The Problem of Drug Resistance

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The Problem of Drug Resistance
E3 Lecture 11
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Clicker Questions R_4_E3

• What does the following graph from the Gagneux
  et al. paper NOT tell you?
• Resistance to rifampicin is generally costly in
  the absence of the drug.
• The fitness effect of a mutation conferring
  resistance to rifampicin can depend on the
  genetic background of the strain under
  investigation.
• Only a few of these mutants would show
  compensation after further evolution, most would
  revert to sensitivity in the absence of
  rifampicin

KEY
fitness (relative to ancestor)
Strain CDC1551
Strain T85
mutation conferring resistance to rifampicin
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Early Antibiotic Research

• Joseph Lister (1827-1912)
• - In 1871, he noted that samples of urine with
  mold did not permit bacterial growth.
• - He also pioneered the introduction of an
  antiseptic (phenol) before and during surgery,
  drastically reducing the rate of infection.
• Ernest Duchesne (1874-1912)
• In 1897, he demonstrated that E. coli was killed
  when cultured with Penicillium glaucum.
• He also showed that injection of this mold into
  animals infected with typhoid bacilli prevented
  the advent of the disease.
• Alexander Flemming (1881-1955)
• In 1928, noticed a mold contaminant on a
  bacterial plate that had been sitting out in the
  lab.
• He isolated the Penicillium notatum and
  demonstrated that it had antimicrobial effects on
  Gram-positive pathogens (that cause scarlet
  fever, pneumonia, gonorrhea, meningitis,
  diphteria)

Joseph Lister
Ernest Duchesne
Alexander Flemming
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Earlier Antibiotic Research

• Microbes have produced antibiotics for a number
  of reasons
• As anticompetitor compounds (e.g., bacteriocins)
• As predatory compounds (e.g., lysing enzymes)
• As quorum-sensing molecules (e.g., nisin)
• Such antibiotics can affect many other species
  (broad spectrum) or affect only a few species
  (narrow spectrum).
• Most of our antibiotics are derivatives of
  natural microbial products.
• We are taking an ancient form of chemical
  warfare with the human body as the battlefield.

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The Problem of Drug Resistance

• Lecture Outline
• Antibiotics resistance
• Costs Reversion Compensation
• Antibiotics Adaptive Landscapes
• Predicting Resistance
• Summary

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The Problem of Drug Resistance

• Lecture Outline
• Antibiotics resistance
• Costs Reversion Compensation
• Antibiotics Adaptive Landscapes
• Predicting Resistance
• Summary

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Resistance in the Intensive Care UnitNational
Nosocomial Infections Surveillance System Report,
2003
Pseudomonas aeruginosa
Klebsiella pneumoniae
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10
52
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Staphylococcus aureus
Enterococcus sp.
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Resistance to Resistance is Futile

• With sustained use of an antibiotic, resistant
  strains appear and spread.
• As a new antibiotic is introduced, the
  evolutionary challenge is on and microbes
  generally answer this challenge.
• Facilitating spread is the appearance of
  resistance genes on mobile genetic elements, such
  as plasmids (this can lead to transfer between
  species).
• Often resistance is found in commensal bacteria,
  which in some cases can serve as a genetic
  reservoir for pathogenic species.
• Particularly troubling is the generation of
  multi-drug resistant strains of pathogenic
  bacteria.

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Resistance Matters
Causes of death, USA

• In human disease, drug-resistant bacteria can
  lead to
• Increased risk of mortality
• Increased length of hospital stay
• Increased use of other drugs (which can be
  expensive and lead to complications)
• Foci for the spread of all these problems to
  other patients
• Thus, drug-resistance causes large financial and
  health costs.

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The Problem of Drug Resistance

• Lecture Outline
• Antibiotics resistance
• Costs Reversion Compensation
• Antibiotics Adaptive Landscapes
• Predicting Resistance
• Summary

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Case Study Tuberculosis

• Tuberculosis is an infectious disease caused by
  the bacterium Mycobacterium tuberculosis. The
  disease generally progresses in the lungs causing
  tissue destruction and necrosis.
• The global incidence of TB has been on the rise,
  reaching highest densities in Africa, the Middle
  East and Asia.
• Particularly alarming is the rise of
  drug-resistant and multi-drug resistant strains
  of TB (e.g., bacteria resistant to isoniazid and
  rifampicin).

• The origin of resistance in TB will be affected
  by the intensity of antibiotic usage in a given
  region.
• The maintenance of resistance will depend, in
  part, on its fitness effects and evolutionary
  options of various TB strains.

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Resistance in Tuberculosis

• Gagneux, Davis Long and colleagues explored the
  fitness cost of drug resistance in TB in vitro.
• From a fully grown culture of a clinical
  isolate, they exposed the bacteria to the
  antibiotic rifampicin.
• Resistant colonies were isolated and genotyped
  (generally single base changes in the rpoB gene)
• These authors wanted to gauge the costs (if any)
  of antibiotic resistance.
• The antibiotic resistant strain and
  antibiotic-sensitive ancestor were placed (at
  roughly equal starting frequency) in a liquid
  broth and competed for a growth period (one
  month!)
• With knowledge about the starting densities and
  final densities of the resistant strain (R) and
  the ancestor (A), a relative fitness measure can
  be computed

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Costs of Resistance

• Gagneux et al. find that rifampicin resistance
  is costly in TB.
• Furthermore, they find that the cost of
  resistance can depend on the genetic background
  of the strain.
• Such costs have been found in many other cases
• Streptomycin resistance in E. coli
• Fusidic acid resistance in S. aureus
• Fusidic acid resistance in S. typhimurium
• Colicin resistance in E. coli
• Rifampicin resistance in E. coli
• Most of these costs were measured in vitro.
  But
• By looking in paired patient isolates, these
  authors found that resistance was often costly,
  but not always

?

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Reversion and Compensation

• Schrag, Perrot Levin (1997) selected for
  streptomycin-resistant bacteria.
• These authors then evolved this bacteria for 180
  generations in the absence of streptomycin.
• The initial resistant mutant was costly.
• However, the streptomycin resistant strain did
  not revert to sensitivity. It remained resistant
  to strep.
• Further, the initial cost of streptomycin
  resistance was ameliorated there was
  compensation.
• They discovered second site mutations (in rpsL).
• Through genetic manipulation, they constructed
  all combinations of base changes and found a
  rugged landscape!

24 hrs.
24 hrs.
Take 5 minutes to talk about the following Why
do you think this landscape is rugged? If
landscapes of pathogenic bacteria generally
resemble the one found by Schrag et al., how
would that affect your decision about length and
strength of antibiotic treatments?
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Eyeing the Landscape
sensitive wild-type

• Lets extend the landscape metaphor further
• Imagine that in the absence of the antibiotic,
  the population (mostly) resides on a sensitive
  wild-type peak.
• Then an antibiotic is applied.
• The sensitive peak drops out.
• Any resistant mutants are immediately selected
  now the population (mostly) resides on a
  resistant peak.
• Assume that the antibiotic is removed.
• Now, the sensitive peak reappears.
• If there are many ways to compensate, then the
  evolutionary trajectory can take several possible
  paths.
• It is possible that reversion occurs it is
  possible compensation occurs.
• Some relevant questions
• Is the landscape actually rugged?
• Are compensatory peaks higher or lower than
  reversion peaks?
• How many ways are there to become resistant? How
  many ways to compensate?

antibiotic absent
resistant-types
sensitive wild-type
antibiotic present
resistant-types
?
sensitive wild-type
?
?
?
compensated resistants
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The Problem of Drug Resistance

• Lecture Outline
• Antibiotics resistance
• Costs Reversion Compensation
• Antibiotics Adaptive Landscapes
• Predicting Resistance
• Summary

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Evolution Done Wright

• Two basic assumptions
• Some genetic epistasis leading to distinct
  peaks in the landscape
• A metapopulation of semi-isolated sparsely
  populated subpopulations
• Migration is low between subpopulations, but
  present
• Genetic drift occurs within demes

Phase 1 Subpopulations drift over the adaptive
landscape Phase 2 Selection drives
subpopulations to new peaks Phase 3
Competition between subpopulations where the
most fit pulls the metapopulation onto its
adaptive peak
Fishers theory is one of complete and direct
control by natural selection while I attribute
greatest immediate importance to the effects of
incomplete isolation (Wright, 1931 as quoted
in Provine, 1986)
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Resistance in the Balance
Phase 1 Demes drift over the adaptive
landscape Phase 2 Selection drives demes to
new peaks Phase 3 Interdemic competition where
the most fit deme pulls the metapopulation onto
its adaptive peak
Population structure allows a more thorough
exploration of the adaptive landscape and thus
the ascent of a higher peak globally.
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Extending the Metaphor
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The Role of Population Structure
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Simulating Population Structure

• The population need not be structured into
  discrete subpopulations for the discovery of
  higher peaks.
• Imagine that individual genotypes live on a
  lattice and can reproduce with either global or
  local dispersal.
• If the adaptive landscape is rugged and the
  population starts off in a valley, then the
  following predictions can be made
• Under global dispersal, a new mutation that
  improves fitness quickly takes over the
  population. It is likely that this selective
  sweep moves the population to a sub-optimal peak.
• Under local dispersal, a new mutation that
  improves fitness slowly spreads through the
  population. It is possible that an even better
  mutation may be discovered during this selective
  creep.

local
global
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Antibiotics as a Test Case
It would clearly be desirableto conduct
selection experiments in subdivided and mass
populations, making sure that each selection
regime is replicated so that any treatment
effects can be discerned. (Coyne et al., 1997)
1) Obtain several rifampicin resistant strains in
E. coli
2) Place each strain in an environment with
structure (local dispersal) and no structure
(global dispersal) without rifampicin
3) Track the average fitness in each treatment
Media Rifampicin
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Slow and Steady Wins the Race
Theoretical Predictions
Lab Results




Hypothesis A structured antibiotic resistant
population is more likely to find higher fitness
mutations (be they reversions or compensations)
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Not a Creature Was Stirring

• Another group of researchers allowed
  antibiotic-resistant bacteria to evolve over many
  generations in both a flask (in vitro) and in a
  mouse (in vivo). Their results were the
  following

?
Take 5 minutes to talk about the
following Propose some alternative hypotheses
to explain the differences between the rates of
reversion in vitro versus in vivo. How would you
experimentally distinguish your hypotheses?
?
?
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The Problem of Drug Resistance

• Lecture Outline
• Antibiotics resistance
• Costs Reversion Compensation
• Antibiotics Adaptive Landscapes
• Predicting Resistance
• Summary

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Predicting Evolution

• Miriam Barlow and Barry Hall are developing a
  technique to predict the likely paths of
  antibiotic resistance.
• They start with a gene that currently does not
  confer high resistance (e.g., TEM-1 b lactamase
  does not hydrolyze modern cephalosporins).
• Next, they produce many mutant versions of the
  gene through error prone PCR.
• Then, they introduce these mutant genes into
  bacterial cells.
• Next, they grow up this population of mutants in
  a gradient of antibiotic and select cells from
  the highest drug concentration.
• They isolate the resistance gene and begin the
  process anew. After a few rounds of this cycle,
  they sometimes have a gene that confers high
  levels of resistance.

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The Barlow-Hall Method

• How well does this in vitro method predict
  natural antibiotic resistant mutations?
• Using this method on TEM alleles, the four most
  common amino acid substitutions found in vitro
  (E104K, R164S, G238S, and E240K) were also the
  four most common amino acid substitutions found
  in naturally occurring extended-spectrum TEM
  alleles.
• How does knowledge of the likely evolutionary
  paths help us?
• As we design new drugs, knowing the mutations
  likely to generate resistance may help us discern
  tradeoffs between resistance to different drugs.
• That is, we may be able to map those regions of
  genome space (a HUGE space) that engender
  resistance to drug A and those regions that
  engender resistance to drug B. If these regions
  do not overlap, then we may be able to trap our
  bacterium by simultaneous drug use.
• Some evidence of tradeoffs between cefepime and
  cefuroxime.

types resistant to drug A
types resistant to drug B
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The Problem of Drug Resistance

• Lecture Outline
• Antibiotics resistance
• Costs Reversion Compensation
• Antibiotics Adaptive Landscapes
• Predicting Resistance
• Summary

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Summary

• Antibiotic resistance is a serious public health
  problem. Multi-drug resistance is particularly
  worrying.
• Understanding the ecological and evolutionary
  consequences of resistance (e.g., fitness costs,
  probability of reversion versus compensation) can
  actually inform epidemiological thinking (e.g.,
  in the case of TB).
• Antibiotic resistance also serves as an ideal
  testing ground to explore critical issues within
  evolutionary biology (issues that concerned
  Wright and Fisher), including the shape of
  adaptive landscapes, the role of population
  structure, and the constraints on evolutionary
  trajectories.
• One exciting area (from both practical and
  academic perspectives) is the prospect of
  predicting specific evolutionary trajectories
  engendering drug resistance and using this
  information to design more effective treatment.

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