[{"project":[{"name":"Coordination of Patterning And Growth In the Spinal Cord","_id":"B6FC0238-B512-11E9-945C-1524E6697425","call_identifier":"H2020","grant_number":"680037"},{"name":"Mechanisms of tissue size regulation in spinal cord development","_id":"bd7e737f-d553-11ed-ba76-d69ffb5ee3aa","grant_number":"101044579"},{"name":"Morphogen control of growth and pattern in the spinal cord","_id":"059DF620-7A3F-11EA-A408-12923DDC885E","grant_number":"F07802"},{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"isi":1,"language":[{"iso":"eng"}],"publication_identifier":{"issn":["1745-2473"],"eissn":["1745-2481"]},"doi":"10.1038/s41567-023-01977-w","quality_controlled":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Springer Nature","department":[{"_id":"EdHa"},{"_id":"AnKi"}],"publication":"Nature Physics","ec_funded":1,"scopus_import":"1","article_processing_charge":"No","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_type":"original","author":[{"id":"4896F754-F248-11E8-B48F-1D18A9856A87","full_name":"Bocanegra, Laura","first_name":"Laura","last_name":"Bocanegra"},{"first_name":"Amrita","last_name":"Singh","id":"76250f9f-3a21-11eb-9a80-a6180a0d7958","full_name":"Singh, Amrita"},{"id":"3A9DB764-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6005-1561","full_name":"Hannezo, Edouard B","first_name":"Edouard B","last_name":"Hannezo"},{"full_name":"Zagórski, Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","first_name":"Marcin P","last_name":"Zagórski"},{"last_name":"Kicheva","first_name":"Anna","full_name":"Kicheva, Anna","id":"3959A2A0-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4509-4998"}],"file":[{"success":1,"file_name":"2023_NaturePhysics_Boncanegra.pdf","content_type":"application/pdf","relation":"main_file","file_size":5532285,"creator":"dernst","date_updated":"2023-10-04T11:13:28Z","file_id":"14392","checksum":"858225a4205b74406e5045006cdd853f","date_created":"2023-10-04T11:13:28Z","access_level":"open_access"}],"day":"01","title":"Cell cycle dynamics control fluidity of the developing mouse neuroepithelium","status":"public","external_id":{"isi":["000964029300003"]},"related_material":{"record":[{"id":"13081","status":"public","relation":"dissertation_contains"}]},"intvolume":"        19","citation":{"short":"L. Bocanegra, A. Singh, E.B. Hannezo, M.P. Zagórski, A. Kicheva, Nature Physics 19 (2023) 1050–1058.","chicago":"Bocanegra, Laura, Amrita Singh, Edouard B Hannezo, Marcin P Zagórski, and Anna Kicheva. “Cell Cycle Dynamics Control Fluidity of the Developing Mouse Neuroepithelium.” <i>Nature Physics</i>. Springer Nature, 2023. <a href=\"https://doi.org/10.1038/s41567-023-01977-w\">https://doi.org/10.1038/s41567-023-01977-w</a>.","ieee":"L. Bocanegra, A. Singh, E. B. Hannezo, M. P. Zagórski, and A. Kicheva, “Cell cycle dynamics control fluidity of the developing mouse neuroepithelium,” <i>Nature Physics</i>, vol. 19. Springer Nature, pp. 1050–1058, 2023.","apa":"Bocanegra, L., Singh, A., Hannezo, E. B., Zagórski, M. P., &#38; Kicheva, A. (2023). Cell cycle dynamics control fluidity of the developing mouse neuroepithelium. <i>Nature Physics</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41567-023-01977-w\">https://doi.org/10.1038/s41567-023-01977-w</a>","ista":"Bocanegra L, Singh A, Hannezo EB, Zagórski MP, Kicheva A. 2023. Cell cycle dynamics control fluidity of the developing mouse neuroepithelium. Nature Physics. 19, 1050–1058.","mla":"Bocanegra, Laura, et al. “Cell Cycle Dynamics Control Fluidity of the Developing Mouse Neuroepithelium.” <i>Nature Physics</i>, vol. 19, Springer Nature, 2023, pp. 1050–58, doi:<a href=\"https://doi.org/10.1038/s41567-023-01977-w\">10.1038/s41567-023-01977-w</a>.","ama":"Bocanegra L, Singh A, Hannezo EB, Zagórski MP, Kicheva A. Cell cycle dynamics control fluidity of the developing mouse neuroepithelium. <i>Nature Physics</i>. 2023;19:1050-1058. doi:<a href=\"https://doi.org/10.1038/s41567-023-01977-w\">10.1038/s41567-023-01977-w</a>"},"publication_status":"published","oa":1,"has_accepted_license":"1","ddc":["570"],"date_published":"2023-07-01T00:00:00Z","acknowledgement":"We thank S. Hippenmeyer for the reagents and C. P. Heisenberg, J. Briscoe and K. Page for comments on the manuscript. This work was supported by IST Austria; the European Research Council under Horizon 2020 research and innovation programme grant no. 680037 and Horizon Europe grant 101044579 (A.K.); Austrian Science Fund (FWF): F78 (Stem Cell Modulation) (A.K.); ISTFELLOW postdoctoral program (A.S.); Narodowe Centrum Nauki, Poland SONATA, 2017/26/D/NZ2/00454 (M.Z.); and the Polish National Agency for Academic Exchange (M.Z.).","year":"2023","_id":"12837","page":"1050-1058","abstract":[{"text":"As developing tissues grow in size and undergo morphogenetic changes, their material properties may be altered. Such changes result from tension dynamics at cell contacts or cellular jamming. Yet, in many cases, the cellular mechanisms controlling the physical state of growing tissues are unclear. We found that at early developmental stages, the epithelium in the developing mouse spinal cord maintains both high junctional tension and high fluidity. This is achieved via a mechanism in which interkinetic nuclear movements generate cell area dynamics that drive extensive cell rearrangements. Over time, the cell proliferation rate declines, effectively solidifying the tissue. Thus, unlike well-studied jamming transitions, the solidification uncovered here resembles a glass transition that depends on the dynamical stresses generated by proliferation and differentiation. Our finding that the fluidity of developing epithelia is linked to interkinetic nuclear movements and the dynamics of growth is likely to be relevant to multiple developing tissues.","lang":"eng"}],"date_updated":"2023-10-04T11:14:05Z","oa_version":"Published Version","type":"journal_article","month":"07","volume":19,"file_date_updated":"2023-10-04T11:13:28Z","date_created":"2023-04-16T22:01:09Z"},{"project":[{"call_identifier":"H2020","_id":"B6FC0238-B512-11E9-945C-1524E6697425","name":"Coordination of Patterning And Growth In the Spinal Cord","grant_number":"680037"}],"isi":1,"language":[{"iso":"eng"}],"issue":"23","publication_identifier":{"eissn":["1477-9129"],"issn":["0950-1991"]},"doi":"10.1242/dev.176297","quality_controlled":"1","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"The Company of Biologists","pmid":1,"department":[{"_id":"AnKi"}],"publication":"Development","scopus_import":"1","ec_funded":1,"article_processing_charge":"No","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_type":"original","author":[{"last_name":"Guerrero","first_name":"Pilar","full_name":"Guerrero, Pilar"},{"last_name":"Perez-Carrasco","first_name":"Ruben","full_name":"Perez-Carrasco, Ruben"},{"orcid":"0000-0001-7896-7762","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","full_name":"Zagórski, Marcin P","first_name":"Marcin P","last_name":"Zagórski"},{"full_name":"Page, David","first_name":"David","last_name":"Page"},{"full_name":"Kicheva, Anna","orcid":"0000-0003-4509-4998","id":"3959A2A0-F248-11E8-B48F-1D18A9856A87","last_name":"Kicheva","first_name":"Anna"},{"last_name":"Briscoe","first_name":"James","full_name":"Briscoe, James"},{"first_name":"Karen M.","last_name":"Page","full_name":"Page, Karen M."}],"day":"04","file":[{"file_name":"2019_Development_Guerrero.pdf","creator":"dernst","file_size":7797881,"content_type":"application/pdf","relation":"main_file","checksum":"b6533c37dc8fbd803ffeca216e0a8b8a","file_id":"7177","date_updated":"2020-07-14T12:47:50Z","access_level":"open_access","date_created":"2019-12-13T07:34:06Z"}],"title":"Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium","article_number":"dev176297","external_id":{"pmid":["31784457"],"isi":["000507575700004"]},"status":"public","intvolume":"       146","citation":{"short":"P. Guerrero, R. Perez-Carrasco, M.P. Zagórski, D. Page, A. Kicheva, J. Briscoe, K.M. Page, Development 146 (2019).","ieee":"P. Guerrero <i>et al.</i>, “Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium,” <i>Development</i>, vol. 146, no. 23. The Company of Biologists, 2019.","chicago":"Guerrero, Pilar, Ruben Perez-Carrasco, Marcin P Zagórski, David Page, Anna Kicheva, James Briscoe, and Karen M. Page. “Neuronal Differentiation Influences Progenitor Arrangement in the Vertebrate Neuroepithelium.” <i>Development</i>. The Company of Biologists, 2019. <a href=\"https://doi.org/10.1242/dev.176297\">https://doi.org/10.1242/dev.176297</a>.","mla":"Guerrero, Pilar, et al. “Neuronal Differentiation Influences Progenitor Arrangement in the Vertebrate Neuroepithelium.” <i>Development</i>, vol. 146, no. 23, dev176297, The Company of Biologists, 2019, doi:<a href=\"https://doi.org/10.1242/dev.176297\">10.1242/dev.176297</a>.","ista":"Guerrero P, Perez-Carrasco R, Zagórski MP, Page D, Kicheva A, Briscoe J, Page KM. 2019. Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium. Development. 146(23), dev176297.","apa":"Guerrero, P., Perez-Carrasco, R., Zagórski, M. P., Page, D., Kicheva, A., Briscoe, J., &#38; Page, K. M. (2019). Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium. <i>Development</i>. The Company of Biologists. <a href=\"https://doi.org/10.1242/dev.176297\">https://doi.org/10.1242/dev.176297</a>","ama":"Guerrero P, Perez-Carrasco R, Zagórski MP, et al. Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium. <i>Development</i>. 2019;146(23). doi:<a href=\"https://doi.org/10.1242/dev.176297\">10.1242/dev.176297</a>"},"publication_status":"published","oa":1,"has_accepted_license":"1","date_published":"2019-12-04T00:00:00Z","ddc":["570"],"year":"2019","_id":"7165","date_updated":"2023-09-06T11:26:36Z","abstract":[{"text":"Cell division, movement and differentiation contribute to pattern formation in developing tissues. This is the case in the vertebrate neural tube, in which neurons differentiate in a characteristic pattern from a highly dynamic proliferating pseudostratified epithelium. To investigate how progenitor proliferation and differentiation affect cell arrangement and growth of the neural tube, we used experimental measurements to develop a mechanical model of the apical surface of the neuroepithelium that incorporates the effect of interkinetic nuclear movement and spatially varying rates of neuronal differentiation. Simulations predict that tissue growth and the shape of lineage-related clones of cells differ with the rate of differentiation. Growth is isotropic in regions of high differentiation, but dorsoventrally biased in regions of low differentiation. This is consistent with experimental observations. The absence of directional signalling in the simulations indicates that global mechanical constraints are sufficient to explain the observed differences in anisotropy. This provides insight into how the tissue growth rate affects cell dynamics and growth anisotropy and opens up possibilities to study the coupling between mechanics, pattern formation and growth in the neural tube.","lang":"eng"}],"oa_version":"Published Version","type":"journal_article","month":"12","volume":146,"date_created":"2019-12-10T14:39:50Z","file_date_updated":"2020-07-14T12:47:50Z"},{"project":[{"grant_number":"680037","_id":"B6FC0238-B512-11E9-945C-1524E6697425","call_identifier":"H2020","name":"Coordination of Patterning And Growth In the Spinal Cord"}],"language":[{"iso":"eng"}],"series_title":"MIMB","publication_identifier":{"issn":["1064-3745"],"isbn":["978-1-4939-8771-9"]},"quality_controlled":"1","doi":"10.1007/978-1-4939-8772-6_4","department":[{"_id":"AnKi"}],"publisher":"Springer Nature","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","ec_funded":1,"article_processing_charge":"No","scopus_import":"1","publication":"Morphogen Gradients ","day":"16","file":[{"creator":"dernst","file_size":4906815,"content_type":"application/pdf","relation":"main_file","file_name":"2018_MIMB_Zagorski.pdf","success":1,"access_level":"open_access","date_created":"2020-10-13T14:20:37Z","checksum":"2a97d0649fdcfcf1bdca7c8ad1dce71b","file_id":"8656","date_updated":"2020-10-13T14:20:37Z"}],"author":[{"id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P","first_name":"Marcin P","last_name":"Zagórski"},{"id":"3959A2A0-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4509-4998","full_name":"Kicheva, Anna","first_name":"Anna","last_name":"Kicheva"}],"publist_id":"8018","title":"Measuring dorsoventral pattern and morphogen signaling profiles in the growing neural tube","status":"public","alternative_title":["Methods in Molecular Biology"],"citation":{"chicago":"Zagórski, Marcin P, and Anna Kicheva. “Measuring Dorsoventral Pattern and Morphogen Signaling Profiles in the Growing Neural Tube.” In <i>Morphogen Gradients </i>, 1863:47–63. MIMB. Springer Nature, 2018. <a href=\"https://doi.org/10.1007/978-1-4939-8772-6_4\">https://doi.org/10.1007/978-1-4939-8772-6_4</a>.","ieee":"M. P. Zagórski and A. Kicheva, “Measuring dorsoventral pattern and morphogen signaling profiles in the growing neural tube,” in <i>Morphogen Gradients </i>, vol. 1863, Springer Nature, 2018, pp. 47–63.","short":"M.P. Zagórski, A. Kicheva, in:, Morphogen Gradients , Springer Nature, 2018, pp. 47–63.","ama":"Zagórski MP, Kicheva A. Measuring dorsoventral pattern and morphogen signaling profiles in the growing neural tube. In: <i>Morphogen Gradients </i>. Vol 1863. MIMB. Springer Nature; 2018:47-63. doi:<a href=\"https://doi.org/10.1007/978-1-4939-8772-6_4\">10.1007/978-1-4939-8772-6_4</a>","apa":"Zagórski, M. P., &#38; Kicheva, A. (2018). Measuring dorsoventral pattern and morphogen signaling profiles in the growing neural tube. In <i>Morphogen Gradients </i> (Vol. 1863, pp. 47–63). Springer Nature. <a href=\"https://doi.org/10.1007/978-1-4939-8772-6_4\">https://doi.org/10.1007/978-1-4939-8772-6_4</a>","mla":"Zagórski, Marcin P., and Anna Kicheva. “Measuring Dorsoventral Pattern and Morphogen Signaling Profiles in the Growing Neural Tube.” <i>Morphogen Gradients </i>, vol. 1863, Springer Nature, 2018, pp. 47–63, doi:<a href=\"https://doi.org/10.1007/978-1-4939-8772-6_4\">10.1007/978-1-4939-8772-6_4</a>.","ista":"Zagórski MP, Kicheva A. 2018.Measuring dorsoventral pattern and morphogen signaling profiles in the growing neural tube. In: Morphogen Gradients . Methods in Molecular Biology, vol. 1863, 47–63."},"intvolume":"      1863","has_accepted_license":"1","oa":1,"publication_status":"published","date_published":"2018-10-16T00:00:00Z","ddc":["570"],"year":"2018","_id":"37","oa_version":"Submitted Version","month":"10","type":"book_chapter","abstract":[{"lang":"eng","text":"Developmental processes are inherently dynamic and understanding them requires quantitative measurements of gene and protein expression levels in space and time. While live imaging is a powerful approach for obtaining such data, it is still a challenge to apply it over long periods of time to large tissues, such as the embryonic spinal cord in mouse and chick. Nevertheless, dynamics of gene expression and signaling activity patterns in this organ can be studied by collecting tissue sections at different developmental stages. In combination with immunohistochemistry, this allows for measuring the levels of multiple developmental regulators in a quantitative manner with high spatiotemporal resolution. The mean protein expression levels over time, as well as embryo-to-embryo variability can be analyzed. A key aspect of the approach is the ability to compare protein levels across different samples. This requires a number of considerations in sample preparation, imaging and data analysis. Here we present a protocol for obtaining time course data of dorsoventral expression patterns from mouse and chick neural tube in the first 3 days of neural tube development. The described workflow starts from embryo dissection and ends with a processed dataset. Software scripts for data analysis are included. The protocol is adaptable and instructions that allow the user to modify different steps are provided. Thus, the procedure can be altered for analysis of time-lapse images and applied to systems other than the neural tube."}],"date_updated":"2021-01-12T07:49:03Z","page":"47 - 63","date_created":"2018-12-11T11:44:17Z","file_date_updated":"2020-10-13T14:20:37Z","volume":1863},{"publication":"PNAS","article_processing_charge":"No","ec_funded":1,"scopus_import":"1","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"National Academy of Sciences","pmid":1,"department":[{"_id":"ToBo"}],"title":"Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections","publist_id":"6827","author":[{"first_name":"Marjon","last_name":"De Vos","full_name":"De Vos, Marjon","id":"3111FFAC-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Zagórski","first_name":"Marcin P","full_name":"Zagórski, Marcin P","orcid":"0000-0001-7896-7762","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Alan","last_name":"Mcnally","full_name":"Mcnally, Alan"},{"full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias"}],"day":"03","isi":1,"language":[{"iso":"eng"}],"issue":"40","project":[{"grant_number":"303507","name":"Optimality principles in responses to antibiotics","call_identifier":"FP7","_id":"25E83C2C-B435-11E9-9278-68D0E5697425"},{"grant_number":"P27201-B22","name":"Revealing the mechanisms underlying drug interactions","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"}],"doi":"10.1073/pnas.1713372114","quality_controlled":"1","publication_identifier":{"issn":["00278424"]},"_id":"822","year":"2017","volume":114,"date_created":"2018-12-11T11:48:41Z","page":"10666 - 10671","abstract":[{"lang":"eng","text":"Polymicrobial infections constitute small ecosystems that accommodate several bacterial species. Commonly, these bacteria are investigated in isolation. However, it is unknown to what extent the isolates interact and whether their interactions alter bacterial growth and ecosystem resilience in the presence and absence of antibiotics. We quantified the complete ecological interaction network for 72 bacterial isolates collected from 23 individuals diagnosed with polymicrobial urinary tract infections and found that most interactions cluster based on evolutionary relatedness. Statistical network analysis revealed that competitive and cooperative reciprocal interactions are enriched in the global network, while cooperative interactions are depleted in the individual host community networks. A population dynamics model parameterized by our measurements suggests that interactions restrict community stability, explaining the observed species diversity of these communities. We further show that the clinical isolates frequently protect each other from clinically relevant antibiotics. Together, these results highlight that ecological interactions are crucial for the growth and survival of bacteria in polymicrobial infection communities and affect their assembly and resilience. "}],"date_updated":"2023-09-26T16:18:48Z","type":"journal_article","month":"10","oa_version":"Submitted Version","intvolume":"       114","citation":{"apa":"de Vos, M., Zagórski, M. P., Mcnally, A., &#38; Bollenbach, M. T. (2017). Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1713372114\">https://doi.org/10.1073/pnas.1713372114</a>","ista":"de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. 2017. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. 114(40), 10666–10671.","mla":"de Vos, Marjon, et al. “Interaction Networks, Ecological Stability, and Collective Antibiotic Tolerance in Polymicrobial Infections.” <i>PNAS</i>, vol. 114, no. 40, National Academy of Sciences, 2017, pp. 10666–71, doi:<a href=\"https://doi.org/10.1073/pnas.1713372114\">10.1073/pnas.1713372114</a>.","ama":"de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. <i>PNAS</i>. 2017;114(40):10666-10671. doi:<a href=\"https://doi.org/10.1073/pnas.1713372114\">10.1073/pnas.1713372114</a>","short":"M. de Vos, M.P. Zagórski, A. Mcnally, M.T. Bollenbach, PNAS 114 (2017) 10666–10671.","chicago":"Vos, Marjon de, Marcin P Zagórski, Alan Mcnally, and Mark Tobias Bollenbach. “Interaction Networks, Ecological Stability, and Collective Antibiotic Tolerance in Polymicrobial Infections.” <i>PNAS</i>. National Academy of Sciences, 2017. <a href=\"https://doi.org/10.1073/pnas.1713372114\">https://doi.org/10.1073/pnas.1713372114</a>.","ieee":"M. de Vos, M. P. Zagórski, A. Mcnally, and M. T. Bollenbach, “Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections,” <i>PNAS</i>, vol. 114, no. 40. National Academy of Sciences, pp. 10666–10671, 2017."},"status":"public","external_id":{"isi":["000412130500061"],"pmid":["28923953"]},"date_published":"2017-10-03T00:00:00Z","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635929/","open_access":"1"}],"publication_status":"published","oa":1},{"publication_identifier":{"issn":["00368075"]},"doi":"10.1126/science.aam5887","quality_controlled":"1","project":[{"grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425"},{"grant_number":"680037","name":"Coordination of Patterning And Growth In the Spinal Cord","_id":"B6FC0238-B512-11E9-945C-1524E6697425","call_identifier":"H2020"},{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"},{"grant_number":"201439","name":"Developing High-Throughput Bioassays for Human Cancers in Zebrafish","_id":"2524F500-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"isi":1,"language":[{"iso":"eng"}],"issue":"6345","author":[{"id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P","last_name":"Zagórski","first_name":"Marcin P"},{"last_name":"Tabata","first_name":"Yoji","full_name":"Tabata, Yoji"},{"full_name":"Brandenberg, Nathalie","last_name":"Brandenberg","first_name":"Nathalie"},{"full_name":"Lutolf, Matthias","first_name":"Matthias","last_name":"Lutolf"},{"last_name":"Tkacik","first_name":"Gasper","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455"},{"last_name":"Bollenbach","first_name":"Tobias","full_name":"Bollenbach, Tobias"},{"full_name":"Briscoe, James","first_name":"James","last_name":"Briscoe"},{"last_name":"Kicheva","first_name":"Anna","full_name":"Kicheva, Anna","id":"3959A2A0-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4509-4998"}],"day":"30","title":"Decoding of position in the developing neural tube from antiparallel morphogen gradients","publist_id":"6474","publisher":"American Association for the Advancement of Science","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","pmid":1,"department":[{"_id":"AnKi"},{"_id":"GaTk"}],"publication":"Science","article_processing_charge":"No","scopus_import":"1","ec_funded":1,"publication_status":"published","oa":1,"date_published":"2017-06-30T00:00:00Z","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/","open_access":"1"}],"status":"public","external_id":{"isi":["000404351500036"],"pmid":["28663499"]},"intvolume":"       356","citation":{"ama":"Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing neural tube from antiparallel morphogen gradients. <i>Science</i>. 2017;356(6345):1379-1383. doi:<a href=\"https://doi.org/10.1126/science.aam5887\">10.1126/science.aam5887</a>","apa":"Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach, T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from antiparallel morphogen gradients. <i>Science</i>. American Association for the Advancement of Science. <a href=\"https://doi.org/10.1126/science.aam5887\">https://doi.org/10.1126/science.aam5887</a>","mla":"Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” <i>Science</i>, vol. 356, no. 6345, American Association for the Advancement of Science, 2017, pp. 1379–83, doi:<a href=\"https://doi.org/10.1126/science.aam5887\">10.1126/science.aam5887</a>.","ista":"Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 356(6345), 1379–1383.","chicago":"Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf, Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” <i>Science</i>. American Association for the Advancement of Science, 2017. <a href=\"https://doi.org/10.1126/science.aam5887\">https://doi.org/10.1126/science.aam5887</a>.","ieee":"M. P. Zagórski <i>et al.</i>, “Decoding of position in the developing neural tube from antiparallel morphogen gradients,” <i>Science</i>, vol. 356, no. 6345. American Association for the Advancement of Science, pp. 1379–1383, 2017.","short":"M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach, J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383."},"page":"1379 - 1383","date_updated":"2023-09-26T15:38:05Z","abstract":[{"text":"Like many developing tissues, the vertebrate neural tube is patterned by antiparallel morphogen gradients. To understand how these inputs are interpreted, we measured morphogen signaling and target gene expression in mouse embryos and chick ex vivo assays. From these data, we derived and validated a characteristic decoding map that relates morphogen input to the positional identity of neural progenitors. Analysis of the observed responses indicates that the underlying interpretation strategy minimizes patterning errors in response to the joint input of noisy opposing gradients. We reverse-engineered a transcriptional network that provides a mechanistic basis for the observed cell fate decisions and accounts for the precision and dynamics of pattern formation. Together, our data link opposing gradient dynamics in a growing tissue to precise pattern formation.","lang":"eng"}],"type":"journal_article","oa_version":"Submitted Version","month":"06","volume":356,"date_created":"2018-12-11T11:49:20Z","year":"2017","_id":"943"},{"status":"public","related_material":{"record":[{"relation":"research_data","status":"public","id":"9866"}]},"intvolume":"        12","citation":{"ama":"Zagórski MP, Burda Z, Wacław B. Beyond the hypercube evolutionary accessibility of fitness landscapes with realistic mutational networks. <i>PLoS Computational Biology</i>. 2016;12(12). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005218\">10.1371/journal.pcbi.1005218</a>","mla":"Zagórski, Marcin P., et al. “Beyond the Hypercube Evolutionary Accessibility of Fitness Landscapes with Realistic Mutational Networks.” <i>PLoS Computational Biology</i>, vol. 12, no. 12, e1005218, Public Library of Science, 2016, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005218\">10.1371/journal.pcbi.1005218</a>.","ista":"Zagórski MP, Burda Z, Wacław B. 2016. Beyond the hypercube evolutionary accessibility of fitness landscapes with realistic mutational networks. PLoS Computational Biology. 12(12), e1005218.","apa":"Zagórski, M. P., Burda, Z., &#38; Wacław, B. (2016). Beyond the hypercube evolutionary accessibility of fitness landscapes with realistic mutational networks. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005218\">https://doi.org/10.1371/journal.pcbi.1005218</a>","ieee":"M. P. Zagórski, Z. Burda, and B. Wacław, “Beyond the hypercube evolutionary accessibility of fitness landscapes with realistic mutational networks,” <i>PLoS Computational Biology</i>, vol. 12, no. 12. Public Library of Science, 2016.","chicago":"Zagórski, Marcin P, Zdzisław Burda, and Bartłomiej Wacław. “Beyond the Hypercube Evolutionary Accessibility of Fitness Landscapes with Realistic Mutational Networks.” <i>PLoS Computational Biology</i>. Public Library of Science, 2016. <a href=\"https://doi.org/10.1371/journal.pcbi.1005218\">https://doi.org/10.1371/journal.pcbi.1005218</a>.","short":"M.P. Zagórski, Z. Burda, B. Wacław, PLoS Computational Biology 12 (2016)."},"publication_status":"published","oa":1,"has_accepted_license":"1","ddc":["570"],"date_published":"2016-12-09T00:00:00Z","acknowledgement":"MZ acknowledges the Polish National Science Centre grant no. DEC-2012/07/N/NZ2/00107. BW was supported by the Scottish Government/Royal Society of Edinburgh Personal Research Fellowship. We thank Marjon de Vos and Oliver Martin for critically reading the manuscript.","year":"2016","_id":"1167","type":"journal_article","month":"12","oa_version":"Published Version","abstract":[{"text":"Evolutionary pathways describe trajectories of biological evolution in the space of different variants of organisms (genotypes). The probability of existence and the number of evolutionary pathways that lead from a given genotype to a better-adapted genotype are important measures of accessibility of local fitness optima and the reproducibility of evolution. Both quantities have been studied in simple mathematical models where genotypes are represented as binary sequences of two types of basic units, and the network of permitted mutations between the genotypes is a hypercube graph. However, it is unclear how these results translate to the biologically relevant case in which genotypes are represented by sequences of more than two units, for example four nucleotides (DNA) or 20 amino acids (proteins), and the mutational graph is not the hypercube. Here we investigate accessibility of the best-adapted genotype in the general case of K &gt; 2 units. Using computer generated and experimental fitness landscapes we show that accessibility of the global fitness maximum increases with K and can be much higher than for binary sequences. The increase in accessibility comes from the increase in the number of indirect trajectories exploited by evolution for higher K. As one of the consequences, the fraction of genotypes that are accessible increases by three orders of magnitude when the number of units K increases from 2 to 16 for landscapes of size N ∼ 106genotypes. This suggests that evolution can follow many different trajectories on such landscapes and the reconstruction of evolutionary pathways from experimental data might be an extremely difficult task.","lang":"eng"}],"date_updated":"2023-02-23T14:11:22Z","volume":12,"file_date_updated":"2020-07-14T12:44:37Z","date_created":"2018-12-11T11:50:30Z","issue":"12","language":[{"iso":"eng"}],"pubrep_id":"740","doi":"10.1371/journal.pcbi.1005218","quality_controlled":"1","publisher":"Public Library of Science","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","department":[{"_id":"AnKi"}],"publication":"PLoS Computational Biology","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"scopus_import":"1","article_processing_charge":"No","author":[{"id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P","first_name":"Marcin P","last_name":"Zagórski"},{"full_name":"Burda, Zdzisław","last_name":"Burda","first_name":"Zdzisław"},{"first_name":"Bartłomiej","last_name":"Wacław","full_name":"Wacław, Bartłomiej"}],"day":"09","file":[{"file_name":"IST-2017-740-v1+1_journal.pcbi.1005218.pdf","content_type":"application/pdf","relation":"main_file","file_size":3822299,"creator":"system","date_updated":"2020-07-14T12:44:37Z","file_id":"4926","checksum":"84f44ae92866c52ff1ca8a574558dca7","date_created":"2018-12-12T10:12:08Z","access_level":"open_access"}],"article_number":"e1005218","title":"Beyond the hypercube evolutionary accessibility of fitness landscapes with realistic mutational networks","publist_id":"6190"},{"year":"2016","department":[{"_id":"AnKi"}],"acknowledgement":"MZ has been supported by Polish National Science Centre Grant No. DEC-2012/07/N/NZ2/00107 and by Foundation of Polish Science award START. ","publisher":"Elsevier","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","ec_funded":1,"scopus_import":1,"_id":"1371","publication":"Physics of Life Reviews","oa_version":"None","month":"07","type":"journal_article","day":"01","abstract":[{"text":"Living cells can maintain their internal states, react to changing environments, grow, differentiate, divide, etc. All these processes are tightly controlled by what can be called a regulatory program. The logic of the underlying control can sometimes be guessed at by examining the network of influences amongst genetic components. Some associated gene regulatory networks have been studied in prokaryotes and eukaryotes, unveiling various structural features ranging from broad distributions of out-degrees to recurrent &quot;motifs&quot;, that is small subgraphs having a specific pattern of interactions. To understand what factors may be driving such structuring, a number of groups have introduced frameworks to model the dynamics of gene regulatory networks. In that context, we review here such in silico approaches and show how selection for phenotypes, i.e., network function, can shape network structure.","lang":"eng"}],"date_updated":"2021-01-12T06:50:13Z","page":"124 - 158","author":[{"first_name":"Olivier","last_name":"Martin","full_name":"Martin, Olivier"},{"full_name":"Krzywicki, André","last_name":"Krzywicki","first_name":"André"},{"last_name":"Zagórski","first_name":"Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P"}],"date_created":"2018-12-11T11:51:38Z","publist_id":"5840","volume":17,"title":"Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function","status":"public","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"language":[{"iso":"eng"}],"citation":{"chicago":"Martin, Olivier, André Krzywicki, and Marcin P Zagórski. “Drivers of Structural Features in Gene Regulatory Networks: From Biophysical Constraints to Biological Function.” <i>Physics of Life Reviews</i>. Elsevier, 2016. <a href=\"https://doi.org/10.1016/j.plrev.2016.06.002\">https://doi.org/10.1016/j.plrev.2016.06.002</a>.","ieee":"O. Martin, A. Krzywicki, and M. P. Zagórski, “Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function,” <i>Physics of Life Reviews</i>, vol. 17. Elsevier, pp. 124–158, 2016.","short":"O. Martin, A. Krzywicki, M.P. Zagórski, Physics of Life Reviews 17 (2016) 124–158.","ama":"Martin O, Krzywicki A, Zagórski MP. Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function. <i>Physics of Life Reviews</i>. 2016;17:124-158. doi:<a href=\"https://doi.org/10.1016/j.plrev.2016.06.002\">10.1016/j.plrev.2016.06.002</a>","apa":"Martin, O., Krzywicki, A., &#38; Zagórski, M. P. (2016). Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function. <i>Physics of Life Reviews</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.plrev.2016.06.002\">https://doi.org/10.1016/j.plrev.2016.06.002</a>","mla":"Martin, Olivier, et al. “Drivers of Structural Features in Gene Regulatory Networks: From Biophysical Constraints to Biological Function.” <i>Physics of Life Reviews</i>, vol. 17, Elsevier, 2016, pp. 124–58, doi:<a href=\"https://doi.org/10.1016/j.plrev.2016.06.002\">10.1016/j.plrev.2016.06.002</a>.","ista":"Martin O, Krzywicki A, Zagórski MP. 2016. Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function. Physics of Life Reviews. 17, 124–158."},"intvolume":"        17","publication_status":"published","quality_controlled":"1","date_published":"2016-07-01T00:00:00Z","doi":"10.1016/j.plrev.2016.06.002"},{"publication_status":"published","oa":1,"date_published":"2016-07-01T00:00:00Z","doi":"10.1016/j.plrev.2016.06.006","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://hal.archives-ouvertes.fr/hal-01531698"}],"status":"public","intvolume":"        17","language":[{"iso":"eng"}],"citation":{"ama":"Martin O, Zagórski MP. Network architectures and operating principles. Reply to comments on &#38;quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&#38;quot; <i>Physics of Life Reviews</i>. 2016;17:168-171. doi:<a href=\"https://doi.org/10.1016/j.plrev.2016.06.006\">10.1016/j.plrev.2016.06.006</a>","mla":"Martin, Olivier, and Marcin P. Zagórski. “Network Architectures and Operating Principles. Reply to Comments on &#38;quot;Drivers of Structural Features in Gene Regulatory Networks: From Biophysical Constraints to Biological Function&#38;quot;” <i>Physics of Life Reviews</i>, vol. 17, Elsevier, 2016, pp. 168–71, doi:<a href=\"https://doi.org/10.1016/j.plrev.2016.06.006\">10.1016/j.plrev.2016.06.006</a>.","ista":"Martin O, Zagórski MP. 2016. Network architectures and operating principles. Reply to comments on &#38;quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&#38;quot; Physics of Life Reviews. 17, 168–171.","apa":"Martin, O., &#38; Zagórski, M. P. (2016). Network architectures and operating principles. Reply to comments on &#38;quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&#38;quot; <i>Physics of Life Reviews</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.plrev.2016.06.006\">https://doi.org/10.1016/j.plrev.2016.06.006</a>","ieee":"O. Martin and M. P. Zagórski, “Network architectures and operating principles. Reply to comments on &#38;quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&#38;quot;,” <i>Physics of Life Reviews</i>, vol. 17. Elsevier, pp. 168–171, 2016.","chicago":"Martin, Olivier, and Marcin P Zagórski. “Network Architectures and Operating Principles. Reply to Comments on &#38;quot;Drivers of Structural Features in Gene Regulatory Networks: From Biophysical Constraints to Biological Function&#38;quot;” <i>Physics of Life Reviews</i>. Elsevier, 2016. <a href=\"https://doi.org/10.1016/j.plrev.2016.06.006\">https://doi.org/10.1016/j.plrev.2016.06.006</a>.","short":"O. Martin, M.P. Zagórski, Physics of Life Reviews 17 (2016) 168–171."},"page":"168 - 171","author":[{"last_name":"Martin","first_name":"Olivier","full_name":"Martin, Olivier"},{"last_name":"Zagórski","first_name":"Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P"}],"oa_version":"Preprint","type":"journal_article","month":"07","date_updated":"2022-08-26T09:39:27Z","day":"01","volume":17,"title":"Network architectures and operating principles. Reply to comments on &quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&quot;","publist_id":"5838","date_created":"2018-12-11T11:51:39Z","publisher":"Elsevier","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"AnKi"}],"year":"2016","_id":"1373","publication":"Physics of Life Reviews","article_processing_charge":"No","scopus_import":"1"},{"article_processing_charge":"No","_id":"9866","year":"2016","department":[{"_id":"AnKi"}],"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","publisher":"Public Library of Science","date_created":"2021-08-10T08:37:20Z","title":"ZIP-archived directory containing all data and computer programs","day":"09","date_updated":"2023-02-21T16:24:29Z","type":"research_data_reference","oa_version":"Published Version","month":"12","author":[{"full_name":"Zagórski, Marcin P","orcid":"0000-0001-7896-7762","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","first_name":"Marcin P","last_name":"Zagórski"},{"full_name":"Burda, Zdzisław","last_name":"Burda","first_name":"Zdzisław"},{"full_name":"Wacław, Bartłomiej","last_name":"Wacław","first_name":"Bartłomiej"}],"citation":{"short":"M.P. Zagórski, Z. Burda, B. Wacław, (2016).","chicago":"Zagórski, Marcin P, Zdzisław Burda, and Bartłomiej Wacław. “ZIP-Archived Directory Containing All Data and Computer Programs.” Public Library of Science, 2016. <a href=\"https://doi.org/10.1371/journal.pcbi.1005218.s009\">https://doi.org/10.1371/journal.pcbi.1005218.s009</a>.","ieee":"M. P. Zagórski, Z. Burda, and B. Wacław, “ZIP-archived directory containing all data and computer programs.” Public Library of Science, 2016.","apa":"Zagórski, M. P., Burda, Z., &#38; Wacław, B. (2016). ZIP-archived directory containing all data and computer programs. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005218.s009\">https://doi.org/10.1371/journal.pcbi.1005218.s009</a>","ista":"Zagórski MP, Burda Z, Wacław B. 2016. ZIP-archived directory containing all data and computer programs, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pcbi.1005218.s009\">10.1371/journal.pcbi.1005218.s009</a>.","mla":"Zagórski, Marcin P., et al. <i>ZIP-Archived Directory Containing All Data and Computer Programs</i>. Public Library of Science, 2016, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005218.s009\">10.1371/journal.pcbi.1005218.s009</a>.","ama":"Zagórski MP, Burda Z, Wacław B. ZIP-archived directory containing all data and computer programs. 2016. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005218.s009\">10.1371/journal.pcbi.1005218.s009</a>"},"related_material":{"record":[{"id":"1167","status":"public","relation":"used_in_publication"}]},"status":"public","doi":"10.1371/journal.pcbi.1005218.s009","date_published":"2016-12-09T00:00:00Z"}]