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Chessel A, Carazo Salas RE. From observing to predicting single-cell structure and function with high-throughput/high-content microscopy. Essays Biochem 2019; 63:197-208. [PMID: 31243141 PMCID: PMC6610450 DOI: 10.1042/ebc20180044] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 05/24/2019] [Accepted: 05/24/2019] [Indexed: 02/08/2023]
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.
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Affiliation(s)
- Anatole Chessel
- École polytechnique, Université Paris-Saclay, 91128 Palaiseau Cedex, France
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Henkel L, Rauscher B, Boutros M. Context-dependent genetic interactions in cancer. Curr Opin Genet Dev 2019; 54:73-82. [PMID: 31026747 DOI: 10.1016/j.gde.2019.03.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 03/18/2019] [Indexed: 01/03/2023]
Abstract
Genetic co-dependencies have been found in many contexts, from processes during the development of organisms to many diseases in man, including cancer. Genetic interactions - and in particular synthetic lethal phenotypes - have provided fundamental insights into the genetic architecture of cells and identified potential new opportunities for therapeutic interventions. However, recent studies also demonstrated that genetic interactions are highly context dependent and synthetic lethal interactions in one tumor context might not be translatable to others. Therefore, to better define and understand contexts will be a key challenge for future studies to fully exploit genetic interaction networks for target identification and cancer therapy. In this review, we summarize recent developments in mapping context-specific genetic interaction networks with a particular focus on conceptual and experimental advances in the past years. We then discuss genetic and environmental contexts that influence genetic interaction networks. Finally, we outline challenges of putting genetic interaction networks into context and give an outlook on future directions.
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Affiliation(s)
- Luisa Henkel
- Division of Signaling and Functional Genomics, German Cancer Research Center (DKFZ) and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Benedikt Rauscher
- Division of Signaling and Functional Genomics, German Cancer Research Center (DKFZ) and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Michael Boutros
- Division of Signaling and Functional Genomics, German Cancer Research Center (DKFZ) and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
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Heigwer F, Scheeder C, Miersch T, Schmitt B, Blass C, Pour Jamnani MV, Boutros M. Time-resolved mapping of genetic interactions to model rewiring of signaling pathways. eLife 2018; 7:40174. [PMID: 30592458 PMCID: PMC6319608 DOI: 10.7554/elife.40174] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Accepted: 11/21/2018] [Indexed: 12/23/2022] Open
Abstract
Context-dependent changes in genetic interactions are an important feature of cellular pathways and their varying responses under different environmental conditions. However, methodological frameworks to investigate the plasticity of genetic interaction networks over time or in response to external stresses are largely lacking. To analyze the plasticity of genetic interactions, we performed a combinatorial RNAi screen in Drosophila cells at multiple time points and after pharmacological inhibition of Ras signaling activity. Using an image-based morphology assay to capture a broad range of phenotypes, we assessed the effect of 12768 pairwise RNAi perturbations in six different conditions. We found that genetic interactions form in different trajectories and developed an algorithm, termed MODIFI, to analyze how genetic interactions rewire over time. Using this framework, we identified more statistically significant interactions compared to end-point assays and further observed several examples of context-dependent crosstalk between signaling pathways such as an interaction between Ras and Rel which is dependent on MEK activity. Editorial note This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
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Affiliation(s)
- Florian Heigwer
- Division Signaling and Functional Genomics, German Cancer Research Center, Heidelberg, Germany.,HBIGS Graduate School, Heidelberg University, Heidelberg, Germany.,Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Christian Scheeder
- Division Signaling and Functional Genomics, German Cancer Research Center, Heidelberg, Germany.,Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany.,HBIGS Graduate School, Heidelberg University, Heidelberg, Germany
| | - Thilo Miersch
- Division Signaling and Functional Genomics, German Cancer Research Center, Heidelberg, Germany.,Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Barbara Schmitt
- Division Signaling and Functional Genomics, German Cancer Research Center, Heidelberg, Germany.,Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Claudia Blass
- Division Signaling and Functional Genomics, German Cancer Research Center, Heidelberg, Germany.,Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Mischan Vali Pour Jamnani
- Division Signaling and Functional Genomics, German Cancer Research Center, Heidelberg, Germany.,Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Michael Boutros
- Division Signaling and Functional Genomics, German Cancer Research Center, Heidelberg, Germany.,Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
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