Browsing by Author "Bertocchi, Cristina"
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- ItemA characterization of cancer vasculogenic mimicry: Extracellular matrix induced cellular signaling to lumen formation.(AMER ASSOC CANCER RESEARCH, 2021) Mingo, Gabriel; Valdivia, Andres; Aldana, Varina; Pradenas, Javiera; Babbitt, Nicole; Gonzalez, Pamela; Nualart, Francisco; Diaz, Jorge; Leyton, Lisette; Bertocchi, Cristina; Owen, Gareth
- ItemA computational framework for testing hypotheses of the minimal mechanical requirements for cell aggregation using early annual killifish embryogenesis as a model(FRONTIERS MEDIA SA, 2023) Montenegro-Rojas, Ignacio; Yanez, Guillermo; Skog, Emily; Guerrero-Calvo, Oscar; Andaur-Lobos, Martin; Dolfi, Luca; Cellerino, Alessandro; Cerda, Mauricio; Concha, Miguel L.; Bertocchi, Cristina; Rojas, Nicolas O.; Ravasio, Andrea; Rudge, Timothy J.Introduction: Deciphering the biological and physical requirements for the outset of multicellularity is limited to few experimental models. The early embryonic development of annual killifish represents an almost unique opportunity to investigate de novo cellular aggregation in a vertebrate model. As an adaptation to seasonal drought, annual killifish employs a unique developmental pattern in which embryogenesis occurs only after undifferentiated embryonic cells have completed epiboly and dispersed in low density on the egg surface. Therefore, the first stage of embryogenesis requires the congregation of embryonic cells at one pole of the egg to form a single aggregate that later gives rise to the embryo proper. This unique process presents an opportunity to dissect the self-organizing principles involved in early organization of embryonic stem cells. Indeed, the physical and biological processes required to form the aggregate of embryonic cells are currently unknown., Methods: Here, we developed an in silico, agent-based biophysical model that allows testing how cell-specific and environmental properties could determine the aggregation dynamics of early Killifish embryogenesis. In a forward engineering approach, we then proceeded to test two hypotheses for cell aggregation (cell-autonomous and a simple taxis model) as a proof of concept of modeling feasibility. In a first approach (cell autonomous system), we considered how intrinsic biophysical properties of the cells such as motility, polarity, density, and the interplay between cell adhesion and contact inhibition of locomotion drive cell aggregation into self-organized clusters. Second, we included guidance of cell migration through a simple taxis mechanism to resemble the activity of an organizing center found in several developmental models., Results: Our numerical simulations showed that random migration combined with low cell-cell adhesion is sufficient to maintain cells in dispersion and that aggregation can indeed arise spontaneously under a limited set of conditions, but, without environmental guidance, the dynamics and resulting structures do not recapitulate in vivo observations., Discussion: Thus, an environmental guidance cue seems to be required for correct execution of early aggregation in early killifish development. However, the nature of this cue (e.g., chemical or mechanical) can only be determined experimentally. Our model provides a predictive tool that could be used to better characterize the process and, importantly, to design informed experimental strategies.
- ItemAuthor Correction: Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity(2020) Ravasio, Andrea; Myaing, Myint Z.; Chia, Shumei; Arora, Aditya; Sathe, Aneesh; Cao, Elaine Yiqun; Bertocchi, Cristina; Sharma, Ankur; Arasi, Bakya; Chung, Vin Yee; Greene, Adrienne C.; Tan, Tuan Zea; Chen, Zhongwen; Ong, Hui Ting; Iyer, N. Gopalakrishna; Huang, Ruby YunJu; DasGupta, Ramanuj; Groves, Jay T.; Viasnoff, Virgile
- ItemAuthor Correction: Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity(2020) Andrea Ravasio; Myint Z. Myaing; Shumei Chia; Aditya Arora; Aneesh Sathe; Elaine Yiqun Cao; Bertocchi, Cristina; Ankur Sharma; Bakya Arasi; Vin Yee Chung; Adrienne C. Greene; Tuan Zea Tan; Zhongwen Chen; Hui Ting Ong; N. Gopalakrishna Iyer; Ruby YunJu Huang; Ramanuj DasGupta; Jay T. Groves; Virgile ViasnoffCorrection to: Communications Biology https://doi.org/10.1038/s42003-020-01136-4, published online 6 August 2020. In the original published version of the Article, contributing author Adrienne C. Greene of the University of California, Berkeley was incorrectly listed as Adrianne C. Green of the National Cancer Centre Singapore. The error has been corrected in the HTML and PDF versions of the Article.
- ItemCommunity-developed checklists for publishing images and image analyses(2023) Schmied, Christopher; Nelson, Michael S.; Avilov, Sergiy; Bakker, Gert-Jan; Bertocchi, Cristina; Bischof, Johanna; Boehm, Ulrike; Brocher, Jan; Carvalho, Mariana; Chiritescu, Catalin; Christopher, Jana; Cimini, Beth A.; Conde-Sousa, Eduardo; Ebner, Michael; Ecker, Rupert; Eliceiri, Kevin; Fernandez-Rodriguez, Julia; Gaudreault, Nathalie; Gelman, Laurent; Grunwald, David; Gu, Tingting; Halidi, Nadia; Hammer, Mathias; Hartley, Matthew; Held, Marie; Jug, Florian; Kapoor, Varun; Koksoy, Ayse Aslihan; Lacoste, Judith; Le Dévédec, Sylvia; Le Guyader, Sylvie; Liu, Penghuan; Martins, Gabriel G.; Mathur, Aastha; Miura, Kota; Montero Llopis, Paula; Nitschke, Roland; North, Alison; Parslow, Adam C.; Payne-Dwyer, Alex; Plantard, Laure; Ali, Rizwan; Schroth-Diez, Britta; Schütz, Lucas; Scott, Ryan T.; Seitz, Arne; Selchow, Olaf; Sharma, Ved P.; Spitaler, Martin; Srinivasan, Sathya; Strambio-De-Castillia, Caterina; Taatjes, Douglas; Tischer, Christian; Jambor, Helena KlaraImages document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.
- ItemCommunity-developed checklists for publishing images and image analysis(2023) Schmied, Christopher; Nelson, Michael S.; Avilov, Sergiy; Bakker, Gert-Jan; Bertocchi, Cristina; Bischof, Johanna; Boehm, Ulrike; Brocher, Jan; Carvalho, Mariana; Chiritescu, Catalin; Christopher, Jana; Cimini, Beth A.; Conde Sousa, Eduardo; Ebner, Michael; Ecker, Rupert; Eliceiri, Kevin; Fernandez Rodriguez, Julia; Gaudreault, Nathalie; Gelman, Laurent; Grunwald, DavidImages document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality of microscopy data is in publications.
- ItemIllumination Power, Stability, and Linearity Measurements for Confocal and Widefield Microscopes(2023) Gaudreault, Nathalie; Ali, Rizwan; Avilov, Sergiy V.; Bagley, Steve; Bammann, Rodrigo R.; Barachati, Fabio; Bertocchi, Cristina; Boehm, Ulrike; Bosch, Manel; Brideau, Craig; Carvalho, M. T.; Colarusso, Pina; Duwé, Sam; Guilbert, Thomas; Kirchner, Marcel; Aydemir-Koksoy, Ayse Aslihan; Krens, Gabriel; Laude, Alex; Ledue, Jeffrey M.; Liu, PenghuanTo obtain accurate, reproducible, and interpretable data when conducting imaging experiments, it is critical to consider external factors affecting data acquisition at various steps of the experimental workflow. Illumination power and stability represent two critical factors, especially when comparing fluorescence intensities between images during a time-lapse experiment or experiments performed at different times or on different microscopes. The fluorescence signal can be generated by different types of light sources. These light sources and their coupling elements (e.g., fibers) can display varying performances over time as they age, move, or as environmental conditions change. Unfortunately, microscope users can often only set illumination power as a percentage of its maximal output and may, therefore, not be aware of potential performance changes. It is important to recognize that a set percentage will not always yield the same illumination power in Watts at the objective over the course of an experiment, not to mention between days or systems. This means that selecting for example 10% output may lead to different experimental results over time or even between two microscopes of the same model. In addition to illumination stability, working within the linear range of the illumination power allows to adjust accurately the illumination power absolute value (in mW) using fraction (or %) of its maximal value through the imaging software. If you are responsible for system maintenance, routinely measuring the illumination power, stability, and linearity over time can help you detect issues that affect the integrity of the system and thus the reproducibility of an experiment. This protocol describes how to measure the stability and linearity of the illumination power using calibrated external power sensors. This protocol is at the moment intended for confocal systems (raster scanning and spinning disks), and widefield systems. It represents the collective experience of over 50 imaging scientists. Measurements made by our working group with this protocol are available in a public database, which will be updated with further contributions from the community.
- ItemMechanoautophagy: Synergies Between Autophagy and Cell Mechanotransduction at Adhesive Complexes(FRONTIERS MEDIA SA, 2022) Ravasio, Andrea; Morselli, Eugenia; Bertocchi, CristinaCells are exposed and respond to various mechanical forces and physical cues stemming from their environment. This interaction has been seen to differentially regulate various cellular processes for maintenance of homeostasis, of which autophagy represents one of the major players. In addition, autophagy has been suggested to regulate mechanical functions of the cells including their interaction with the environment. In this minireview, we summarize the state of the art of the fascinating interplay between autophagy and the mechanotransduction machinery associated with cell adhesions, that we name center dot Mechanoautophagy center dot
- ItemPalmitic acid control of ciliogenesis modulates insulin signaling in hypothalamic neurons through an autophagy-dependent mechanism(SPRINGERNATURE, 2022) Avalos, Yenniffer; Paz Hernandez-Caceres, Maria; Lagos, Pablo; Pinto-Nunez, Daniela; Rivera, Patricia; Burgos, Paulina; Diaz-Castro, Francisco; Joy-Immediato, Michelle; Venegas-Zamora, Leslye; Lopez-Gallardo, Erik; Kretschmar, Catalina; Batista-Gonzalez, Ana; Cifuentes-Araneda, Flavia; Toledo-Valenzuela, Lilian; Rodriguez-Pena, Marcelo; Espinoza-Caicedo, Jasson; Perez-Leighton, Claudio; Bertocchi, Cristina; Cerda, Mauricio; Troncoso, Rodrigo; Parra, Valentina; Budini, Mauricio; Burgos, Patricia, V; Criollo, Alfredo; Morselli, EugeniaPalmitic acid (PA) is significantly increased in the hypothalamus of mice, when fed chronically with a high-fat diet (HFD). PA impairs insulin signaling in hypothalamic neurons, by a mechanism dependent on autophagy, a process of lysosomal-mediated degradation of cytoplasmic material. In addition, previous work shows a crosstalk between autophagy and the primary cilium (hereafter cilium), an antenna-like structure on the cell surface that acts as a signaling platform for the cell. Ciliopathies, human diseases characterized by cilia dysfunction, manifest, type 2 diabetes, among other features, suggesting a role of the cilium in insulin signaling. Cilium depletion in hypothalamic pro-opiomelanocortin (POMC) neurons triggers obesity and insulin resistance in mice, the same phenotype as mice deficient in autophagy in POMC neurons. Here we investigated the effect of chronic consumption of HFD on cilia; and our results indicate that chronic feeding with HFD reduces the percentage of cilia in hypothalamic POMC neurons. This effect may be due to an increased amount of PA, as treatment with this saturated fatty acid in vitro reduces the percentage of ciliated cells and cilia length in hypothalamic neurons. Importantly, the same effect of cilia depletion was obtained following chemical and genetic inhibition of autophagy, indicating autophagy is required for ciliogenesis. We further demonstrate a role for the cilium in insulin sensitivity, as cilium loss in hypothalamic neuronal cells disrupts insulin signaling and insulin-dependent glucose uptake, an effect that correlates with the ciliary localization of the insulin receptor (IR). Consistently, increased percentage of ciliated hypothalamic neuronal cells promotes insulin signaling, even when cells are exposed to PA. Altogether, our results indicate that, in hypothalamic neurons, impairment of autophagy, either by PA exposure, chemical or genetic manipulation, cause cilia loss that impairs insulin sensitivity.
- ItemPalmitic acid reduces the autophagic flux in hypothalamic neurons by impairing autophagosome-lysosome fusion and endolysosomal dynamics(2020) Hernández Cáceres, María Paz; Cereceda, K.; Hernández, S.; Li, Y.; Rivera Reyes, Patricia Ximena; Toledo Valenzuela, Lilian Alejandra; Cifuentes Araneda, Flavia Dominique; Pérez Leighton, Claudio; Bertocchi, Cristina; Morselli, Eugenia; Narro, C.; Silva, P.; Avalos, Y.; Jara, C.; Burgos, P.; Lagos, P.; Clegg, D. J.; Criollo, A.; Tapia Rojas, C.; Burgos, P. V.
- ItemSingle-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity(2020) Ravasio, Andrea; Myaing, M. Z.; Chia, S. M.; Arora, A.; Sathe, A.; Cao, E. Y.; Bertocchi, Cristina; Sharma, A.; Arasi, B.; Chung, V. Y.; Green, A. C.; Tan, T. Z.; Chen, Z. W.; Ong, H. T.; Iyer, N. G.; Huang, R. Y.; DasGupta, R.; Groves, J. T.; Viasnoff, V.
- ItemVolumePeeler: a novel FIJI plugin for geometric tissue peeling to improve visualization and quantification of 3D image stacks(BMC, 2023) Gatica, Marilyn; Navarro, Carlos F. F.; Lavado, Alejandro; Reig, German; Pulgar, Eduardo; Llanos, Paula; Haertel, Steffen; Ravasio, Andrea; Bertocchi, Cristina; Concha, Miguel L. L.; Cerda, MauricioMotivation Quantitative descriptions of multi-cellular structures from optical microscopy imaging are prime to understand the variety of three-dimensional (3D) shapes in living organisms. Experimental models of vertebrates, invertebrates and plants, such as zebrafish, killifish, Drosophila or Marchantia, mainly comprise multilayer tissues, and even if microscopes can reach the needed depth, their geometry hinders the selection and subsequent analysis of the optical volumes of interest. Computational tools to "peel" tissues by removing specific layers and reducing 3D volume into planar images, can critically improve visualization and analysis.Results We developed VolumePeeler, a versatile FIJI plugin for virtual 3D "peeling" of image stacks. The plugin implements spherical and spline surface projections. We applied VolumePeeler to perform peeling in 3D images of spherical embryos, as well as non-spherical tissue layers. The produced images improve the 3D volume visualization and enable analysis and quantification of geometrically challenging microscopy datasets.