Literature DB >> 33253635

Persistence as an Optimal Hedging Strategy.

Alexander P Browning1, Jesse A Sharp2, Tarunendu Mapder3, Christopher M Baker4, Kevin Burrage5, Matthew J Simpson6.   

Abstract

Bacteria invest in a slow-growing subpopulation, called persisters, to ensure survival in the face of uncertainty. This hedging strategy is remarkably similar to financial hedging, where diversifying an investment portfolio protects against economic uncertainty. We provide a new, to our knowledge, theoretical foundation for understanding cellular hedging by unifying the study of biological population dynamics and the mathematics of financial risk management through optimal control theory. Motivated by the widely accepted role of volatility in the emergence of persistence, we consider several models of environmental volatility described by continuous-time stochastic processes. This allows us to study an emergent cellular hedging strategy that maximizes the expected per capita growth rate of the population. Analytical and simulation results probe the optimal persister strategy, revealing results that are consistent with experimental observations and suggest new opportunities for experimental investigation and design. Overall, we provide a new, to our knowledge, way of conceptualizing and modeling cellular decision making in volatile environments by explicitly unifying theory from mathematical biology and finance.
Copyright © 2020 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2020        PMID: 33253635      PMCID: PMC7820789          DOI: 10.1016/j.bpj.2020.11.2260

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  58 in total

1.  Modelling protection from antimicrobial agents in biofilms through the formation of persister cells.

Authors:  Mark E Roberts; Philip S Stewart
Journal:  Microbiology (Reading)       Date:  2005-01       Impact factor: 2.777

Review 2.  Bacterial persister cell formation and dormancy.

Authors:  Thomas K Wood; Stephen J Knabel; Brian W Kwan
Journal:  Appl Environ Microbiol       Date:  2013-09-13       Impact factor: 4.792

3.  Incorporating environmental stochasticity within a biological population model.

Authors:  M M Varughese; L P Fatti
Journal:  Theor Popul Biol       Date:  2008-05-27       Impact factor: 1.570

4.  Noise and low-level dynamics can coordinate multicomponent bet hedging mechanisms.

Authors:  Javier Garcia-Bernardo; Mary J Dunlop
Journal:  Biophys J       Date:  2015-01-06       Impact factor: 4.033

5.  Herpes viruses hedge their bets.

Authors:  Michael P H Stumpf; Zoe Laidlaw; Vincent A A Jansen
Journal:  Proc Natl Acad Sci U S A       Date:  2002-10-30       Impact factor: 11.205

6.  Designing combination therapies using multiple optimal controls.

Authors:  Jesse A Sharp; Alexander P Browning; Tarunendu Mapder; Christopher M Baker; Kevin Burrage; Matthew J Simpson
Journal:  J Theor Biol       Date:  2020-04-13       Impact factor: 2.691

7.  The adaptive advantage of phenotypic memory in changing environments.

Authors:  E Jablonka; B Oborny; I Molnár; E Kisdi; J Hofbauer; T Czárán
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1995-11-29       Impact factor: 6.237

8.  Experimental evolution of bet hedging.

Authors:  Hubertus J E Beaumont; Jenna Gallie; Christian Kost; Gayle C Ferguson; Paul B Rainey
Journal:  Nature       Date:  2009-11-05       Impact factor: 49.962

9.  An Experimental Framework for Quantifying Bacterial Tolerance.

Authors:  Asher Brauner; Noam Shoresh; Ofer Fridman; Nathalie Q Balaban
Journal:  Biophys J       Date:  2017-06-20       Impact factor: 4.033

10.  Fibroblasts and alectinib switch the evolutionary games played by non-small cell lung cancer.

Authors:  Artem Kaznatcheev; Jeffrey Peacock; David Basanta; Andriy Marusyk; Jacob G Scott
Journal:  Nat Ecol Evol       Date:  2019-02-18       Impact factor: 15.460

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  4 in total

1.  Identifiability analysis for stochastic differential equation models in systems biology.

Authors:  Alexander P Browning; David J Warne; Kevin Burrage; Ruth E Baker; Matthew J Simpson
Journal:  J R Soc Interface       Date:  2020-12-16       Impact factor: 4.118

2.  Identifying cell-to-cell variability in internalization using flow cytometry.

Authors:  Alexander P Browning; Niloufar Ansari; Christopher Drovandi; Angus P R Johnston; Matthew J Simpson; Adrianne L Jenner
Journal:  J R Soc Interface       Date:  2022-05-25       Impact factor: 4.293

Review 3.  Group Behavior and Emergence of Cancer Drug Resistance.

Authors:  Supriyo Bhattacharya; Atish Mohanty; Srisairam Achuthan; Sourabh Kotnala; Mohit Kumar Jolly; Prakash Kulkarni; Ravi Salgia
Journal:  Trends Cancer       Date:  2021-02-20

4.  Dynamic Boolean modelling reveals the influence of energy supply on bacterial efflux pump expression.

Authors:  Ryan Kerr; Sara Jabbari; Jessica M A Blair; Iain G Johnston
Journal:  J R Soc Interface       Date:  2022-01-26       Impact factor: 4.118

  4 in total

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