Antibiotic resistance and persistence-Implications for human health and treatment perspectives

Abstract

Antimicrobial resistance (AMR) and persistence are associated with an elevated risk of treatment failure and relapsing infections. They are thus important drivers of increased morbidity and mortality rates resulting in growing healthcare costs. Antibiotic resistance is readily identifiable with standard microbiological assays, and the threat imposed by antibiotic resistance has been well recognized. Measures aiming to reduce resistance development and spreading of resistant bacteria are being enforced. However, the phenomenon of bacteria surviving antibiotic exposure despite being fully susceptible, so-called antibiotic persistence, is still largely underestimated. In contrast to antibiotic resistance, antibiotic persistence is difficult to measure and therefore often missed, potentially leading to treatment failures. In this review, we focus on bacterial mechanisms allowing evasion of antibiotic killing and discuss their implications on human health. We describe the relationship between antibiotic persistence and bacterial heterogeneity and discuss recent studies that link bacterial persistence and tolerance with the evolution of antibiotic resistance. Finally, we review persister detection methods, novel strategies aiming at eradicating bacterial persisters and the latest advances in the development of new antibiotics.

Keywords: persistence; persistent infections; persisters; resistance; tolerance.

Conflict of interest statement

The authors declare that they have no conflict of interest.

© 2020 The Authors.

Figures

Figure 1. Invasive bacterial isolates and resistance development over time in the European Union (EU) and European Economic Area (EEA)

(A) Total number of invasive E. coli isolates tested and percentage with combined resistance to fluoroquinolones, 3rd‐generation cephalosporins and aminoglycosides, including 95% confidence intervals (95% CI, shaded area). (B) Total number of invasive E. faecium isolates tested and percentage with resistance to vancomycin, including 95% CI. (C) Total number of invasive S. aureus isolates tested and percentage with resistance to methicillin (MRSA), including 95% CI. (D) Total number of invasive K. pneumoniae isolates tested and percentage with combined resistance to fluoroquinolones, 3rd‐generation cephalosporins and aminoglycosides, including 95% CI. (E) Total number of invasive Acinetobacter spp., including most of the disease‐causing species (A. baumannii, A. pittii and A. nosocomialis) and the generally less pathogenic A. non‐baumannii group, isolates tested and percentage with combined resistance to fluoroquinolones, aminoglycosides and carbapenems, including 95% CI. (F) Total number of invasive P. aeruginosa isolates tested and percentage with combined resistance (resistance to three or more antimicrobial groups among piperacillin—tazobactam, ceftazidime, fluoroquinolones, aminoglycosides and carbapenems), including 95% CI. (A‐F) Data are derived from European Centre for Disease Prevention and Control’s yearly Surveillance of antimicrobial resistance in Europe (reports 2013‐2018 were used). ECDC collects data from invasive isolated reported to the European Antimicrobial Resistance Surveillance Network (EARS‐Net) by 30 EU and EEA (Iceland and Norway) countries.

Figure 2. Environmental triggers of antibiotic persistence and bacterial response mechanisms

Environmental stressors such as oxidative stress and antibiotic exposure can trigger the bacterial SOS response via induction of RecA expression and the upregulation of the Lex box containing TA systems leading to a drop in ATP levels and a downregulation of essential cellular functions, e.g. transcription, translation, DNA replication and energy production. Other stressors such as pH changes, heat shock and starvation trigger the stringent response via production of (p)ppGpp, mainly by SpoT and RelA, and activation of toxin/antitoxin systems leading to the inhibition of essential cellular functions. Low intracellular ATP levels can favour the accumulation of insoluble proteins, a feature linked to increased antibiotic tolerance and dormancy. Additionally, high population densities can inhibit cellular functions via quorum sensing and T/A systems. External triggers/signals are shown in red boxes. Abbreviations: T/A, antitoxin/toxin; PMF, proton motive force.

Figure 3. Characterization of colony radius heterogeneity and single‐cell growth dynamics of bacteria

(A) Stress‐exposed S. aureus and genetically determined auxotrophic mutants show small colony phenotypes. Top: The stress‐exposed bacteria display colony radius heterogeneity on agar plates by forming non‐stable small colonies (nsSCs), whereas the auxotrophic mutants grow as genetically determined small colony variants (SCVs). Middle: The colony radius histograms for stress‐triggered bacteria show a broad distribution towards smaller colony sizes compared to exponentially growing bacteria (most colonies have the same size) and SCVs (most colonies are small and the same size). Bottom: Translated into colony appearance times, the exponentially growing bacteria almost all appear at the same time early after plating, whereas the stress‐exposed bacteria show a broad lag time distribution with some colonies appearing early and others later. In contrast, SCVs all appear later after a longer incubation time, but almost all at the same time. (B) The schemes show bacterial growth dynamics on a single‐cell level as well as different scenarios explaining the colony size at a certain time point. Short arrows indicate a fast division rate of wild type bacteria (yellow), whereas longer arrows represent a slower growth rate for SCV forming mutants (green). Colonies can be small because of a late onset of growth (lag time) or because of a slower growth rate.

Figure 4. Different detection methods of antibiotic tolerance and persister cells

(A) The traditional method to test for antibiotic persistence is performing time–kill curves. Green line shows killing of a susceptible population and blue line displays the biphasic kill curve of a mixed population consisting of susceptible rapidly killed bacteria and persisters killed at a slower rate. (B) Tolerance Disk (TD) test allows the detection of bacteria that survive antibiotic exposure (persisters) by combining standard antibiotic disk assay (step 1) with regrowth after glucose addition (step 2). (C) The replica plating tolerance isolation system (REPTIS) allows detection of bacterial survivors on antibiotic plates (master plates). Colony‐forming units (CFUs) are transferred via a sterile velvet from a master plate on a fresh replica plate that does not contain antibiotics and allows growth of bacteria. Regrowth of bacteria indicates the presence of persister cells. (D) Detection of antibiotic persistence via lag phase determination. ScanLag, ColTapp and single‐cell microscopy determine colony and bacterial lag times that serve as a proxy for bacterial persistence (persistence by lag). (E) Determination of the minimum duration of killing 99% of a bacterial population (MDK99) can be used to measure antibiotic persistence. High MDK99 values indicate high antibiotic persistence.

Figure 5. New approaches to target multidrug‐resistant bacteria and bacterial persister cells

(A) Scheme showing novel strategies to target multidrug‐resistant Gram‐negative and Gram‐positive bacteria. New approaches to target multiresistant bacteria include darobactin, chimeric peptidomimetic antibiotics, antibacterial drones (ABD), bacteriophages, endolysins, halicin and cyclic hepta‐pseudopeptides and lugdunin. (B) Scheme of persister‐targeting approaches. Different strategies have been suggested to specifically target bacterial persister cells, e.g. addition of cell wall targeting substances like endolysins, NT‐61, XF‐73 or NCK10, simple sugars, bacterial opsonization by antibody–antibiotic conjugates (AACs), 3‐[4‐(4‐methoxyphenyl)piperazin‐1‐yl] piperidin‐4‐yl biphenyl‐4‐carboxylate (C10), cis‐2‐decenoic acid, (p)ppGpp analogues like relacin, mitomycin C, acyldeptipeptide (ADEP4) or retinoid acid derivatives (e.g. CD437 and CD1530).