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      Predictive model for cytoneme guidance in Hedgehog signaling based on Ihog- Glypicans interaction

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          Abstract

          During embryonic development, cell-cell communication is crucial to coordinate cell behavior, especially in the generation of differentiation patterns via morphogen gradients. Morphogens are signaling molecules secreted by a source of cells that elicit concentration-dependent responses in target cells. For several morphogens, cell-cell contact via filopodia-like-structures (cytonemes) has been proposed as a mechanism for their gradient formation. Despite of the advances on cytoneme signaling, little is known about how cytonemes navigate through the extracellular matrix and how they orient to find their target. For the Hedgehog (Hh) signaling pathway in Drosophila, Hh co-receptor and adhesion protein Interference hedgehog (Ihog) and the glypicans Dally and Dally-like-protein (Dlp) interact affecting the cytoneme behavior. Here, we describe that differences in the cytoneme stabilization and orientation depend on the relative levels of Ihog and glypicans, suggesting a mechanism for cytoneme guidance. Furthermore, we have developed a mathematical model to study and corroborate this cytoneme guiding mechanism.

          Abstract

          Cytonemes are specialized filopodia-like structures known to be involved in signal transduction. Here they propose a new predictive model for cytoneme guidance in Hedgehog signaling, which is based on Ihog, Dally, and Dlp protein levels.

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          Most cited references50

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          Reaction-diffusion model as a framework for understanding biological pattern formation.

          The Turing, or reaction-diffusion (RD), model is one of the best-known theoretical models used to explain self-regulated pattern formation in the developing animal embryo. Although its real-world relevance was long debated, a number of compelling examples have gradually alleviated much of the skepticism surrounding the model. The RD model can generate a wide variety of spatial patterns, and mathematical studies have revealed the kinds of interactions required for each, giving this model the potential for application as an experimental working hypothesis in a wide variety of morphological phenomena. In this review, we describe the essence of this theory for experimental biologists unfamiliar with the model, using examples from experimental studies in which the RD model is effectively incorporated.
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            Targeted gene expression as a means of altering cell fates and generating dominant phenotypes

            We have designed a system for targeted gene expression that allows the selective activation of any cloned gene in a wide variety of tissue- and cell-specific patterns. The gene encoding the yeast transcriptional activator GAL4 is inserted randomly into the Drosophila genome to drive GAL4 expression from one of a diverse array of genomic enhancers. It is then possible to introduce a gene containing GAL4 binding sites within its promoter, to activate it in those cells where GAL4 is expressed, and to observe the effect of this directed misexpression on development. We have used GAL4-directed transcription to expand the domain of embryonic expression of the homeobox protein even-skipped. We show that even-skipped represses wingless and transforms cells that would normally secrete naked cuticle into denticle secreting cells. The GAL4 system can thus be used to study regulatory interactions during embryonic development. In adults, targeted expression can be used to generate dominant phenotypes for use in genetic screens. We have directed expression of an activated form of the Dras2 protein, resulting in dominant eye and wing defects that can be used in screens to identify other members of the Dras2 signal transduction pathway.
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              Molecular mechanisms of axon guidance.

              Axons are guided along specific pathways by attractive and repulsive cues in the extracellular environment. Genetic and biochemical studies have led to the identification of highly conserved families of guidance molecules, including netrins, Slits, semaphorins, and ephrins. Guidance cues steer axons by regulating cytoskeletal dynamics in the growth cone through signaling pathways that are still only poorly understood. Elaborate regulatory mechanisms ensure that a given cue elicits the right response from the right axons at the right time but is otherwise ignored. With such regulatory mechanisms in place, a relatively small number of guidance factors can be used to generate intricate patterns of neuronal wiring.
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                Author and article information

                Contributors
                jsoler@ugr.es
                iguerrero@cbm.csic.es
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                26 September 2022
                26 September 2022
                2022
                : 13
                : 5647
                Affiliations
                [1 ]GRID grid.5515.4, ISNI 0000000119578126, Tissue and Organ Homeostasis, Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Nicolás Cabrera 1, , Universidad Autónoma de Madrid, Cantoblanco, ; E-28049 Madrid, Spain
                [2 ]GRID grid.4489.1, ISNI 0000000121678994, Departamento de Matemática Aplicada and Research Unit “Modeling Nature” (MNat), Facultad de Ciencias, , Universidad de Granada, ; E-18071 Granada, Spain
                [3 ]GRID grid.7849.2, ISNI 0000 0001 2150 7757, Institut Camille Jordan (ICJ), , UMR 5208 CNRS & Université Claude Bernard Lyon 1, ; F-69100 Villeurbanne, France
                Author information
                http://orcid.org/0000-0001-6582-1369
                http://orcid.org/0000-0002-4257-9343
                http://orcid.org/0000-0001-6927-899X
                http://orcid.org/0000-0002-8683-5994
                http://orcid.org/0000-0001-6761-1218
                Article
                33262
                10.1038/s41467-022-33262-4
                9512826
                36163184
                2a313982-4785-4104-8210-a6ed631cfabe
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 November 2021
                : 9 September 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100010198, Ministerio de Economía, Industria y Competitividad, Gobierno de España (Ministerio de Economía, Industria y Competitividad);
                Award ID: (FPI) BFU2014-59438-P
                Award ID: BFU2017-83789-P
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003329, Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness);
                Award ID: FPI2015/074837
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003176, Ministerio de Educación, Cultura y Deporte (Ministry of Education, Culture and Sports, Spain);
                Award ID: FPU14/06304
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010663, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council);
                Award ID: ERC-COG-2019 WACONDY
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100011011, Junta de Andalucía;
                Award ID: PY18-RT-2422
                Award ID: A-FQM-311-UGR18
                Award Recipient :
                Funded by: Ministerio de Ciencia, Innovación y Universidades (RTI2018-098850-B-I00)
                Funded by: Ministerio de Ciencia, Innovación y Universidades (RED2018-102411-T) Ministerio de Ciencia e Innovación (PID2020-114533GB-C21)
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                cell proliferation,morphogenesis,computational biophysics,morphogen signalling
                Uncategorized
                cell proliferation, morphogenesis, computational biophysics, morphogen signalling

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