Selected article for: "cc NC ND International license and differential model"

Author: Brandon Alexander Holt; Gabriel A. Kwong
Title: Bacterial defiance as a form of prodrug failure
  • Document date: 2019_2_21
  • ID: 9le4s67m_4
    Snippet: To understand the mechanism by which bacteria become resistant to AMP prodrugs, we built a 15 system of coupled ordinary differential equations (ODE) that model the dynamics of the bacteriaprodrug competition. We use this model to identify a dimensionless quantitythe Bacterial Advantage Heuristic (B.A.H.)which predicts with perfect accuracy whether bacteria will become defiant under a broad range of environmental conditions. At low BAH values, ba.....
    Document: To understand the mechanism by which bacteria become resistant to AMP prodrugs, we built a 15 system of coupled ordinary differential equations (ODE) that model the dynamics of the bacteriaprodrug competition. We use this model to identify a dimensionless quantitythe Bacterial Advantage Heuristic (B.A.H.)which predicts with perfect accuracy whether bacteria will become defiant under a broad range of environmental conditions. At low BAH values, bacteria are susceptible to elimination, but beyond a critical BAH threshold, the bacteria switch to a state of 20 defiance, in which the bacteria proliferate in the presence of activated drug. To combat prodrug failure due to defiance, we design biological circuits that eliminate bacteria under all conditions (BAH values) by recognizing that AMP prodrugs behave analogously to transistors: above a critical BAH threshold (i.e., gate voltage), bacteria (i.e., input current) pass through the prodrug and exhibit defiance. We use this framework to build logic gates with prodrug transistors, which 25 . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/556951 doi: bioRxiv preprint we use to construct a multi-prodrug circuit that outputs 0 (i.e., dead bacteria) under all eight combinations of three input BAH values. These quantitative mechanistic insights will inform future drug design and treatment protocols to combat antibiotic resistance.

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