Abstract
The rise of antibiotic resistance in many bacterial pathogens has been
driven by the spread of a few successful strains, suggesting that some
bacteria are genetically pre-disposed to evolving resistance. Here, we
test this hypothesis by challenging a diverse set of 222 isolates of
Staphylococcus aureus with the antibiotic ciprofloxacin in a
large-scale evolution experiment. We find that a single efflux pump,
norA, causes widespread variation in evolvability across isolates.
Elevated norA expression potentiates evolution by increasing the
fitness benefit provided by DNA topoisomerase mutations under
ciprofloxacin treatment. Amplification of norA provides a further
mechanism of rapid evolution in isolates from the CC398 lineage.
Crucially, chemical inhibition of NorA effectively prevents the
evolution of resistance in all isolates. Our study shows that
pre-existing genetic diversity plays a key role in shaping resistance
evolution, and it may be possible to predict which strains are likely
to evolve resistance and to optimize inhibitor use to prevent this
outcome.
Subject terms: Experimental evolution, Bacterial genetics,
Antimicrobial resistance, Bacterial genomics
__________________________________________________________________
Some bacterial lineages appear to be pre-disposed to evolving
antibiotic resistance. Here, the authors show that differential
expression of an efflux pump causes widespread variation in
evolvability across Staphylococcus aureus isolates, and chemical
inhibition of the pump prevents resistance evolution.
Introduction
Infections caused by antibiotic resistant bacteria are currently
estimated to cause ~700,000 deaths per year, and this mortality rate is
predicted to increase to 10 million per year by 2050^[32]1. Given this
threat, resistance has been identified as one of the most important
challenges to human health by a wide variety of national and
international bodies, including the WHO, the G8 and the IMF. To solve
this crisis, we require new antimicrobials to treat infections caused
by resistant pathogens and new approaches to predict and prevent the
spread of resistance in pathogen populations^[33]2–[34]4.
The increase in antibiotic resistance in many pathogens has been driven
by the spread of a relatively small number of very successful
antibiotic resistant lineages^[35]5–[36]10. One explanation for this
pattern is that these successful lineages are simply those that, by
chance, successfully acquire rare antibiotic resistance genes by
mutation or horizontal gene transfer^[37]11,[38]12. Alternatively, it
is possible that some strains of bacteria are more likely to evolve
resistance than others, for example because they have an elevated
mutation rate^[39]13, or because they carry ‘potentiator’ genes that
open up new genetic paths to evolving resistance^[40]14,[41]15. If so,
it may be possible to identify strains of bacteria that are at high
risk of evolving resistance to antibiotics, and to change antibiotic
usage to prevent this outcome and associated treatment failure^[42]16.
In this paper, we investigate genomic drivers of evolvability using
comparative experimental evolution. In this approach, many bacterial
‘parental’ strains are challenged with a common selective pressure
using controlled and highly replicated in vitro evolution experiments.
Following the trajectory of replicate selection lines after antibiotic
exposure makes it possible to estimate the evolvability of each strain,
and downstream phenotypic and genomic analyses are used to characterize
evolved populations^[43]14,[44]17. This approach makes it possible to
address three separate questions: (i) Does the ability to evolve
antibiotic resistance differ between bacterial strains? (ii) What are
the underlying mechanisms of resistance evolution? (iii) How does
genome content determine the rate and mechanisms of resistance
evolution?
We applied this approach at a very large scale by challenging a diverse
collection of 222 parental strains of Staphylococcus aureus with
ciprofloxacin using a highly replicated selection experiment. Parental
strains were sampled from a large collection of nasal carriage and
bacteraemia isolates of S. aureus collected at hospitals in Oxford and
Brighton, UK^[45]18, and were chosen to capture a diverse set of
clonal-complexes of human-associated S. aureus. We chose to focus on
ciprofloxacin because the evolution of ciprofloxacin resistance has
played a key role in the success of MRSA lineages^[46]19, and has been
associated with poor clinical outcomes for patients infected with CC22
S. aureus^[47]20.
Results
Evolution of ciprofloxacin resistance across S. aureus
We serially passaged 12 replicate populations of 222 parental strains
of S. aureus into fresh culture medium supplemented with the clinical
breakpoint concentration of ciprofloxacin (1 mg l^−1) for 5 days and
recorded bacterial density over time (Fig. [48]1a, b and Supplementary
Fig. [49]1). All of the parental strains were ciprofloxacin sensitive
according to EUCAST clinical breakpoint (MIC < 1 mg l^−1) and we
initiated our populations with an inoculum small enough (~3 × 10^5
cells) to virtually guarantee that no pre-existing resistance mutations
were present at the outset of the experiment (cip^R mutation rate
5.1 × 10^−9 per cell division, 95% CI = [3.7 × 10^−9, 6.7 × 10^−9]).
Conventional antibiotic treatment strategies rely on using large doses
of antibiotics to clear pathogen populations, and this simple
experimental design seeks to capture this by creating a scenario in
which populations must either evolve resistance or face extinction.
Fig. 1. Experimental evolution of ciprofloxacin resistance.
[50]Fig. 1
[51]Open in a new tab
a Maximum-likelihood phylogeny of S. aureus strains included in this
study. The tree was constructed using a whole-genome alignment of 222
strains mapped to the S. aureus MRSA252 reference genome and corrected
for recombination. b Population growth during experimental evolution.
Five heatmaps show optical density (λ = 595) of bacterial populations
at the end of each transfer. The optical density varies from low (no
growth, OD[595] < 0.08, black) to high density (high growth,
OD[595] > 1, bright yellow). In each heatmap, the columns correspond to
12 replicate populations, and the rows correspond to 222 strains. c The
correlation of population survival and intrinsic resistance in 14
phylogenetic clusters. Each data point represents one strain where
population survival is the proportion of replicate populations that
evolved resistance, and intrinsic resistance is IC[50] (half growth
inhibition dose) of a parental strain. Colour and shape for each strain
indicate MLST (multilocus sequence type). An open circle is shown when
MLST could not be determined. 222 strains were assigned to 14
phylogenetic clusters based on a genetic distance matrix obtained from
the phylogenetic tree in (a). The black curves show a model fit for the
logistic regression between survival and intrinsic resistance across
all 222 strains (the same for all clusters, GLM: χ^2 = 393.93,
d.f. = 1, residual d.f. = 220, p < 2.2e−16), and the red curves show
cluster-specific effects. Post hoc tests for cluster-specific effects
are shown in Supplementary Table [52]6.
Bacterial population density declined at the start of the experiment
due to the bactericidal effects of ciprofloxacin and the population
bottlenecking imposed by serially passaging cultures. However,
population density eventually recovered in a subset (1075 of 2664; 40%)
of cultures, suggesting that these populations had expanded due to the
de novo evolution of ciprofloxacin resistance during our experiment. To
test this idea, we measured the ciprofloxacin MIC for 83 populations
that recovered, each derived from a different parental strain
(Supplementary Fig. [53]2). All evolved populations had an
MIC > 1 mg l^−1, demonstrating that population recovery was driven by
the evolution of resistance. Therefore, we measured the evolvability of
ciprofloxacin resistance in the parental strains as the fraction of
populations that survived until the end of the selection experiment.
Our selection experiment revealed striking variation in evolvability
across S. aureus; for example, resistance always evolved in 24 strains,
whereas resistance never evolved in 39 strains (Supplementary
Fig. [54]3a).
All else being equal, strains with a higher initial resistance to
ciprofloxacin should have a greater opportunity to evolve resistance to
a fixed dose of ciprofloxacin. For example, populations of strains with
higher initial resistance should decline more slowly under
ciprofloxacin treatment, allowing more opportunity for the emergence of
novel ciprofloxacin resistance mutations^[55]21. To test this
hypothesis, we measured the growth of the parental strains across a
fine gradient of ciprofloxacin concentrations, and used growth data to
calculate a ciprofloxacin MIC and IC[50] for each strain. Although the
parental strains were all ciprofloxacin sensitive with respect to the
EUCAST clinical breakpoint (i.e. MIC ≤ 1 mg l^−1), we found subtle and
quantitative variation in initial resistance between the parental
strains—for the rest of the manuscript we refer to this variation as
the intrinsic resistance of the parental strains (Supplementary
Fig. [56]4).
Evolvability increased with intrinsic ciprofloxacin resistance, and
intrinsic resistance accounts for 27% of the variation in evolvability
between parental strains (Pearson’s correlation r = 0.55, N = 222,
P = 2e−18; Supplementary Table [57]1). One interesting insight from
this analysis is that small differences in intrinsic resistance between
strains were associated with large differences in evolvability. For
example, using a logistic regression we estimated that a strain with
IC[50] = 0.12 mg l^−1 (median across all strains) would have a 0.36
probability of evolving resistance. Decreasing or increasing the IC[50]
by only 0.1 mg l^−1 (equivalent to 1/10 of the selection dose) would
change the predicted evolvability to 0.10 or 0.72, correspondingly
(Supplementary Fig. [58]3b, Supplementary Table [59]1, [60]2). In
contrast, there was no correlation between the resistance (i.e. IC[50])
of evolved populations and their parental strains, suggesting that the
mechanisms of high level resistance that evolved during the selection
experiment were independent of the intrinsic resistance of the parental
strains (Pearson’s correlation r = −0.03, N = 83, P = 0.7989).
It is also possible that some strains of S. aureus are genetically
pre-disposed to evolving resistance, for example because they have a
high mutation rate^[61]13,[62]22, or alternative mechanisms for
evolving resistance^[63]14. To test if strains belonging to different
lineages of S. aureus evolved resistance at different rates, we grouped
all parental strains into 14 non-overlapping clusters based on genetic
distance estimated from whole genome data (see
“Methods”)^[64]23,[65]24. We chose to focus on these clusters, rather
than pre-defined clonal complexes , because some clonal complexes, such
as CC1 and CC8 were very prevalent in our parental strains, whereas
other clonal complexes were represented by only few strains, making it
difficult to accurately quantify variability within and between clonal
complexes (Supplementary Tables [66]3 and [67]4). This sampling bias
was not deliberate; rather, our pool of parental strains was skewed
towards dominant ciprofloxacin-sensitive strains found in the UK.
Evolvability varied significantly between clusters, and among-cluster
variation accounted for an additional 16.6% of the variation in
evolvability (Fig. [68]1c, Supplementary Tables [69]1–[70]3). This
effect was largely driven by the fact that clusters with high levels of
intrinsic resistance also had high evolvability (Supplementary
Fig. [71]5). However, we found significant variation in evolvability
between clusters after correcting for intrinsic resistance, implying
that some strains of S. aureus have elevated evolvability that cannot
be explained simply by high intrinsic resistance (likelihood ratio test
χ^2 = 187.13, d.f. = 13, P = 5.94e−33). For example, strains from
cluster 10, which is made up CC398, evolved resistance at a much higher
rate than would have been expected based on their intrinsic resistance
(Supplementary Table [72]5, cluster 10, Supplementary Fig. [73]5).
Genomic basis of resistance evolution
One simple hypothesis to explain variation in evolvability between
clusters is that some strains might have access to evolutionary paths
to ciprofloxacin resistance that are not accessible to
others^[74]14,[75]15. To test this hypothesis, we sequenced the genome
of a single evolved population from each of 121 parental strains that
spanned the spectrum of evolvability.
The canonical mechanism for S. aureus to evolve ciprofloxacin
resistance is by point mutations that alter ciprofloxacin targets,
including topoisomerase IV (grlA, grlB) and DNA gyrase (gyrA,
gyrB)^[76]25,[77]26. Most (106/121; 88%) evolved populations had a
single mutation in these established targets (grlA, n = 100; grlB,
n = 6; Fig. [78]2a) and the most common SNPs in evolved populations,
such as grlA E84K and grlA S80F/Y, are often found in ciprofloxacin
resistant clinical isolates.
Fig. 2. Genomic basis of evolved ciprofloxacin resistance.
[79]Fig. 2
[80]Open in a new tab
a Resistance mutations in the evolved S. aureus populations identified
by whole-genome sequencing (N = 121). The panels shows the identified
mutations in gyrA, grlB and grlA (red) or the amplification of norA
gene (blue). The populations are ranked by the evolvability of their
parental strains shown as barplots on top of the panel. b Mutation rate
in high and low evolvability strains. We measured the mutation rate to
rifampicin resistance using a Luria-Delbruck fluctuation test. Lines in
the figure connect pairs of high and low evolvability strains (N = 11
pairs). Two-sided Wilcoxon signed-rank test: W = 0.8311, P = 0.8311,
N = 12. c Copy number across sites spanning the 7239 bp region that is
amplified in ST3535 and ST291 evolved strains. Copy number was
calculated by summing the number of reads per site, normalized by the
mean sequencing depth across all sites mapping to the ST291 reference
genome, and smoothed using a generalized additive model. Gene
annotations are shown below: yellow = ISSau1 transposases; blue = norA.
We found very few mutations (n = 36; =0.30 mutations per population)
outside of these known ciprofloxacin resistance genes, and two lines of
evidence suggest that the majority of these mutations were neutral with
respect to ciprofloxacin-mediated selection. Strong selection for
resistance consistently leads to parallel evolution in key genes
involved in antibiotic resistance^[81]14,[82]27–[83]30, but we found no
evidence of parallel evolution in genes other than grlA and grlB.
Second, we compared the ratio of replacement to silent mutations in
proteins across the genome, under the assumption that positive
selection leads to an excess of replacement mutations that alter
protein function relative to what we would expect from spontaneous
mutation alone^[84]31. Replacement mutations (n = 33) were more common
than silent (n = 3) mutations, but the excess of replacement mutations
was only marginally greater than the neutral expectation
(K[a]/K[s] = 2.80; N = 36; P = 0.095), suggesting that many non-target
site mutations were neutral mutations that hitch-hiked to high
frequency with adaptive resistance mutations. The key insight from this
analysis is that resistance usually evolved through SNPs in
well-defined ciprofloxacin targets, demonstrating a common evolutionary
path to resistance in both high and low evolvability strains.
Given the key role of SNPs in resistance, variation in the underlying
mutation rate might drive differences in evolvability between strains,
as is the case in M. tuberculosis^[85]13. To test this hypothesis, we
measured the mutation rate of pairs of high and low evolvability
strains sampled across the S. aureus phylogeny. Mutation rate varied
substantially across strains, but high evolvability was not associated
with an elevated spontaneous mutation rate (Fig. [86]2b, two-sided
Wilcoxon signed-rank test; P = 0.83, N = 12). Furthermore, we found no
evidence of an increased substitution rate in high evolvability strains
during the selection experiment (Supplementary Fig. [87]6, W = 273.5,
P = 0.16, two-sided Mann–Whitney U test). Although mutation rate varies
between ancestral strains, we found no evidence that high evolvability
was associated with hypermutator strains.
One of the most conspicuous cases of high evolvability is the ST291
strains from clonal complex CC398. All eight strains from this group
evolved resistance at a high rate, but only 1/8 evolved populations had
a classical resistance SNP. Instead, the evolved populations from ST291
lineage carried 3–24-fold amplifications of a ~7 kb region of the
chromosome that includes norA (Fig. [88]2c), an efflux pump that
contributes to the intrinsic resistance of S. aureus towards
ciprofloxacin^[89]32,[90]33. Although the extent of norA amplification
was impressive, the resistance of evolved populations with norA
amplification (median MIC = 8 mg l^−1; n = 7) was only marginally
higher than the resistance of populations with topoisomerase
substitutions (median MIC = 4 mg l^−1; N = 69; two-sided Wilcoxon rank
sum test W = 138.5, P = 0.0474).
The amplified region is flanked by two homologous copies of an IS30
family transposase (ISSau1), suggesting that amplification could have
been caused by either transposition to different sites in the genome or
tandem amplification driven by the homologous copies of ISSau1^[91]34.
To discriminate between these possibilities, we used ISmapper^[92]35 to
search for new transposon insertion sites in the chromosome. We did not
detect any new ISSau1 insertion sites in the evolved populations,
demonstrating that tandem amplification, which can occur at a much
higher rate than point mutations^[93]36,[94]37, drove the increase in
norA copy number. While the ISSAu1 transposon is also found in a few
strains outside of CC398 (Supplementary Fig. [95]7), we speculate that
norA amplification is not observed in those strains because norA is not
flanked by nearby copies of ISSAu1, as determined by re-analysing the
genomes of parental strains.
Given the uniform selective pressure imposed by our experiment, we were
surprised by the extent of variation in ISSau1-mediated gene
amplification. All of the evolved populations with gene amplification
had increased ciprofloxacin MIC, but ciprofloxacin resistance was not
correlated with norA copy number (Pearson’s correlation r = −0.5733,
N = 7, P = 0.1374), suggesting that selection for resistance does not
explain variation in the extent of norA gene amplification. Gene
amplification is often associated with fitness costs^[96]37, suggesting
that selection to minimize the cost of resistance may drive variation
in gene amplification. However, we found no detectable costs of gene
amplification, suggesting that selection for high growth rate did not
shape variation in norA copy number (Supplementary Fig. [97]8,
two-sided Wilcoxon signed-rank test, N = 16, P = 0.3125).
In summary, whole genome sequencing allowed us to uncover the
mechanistic basis of evolved ciprofloxacin resistance in
(114/121 = 94%) of evolved populations. Most strains of S. aureus
evolved ciprofloxacin resistance via canonical mutations in DNA
topoisomerase, albeit at different rates. In contrast, strains from
CC398 evolved resistance at a very high rate via a different mechanism
involving amplification of the norA efflux pump gene mediated by a
lineage-specific IS element. We found no evidence of parallel evolution
in the remaining seven strains, suggesting that they acquired less
common mechanisms of ciprofloxacin resistance (see a list of mutations
in Supplementary Data [98]2).
Transcriptomic insights into high evolvability
Sequencing the genomes of evolved populations does not provide any
obvious insights into why the rate of evolution of resistance by target
alteration varied so widely among non-CC398 strains. One possible
solution to this problem is that ‘potentiator’ genes that alter the
fitness effects of topoisomerase mutations may underpin variation in
evolvability in non-CC398 strains. To search for candidate potentiator
genes, we sequenced the transcriptomes of 14 pairs of high and low
evolvability parental strains after exposure to ciprofloxacin. These
pairs of parental strains were sampled from different parts of the
phylogeny by choosing pairs of strains which are closely related (based
on genetic distance) yet showed a striking difference in their
evolvability (survival ≥ 9/12 and ≤1/12, Supplementary Table [99]6).
The goal of this paired design was to identify genes that are
consistently associated with high evolvability across a range of
genetic backgrounds. Gene expression was always measured after 1.5 h of
exposure to 1 mg l^−1 of ciprofloxacin to match the conditions of the
evolution experiment, and our transcriptome experiment did not measure
basal gene expression in the absence of ciprofloxacin stress^[100]38.
In total, we identified 179 genes that were differentially expressed
between high and low evolvability parental strains (Fig. [101]3a;
Supplementary Data [102]3). Ciprofloxacin induces the SOS response,
which provides both protection against ciprofloxacin and increased
mutagenesis^[103]39, making SOS expression an obvious candidate
mechanism to potentiate resistance evolution^[104]38. The SOS regulon
was expressed in all strains, but there was no difference in the
expression level of SOS regulated genes between high and low
evolvability strains (Supplementary Table [105]7). Instead,
overexpressed genes in high evolvability strains were enriched for
metabolic functions, while genes that were overexpressed in low
evolvability strains were enriched for DNA repair and nucleotide
biosynthesis, which is consistent with the DNA damage caused by
ciprofloxacin treatment (Supplementary Data [106]4). The only
overexpressed gene in high evolvability strains with a known role in
resistance was norA, suggesting that this efflux pump might play a very
general role in the evolution of ciprofloxacin resistance across S.
aureus (Fig. [107]3b).
Fig. 3. Gene expression analysis.
[108]Fig. 3
[109]Open in a new tab
a Plotted points show the average difference (high evolvability−low
evolvability) in gene expression between 14 pairs of high and low
evolvability strains. Gene expression was measured after 1.5 h of
exposure to ciprofloxacin (1 mg l^−1) and each point represents a gene
in the MRSA252 transcriptome (the number of genes is n = 2047).
Significantly differentially expressed genes are coloured red
(p < 0.05, two-sided Wald tests) and norA is coloured blue. P-values
were adjusted using Benjamini-Hochberg method. b The expression of norA
in low and high evolvability strains. The read counts for the norA gene
were normalised by sequencing depth. Pairs of strains are connected
with a line (the number of pairs was N = 14). Two-sided Wald test:
log[2] fold-change = 0.979, standard error = 0.246, t = 3.979, adjusted
p = 0.006802703).
Testing the ability of norA to potentiate resistance evolution
To directly test the role of norA expression in evolution, we cloned
norA into RN4220, a genetically tractable model strain with low
evolvability. Overexpressing norA from its native promoter marginally
increased ciprofloxacin resistance, as we would expect given the
established role of this pump in exporting ciprofloxacin from the
cytoplasm. However, this effect was very weak, and norA overexpression
was not actually sufficient to increase the MIC of RN4220 above the
clinical break-point concentration of 1 mg l^−1 (Fig. [110]4a,
Supplementary Table [111]8). To test the role of elevated norA
expression in evolution, we repeated our evolution experiment by
passaging 40 replicate cultures of strain RN4220 in ciprofloxacin
supplemented media under basal or elevated levels of norA expression.
In contrast to the subtle effect of norA overexpression on
ciprofloxacin resistance, we found that norA overexpression had a
dramatic effect on population survival under sustained ciprofloxacin
treatment, transforming RN4220 from a low evolvability (9/40
populations) to high evolvability (40/40 populations) strain
(Fig. [112]4b; Supplementary Tables [113]9, [114]10).
Fig. 4. The role of norA in resistance evolution.
[115]Fig. 4
[116]Open in a new tab
a The effect of norA overexpression on ciprofloxacin resistance.
Resistance was measured in the RN4220 cells overexpressing norA from
vector pRMC2 under a native promoter (red), compared to an pRMC2 empty
vector control (grey) and a vector-free control (blue). N = 3
independent cultures were used per treatment per concentration.
Dose-response curves show model fit from the analysis presented in
Supplementary Table [117]8. b The effect of norA overexpression on the
evolution of ciprofloxacin resistance. Optical density (λ = 595) was
measured for five daily transfers with 1 mg l^−1 of ciprofloxacin in
RN4220 cells overexpressing norA from the pRMC2-norA vector (red),
cells with the empty pRMC2 vector (blue) and the cells without the
vector (grey). N = 40 independent cultures were used for each type of
cells. Statistical analysis in shown in Supplementary Table [118]10. c
The effect of reserpine on intrinsic resistance. Intrinsic resistance
to ciprofloxacin (IC[50], mg l^−1) was determined for a representative
set of 27 strains in the presence (y-axis) or absence of 33 µM
reserpine (x-axis) (N = 5 per dose/reserpine combination). Two-sided
Wilcoxon signed-rank test: W = 308, d.f. = 26, p = 0.003. d
Evolvability was determined for the same set of 27 strains with 33 µM
reserpine (y-axis) or without reserpine (x-axis). Evolvability was
measured as the probability of population survival after 5 serial
transfers at 1 mg l^−1 of ciprofloxacin (N = 16 replicate populations
for each strain/reserpine combination). Two-sided Wilcoxon signed-rank
test: W = 226, N = 27, p-value = 0.000128.
Despite the recent progress in S. aureus forward genetics
methods^[119]40, it remains a difficult task to test the importance of
norA across many S. aureus strains. To overcome this problem, we
re-assayed the intrinsic resistance of a sub-set of our parental
strains (N = 27) in the presence and absence of reserpine, a chemical
inhibitor of NorA^[120]41 (Supplementary Fig. [121]9a, Supplementary
Table [122]11). Reserpine treatment reduced intrinsic resistance to
ciprofloxacin (Fig. [123]4c). Although this impact of reserpine on
intrinsic resistance was evident, it translated on average into less
than twofold reduction (IC[50]/IC[50 RES] = 1.31±0.47 s.d.;
MIC/MIC[RES] = 1.52 ± 0.49 s.d.), with a stronger inhibition of strains
with high intrinsic resistance (Spearman’s correlation ρ = 0.76,
p = 7.4e−06, n = 27), suggesting that this higher intrinsic resistance
is at least partly based on the efflux of ciprofloxacin.
To understand the evolutionary consequence of norA expression more
broadly, we repeated our evolution experiment by passaging 16 replicate
cultures of these 27 strains in media containing ciprofloxacin, or both
ciprofloxacin and reserpine (Supplementary Fig. [124]9b; Supplementary
Tables [125]12, [126]13). The overall effect of reserpine was to
suppress the evolution of resistance (two-sided Wilcoxon signed-rank
test: W = 226, N = 27, P = 0.000128). Reserpine had little effect on
low evolvability strains, but it almost completely suppressed the
evolution of ciprofloxacin resistance in high evolvability strains,
including strains from CC398 (Fig. [127]4d). Collectively, these
results show that norA expression modulates the intrinsic resistance of
S. aureus to ciprofloxacin and potentiates the subsequent evolution of
clinically relevant levels of resistance. These findings provide a
simple explanation for the positive correlation between intrinsic
ciprofloxacin resistance and evolvability that occurs in S. aureus
(Fig. [128]1).
Evolutionary consequences of norA expression
The most obvious effect of norA expression is to provide protection
against ciprofloxacin. This protective effect of norA could accelerate
the evolution of resistance by providing populations with more time to
generate resistance mutations until population
extinction^[129]42,[130]43. To test the plausibility of this mechanism,
we measured the population dynamics of strain RN4220 under
ciprofloxacin treatment (Fig. [131]5a). As expected, increased norA
expression reduced the rate of population decline under ciprofloxacin
treatment. However, the magnitude of this effect was marginal—norA
overexpression simply delayed the onset of ciprofloxacin-induced cell
mortality by ~1 h. This weak effect of norA overexpression on cell
viability further highlights the fact that this efflux pump makes a
small contribution to the intrinsic resistance of S. aureus to high
doses of ciprofloxacin (i.e. 1 mg l^−1; Fig. [132]4a). Importantly, it
is very difficult to reconcile this marginal effect of norA on cell
viability with the massive effect of norA overexpression on
evolvability (Fig. [133]4b), suggesting that norA expression does not
accelerate evolution by increasing the rate of appearance of resistance
mutations.
Fig. 5. The mechanism of norA potentiation.
[134]Fig. 5
[135]Open in a new tab
a Exponentially growing cells were exposed to 1 mg l^−1 of
ciprofloxacin and viable cells counts were estimated by plating on TSB
agar. Four treatments were compared: (i) norA overexpression = red
solid line, (ii) norA overexpression and reserpine (33 μM)
inhibition = orange solid line, (iii) empty vector control = grey line,
and (iv) no vector control = blue line. In addition, cell density was
measured in treatments (i) and (ii) without ciprofloxacin (red
dash-dotted line and orange dash-dotted line, correspondingly). For
each time-point, six independent replicates per treatment were measured
(with the exception of the pRCM-norA cells in ciprofloxacin at 0 h
which had N = 5). The lines show model fit for polynomial regression
(F[23, 191] = 622.6, p-value < 2.2e−16). Post-hoc comparisons are shown
in Supplementary Table [136]14. b Growth rate of grlA mutants with or
without norA overexpression. We estimated the growth rate of the RN4220
wild type (WT) and three independently obtained mutants carrying each
grlA substitution in the presence of 1 mg l^−1 of ciprofloxacin. Growth
rate in cells carrying pRMC2-norA (red) or cells without the vector
(blue) was determined using growth curves shown in Supplementary
Fig. [137]10b. Black horizontal lines show the mean growth rate of
independent cultures (N = 6 per mutant/treatment combination for A116E,
E84K, S80F and S80Y, N = 11 for WT pRMC2-norA and N = 12 for WT no
vector). Paired two-sided t-test comparing the means in the mutants
with and without pRMC2-norA: t = 11.958, d.f. = 11, p = 1.206e−07.
Two-sided t-test comparing pRMC2-norA and no vector control in WT:
t = 0.96281, d.f. = 12.136, p = 0.3544. c Representative dose-response
experiments for grlA mutants. Red lines show mean optical density with
norA overexpression, and blue lines show mean density without
overexpression. Black arrow shows the concentration used during
experimental evolution. Five independent cultures were used per
mutant/treatment/concentration. The results for all mutants are shown
in Supplementary Fig. [138]10a. The difference of means between
pRMC2-norA and no vector cells at 1 mg l^−1 for all mutants was tested
using two-sided paired t- test: t = −18.712, P = 1.09e−09, d.f. = 11.
The appearance of a ciprofloxacin resistance mutation in a population
does not guarantee that a population will successfully evolve
resistance, because stochastic processes can lead to the extinction of
small populations of resistant mutants, for example during population
bottlenecks^[139]44. All else being equal, mutants with a high fitness
upon antibiotic exposure should be more likely to successfully expand
their populations and cause populations to evolve elevated resistance.
To test the impact of norA expression on fitness, we measured the
growth rate of RN4220 carrying key ciprofloxacin resistance SNPs under
basal and elevated levels of norA expression (Supplementary
Fig. [140]10). Elevated norA expression did not increase growth rate in
wild-type RN4220, which is consistent with our previous ciprofloxacin
susceptibility assays (Fig. [141]4a). In contrast, increased norA
expression led to large increases in growth rate in ciprofloxacin
resistant mutants, demonstrating positive epistasis between target
alteration and antibiotic efflux (Fig. [142]5b).
norA expression could increase the fitness benefit provided by
resistance mutations in the presence of ciprofloxacin by reducing the
fitness costs of topoisomerase substitutions and/or increasing the
protective effect of topoisomerase mutations. To test this hypothesis,
we measured the growth of ciprofloxacin resistant mutants under basal
and elevated levels of norA expression across a range of ciprofloxacin
concentrations (Fig. [143]5c). Elevated norA expression did not change
the growth rate of resistant mutants in the absence of antibiotics
(two-sided paired t-test: t = 0.42009, P = 0.6825, N = 12,
Supplementary Fig. [144]10a), providing further evidence that the
expression of this pump has marginal effects on fitness per se (see
Fig. [145]4a and Supplementary Fig. [146]8). In contrast, we found that
elevated norA expression dramatically increased the ability of grlA
mutants to grow at high concentrations of ciprofloxacin (i.e. 1 mg
l^−1, two-sided paired t-test: t = −18.712, P = 1.09e−09, N = 12). In
other words, positive epistasis occurs because ciprofloxacin efflux
mediated by norA and altered topoisomerase structure (i.e. grlA)
interact synergistically to increase resistance to high doses of
ciprofloxacin without imposing any additional fitness burden.
Identifying variants associated with high evolvability
In order to systematically search for genetic variants associated with
high evolvability, we carried out a genome-wide association study
(GWAS) to test for associations between core-genome SNPs and
evolvability across the strains used in this study (Supplementary
data [147]5). The GWAS analysis showed that 16.3% of variation in
evolvability can be explained by genetic variability across strains
(Supplementary Fig. [148]11). However, after controlling for multiple
testing, the GWAS failed to identify any SNPs that show a significant
association with high evolvability.
Given the strong association between norA and evolvability, we then
focused more closely on variants that are likely to be associated with
norA expression and function. All of the strains used in this study are
predicted to carry a functional copy of norA (i.e. no pre-mature stop
codons or frameshift mutations). In line with previous work^[149]45, we
found that the norA coding sequence is polymorphic, and we identified
polymorphisms in a previously characterized norA promoter
region^[150]46–[151]48. However, the P values associated with these
polymorphisms are 1000 times higher than the conservative significance
threshold used in our GWAS analysis, suggesting that these associations
are true negatives. Moreover, we failed to identify any norA variants
associated with high evolvability through manual inspection of our
data.
The expression of norA is known to be repressed by the mgrA
transcription factor^[152]46,[153]49,[154]50, and two lines of evidence
from our transcriptome experiment suggest that mgrA plays a role in
evolvability. First, mgrA was overexpressed in low evolvability strains
(two-sided Wald test: log2 fold-change = 0.885, standard error = 0.206,
t = −4.305, adjusted p = 0.005597, Supplementary data [155]3). Second,
we found a negative correlation between mgrA and norA transcript levels
across 12 of the 14 pairs of high and low evolvability strains
(Supplementary Fig. [156]12, exact binomial test P = 0.00091, N = 14),
suggesting that mgrA represses norA in low evolvability strains.
Although this relationship between norA and mgrA is clear at a
qualitative level, the quantitative correlation between mgrA and norA
transcript levels is weak (Supplementary Fig. [157]12), suggesting that
other regulatory genes and/or post-translational modification of MgrA
play important roles in mediating norA expression^[158]49–[159]51.
Interestingly, mgrA is highly conserved, and we only identified two
polymorphic sites in the strains used in our study. These polymorphisms
showed no evidence of association with evolvability in our GWAS (P
values > 10^5 above conservative threshold), potentially providing
evidence that the connection between mgrA and evolvability is complex.
Discussion
We found that the rate and mechanisms of evolution of ciprofloxacin
resistance vary dramatically across the diversity of S. aureus, an
important human pathogen (Figs. [160]1, [161]2). Studying the evolution
of resistance at this broad scale using a combination of genomic and
transcriptomic approaches allowed us to identify lineages with high
evolvability and genes that potentiate the evolution of resistance,
implying that it is possible to predict the evolution of resistance
from genomic data. Remarkably, a single efflux pump gene (norA) plays a
key role in accelerating the evolution of ciprofloxacin resistance,
either by increasing resistance directly, as in the high evolvability
CC398 lineage, or by increasing the benefit provided by classical
ciprofloxacin resistance mutations that alter DNA topoisomerase.
NorA is a narrow-spectrum efflux pump that is known to contribute to
the intrinsic ciprofloxacin resistance in S. aureus, but has not
previously been linked to clinically relevant levels of
resistance^[162]32,[163]41,[164]52,[165]53. High evolvability strains
of S. aureus show elevated levels of norA expression (Fig. [166]3), and
overexpressing norA in a lab strain dramatically increases evolvability
(Fig. [167]4b) by increasing the protective effect of ‘classical’
ciprofloxacin resistance mutations in grlA (Fig. [168]5b, c).
Inhibiting NorA in clinical isolates leads to a marginal loss of
intrinsic resistance (Fig. [169]4c) and a massive reduction in
evolvability (Fig. [170]4d), suggesting that variation in norA
expression creates a strong association between intrinsic resistance
and evolvability across the diversity of S. aureus (Fig. [171]1).
Interestingly, positive epistasis has been found between ciprofloxacin
resistance SNPs and mutations that increase drug efflux in
Gram-negative bacteria^[172]54–[173]57, suggesting that our findings
may help to explain the evolution of ciprofloxacin resistance across a
broad spectrum of bacterial pathogens where ciprofloxacin resistance
has emerged as an important clinical problem, such as E. coli and P.
aeruginosa. More generally, our findings suggest that more attention
should be given to understanding interactions between resistance
mutations and ‘background’ genetic variation that can epistatically
modify the fitness effects of canonical resistance
mutations^[174]14,[175]30.
Although we have succeeded in linking norA expression to evolvability,
we were not able to determine the underlying genetic basis of high
evolvability outside of CC398. GWAS analysis has promising potential to
uncover the genetic basis of bacterial traits, such as high
resistance^[176]58 or virulence^[177]24, but this approach was unable
to uncover any associations between SNPs and high evolvability. On the
one hand, this lack of significance could be explained by the fact that
high evolvability is driven by SNPs that are unique to individual
lineages of S. aureus, in much the same way as lineage-specific IS
elements potentiate the rapid evolution of resistance in CC398.
Alternatively, it is possible that our analysis simply lacked the
statistical power needed to uncover SNPs that are associated with high
evolvability, perhaps as a result of limited recombination in S.
aureus^[178]59. The negative correlation between the expression of the
mgrA repressor and evolvability suggests that mgrA-mediated repression
of norA expression helps to constrain evolvability, and an important
goal for future work will be to understand the connection between
genetic variation, transcriptional regulation and evolvability in
pathogenic bacteria.
Our study included a number of strains from clonal complex CC398,
containing three sequence types—ST398 (n = 4), ST291 (n = 7) and ST3535
(n = 1). The ST398 strains belong to the human-associated lineage of
ST398^[179]60 and they evolved via mutations in grlA. The ST291 strains
are genetically quite different from ST398 and represent a separate
lineage within CC398^[180]61; they are usually associated with
humans^[181]62, but more recently isolated from
livestock^[182]63,[183]64. These ST291 strains (and the related ST3535
strain) rapidly and repeatedly evolved in response to ciprofloxacin by
ISSau1-mediated tandem amplification of norA^[184]34, allowing them to
increase ciprofloxacin resistance without any detectable fitness cost.
This is perhaps surprising, given that the largest amplifications
increased genome size by about 200 kb, which is equivalent to a ~7%
increase in genome size. However, a number of other studies have found
evidence that S. aureus can acquire novel DNA, such as plasmids and
SCCmec elements, without any additional detectable fitness
burden^[185]65,[186]66. More generally, the high copy number of ISSau1
in CC398 suggests that gene amplification may be an important mechanism
of adaptation to novel environments, such as new host species and
antimicrobials^[187]67.
Whole-genome sequencing of bacterial pathogens is fundamentally
transforming clinical microbiology^[188]68,[189]69, and a key challenge
for this field is to exploit the wealth of data provided by genomic
sequences to better understand bacterial pathogenesis and
epidemiology^[190]3,[191]23,[192]24,[193]70. By uncovering the link
between genotype and evolvability, it should be possible to use
pathogen genomic data to help predict the likelihood that resistance
will evolve during antibiotic treatment and to alter treatment
strategies accordingly. For example, our work suggests that
ciprofloxacin should be used cautiously to treat infections caused by
CC398 (and in particular ST291), due to the high risk of de novo
evolution of resistance. Outside of CC398, measuring the intrinsic
ciprofloxacin resistance of clinical isolates could be used in
conjunction with phylogenetic data obtained from genome sequencing
(Fig. [194]1) to predict the risk of resistance evolution during
treatment. For example, several clusters of strains in Fig. [195]1c
have low evolvability given their intrinsic resistance, making these
strains good candidates for ciprofloxacin treatment. Although we have
focused on ciprofloxacin resistance in S. aureus, it should be possible
to use experimental evolution and genomics to predict the risk of
resistance evolution for other pathogen/drug combinations. This
approach should be particularly useful to predict the evolution of
resistance to novel antimicrobials prior to their introduction into
clinical use^[196]3,[197]71.
Understanding the genetic basis of evolvability also opens up the
possibility of using novel therapies to prevent the evolution of
resistance. For example, we have shown that using an efflux pump
inhibitor can prevent the evolution of resistance by blocking an
important evolutionary path to low costs resistance (see also ref.
^[198]14). Recent work has shown that efflux pumps can also accelerate
resistance evolution by increasing the mutation rate^[199]72 or
facilitating the acquisition of plasmids^[200]73, suggesting that
efflux pump inhibitors may have promising potential to suppress the
evolution of resistance^[201]74 for a large number of combinations of
pathogen and antibiotic.
Methods
Media and reagents
96-well flat-bottom plates (Nunc, 260860) and Mueller-Hinton 2 medium
(MH2 medium, Sigma-Aldrich, 90922) were used for culturing S. aureus,
measuring antibiotic resistance and performing all evolution
experiments. Tryptic Soy Broth (TSB medium; Sigma-Aldrich, 22092) was
used for preparation of competent cells, for selecting transformed
clones and for growing S. aureus prior to DNA isolation. Incubation was
performed at 37 °C and 225 rpm orbital shaking inside a MaxQ 8000
shaking incubator (Thermo Fisher).
Ciprofloxacin (Sigma, 17850) was dissolved in water (5 mg ml^−1) and
stored at −20 °C. The other reagents used in this study were
chloramphenicol (25 mg ml^−1 in ethanol, Acros Organics, 227920250),
ampicillin (50 mg ml^−1 in water, Sigma, A1593), kanamycin sulfate
(25 mg ml^−1 in water, Fisher Chemicals), rifampicin (50 mg ml^−1 in
DMSO, Millipore, 557303), reserpine (10 mg ml^−1 in DMSO,
Sigma-Aldrich, 83580).
S. aureus strains
In total, 222 strains of S. aureus were collected from colonized and
infected patients in Oxford and Brighton, as previously
described^[202]18. To ensure that these isolates were clonal, the
strains were streaked out on TSB agar plates. A single colony was
picked to inoculate overnight culture in TSB broth. The overnight
cultures of 222 strains were mixed with glycerol to a final
concentration of 15% v/v and stored at −80 °C.
Measuring intrinsic resistance by broth microdilution
Intrinsic resistance was determined for 222 strains by exposing five
replicate cultures per strain to 8 doses of ciprofloxacin (>8800
cultures in total). The strains were handled in five batches with up to
60 strains per batch. Five replicate plates were included for each
batch/dose combination, and each plate contained only one replicate of
each strain. In order to minimize the effect of well location, five
different strain layouts were created by randomization. As a result,
every strain was exposed to a given ciprofloxacin concentration in five
different plates and at five different well locations. To control for
contamination, limit excessive evaporation and avoid an edge effect, 36
wells on the edge of each 96-well plate did not contain bacteria.
The strains were recovered from −80 °C stock by growing overnight
cultures for 22 h, diluted 1:100 and randomized across five 96-well
plates using a Precision XS automatic pipetting station (BioTek). The
resulting master plates were used for transferring 10 µl of bacteria to
assay plates containing 190 µl of MH2 broth with ciprofloxacin. The
assay plates were placed into the incubator for 22 h. After incubation
was completed, optical density was measured at OD[595] using a Synergy
2 plate reader (BioTek).
OD[595] values were used to estimate the MIC (minimal inhibitory
concentration) and perform a dose-response analysis. A concentration
was considered inhibitory if 3/5 replicate cultures did not reach a
cut-off value of 0.08 OD[595] including a blank. The median blank value
was 0.042 OD[595] (s.d. = 0.003), however higher values were
occasionally observed due to dust, excessive evaporation, etc. Two
assay plates were excluded from the analysis because of unusually high
variation in control wells (batch 3, dose = 0.1, replicate plate 5, and
batch 4, dose = 0.025, replicate plate 4). In the remaining dataset,
only 2/6406 control wells had OD[595] > 0.08.
For the dose-response analysis, a non-linear 4-parameter model was
fitted:
[MATH: fx=c+d−c1
+exp[b×logx−loge]
, :MATH]
where c is te lower asymptote (i.e. response variable at complete
inhibition), d is the upper asymptote (uninhibited growth), e is an
inflection point equivalent to a half growth inhibition dose (IC[50])
and b is a slope of the curve at the inflection point. Parameter c was
fixed at 0.08 to be consistent with the cut-off value, the remaining 3
parameters were estimated separately for each strain by fitting dose
response curves using the drc package in R^[203]75. The standard errors
for IC[50] were obtained using the coeftest function from the package
lmtest The dose response curves were also used to calculate the area
under a curve (AUC) using the trapz function in the pracma package.
Experimental evolution of resistance
The evolvability of 222 ciprofloxacin-sensitive strains
(MIC ≤1 mg l^−1) was measured by exposing each strain to 1 mg l^−1 for
5 daily transfers. For each strain, 12 replicate populations were
included, amounting to more than 2600 bacterial populations, which were
transferred daily in 96-well plates. Prior to the experiment,
replicates were distributed across the plates so that each plate had a
maximum of one replicate of any strain (except for six plates which had
two replicates for a set of 30 strains). For convenience, the strains
were handled in sets of up to 60 strains. For each set of strains,
three-randomized plate layouts were generated to assign strain
locations within a plate. Each randomization layout was used for only
four replicate plates. As a result, any given strain had replicate
cultures located in 12 plates and in four different well locations (or
in six plates for the set of 30 strains mentioned previously). Wells at
the plate edges (rows A and H, and columns 1 and 12) were used for
blank measurements and as contamination controls.
The strains from −80 °C stock were grown overnight in 200 µl of MH2 (a
single culture per strain, five 96-well plates in total). After 22 h of
incubation, each plate was used to inoculate three fresh plates by
transferring 20 µl of bacteria to 180 µl of MH2. This step was
simultaneously used to randomize the locations of strains within plates
and was performed using a BioTek Precision XS automatic pipetting
station. The resulting 15 plates contained three replicate cultures per
strain and had unique strain layouts. After 20 h at 37 °C, the cultures
were transferred again to fresh plates with MH2 and returned to the
incubator. After the third recovery transfer, 10 µl of culture was
inoculated into MH2 medium containing 190 µl of 1 mg l^−1 of
ciprofloxacin. Each culture was used to establish four replicate
populations resulting in 12 populations per strain. The plates were
incubated for 22 h until the next transfer. In total, five transfers
were performed in MH2 medium with ciprofloxacin. At the end of each
transfer, the optical density at OD[595] was measured. By transfer 5,
most populations had either gone extinct or evolved resistance and had
a high density (more than 90% of surviving populations had an
OD[595] > 0.5). At this point, one more transfer without ciprofloxacin
was performed and the evolved populations were frozen in −80 °C in 15%
glycerol.
Populations were considered to have survived if they had an
OD[595] > 0.08 (including blank) by transfer 5. Only 2/1942 control
populations had an optical density above 0.08, indicating a detectable
but very low error rate due to experimental artefacts and
contamination. In the final dataset, evolvability was defined as the
proportion of survived populations per strain, ranging from 0/12 to
12/12.
To determine whether intrinsic resistance is a good predictor for
evolvability, a generalized linear model was fitted with a binomial
family of distribution of errors. Numbers of survived and extinct
populations per strain were used as a response variable (via the logit
link function) and IC[50] as a continuous covariate. In order to
control for a lineage effect on evolvability, each strain was assigned
to one of 14 phylogenetic clusters. In particular, the cluster package
in R was used to perform PAM-clustering algorithm (“partition around
medoids”, [204]https://cran.r-project.org/package=cluster). The
performance of PAM-clustering was checked using the silhouette
diagnostic plots provided by the same package. Similar clustering
approaches have been used in previous studies to control for a lineage
effect^[205]23,[206]24. Phylogenetic clustering was performed using a
genetic distance matrix calculated from a whole genome tree generated
from sequence data mapped to MRSA252. Cluster identities and their
interaction with the IC[50]-covariate were added to the model as fixed
predictors. The emmeans package in R was used to test whether
cluster-specific effects differed significantly from the effects
calculated for the overall sample.
Ciprofloxacin resistance of evolved populations was determined by broth
microdilution method. Evolved populations were selected to maximize
phylogenetic diversity and variation in evolvability. Each population
was derived from a different parental strain (except strain ERR418532
for which two populations were included). The growth of five replicate
cultures for 83 evolved populations was assayed across eight different
concentrations of ciprofloxacin, ranging from 0 to 32 mg l^−1. The
assays were performed in two blocks using five-randomized plate
layouts. MIC, IC[50], and AUC was calculated using OD[595] after 22 h
of incubation.
DNA extraction and sequencing
DNA was extracted from one representative evolved population for a
subset of strains. In this subset, almost all the strains which had an
evolvability ≤3/12 (n = 48) or ≥ 9/12 (n = 44) were included. Eight
strains were excluded because they either failed to grow or the DNA
concentration was too low for sequencing. In addition, one evolved
population for a representative subset of strains with evolvability
ranging from 4/12 to 8/12 (n = 29) was included, resulting in a total
selection of 121 evolved strains.
Strains were re-grown from −80 °C stock in 2 ml of TSB. Cells were
collected by centrifuging for 5 min at 5000 rpm and re-suspended in
enzymatic digest buffer (20 mM Tris-HCl, 2 mM EDTA, 1.2% Triton-X100,
0.03 mg ml^−1 lysostaphin (Sigma-Aldrich, L7386), 25 mg ml^−1 chicken
egg lysozyme (Sigma-Aldrich, 62970)). After 2–4 h of incubation at
37 °C to digest the cell wall, DNA was extracted using DNeasy Blood &
Tissue kit (Qiagen) following the manufacturer’s protocol for
Gram-positive bacteria. The integrity of genomic DNA was checked on
0.9% agarose gel and the concentration was measured using a QuantiFluor
dsDNA Kit (Promega).
All parental strains were previously sequenced^[207]76 using an
Illumina HiSeq 2000 platform (San Diego, CA, USA) and downloaded from
the European Nucleotide Archive Sequence Read Archive (study accession
number: PRJEB5261). Evolved strains were sequenced using an Illumina
HiSeq 4000 platform with 150 base pair (bp) paired-end reads at the
Oxford Genomics Centre (Wellcome Centre for Human Genetics, University
of Oxford, Oxford, UK). Sequencing of evolved strains yielded a mean
coverage of 302x.
Sequencing reads from both the parental and evolved strains were
trimmed using Trimmomatic v0.36^[208]77. Leading and trailing bases
were trimmed if the Phred quality score was less than 20 and a 4-base
wide sliding window was used to cut reads when the average quality per
base dropped below 15. Any read less than 50 bp long was dropped.
Sequences were mapped to the ST36 reference strain MRSA252 (GenBank
accession no. [209]BX571856.1) using Stampy v1.0.31^[210]78, with an
expected substitution rate of 0.01. Single nucleotide polymorphisms
(SNPs) were called using the SAMtools v1.7^[211]79 mpileup command,
with the following command line options: -F 0.002 -g -t DP -t SP, and
the bcftools v1.7^[212]80 call command with the following command line
options: -m -O v -M -P 0.001 -p 0.5. All SNPs supported by fewer than 5
reads or by more than twice the mean sequencing depth (calculated
across all sites in the genome) were filtered from the consensus FASTA
sequence, which was generated using the bcftools consensus command.
Non-unique regions in the reference genome were identified by self-self
BLAST analysis of the reference with a word size of 28, using the
megablast algorithm in BLAST v2.5.0^[213]81. Such regions represented
5.93% of the genome and were filtered from the consensus FASTA sequence
for each strain. Any base with a heterozygous call under a diploid
model was also filtered. Sequences were assembled into de novo contigs
for each genome using SPAdes v3.11.1 with the -careful mode turned
on^[214]82. Multi-locus sequence typing was performed on the assemblies
using the S. aureus MLST website ([215]https://pubmlst.org) sited at
the University of Oxford^[216]83.
Phylogenetic analysis of full parental sequence dataset
After mapping to the MRSA252 reference genome, genome sequence data
were used to construct a maximum likelihood phylogenetic tree in RAxML
v8.2.9^[217]84, using the GTRCAT model of nucleotide substitution.
Branch lengths were corrected for recombination using
ClonalFrameML^[218]85, with a transition/transversion rate ratio
(kappa) value of 4.04. This value of kappa was estimated from four
independent analyses of subsets of the data (n = 50) in PhyML v
3.3.20170105^[219]86.
Determination of evolved SNPs
Sequence assemblies for the parental strains were annotated using
Prokka 1.12-beta^[220]87. Snippy v4.0-dev2
([221]https://github.com/tseemann/snippy) and breseq v0.33.1^[222]88
were used to identify SNPs between each annotated parental genome and
the sequence reads from its corresponding evolved genome for 121
strains. Snippy uses bwa to align reads to a reference (here, the
assembled parental genome) and FreeBayes to call
variants^[223]89,[224]90. SNPs were required to have a minimum read
mapping quality of 60, minimum base quality of 30 and a minimum
coverage of 30. A lower mapping coverage threshold (15) was used for
SNPs in ancestral isolates due to the lower depth at which these were
sequenced. Snippy does not call SNPs at sites with heterozygous
genotypes, which here represent diversity within the sequenced culture.
This means that any minor variants present in the parental population
that subsequently rose to fixation in the evolved population are
reported as evolved SNPs by Snippy. As such, only those SNPs reported
by both Snippy and breseq, and located at sites without a heterozygous
call in the parental strain, were classified as evolved SNPs. In 15/121
strains, no SNPs were identified in genes for established ciprofloxacin
resistance targets (topoisomerase IV, DNA gyrase, norA). 6/15 strains
were ST291/ST3535, for which resistance is inferred to be conferred by
amplification of norA. Inspection of the variant call format (VCF) file
revealed that four of the remaining nine strains had heterozygous calls
at known ciprofloxacin resistance sites, suggesting that these evolved
populations represented a mix of resistant and susceptible clones.
These strains were, therefore, classified as resistant. No known
resistance mechanism could be identified in five strains.
Copy number estimation of amplified region
Sequence data were remapped to the ST291 reference genome JP80 (GenBank
accession no. [225]AP017922.1) to obtain sequence depth estimates for
the flanking transposase genes (not present in MRSA252). Copy number
was estimated as the total number of good quality reads mapping at each
site, normalized by the mean depth across all sites in the mapped
genome.
Evolutionary analysis of norA
To explore genetic diversity of norA within the dataset, BLAST was used
to identify the norA gene and 250 bp region upstream of norA in the
sequence assembly for each parental strain. Sequences were aligned
using Muscle v3.8.31 and a maximum likelihood phylogenetic tree was
constructed in PhyML using an HKY85 model of nucleotide substitution.
Tree topology improvement was computed using nearest-neighbour
interchange and subtree pruning and regrafting, selecting the best from
both searches. This analysis identified three genetically distinct
clades within the phylogeny, from which clade-specific consensus
sequences were generated by taking the majority allele at each site.
All SNPs within the promoter region for each sequence relative to the
respective clade-specific consensus and occurring at the tips of the
whole genome phylogeny were tested for association with norA
expression, where this was measured. Ten SNPs were identified in total,
five of which were in strains with expression data across all three
clades in the norA phylogenetic tree.
Copy number estimation of ISSau1 in parental strains
Sequence data from all parental strains were mapped to the JP02758_0628
transposase gene located at the 5′ end of the amplified region of the
genome using Stampy. Depth of sequence coverage at each site was
calculated using the samtools depth program. Transposase copy number
was estimated by normalizing the mean sequence depth across all mapped
sites by the mean sequence depth across all sites in the corresponding
genome mapped to MRSA252.
Mapping the genomic location of new copies of transposase gene
The increase in transposase copy number can be a result of tandem
amplification or transposition to a different genomic location. To
differentiate these two mechanisms, the location of the JP02758_0628
transposase gene was mapped in eight parental and eight evolved
strains, in which the transposase amplification was detected. This
analysis was carried out using ISmapper v2.0.1^[226]35. ISMapper takes
unmapped paired reads, maps them to an IS element and, then, identifies
pairs in which only one read is mapped to the IS element
(JP02758_0628). These partially mapped pairs are assumed to be at the
junction of a transposon and its genomic neighbourhood, and later used
to determine transposition sites within a reference genome (JP80,
GenBank accession no. [227]AP017922.1). As a result, a consistent
pattern of JP02758_0628 locations was detected between ancestral and
evolved sequences, identifying no new transposition sites in the
evolved strains and supporting the hypothesis of tandem amplification.
Genome-wide association study
A GWAS was carried out using the bugwas^[228]70 package in R^[229]91.
bugwas uses a linear mixed model to test for phenotype associations
with both SNPs and lineages, while controlling for relatedness between
samples. As input, bugwas requires a sequence alignment, phylogenetic
tree and phenotype data for each sample. While it is possible to
perform a continuous trait GWAS in bugwas, the evolvability phenotype
was not normally distributed and therefore a continuous trait model was
not suitable for this dataset. As such, a binary trait GWAS was
performed by limiting the analysis to low (evolvability ≤2/12) and high
(evolvability ≥9/12) evolvability strains, encoding phenotypes as
either 0 or 1 respectively. All strains with intermediate evolvability
estimates were excluded from the GWAS analysis, leaving a dataset of 96
strains. A sequence alignment for all strains was obtained by mapping
the corresponding sequence data to the MRSA252 reference genome (as
described above). A phylogenetic tree was constructed from this
sequencing alignment in RAxML v8.2.9^[230]84 using the GTRCAT model of
nucleotide substitution. 89,874 biallelic and 8,591 multiallelic SNPs
were tested for association with evolvability and annotated in bugwas
using the MRSA252 reference genome. P-values were calculated using a
likelihood ratio test and a Bonferroni correction was applied.
Transcriptome analysis of parental strains
RNA-Seq analysis was performed using the RNA from 30 parental strains.
Since differences in gene expression may be confounded by phylogenetic
relationship, especially between phylogenetically distant strains,
expression was measured for 15 pairs of closely related high and low
evolvability strains. First, 15 high evolvability parental strains
(evolvability ≥9/12) were chosen to maximize phylogenetic diversity.
For each high evolvability strain, the most closely related low
evolvability strain (evolvability ≤1/12) was identified (Supplementary
Table [231]6). The strains were grown for 16 h overnight in MH2 broth
at 37 °C at 225 rpm, diluted 1:20 in a fresh pre-warmed MH2 and
incubated for an additional 1 h and 20 min until they reached a density
of 0.160–0.170 OD[595]. Ciprofloxacin was added to achieve a final
concentration of 1 mg l^−1. After 1.5 h, the exposure to ciprofloxacin
was stopped by spinning cells for 10 min at 7000 rpm, decanting
supernatant and re-suspending the cells in 200 µl of PBS. Finally,
500 µl of RNA-protect Bacteria Reagent (Qiagen) was added and the cells
were equilibrated at room temperature for 5 min and then frozen at
−80 °C. The cells in RNA-protect solution were thawed, centrifuged for
10 min at 5000 rpm and separated from the supernatant. Next, the cells
were mixed with 100 µl of enzymatic digest buffer (30 mM Tris-HCl, 1 mM
EDTA, 2 mg l^−1 protease K (Thermo Fisher), 3.25 mg l^−1 lysozyme
(Sigma-Aldrich, 62970) and 0.15 mg l^−1 lysostaphin (Sigma-Aldrich,
L7386)), re-suspended by pipetting and incubated for 10 min at room
temperature with shaking. Three hundred and fifty microliters of RTL
buffer (containing 2-mercaptoethanol (Sigma-Aldrich, M3148)) was added
and RNA extraction was performed using RNeasy Mini Kit (Qiagen),
following the manufacturer’s protocol and including the optional step
of DNase I on-column digestion. Elution was performed twice using the
same volume of 50 µl of RNase-free water. RNA concentration was
determined using the QuantiFluor RNA System (Promega). Samples were
sent to Oxford Genomics Centre (Wellcome Centre for Human Genetics,
University of Oxford, Oxford, UK), where rRNA depletion was performed
prior to sequencing using an Illumina HiSeq 4000 platform, generating
75 bp paired-end reads.
Initial principal component analysis identified a likely batch effect,
affecting one high evolvability strain. This strain and its low
evolvability pair was removed from subsequent analysis. Transcript
quantification of the RNA-Seq data from the remaining 14 pairs was
performed using Salmon v0.11.3, which maps reads to an indexed
reference transcriptome (MRSA252; GenBank accession no.
[232]BX571856.1) using quasi-mapping approach and an inbuilt correction
for fragment-level GC bias^[233]92. Indexing of the reference
transcriptome removed sequence-identical duplicate transcripts and used
a kmer length of 31 bp. The DESeq2 library in R was used to estimate
gene counts and perform differential expression analysis^[234]93 in
Bioconductor, with the requirement of at least 1 read mapping to each
gene for every strain. Normalised norA transcript counts for individual
strains were obtained using the plotCounts function in the DESeq2
library in R.
To test whether genes in different KEGG pathways were up or
downregulated in high or low evolvability strains, a KEGG pathway
enrichment analysis was carried out using the kegga and topKEGG
functions in the limma library in R. A false discovery rate cutoff for
differentially expressed genes of 0.05 was used. A given KEGG pathway
was considered to be significantly enriched when P < 0.05.
Mutation rate estimation (fluctuation test)
Mutation rate was determined for 33 parental strains. These 33 strains
were selected in the following way. First, 11 high evolvability strains
(survival > 10/12) were chosen to maximize phylogenetic representation.
Second, each of these strains was paired to the closest low
evolvability strain (survival ≤ 1/12). In addition, 11 strains
representing CC398 (ST398, ST291 and ST3535) were included. The strains
were assigned to three experimental blocks, ensuring a similar
representation of high and low evolvability strains in each block.
The strains were re-grown from −80 °C stock in 200 µl of MH2 medium.
After 24 h of incubation, strains were subject to a bottleneck by
diluting them 10^7 times. The bottleneck step was required to remove
any pre-existing low frequency mutations. The diluted bacterial
cultures were used to establish 16 replicate cultures per strain in
1.2 ml deep well plates (Brand, 701340) with 300 µl of MH2 per well.
After overnight incubation at 37 °C, 5 µl were sampled from eight
replicates, diluted 10^7or 10^8 times and plated on TSB agar plates to
estimate population density. Two hundred microliters of overnight
cultures from all 16 replicates per strains were plated on TSB-agar
plates containing 100 mg l^−1 of the antibiotic rifampicin. After 24 h,
the TSB plates without antibiotic were photographed using a
ColonyDoc-It Imaging Station (UVP, Cambridge, UK). The plates with
antibiotic and containing rifampicin-resistant mutants were
photographed after 48 h. Colonies were counted in ImageJ^[235]94 using
a custom script written in ImageJ macro language.
The colony counts from both types of plates were imported into R. The
mutation rate was calculated using the rSalvador package in R, which
provides a maximum likelihood estimate of mutation rate under the
Luria-Delbruck model and accounts for variation in population
density^[236]95. To compare mutation rates between strains, a Wilcoxon
signed rank test (paired, two-sided) was performed.
The effect of reserpine on ciprofloxacin resistance
To determine the effect of the norA inhibitor reserpine on intrinsic
resistance and evolvability, 27 parental strains (out of 222) were
chosen using the following algorithm. First, nine high evolvability
strains (survival >10/12) were selected in different parts of the
phylogenetic tree. Then, for each high evolvability strain the closest
low evolvability strains was identified (survival ≤1/12). In addition,
we included nine strains from the high evolvability clonal complex
CC398. This set of strains is a subset from the 33 strains used for
measuring mutation rates. However, this set of 27 strains is different
from the set used in transcriptomic analysis (though, two sets are
overlapping), because of different survival thresholds used for
defining high and low evolvability strains and because here we included
CC398 strains.
The strains were recovered from −80 °C stock and re-grown for two
transfers in 200 µl of MH2 broth. During the second transfers, strain
layouts were randomized on plates using a Precision XS automated
pipetting station (BioTek). Five different randomization layouts were
used corresponding to five replicate cultures included per
dose/treatment combination. Half of the cultures were exposed to eight
different concentrations of ciprofloxacin, and half to the same
antibiotic concentration and 33 µM of reserpine. After 22 h of
incubation, population growth was measured using a plate reader
(OD[595]).
A dose-response analysis was performed by fitting a 4-parameter model.
The dose-responses curves were used to estimate IC[50]. The effect of
reserpine on IC[50] was evaluated by using the function EDcomp from the
R package drc (version 3.0-1). In addition, IC[50] was compared using a
two-sided Wilcoxon signed-rank test.
The effect of reserpine on evolvability
To estimate the effect of efflux pump inhibitor on evolvability,
experimental evolution was performed by exposing S. aureus strains to
1 mg l^−1 of ciprofloxacin, either with or without 33 µM of reserpine.
The same 27 strains that were used for measuring the effect of
reserpine on intrinsic resistance were used here. For each strain, 16
replicates with reserpine and 16 replicates without reserpine were
included. Strain positions on plates were randomized using four
different plate layouts. The wells at the plate edges (i.e. rows A and
H and columns 1 and 12) were used as controls.
The strains from −80 °C stock were re-grown overnight. During the
second transfers, strain positions within the plate were randomized
using an automated pipetting station. Half of the populations were
challenged with 1 mg l^−1 of ciprofloxacin, and the other half with
1 mg l^−1 ciprofloxacin and 33 µM reserpine. Every day, >800
populations were transferred to fresh medium containing the same dose
of ciprofloxacin and/or reserpine. Population growth was measured after
each transfer by reading optical densities (OD[595]) using a plate
reader. The experiment was completed after five transfers.
Due to incomplete solubility of reserpine in water, the optical density
of MH2 with reserpine was slightly higher than without reserpine. The
average increase in optical density due to reserpine was 0.011 OD[595],
as estimated by comparing a blank sample with and without reserpine
(0.049 ± 0.002 and 0.060 ± 0.008, correspondingly; median ± s.d.).
Therefore, prior to analysis, measurements from wells containing
reserpine were corrected by subtracting 0.011. After applying the
correction, populations that reached a density greater than 0.08
OD[595]were considered to have survived. The difference in survival due
to the presence/absence of reserpine was analysed separately for each
strain by performing a Fisher’s exact test. The resulting p-values were
adjusted using Holm–Bonferroni method (n = 27).
Cloning norA into the pRMC2 expression vector and transformation
Vector pRMC2 was obtained from Addgene (#68940)^[237]96. The pRMC2 was
linearized with EcoRI and KpnI restriction enzymes (NEB) and gel
purified using the QIAquick Gel Extraction Kit (Qiagen). The norA gene
and a 69 bp upstream region was amplified with PCR, using Phusion DNA
Polymerase (NEB). The genomic DNA of strain ERR418607 (ST398) was used
as a template. The primers contained 5′-overhangs and were designed for
Gibson assembly (see Supplementary Table [238]15). The linearized
vector and the PCR product were assembled using NEBuilder HiFi DNA
Assembly Kit (NEB) and transformed into E. coli DC10B (BCCM, Belgium,
LMBP 9585). The clones were selected on LB plates with ampicillin
(100 mg l^−1), screened using PCR and confirmed by Sanger sequencing
(primers are listed in Supplementary Table [239]15). The expression
vector containing norA was transformed into S. aureus RN4220 (DSMZ,
Germany, DSM 26309) by electroporation using the protocol described in
ref. ^[240]40. The S. aureus transformants were selected on TSB agar
plates with chloramphenicol (10 mg l^−1) and verified by PCR and Sanger
sequencing.
norA overexpression experiments (resistance and evolvability to
ciprofloxacin)
The effect of norA overexpression on ciprofloxacin resistance was
measured using the broth microdilution method. Although norA was cloned
under a tetracycline-inducible promoter, increased resistance was also
observed without adding the inducer. This is potentially because a
native promoter was also cloned as a part of the norA upstream region.
Further induction of norA with an anhydrotetracycline inducer increased
resistance but simultaneously affected RN4220 growth rate in the
absence of the antibiotic. In order to avoid a negative effect of high
overexpression on bacterial fitness and the antimicrobial effect of
anhydrotetracycline itself, we decided not use the inducer in all
following experiments and relied on the uninduced level of expression.
To assess the effect of norA overexpression on resistance, the growth
of RN4220 cells carrying pRMC2-norA was compared with cells carrying an
empty vector and cells without vector. First, S. aureus strains were
cultured overnight in MH2 (cultures that contained the plasmid were
supplemented with 10 mg l^−1 chloramphenicol). The next day, cultures
were adjusted to a density of 5 × 10^6 CFU ml^−1 and inoculated into
MH2 medium containing 10 different doses of ciprofloxacin. After 22 h
of incubation, optical densities were measured. Three replicate
cultures were included per dose/genotype combination. The effect of
overexpressing norA was analysed using a dose-response curve.
To measure the effect of norA overexpression on evolvability, the
RN4220 cells carrying pRMC2-norA or an empty vector pRMC2, and
vector-free cells were experimentally evolved for five transfers at
1 mg l^−1 of ciprofloxacin. Prior to the experiment, 40 colonies per
genotype were selected to establish parallel cultures. After 22 h of
incubation in MH2 broth (cultures with the plasmid were supplemented
with chloramphenicol). Ten microliters of overnight culture were
inoculated to wells containing 190 µl of MH2 and 1 mg l^−1 of
ciprofloxacin. The cultures were transferred daily to a fresh medium
with ciprofloxacin. Populations that reached an optical density of 0.08
or higher by transfer 5 were considered to be alive. To test the
differences in evolvability between genotypes, Fisher’s exact test was
performed on the number of survived/extinct populations and p-values
were corrected using the Holm-Bonferroni correction.
Killing assay using ciprofloxacin (the effect of norA expression on survival)
To measure the effect of norA expression on cell survival during the
exposure to ciprofloxacin, a killing assay was performed including four
ciprofloxacin treatments (1 mg l^−1) and two control treatments (no
ciprofloxacin). The ciprofloxacin treatments were: (i) the RN4220 cells
overexpressing norA, (ii) the RN4220 cells overexpressing norA with
33 μM reserpine (NorA inhibitor), (iii) the RN4220 carrying the empty
vector pRMC2 and (iv) RN4220 cells with no vector. The control
treatments (no ciprofloxacin) were (v) the RN4220 cells overexpressing
norA and (vi) the RN4220 cells overexpressing norA supplemented with
33 μM reserpine. A day before the experiment, overnight cultures were
prepared in MH2 broth including 10 µg ml^−1 of chloramphenicol for the
bacteria carrying vector pRMC2. The overnight cultures were diluted
1:10 in pre-warmed MH2 broth and incubated for 2.5–3 h (225 rpm, 37 °C)
until they entered an exponential growth phase. Next, all strains cells
were diluted 1:5 times in pre-warmed MH2, the cell densities were
brought to OD[595] = 0.072 in 100 μl of MH2 (including blank). The
adjusted cultures were diluted 1:1000 using the pre-warmed media
corresponding to their treatments (i.e. with or without 1 mg l^−1
ciprofloxacin and with or without 33 µM reserpine) resulting in
~5 × 10^4 CFU ml^−1. The cell suspensions were transferred into
pre-warmed 96 deep well plates (Brand, 701340) with 250 µl per well,
sealed with gas-permeable foil and incubated at 225 rpm at 37 °C. Every
hour, six replicate cultures per treatment were sampled, diluted in PBS
buffer and plated to MH2 agar plates. For each time point, new cultures
were sampled to avoid repeated measurements of the same cultures. The
agar plates were incubated at 37 °C for 24 h and, then, photographed
using a ColonyDoc-It Imaging Station (UVP, Cambridge, UK). Colonies
were counted with ImageJ^[241]94 using a custom script written in
ImageJ macro language.
Obtaining spontaneous grlA mutants
Two hundred microliters of several independent overnight cultures of
the S. aureus RN4220 were plated onto MH2 agar plate containing either
1 or 2 mg l^−1 ciprofloxacin. Twenty-two colonies were isolated for DNA
extraction and Sanger sequencing to identify resistance mutations. The
primers used to amplify known fluoroquinolone resistance regions in
grlA, gyrA, grlB and gyrB genes are listed in Supplementary
Table [242]15. Twenty out of 22 mutants had grlA mutation (one A116P,
seven A116E, three E84K, four S80Y and five S80F). For further
characterization, three independently isolated mutants (i.e., isolated
from different overnight cultures) were selected to represent
four resistant mutations (A116E, E84K, S80Y and S80F) resulting in
total 12 ciprofloxacin-resistant mutants of RN4220.
Transformation of grlA mutants with pRMC2-norA
Electro-competent cells were prepared for 12 grlA RN4220 following the
protocol from^[243]40. The competent cells were transformed with the
pRMC2-norA expression vector. The transformants were selected on
TSB-plates supplemented with 10 µg ml^−1 of chloramphenicol and
confirmed by PCR and Sanger sequencing (primers are listed in
Supplementary Table [244]15).
Measuring maximum growth rate of grlA mutants
To estimate the effect of norA overexpression on growth rate of the
grlA mutants, 12 mutants carrying pRMC2-norA vector and the 12
corresponding parental mutants having no vector were compared. In
addition, the wild-type RN4220 was included as a control (with or
without pRMC2-norA). The mutants were grown overnight in MH2 broth
(containing 10 µg ml^−1 of chloramphenicol wherever necessary for
pRMC2-norA selection). The overnight cultures were diluted 1:1000 in
the MH2 broth with 1 mg l^−1 of ciprofloxacin and distributed in a
96-well plate with 200 µl of cell suspensions per well. The assay
plates were placed into a Synergy 2 plate reader (BioTek) and incubated
at 37 °C with continuous shaking. The bacterial growth was recorded by
measuring the optical density (λ = 595 nm) every 10 min for minimum
14 h. For each mutant, six replicate cultures were included, and the
experiment was performed in several blocks to accommodate all
replicates.
Growth curves were used to estimate the maximum growth rate. A linear
regression was used to calculate a slope for each 5 time-point interval
of a growth curve in a sliding window fashion (by moving a window one
time-point and repeating regression). The resulting distribution of
slopes was used to find a maximum growth rate (corresponding to a
maximum change in optical density per time unit (an hour)). Because the
optical density data were log2-transformed prior the analysis, the
obtained estimates should be equivalent to a number of cell divisions
per hour (assuming linear relationship between the optical density and
cell density during the log growth phase).
Measuring resistance to ciprofloxacin of grlA mutants
Twelve grlA mutants without vector and their corresponding
transformants carrying the pRMC2-norA vector were cultured overnight in
MH2 broth. Cultures that contained the vector were supplemented with
10 mg l^−1 chloramphenicol. The next day, cultures were adjusted to a
cell density of 5 × 10^6 CFU ml^−1 and inoculated into MH2 medium
containing 13 different doses of ciprofloxacin (0.01–12 mg ml^−1).
After 22 h of incubation, optical densities were measured using a plate
reader. Five replicate cultures were included per dose/genotype
combination. The effect of norA overexpression was analysed using a
dose-response analysis and, additionally, by performing two-sided
paired t-test for mean optical densities of mutants obtained at
1 mg l^−1 of ciprofloxacin.
Measuring maximum growth rate of strains with norA amplification
To estimate the effect of norA amplification on fitness, eight parental
strains (before amplification) and eight evolved strains (after
amplification) were assayed by determining maximum growth rate. These
assays were performed in the absence of ciprofloxacin. The parental and
evolved strains were grown overnight, diluted 1:1000 in the MH2 broth
and inoculated in a 96-well plate (200 µl of cell suspensions per
well). The assay plates were incubated inside of a Synergy 2 plate
reader (BioTek) at 37 °C with continuous shaking. The bacterial growth
was recorded by measuring the optical density (λ = 595 nm) every 10 min
for minimum 14 h. For each strain, three or four replicate cultures
were included. Growth curves were used to estimate the maximum growth
rate by calculate a slope for each 5 time-point interval of a growth
curve in a sliding window fashion. The maximum slope is equivalent to
the number of cell divisions per hour during the exponential growth
phase in the absence of ciprofloxacin. Maximum growth rate in parental
and evolved strains was compared using two-sided paired Wilcoxon sign
rank test.
Statistics and reproducibility
Experimental evolution of 222 strains was repeated twice. The first
attempt failed due to experimental error. Experimental evolution with
cell expressing norA and experimental evolution with norA inhibitor
were performed one time. The transcriptome experiment and fluctuation
test were performed one time. The determination of resistance to
ciprofloxacin in 222 parental strains, in 83 evolved populations, in 27
strains with reserpine, and in 12 grlA mutants were performed one time.
The experiment with norA overexpression in RN4220, the killing assay
and estimation of growth rates were performed one time after smaller
trial experiments. The results from the trial experiments were
reproducible.
Reporting summary
Further information on research design is available in the [245]Nature
Research Reporting Summary linked to this article.
Supplementary information
[246]Supplementary Information^ (3.2MB, pdf)
[247]Peer Review File^ (2.9MB, pdf)
[248]41467_2020_17735_MOESM3_ESM.pdf^ (65.2KB, pdf)
Description of Additional Supplementary Files
[249]Supplementary Data 1^ (23.4KB, xlsx)
[250]Supplementary Data 2^ (30.4KB, xlsx)
[251]Supplementary Data 3^ (20.3KB, xlsx)
[252]Supplementary Data 4^ (15.9KB, xlsx)
[253]Supplementary Data 5^ (14MB, xlsx)
[254]Reporting Summary^ (144.9KB, pdf)
Acknowledgements