New Tools for Comparative Systems Biology of Threat Agent Action Mechanisms

Abstract

This project aims to develop novel methodologies and technologies for the rapid identification of the mechanism of action (MoA) for emerging chemical and biological threat agents. Our approach integrates systems biology tools to detect and identify differential component levels in the cellular transcriptome, proteome and metabolome following exposure to a threat agent. Knowledge-based network inference and mathematical Bayesian network inference models are utilized to interpret the changes measured by the multi-omics experiments to construct the MoA of the challenge agent. Confirmatory assays are utilized to validate the MoA. The aims of Technical Area 1 are to detect cellular biomolecules within a mass range of 50 to 200,000 Da. In the Base Period, and Option Periods 1, 2, and 3, the objectives are to detect proteins present between 50 and 3107 copies per cell, and other molecules (transcripts and metabolites) present between 4103 and 41010 molecules per cell. Cells are treated with the challenge agent and sampled at several time-points between 2 s and 48 h, followed by transcriptomics, proteomics, and metabolomics analyses. The untargeted detection of proteins and metabolites is to be performed using liquid chromatography and mass spectrometry. The goals of Technical Area 2 are to identify components and events. During the base period, the objective of Technical Area 2 is to identify components and events from minutes to days within whole cells and the cytoplasm compartment. In Option Period 1, the aim is to identify components and events in the time range from seconds to days from whole cells and from the cytoplasm compartment. In Option Period 2, the aim is to identify components and events in the time range from seconds to days from whole cells, and from the cytoplasm and nuclear compartments.

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Document Details

Document Type
Technical Report
Publication Date
Oct 12, 2019
Accession Number
AD1110934

Entities

People

  • Ákos Vértes

Organizations

  • George Washington University

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Bayesian Networks
  • Bioassay
  • Cell Physiological Processes
  • Chemical Synthesis
  • Chemistry
  • Computational Biology
  • Computational Science
  • Databases
  • Information Science
  • Mass Spectrometry
  • Medical Personnel
  • Metabolomics
  • Molecular Biology
  • Proteins
  • Proteomics
  • Small Molecules
  • Systems Biology

Readers

  • Critical Infrastructure Protection in CBRN and WMD Threats.
  • Molecular and Cellular Biology
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML
  • Biotechnology