Basic Phenotypes of Endocytic System Recognized by Independent Phenotypes Analysis of a High-throughput Genomic Screen

Abstract:

High-content screens (HCS) using chemical and genomic interference based on light microscopy and quantitative image analysis yielded a large amount of multi-parametric (MP) phenotypic data. Such data-sets hold great promise for the understanding of cellular mechanisms by systems biology. However, extracting functional information from data-sets, such as links between cellular processes and the functions of unknown genes, remains challenging. The limitation of HCS analysis lies in the complexity of cellular organization. Here, we assumed that cellular processes have a modular structure, and deconvolved the MP data into separate signals from different cellular modules by Blind Source Separation. We applied a combination of quantitative MP image analysis (QMPIA) and Independent Component Analysis (ICA) to an image-based HCS of endocytosis, the process whereby cells uptake molecules from the outside and distribute them to different sub-cellular organelles. We named our approach Independent Phenotypes Analysis (IPA). Phenotypic traits revealed by IPA are interpretable in terms of perturbation of specific endosomal populations (e.g. specific cargo, specific molecular markers) and of specific functional modules (early stages of endocytosis, recycling, cell cycle, etc.). The profile of perturbation of each gene in such basic phenotypic coordinates intrinsically suggest its possible mode of action.

SEEK ID: https://seek.lisym.org/publications/305

DOI: 10.1145/3365966.3365972

Projects: LiSyM Pillar I: Early Metabolic Injury (LiSyM-EMI)

Publication type: InProceedings

Journal: Proceedings of the 2019 3rd International Conference on Computational Biology and Bioinformatics - ICCBB '19

Book Title: Proceedings of the 2019 3rd International Conference on Computational Biology and Bioinformatics - ICCBB '19

Publisher: ACM Press

Citation: Proceedings of the 2019 3rd International Conference on Computational Biology and Bioinformatics - ICCBB '19,pp.69-75,ACM Press

Date Published: 2019

Registered Mode: by DOI

Authors: Unknown, Kseniia Nikitina, Sandra Segeletz, Michael Kuhn, Yannis Kalaidzidis, Marino Zerial

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Citation
Nikitina, K., Segeletz, S., Kuhn, M., Kalaidzidis, Y., & Zerial, M. (2019). Basic Phenotypes of Endocytic System Recognized by Independent Phenotypes Analysis of a High-throughput Genomic Screen. In Proceedings of the 2019 3rd International Conference on Computational Biology and Bioinformatics. ICCBB '19: 2019 3rd International Conference on Computational Biology and Bioinformatics. ACM. https://doi.org/10.1145/3365966.3365972
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Created: 23rd Jun 2021 at 08:00

Last updated: 8th Mar 2024 at 07:44

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