@article{14484,
  abstract     = {Intercellular signaling molecules, known as morphogens, act at a long range in developing tissues to provide spatial information and control properties such as cell fate and tissue growth. The production, transport, and removal of morphogens shape their concentration profiles in time and space. Downstream signaling cascades and gene regulatory networks within cells then convert the spatiotemporal morphogen profiles into distinct cellular responses. Current challenges are to understand the diverse molecular and cellular mechanisms underlying morphogen gradient formation, as well as the logic of downstream regulatory circuits involved in morphogen interpretation. This knowledge, combining experimental and theoretical results, is essential to understand emerging properties of morphogen-controlled systems, such as robustness and scaling.},
  author       = {Kicheva, Anna and Briscoe, James},
  issn         = {1530-8995},
  journal      = {Annual Review of Cell and Developmental Biology},
  pages        = {91--121},
  publisher    = {Annual Reviews},
  title        = {{Control of tissue development by morphogens}},
  doi          = {10.1146/annurev-cellbio-020823-011522},
  volume       = {39},
  year         = {2023},
}

@article{12837,
  abstract     = {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.},
  author       = {Bocanegra, Laura and Singh, Amrita and Hannezo, Edouard B and Zagórski, Marcin P and Kicheva, Anna},
  issn         = {1745-2481},
  journal      = {Nature Physics},
  pages        = {1050--1058},
  publisher    = {Springer Nature},
  title        = {{Cell cycle dynamics control fluidity of the developing mouse neuroepithelium}},
  doi          = {10.1038/s41567-023-01977-w},
  volume       = {19},
  year         = {2023},
}

@article{7883,
  abstract     = {All vertebrates have a spinal cord with dimensions and shape specific to their species. Yet how species‐specific organ size and shape are achieved is a fundamental unresolved question in biology. The formation and sculpting of organs begins during embryonic development. As it develops, the spinal cord extends in anterior–posterior direction in synchrony with the overall growth of the body. The dorsoventral (DV) and apicobasal lengths of the spinal cord neuroepithelium also change, while at the same time a characteristic pattern of neural progenitor subtypes along the DV axis is established and elaborated. At the basis of these changes in tissue size and shape are biophysical determinants, such as the change in cell number, cell size and shape, and anisotropic tissue growth. These processes are controlled by global tissue‐scale regulators, such as morphogen signaling gradients as well as mechanical forces. Current challenges in the field are to uncover how these tissue‐scale regulatory mechanisms are translated to the cellular and molecular level, and how regulation of distinct cellular processes gives rise to an overall defined size. Addressing these questions will help not only to achieve a better understanding of how size is controlled, but also of how tissue size is coordinated with the specification of pattern.},
  author       = {Kuzmicz-Kowalska, Katarzyna and Kicheva, Anna},
  issn         = {17597692},
  journal      = {Wiley Interdisciplinary Reviews: Developmental Biology},
  publisher    = {Wiley},
  title        = {{Regulation of size and scale in vertebrate spinal cord development}},
  doi          = {10.1002/wdev.383},
  year         = {2021},
}

@article{9349,
  abstract     = {The way in which interactions between mechanics and biochemistry lead to the emergence of complex cell and tissue organization is an old question that has recently attracted renewed interest from biologists, physicists, mathematicians and computer scientists. Rapid advances in optical physics, microscopy and computational image analysis have greatly enhanced our ability to observe and quantify spatiotemporal patterns of signalling, force generation, deformation, and flow in living cells and tissues. Powerful new tools for genetic, biophysical and optogenetic manipulation are allowing us to perturb the underlying machinery that generates these patterns in increasingly sophisticated ways. Rapid advances in theory and computing have made it possible to construct predictive models that describe how cell and tissue organization and dynamics emerge from the local coupling of biochemistry and mechanics. Together, these advances have opened up a wealth of new opportunities to explore how mechanochemical patterning shapes organismal development. In this roadmap, we present a series of forward-looking case studies on mechanochemical patterning in development, written by scientists working at the interface between the physical and biological sciences, and covering a wide range of spatial and temporal scales, organisms, and modes of development. Together, these contributions highlight the many ways in which the dynamic coupling of mechanics and biochemistry shapes biological dynamics: from mechanoenzymes that sense force to tune their activity and motor output, to collectives of cells in tissues that flow and redistribute biochemical signals during development.},
  author       = {Lenne, Pierre François and Munro, Edwin and Heemskerk, Idse and Warmflash, Aryeh and Bocanegra, Laura and Kishi, Kasumi and Kicheva, Anna and Long, Yuchen and Fruleux, Antoine and Boudaoud, Arezki and Saunders, Timothy E. and Caldarelli, Paolo and Michaut, Arthur and Gros, Jerome and Maroudas-Sacks, Yonit and Keren, Kinneret and Hannezo, Edouard B and Gartner, Zev J. and Stormo, Benjamin and Gladfelter, Amy and Rodrigues, Alan and Shyer, Amy and Minc, Nicolas and Maître, Jean Léon and Di Talia, Stefano and Khamaisi, Bassma and Sprinzak, David and Tlili, Sham},
  issn         = {1478-3975},
  journal      = {Physical biology},
  number       = {4},
  publisher    = {IOP Publishing},
  title        = {{Roadmap for the multiscale coupling of biochemical and mechanical signals during development}},
  doi          = {10.1088/1478-3975/abd0db},
  volume       = {18},
  year         = {2021},
}

@article{7165,
  abstract     = {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.},
  author       = {Guerrero, Pilar and Perez-Carrasco, Ruben and Zagórski, Marcin P and Page, David and Kicheva, Anna and Briscoe, James and Page, Karen M.},
  issn         = {1477-9129},
  journal      = {Development},
  number       = {23},
  publisher    = {The Company of Biologists},
  title        = {{Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium}},
  doi          = {10.1242/dev.176297},
  volume       = {146},
  year         = {2019},
}

@article{162,
  abstract     = {Facial shape is the basis for facial recognition and categorization. Facial features reflect the underlying geometry of the skeletal structures. Here, we reveal that cartilaginous nasal capsule (corresponding to upper jaw and face) is shaped by signals generated by neural structures: brain and olfactory epithelium. Brain-derived Sonic Hedgehog (SHH) enables the induction of nasal septum and posterior nasal capsule, whereas the formation of a capsule roof is controlled by signals from the olfactory epithelium. Unexpectedly, the cartilage of the nasal capsule turned out to be important for shaping membranous facial bones during development. This suggests that conserved neurosensory structures could benefit from protection and have evolved signals inducing cranial cartilages encasing them. Experiments with mutant mice revealed that the genomic regulatory regions controlling production of SHH in the nervous system contribute to facial cartilage morphogenesis, which might be a mechanism responsible for the adaptive evolution of animal faces and snouts.},
  author       = {Kaucka, Marketa and Petersen, Julian and Tesarova, Marketa and Szarowska, Bara and Kastriti, Maria and Xie, Meng and Kicheva, Anna and Annusver, Karl and Kasper, Maria and Symmons, Orsolya and Pan, Leslie and Spitz, Francois and Kaiser, Jozef and Hovorakova, Maria and Zikmund, Tomas and Sunadome, Kazunori and Matise, Michael P and Wang, Hui and Marklund, Ulrika and Abdo, Hind and Ernfors, Patrik and Maire, Pascal and Wurmser, Maud and Chagin, Andrei S and Fried, Kaj and Adameyko, Igor},
  journal      = {eLife},
  publisher    = {eLife Sciences Publications},
  title        = {{Signals from the brain and olfactory epithelium control shaping of the mammalian nasal capsule cartilage}},
  doi          = {10.7554/eLife.34465},
  volume       = {7},
  year         = {2018},
}

@inbook{37,
  abstract     = {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.},
  author       = {Zagórski, Marcin P and Kicheva, Anna},
  booktitle    = {Morphogen Gradients },
  isbn         = {978-1-4939-8771-9},
  issn         = {1064-3745},
  pages        = {47 -- 63},
  publisher    = {Springer Nature},
  title        = {{Measuring dorsoventral pattern and morphogen signaling profiles in the growing neural tube}},
  doi          = {10.1007/978-1-4939-8772-6_4},
  volume       = {1863},
  year         = {2018},
}

@article{685,
  abstract     = {By applying methods and principles from the physical sciences to biological problems, D'Arcy Thompson's On Growth and Form demonstrated how mathematical reasoning reveals elegant, simple explanations for seemingly complex processes. This has had a profound influence on subsequent generations of developmental biologists. We discuss how this influence can be traced through twentieth century morphologists, embryologists and theoreticians to current research that explores the molecular and cellular mechanisms of tissue growth and patterning, including our own studies of the vertebrate neural tube.},
  author       = {Briscoe, James and Kicheva, Anna},
  issn         = {09254773},
  journal      = {Mechanisms of Development},
  pages        = {26 -- 31},
  publisher    = {Elsevier},
  title        = {{The physics of development 100 years after D'Arcy Thompson's “on growth and form”}},
  doi          = {10.1016/j.mod.2017.03.005},
  volume       = {145},
  year         = {2017},
}

@article{654,
  abstract     = {In November 2016, developmental biologists, synthetic biologists and engineers gathered in Paris for a meeting called ‘Engineering the embryo’. The participants shared an interest in exploring how synthetic systems can reveal new principles of embryonic development, and how the in vitro manipulation and modeling of development using stem cells can be used to integrate ideas and expertise from physics, developmental biology and tissue engineering. As we review here, the conference pinpointed some of the challenges arising at the intersection of these fields, along with great enthusiasm for finding new approaches and collaborations.},
  author       = {Kicheva, Anna and Rivron, Nicolas},
  issn         = {09501991},
  journal      = {Development},
  number       = {5},
  pages        = {733 -- 736},
  publisher    = {Company of Biologists},
  title        = {{Creating to understand – developmental biology meets engineering in Paris}},
  doi          = {10.1242/dev.144915},
  volume       = {144},
  year         = {2017},
}

@article{943,
  abstract     = {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.},
  author       = {Zagórski, Marcin P and Tabata, Yoji and Brandenberg, Nathalie and Lutolf, Matthias and Tkacik, Gasper and Bollenbach, Tobias and Briscoe, James and Kicheva, Anna},
  issn         = {00368075},
  journal      = {Science},
  number       = {6345},
  pages        = {1379 -- 1383},
  publisher    = {American Association for the Advancement of Science},
  title        = {{Decoding of position in the developing neural tube from antiparallel morphogen gradients}},
  doi          = {10.1126/science.aam5887},
  volume       = {356},
  year         = {2017},
}

