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Comparative transcriptomics and metabolomics in a rhesus macaque drug administration study.

Kevin J Lee1, Weiwei Yin2, Dalia Arafat1

  • 1Center for Integrative Genomics, School of Biology, Georgia Institute of Technology Atlanta, GA, USA.

Frontiers in Cell and Developmental Biology
|December 3, 2014
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Summary

This study used multi-omic approaches to investigate pyrimethamine

Keywords:
axes of variationbayesian network inferencebone marrowperipheral bloodprincipal component analysis (PCA)pyrimethamine

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Area of Science:

  • Immunology
  • Pharmacology
  • Systems Biology
  • Genomics
  • Metabolomics

Background:

  • The anti-malarial drug pyrimethamine is known to affect immune cell division and metabolism.
  • Understanding its precise impact on immune physiology requires comprehensive analysis of molecular changes.
  • Rhesus macaques serve as a valuable model for studying human immune responses.

Purpose of the Study:

  • To investigate the effects of pyrimethamine on immune physiology in rhesus macaques using a multi-omic approach.
  • To analyze changes in whole blood and bone marrow transcriptomes, and plasma metabolomes following drug administration.
  • To explore the influence of statistical modeling strategies on biological inference in multi-omic data.

Main Methods:

  • Generated whole blood and bone marrow RNA-Seq and plasma metabolome profiles for five rhesus macaques.
  • Collected data across multiple timepoints before, during, and after three rounds of pyrimethamine administration.
  • Employed linear modeling and Bayesian network analyses, considering individual variation and statistical modeling impacts.

Main Results:

  • Individual macaques represented a significant source of variance in both transcriptomic and metabolomic data.
  • Incorporating individual variation into modeling enhanced the detection of temporal effects.
  • Pyrimethamine administration impacted both blood and bone marrow compartments, but with limited perturbation of transcript or metabolite abundance.

Conclusions:

  • Pyrimethamine exerts subtle but detectable effects on immune system compartments.
  • The study provides new insights into the drug's mode of action, potentially involving suppression of cell division and metabolism.
  • Multi-omic approaches combined with robust statistical modeling are crucial for understanding drug-induced immune responses.