evolution of parasite countermeasures

General principles

• two stages of evolution: de novo mutation and selection
• limiting factors in de novo mutation
  • mutation rate (per locus/per genome)
  • population size
  • generation time
  • rate appearance of new mutations = (mutation rate × pop size)/(generation time)
  • mutational spectrum: what can mutations achieve?
• limiting factors in selection:
  • selection differential
    • benefits (= prob of encountering antibiotic × benefit of resistance)
    • costs [metabolic/energetic; reduced efficiency]
      • compensatory mutations (reduce cost)
  • pop size (drift vs selection; bottlenecks in between-host transmission)
  • variation in selection (within- vs between-host)
  • recombination and/or horizontal transmission via mobile elements (plasmids etc.)
• competition between susceptible and resistant strains (Lipsitch & Samore, 2002)

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1. resistant bacteria take over during treatment failure (within-host competition)
2. resistant bacteria take advantage of reduced transmission by treated hosts (between-host)
3. resistant bacteria colonize a treated host (empty patch)
4. resistant bacteria take advantage of side effects (bystander effects)

Bacteria

Mechanisms

• because bacteria and animals are biochemically different, can use substances that disrupt bacterial but not animal metabolic processes
• many biologically derived
  • fungi (penicillin!) (Karwehl & Stadler, 2016)
  • soil bacteria (esp Streptomyces; streptomycin, tetracycline)
  • (also chemical/synthetic, e.g. derived from dyes - sulfa drugs)
• because antibiotics have been around “forever”, so has antibiotic resistance (D’Costa et al., 2011)
  • but presence as mobile elements may be recent, human/animal derived (Ebmeyer et al., 2021)
  • often present in antibiotic producers (Benveniste & Davies, 1973)
• huge problem, e.g. mdrMRSA ([multi-drug resistant], methicillin-resistant Staphylococcus aureus), extensively drug-resistant (XDR) tuberculosis (Centers for Disease Control, 2020)
  • threatens to wipe out disease cures …
• horizontal transfer is rampant
  • resistance gene can be anywhere in the microbiome …
  • collateral or non-target selection (Llewelyn et al., 2017)
  • also makes it easier to lose resistance when no longer required
  • thus resistance is usually/often pre-existing
• mechanisms of action:
  • pumps (“efflux system”: remove toxic substances from the cell)
  • inactivation or degradation/detoxification
  • altered pathways?
• antibiotics are effectors (not recognizers)
• cost of resistance; are resistance alleles lost or compensated in the absence of antibiotics? (Bjorkholm et al., 2001; Levin et al., 2000)

Implications for antibiotic use

• avoid overuse! “antibiotic conservation”
• regulate agricultural use
  • for human-to-human transmission, regulating agriculture may be too late once resistance is already established in humans (Smith et al., 2002)
  
  • but regulation still helps with spillover infections (Lipsitch et al., 2002)
• “the long-term benefit of single drug treatment from introduction of the antibiotic until a high frequency of resistance precludes its use is almost independent of the pattern of antibiotic use” (Bonhoeffer, Lipsitch, et al., 1997)
• “cocktails” may be best; varying treatments in space is better than cycling (Bergstrom et al., 2004)
• treating for longer increases collateral selection (Llewelyn et al., 2017)
• contrast: Tb (chronic disease, resistance from point mutations)

Viruses

• similar biochemistry to hosts
  • often fought by priming immune system, i.e. vaccination
  • resistance via recognition escape rather than disabling effectors
  • usually strain replacement rather than within-lineage selection on escape alleles
    • horizontal transfer/lineage-mixing does happen via recombination (especially influenza, phages), but less typical (Mavrich & Hatfull, 2017; Wu et al., 2023)
• very high mutation rate
  • de novo mutation is a bigger problem
• HIV
  • single-drug resistance evolves quickly (Bonhoeffer, Coffin, et al., 1997)
  • target non-host-like biochemistry: nucleoside and non-nucleoside resistance transcriptase inhibitors; protease, integrase inhibitors
  • HAART (Eggleton & Nagalli, 2022); e.g. standard South African regimen includes tenofovir, lamivudine (nucleotide analog), dolutegravir (integrase inhibitor) (South Africa National Department of Health, 2019)
  • keeping load low reduces transmission and within-host evolution of resistance
  • between-host transmission maybe less important because of early infectivity
• strain replacement
  • COVID-19! alpha, delta, omicron (Ferguson et al., 2021)
  • influenza, every year (antigenic drift)/pandemic (antigenic shift)
  • other examples: Haemophilus influenzae B (Adam et al., 2010)
  • human papilloma virus: maybe not? (Covert et al., 2019; Man et al., 2021)
  • not: smallpox (gone), rinderpest, chickenpox, measles, rubella
  • importance of focusing on conserved viral epitopes; universal flu vaccine? (Wang et al., 2022) (back to the mutational spectrum)

• back to bacteria: vaccine-preventable Bordetella pertussis, resurgence and evolution of immune evasion (?) (van Gent et al., 2012)

(to be added, maybe)

malaria control

Twitter:

reading various malaria documents that discuss having endemic malaria today despite spending ~$4.1B/yr, I always want to insert the comment, “Well, WTF did you expect? No one who understands malaria believes elimination would be possible without spending at least $10B/yr”

Main components:

• antimalarial drugs
• vaccine (children only, max effectiveness \(\approx\) 40%, safety concerns …) (Jarry, 2021; Seo et al., 2014)
• vector control
  • indoor residual spraying (lethality + avoidance)
  • treated bednets (lethality + avoidance)
  • biocontrol (e.g. Gambusia, “mosquito fish”)
  • improved housing? (Musiime et al., 2022)

malaria resistance to antimalarial drugs

• protozoan parasite
• quinine, chloroquine (Achan et al., 2011; Ashley et al., 2014)
• artemisinin (and combination therapy, ACT)

From Ashley et al. (2014)

Rosenthal (2021): “Recent data suggest that we are on the verge of clinically meaningful artemisinin-resistance in Africa”

From Imwong et al. (2017). Red box=C580Y. Light blue box=wild type. Each row represents one parasite isolate; white cells indicate identical microsatellite alleles compared with the most frequent allele and dark blue cells indicate differences. containment strategies: eliminate falciparum malaria from Greater Mekong region or “firewall”?

vectors and resistance to insecticides

• DDT Wikipedia
  • environmental side effects
    • fast evolution of resistance: 6-7 years (Gladwell, 2001)
• other methods?
  • sterile male release (irradiation, Wolbachia) (Atyame et al., 2016)
  • gene drive (Burt et al., 2018) and/or bacterial infection (Dennison et al., 2014)
    • reduce vector competence
    • shift sex ratios toward males
  • evolution-resistant insecticides: shorten host life span (Koella et al., 2009; McMeniman et al., 2009)
    • weak selection against late-acting processes (Medawar, 2019)
    • late-acting insecticides (W. or fungal)
    • larvicides: resistant phenotypes are smaller/short-lived

References

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Last updated: 2023-11-26 16:37:08.182645