DSpace Angular :: Browsing by Author "Bertocchi, Cristina"

Browsing by Author "Bertocchi, Cristina"

Now showing 1 - 13 of 13

A 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
A 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.
AI-assisted imaging screening reveals mechano-molecular tissue organizers and network of signaling hubs
(2024) Bertocchi, Cristina; Alegría, Juan José; Vásquez Sepúlveda, Sebastian Ignacio; Ibañez Prat, Rosario; Aishwarya, Srinivasan; Arraño Valenzuela, Ignacio Alberto; Castro Pereira, Barbara Helen; Soto Montandon, Catalina Andrea; Trujillo Espergel, Alejandra Isabel; Owen, Gareth Ivor; Kanchanawong, Pakorn; Cerda, Mauricio; Motta, Giovanni; Zaidel Bar, Ronen; Ravasio, Andrea
Cadherin-mediated adhesions are crucial mechanical and signaling hubs that connect cells within a tissue and probe the mechanics of the surrounding environment. They constitute a physical link between the actin cytoskeleton of neighboring cells, providing the mechanical coordination needed for morphogenetic processes, tissue homeostasis, collective migration, and regeneration. Disruptions in adhesion mechanisms are closely linked to the breakdown of epithelial structure and the emergence of disease-related traits characteristic of cancer progression. The cadhesome network comprises over 170 structural and regulatory proteins involved in cadherin-mediated adhesion. While this network is essential for coordinating tissue responses to mechanical stress, its complexity has historically limited our understanding of how individual components contribute to force transmission and tissue homeostasis. Recent technological advances offer tools to investigate large molecular networks in cellular function and pathology (functional omics). Leveraging these advances, we developed an experimental and analytical platform combining high-throughput gene silencing, imaging, and artificial intelligence (AI) to systematically profile each role of each protein in tissue formation, mechanical stability, and response to induced tension. Using EpH4 cells as an epithelial tissue model, we performed systematic silencing in triplicate, capturing a range of tissue phenotypes under baseline and tension-inducing conditions. Machine learning methods were used to analyze complex imaging data, quantify tissue ruptures, characterize junctional organization, and measure tension states of the tissue. By incorporating machine learning algorithms, we automated image feature extraction, clustering, and classification, enabling an unprecedented quantitative evaluation of tissue mechanics at scale. Our machine learning models allowed us to identify significant patterns, including protein specific responses to tension and their roles in tissue-level mechanical integrity. Finally, we constructed a protein interaction network detailing the roles of each protein, their physical interactions, and known links to cancer. The network analysis revealed three prominent mechanotransductive and signaling subnetworks centered around E-cadherin, EGFR, and RAC1. Our study provides a foundational framework for investigating mechanosensing proteins and it offers a scalable blueprint for discovering potential therapeutic targets in diseases like cancer, where tissue mechanics play a crucial role.
Alternative molecular mechanisms for force transmission at adherens junctions via β-catenin-vinculin interaction
(2024) Morales-Camilo, Nicole; Liu, Jingzhun; Ramírez Contador, Manuel José; Canales Salgado, Patricio Andrés; Alegría Fuentes, Juan José; Liu, Xuyao; Ong, Ting Ong; Barrera Rojas, Nelson Patricio; Fierro Huerta, Angélica María; Toyama, Yusuke; Goult, Benjamin; Wang, Yilin; Meng, Yue; Nishimura, Ryosuke; Fong-Ngern, Kedsarin; Low, Christine Siok Lan; Kanchanawong, Pakorn; Yan, Jie; Ravasio, Andrea; Bertocchi, Cristina
Force transmission through adherens junctions (AJs) is crucial for multicellular organization, wound healing and tissue regeneration. Recent studies shed light on the molecular mechanisms of mechanotransduction at the AJs. However, the canonical model fails to explain force transmission when essential proteins of the mechanotransduction module are mutated or missing. Here, we demonstrate that, in absence of α-catenin, β-catenin can directly and functionally interact with vinculin in its open conformation, bearing physiological forces. Furthermore, we found that β-catenin can prevent vinculin autoinhibition in the presence of α-catenin by occupying vinculin´s head-tail interaction site, thus preserving force transmission capability. Taken together, our findings suggest a multi-step force transmission process at AJs, where α-catenin and β-catenin can alternatively and cooperatively interact with vinculin. This can explain the graded responses needed to maintain tissue mechanical homeostasis and, importantly, unveils a force-bearing mechanism involving β-catenin and extended vinculin that can potentially explain the underlying process enabling collective invasion of metastatic cells lacking α-catenin.
Author 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
Author 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 Viasnoff
Correction 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.
Community-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 Klara
Images 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.
Integrating bioengineering, super-resolution microscopy and mechanobiology in autophagy research: addendum to the guidelines (4th edition)
(2024) Ravasio, Andrea; Klionsky, Daniel J.; Bertocchi, Cristina
Recent key technological developments, such as super-resolution microscopy and microfabrication, enabled investigation of biological processes, including macroautophagy/autophagy, with unprecedented spatiotemporal resolution and control over experimental conditions. Such disruptive innovations deepened our capability to provide mechanistic understandings of the autophagic process and its causes. This addendum aims to expand the guidelines on autophagy in three key directions: optical methods enabling visualization of autophagic machinery beyond the diffraction-limited resolution; bioengineering enabling accurate designs and control over experimental conditions; and theoretical advances in mechanobiology connecting autophagy and mechanical processes of the cell.
Mechanoautophagy: Synergies Between Autophagy and Cell Mechanotransduction at Adhesive Complexes
(FRONTIERS MEDIA SA, 2022) Ravasio, Andrea; Morselli, Eugenia; Bertocchi, Cristina
Cells 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
Palmitic 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, Eugenia
Palmitic 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.
Palmitic 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.
Single-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.
VolumePeeler: 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, Mauricio
Motivation 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.

Browsing by Author "Bertocchi, Cristina"

Results Per Page

Sort Options