| Literature DB >> 35352028 |
Matthew C Fisher1, Ana Alastruey-Izquierdo2, Judith Berman3, Tihana Bicanic4, Elaine M Bignell5, Paul Bowyer6, Michael Bromley6, Roger Brüggemann7, Gary Garber8, Oliver A Cornely9, Sarah J Gurr10, Thomas S Harrison4,5, Ed Kuijper11, Johanna Rhodes12, Donald C Sheppard13, Adilia Warris5, P Lewis White14, Jianping Xu15, Bas Zwaan16, Paul E Verweij17,18.
Abstract
Invasive fungal infections pose an important threat to public health and are an under-recognized component of antimicrobial resistance, an emerging crisis worldwide. Across a period of profound global environmental change and expanding at-risk populations, human-infecting pathogenic fungi are evolving resistance to all licensed systemic antifungal drugs. In this Review, we highlight the main mechanisms of antifungal resistance and explore the similarities and differences between bacterial and fungal resistance to antimicrobial control. We discuss the research and innovation topics that are needed for risk reduction strategies aimed at minimizing the emergence of resistance in pathogenic fungi. These topics include links between the environment and One Health, surveillance, diagnostics, routes of transmission, novel therapeutics and methods to mitigate hotspots for fungal adaptation. We emphasize the global efforts required to steward our existing antifungal armamentarium, and to direct the research and development of future therapies and interventions.Entities:
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Year: 2022 PMID: 35352028 PMCID: PMC8962932 DOI: 10.1038/s41579-022-00720-1
Source DB: PubMed Journal: Nat Rev Microbiol ISSN: 1740-1526 Impact factor: 78.297
Comparing drivers of bacterial and fungal antimicrobial resistance
| Comparison | Bacterial resistance | Fungal resistance |
|---|---|---|
| Differences | Low-fidelity species boundaries drive widespread horizontal and vertical gene transfers, via both heterologous and homologous recombination | High-fidelity species boundaries dictated by pre and post-zygotic reproductive barriers; homologous recombination predominates |
| Species boundaries are porous to gene transfer by MGEs, allowing widespread HGT amongst species; hitch-hiking of ARGs occurs upon MGEs — bacteriophages, plasmids, transposable elements and gene cassettes — comprising the bacterial ‘resistome’ | No evidence to date of antifungal resistance genes and alleles undergoing HGT among species, and no evidence of a pan-kingdom fungal ‘resistome’; limited hybridization and rare HGT of MGEs such as homing endonuclease genes occurs, but not on the scale seen in bacteria | |
| Environmental and commensal bacteria comprise the main reservoir of ARGs that are available to potentially pathogenic species via HGT; therefore, in most cases, resistance does not evolve de novo for each species–drug combination | Environmental and commensal fungal species regularly cause disease, but AMR genes and alleles are constrained within species boundaries; therefore, resistance to antifungals needs to evolve de novo for each species–drug combination, which imposes limits on evolutionary rates | |
| Haploid core genome consisting of a single circular chromosome and housekeeping genes; extrachromosomal accessory genome on plasmids constitutes a ‘pan-genome’ of variable size containing the majority of ARGs | Haploid, diploid and multinucleated cells with each nucleus containing multiple chromosomes and with complex AMR determinants (see Fig. | |
| Zoonotic human infections by AMR-rich pathogens such as | Animal reservoir of antifungal AMR currently unknown; zoonotic transmission occurs (for example, sporotrichosis and dermatophytosis), so theoretically possible | |
| Multiplicity of cidal drugs but extensive use of bacteriostatic drugs in settings of functioning host immunity to achieve full effect; tolerant bacterial subpopulations apply only to cidal drug use and arise via slowing of essential processes; quiescent persister subpopulations derived from epigenetically mediated tolerance remain dormant and metabolically inactive; higher tolerance in bacterial isolates is associated with longer lag phase growth | Paucity of cidal drugs and extensive use of fungistatic agents for prolonged periods in settings of immune dysfunction, promoting acquisition of drug tolerance; tolerant fungal subpopulations apply only to fungistatic drugs and arise through altered thresholds in stress responses and only indirectly, often via epigenetic or physiological changes that affect the ability to grow in the presence of a drug; tolerance may involve altered rates of drug efflux or uptake that can indirectly affect target–drug interactions; fungal isolates with higher tolerance levels have shorter lag phase growth | |
| Antibiotic resistance has been a target of international study for 30+ years with systematic surveillance and reference laboratories | Antifungal resistance only recognized in the 1990s with little organized surveillance and a paucity of reference laboratories | |
| Similarities | Active global spread of AMR through travel and trade; clonal expansion for ARG-bearing lineages (for example, | Active spread through nosocomial transmission and travel (for example, fluconazole-resistant |
| Gut, mucosal and skin commensal carriage in Gram-negative and Gram-positive bacteria leading to local nosocomial health-care outbreaks as well as global spread of AMR | Gut, mucosal and epithelial commensal carriage in | |
| Subtherapeutic levels or inadequate exposure to antibiotics can drive resistance emergence (for example, β-lactams); need for therapeutic drug monitoring to optimize pharmacokinetic and pharmacodynamic targets as an integral part of antibiotic stewardship | Subtherapeutic concentrations or inadequate exposure to antifungal drugs can drive resistance emergence (for example, azoles); need for therapeutic drug monitoring to optimize pharmacokinetics and pharmacodynamics as an integral part of antifungal stewardship | |
| Large-scale use of antibiotics in agriculture and livestock (for example, livestock-associated methicillin-resistant | Large-scale use of fungicides in agriculture (for example, azole-resistant | |
| Gene amplifications resulting in copy number variation can confer resistance to antibiotics | Aneuploid chromosomes and copy number variation can confer resistance or tolerance to stresses including antifungal drugs |
The AMR, antimicrobial resistance; ARG, antimicrobial resistance gene; HGT, horizontal gene transfer; MGE, mobile genetic element.
Fig. 1Major routes to acquiring antifungal drug resistance and/or tolerance in key invasive human fungal pathogens.
Routes to acquiring antifungal drug resistance and/or tolerance vary depending on the mode of action (MOA). a | Azole drug resistance is primarily due to increased efflux of the drug from the fungal cell (particularly in Candida spp.) and modifications to the sterol biosynthesis pathway caused by point mutations and promoter insertions in CYP51A (Aspergillus fumigatus). In other fungal species, such as Cryptococcus neoformans, overexpression of the drug target and efflux pumps caused by chromosomal aneuploidy and hypermutation is common. b | Polyenes alter cell membrane permeability by forming a complex with ergosterol, and resistance is caused by loss-of-function mutations in ergosterol biosynthesis genes (particularly in Aspergillus and Candida spp.). In Candida albicans in particular, double loss of ERG3 confers resistance. However, drug tolerance is common, via upregulation of ERG5, ERG6 and ERG25 in C. albicans. c | Cell membrane stress can also impact regulators of HSP90, conferring drug tolerance. Echinocandins inhibit 1,3-β-d-glucan synthase (FKS1), and mutations in this gene cause resistance in Candida and Fusarium spp. Echinocandin exposure can also lead to cell wall stress through inhibition of β-glucan synthase, with indirect downstream activation of Ca2+/calcineurin or HSP90/mTOR pathways, which are involved in drug tolerance. d | Pyrimidine analogues such as 5-flucytosine inhibit DNA and RNA synthesis. Resistance can arise via point mutations in the target gene FCY1, and is common in Candida spp. Hypermutation in Cryptococcus spp. is also known to cause resistance to this drug class. TR, tandem repeat.
Fig. 2Emerging antifungal resistance and environment–One Health drivers.
Fungi in the environment are exposed to broad-spectrum classes of antifungals that are also utilized as frontline antifungal treatments in the clinic. Ecological hotspots occur that can act as amplifiers of resistant genotypes. One example is green waste stockpiling and composting. Humans with invasive fungal diseases (IFDs) may also transmit resistant genotypes (for instance in nosocomial outbreaks); however, the extent to which humans and other animals contribute to the presence of antifungal resistance in the environment remains unknown. Multiple extrinsic factors exist that are expected to influence the incidence of antifungal resistance. These include changing patterns of fungicide use in the environment and in waste management[33]; changing at-risk human host groups including viral infections such as COVID-19; changing climates that may alter the geographical range of fungi and adaptive landscape for resistance[50] as well as providing novel routes for infection (for example, natural disasters); changing biotic interactions that may include xenobiotic chemicals that are analogues to antifungals; and changing virulence of the fungi themselves owing to intrinsic genetic change or synergies with combinations of the above drivers[47].
Fig. 3Resistance detection, tracking and surveillance.
Fungal samples can be acquired from the clinic or environment, including engaging with the public as ‘citizen scientists’[42]. Traditional, established microbiology methods can culture and select isolates from these samples, ready for extraction of genomic DNA. These DNA fragments are used to generate a sequencing library for whole-genome sequencing (WGS). There are many sequencing platforms available, generating both long-read and short-read sequence data. Raw sequence data need to be quality controlled prior to mapping against a reference genome, either locally or using cloud computing. Calling high-confidence single-nucleotide polymorphisms (SNPs) can help infer alleles associated with drug resistance and their evolutionary histories. Phylodynamic inference and building interactive online portals (such as Nextstrain[131] or Microreact[132]) that are available to researchers and clinicians alike enable tracing of transmission events.
Fig. 4Interventions for invasive fungal infections within the landscape of antifungal resistance.
Synoptic integrated One Health understanding is necessary to understand not only the complex multifactorial pathways that lead to the emergence of resistance across the fungal kingdom but also potential interventions to mitigate the rate of emergence. a | Complex biotic and abiotic interactions lead to occurrence of evolutionary hotspots for antimicrobial resistance (AMR) development in environmental opportunistic fungi requiring targeted interventions in the environment. b,c | Patient exposures to environmental AMR require enhanced methods of detection with more focus on key fungal life-history factors (part b), and new and emerging drug-resistant fungal pathogens that have the potential for global nosocomial carriage and outbreaks in health-care settings require transnational surveillance (part c). A cross-cutting theme is the need for industry to separate development and use of agricultural fungicides from those antifungals that are used in the clinic to develop treatments that are resilient to the evolutionary forces at play in parts a–c. GLASS, Global Antimicrobial Resistance Surveillance System; WHO, World Health Organization.