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Related Experiment Video

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Quantifying Nitric Oxide Flux Distributions.

Darshan M Sivaloganathan1, Xuanqing Wan2, Mark P Brynildsen3

  • 1Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.

Methods in Molecular Biology (Clifton, N.J.)
|January 2, 2020
PubMed
Summary

This study introduces a computational modeling approach to measure nitric oxide (NO) distribution in bacteria. This method helps understand how NO impacts bacterial biochemistry and survival during immune responses.

Keywords:
Escherichia coliMetabolic fluxNitric oxideNitric oxide dioxygenaseNitric oxide reductase

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Area of Science:

  • Biochemistry
  • Microbiology
  • Computational Biology

Background:

  • Nitric oxide (NO) is a key immune signaling molecule and a potent antimicrobial agent.
  • Understanding NO's distribution within bacterial biochemical networks is crucial for predicting cellular outcomes.
  • Direct measurement of NO fluxes is challenging due to the transient nature and low abundance of its reaction products.

Purpose of the Study:

  • To develop and present a protocol for estimating nitric oxide (NO) flux distribution in bacterial cultures.
  • To integrate experimental measurements with computational modeling for a comprehensive analysis of NO dynamics.
  • To address the challenges in measuring NO fluxes by translating readily measurable species into flux data.

Main Methods:

  • Utilized computational modeling to interpret measurements of biochemical species including NO, O2, and NO2-.
  • Developed a detailed protocol combining experimental measurements and mathematical modeling.
  • Applied the protocol to an Escherichia coli culture to estimate NO flux distribution.

Main Results:

  • Successfully translated measurements of NO, O2, and NO2- into NO flux distributions within Escherichia coli.
  • Provided a quantitative estimation of NO flux dynamics in a bacterial system.
  • Identified uncertainties associated with the estimated NO fluxes.

Conclusions:

  • The combined experimental and computational approach provides a viable method for estimating NO flux distributions in bacteria.
  • This methodology offers insights into the biochemical impact of NO on bacterial cells.
  • Further refinement of flux estimations can be achieved through iterative experimental and modeling strategies.