77 research outputs found
From observing to predicting single-cell structure and function with high-throughput/high-content microscopy
Abstract In the past 15 years, cell-based microscopy has evolved its focus from observing cell function to aiming to predict it. In particular—powered by breakthroughs in computer vision, large-scale image analysis and machine learning—high-throughput and high-content microscopy imaging have enabled to uniquely harness single-cell information to systematically discover and annotate genes and regulatory pathways, uncover systems-level interactions and causal links between cellular processes, and begin to clarify and predict causal cellular behaviour and decision making. Here we review these developments, discuss emerging trends in the field, and describe how single-cell ‘omics and single-cell microscopy are imminently in an intersecting trajectory. The marriage of these two fields will make possible an unprecedented understanding of cell and tissue behaviour and function
Dynamics of cell shape inheritance in fission yeast.
Every cell has a characteristic shape key to its fate and function. That shape is not only the product of genetic design and of the physical and biochemical environment, but it is also subject to inheritance. However, the nature and contribution of cell shape inheritance to morphogenetic control is mostly ignored. Here, we investigate morphogenetic inheritance in the cylindrically-shaped fission yeast Schizosaccharomyces pombe. Focusing on sixteen different 'curved' mutants--a class of mutants which often fail to grow axially straight--we quantitatively characterize their dynamics of cell shape inheritance throughout generations. We show that mutants of similar machineries display similar dynamics of cell shape inheritance, and exploit this feature to show that persistent axial cell growth in S. pombe is secured by multiple, separable molecular pathways. Finally, we find that one of those pathways corresponds to the swc2-swr1-vps71 SWR1/SRCAP chromatin remodelling complex, which acts additively to the known mal3-tip1-mto1-mto2 microtubule and tea1-tea2-tea4-pom1 polarity machineries.This is the published manuscript. It has been published by PLoS in PLoS ONE and is available online here: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0106959
Mineotaur:a tool for high-content microscopy screen sharing and visual analytics
High-throughput/high-content microscopy-based screens are powerful tools for functional genomics, yielding intracellular information down to the level of single-cells for thousands of genotypic conditions. However, accessing their data requires specialized knowledge and most often that data is no longer analyzed after initial publication. We describe Mineotaur (http://www.mineotaur.org), a open-source, downloadable web application that allows easy online sharing and interactive visualisation of large screen datasets, facilitating their dissemination and further analysis, and enhancing their impact. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0836-5) contains supplementary material, which is available to authorized users
Mechanical cell competition kills cells via induction of lethal p53 levels.
Cell competition is a quality control mechanism that eliminates unfit cells. How cells compete is poorly understood, but it is generally accepted that molecular exchange between cells signals elimination of unfit cells. Here we report an orthogonal mechanism of cell competition, whereby cells compete through mechanical insults. We show that MDCK cells silenced for the polarity gene scribble (scrib(KD)) are hypersensitive to compaction, that interaction with wild-type cells causes their compaction and that crowding is sufficient for scrib(KD) cell elimination. Importantly, we show that elevation of the tumour suppressor p53 is necessary and sufficient for crowding hypersensitivity. Compaction, via activation of Rho-associated kinase (ROCK) and the stress kinase p38, leads to further p53 elevation, causing cell death. Thus, in addition to molecules, cells use mechanical means to compete. Given the involvement of p53, compaction hypersensitivity may be widespread among damaged cells and offers an additional route to eliminate unfit cells.This work was supported by a Cancer Research UK Programme Grant (EP and LW A12460), a Royal Society University Research fellowship to EP (UF0905080), a Wellcome Trust PhD studentship to I.K, a Cambridge Cancer Centre PhD studentship to MG and Core grant funding from the Wellcome Trust (092096) and CRUK (C6946/A14492).This is the final version of the article. It first appeared from Nature Publishing Group via https://doi.org/10.1038/ncomms1137
Publisher Correction: Image Data Resource: a bioimage data integration and publication platform
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EDAM-bioimaging : The ontology of bioimage informatics operations, topics, data, and formats
International audienceThe ontology of bioimage informatics operations, topics, data, and formats What? EDAM-bioimaging is an extension of the EDAM ontology, dedicated to bioimage analysis, bioimage informatics, and bioimaging. Why? EDAM-bioimaging enables interoperable descriptions of software, publications, data, and workflows, fostering reliable and transparent science. How? EDAM-bioimaging is developed in a community spirit, in a welcoming collaboration between numerous bioimaging experts and ontology developers. How can I contribute? We need your expertise! You can help by reviewing parts of EDAM-bioimaging, posting comments with suggestions, requirements, or needs for clarification, or participating in a Taggathon or another hackathon. Please see https://github.com/edamontology/edam-bioimaging#contributing. EDAM-bioimaging is developed in an interdisciplinary open collaboration supported by the hosting institutions, participating individuals, and NEUBIAS COST Action (CA15124) and ELIXIR-EXCELERATE (676559) funded by the Horizon 2020 Framework Programme of the European Union. https://github.com/edamontology/edam-bioimaging @edamontology /edamontology/edam-bioimagin
Vision par ordinateur et otolithe (de la perception visuelle à une représentation des connaissances)
Cette thèse s'intéresse à l'application des techniques de vision par ordinateur aux images d'otolithes de poisson, de petites concrétions calcaires d'un grand intérêt en biologie et écologie marine. Des considérations tant biologiques que perceptuelles permettent d'identifier dans les images de coupes d'otolithes deux informations comme étant utiles et importantes à l'analyse et l'utilisation des otolithes: l'évolution géométrique de la forme de l'otolithe, et les marques de croissances, des courbes correspondant localement à des crêtes et vallées. Un algorithme basé sur la détection a contrario est proposé pour extraire itérativement ces deux informations. Celui-ci passe par une reconstruction par interpolation de l'orientation en chaque point de l'image. Les buts incluent à la fois une meilleure compréhension et modélisation des otolithes et l'automatisation de processus fastidieux manuellement, comme l'estimation de l'âge pour la gestion des stock de poissons.This work studies the application of computer vision methods to the analysis of fish otoliths. Fish otoliths are small calcerous concretions set in fishes inner ears of much interest in biology and ecology. From both biological and perceptual analysis, two informations from otoliths sections images are characterised as being useful and important in the analysis and use of otolith: the global geometrical evolution of the outline, and the growth rings, corresponding to ridges and valley of the image. An algorithm based on an a contrario detection is proposed to iteratively compute both of those informations. An orientation field of the tangent to the locally relevant structures is estimated in this algorithm using orientation interpolation techniques. Biological aims include a better understanding of otolith formation and automating tedious tasks such as fish age estimation, of key importance in fish stock management.RENNES1-BU Sciences Philo (352382102) / SudocSudocFranceF
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