Persistence as an Optimal Hedging Strategy
Tài liệu tham khảo
Bigger, 1944, Treatment of staphylococcal infections with penicillin by intermittent sterilisation, Lancet, 244, 497, 10.1016/S0140-6736(00)74210-3
Veening, 2008, Bistability, epigenetics, and bet-hedging in bacteria, Annu. Rev. Microbiol, 62, 193, 10.1146/annurev.micro.62.081307.163002
Merton, 1971, Optimum consumption and portfolio rules in a continuous-time model, J. Econ. Theory, 3, 373, 10.1016/0022-0531(71)90038-X
Wolf, 2005, Diversity in times of adversity: probabilistic strategies in microbial survival games, J. Theor. Biol, 234, 227, 10.1016/j.jtbi.2004.11.020
Williams, 2011, Paradoxical persistence through mixed-system dynamics: towards a unified perspective of reversal behaviours in evolutionary ecology, Proc. Biol. Sci, 278, 1281
Jia, 2014, Modeling stochastic phenotype switching and bet-hedging in bacteria: stochastic nonlinear dynamics and critical state identification, Quant. Biol, 2, 110, 10.1007/s40484-014-0035-5
Nichol, 2016, Stochasticity in the genotype-phenotype map: implications for the robustness and persistence of bet-hedging, Genetics, 204, 1523, 10.1534/genetics.116.193474
Ardaševa, 2020, Evolutionary dynamics of competing phenotype-structured populations in periodically fluctuating environments, J. Math. Biol, 80, 775, 10.1007/s00285-019-01441-5
Villa Martín, 2019, Bet-hedging strategies in expanding populations, PLoS Comput. Biol, 15, e1006529, 10.1371/journal.pcbi.1006529
Balaban, 2004, Bacterial persistence as a phenotypic switch, Science, 305, 1622, 10.1126/science.1099390
Wood, 2013, Bacterial persister cell formation and dormancy, Appl. Environ. Microbiol, 79, 7116, 10.1128/AEM.02636-13
Brauner, 2017, An experimental framework for quantifying bacterial tolerance, Biophys. J, 112, 2664, 10.1016/j.bpj.2017.05.014
Şimşek, 2019, Power-law tail in lag time distribution underlies bacterial persistence, Proc. Natl. Acad. Sci. USA, 116, 17635, 10.1073/pnas.1903836116
Barrett, 2019, Enhanced antibiotic resistance development from fluoroquinolone persisters after a single exposure to antibiotic, Nat. Commun, 10, 1177, 10.1038/s41467-019-09058-4
Van den Bergh, 2016, Frequency of antibiotic application drives rapid evolutionary adaptation of Escherichia coli persistence, Nat. Microbiol, 1, 16020, 10.1038/nmicrobiol.2016.20
Bartell, 2019, Evolutionary highways to persistent bacterial infection, Nat. Commun, 10, 629, 10.1038/s41467-019-08504-7
Fauvart, 2011, Role of persister cells in chronic infections: clinical relevance and perspectives on anti-persister therapies, J. Med. Microbiol, 60, 699, 10.1099/jmm.0.030932-0
Windels, 2019, Bacterial persistence promotes the evolution of antibiotic resistance by increasing survival and mutation rates, ISME J, 13, 1239, 10.1038/s41396-019-0344-9
Amato, 2013, Metabolic control of persister formation in Escherichia coli, Mol. Cell, 50, 475, 10.1016/j.molcel.2013.04.002
Harms, 2016, Mechanisms of bacterial persistence during stress and antibiotic exposure, Science, 354, aaf4268, 10.1126/science.aaf4268
Moyed, 1983, hipA, a newly recognized gene of Escherichia coli K-12 that affects frequency of persistence after inhibition of murein synthesis, J. Bacteriol, 155, 768, 10.1128/jb.155.2.768-775.1983
Kussell, 2005, Bacterial persistence: a model of survival in changing environments, Genetics, 169, 1807, 10.1534/genetics.104.035352
Alonso, 2014, Modeling bacterial population growth from stochastic single-cell dynamics, Appl. Environ. Microbiol, 80, 5241, 10.1128/AEM.01423-14
Rivoire, 2011, The value of information for populations in varying environments, J. Stat. Phys, 142, 1124, 10.1007/s10955-011-0166-2
Øksendal, 1998
Turelli, 1977, Random environments and stochastic calculus, Theor. Popul. Biol, 12, 140, 10.1016/0040-5809(77)90040-5
Merton, 1976, Option pricing when underlying stock returns are discontinuous, J. Financ. Econ, 3, 125, 10.1016/0304-405X(76)90022-2
Merton, 1973, Theory of rational option pricing, Bell J. Econ, 4, 141, 10.2307/3003143
Black, 1973, The pricing of options and corporate liabilities, J. Polit. Econ, 81, 637, 10.1086/260062
Gaál, 2010, Exact results for the evolution of stochastic switching in variable asymmetric environments, Genetics, 184, 1113, 10.1534/genetics.109.113431
Müller, 2013, Bet-hedging in stochastically switching environments, J. Theor. Biol, 336, 144, 10.1016/j.jtbi.2013.07.017
Hanson, 2007
Hidalgo, 2015, Stochasticity enhances the gaining of bet-hedging strategies in contact-process-like dynamics, Phys. Rev. E Stat. Nonlin. Soft Matter Phys, 91, 032114, 10.1103/PhysRevE.91.032114
Garcia-Bernardo, 2015, Noise and low-level dynamics can coordinate multicomponent bet hedging mechanisms, Biophys. J, 108, 184, 10.1016/j.bpj.2014.11.048
Varughese, 2008, Incorporating environmental stochasticity within a biological population model, Theor. Popul. Biol, 74, 115, 10.1016/j.tpb.2008.05.004
Wong, 1965, On the convergence of ordinary integrals to stochastic integrals, Ann. Math. Stat, 36, 1560, 10.1214/aoms/1177699916
Thattai, 2004, Stochastic gene expression in fluctuating environments, Genetics, 167, 523, 10.1534/genetics.167.1.523
Acar, 2008, Stochastic switching as a survival strategy in fluctuating environments, Nat. Genet, 40, 471, 10.1038/ng.110
Maisonneuve, 2014, Molecular mechanisms underlying bacterial persisters, Cell, 157, 539, 10.1016/j.cell.2014.02.050
Feng, 2014, Growth feedback as a basis for persister bistability, Proc. Natl. Acad. Sci. USA, 111, 544, 10.1073/pnas.1320396110
Pai, 2009, Optimal tuning of bacterial sensing potential, Mol. Syst. Biol, 5, 286, 10.1038/msb.2009.43
Ghosh, 2018, Contact-dependent growth inhibition induces high levels of antibiotic-tolerant persister cells in clonal bacterial populations, EMBO J, 37, e98026, 10.15252/embj.201798026
Xue, 2017, Bet hedging against demographic fluctuations, Phys. Rev. Lett, 119, 108103, 10.1103/PhysRevLett.119.108103
Roberts, 2005, Modelling protection from antimicrobial agents in biofilms through the formation of persister cells, Microbiology (Reading), 151, 75, 10.1099/mic.0.27385-0
Cogan, 2006, Effects of persister formation on bacterial response to dosing, J. Theor. Biol, 238, 694, 10.1016/j.jtbi.2005.06.017
Carvalho, 2018, How do environment-dependent switching rates between susceptible and persister cells affect the dynamics of biofilms faced with antibiotics?, NPJ Biofilms Microbiomes, 4, 6, 10.1038/s41522-018-0049-2
Jablonka, 1995, The adaptive advantage of phenotypic memory in changing environments, Philos. Trans. R. Soc. Lond. B Biol. Sci, 350, 133, 10.1098/rstb.1995.0147
Tourigny, 2020, Dynamic metabolic resource allocation based on the maximum entropy principle, J. Math. Biol, 80, 2395, 10.1007/s00285-020-01499-6
Bellman, 1954, Dynamic programming and a new formalism in the calculus of variations, Proc. Natl. Acad. Sci. USA, 40, 231, 10.1073/pnas.40.4.231
Kirk, 2004
Kushner, 2001
Higham, 2001, An algorithmic introduction to numerical simulation of stochastic differential equations, SIAM Rev, 43, 525, 10.1137/S0036144500378302
Sharp, 2019, Optimal control of acute myeloid leukaemia, J. Theor. Biol, 470, 30, 10.1016/j.jtbi.2019.03.006
Maltas, 2019, Pervasive and diverse collateral sensitivity profiles inform optimal strategies to limit antibiotic resistance, PLoS Biol, 17, e3000515, 10.1371/journal.pbio.3000515
Nichol, 2019, Antibiotic collateral sensitivity is contingent on the repeatability of evolution, Nat. Commun, 10, 334, 10.1038/s41467-018-08098-6
de Jong, 2011, Bet hedging or not? A guide to proper classification of microbial survival strategies, BioEssays, 33, 215, 10.1002/bies.201000127
Rotem, 2010, Regulation of phenotypic variability by a threshold-based mechanism underlies bacterial persistence, Proc. Natl. Acad. Sci. USA, 107, 12541, 10.1073/pnas.1004333107
Cogan, 2012, Optimal control strategies for disinfection of bacterial populations with persister and susceptible dynamics, Antimicrob. Agents Chemother, 56, 4816, 10.1128/AAC.00675-12
Sharp, 2020, Designing combination therapies using multiple optimal controls, J. Theor. Biol, 497, 110277, 10.1016/j.jtbi.2020.110277
Iram, 2020, Controlling the speed and trajectory of evolution with counterdiabatic driving, Nat. Phys
Nichol, 2015, Steering evolution with sequential therapy to prevent the emergence of bacterial antibiotic resistance, PLoS Comput. Biol, 11, e1004493, 10.1371/journal.pcbi.1004493
Gefen, 2008, Single-cell protein induction dynamics reveals a period of vulnerability to antibiotics in persister bacteria, Proc. Natl. Acad. Sci. USA, 105, 6145, 10.1073/pnas.0711712105
Emerenini, 2015, A mathematical model of quorum sensing induced biofilm detachment, PLoS One, 10, e0132385, 10.1371/journal.pone.0132385
Perkins, 2009, Strategies for cellular decision-making, Mol. Syst. Biol, 5, 326, 10.1038/msb.2009.83
Beaumont, 2009, Experimental evolution of bet hedging, Nature, 462, 90, 10.1038/nature08504
Rodriguez-Beltran, 2018, Multicopy plasmids allow bacteria to escape from fitness trade-offs during evolutionary innovation, Nat. Ecol. Evol, 2, 873, 10.1038/s41559-018-0529-z
Boettiger, 2016, Optimal management of a stochastically varying population when policy adjustment is costly, Ecol. Appl, 26, 808, 10.1890/15-0236
Haass, 2014, Real-time cell cycle imaging during melanoma growth, invasion, and drug response, Pigment Cell Melanoma Res, 27, 764, 10.1111/pcmr.12274
Kaznatcheev, 2019, Fibroblasts and alectinib switch the evolutionary games played by non-small cell lung cancer, Nat. Ecol. Evol, 3, 450, 10.1038/s41559-018-0768-z
Stumpf, 2002, Herpes viruses hedge their bets, Proc. Natl. Acad. Sci. USA, 99, 15234, 10.1073/pnas.232546899
Rouzine, 2015, An evolutionary role for HIV latency in enhancing viral transmission, Cell, 160, 1002, 10.1016/j.cell.2015.02.017
Lu, 2013, MicroRNA-based regulation of epithelial-hybrid-mesenchymal fate determination, Proc. Natl. Acad. Sci. USA, 110, 18144, 10.1073/pnas.1318192110