Differential epigenetic compatibility of qnr antibiotic resistance determinants with the chromosome of Escherichia coli.
ABSTRACT Environmental bacteria harbor a plethora of genes that, upon their horizontal transfer to new hosts, may confer resistance to antibiotics, although the number of such determinants actually acquired by pathogenic bacteria is very low. The founder effect, fitness costs and ecological connectivity all influence the chances of resistance transfer being successful. We examined the importance of these bottlenecks using the family of quinolone resistance determinants Qnr. The results indicate the epigenetic compatibility of a determinant with the host genome to be of great importance in the acquisition and spread of resistance. A plasmid carrying the widely distributed QnrA determinant was stable in Escherichia coli, whereas the SmQnr determinant was unstable despite both proteins having very similar tertiary structures. This indicates that the fitness costs associated with the acquisition of antibiotic resistance may not derive from a non-specific metabolic burden, but from the acquired gene causing specific changes in bacterial metabolic and regulatory networks. The observed stabilization of the plasmid encoding SmQnr by chromosomal mutations, including a mutant lacking the global regulator H-NS, reinforces this idea. Since quinolones are synthetic antibiotics, and since the origin of QnrA is the environmental bacterium Shewanella algae, the role of QnrA in this organism is unlikely to be that of conferring resistance. Its evolution toward this may have occurred through mutations or because of an environmental change (exaptation). The present results indicate that the chromosomally encoded Qnr determinants of S. algae can confer quinolone resistance upon their transfer to E. coli without the need of any further mutation. These results suggest that exaptation is important in the evolution of antibiotic resistance.
- SourceAvailable from: Ana P. Tedim[Show abstract] [Hide abstract]
ABSTRACT: Antibiotics have natural functions, mostly involving cell-to-cell signaling networks. The anthropogenic production of antibiotics, and its release in the microbiosphere results in a disturbance of these networks, antibiotic resistance tending to preserve its integrity. The cost of such adaptation is the emergence and dissemination of antibiotic resistance genes, and of all genetic and cellular vehicles in which these genes are located. Selection of the combinations of the different evolutionary units (genes, integrons, transposons, plasmids, cells, communities and microbiomes, hosts) is highly asymmetrical. Each unit of selection is a self-interested entity, exploiting the higher hierarchical unit for its own benefit, but in doing so the higher hierarchical unit might acquire critical traits for its spread because of the exploitation of the lower hierarchical unit. This interactive trade-off shapes the population biology of antibiotic resistance, a composed-complex array of the independent "population biologies." Antibiotics modify the abundance and the interactive field of each of these units. Antibiotics increase the number and evolvability of "clinical" antibiotic resistance genes, but probably also many other genes with different primary functions but with a resistance phenotype present in the environmental resistome. Antibiotics influence the abundance, modularity, and spread of integrons, transposons, and plasmids, mostly acting on structures present before the antibiotic era. Antibiotics enrich particular bacterial lineages and clones and contribute to local clonalization processes. Antibiotics amplify particular genetic exchange communities sharing antibiotic resistance genes and platforms within microbiomes. In particular human or animal hosts, the microbiomic composition might facilitate the interactions between evolutionary units involved in antibiotic resistance. The understanding of antibiotic resistance implies expanding our knowledge on multi-level population biology of bacteria.Frontiers in Microbiology 01/2013; 4:15. · 3.90 Impact Factor
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ABSTRACT: Abstract The emergence and spread of antibiotic resistance among human pathogens is a relevant problem for human health and one of the few evolution processes amenable to experimental studies. In the present review, we discuss some basic aspects of antibiotic resistance, including mechanisms of resistance, origin of resistance genes, and bottlenecks that modulate the acquisition and spread of antibiotic resistance among human pathogens. In addition, we analyse several parameters that modulate the evolution landscape of antibiotic resistance. Learning why some resistance mechanisms emerge but do not evolve after a first burst, whereas others can spread over the entire world very rapidly, mimicking a chain reaction, is important for predicting the evolution, and relevance for human health, of a given mechanism of resistance. Because of this, we propose that the emergence and spread of antibiotic resistance can only be understood in a multi-parameter space. Measuring the effect on antibiotic resistance of parameters such as contact rates, transfer rates, integration rates, replication rates, diversification rates, and selection rates, for different genes and organisms, growing under different conditions in distinct ecosystems, will allow for a better prediction of antibiotic resistance and possibilities of focused interventions.Upsala journal of medical sciences 03/2014; · 0.73 Impact Factor
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ABSTRACT: Fluoroquinolones, rapidly gaining prominence in treatment of Stenotrophomonas maltophilia (SMP), are noted for their potency and tolerability. However, SMP may rapidly acquire resistance to fluoroquinolones. We evaluated associations of clinical factors with acquisition of levofloxacin resistance (LFr) in SMP.Yonsei medical journal. 07/2014; 55(4):987-93.
Differential Epigenetic Compatibility of qnr Antibiotic
Resistance Determinants with the Chromosome of
Marı ´a B. Sa ´nchez, Jose ´ L. Martı ´nez*
Departamento de Biotecnologı ´a Microbiana, Centro Nacional de Biotecnologı ´a, CSIC, Cantoblanco, Madrid, Spain
Environmental bacteria harbor a plethora of genes that, upon their horizontal transfer to new hosts, may confer resistance
to antibiotics, although the number of such determinants actually acquired by pathogenic bacteria is very low. The founder
effect, fitness costs and ecological connectivity all influence the chances of resistance transfer being successful. We
examined the importance of these bottlenecks using the family of quinolone resistance determinants Qnr. The results
indicate the epigenetic compatibility of a determinant with the host genome to be of great importance in the acquisition
and spread of resistance. A plasmid carrying the widely distributed QnrA determinant was stable in Escherichia coli, whereas
the SmQnr determinant was unstable despite both proteins having very similar tertiary structures. This indicates that the
fitness costs associated with the acquisition of antibiotic resistance may not derive from a non-specific metabolic burden,
but from the acquired gene causing specific changes in bacterial metabolic and regulatory networks. The observed
stabilization of the plasmid encoding SmQnr by chromosomal mutations, including a mutant lacking the global regulator H-
NS, reinforces this idea. Since quinolones are synthetic antibiotics, and since the origin of QnrA is the environmental
bacterium Shewanella algae, the role of QnrA in this organism is unlikely to be that of conferring resistance. Its evolution
toward this may have occurred through mutations or because of an environmental change (exaptation). The present results
indicate that the chromosomally encoded Qnr determinants of S. algae can confer quinolone resistance upon their transfer
to E. coli without the need of any further mutation. These results suggest that exaptation is important in the evolution of
Citation: Sa ´nchez MB, Martı ´nez JL (2012) Differential Epigenetic Compatibility of qnr Antibiotic Resistance Determinants with the Chromosome of Escherichia
coli. PLoS ONE 7(5): e35149. doi:10.1371/journal.pone.0035149
Editor: Pierre Cornelis, Vrije Universiteit Brussel, Belgium
Received January 12, 2012; Accepted March 8, 2012; Published May 4, 2012
Copyright: ? 2012 Martı ´nez, Sa ´nchez. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Work in our laboratory is funded by grants BIO2008-00090 and BIO2011-25255 from the Spanish Ministry of Science and Innovation, KBBE-227258
(BIOHYPO), HEALTH-F3-2010-241476 (PAR), and HEALTH-F3-2011-282004 (EVOTAR) from European the Union. The funders had no role in study design, data
collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
The study of the emergence and spread of antibiotic resistance
is clearly important with respect to human health, and offers one
of the few possibilities of following evolution in real time. Learning
the mechanisms involved in the recruitment and spread of
resistance genes to human bacterial pathogens is therefore
important from an evolutionary perspective. It has been indicated
that the resistance genes that have been acquired by pathogens via
horizontal gene transfer (HGT) likely originated in antibiotic-
producing bacteria, in which they played a self-protection role
[1,2,3,4]. Accordingly to that view, their function – to provide
resistance to antibiotics – is therefore the same in both the original
and new host. However, it is difficult to imagine that the same
holds true for genes conferring resistance to synthetic antibiotics
such as quinolones . The quinolones are a family of widely used
synthetic antimicrobial agents that target bacterial topoisomerases
(DNA gyrase and topoisomerase IV) and, as a consequence, inhibit
DNA replication and transcription. Given their synthetic origin, it
was supposed that no quinolone resistance genes would exist, the
only cause of resistance to these drugs arising through mutations in
the genes encoding their targets. However, the study of multidrug
(MDR) efflux pumps, which are chromosomally-encoded in all
microorganisms , has shown that quinolones are among the
most common substrates of these resistance elements, indicating
that microorganisms possess genes involved in quinolone resis-
tance despite the synthetic origin of these drugs . Once this
became known, it was predicted that plasmid-encoded quinolone
resistance was possible [8,9], and indeed, a plasmid-encoded
quinolone resistance element (dubbed Qnr) was eventually found
in a transferable plasmid in Klebsiella pneumoniae . Since then,
qnr genes have been described in plasmids from Enterobacteriaceae,
and other plasmid-encoded quinolone resistance genes such as
aac(69)-Ib-cr  qepA and oqxAB [12,13] have been found in
Since there are no quinolone producers in nature, qnr genes
must have originated in non-producer organisms. Indeed, the
origin of the widely distributed, plasmid-encoded qnr determinant,
qnrA, has been tracked to the non-antibiotic-producer bacterium
Shewanella algae , and qnr genes have been found in the
chromosomes of different bacteria, most of which occupy aquatic
habitats . The fact that chromosomally-encoded qnr genes are
not flanked by elements involved in gene mobility, that they show
strong sequence conservation, and that synteny is maintained
PLoS ONE | www.plosone.org1May 2012 | Volume 7 | Issue 5 | e35149
across the strains of a given species, indicates that they have not
been recently acquired by these species; rather they are the origin
of the qnr genes involved in quinolone resistance in bacterial
pathogens. This raises important evolutionary questions. Quino-
lones are synthetic compounds that were not present in natural
ecosystems at the time of the evolution of chromosomally-encoded
qnr determinants, so the original function of the latter is not to
provide resistance to quinolones. Which evolutionary process,
then, allowed the conversion of a gene not involved in resistance
into an element that provides resistance against a synthetic
compound not present in natural ecosystems?  In other words,
has the exposure of microorganisms to human-produced quino-
lones influenced the evolution of these otherwise housekeeping
genes? Further, given that there are several qnr genes that can
potentially be transferred to a heterologous host , why are only
a few of them currently present in the plasmids found in human
To explain the above, the existence of pre-resistance genes able
to recognize chemical moieties similar to antibiotics has been
suggested. These pre-resistance genes would not confer resistance
by themselves, but might easily evolve under antibiotic selective
pressure to finally result in a bona fide antibiotic resistance
determinant [17,18]. Alternatively, a gene with a functional role
different to resistance in its original host, might confer resistance
without any modification . This type of evolution, in which the
function of a given determinant alters as a consequence of changes
in the environment (i.e., not because of changes in the sequence of
the gene encoding it) has been termed exaptation [20,21]. In the
case of antibiotic resistance, exaptation is linked to the metabolic
and regulatory de-contextualization suffered by these genes when
jumping from the original host chromosome to that of a novel host
with a different metabolism and regulatory networks (for a review
of this concept see ).
Despite the large number of resistance genes present in
environmental bacteria, which could serve as donors of resistance
[18,22,23], the actual variability of resistance genes acquired by
HGT in pathogenic bacteria is very small. This might be
explained by the founder effect, i.e., once a resistance gene is
introduced into a plasmid capable of spreading among the most
important clones of a bacterial pathogen, its displacement by a
new determinant conferring resistance to the same antibiotic
would be difficult (for a discussion on this concept see ).
Alternatively, fitness costs might impede the dissemination of a
given gene [25,26]. However, it might be predicted that the fitness
costs of antibiotic resistance determinants belonging to the same
structural family, and thus with the same mechanism of action,
would be very similar unless their levels of expression differ .
To gain more insight into the basic mechanisms driving the
evolution of antibiotic resistance, we focused on qnr genes as
models. Over the last few decades the qnrA gene has spread widely
among populations of Enterobacteriaceae, conferring protection
against quinolones upon them. Shewanella algae, the origin of qnrA,
rarely produces human infections, and is therefore not significantly
exposed to quinolones in its natural habitat. We also studied the
Smqnr gene, naturally present in the chromosome of the
opportunistic pathogen Stenotrophomonas maltophilia , which
confers low-level resistance to quinolones in heterologous hosts
[15,29]. Since S. maltophilia is more commonly in contact with
human-linked microbiota than S. algae, the possibility of it being a
donor of qnr genes to Enterobacteriaceae is potentially greater .
However, while qnrA is a widespread gene, no transfer of Smqnr
has ever been documented.
To address the evolutionary mechanisms that affect the spread
of qnr genes, we compared the stability of different qnr genes upon
their expression in a heterologous host, and performed experi-
mental evolution assays [31,32] to assess the associated fitness costs
and to track potential compensatory mutations. Surprisingly, the
fitness costs associated with one or another Qnr determinant were
very different in the same host, despite their belonging to the same
structural family. These results indicate that, at least for the studied
determinants, fitness costs are not necessarily a general burden
linked to the energy required to keep a new mobile genetic
element in a cell (and thus associated with the acquisition of a
genetic platform), but might be specific for the type of resistance
determinant encoded into the element (and thus to the interactions
of a specific mechanism with the cellular regulatory and metabolic
networks). This might provide an explanation for the stability and
further spread of specific resistance genes to be considered
alongside the founder effect above discussed. We also found that
chromosomally-encoded qnr determinants belonging to the core
genome of bacterial species are not pre-resistance genes that
require further evolution to become resistance determinants.
Rather, the main evolutionary process involved in their change of
function is exaptation.
The qnr Genes Present in the Chromosome of S. algae
Confer Resistance to Quinolones
It has been suggested that antibiotic resistance can be achieved
as the consequence of the evolution of pre-resistance genes,
chromosomally encoded in non-producer organisms, towards
resistance as the consequence of the selection of specific mutants
that allow the interaction of the pre-resistance determinant with
the antibiotic . The first described plasmid-encoded qnr gene
(qnrA1)  differs from those encoded in the chromosomes of S.
algae isolates  by 3 or 4 amino acids. It is therefore possible that
qnrA1 evolved from a pre-resistance gene with a different role in its
original host, i.e., not that of conferring resistance. To address this
possibility, qnrA1 from plasmid pMG252, qnrA3 from S. algae KB-1
and qnrA4 from S. algae KB-2 were cloned in the vector pGEM-T,
generating the plasmids pBS18, pBS19 and pBS20 respectively.
These were used to transform the Escherichia coli strain MC4100.
As shown in Table 1, the expression of the chromosomally-
encoded qnrA genes from S. algae reduced the susceptibility of the
recipient E. coli to quinolones. This indicates that those elements
are not pre-resistance determinants that must evolve through
adaptive genetic changes in order to confer resistance, but rather
that exaptation is an important evolutionary event in their change
of function. QnrA1 was the most efficient resistance determinant
among the three tested in terms of increasing MICs (Table 1). This
might be explained either by its post-exaptation evolution through
mutation, or, among the different alleles present in the chromo-
somes of different S. algae isolates, by its being the one that confers
the strongest resistance upon heterologous hosts, and thus that
which provides the greatest gain in fitness under selective pressure
Stability of qnr Genes upon Expression in an
To test whether the prevalence of qnrA in the plasmids of
bacterial pathogens might be the consequence of a founder effect
or of it being associated with smaller fitness costs than other qnr
determinants, we measured the stability in E. coli MC4100 of
plasmids containing the different qnrA alleles, as well that of the
plasmid pBS3.25, containing Smqnr, which is chromosomally-
encoded in S. maltophilia . Single colonies of each strain were
grown in LB medium with carbenicillin (a selector of the TEM1
Fitness Cost of Qnr Resistance Is Allele-Specific
PLoS ONE | www.plosone.org2 May 2012 | Volume 7 | Issue 5 | e35149
ß-lactamase gene present in the pGEM-T backbone) overnight at
37uC, and the percentage of cells containing the plasmid
determined as described in Methods. The plasmid harboring
Smqnr was lost in nearly 80% of the population, indicating that
the acquisition of Smqnr incurs a high immediate fitness cost
upon E. coli (Figure 1). Plasmid loss can be achieved in the
presence of carbenicillin since the ß-lactamase encoded by the
plasmid destroys the antibiotic; thus, the selective pressure is
removed a few hours after its introduction . Since the efflux
pump AcrAB-TolC is involved in quinolone resistance in E. coli
, the same study was performed in the strain E. coli
KZM120, which lacks acrAB , in order to avoid any
problems of interference between the two types of quinolone
resistance mechanism that might compromise bacterial fitness.
The plasmid containing Smqnr was lost in this strain as well
Unlike that seen for Smqnr, no plasmids encoding qnrA alleles
were lost by either of the E. coli strains (Figure 1). This shows that
the acquisition of qnrA does not impose large fitness costs on E. coli,
and that, at least for the tested genes, the effect on bacterial fitness
of different antibiotic resistance elements belonging to the same
structural and functional family can be very different. The
corollary of this reasoning is that resistance genes might not be
replaced even if they encode proteins belonging to the same family
and confer a similar phenotype - the associated fitness costs might
be different for each gene. These results indicate that allelic fitness
costs should be considered together with the founder effect when
explaining the introduction and spread of a given resistance
determinant in a population of bacterial pathogens.
The plasmids containing the different qnr genes used in this
work have the same size and structural backbone, indicating that
the observed differences in fitness costs are the consequence of a
specific effect of the resistance gene and not of a non-specific
burden on bacterial metabolism. Since Qnr proteins bind bacterial
topoisomerases, it is possible that they alter DNA supercoiling and
consequently modify global transcription and challenge bacterial
physiology. Besides topoisomerases, one of the elements that
modulate bacterial DNA supercoiling is the nucleoid-associated
protein H-NS . We thus measured the stability of the plasmids
in the E. coli strain JMG100, an hns defective strain derived from E.
coli MC4100. As shown in Figure 1, the lack of H-NS allowed the
maintenance of the plasmid pBS3.25, which harbors Smqnr. This
increased stability of the plasmid conferred slightly greater
resistance to quinolones than in the wild-type strain (Table 1).
Mutations Compensating Fitness Costs Associated with
the Expression of Smqnr Occur in the Chromosome of E.
Even though the expression of Smqnr incurs an immediate
fitness cost on E. coli, this might be alleviated if secondary
compensatory mutations are selected for. If these mutations occur
in the plasmid containing the gene, its dissemination will be aided.
In contrast, if these mutations occur in the chromosome, the
plasmid will be lost upon entering a novel host and dissemination
precluded. We thus performed an experimental evolution study,
making serial passages of E. coli KZM120 containing the plasmid
pBS3.25 harboring Smqnr. Passages were performed for two
replicate isolates 1) in the presence of carbenicillin for selecting the
plasmid 2) in the presence of ofloxacin for selecting Smqnr, and 3)
alternating the selection pressure (one week carbenicillin, one week
ofloxacin) for sequentially selecting the plasmid and the resistance
gene. The presence of the plasmid was analyzed after four weeks
(around 200 generations) of growth. All cultures grown in the
presence of ofloxacin lost the pBS3.25 plasmid harboring Smqnr,
whereas it was maintained in cultures exposed to carbenicillin
(strains MBS228, MBS229) and under alternating selection with
carbenicillin and ofloxacin (strains MBS230 and MBS231).
To ascertain whether the mutations stabilizing the plasmids
occurred in the plasmids themselves or in the chromosome, the
pBS3.25 plasmids obtained from the evolved strains were
introduced into the original, non-evolved E. coli KZM120 strain.
As shown in Figure 2, pBS3.25 plasmids obtained from the
evolved strains were lost in a manner similar to that observed for
the original pBS3.25 plasmid when introduced into a new host.
This suggests that stabilization was not due to mutations in the
plasmids. To further confirm this, the plasmids from the evolved
strains were extracted and sequenced. No change was detected in
Table 1. Effect of different qnr determinants on the
susceptibility to quinolones of wild-type and hns-deficient E.
MC4100 (wild-type) MOXOFX CIPLVXGAT
pGEM-T/None0.0320.032 0.006 0.016 0.012
pBS3.25/Smqnr0.047 0.047 0.008 0.016 0.023
pBS18/qnrA10.380.5 0.250.38 0.25
pBS19/qnrA30.250.38 0.094 0.125 0.19
pBS20/qnrA40.250.25 0.094 0.125 0.19
JMG100 (hns mutant)
pGEM-T/None0.032 0.047 0.008 0.016 0.012
pBS3.25/Smqnr0.0940.094 0.016 0.032 0.047
pBS19/qnrA30.250.38 0.094 0.125 0.125
pBS20/qnrA220.127.116.11 0.125 0.125
MOX, moxifloxacin; OFX, ofloxacin; CIP, ciprofloxacin; LVX, levofloxacin; GAT,
Figure 1. Differential fitness costs of different qnr determi-
nants. Plasmid loss was measured in the acrAB defective E. coli KZM120
strain (black bars), in the wild-type strain E. coli MC4100 (gray bars) and
in the hns defective E. coli JMG100 strain (white bars). pGEM-T, empty
vector; pBS3.25, plasmid with Smqnr; pBS18, plasmid with qnrA1; pBS19,
plasmid with qnrA3; pBS20 plasmid with qnrA4. Bars show the
percentage of cells containing the plasmids. As shown, the qnrA-
containing plasmid was stable in all strains, whereas the Smqnr-
containing plasmid was rapidly lost, indicating that Smqnr incurs a high
fitness cost not observed with qnrA. This cost is not observed in the hns
deficient strain, in which the Smqnr-containing plasmid is maintained.
Fitness Cost of Qnr Resistance Is Allele-Specific
PLoS ONE | www.plosone.org3May 2012 | Volume 7 | Issue 5 | e35149
the sequence of any of the plasmids; thus, stabilization was only
due to chromosomal mutations.
Since Qnr binds bacterial topoisomerases, it may be that
compensatory mutations occur in the genes coding for them. We
thus sequenced gyrA, gyrB, parC and parE in the evolved MBS228,
MBS229, MBS230 and MBS231 strains. No mutation was
detected in MBS228 or MBS229, while a change at position 87
of GyrA was detected in MBS230 and MBS231. However, this
mutation was also found in other strains that lost their plasmids
during the ofloxacin evolution experiment (see below); it is
responsible for the reduction in quinolone susceptibility shown
by these two strains, not for the stabilization of pBS3.25.
Given the pBS3.25 plasmid stabilization observed in the hns
defective mutant, hns is a potential candidate for acquiring
compensatory mutations. The hns gene was sequenced in
MBS228, MBS229, MBS230 and MBS231. No mutations were
detected indicating that compensation is not due to the
modification of H-NS. It is possible, however, that even if hns is
not mutated, its expression might be impaired. We thus compared
the level of expression of hns in the evolved MBS228, MBS229,
MBS230 and MBS231 strains to that in the non-evolved MBS25.
No differences were seen (Figure 3), indicating that stabilization is
due neither to mutations in hns nor to differences in its expression.
An intriguing aspect of strains MBS228 and MBS229 that
evolved under selective pressure from carbenicillin is that their
susceptibility to quinolones was higher than that seen in the
original non-evolved strain, whereas strains MBS230 and
MBS231, which evolved under alternating pressure from ofloxacin
and carbenicillin, were less susceptible to quinolones than the non-
evolved strains (Table S1). Since the level of expression of a given
resistance determinant affects the conferred fitness costs , and
since the level of Smqnr expression correlates with susceptibility to
quinolones , we measured the expression of Smqnr in the
MBS228, MBS229, MBS230 and MBS231 evolved strains and in
the non-evolved strain MBS25. The finding that Smqnr expression
was lower in the evolved strains indicates that the alleviation of the
fitness costs is likely due to the reduced expression of Smqnr
(Figure 3). Low Smqnr expression was also observed in the strains
MBS230 and MBS231, despite their reduced susceptibility to
quinolones, suggesting that, even when selective pressure with
quinolones is exerted, E. coli evolves towards the acquisition of
resistance by chromosomal mutations (see below) and tends to lose
the pBS3.25 plasmid containing the Smqnr gene. The benefits of
harboring this gene are probably smaller than the burden it
generates, even in the presence of the selective antibiotic.
The reduced expression of Smqnr in the evolved strains might be
due either to mutations altering this, or to mutations that reduce
the copy number of pBS3.25. To determine which was at work, we
quantified the amount of plasmid DNA as described in Methods.
Figure 3 shows that the amount of pBS3.25 in the evolved clones
was smaller than in the original strain, indicating that compen-
satory mutation(s) reduce the plasmid copy number. Consequent-
ly, the expression of Smqnr and the associated fitness costs were
lower. This reduction in plasmid copy numbers and its effect on E.
coli fitness was evident from the beginning of the experimental
evolution experiment. Indeed, we detected that even the non-
evolved strain showed diversity in terms of the colony size, with
Figure 2. Stability of Smqnr-containing plasmids after exper-
imental evolution. Plasmid stability was estimated in the evolved
strains (gray bars) and in E. coli KZM120 clones retransformed with
plasmids obtained from the evolved strains (white bars). Bars show the
percentage of cells containing the plasmids. Black bars pGEM-T, empty
vector and MBS25 original strain with pBS3.25 plasmid without
evolution; gray bars, evolved strains obtained after growth in the
presence of carbenicillin (MBS228 and MBS229) or with carbenicillin and
ofloxacin alternatively (MBS230 and MBS231); white bars, strains
obtained after transforming E. coli KZM120 with the plasmids from
the evolved strains MBS228, MBS229, MBS230 and MBS231. As shown,
the plasmids were stable in the evolved strains but remained unstable
upon their transfer to a new host.
Figure 3. Analysis of the expression of hns and Smqnr25, and
copy number of the pBS3.25 plasmid upon experimental
evolution. Panel A, analysis of expression of hns and Smqnr. Black
bars, hns expression; gray bars, Smqnr25 expression. Despite pBS3.25
being stabilized in the hns defective mutant, the expression of this gene
did not change in the evolved strains, indicating that plasmid
stabilization in these isolates is not due to reduced hns expression.
The copy number of values were normalized taking the value for
MBS231 as 1. MBS228, MBS229, MBS230 and MBS231 are the evolved
strains and MBS25 the original, non-evolved strain. Panel B. Copy
number of pBS3.25 after experimental evolution. White bars, copy
number of pBS3.25 plasmid in the evolved strains and in the overall
MBS25 population. The large deviation observed in the full MBS25
population reflects that it is formed by two subpopulations, one (small
colonies) harboring pBS3.25 in high copy numbers, and another (larger
colonies) in which the plasmid copy number is low. The copy number of
pBS3.25 in the small colonies is shown with a gray bar; the copy
number of pBS2.35 in the colonies of normal size is shown with a black
bar. As shown, bacteria evolved to reduce the plasmid copy number
and hence express low levels of Smqnr. This reduction is evident even in
the original population, which has small colonies with plasmids in high
copy number and normal size colonies with low copy numbers of
pBS3.25. Values were normalized using the values for the normal-sized
colonies of MBS25 (black bar) as 1.
Fitness Cost of Qnr Resistance Is Allele-Specific
PLoS ONE | www.plosone.org4May 2012 | Volume 7 | Issue 5 | e35149
some of the population forming regular colonies and some forming
small colonies. We thus measured the amount of pBS3.25 in both
types. As shown in Figure 3, the small colonies had higher copy
numbers of pBS3.25 than the larger ones. This indicates the co-
existence of fitter derivatives with low copy numbers of pBS3.25
and low expression of Smqnr that overcome the less fit derivatives,
which express higher levels of Smqnr.
Experimental Evolution in the Presence of Quinolones
Selects for Chromosomal Mutations Allowing Plasmid
An intriguing aspect of the evolved strains MBS230 and
MBS231 is their showing lower susceptibility to quinolones than
the non-evolved MBS25 (Table S1), despite the former having
lower copy numbers of pBS3.25 than the latter. This suggests that
they acquired chromosomal mutation(s) leading to this reduced
susceptibility. Since the main mechanism of quinolone resistance
consists of mutations in the quinolone resistance determinant
regions (QRDRs) of the genes gyrA/B and parC/E, which code for
bacterial topoisomerases, the QRDRs of gyrA, gyrB, parC and parE
were sequenced. An amino acid change in GyrA - D87Y - was
found in both MBS230 and MBS231.
Low-level resistance to antibiotics can allow bacteria to develop
high-level resistance more easily because it allows persistence of
sufficient number of cells in the presence of the selector, facilitating
the random emergence of mutants. Thus, to ascertain whether or
not the presence of the pBS3.25 plasmid containing the Smqnr
gene increases the capability of E.coli to acquire quinolone
resistance, new sets of experimental evolution experiments were
performed. Independent cultures of E. coli containing either
pBS3.25 or pGEM-T were subjected to serial passages in the
presence of ofloxacin (8, 16 or 32 ng/ml) for four weeks. In all
cases, the evolved clones showed lower susceptibility to quinolones
irrespective of their harboring the Smqnr gene. Further, inspection
of the inhibition zones around the quinolone-containing disks
revealed the presence of resistant colonies one week after
quinolone challenge in some of the evolving clones, irrespective
of whether the plasmid harbored Smqnr (Figure 4). These results
show the existence of a mixed population of resistant and
susceptible bacteria in the culture. Inspection of the quinolone
inhibition zones at weeks 2, 3 and 4 showed that the resistant
population displaced the susceptible one over time (Figure 4), a
feature that fits with the recent description of selection of
quinolone resistance at sub-inhibitory concentrations of antibiotics
as the consequence of differential fitness in the presence or in the
absence of antimicrobials . The QRDR regions of genes gyrA/
B and parC/E from the evolved clones were sequenced. Most
evolved clones (90%) showed a change at position 87 of GyrA
(Table S1), as seen in MBS230 and MBS231, which evolved under
alternating selective pressure from carbenicillin and ofloxacin.
Since this mutation is present in the strains containing pGEM-T
(Table S1), and since all the clones containing pBS3.25 evolving in
the presence of ofloxacin alone lost this plasmid, this mutation was
clearly not selected to compensate for the fitness costs associated
with Smqnr in MBS230 and MBS231 (which kept the plasmid
pBS3.25). Among the other evolved clones, MBS237 showed an
S83L amino acid change in GyrA, MBS232 showed a G466A
change in GyrB, and MBS258 showed the deletion of two amino
acids (L,G), at positions 474 and 475 of GyrB. Two clones
(MBS244 and MBS253) showed no mutation within the QRDRs
of gyrA/B and parC/E; their phenotypes might be due to changes in
the level of expression of other genes such as those coding for
porins or for multidrug efflux pumps.
Environmental bacteria together possess a huge number of
resistance determinants  that could confer resistance to
antibiotics upon their transfer to a heterologous host (resistome).
However, the number of resistance genes actually acquired by
human pathogens though HGT is very low, and when it has
occurred the original environmental microbial host has usually
remained unknown [6,19,37]. There are four main bottlenecks
that might account for this. The first is ecological connectivity,
which is a needed condition. If the potential donor of resistance
never shares its habitat with pathogenic bacteria, the resistance
gene has no chance of being transferred. Secondly, even if they
share the same habitat, the potential donor and the recipient may
not belong to the same genetic exchange community, understood
as the cohort of bacterial species among which DNA transfer can
occur . Thirdly, a founder effect may exist, understood as the
‘first gene to come being the one to win’. This implies a large
degree of stochasticity in the acquisition and spread of resistance.
If a resistance gene is incorporated into a proficient mobile genetic
element, and is acquired by a competitive bacterial clone, it is
likely that it will rapidly spread under antibiotic selective pressure.
This can occur locally, in which case different genes can arise at
different places or, if the elements/clones that allow its dissemi-
nation are highly epidemic, one single gene can be disseminated.
Once this gene is disseminated, the chances of another gene
conferring the same type of resistance entering and spreading
among the population would be low; once bacteria are resistant,
there is no further selective pressure for replacing one gene by
another. The last bottleneck is the fitness cost. If the acquisition of
a given resistance determinant incurs a high fitness cost, its
chances of remaining in the bacterial population will be low; the
resistant bacteria will be outcompeted by their susceptible
counterparts in the absence of selection . In this regards, it
has been discussed that the probability of a successful HGT event
is strongly affected by the number of interactions that a protein
can make with its neighbors [40,41]. These bottlenecks are not
mutually exclusive, and combinations might be at work in specific
To analyze the importance of these mechanisms in the
evolution of antibiotic resistance, we determined the stability of
plasmids encoding either the widely-spread qnrA gene or the S.
maltophilia Smqnr gene, both of which code for low-level
quinolone resistance. S. algae, the original host of qnrA, is a
water-dwelling bacterium rarely involved in infections; there is
therefore probably only a small chance of quinolone-resistance
being transferred to E. coli. In contrast, S. maltophilia is an
opportunistic pathogen and thus the chance of Smqnr being
transferred to a human pathogen under selective antibiotic
pressure is higher. Even so, the literature contains no reports of
the transfer of Smqnr to another bacterium, suggesting that
ecological connectivity is not the major bottleneck affecting the
prevalence of a given qnr gene in bacterial pathogens. The fact
that the plasmid encoding the QnrA protein was stable in the
studies made in the present work, whereas the plasmid encoding
SmQnr was rapidly lost by E. coli, shows that differential allelic
fitness costs likely explain much of the probability of quinolone
resistance genes being spread among bacterial populations.
The experimental evolution experiments performed permitted
the selection of compensatory mutations that allowed plasmid
maintenance. However, these mutations occurred in the bacterial
chromosome, and reduced the plasmid copy number. The plasmid
used in these experiments harbours a ColE1 origin of replication.
The regulation of copy number of this family of plasmids involves
Fitness Cost of Qnr Resistance Is Allele-Specific
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several chromosomal genes, some of which deal with plasmid
replication, some with dimers resolution and even some others as
that encoding the bacterial tryptophanase, which are involved in
the basic bacterial metabolism [42,43,44,45]. The identity of the
compensatory mutations remains to be established.
A decrease in plasmid copy number reduces the resistance to
quinolones. Thus, in the presence of antibiotics, the evolved
mutants lost the gain in fitness conferred by the plasmid encoding
SmQnr (lower susceptibility to quinolones) without higher
transmissibility of Smqnr; the plasmid remained unstable upon
transferring to a new host. Even when quinolones were present,
the SmQnr-containing plasmid was lost, and the quinolone-
resistant mutants mainly showed mutations in the genes coding for
bacterial topoisomerases. Further, the co-existence of susceptible
and resistant populations in the same culture, and the finding that
resistant mutants overcome the susceptible population over time,
indicates that concentrations of antibiotic that do not fully inhibit
bacterial growth can select for antibiotic resistance .
It is generally accepted that fitness costs due to the acquisition of
a plasmid-encoded antibiotic resistance gene mainly derive from
the metabolic load involved in the replication, transcription and
translation of the mobile element. The present results show,
however, that fitness costs can be much more specific than
expected, and derive from the epigenetic compatibility of the
determinants encoded by the plasmid with those encoded by the
host genome. Recently published results indicating that epistatic
effects are critical in the acquisition of multidrug resistance 
and in the evolution of bacterial populations  are in line with
the present findings.
Although the similarity of the primary structures of QnrA and
SmQnr is low, they belong to the pentapeptide repeats family, and
model predictions suggest a remarkable similarity in their tertiary
structure with just a few differences at the N terminus (Figure 5).
The present results therefore indicate that, even for antibiotic
resistance determinants with a very similar structure and
mechanism of action, fitness costs can vary greatly, and that these
are due to specific changes in bacterial physiology more than to
any general, non-specific, metabolic burden.
The finding that SmQnr expression incurs no large fitness cost
in an hns mutant strongly supports the idea that SmQnr disturbs E.
coli regulatory networks. H-NS is a nucleoid-associated protein
that modulates the expression of several genes in the latter species
 and can silence the expression of HGT-acquired genes in
Enterobacteriaceae . The effect we observed cannot be attributed
to silencing since the susceptibility to quinolones conferred by the
plasmid encoding SmQnr was slightly lower in the hns mutant than
that in the wild-type strain. Further, silencing should allow
stabilization in the wild-type strain and impair plasmid mainte-
nance in the hns mutant, the opposite to that actually observed.
Since H-NS can modulate DNA supercoiling , and since Qnr
proteins bind bacterial DNA topoisomerases [50,51], it might be
that the effect of SmQnr on E. coli physiology derives from a
stronger effect of this protein than that of QnrA1 on DNA
supercoiling. Alternatively, the effect might be due to a specific
effect on some of the genes that are regulated by H-NS. In this
regard, it has recently been proposed that the connectivity of an
HGT-acquired protein with the cellular networks of the new host,
rather than its function, provides a barrier to HGT .
Antibiotic resistance genes have been said to originate in
producer organisms in which they play an autoprotection role,
Figure 4. Selection of chromosomally-encoded quinolone resistance in strains containing - or not containing - Smqnr. The figure
shows the zones of inhibition of two evolved clones (one containing pBS3.25, the other the pGEM-T vector) over four weeks of evolution under
selective pressure with ofloxacin. Left disk, ofloxacin (5 mg), right disk, nalidixic acid (30 mg). As shown, some scattered resistant colonies appeared
inside the nalidixic acid inhibition zone that, after evolution displaced the otherwise susceptible population. The selection of resistance was
independent of the presence of the SmQnr-coding plasmid pBS3.25.
Figure 5. Overlapping of QnrA1 and SmQnr tertiary structures.
The structures of SmQnr and QnrA1 were modeled at http://
swissmodel.expasy.org/in the automated mode, using the structure of
the QnrB1 protein as a template . Both predicted structures were
overlapped using MacPyMOL. As shown in the Figure, the predicted
structures were very similar. The program did not allow the first 13
amino acids of SmQnr and the first 4 amino acids of QnrA1 to be
modeled. Green QnrA1, orange SmQnr.
Fitness Cost of Qnr Resistance Is Allele-Specific
PLoS ONE | www.plosone.org6May 2012 | Volume 7 | Issue 5 | e35149
similar to the function they have after their transfer to human
pathogens [1,2,52]. However, although the resistance genes
acquired by human pathogens code for proteins in the same
families as found in antibiotic producers , there are still few
examples in which a direct origin can be unequivocally tracked.
One of these cases involves the qnrA gene; this has been found in
the chromosome of different strains of S. algae without any
apparent evidence of its recent acquisition . Since S. algae is not
an antibiotic producer, and since quinolones are synthetic
antibiotics, it is reasonable to think that Qnr determinants cannot
have been selected for avoiding the activity of quinolones. Indeed,
it has been suggested that Qnr proteins are involved in the
adaptation of bacterial cells to different stresses, including
naturally occurring DNA-damaging agents  and cold-shock
A central dogma in evolution is that a change in the function of
a given protein occurs as the consequence of mutations that are
selected under a particular type of pressure. It is thus tempting to
speculate that those determinants whose original function is not
antibiotic resistance are pre-resistance genes that evolved towards
resistance by the selection of proficient mutant variants in the
presence of antibiotics. Since the QnrA1 determinant present in
human pathogens varies by 3 or 4 amino acids to those currently
described for S. algae, it may be that this gene evolved towards
resistance from a former pre-resistance gene. However, the fact
that the Qnr elements encoded in the chromosomes of S. algae
confer low-level quinolone resistance to E. coli goes against this
hypothesis. The term exaptation was coined to describe an
evolutionary process in which a given element acquires a new
function, not because the element itself changes, but because the
environment changes . Our data indicate that, at least for Qnr
determinants, exaptation might be an important evolutionary
process in the acquisition of resistance to antibiotics by human
Materials and Methods
Bacterial Strains, Plasmids and Growth Conditions
The bacterial strains and plasmids used in this work are
described in Table 2. All strains were grown in Luria-Bertani (LB)
broth  at 37uC.
DNA Manipulation, PCR and Sequencing
The genes qnrA1, qnrA3 and qnrA4 were obtained by PCR, using
the Expand Long Template PCR System (Roche) and the primers
QnrAfor and QnrArev (Table S2), using as templates the plasmid
pMG252 for qnrA1, and chromosomal DNA from Shewanella algae
KB-1 and KB-2 for qnrA3 and qnrA4 respectively. The reactions
had one denaturation step at 94uC for 2 min, followed by 10
amplification cycles: 94uC for 30 s, 50uC for 30 s, and 68uC for
2 min, followed by 20 further amplification cycles: 94uC for 30 s,
55uC for 30 s, and 68uC for 2 min, with a final extension step of
68uC for 7 min. The PCR products were electrophoresed in 1%
agarose gels with TAE, removed from the gel using the GFXTM
PCR DNA and Gel Band Purification Kit (GE Healthcare), and
cloned into the pGEM-T vector (Promega), generating the
plasmids pBS18, pBS19 and pBS20, which contained the qnrA1,
qnrA3 and qnrA4 genes respectively. These were used to transform
E. coli KZM120, MC4100 and JMG100 strains as previously
described . The qnr-cloned genes were sequenced by
Macrogen (http://dna.macrogen.com/eng/) to assure that no-
mutation was introduced during the cloning procedure.
The QRDRs of gyrA, gyrB, parC and parE were amplified using
the PCR Master Mix (Promega) and previously described primers
. The complete topoisomerase genes and the hns gene were
amplified using the primers gyrA1/gyrA8, gyrB1/gyrB8, parC1/
parC6, parE1/parE6 and Hns1/Hns2 respectively (Table S2).
PCR products were purified using the QIAquick PCR Purification
Kit (QIAGEN) and sequenced at Macrogen (http://dna.
macrogen.com/eng/) using the primers described in Table S2.
Real Time PCR and RT-PCR
To analyze the expression of hns and Smqnr25, the strains were
grown overnight in LB broth with 100 mg/ml carbenicillin at
37uC. The cultures were then diluted to O.D.600=0.01 and grown
(O.D.600=0.3–0.4). Total RNA was isolated from 30 ml of
exponential cultures using the RNeasy Mini Kit (QIAGEN,
Valencia, CA), treated with Turbo DNA-free reagent (Ambion,
Inc., Austin, TX) and quantified in a Nanodrop spectrophotom-
eter. 400 ng of each sample were used for reverse transcription
with the High-Capacity cDNA Reverse Transcription Kit
(Applied Biosystems). Real-time PCR was performed in a 7300
Real-Time PCR System (Applied Biosystems, Foster, CA, USA),
Table 2. Strains and plasmids used in this work.
StrainDescriptionReference or source
Escherichia coli KZM120
Escherichia coli MC4100araD139 D(argF-lac)U196 rpsL150 relA1 deoC1 ptsF25 rbsR flb B5301 
Escherichia coli JMG100 MC4100 hns-90::Tn10
Shewanella algae KB-1Strain with the gene qnrA3 in its chromosome.
Shewanella algae KB-2 Strain with the gene qnrA4 in its chromosome.
pGEM-T Cloning vector with polyA, ampr
pBS3.25pGEM-T with Smqnr of S. maltophilia E847 
pBS18pGEM-T with qnrA1 of plasmid pMG252 of Klebsiella pneumoniaeThis work
pBS19 pGEM-T with qnrA3 of Shewanella algae KB-1This work
pBS20pGEM-T with qnrA4 of Shewanella algae KB-2This work
pMG252 Clinical plasmid with the gene qnrA1 
Fitness Cost of Qnr Resistance Is Allele-Specific
PLoS ONE | www.plosone.org7 May 2012 | Volume 7 | Issue 5 | e35149
using SYBR Green PCR Master Mix (Applied Biosystems) and the
primers RThnsfwd/rv for the hns gene and RTqnr25fwd/rv for
Smqnr25 gene (Table S2). RNA samples corresponding to four
independent experiments were analyzed. The gapA gene (primers
RTgapAfwd/rv Table S2) was used to normalize the data. The
relative amount of mRNA for hns, and Smqnr25 versus the internal
controls (gapA), was calculated following the 2–DDCtmethod .
The absence of genomic DNA contamination was verified by real-
time PCR of the RNA samples before reverse transcription.
The conditions described above were used to determine the
pBS3.25 plasmid copy number. For this, the copy number of the
blaTEM1gene, present in the plasmid backbone and conferring
resistance to ß-lactams, was determined using the primers
ampRF/R (Table S2) by real-time PCR as described above.
The plasmid copy number was calculated using a standard curve
made using known pBS3.25 copy numbers in the real-time PCR
reaction. All data were normalized to that obtained for the
colonies showing a normal size, which received a value 1.
To estimate the number of cells in a given population
containing the plasmid, sequential dilutions of the cultures to be
tested were seeded onto LB plates containing either 100 mg/ml
carbenicillin, or no antibiotic, and the number of colony forming
units (c.f.u.) recorded after culturing the plates for 24 h at 37uC.
The number of cells carrying the plasmid was estimated as the
ratio of c.f.u. in the presence of carbenicillin and total c.f.u.
(100%). Data for each plasmid are the results of at least four
Susceptibility to Antibiotics
The susceptibility of E. coli MC4100, JMG100 and their
derivatives was analyzed in Mueller Hinton agar (Pronadisa)
containing 0.5 mM isopropyl-thio-ß-D-galactopyranoside (IPTG)
using the Epsilon test (AB Biodisk) following the manufacturer’s
instructions. The susceptibility of the evolved E. coli KZM120
(pBS3.25) and E. coli KZM120 (pGEM-T) derived clones was
analyzed by the agar dilution method in Mueller Hinton agar
containing 0.5 mM IPTG. Each assay was performed at least four
times; results were recorded after 24 h of incubation at 37uC.
Experimental Evolution Assays
E. coli KZM120 (pBS3.25) was grown in LB containing each of
the following antibiotics: 100 mg/ml carbenicillin; 8 ng/ml oflox-
acin (1/2 CMI); 16 ng/ml ofloxacin (CMI); 32 ng/ml ofloxacin
(2X CMI). All cultures were grown for four weeks, with daily
1:1000 dilutions of fresh medium and the corresponding antibiotic.
The same procedure was followed using alternate selection
pressures, i.e., one week with 8 ng/ml ofloxacin and then with
100 mg/ml carbenicillin. As a control for the selection of quinolone
resistant mutants in the absence of Smqnr, the same experimental
evolution assays were preformed with E. coli KZM120 (pGEM-T)
challenged with 8 ng/ml ofloxacin (CMI), 16 ng/ml ofloxacin (2X
CMI) and 32 ng/ml ofloxacin (4X CMI).
QRDR of in vitro evolved clones of E. coli KZM120 pBS3.25
(MBS228-MBS251) and pGEM-T (MBS252-MBS270).
Quinolone susceptibility and mutations in their
Primers used in this work.
We thank Adrian Burton for English editing assistance with the
Conceived and designed the experiments: MBS JLM. Performed the
experiments: MBS. Analyzed the data: MBS JLM. Wrote the paper: MBS
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PLoS ONE | www.plosone.org9May 2012 | Volume 7 | Issue 5 | e35149