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Processes in DNA damage response from a whole-cell multi-omics perspective.

James C Pino1,2,3, Alexander L R Lubbock2,4, Leonard A Harris5,6,7

  • 1Chemical and Physical Biology Graduate Program, Vanderbilt University, Nashville, TN, USA.

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|November 7, 2022
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Summary
This summary is machine-generated.

We developed a new framework, MAGINE, to analyze complex multi-omics data from cellular responses to drugs. This tool helps reveal detailed molecular mechanisms of drug action, like DNA damage and cell death, over time.

Keywords:
BioinformaticsComplex system biologyData processing in systems biologySystems biology

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Pharmacology

Background:

  • Collecting multi-condition, multi-omic time-course data of cellular responses to perturbations is now feasible.
  • However, the complexity of these datasets presents significant challenges in data management, analysis, visualization, and interpretation, hindering scientific discovery.

Purpose of the Study:

  • To develop and demonstrate an interactive analysis framework for multi-omics data to enable whole-cell mechanistic analysis of cellular responses.
  • Specifically, to analyze the temporal progression of DNA damage and programmed cell death in HL-60 cells treated with bendamustine.

Main Methods:

  • Integration of enrichment and network analysis techniques.
  • Development of the Mechanism of Action Generator Involving Network analysis (MAGINE) framework to automate network construction and enrichment analysis.
  • Utilizing an annotated gene-set network to combine network-based and ontology-driven analysis.

Main Results:

  • The study successfully applied the MAGINE framework to analyze HL-60 cellular response to bendamustine.
  • Detailed progression of DNA damage and programmed cell death was elucidated at molecular, pathway, and process levels over time.
  • The analysis revealed multi-pathway involvement, extending beyond the canonical mechanism of bendamustine.

Conclusions:

  • Multi-omics data integration, facilitated by frameworks like MAGINE, is crucial for exploring cellular signaling processes at various resolutions.
  • The developed framework automates complex analyses, making multi-omics data more accessible for mechanistic insights.
  • This approach provides a comprehensive understanding of drug mechanisms and identifies novel pathways involved in cellular responses.