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Curr Opin Microbiol. Author manuscript; available in PMC 2012 October 1.
Published in final edited form as:
PMCID: PMC3196368

Heterogeneous Bacterial Persisters and Engineering Approaches to Eliminate them


Bacterial persistence is state in which a sub-population of cells (persisters) survives antibiotic treatment, and has been implicated in the tolerance of clinical infections and the recalcitrance of biofilms. There has been a renewed interest in the role of bacterial persisters in treatment failure in light of a wealth of recent findings. Here we review recent laboratory studies of bacterial persistence. Further, we pose the hypothesis that each bacterial population may contain a diverse collection of persisters and discuss engineering strategies for persister eradication.


Bacterial persistence is a phenomenon in which a sub-population of cells survives antibiotic treatment [1•, 2•, 37]. In contrast to resistant bacteria, persisters do not grow in the presence of antibiotics and their tolerance arises from physiological processes rather than genetic mutations in a sub-population of bacteria. Persistence was first described by Joseph Bigger in 1944 [8] while attempting to sterilize cultures of pathogenic Staphylococcus aureus with penicillin. He found that a small number of cells “persisted” and could later form colonies even after treatment with high antibiotic concentrations.

The possible clinical implications of persisters were apparent: antibiotics might not sterilize infections and remaining bacteria could later cause recurrence once treatment ended [9••]. Early clinical studies of in vivo persistence in S. aureus, S. pneumoniae, and M. tuberculosis demonstrated that the phenotype was indeed an important and distinct problem in the treatment of infections [9••,10••]. Driven by an abundance of recent laboratory findings [1124], there is renewed interest in clinical persistence [25,26••], which has led to the demonstration that high-persistent mutants can arise during treatment of chronic infections [26••]. Here, we review some of the recent laboratory studies of bacterial persistence in E. coli [1•, 2•, 3] and propose that persistence might be explained by variance in the many processes governing stress responses and antibiotic lethality, suggesting that a single population of bacteria contains a collection of distinct persisters.

hipA and the dawn of persister genetics

The first paper in persister genetics was published in 1983 by Moyed and Bertrand, who presented the results of a mutagenesis-and-selection scheme designed to create mutants with high persistence to penicillin [27]. After 24 independent attempts, they created four high-persistence strains, two of which were found to have mutations in the same gene, named hipA (for “high persistence”). 1% of the hipA mutant cells persisted treatment with multiple antibiotics targeting peptidoglycan synthesis [28], representing a 100-fold increase over wild-type persistence. Rather than being resistant, an isogenic population of hipA mutants instead had a higher frequency of persisters. Noting that antibiotics that inhibit peptidoglycan synthesis are most lethal immediately following a round of DNA replication, the authors hypothesized that the mutant hipA arrests the cell cycle prior to entry into this susceptible phase. Studies have indicated that both the native hipA [29] and mutant hipA [30], which is considered a gain-of-function mutation [29,31], appear to target peptidoglycan synthesis, and that such inhibition may explain persistence [32,33]. However, though native hipA expressed heterologously can induce persistence under multiple conditions, the chromosomal hipA only appears to play a role in persistence in stationary phase [22,29], which raises the question of the importance of hipA in persistence generally.

Recent studies add to the early physiological research by suggesting that hipA is a kinase that inhibits translation by phosphorylating the EF-Tu elongation factor. Experiments showed incorporation of radio-labeled ATP into hipA when the two were incubated together, an effect abolished by mutations to specific residues in a predicted binding pocket, suggesting that hipA has the capability of autophosphorylation [34]. Later studies suggested that hipA interacts with and phosphorylates translation elongation factor EF-Tu [35], and two separate crystallography studies suggest that hipA possesses a novel phosphorylation mechanism [35,36]. This phosphorylation event was posed as a possible mechanism for hipA-induced persistence in which hipA phosphorylates EF-Tu, leading to translational inhibition and subsequent tolerance to antibiotics. Whether this is the mechanism for the high persistence of mutant hipA is an open question, and further work testing this hypothesis is required as translational inhibition alone does not induce ampicillin persistence [31] and hipA has not been implicated in tolerance to aminoglycosides [27]. Connecting these recent biochemical insights to the physiological responses elicited by the native and mutant hipA will be critical to understanding the role of this protein in bacterial persistence.

Since the description of the hipA mutation, hipA has become the persister gene of choice and has been studied extensively [22,27,2931,3439], playing an important role as a model system for the study of bacterial persistence [1113,40,41]. Though hipA launched the field of persister genetics, numerous other genes and processes have since been found to contribute to bacterial persistence, as we discuss below.

More than one way to make a persister

There have been many laboratory studies on persistence in the last decade, many of which have uncovered previously unrecognized conditions and processes contributing to the phenotype. Here, we focus on three of these: heterogeneous growth, nutrient limitation, and the SOS response.

Heterogeneous growth

Heterogeneity in growth rates has been shown to play a role in bacterial persistence [11,13,20]. Studies have demonstrated that non-growing and dormant cells are more likely to persist antibiotic treatment than actively growing cells. Evidently, the growth rate of E. coli fits a bimodal distribution, in which two distinct populations, growing and non-growing, coexist in the same culture [20]. Cell-sorting experiments showed that dormancy of the non-growing population correlates with persistence as dormant populations have 20 times more persisters than normally growing populations. This additionally suggests that dormancy does not entirely explain persistence as many dormant cells are not persisters and many persisters are not dormant.

Interestingly, the dormant cells in one of these studies appear to be narrower than normally growing cells, suggesting that stationary-phase cellular dwarfing [42], bacterial self-digestion, may play a role in persistence. These dormant cells may be stationary-phase remnants that have yet to wake up rather than population variants that chose to cease growing, and it would be interesting to examine whether serial passage of a culture eliminates this population [21].

Nutrient limitation

Under laboratory conditions, the environment and physiology of bacteria change considerably once they have exhausted the majority of nutrients, a situation referred to as stationary phase [42]. It has been shown that persisters predominantly form as cultures approach and enter stationary phase [11,21] and they are lost from cultures which have been serially passed through rich media conditions to promote early exponential-phase growth [21]. These data suggest that persisters examined in rapidly growing populations may be relics of the overnight culture used for culture inoculation, though this clearly does not account for persisters that arise from induction of processes such as hipA over-expression or the SOS response (discussed below).

A recent study highlights the importance of stationary phase in bacterial persistence by demonstrating that the age of inocula has a dramatic effect on persister levels [43•]. This work suggests that the differences in persistence observed upon perturbing certain genes can be explained by the amount of time spent in stationary phase prior to inoculation, indicating that these genes may not be important contributors to persistence. The age of the bacterial inoculum is rarely controlled for in persister methods, and this study strongly suggests that it should be.

SOS response

The SOS response, a major stress response system in bacteria which is induced by DNA damage [44], has recently been implicated in persistence [23,24,45]. Strains in which the SOS response cannot be activated have decreased persistence to DNA-damaging quinolone antibiotics. It was further shown that induction of the SOS response by sub-inhibitory levels of mitomycin C increased persistence [23,45], demonstrating that bacteria can adjust their tolerance to antibiotics by sensing and responding to stressful environmental conditions. The antibiotic concentration dynamics appear to be critical for SOS-induced persistence as only 1% of those that survive treatment with high antibiotic concentrations had induced the SOS response. This work implies that persistence is in some cases inducible, which adds to models of persistence as a random switching event [11].

Persisters and physiological heterogeneity

The diversity of the pathways implicated in bacterial persistence suggests that, in addition to there being more than one way to make a persister, there may be different types of persisters. This raises the possibility that each persister has its own specific tolerances to antibiotics.

Total dormancy of a subpopulation is an attractive model for persistence as it simplifies the phenotype and suggests a possible unified theory of persistence. However, this model does not fit the growing body of experimental findings demonstrating diversity in both the tolerance to different antibiotics and the genes that contribute to persistence. This diversity suggests that the processes involved in stress responses and those required for antibiotic lethality are not simultaneously controlled within individual cells as part of a physiological program leading to a persistent state. As a result, the persistent sub-population may not be uniformly distinct, physiologically speaking, from the susceptible population.

An alternative model is that each population contains a diversity of persisters based on fluctuations and variability in cellular processes (Figure 1). This diversity hypothesis suggests that persistence may be a result of multiple distinct cellular physiologies within a population. The apparent population split between tolerant and persistent cells when treated with antibiotic would then be masking an abundance of different mechanisms and associated phenotypes by which cells evade antibiotic lethality. Given the potential variance in cellular processes [46•, 4749], it seems plausible that persistence could result from stochastic fluctuations in lethality-governing processes. Whether persister states explored through fluctuations can be stabilized by epigenetic DNA modifications, which play an important role in other heterogeneous phenotypes [50], remains an open question. This hypothesis suggests that each bacterial culture contains a collection of distinct persister subpopulations, each with its own unique tolerance mechanisms. The study of such persistent heterogeneity is beyond many current experimental methods and will benefit greatly from increased investigation of single cells [5153].

Figure 1
A plurality of persisters

Following this reasoning, experimentally-determined persisters levels are the result of the distributions of stress-response and lethality-governing processes, which suggests that environmental conditions and genetic perturbations affecting these processes alter persistence. Experiments which perturb “persister genes” impact related processes and tune the distributions of processes governing antibiotic tolerance. Given the role of stochastic fluctuations in large populations studied in the lab, persistence may be a statistical certainty, regardless of the exact persister level, the antibiotic used, or the particular tolerance mechanisms present. As a result, a model of bacterial persistence as a unified and distinct state may be impossible. Though persisters may currently be beyond comprehensive mechanistic study, attempts to eliminate persisters may not require full attention to the complicated set of processes leading to persistence.

Engineering treatments for persisters

The clinical importance of developing anti-persister strategies is self-evident, though there have been few attempts to target the elimination of persisters. It has been suggested that drugs and methods could be developed to target the genetic determinants leading to persister formation so as to prevent or reverse persistence [2]. Given the number of genes involved in persistence, such an approach may prove difficult. Toward development of treatments for a diversity of persisters, it may be advantageous to focus instead on the mechanistic aspects of bactericidal antibiotics. Regardless of how they form, persisters must tune certain processes, such as peptidoglycan synthesis in the case of hipA-associated persisters, in order to avoid the lethal effects of antibiotics. Many of these processes are known and have been characterized for commonly-used, bactericidal antibiotics [54•]. The distributions of these processes can be tuned by external stimuli, an approach that could be aided by single-cell based methods such as fluorescently-activated cells sorting. Tuning these processes would alter the distribution of susceptibility in a population, thereby rendering persisters vulnerable to the antibiotics that target such processes (Figure 2). Though easier said than done, we have recently demonstrated the success of such an approach.

Figure 2
Tuning tolerance-associated processes

As protein translation occurs in persisters [12], we reasoned that persisters should be susceptible to aminoglycoside antibiotics, which are ribosome-targeting, bactericidal antibiotics [55,56]. Persisters are however not susceptible to aminoglycosides [18,22], and we suspected that this could be due to decreased proton-motive force (PMF), as it is well established that PMF is required for aminoglycoside uptake [57•]. Through specific metabolic stimuli (e.g., mannitol, fructose), we induced PMF in persisters, thereby enabling aminoglycoside uptake and killing [58•]. This approach specifically induced processes necessary for aminoglycoside killing as the metabolic stimuli did not facilitate persister killing by quinolones or β-lactams. Not only was this approach successful in laboratory cultures, but it was also effective at eliminating E. coli and S. aureus biofilms and improving treatment in a mouse chronic, urinary-tract-infection model. Hence, through mechanistic understanding of aminoglycoside lethality and by tuning persister physiology, we were able to engineer a clinically-viable treatment for eradicating persisters.

Given the wealth of knowledge on how bactericidal antibiotics kill bacteria, it should be possible to develop a variety of similar mechanism-based approaches for treating persisters. Future anti-persister strategies could be engineered by utilizing methods promoting peptidoglycan synthesis or autolysin activity for the β-lactams [5961], by harnessing methods promoting DNA replication or inhibiting SOS response for the quinolones [62], or by employing methods inducing reactive oxygen species (ROS) or inhibiting ROS-protective genes for all bactericidal antibiotics [6365]. These methods might utilize external metabolic and chemical stimuli or engineered bacteriophage [66] to evoke the needed physiological responses. Additionally, incorporation of mechanistic knowledge of antibiotic lethality in bacterial persistence may shed light on the tolerance of quiescent cancer cells to chemotherapeutic agents [6769].


Studies over the past decade have implicated a multiplicity of processes contributing to bacterial persistence. Given the physiological complexity of each bacterial cell, it seems plausible that persistence may be the result of fluctuations and variance in different tolerance-associated processes. This suggests, that in a single bacterial population, there may be many different types of persisters, each with distinct mechanisms for evading the lethal effects of bactericidal antibiotics. Advances in sequencing and single-cell technologies will help test this hypothesis and aid standard techniques in the elucidation of persister physiology. This hypothesis further suggests the importance of incorporating mechanistic understanding of antibiotic modes of action into models of persistence. The wealth of available knowledge and insights into the action of antibiotics could be utilized to develop clinically viable, mechanism-based methods for eradicating persisters.


  • -
    Review of current laboratory research on persisters, including the roles of growth heterogeneity, stationary phase, and the SOS-response
  • -
    History and phenotypes associated with hipA
  • -
    Hypothesis that each bacterial population contains many different persisters with different tolerance mechanisms
  • -
    Engineering strategies for eradicating bacterial persisters


We thank Daniel J. Dwyer and D. Ewen Cameron for helpful suggestions on the manuscript. This work was supported by the NIH Director's Pioneer Award Program and the Howard Hughes Medical Institute.


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1. Gefen O, Balaban NQ. The importance of being persistent: Heterogeneity of bacterial populations under antibiotic stress. FEMS Microbiol Rev. 2009;33(4):704–717. [PubMed]
2. Lewis K. Persister cells. Annu Rev Microbiol. 2010;64:357–372. [PubMed] These are both excellent recent reviews on bacterial persistence and the current state of the field.
3. Lewis K. Persister cells, dormancy and infectious disease. Nat Rev Microbiol. 2007;5(1):48–56. [PubMed]
4. Levin BR, Rozen DE. Non-inherited antibiotic resistance. Nat Rev Microbiol. 2006;4(7):556–562. [PubMed]
5. Smith PA, Romesberg FE. Combating bacteria and drug resistance by inhibiting mechanisms of persistence and adaptation. Nat Chem Biol. 2007;3(9):549–556. [PubMed]
6. Jayaraman R. Bacterial persistence: Some new insights into an old phenomenon. J Biosci. 2008;33(5):795–805. [PubMed]
7. Dhar N, McKinney JD. Microbial phenotypic heterogeneity and antibiotic tolerance. Curr Opin Microbiol. 2007;10(1):30–38. [PubMed]
8. Bigger JW. The bactericidal action of penicillin on Staphylococcus pyogenes. The Irish Journal of Medical Science. 1944;6(228)
9. McDermott W. Microbial persistence. Yale J Biol Med. 1958;30(4):257–291. [PMC free article] [PubMed]
10. McDermott W. Inapparent infection: Relation of latent and dormant infections to microbial persistence. Public Health Rep. 1959;74(6):485–499. [PubMed] These are two excellent papers for those interested in the pre-genetic history of bacterial persisters.
11. Balaban NQ, Merrin J, Chait R, Kowalik L, Leibler S. Bacterial persistence as a phenotypic switch. Science. 2004;305(5690):1622–1625. [PubMed]
12. Gefen O, Gabay C, Mumcuoglu M, Engel G, Balaban NQ. Single-cell protein induction dynamics reveals a period of vulnerability to antibiotics in persister bacteria. Proc Natl Acad Sci U S A. 2008;105(16):6145–6149. [PubMed]
13. Rotem E, Loinger A, Ronin I, Levin-Reisman I, Gabay C, Shoresh N, Biham O, Balaban NQ. Regulation of phenotypic variability by a threshold-based mechanism underlies bacterial persistence. Proc Natl Acad Sci U S A. 2010;107(28):12541–12546. [PubMed]
14. Wang X, Wood TK. Toxin-antitoxin systems influence biofilm and persister cell formation and the general stress response. Appl Environ Microbiol. 2011;77(16):5577–5583. [PMC free article] [PubMed]
15. Brown BL, Wood TK, Peti W, Page R. Structure of the Escherichia coli antitoxin mqsA (ygiT/b3021) bound to its gene promoter reveals extensive domain rearrangements and the specificity of transcriptional regulation. J Biol Chem. 2011;286(3):2285–2296. [PubMed]
16. Kim Y, Wang X, Zhang XS, Grigoriu S, Page R, Peti W, Wood TK. Escherichia coli toxin/antitoxin pair mqsR/mqsA regulate toxin cspD. Environ Microbiol. 2010;12(5):1105–1121. [PubMed]
17. Brown BL, Grigoriu S, Kim Y, Arruda JM, Davenport A, Wood TK, Peti W, Page R. Three dimensional structure of the mqsR:mqsA complex: A novel TA pair comprised of a toxin homologous to rele and an antitoxin with unique properties. PLoS Pathog. 2009;5(12):e1000706. [PMC free article] [PubMed]
18. Spoering AL, Lewis K. Biofilms and planktonic cells of Pseudomonas aeruginosa have similar resistance to killing by antimicrobials. J Bacteriol. 2001;183(23):6746–6751. [PMC free article] [PubMed]
19. Spoering AL, Vulic M, Lewis K. GlpD and plsB participate in persister cell formation in Escherichia coli. J Bacteriol. 2006;188(14):5136–5144. [PMC free article] [PubMed]
20. Shah D, Zhang Z, Khodursky A, Kaldalu N, Kurg K, Lewis K. Persisters: A distinct physiological state of E. coli. BMC Microbiol. 2006;6:53. [PMC free article] [PubMed]
21. Keren I, Kaldalu N, Spoering A, Wang Y, Lewis K. Persister cells and tolerance to antimicrobials. FEMS Microbiol Lett. 2004;230(1):13–18. [PubMed]
22. Keren I, Shah D, Spoering A, Kaldalu N, Lewis K. Specialized persister cells and the mechanism of multidrug tolerance in Escherichia coli. J Bacteriol. 2004;186(24):8172–8180. [PMC free article] [PubMed]
23. Dorr T, Lewis K, Vulic M. SOS response induces persistence to fluoroquinolones in Escherichia coli. PLoS Genet. 2009;5(12):e1000760. [PMC free article] [PubMed]
24. Dorr T, Vulic M, Lewis K. Ciprofloxacin causes persister formation by inducing the tisB toxin in Escherichia coli. PLoS Biol. 2010;8(2):e1000317. [PMC free article] [PubMed]
25. Lafleur MD, Qi Q, Lewis K. Patients with long-term oral carriage harbor high-persister mutants of Candida albicans. Antimicrob Agents Chemother. 2010;54(1):39–44. [PMC free article] [PubMed]
26. Mulcahy LR, Burns JL, Lory S, Lewis K. Emergence of Pseudomonas aeruginosa strains producing high levels of persister cells in patients with cystic fibrosis. J Bacteriol. 2010;192(23):6191–6199. [PubMed] This paper demonstrates, by tracking isolates from individuals with cystic fibrosis, that high-persistence P. aeruginosa can develop over time, thereby suggesting a role for persistence in P. aeruginosa treatment failure.
27. Moyed HS, Bertrand KP. HipA, a newly recognized gene of Escherichia coli K-12 that affects frequency of persistence after inhibition of murein synthesis. J Bacteriol. 1983;155(2):768–775. [PMC free article] [PubMed]
28. Holtje JV. Growth of the stress-bearing and shape-maintaining murein sacculus of Escherichia coli. Microbiol Mol Biol Rev. 1998;62(1):181–203. [PMC free article] [PubMed]
29. Korch SB, Henderson TA, Hill TM. Characterization of the hipA7 allele of Escherichia coli and evidence that high persistence is governed by (p)ppGpp synthesis. Mol Microbiol. 2003;50(4):1199–1213. [PubMed]
30. Scherrer R, Moyed HS. Conditional impairment of cell division and altered lethality in hipA mutants of Escherichia coli K-12. J Bacteriol. 1988;170(8):3321–3326. [PMC free article] [PubMed]
31. Korch SB, Hill TM. Ectopic overexpression of wild-type and mutant hipA genes in Escherichia coli: Effects on macromolecular synthesis and persister formation. J Bacteriol. 2006;188(11):3826–3836. [PMC free article] [PubMed]
32. Tomasz A, Albino A, Zanati E. Multiple antibiotic resistance in a bacterium with suppressed autolytic system. Nature. 1970;227(5254):138–140. [PubMed]
33. Goodell EW, Lopez R, Tomasz A. Suppression of lytic effect of beta lactams on Escherichia coli and other bacteria. Proc Natl Acad Sci U S A. 1976;73(9):3293–3297. [PubMed]
34. Correia FF, D'Onofrio A, Rejtar T, Li L, Karger BL, Makarova K, Koonin EV, Lewis K. Kinase activity of overexpressed hipA is required for growth arrest and multidrug tolerance in Escherichia coli. J Bacteriol. 2006;188(24):8360–8367. [PMC free article] [PubMed]
35. Schumacher MA, Piro KM, Xu W, Hansen S, Lewis K, Brennan RG. Molecular mechanisms of hipA-mediated multidrug tolerance and its neutralization by hipB. Science. 2009;323(5912):396–401. [PMC free article] [PubMed]
36. Evdokimov A, Voznesensky I, Fennell K, Anderson M, Smith JF, Fisher DA. New kinase regulation mechanism found in hipBA: A bacterial persistence switch. Acta Crystallogr D Biol Crystallogr. 2009;65(Pt 8):875–879. [PubMed]
37. Moyed HS, Broderick SH. Molecular cloning and expression of hipA, a gene of Escherichia coli K-12 that affects frequency of persistence after inhibition of murein synthesis. J Bacteriol. 1986;166(2):399–403. [PMC free article] [PubMed]
38. Black DS, Kelly AJ, Mardis MJ, Moyed HS. Structure and organization of hip, an operon that affects lethality due to inhibition of peptidoglycan or DNA synthesis. J Bacteriol. 1991;173(18):5732–5739. [PMC free article] [PubMed]
39. Black DS, Irwin B, Moyed HS. Autoregulation of hip, an operon that affects lethality due to inhibition of peptidoglycan or DNA synthesis. J Bacteriol. 1994;176(13):4081–4091. [PMC free article] [PubMed]
40. Levin-Reisman I, Gefen O, Fridman O, Ronin I, Shwa D, Sheftel H, Balaban NQ. Automated imaging with scanlag reveals previously undetectable bacterial growth phenotypes. Nat Methods. 2010;7(9):737–739. [PubMed]
41. Kussell E, Kishony R, Balaban NQ, Leibler S. Bacterial persistence: A model of survival in changing environments. Genetics. 2005;169(4):1807–1814. [PubMed]
42. Nystrom T. Stationary-phase physiology. Annu Rev Microbiol. 2004;58:161–181. [PubMed]
43. Luidalepp H, Joers A, Kaldalu N, Tenson T. Age of inoculum strongly influences persister frequency and can mask effects of mutations implicated in altered persistence. J Bacteriol. 2011;193(14):3598–3605. [PubMed] This paper demonstrates the persister frequency in a culture depends on the age of the inocula used to seed the culture. The results suggest that some previously identified persister genes affect persister levels due to altered growth rates and altered age, rather than contributing to a mechanism of persistence.
44. Walker GC. Understanding the complexity of an organism's responses to DNA damage. Cold Spring Harb Symp Quant Biol. 2000;65:1–10. [PubMed]
45. Debbia EA, Roveta S, Schito AM, Gualco L, Marchese A. Antibiotic persistence: The role of spontaneous DNA repair response. Microb Drug Resist. 2001;7(4):335–342. [PubMed]
46. Lidstrom ME, Konopka MC. The role of physiological heterogeneity in microbial population behavior. Nat Chem Biol. 2010;6(10):705–712. [PubMed] This is a good recent review of heterogeneity in bacterial populations and is not limited to variance in gene expression. Methods for studying heterogeneity are also discussed.
47. Balazsi G, van Oudenaarden A, Collins JJ. Cellular decision making and biological noise: From microbes to mammals. Cell. 2011;144(6):910–925. [PMC free article] [PubMed]
48. Tawfik DS. Messy biology and the origins of evolutionary innovations. Nat Chem Biol. 2010;6(10):692–696. [PubMed]
49. Dubnau D, Losick R. Bistability in bacteria. Mol Microbiol. 2006;61(3):564–572. [PubMed]
50. Veening JW, Smits WK, Kuipers OP. Bistability, epigenetics, and bet-hedging in bacteria. Annu Rev Microbiol. 2008;62:193–210. [PubMed]
51. Locke JC, Elowitz MB. Using movies to analyse gene circuit dynamics in single cells. Nat Rev Microbiol. 2009;7(5):383–392. [PMC free article] [PubMed]
52. Bennett MR, Hasty J. Microfluidic devices for measuring gene network dynamics in single cells. Nat Rev Genet. 2009;10(9):628–638. [PMC free article] [PubMed]
53. Weibel DB, Diluzio WR, Whitesides GM. Microfabrication meets microbiology. Nat Rev Microbiol. 2007;5(3):209–218. [PubMed]
54. Kohanski MA, Dwyer DJ, Collins JJ. How antibiotics kill bacteria: From targets to networks. Nat Rev Microbiol. 2010;8(6):423–435. [PubMed] This review provides a comprehensive yet concise description of the processes instrumental to the lethality of bactericidal antibiotics.
55. Vakulenko SB, Mobashery S. Versatility of aminoglycosides and prospects for their future. Clin Microbiol Rev. 2003;16(3):430–450. [PMC free article] [PubMed]
56. Magnet S, Blanchard JS. Molecular insights into aminoglycoside action and resistance. Chem Rev. 2005;105(2):477–498. [PubMed]
57. Taber HW, Mueller JP, Miller PF, Arrow AS. Bacterial uptake of aminoglycoside antibiotics. Microbiol Rev. 1987;51(4):439–457. [PubMed] This is an excellent review of aminoglycoside uptake and an essential starting point for anyone interested in the subject.
58. Allison KR, Brynildsen MP, Collins JJ. Metabolite-enabled eradication of bacterial persisters by aminoglycosides. Nature. 2011;473(7346):216–220. [PubMed] This paper is the first demonstrated approach specifically targeting the elimination of bacterial persisters.
59. Heidrich C, Ursinus A, Berger J, Schwarz H, Holtje JV. Effects of multiple deletions of murein hydrolases on viability, septum cleavage, and sensitivity to large toxic molecules in Escherichia coli. J Bacteriol. 2002;184(22):6093–6099. [PMC free article] [PubMed]
60. Uehara T, Dinh T, Bernhardt TG. LytM-domain factors are required for daughter cell separation and rapid ampicillin-induced lysis in Escherichia coli. J Bacteriol. 2009;191(16):5094–5107. [PMC free article] [PubMed]
61. Tomasz A. The role of autolysins in cell death. Ann N Y Acad Sci. 1974;235(0):439–447. [PubMed]
62. Drlica K, Malik M, Kerns RJ, Zhao X. Quinolone-mediated bacterial death. Antimicrob Agents Chemother. 2008;52(2):385–392. [PMC free article] [PubMed]
63. Dwyer DJ, Kohanski MA, Collins JJ. Role of reactive oxygen species in antibiotic action and resistance. Curr Opin Microbiol. 2009;12(5):482–489. [PMC free article] [PubMed]
64. Kohanski MA, Dwyer DJ, Hayete B, Lawrence CA, Collins JJ. A common mechanism of cellular death induced by bactericidal antibiotics. Cell. 2007;130(5):797–810. [PubMed]
65. Dwyer DJ, Kohanski MA, Hayete B, Collins JJ. Gyrase inhibitors induce an oxidative damage cellular death pathway in Escherichia coli. Mol Syst Biol. 2007;3:91. [PMC free article] [PubMed]
66. Lu TK, Collins JJ. Engineered bacteriophage targeting gene networks as adjuvants for antibiotic therapy. Proc Natl Acad Sci U S A. 2009;106(12):4629–4634. [PubMed]
67. Menchon SACCA. Quiescent cells: A natural way to resist chemotherapy. Physica A. 2011;390(20):8.
68. Mellor HR, Ferguson DJ, Callaghan R. A model of quiescent tumour microregions for evaluating multicellular resistance to chemotherapeutic drugs. Br J Cancer. 2005;93(3):302–309. [PMC free article] [PubMed]
69. Kim JJ, Tannock IF. Repopulation of cancer cells during therapy: An important cause of treatment failure. Nat Rev Cancer. 2005;5(7):516–525. [PubMed]