan
- Chemotaxis Signal Section, Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD 20852, USA
| | - Fengkai Zhang
- Computational Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Tian Jin
- Chemotaxis Signal Section, Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD 20852, USA
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Pomeroy AE, Peña MI, Houser JR, Dixit G, Dohlman HG, Elston TC, Errede B. A predictive model of gene expression reveals the role of network motifs in the mating response of yeast. Sci Signal 2021; 14:14/670/eabb5235. [PMID: 33593998 DOI: 10.1126/scisignal.abb5235] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Cells use signaling pathways to receive and process information about their environment. These nonlinear systems rely on feedback and feedforward regulation to respond appropriately to changing environmental conditions. Mathematical models describing signaling pathways often lack predictive power because they are not trained on data that encompass the diverse time scales on which these regulatory mechanisms operate. We addressed this limitation by measuring transcriptional changes induced by the mating response in Saccharomyces cerevisiae exposed to different dynamic patterns of pheromone. We found that pheromone-induced transcription persisted after pheromone removal and showed long-term adaptation upon sustained pheromone exposure. We developed a model of the regulatory network that captured both characteristics of the mating response. We fit this model to experimental data with an evolutionary algorithm and used the parameterized model to predict scenarios for which it was not trained, including different temporal stimulus profiles and genetic perturbations to pathway components. Our model allowed us to establish the role of four architectural elements of the network in regulating gene expression. These network motifs are incoherent feedforward, positive feedback, negative feedback, and repressor binding. Experimental and computational perturbations to these network motifs established a specific role for each in coordinating the mating response to persistent and dynamic stimulation.
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Affiliation(s)
- Amy E Pomeroy
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | - Matthew I Peña
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | - John R Houser
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Gauri Dixit
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Henrik G Dohlman
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Timothy C Elston
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. .,Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Beverly Errede
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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Shellhammer JP, Pomeroy AE, Li Y, Dujmusic L, Elston TC, Hao N, Dohlman HG. Quantitative analysis of the yeast pheromone pathway. Yeast 2019; 36:495-518. [PMID: 31022772 DOI: 10.1002/yea.3395] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 04/10/2019] [Accepted: 04/16/2019] [Indexed: 01/04/2023] Open
Abstract
The pheromone response pathway of the yeast Saccharomyces cerevisiae is a well-established model for the study of G proteins and mitogen-activated protein kinase (MAPK) cascades. Our longstanding ability to combine sophisticated genetic approaches with established functional assays has provided a thorough understanding of signalling mechanisms and regulation. In this report, we compare new and established methods used to quantify pheromone-dependent MAPK phosphorylation, transcriptional induction, mating morphogenesis, and gradient tracking. These include both single-cell and population-based assays of activity. We describe several technical advances, provide example data for benchmark mutants, highlight important differences between newer and established methodologies, and compare the advantages and disadvantages of each as applied to the yeast model. Quantitative measurements of pathway activity have been used to develop mathematical models and reveal new regulatory mechanisms in yeast. It is our expectation that experimental and computational approaches developed in yeast may eventually be adapted to human systems biology and pharmacology.
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Affiliation(s)
- James P Shellhammer
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Amy E Pomeroy
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Yang Li
- Division of Biological Sciences, University of California San Diego, San Diego, CA, 92093, USA
| | - Lorena Dujmusic
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Timothy C Elston
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.,Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Nan Hao
- Division of Biological Sciences, University of California San Diego, San Diego, CA, 92093, USA
| | - Henrik G Dohlman
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.,Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
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Emmerstorfer-Augustin A, Augustin CM, Shams S, Thorner J. Tracking yeast pheromone receptor Ste2 endocytosis using fluorogen-activating protein tagging. Mol Biol Cell 2018; 29:2720-2736. [PMID: 30207829 PMCID: PMC6249837 DOI: 10.1091/mbc.e18-07-0424] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
To observe internalization of the yeast pheromone receptor Ste2 by fluorescence microscopy in live cells in real time, we visualized only those molecules present at the cell surface at the time of agonist engagement (rather than the total cellular pool) by tagging this receptor at its N-terminus with an exocellular fluorogen-activating protein (FAP). A FAP is a single-chain antibody engineered to bind tightly a nonfluorescent, cell-impermeable dye (fluorogen), thereby generating a fluorescent complex. The utility of FAP tagging to study trafficking of integral membrane proteins in yeast, which possesses a cell wall, had not been examined previously. A diverse set of signal peptides and propeptide sequences were explored to maximize expression. Maintenance of the optimal FAP-Ste2 chimera intact required deletion of two, paralogous, glycosylphosphatidylinositol (GPI)-anchored extracellular aspartyl proteases (Yps1 and Mkc7). FAP-Ste2 exhibited a much brighter and distinct plasma membrane signal than Ste2-GFP or Ste2-mCherry yet behaved quite similarly. Using FAP-Ste2, new information was obtained about the mechanism of its internalization, including novel insights about the roles of the cargo-selective endocytic adaptors Ldb19/Art1, Rod1/Art4, and Rog3/Art7.
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Affiliation(s)
- Anita Emmerstorfer-Augustin
- Division of Biochemistry, Biophysics and Structural Biology, Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720-3202
| | - Christoph M Augustin
- Department of Mechanical Engineering, University of California, Berkeley, Berkeley, CA 94720-3202
| | - Shadi Shams
- Division of Biochemistry, Biophysics and Structural Biology, Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720-3202
| | - Jeremy Thorner
- Division of Biochemistry, Biophysics and Structural Biology, Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720-3202
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Atay O, Skotheim JM. Spatial and temporal signal processing and decision making by MAPK pathways. J Cell Biol 2017; 216:317-330. [PMID: 28043970 PMCID: PMC5294789 DOI: 10.1083/jcb.201609124] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Revised: 11/25/2016] [Accepted: 12/12/2016] [Indexed: 01/14/2023] Open
Abstract
Mitogen-activated protein kinase (MAPK) pathways are conserved from yeast to man and regulate a variety of cellular processes, including proliferation and differentiation. Recent developments show how MAPK pathways perform exquisite spatial and temporal signal processing and underscores the importance of studying the dynamics of signaling pathways to understand their physiological response. The importance of dynamic mechanisms that process input signals into graded downstream responses has been demonstrated in the pheromone-induced and osmotic stress-induced MAPK pathways in yeast and in the mammalian extracellular signal-regulated kinase MAPK pathway. Particularly, recent studies in the yeast pheromone response have shown how positive feedback generates switches, negative feedback enables gradient detection, and coherent feedforward regulation underlies cellular memory. More generally, a new wave of quantitative single-cell studies has begun to elucidate how signaling dynamics determine cell physiology and represents a paradigm shift from descriptive to predictive biology.
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Affiliation(s)
- Oguzhan Atay
- Department of Biology, Stanford University, Stanford, CA 94305
| | - Jan M Skotheim
- Department of Biology, Stanford University, Stanford, CA 94305
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Druey KM. Emerging Roles of Regulators of G Protein Signaling (RGS) Proteins in the Immune System. Adv Immunol 2017; 136:315-351. [PMID: 28950950 DOI: 10.1016/bs.ai.2017.05.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Kirk M Druey
- Molecular Signal Transduction Section, Laboratory of Allergic Diseases, NIAID/NIH, Bethesda, MD, United States.
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Bush A, Vasen G, Constantinou A, Dunayevich P, Patop IL, Blaustein M, Colman-Lerner A. Yeast GPCR signaling reflects the fraction of occupied receptors, not the number. Mol Syst Biol 2016; 12:898. [PMID: 28034910 PMCID: PMC5199120 DOI: 10.15252/msb.20166910] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
According to receptor theory, the effect of a ligand depends on the amount of agonist-receptor complex. Therefore, changes in receptor abundance should have quantitative effects. However, the response to pheromone in Saccharomyces cerevisiae is robust (unaltered) to increases or reductions in the abundance of the G-protein-coupled receptor (GPCR), Ste2, responding instead to the fraction of occupied receptor. We found experimentally that this robustness originates during G-protein activation. We developed a complete mathematical model of this step, which suggested the ability to compute fractional occupancy depends on the physical interaction between the inhibitory regulator of G-protein signaling (RGS), Sst2, and the receptor. Accordingly, replacing Sst2 by the heterologous hsRGS4, incapable of interacting with the receptor, abolished robustness. Conversely, forcing hsRGS4:Ste2 interaction restored robustness. Taken together with other results of our work, we conclude that this GPCR pathway computes fractional occupancy because ligand-bound GPCR-RGS complexes stimulate signaling while unoccupied complexes actively inhibit it. In eukaryotes, many RGSs bind to specific GPCRs, suggesting these complexes with opposing activities also detect fraction occupancy by a ratiometric measurement. Such complexes operate as push-pull devices, which we have recently described.
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Affiliation(s)
- Alan Bush
- Department of Physiology, Molecular and Cellular Biology, University of Buenos Aires, Buenos Aires, Argentina.,Institute of Physiology, Molecular Biology and Neurosciences, National Research Council (CONICET), Buenos Aires, Argentina
| | - Gustavo Vasen
- Department of Physiology, Molecular and Cellular Biology, University of Buenos Aires, Buenos Aires, Argentina.,Institute of Physiology, Molecular Biology and Neurosciences, National Research Council (CONICET), Buenos Aires, Argentina
| | - Andreas Constantinou
- Department of Physiology, Molecular and Cellular Biology, University of Buenos Aires, Buenos Aires, Argentina.,Institute of Physiology, Molecular Biology and Neurosciences, National Research Council (CONICET), Buenos Aires, Argentina
| | - Paula Dunayevich
- Department of Physiology, Molecular and Cellular Biology, University of Buenos Aires, Buenos Aires, Argentina.,Institute of Physiology, Molecular Biology and Neurosciences, National Research Council (CONICET), Buenos Aires, Argentina
| | - Inés Lucía Patop
- Department of Physiology, Molecular and Cellular Biology, University of Buenos Aires, Buenos Aires, Argentina.,Institute of Physiology, Molecular Biology and Neurosciences, National Research Council (CONICET), Buenos Aires, Argentina
| | - Matías Blaustein
- Department of Physiology, Molecular and Cellular Biology, University of Buenos Aires, Buenos Aires, Argentina.,Institute of Physiology, Molecular Biology and Neurosciences, National Research Council (CONICET), Buenos Aires, Argentina
| | - Alejandro Colman-Lerner
- Department of Physiology, Molecular and Cellular Biology, University of Buenos Aires, Buenos Aires, Argentina .,Institute of Physiology, Molecular Biology and Neurosciences, National Research Council (CONICET), Buenos Aires, Argentina
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