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      Injury triggers fascia fibroblast collective cell migration to drive scar formation through N-cadherin

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          Abstract

          Scars are more severe when the subcutaneous fascia beneath the dermis is injured upon surgical or traumatic wounding. Here, we present a detailed analysis of fascia cell mobilisation by using deep tissue intravital live imaging of acute surgical wounds, fibroblast lineage-specific transgenic mice, and skin-fascia explants (scar-like tissue in a dish – SCAD). We observe that injury triggers a swarming-like collective cell migration of fascia fibroblasts that progressively contracts the skin and form scars. Swarming is exclusive to fascia fibroblasts, and requires the upregulation of N-cadherin. Both swarming and N-cadherin expression are absent from fibroblasts in the upper skin layers and the oral mucosa, tissues that repair wounds with minimal scar. Impeding N-cadherin binding inhibits swarming and skin contraction, and leads to reduced scarring in SCADs and in animals. Fibroblast swarming and N-cadherin thus provide therapeutic avenues to curtail fascia mobilisation and pathological fibrotic responses across a range of medical settings.

          Abstract

          Extensive scars develop in deep wounds as opposed to superficial wounds but it is unclear why. Here, the authors use live imaging of physiologic wounds and scars formed ex vivo to show that fascia fibroblasts upregulate N-cadherin allowing coordinated cell migration that drives extensive scar formation of deep wounds.

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          Most cited references41

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            The Perseus computational platform for comprehensive analysis of (prote)omics data.

            A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
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              Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ *

              Protein quantification without isotopic labels has been a long-standing interest in the proteomics field. However, accurate and robust proteome-wide quantification with label-free approaches remains a challenge. We developed a new intensity determination and normalization procedure called MaxLFQ that is fully compatible with any peptide or protein separation prior to LC-MS analysis. Protein abundance profiles are assembled using the maximum possible information from MS signals, given that the presence of quantifiable peptides varies from sample to sample. For a benchmark dataset with two proteomes mixed at known ratios, we accurately detected the mixing ratio over the entire protein expression range, with greater precision for abundant proteins. The significance of individual label-free quantifications was obtained via a t test approach. For a second benchmark dataset, we accurately quantify fold changes over several orders of magnitude, a task that is challenging with label-based methods. MaxLFQ is a generic label-free quantification technology that is readily applicable to many biological questions; it is compatible with standard statistical analysis workflows, and it has been validated in many and diverse biological projects. Our algorithms can handle very large experiments of 500+ samples in a manageable computing time. It is implemented in the freely available MaxQuant computational proteomics platform and works completely seamlessly at the click of a button.
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                Author and article information

                Contributors
                yuval.rinkevich@helmholtz-muenchen.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                6 November 2020
                6 November 2020
                2020
                : 11
                : 5653
                Affiliations
                [1 ]GRID grid.4567.0, ISNI 0000 0004 0483 2525, Helmholtz Zentrum München, Institute of Lung Biology and Disease, Group Regenerative Biology and Medicine, ; Munich, Germany
                [2 ]GRID grid.4567.0, ISNI 0000 0004 0483 2525, Helmholtz Zentrum München, Institute of Lung Biology and Disease, Group Systems Medicine of Chronic Lung Disease, ; Munich, Germany
                [3 ]GRID grid.4567.0, ISNI 0000 0004 0483 2525, Helmholtz Zentrum München, Institute of Computational Biology, ; Munich, Germany
                [4 ]Mira-Beau gender esthetics, Berlin, Germany
                [5 ]GRID grid.7704.4, ISNI 0000 0001 2297 4381, Wound Repair Unit, CBIB, Faculty of Biology and Biochemistry, , University of Bremen, ; Bremen, Germany
                [6 ]Department of Dermatology and Allergology, Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany
                [7 ]German Centre for Lung Research (DZL), Munich, Germany
                Author information
                http://orcid.org/0000-0003-0961-2671
                http://orcid.org/0000-0003-2978-6548
                http://orcid.org/0000-0003-2154-4552
                http://orcid.org/0000-0001-9498-7034
                http://orcid.org/0000-0003-3658-0257
                Article
                19425
                10.1038/s41467-020-19425-1
                7648088
                33159076
                bebcf694-ea86-4bf7-a43f-6bf316af9a39
                © The Author(s) 2020

                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
                : 18 May 2020
                : 8 October 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000854, Human Frontier Science Program (HFSP);
                Award ID: CDA00017/2016
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: RI 2787 / 1-1 AOBJ: 628819
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003390, Fritz Thyssen Stiftung (Fritz Thyssen Foundation);
                Award ID: 2016-01277
                Award Recipient :
                Funded by: European Research council Consolidator Grant, ERC-CoG 819933
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                skin models,time-lapse imaging,cadherins
                Uncategorized
                skin models, time-lapse imaging, cadherins

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