Bacterial persistence from a system-level perspective

Radzikowski, Jakub Leszek; Schramke, Hannah; Heinemann, Matthias

doi:10.1016/j.copbio.2017.02.012

Cited by 52 publications

(55 citation statements)

References 57 publications

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“…These mechanisms involve the general stringent response, a strongly regulated process governed by the alternative sigma factor RpoS (35) up-regulated by the accumulation of hyperphosphorylated guanine nucleotides, as the "alarmone" (p)ppGpp (37)(38)(39). That regulation might in fact reflect the metabolism of persisters which is oriented toward energy production, with depleted metabolite fluxes, which perpetuates the slow growth (12,40).…”

Section: Discussionmentioning

confidence: 99%

“…First, they may have exhausted the locally available resources; thus modified their environment so their populations are at or near stationary phase (2)(3)(4)(5)(6). Second, although local nutrients may be sufficient for their replication, for hosts treated with bactericidal drugs these bacteria may be minority populations of physiologically refractory survivors, the so-called "persisters" (7)(8)(9)(10)(11)(12)(13). Third, the offending bacteria may be non-replicating because of exposure to bacteriostatic antibiotics, a state we shall refer to as antibiotic-induced stasis.…”

Section: Introductionmentioning

confidence: 99%

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Antibiotic killing of diversely generated populations of non-replicating bacteria

Shah

McCall

Govindan

et al. 2018

Preprint

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Non-replicating bacteria are known to be (or at least commonly thought to be) refractory to antibiotics to which they are genetically susceptible. Here, we explore the sensitivity to killing by bactericidal antibiotics of three classes of non-replicating populations of planktonic bacteria; (1) stationary phase, when the concentration of resources and/or nutrients are too low to allow for population growth; (2) persisters, minority subpopulations of susceptible bacteria surviving exposure to bactericidal antibiotics; (3) antibiotic-static cells, bacteria exposed to antibiotics that prevent their replication but kill them slowly if at all, the so-called bacteriostatic drugs. Using experimental populations of Staphylococcus aureus Newman and Escherichia coli K12 (MG1655) and respectively 9 and 7 different bactericidal antibiotics, we estimate the rates at which these drugs kill these different types of non-replicating bacteria. Contrary to the common belief that bacteria that are non-replicating are refractory to antibiotic-mediated killing, all three types of non-replicating populations of these Gram-positive and Gram-negative bacteria are consistently killed by aminoglycosides and the peptide antibiotics, daptomycin and colistin, respectively. This result indicates that non-replicating cells, irrespectively of why they do not replicate, have an almost identical response to bactericidal antibiotics. We discuss the implications of these results to our understanding of the mechanisms of action of antibiotics and the possibility of adding a short-course of aminoglycosides or peptide antibiotics to conventional therapy of bacterial infections.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Antibiotic killing of diversely generated populations of non-replicating bacteria

Shah

McCall

Govindan

et al. 2018

Preprint

View full text Add to dashboard Cite

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“…For example, addition of metabolic stimuli that promote an increase in proton-motive force by the oxidative electron transport chain triggers the uptake of aminoglycoside antibiotics in persister cells, thereby enhancing persister killing [27]. These observations indicate that persisters retain a distinct -and active -metabolic state, and highlight the importance of metabolism for persistence [6,29]. …”

Section: Introductionmentioning

confidence: 99%

Drug persistence – From antibiotics to cancer therapies

Kochanowski

Morinishi

Altschuler

et al. 2018

Current Opinion in Systems Biology

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Drug-insensitive tumor subpopulations remain a significant barrier to effective cancer treatment. Recent works suggest that within isogenic drug-sensitive cancer populations, subsets of cells can enter a ‘persister’ state allowing them to survive prolonged drug treatment. Such persisters are well-described in antibiotic-treated bacterial populations. In this review, we compare mechanisms of drug persistence in bacteria and cancer. Both bacterial and cancer persisters are associated with slow-growing phenotypes, are metabolically distinct from non-persisters, and depend on the activation of specific regulatory programs. Moreover, evidence suggests that bacterial and cancer persisters are an important reservoir for the emergence of drug-resistant mutants. The emerging parallels between persistence in bacteria and cancer can guide efforts to untangle mechanistic links between growth, metabolism, and cellular regulation, and reveal exploitable therapeutic vulnerabilities.

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“…OxidizeME represents another step in this direction. There is increasing recognition that microbial stress response plays an important role in infectious disease and antibiotic tolerance [7,8]. Stress-ME models (FoldME, OxidizeME, etc.)…”

Section: Discussionmentioning

confidence: 99%

Cellular responses to reactive oxygen species can be predicted on multiple biological scales from molecular mechanisms

Yang

Mih

Anand

et al. 2017

Preprint

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All aerobically growing microbes must deal with oxidative stress from intrinsically-generated reactive oxygen species (ROS), or from external ROS in the context of infection. To study the systems biology of microbial ROS response, we developed a genome-scale model of proteome damage and maintenance in response to ROS, by extending a genome-scale metabolism and macromolecular expression (ME) model of E. coli. This OxidizeME model recapitulated measured microbial oxidative stress response including metalloenzyme inactivation by ROS and amino acid auxotrophies. OxidizeME also correctly predicted differential expression under ROS stress. We used OxidizeME to investigate how environmental context affects the flexibility of ROS stress response. The context-dependency of microbial stress response has important implications for infectious disease. OxidizeME provides a computational resource for model-driven experiment design in this direction.The human immune system includes phagocytes that use reactive oxygen species (ROS) to combat pathogens. Most microbes are considerably weakened by this oxidative stress, whereas certain pathogens can grow inside the phagosome [1]. How microbes, including pathogens, evolve to tolerate such intense oxidative stress remains a long-standing question. To answer it requires a systemslevel understanding of the many interlinked biochemical and physiological adaptations for responding to ROS damage. Here, we approach this question through in silico experiments subjecting E. coli to varying degrees of oxidative stress in a multitude of environments. To this end, we extended a genome-scale model of E. coli metabolism and protein expression by incorporating ROS damage and response mechanisms.By their chemical nature, ROS can react with a broad array of macromolecules, often with deleterious consequences. In particular, a number of protein targets of ROS have been experimentally verified in detail; however, most of the potential targets of ROS have not been characterized individually. Thus, to better understand ROS stress, we must answer two questions: which biomolecules are damaged to what extent, and what is the cellular response to this damage? Here, we address these questions, focusing on ROS damage to metalloproteins. To predict cellular response to damage, we developed a novel model called OxidizeME. OxidizeME accounts for ROS damage to iron and iron-sulfur cluster cofactors of over 40 enzymes. We also modeled enzyme-catalyzed repair of oxidized iron-sulfur clusters. OxidizeME is able to predict cellular response at the metabolic and gene expression levels. RESULTSA multiscale model of reactive oxygen species damage and response.We developed the OxidizeME model by extending the iLE1678-ME model of E. coli Metabolism and macromolecular Expression (ME model) [2] to account for damage to proteins by ROS, and cellular response mechanisms (Fig. 1) For each protein, OxidizeME computes the the fraction of inactivated enzyme due to cofactor oxidation as a function of intracellular ROS concentrati...

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Bacterial persistence from a system-level perspective

Cited by 52 publications

References 57 publications

Antibiotic killing of diversely generated populations of non-replicating bacteria

Antibiotic killing of diversely generated populations of non-replicating bacteria

Drug persistence – From antibiotics to cancer therapies

Cellular responses to reactive oxygen species can be predicted on multiple biological scales from molecular mechanisms

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