Critical Review

Selection and Evolution of Resistance to

Antimicrobial Drugs

Diarmaid Hughes

Department of Medical Biochemistry and Microbiology, Biomedical Center,Uppsala University, Uppsala, Sweden

Abstract

The overuse and misuse of antibiotics over many years has

selected a high frequency of resistance among medically

important bacterial pathogens. The evolution of resistance is

complex, frequently involving multiple genetic alterations that

minimize biological fitness costs and/or increase the resistance

level. Resistance is selected at very low drug concentrations,

such as found widely distributed in the environment, and this

selects for resistant mutants with a high fitness. Once resist-

ance with high fitness is established in a community it is very

difficult to reduce its frequency. Addressing the problem of

resistance is essential if we are to ensure a future where we

can continue to enjoy effective medical control of bacterial

infections. This will require several actions including the dis-

covery and development of novel antibiotics, the creation of a

continuous pipeline of drug discovery, and the implementation

of effective global antibiotic stewardship to reduce the misuse

of antibiotics and their release into the environment. VC 2014

IUBMB Life, 66(8):521–529, 2014

Keywords: antibiotic; fluoroquinolone; rifampicin; fitness; evolution;

resistance; sub-MIC.

IntroductionAntibiotics are the medical wonder of our age. They make pos-sible the safe application of invasive medical procedures wherethe probability of associated bacterial infections is very high,they prolong the lifespan of the elderly and the immunocom-promised, and they reduce morbidity and mortality from com-mon community-acquired infections such as bacterial pneumo-nia (1–4). The widespread perception of antibiotics as wonderdrugs is also the seed to their destruction as an effective medi-cal tool. As wonder drugs they have been grossly overused andabused (5–8). In human therapy, they are often prescribed fornonbacterial infections, and in many parts of the world theyare self-prescribed and sold with little or no medical oversight.In addition, they are added as growth promoters in agricul-tural animal feed, added to the water in aquaculture, or

sprayed onto orchards. A class of drug that was introduced tomedicine to save human lives is now mostly used outside ofhuman medicine. The abuse of antibiotics over the past 70years has exposed global bacterial populations to a selectionpressure to adapt. In abusing antibiotics, humanity has unwit-tingly conducted an uncontrolled experiment in bacterial evo-lution on a global scale with potentially serious negative conse-quences for our continued ability to enjoy the benefits ofmedical knowledge. The result is that today antibiotic-resistance, and frequently multidrug-resistance, is widespreadamong bacterial pathogens.

Resistance compromises our ability to deliver high qualitymedical care in both the community and the hospital environ-ment. Effective antibiotic therapy is essential for manyadvanced medical procedures (e.g., heart transplants or hipreplacements) and for the treatment of cancer patients andothers with suppressed immune systems such as the elderlyand those with AIDS or those undergoing chemotherapy. Inaddition, effective antibiotics are essential for treatmentsrequiring the insertion of catheters, a procedure associatedwith a high risk of bacterial infection. Resistance to antibioticsamong human pathogens increases the risks of treatment fail-ure due to the application of an ineffective antibiotic, it alsoincreases the risk of mortality by increasing the time from aninitial diagnosis to an effective therapy, and it increases mor-bidity by increasing the use of more toxic antibiotics as

VC 2014 International Union of Biochemistry and Molecular BiologyVolume 66, Number 8, August 2014, Pages 521–529

*Address correspondence to: Diarmaid Hughes, Department of MedicalBiochemistry and Microbiology, Biomedical Center, Uppsala University,Box 582, Uppsala, Sweden. E-mail: diarmaid.hughes@imbim.uu.seReceived 26 April 2014; Accepted 21 May 2014DOI 10.1002/iub.1278Published online 16 June 2014 in Wiley Online Library(wileyonlinelibrary.com)

IUBMB Life 521

replacements for those rendered ineffective by resistance(9,10) and imposes an extra healthcare cost and productivityloss that in the EU was estimated as costing at least e1.5 bil-lion in 2007 (Technical Report: The bacterial challenge: timeto react (2009) is available on the website of the EuropeanMedicines Agency, http://www.ema.europa.eu/docs/en_GB/document_library/Report/2009/11/WC500008770.pdf). The increas-ing realization that antibiotic resistance imposes a financialburden on society, in addition to exacerbating personal issuesof morbidity and mortality, is a strong motivation for govern-ments and other stakeholders to adopt measures to addressthe problems caused by antibiotic resistance.

However, before heading bravely into the future andimplementing a raft of measures to deal with a current prob-lem it could be useful to review how we got to this position.This review will examine how bacteria experience andrespond to the selective pressure of antibiotic exposure. Inparticular, the review will discuss evidence that:

i. antibiotic usage is a driving force for resistance frequency;ii. resistance once established is likely to persist in the

population;iii. resistance frequently develops by multistep genetic altera-

tions (MDR can also occur in a single step associated withthe acquisition of a mobile genetic element or overexpres-sion of an efflux system);

iv. fitness is an important issue in the fixation of resistantmutants;

v. selection occurs even at very low antibiotic concentrationssuggesting that selection of resistance can occur in thewider environment;

vi. weak antibiotic selection selects for high fitness.

Finally, the review will outline where we are headed anddiscuss actions that need to be considered if we are to con-tinue to enjoy the medical benefits of effective antibiotics.

Actions Have Consequences

Antimicrobial Resistance Frequency Is Increasing inEuropeThere is reliable information on antibiotic usage and resist-ance frequencies in most European countries, publically avail-able on website of the European Centre for Disease Preventionand Control, ECDC (www.ecdc.europa.eu). The information,contained in the Antimicrobial Resistance Interactive database(EARS-Net, www.ecdc.europa.eu/en/healthtopics/antimicro-bial_resistance/database), covers the most important humanpathogens and antibiotics, and is updated annually. As anexample, the proportion of fluoroquinolone-resistant E. coliisolates has increased significantly throughout Europe in thedecade from 2002 to 2012, the most recent year for whichdata is available (Fig. 1). Overall, the data on EARS-Net showthat there is significant variation in the volume of antibioticusage between European countries, in the use of broad versusnarrow spectrum antibiotics, and in the frequencies of resist-ant pathogens. Although in some cases resistance frequenciesshow a decrease or no change from one year to the next, ingeneral the trend across Europe is for an increasing propor-tion of clinical isolates collected over the past decade to exhibitantibiotic resistance or multidrug-resistance.

Why Is the Frequency of Resistance Increasing?The logical suspicion is that the total amount of antibiotic thatinteracts selectively with bacteria is the major driving force

Fluoroquinolone resistant E. coli in Europe. Increase in the proportion of fluoroquinolone resistant (R1I) E. coli isolates in

Europe from 2002 to 2012. From the website of the European Centre for Disease Prevention and Control (http://www.ecdc.

europa.eu/en/healthtopics/antimicrobial_resistance/database/). [Color figure can be viewed in the online issue, which is avail-

able at wileyonlinelibrary.com.]

FIG 1

IUBMB LIFE

522 EVOLUTION OF RESISTANCE TO ANTIMICROBIAL DRUGS

pushing the global frequency of resistance upward. However,the question is complex and any answer is tentative becausewe are currently observing an uncontrolled experiment, inreal time, where cause and effect are difficult to establish.However, if we accept the hypothesis that it is the relative levelof exposure to antibiotics which correlates positively withselection of resistant clinical isolates, then we must address atleast two related questions: (i) where does this exposure lead-ing to resistance selection occur geographically; and (ii) howdoes exposure lead to the creation of antibiotic-resistanthuman pathogens?

Bacterial exposure to antibiotics not only occurs in thehuman body during therapy but it also occurs in the widerenvironment. A large fraction of the antibiotics used in therapyare excreted in urine in an active form (11), in addition towhich antibiotics are used in very large quantities in veteri-nary medicine, agriculture, and aquaculture (12,13). Thisraises the question of which geographical locations are mostimportant for selecting the resistant pathogens that causeproblems for clinical therapy. For some long-lasting or chronicinfections, such as Mycobacterium tuberculosis causing tuber-culosis or Pseudomonas aeruginosa causing lung infections incystic fibrosis patients, there is good evidence that resistancecan arise by mutation during the course of therapy (14–16).One of the best examples demonstrating the stochastic devel-opment of antibiotic resistance mutations in patients whileundergoing drug therapy is the development of macrolideresistance in Mycobacterium avium septicemia treated bymonotherapy (17). This study analyzed blood isolates of M.avium taken from 38 patients before and after the develop-ment of clarithromycin resistance. Point mutations associatedwith resistance were identified in all resistant relapse isolatesbut in none of the susceptible pretreatment isolates. In vitroinvestigation revealed the same point mutations as observed invivo (17). However, for most combinations of bacteria andantibiotic, where infections are acute and therapy relativelyshort-term, there is very little data showing that resistancearises during therapy, although there are a few well-documented examples (10,18). In the vast majority of acuteinfections whenever resistance is detected it is usually assumedto have pre-existed therapy, leaving open the question of how,when, and where resistant strains arise. Within Europe, wherevery good geographical data are available (www.ecdc.europa.eu/en/healthtopics/antimicrobial_resistance/database), there isa positive correlation between high total levels of antibiotic con-sumption in a country and high proportions of resistant bacte-ria. These data also show a positive correlation between the useof broad-spectrum antibiotics and higher proportions of resist-ant bacteria. The tentative conclusion is that the quantity andquality of antibiotics used in medicine in a country is an impor-tant factor in predicting the proportion of resistant bacteria inthat country, with the important caveat that this does not takeinto account antibiotics used outside of human medicine. Animportant implication of this correlation between total antibi-otic usage in human medicine and frequency of resistance in

different countries is that it suggests that local policies on anti-biotic usage could in principle be used to influence the local fre-quency of resistance.

Acquired antibiotic resistance arises by two different bio-logical processes: (i) mutation within the existing genome thatreduces antibiotic susceptibility and (ii) acquisition of horizon-tally transferred genetic material that introduces a novel geneconferring reduced susceptibility to an antibiotic (19). Forexample, resistance to the first-line drug rifampicin in M.tuberculosis arises exclusively by mutation (there is little or nohorizontal genetic transfer, HGT, into this bacterial species). Incontrast, resistance to b-lactam antibiotics in E. coli is almostexclusively by HGT of plasmids carrying a gene encoding a b-lactamase enzyme. Resistance to fluoroquinolones in E. coli istypically a mixture of the two mechanisms: chromosomalmutations in target and efflux-regulator genes are nearlyalways present, but often in combination with a plasmidencoding a gene that further reduces susceptibility (20). Eachmechanism of resistance is more or less relevant to the clinicalsituation depending on the particular combination of bacterialspecies and antibiotic.

Can Local Actions Mitigate or Minimize the ResistanceProblem?One can compare neighboring countries with significantly dif-ferent levels of antibiotic consumption for evidence that localpolicy can affect resistance frequency. The ECDC (www.ecdc.europa.eu) issues annual reports on the antibiotic consumption(in defined daily doses, DDD, per 1,000 inhabitants per day:DID) for 29 European member countries (Fig. 2). The datashow that annual consumption differs by a factor 3.1 betweenthe highest in Greece (35.1 DID) and the lowest in the Nether-lands (11.4 DID). Huge differences in consumption betweencountries have also recently been reported for eastern Europe,ranging from 15.3 DID in Armenia up to 42.3 DID in Turkey(21). It is especially instructive to compare the Netherlandswith its immediate geographical neighbor, Belgium. Thesecountries cover similar geographical areas, have similarlysized populations, and share an open border allowing peopleto travel freely between the countries, but have separatehealthcare systems and implement significantly differentantibiotic-usage policies. Belgium has a significantly greaterper capita consumption of antibiotics (29.0 DID) than the Neth-erlands (11.4) and this is associated with a significantly higherproportion of resistant bacterial isolates. For example, the flu-oroquinolone resistance data from 2011 recorded for E. coli,K. pneumoniae, and P. aeruginosa. Belgium consumed 2.7 DIDfluoroquinolones versus 0.8 DID in the Netherlands. Fluoroqui-nolone resistance for these three species was recorded as22%, 15%, and 21%, respectively, in Belgium, versus 14%, 7%,and 7% for the same species in the Netherlands. Similar differ-ences are found for b-lactams, macrolides, and aminoglyco-sides. A reasonable conclusion is that locally enforced restric-tive antibiotic usage practices can be beneficial and associatedwith locally lower frequencies of resistance.

HUGHES ET AL. 523

Antibiotic Resistance has a Fitness CostOne reason why restrictive usage of antibiotics might slow therate of increase in the frequency of resistant isolates in a geo-graphical area is that resistant bacteria often have a lowerbiological fitness than susceptible strains. Experimental studieshave shown that the occurrence or acquisition of antibioticresistance is often associated, at least initially, with a reduc-tion in bacterial fitness (22–25). Relative fitness can be definedas a reduction in growth rate in vitro or in vivo or in terms ofcolonization, transmissibility, or virulence. There are severalreasons why a correlation between resistance and reduced fit-ness is expected. One is that target mutations that reduce theantibiotic affinity frequently reduce the activity of essentialbacterial enzymes. Because antibiotics disrupt essential activ-ities in bacteria (cell wall building, protein synthesis, RNAtranscription, DNA replication) the specific molecular targetsof antibiotics are usually essential and conserved and muta-tional alterations usually reduce their specific activity withnegative effects on bacterial fitness. However, a large part ofthe clinical resistance problem is caused by the acquisition ofplasmids expressing genes for enzymes, such as b-lactamases,that reduce the effectiveness of antibiotics without altering theessential target. The evidence suggests that resistance due toHGT, or alteration of regulation of the resistance mechanism,

is frequently associated with reduced fitness, at least initially,but that these costs can be quickly ameliorated by compensa-tory evolution (26,27). The frequent correlation between anti-biotic resistance and fitness costs has raised the questionwhether restrictive usage could be used to as a lever to reducethe frequency of resistant pathogens. The logic of the sugges-tion is that a high frequency of an antibiotic-resistant pathogenwith low-fitness can only be maintained in the population bythe selective pressure of antibiotics.

Resistance PersistsThe possibility that restricting antibiotic usage might result in areduction in the frequency of resistant bacteria has been testedin several studies made in closed environments such as hospi-tals and in open community environments (28). Interventions inclosed systems like hospitals generally show a high level of suc-cess and reduction in resistance frequency can be observedwithin weeks to months (29–31). In addition to possible fitnesscosts an important factor contributing to the success of inter-ventions in hospitals is a dilution effect where the incomingpopulation reduces the frequency of resistance within the hospi-tal (32–34). Interventions in community settings have not beenso successful. A 97% decrease in the consumption of trimetho-prim/sulfamethoxazole in the UK between 1991 and 1999 didnot result in a reduction in sulfamethoxazole resistance (35). Intwo other studies, in Finland and Iceland, restriction was associ-ated with a fall in the subsequent frequency of resistance but thepossibility that clonal shifts rather than fitness costs were thecause, was not addressed or ruled out (36,37). A recent prospec-tive study made in Sweden (38) failed to show any major effect ofrestricting trimethoprim for a 2-year period in a particularSwedish county. The study was controlled with regard to compli-ance, information on previous and concurrent resistance fre-quencies and antibiotic usage, as well as having an equivalentset of data from a comparator county in Sweden. The main con-clusion was that even with very good compliance in restrictinguse of one class of antibiotic (80% reduction in use for the 2-yearperiod), the reduction in the frequency of resistance was mar-ginal and it would require a much longer intervention to achieveeven a small reduction. The authors speculated that confoundingfactors inhibiting a greater reduction in resistance frequencywere possibly a low biological fitness cost of the resistance, andpossible genetic co-selection by the antibiotics used as a replace-ment for the one that was restricted (38). The overall conclusionfrom these studies is that once antibiotic resistance is establishedin a bacterial population it may prove to be very difficult toreverse the process by a policy of restrictive usage (28).

Fitness is Important in the ClinicalSelection of ResistanceThe evidence from in vitro experiments is that antibioticresistance almost always comes with a fitness cost. However,

Differences in antibiotic consumption in different coun-

tries of Europe. Geographical distribution of antimicro-

bial consumption of antibacterials for systemic use in

the community (primary care sector) in Europe, report-

ing year 2011. From the website of the European

Centre for Disease Prevention and Control (http://www.

ecdc.europa.eu/en/healthtopics/antimicrobial_resistance/

database/). [Color figure can be viewed in the online

issue, which is available at wileyonlinelibrary.com.]

FIG 2

IUBMB LIFE

524 EVOLUTION OF RESISTANCE TO ANTIMICROBIAL DRUGS

these experiments also show that the magnitude of the fitnesscost can vary depending on the particular genetic alteration,and in some cases the cost is too small to be measured sug-gesting that it may be entirely absent. This raises the questionof whether relative fitness costs play any role in the clinicalselection of resistant variants. This is an important question toanswer but is difficult to address in a meaningful manner,partly because clinical isolates with resistance phenotypesoften have very complex differences in genotype, making it dif-ficult to make comparisons and definitively link cause witheffect. However, the question has been successfully addressedin M. tuberculosis by applying in vitro information on the rela-tive fitness of different streptomycin resistance mutations (dif-ferences in in vitro growth rates associated with differentmutant alleles) with the relative frequencies of these samealleles among clinical tuberculosis isolates. The analysis ispossible in M. tuberculosis because the species is relativelyuniform genetically, with little or no influence from HGT. Theresults were clear and striking (39). Streptomycin resistantmutants selected in vitro in M. smegmatis (a genetic model forMycobacteria) and in M. tuberculosis each carried one of sev-eral different single amino acid substitutions at codon 42 inribosomal protein S12, each allele arising spontaneously atsimilar frequencies. In contrast, when streptomycin-resistantclinical isolates of M. tuberculosis were examined the resultwas very different. Of 90 resistant isolated tested, 89 carriedone particular allele: Lys42 substituted with Arg42 (39). Thismutant allele has no measureable fitness cost in vitro. Thisresult suggests that at least for streptomycin resistance in M.tuberculosis there is a strong bias in favor of a low-cost resist-ance mutation, and that therefore biological fitness is animportant selected parameter in the development of antibioticresistance.

Evolution of Resistance is Often aMultistep ProcessThe data on the selection of streptomycin resistance above (39),and similar data on other aminoglycosides and macrolides(40,41), show that single nucleotide mutations are sufficient tocause a high-level resistance phenotype. This is the classicalview of resistance development: that resistance occurs becauseof a single event: either the occurrence of a mutation or theacquisition of a resistance gene by HGT. However, while theexample of Lys42Arg causing streptomycin resistance in M.tuberculosis is a good illustration of one change causing clini-cally relevant resistance, there are good reasons for thinkingthat in many cases resistance development is a multistep evolu-tionary process (Fig. 3). Two examples are discussed below.

Genetic Compensation of Fitness Costs of ResistanceThere are many examples of in vitro antibiotic resistance evo-lution where the high fitness cost of a primary resistancemutation has been shown to be genetically compensated bythe acquisition of secondary mutations in the same or other

genes (23,25,42,43). However, it is more difficult to test whetherthat compensatory evolution occurs during clinical resistanceselection. Once again, M. tuberculosis is the source of some con-vincing examples of fitness compensatory evolution. Kanamycinresistance in M. tuberculosis arises by the occurrence of anyone of several different point mutations in the gene for 16SrRNA (A1408G, C1409U, G1491U, and the double mutationC1409A/G1491U). When the frequencies of each mutant allelewere measured in clinical isolates, one allele, A1408G, was mostfrequent being found in 95% of isolates. This suggested thatA1408G was probably a low cost mutation. Each of the mutantalleles was genetically reconstructed in an isogenic wild-typebackground and their relative fitness and resistance levelsmeasured (44). This analysis confirmed that the most frequentallele was indeed a relatively low cost allele that conferred avery high level of resistance (minimal inhibitory concentration[MIC] >1,024), explaining its high frequency among resistantclinical isolates. Especially interesting was the phenotype of dou-ble mutation allele that was isolated at a higher frequency(C1409A/G1491U, 1.2%) than a single mutation allele (G1491U,0.6%). When the phenotypes of the reconstructed strains weremeasured the rare single mutation was found to confer a mod-erate level of resistance (MIC 64) but to have a very high fitnesscost (12% per generation). In contrast, the double mutant alsoconferred a moderate level of resistance (MIC 16) but was essen-tially cost free (0.1% per generation). This seems to be a genuineexample of fitness compensatory evolution occurring during thedevelopment of clinical resistance.

Another example where fitness compensatory evolutionprobably occurs clinically is during the development of rifam-picin resistance in M. tuberculosis. Rifampicin is a first lineantibiotic in the treatment of M. tuberculosis but in vitro selec-tion in many species have shown that high-level resistancearises as a result of individual point mutation in rpoB,

Multistep evolution of antibiotic resistance. A general

model illustrating evolutionary paths for a lineage

under antibiotic selection. Resistance may arise with-

out loss of fitness but more often will involve a loss

of fitness and the possibility of additional mutations

to restore fitness without loss of resistance. [Color

figure can be viewed in the online issue, which is

available at wileyonlinelibrary.com.]

FIG 3

HUGHES ET AL. 525

encoding the b-subunit of RNA polymerase, the molecular tar-get of the antibiotic. Recently, whole genome sequencing of M.tuberculosis isolates has shown a strong correlation betweenrifampicin resistance and the presence of additional mutationsin genes for different subunits of RNA polymerase (45,46).Genetic analysis is difficult in M. tuberculosis so it could onlybe speculated that the presence of additional mutations mightbe an example of fitness compensatory evolution. Support forthe compensatory hypothesis came from a genetic analysismade in Salmonella enterica (47,48). They showed that rifam-picin resistance arises by the selection of any one of severalmutations in a small region of rpoB and that most of thesemutations have a significant fitness cost. When mutant strainswere evolved in vitro they rapidly acquired secondary muta-tions that were shown by genetic reconstruction to be fitnesscompensatory mutations. These compensatory mutationsoccurred in the genes for each of the major subunits of RNApolymerase, and tellingly they mapped in very similar loca-tions to the additional mutations discovered in rifampicin-resistant M. tuberculosis isolates. These data strongly suggeststhat the development of resistance to rifampicin in M. tubercu-losis very frequently involves the selection of second-site fit-ness compensatory mutations.

The data presented above concerning in vitro competitionassays and the relative clinical prevalence of specific antibioticresistance mutations strongly suggest that at least some antibi-otic resistance mutations impose a fitness cost on M. tubercu-losis. Given that M. tuberculosis grows very slowly one couldask what is the nature of that fitness cost: is it growth rate orsome other parameter? A recent population-scale analysis ofnatural populations of M. tuberculosis has found evidence thatgenes involved in transport and in the metabolism of inorganicions are under strong purifying selection (49). The authorsspeculate that the hostile within-host environment imposesstrict demands on M. tuberculosis physiology, and that thisassociates a substantial fitness cost with new mutations,accounting for the purifying selection. The targets of antibiot-ics for which fitness costs have been demonstrated in vitro arein the ribosome and the RNA polymerase. Alterations in thesetargets will very likely result in pleiotropic effects on bacterialphysiology in addition to their influence on drug susceptibility.Accordingly, while it is possible that reduced relative growthrate per se is the relevant in vivo fitness cost of antibioticresistance, it is also possible that growth-rate-neutral altera-tions in cell physiology associated with the resistance muta-tions cause the actual fitness cost in the patient. Regardless,the current data suggest that measurements of growth com-petitiveness in vitro are a good surrogate measure for the rela-tive fitness of M. tuberculosis in vivo.

When One Change is Insufficient to Confer ClinicalResistanceAnother situation in which multistep evolution occurs is whena single genetic change is insufficient to confer a clinically rel-evant level of resistance. This is the situation with regards to

fluoroquinolone resistance and E. coli (24,50). There is no sin-gle genetic alteration that is known to confer resistance in E.coli. Individual target mutations, efflux regulator mutations, orplasmids expressing resistance genes, all result in an MIC thatis at best 5–10-fold below the clinical breakpoint. Resistantclinical isolates always carry multiple resistance mutationsand frequently also carry resistance plasmids. A typicalfluoroquinolone-resistant E. coli isolate will have four to sixand possibly more genetic alterations directly linked withincreasing the MIC (50,51).

Selection Occurs Way Below MicAntibiotic resistant mutants will be selectively enriched in adrug concentration range referred to as the mutant selectivewindow (MSW). The MSW has been defined as the antibioticconcentration range between the MIC of a susceptible strainand the mutant preventive concentration (MPC) of the most-resistant single-step mutant (52). In other words, at concentra-tions above the MIC, concentrations that prevent the growth ofthe susceptible strain, mutants with reduced susceptibility willbe selected. However, this traditional model does not take intoaccount what happens at concentrations below the MIC of thesusceptible strain. Sub-MIC concentrations occur at the begin-ning and end of therapy due to the pharmacodynamics ofdrugs. Sub-MIC concentrations will also occur during therapydue to poor drug penetration at certain body sites, poorpatient compliance, or inadequate dosing regimen that allowsconcentrations to go below MIC, and will occur very frequentlywhen antibiotics are diluted in the wider environment. It hasbeen speculated that low concentrations of antibiotics mightplay a role in the selection of clinical resistance (53,54) but itis only recently that experimental tests of the effects of antibi-otics at sub-MIC on the selection of resistance have been made(55,56). In these studies the relative competitive fitness of iso-genic mutants carrying common resistance mutations or geneswas measured at a range of antibiotic concentrations. Themajor finding of both studies was that mutants were in everycase tested selected at antibiotic concentrations below the MICof the susceptible strain. The logic of sub-MIC antibiotic selec-tion is illustrated in Fig. 4. In the absence of any antibiotic thesusceptible strain typically has a competitive advantage(because of the fitness cost of the resistance determinant).However, at a certain concentration the inhibitory effect of theantibiotic on the susceptible strain will balance the fitness costof the resistance determinant. This is the minimal selectiveconcentration (MSC), above which the resistant strain has aselective advantage. In the concentration range between theMSC and the MIC both strains can grow but the resistantstrain has a competitive advantage and will be enriched. Inthe traditional selective window, above the MIC of the suscepti-ble strain, only the resistant mutant can grow.

There are several important conclusions that came out ofthese studies. One is that sub-MIC selection occurred with allantibiotics tested. A second is that sub-MIC also selected de

IUBMB LIFE

526 EVOLUTION OF RESISTANCE TO ANTIMICROBIAL DRUGS

novo resistance (55). A third is that the concentration rangefor sub-MIC selections went as low as more than 200-foldbelow the MIC of the susceptible strain (55). Thus for the mostcommon mutation associated with ciprofloxacin resistance,GyrA Ser83Leu, the MSC was 1/230 MIC and 0.1 ng/mL. Thisconcentration is below the ciprofloxacin concentration foundin many natural environments (57–59) and suggests that sub-MIC selection of resistance might be a relevant and wide-spread phenomenon in nature. This returns us to the questionof whether resistance is primarily selected and enriched byantibiotic contamination in the wider environment, prior tobecoming as a problem in human infections.

Weak Selection Selects Low-Cost(High-Fitness) MutantsThe significance of sub-MIC selection is twofold. One is that itvastly extends the geographical area where antibiotic resist-ance can be selected, to include soils, lakes, rivers, seas, aswell as compartments in the human body undergoing antibiotictherapy, and less susceptible members of the human micro-biome. However, a second and potentially even more importantconsequence of sub-MIC selection is that it intrinsically selectsfor low-cost resistance. The reason for this connection is appa-rent in Fig. 4. Increasing concentrations of antibiotic progres-sively reduce the relative fitness of a susceptible strain. In gen-eral the relative magnitude of the reduction in fitness (e.g.,growth rate) caused by an antibiotic acting on a susceptiblestrain will be proportional to the concentration of the antibi-otic. For any pair of susceptible and resistant strains there willbe some antibiotic concentration at which their fitness differ-ence is zero. Accordingly, if the intrinsic fitness differencebetween the strains, in the absence of antibiotic, is very smallit will only require the presence of a relatively low antibiotic

concentration to equalize their fitness. Any antibiotic concen-tration above this value (the MSC, minimal selective concentra-tion) will further suppress the relative fitness of the susceptiblestrain and confer an advantage on the mutant strain. This isthe situation for GyrA Ser83Leu which is selected at 1/230 theMIC of the susceptible wild-type (55). Its low fitness cost mayexplain why it is so prevalent among resistant clinical isolates(50,51). Concentrations of ciprofloxacin found widely in naturalenvironments will be sufficiently high to give a growth advant-age to mutant variants carrying the Ser83Leu resistance muta-tion. The implication is that if clinical resistance evolves viasub-MIC selection then it is likely to be associated with verylow fitness costs and will not be amenable to reversal byrestrictive usage policies that are imposed after resistance hasbeen established in the community.

Summary and Conclusions: What Canor Should We Do to Address theProblems?This review summarizes some of what we know about thebiology of antibiotic resistance selection and points out thatthere are still many gaps in our knowledge. What is clear atthis stage is that a high frequency of resistance, once estab-lished in the community for a particular combination of patho-gen and antibiotic, is very unlikely to be reduced by the subse-quent introduction of restrictive usage policies. It will alreadybe too late, the reason being that resistance will most likelyalready have been selected for a very low fitness cost.

Human medicine, relying heavily on effective antibiotics,faces a potential crisis in the coming years unless solutionscan be found. Here are some obvious suggestions for actionsto address the situation.

i. Restrict the use of antibiotics, and their release into the widerenvironment, to reduce selection pressure. As argued above,restrictive use after resistance is established is unlikely toreduce the frequency of resistance, but it might reduce therate at which the frequency of resistance to existing antibiot-ics increases. This will be important to buy time whileresearch and development to find novel antibiotics continues.In addition, if and when novel antibiotics are introduced tothe clinic, having such restrictive measures in place from thebeginning will be important to reduce resistance selectionand prolong the effective lifespan of the new drugs.

ii. Develop improved therapies, including combination thera-pies with existing drugs, that are effective against currentresistant strains. This action may buy some time while newantibiotics are researched but it is very unlikely to providea long-term solution.

iii. Develop improved diagnostics. These should be available atthe point of care and should include rapid tests for suscep-tibility to support the use of the most appropriate antibiotictherapy, and so that narrow spectrum antibiotic therapy

Antibiotic selective windows theory. Between the MIC

of the susceptible strain, MICsusc, and the minimal

selective concentration (MSC) there is a sub-MIC

selective window where both susceptible and resist-

ant mutants can grow but resistant mutants are selec-

tively enriched by the antibiotic. Reproduced from

Ref. 55). [Color figure can be viewed in the online

issue, which is available at wileyonlinelibrary.com.]

FIG 4

HUGHES ET AL. 527

becomes a more attractive and widely used option. Thiscould have the dual benefit of improving the economics ofnarrow spectrum drug development and also reduce theselection pressure for resistance by minimizing the expo-sure experienced by nontargeted bacteria.

iv. Develop new antibiotic drugs that are active against cur-rent resistant strains. Included here could be not only clas-sical antibiotics but also adjuvants that enhance the effectsof antibiotics, and antivirulence drugs that may also proveeffecting in infection control. The discovery and develop-ment of novel drugs is the only realistic long-term option tomaintain effective infection control in medicine. However,its success will depend not only on scientific discovery anddevelopment but also on establishing a viable economicmodel to ensure a continuous pipeline of drugs, and anappreciation of the value of antibiotic stewardship toensure that new drugs remain effective for a long time.

v. Improve the quality of hygiene measures, both at the hospi-tal and in the community, including reducing the release ofantibiotics into the environment.

The political realization that effective healthcare faces apotential crisis because of antibiotic resistance has recentlyresulted in major initiatives being taken in both Europe and theUSA to tackle the problem. The European Union via its Innova-tive Medicines Initiative has launched the New Drugs for BadBugs (ND4BB) programme in 2012 to tackle a range of issuesassociated with antibiotics and antibiotic-resistance (60). Theaim is to combat antibiotic resistance by tackling the scientific,regulatory, and business challenges that hamper the develop-ment of new antibiotics. One of the programmes in ND4BB,ENABLE, is charged with advancing the development of novelantibiotics against Gram-negative bacteria and with identifyingpromising antimicrobial candidates for testing in clinical trials.The overall aim of ND4BB is to encourage public-private collab-orations to improve early-stage antibacterial drug discoveryand help make a sustainable impact on the future of antibacte-rial drug discovery. The reasonable assumption is that resist-ance will ultimately limit the effective useful lifespan of any newantibiotics introduced to the clinic. The long-term solution is todevelop a continuous and sustained drug discovery pipeline andto put in place antibiotic stewardship policies that ensure maxi-mum medical benefit from these investments.

AcknowledgementsD.H. acknowledges support from Vetenskapsrådet (SwedishScience Council), SSF (Swedish Strategic Science Foundation),Vinnova (Swedish Innovation Science), and the Knut and AliceWallenberg Foundation (RiboCore Project).

References

[1] Amin, A. N., Cerceo E. A., Deitelzweig S. B., Pile J. C., Rosenberg, D. J., et al.

(2014) The hospitalist perspective on treatment of community-acquired bacte-

rial pneumonia. Postgrad. Med. 126:18–29.

[2] Thiem, U., Heppner, H. J., and Pientka, L. (2011) Elderly patients with

community-acquired pneumonia: optimal treatment strategies. Drugs Aging

28:519–537.

[3] Schlesinger, A., Paul, M., Gafter-Gvili, A., Rubinovitch, B., and Leibovici, L.

(2009) Infection-control interventions for cancer patients after chemotherapy:

a systematic review and meta-analysis. Lancet Infect. Dis. 9:97–107.

[4] Becker, J. U., Theodosis, C., Jacob, S. T., Wira, C. R., and Groce, N. E. (2009)

Surviving sepsis in low-income and middle-income countries: new directions

for care and research. Lancet Infect. Dis. 9:577–582.

[5] Ilic, K., Jakovljevic, E., and Skodric-Trifunovic, V. (2012) Social-economic fac-

tors and irrational antibiotic use as reasons for antibiotic resistance of bacte-

ria causing common childhood infections in primary healthcare. Eur. J.

Pediatrics 171:767–777.

[6] Nga do, T. T., Chuc, N. T., Hoa, N. P., Hoa, N. Q., Nguyen, N. T., et al. (2014)

Antibiotic sales in rural and urban pharmacies in northern Vietnam: an

observational study. BMC Pharmacol. Toxicol. 15:6.

[7] Holloway, K. A., Ivanovska, V., Wagner, A. K., Vialle-Valentin, C., and Ross-

Degnan, D. (2013) Have we improved use of medicines in developing and

transitional countries and do we know how to? Two decades of evidence.

Trop. Med. Int. Health 18: 656–664.

[8] Kotwani, A., Wattal, C., Joshi, P. C., and Holloway, K. (2012) Irrational use of

antibiotics and role of the pharmacist: an insight from a qualitative study in

New Delhi, India. J. Clin. Pharm. Ther. 37:308–312.

[9] McCaughey, G., Gilpin, D., Elborn, J., and Tunney, M. M. The future of anti-

microbial therapy in the era of antibiotic resistance in cystic fibrosis pulmo-

nary infection. Exp. Rev. Respir. Med. 7:385–96.

[10] McGann, P., Courvalin, P., Snesrud, E., Clifford, R. J., Yoon, E. J., et al.

(2014) Amplification of aminoglycoside resistance gene aphA1 in Acineto-

bacter baumannii results in tobramycin therapy failure. MBio 5:e00915.

[11] Bryskier, A., ed. (2005) Antimicrobial Agents: Antibacterials and Antifungals,

ASM Press, Washington, DC.

[12] Sarmah, A. K., Meyer, M. T., and Boxall, A. B. (2006) A global perspective

on the use, sales, exposure pathways, occurrence, fate and effects of veteri-

nary antibiotics (Vas) in the environment. Chemosphere 65:725–759.

[13] Sukul, P. and Spiteller, M. (2007) Fluoroquinolone antibiotics in the environ-

ment. Rev. Environ. Contam. Toxicol. 191:131–162.

[14] McCaughey, G., Diamond, P., Elborn, J. S., McKevitt, M., and Tunney, M. M.

(2013) Resistance development of cystic fibrosis respiratory pathogens

when exposed to fosfomycin and tobramycin alone and in combination

under aerobic and anaerobic conditions. PloS one 8:e69763.

[15] Marvig, R. L., Johansen, H. K., Molin, S., and Jelsbak, L. (2013) Genome

analysis of a transmissible lineage of pseudomonas aeruginosa reveals

pathoadaptive mutations and distinct evolutionary paths of hypermutators.

PloS Genet. 9:e1003741.

[16] Matteelli, A., Roggi, A., and Carvalho, A. C. (2014) Extensively drug-resistant

tuberculosis: epidemiology and management. Clin. Epidemiol. 6:111–118.

[17] Meier, A., Heifets, L., Wallace, R. J. Jr., Zhang, Y., Brown, B. A., et al. (1996)

Molecular mechanisms of clarithromycin resistance in Mycobacterium

avium: observation of multiple 23S rDNA mutations in a clonal population.

J. Infect. Dis. 174:354–360.

[18] Holmes, N. E., Ballard, S. A., Lam, M. M., Johnson, P. D., Grayson, M. L.,

et al. (2013) Genomic analysis of teicoplanin resistance emerging during

treatment of vanB vancomycin-resistant Enterococcus faecium infections in

solid organ transplant recipients including donor-derived cases. J. Antimi-

crob. Chemother. 68:2134–2139.

[19] Tenover, F. C. (2006) Mechanisms of antimicrobial resistance in bacteria.

Am. J. Infect. Control 34(Suppl 1):S3–S10; discussion S64 – 7S3.

[20] Jacoby, G. A. (2005) Mechanisms of resistance to quinolones. Clin. Infect.

Dis. 41(Suppl 2):S120–S126.

[21] Versporten, A., Bolokhovets, G., Ghazaryan, L., Abilova, V., Pyshnik, G.,

et al. (2014) Antibiotic use in eastern Europe: a cross-national database

study in coordination with the WHO Regional Office for Europe. Lancet

Infect. Dis. 14:381–387.

[22] Andersson, D. I. and Hughes, D. (2010) Antibiotic resistance and its cost: is

it possible to reverse resistance? Nat. Rev. Microbiol. 8:260–271.

IUBMB LIFE

528 EVOLUTION OF RESISTANCE TO ANTIMICROBIAL DRUGS

[23] Nagaev, I., Bjorkman, J., Andersson, D. I., and Hughes, D. (2001) Biological

cost and compensatory evolution in fusidic acid-resistant Staphylococcus

aureus. Mol. Microbiol. 40:433–439.

[24] Marcusson, L. L., Frimodt-Moller, N., and Hughes, D. (2009) Interplay in the

selection of fluoroquinolone resistance and bacterial fitness. PloS Pathog 5:

e1000541.

[25] Schrag, S. J., Perrot, V., and Levin, B. R. (1997) Adaptation to the fitness

costs of antibiotic resistance in Escherichia coli. Proc. Biol. Sci. 264:1287–

1291.

[26] Dahlberg, C. and Chao, L. (2003) Amelioration of the cost of conjugative

plasmid carriage in Eschericha coli K12. Genetics 165:1641–1649.

[27] Starikova, I., Al-Haroni, M., Werner, G., Roberts, A. P., Sorum, V., et al.

(2013) Fitness costs of various mobile genetic elements in Enterococcus fae-

cium and Enterococcus faecalis. J. Antimicrob. Chemother. 68:2755–2765.

[28] Andersson, D. I. and Hughes, D. (2011) Persistence of antibiotic resistance

in bacterial populations. FEMS Microbiol Rev 35:901–911.

[29] McGowan, J. E. Jr. (1986) Minimizing antimicrobial resistance in hospital

bacteria: can switching or cycling drugs help? Infect. Control 7: 573–576.

[30] Mahamat, A., MacKenzie, F. M., Brooker, K., Monnet, D. L., Daures, J. P.,

et al. (2007) Impact of infection control interventions and antibiotic use on

hospital MRSA: a multivariate interrupted time-series analysis. Int. J. Anti-

microb. Agents 30:169–176.

[31] Aldeyab, M. A., Monnet, D. L., Lopez-Lozano, J. M., Hughes, C. M., Scott, M.

G., et al. (2008) Modelling the impact of antibiotic use and infection control

practices on the incidence of hospital-acquired methicillin-resistant Staphy-

lococcus aureus: a time-series analysis. J. Antimicrob. Chemother. 62:593–

600.

[32] Austin, D. J. and Anderson, R. M. (1999) Studies of antibiotic resistance

within the patient, hospitals and the community using simple mathematical

models. Philos. Trans. R Soc. Lond. B Biol. Sci. 354:721–738.

[33] Lipsitch, M., Bergstrom, C. T., and Levin, B. R. (2000) The epidemiology of

antibiotic resistance in hospitals: paradoxes and prescriptions. Proc. Natl.

Acad. Sci. USA 97:1938–1943.

[34] Bonten, M. J., Austin, D. J., and Lipsitch, M. (2001) Understanding the

spread of antibiotic resistant pathogens in hospitals: mathematical models

as tools for control. Clin Infect Dis 33:1739–1746.

[35] Enne, V. I., Livermore, D. M., Stephens, P., and Hall, L. M. (2001) Persistence

of sulphonamide resistance in Escherichia coli in the UK despite national

prescribing restriction. Lancet 357:1325–1328.

[36] Sepp€al€a, H., Klaukka, T., Vuopio-Varkila, J., Muotiala, A., Helenius, H., et al.

(1997) The effect of changes in the consumption of macrolide antibiotics on

erythromycin resistance in group A streptococci in Finland. Finnish Study

Group for Antimicrobial Resistance. N. Engl. J. Med. 337:441–446.

[37] Kristinsson, K. G. (1997) Effect of antimicrobial use and other risk factors on

antimicrobial resistance in Pneumococci. Microb. Drug Resist. 3:117–123.

[38] Sundqvist, M., Geli, P., Andersson, D. I., Sjolund-Karlsson, M., Runehagen,

A., et al. (2009) Little evidence for reversibility of trimethoprim resistance

after a drastic reduction in trimethoprim use. J. Antimicrob. Chemother. 65:

350–360.

[39] Bottger, E. C., Springer, B., Pletschette, M., and Sander, P. (1998) Fitness of

antibiotic-resistant microorganisms and compensatory mutations. Nat. Med.

4:1343–1344.

[40] Pfister, P., Corti, N., Hobbie, S., Bruell, C., Zarivach, R., et al. (2005) 23S

rRNA base pair 2057–2611 determines ketolide susceptibility and fitness

cost of the macrolide resistance mutation 2058A ! G. Proc. Natl. Acad. Sci.

USA 102:5180–5185.

[41] Sander, P., Springer, B., Prammananan, T., Sturmfels, A., Kappler, M., et al.

(2002) Fitness cost of chromosomal drug resistance-conferring mutations.

Antimicrob. Agents Chemother. 46:1204–1211.

[42] Johanson, U., Aevarsson, A., Liljas, A., and D. Hughes (1996) The dynamic

structure of EF-G studied by fusidic acid resistance and internal revertants.

J. Mol. Biol. 258:420–432.

[43] Bjorkman, J., Hughes, D., and Andersson, D. I. (1998) Virulence of antibiotic-

resistant Salmonella typhimurium. Proc. Natl. Acad. Sci. USA 95:3949–3953.

[44] Shcherbakov, D., Akbergenov, R., Matt, T., Sander, P., Andersson, D. I.,

et al. (2010) Directed mutagenesis of Mycobacterium smegmatis 16S rRNA

to reconstruct the in-vivo evolution of aminoglycoside resistance in Myco-

bacterium tuberculosis. Mol. Microbiol. 77:830–840.

[45] Comas, I., Borrell, S., Roetzer, A., Rose, G., Malla, B., et al. (2012) Whole-

genome sequencing of rifampicin-resistant Mycobacterium tuberculosis

strains identifies compensatory mutations in RNA polymerase genes. Nat.

Genet. 44:106–110.

[46] Casali, N., Nikolayevskyy, V., Balabanova, Y., Ignatyeva, O., Kontsevaya, I.,

et al. (2012) Microevolution of extensively drug-resistant tuberculosis in

Russia. Genome Res. 22:735–745.

[47] Brandis, G., Wrande, M., Liljas, L., and Hughes, D. (2012) Fitness-compensatory

mutations in rifampicin-resistant RNA polymerase. Mol. Microbiol. 85:142–151.

[48] Brandis, G. and Hughes, D. (2013) Genetic characterization of compensatory

evolution in strains carrying rpoB Ser531Leu, the rifampicin resistance

mutation most frequently found in clinical isolates. J. Antimicrob. Chemo-

ther. 68:2493–2497.

[49] Pepperell, C. S., Casto, A. M., Kitchen, A., Granka, J. M., Cornejo, O. E.,

et al. (2013) The role of selection in shaping diversity of natural M. tubercu-

losis populations. PLoS Pathogens 9:e1003543.

[50] Komp Lindgren, P., Karlsson, Å., and Hughes, D. (2003) Mutation rate and evo-

lution of fluoroquinolone resistance in Escherichia coli isolates from patients

with urinary tract infections. Antimicrob. Agents Chemother. 47: 3222–3232.

[51] Nazir, H., Cao, S., Hasan, F., and Hughes, D. (2011) Can phylogenetic type

predict resistance development? J. Antimicrob. Chemother. 66:778–787.

[52] Drlica, K. and Zhao, X. (2007) Mutant selection window hypothesis updated.

Clin. Infect. Dis. 44:681–688.

[53] Baquero, F. and Negri, M. C. (1997) Selective compartments for resistant

microorganisms in antibiotic gradients. BioEssays 19:731–736.

[54] Baquero, F., Negri, M. C., Morosini, M. I., and Blazquez, J. (1998) Antibiotic-

selective environments. Clin. Infect. Dis. 27(Suppl 1):S5–S11.

[55] Gullberg, E., Cao, S., Berg, O. G., Ilback, C., Sandegren, L., et al. (2011)

Selection of resistant bacteria at very low antibiotic concentrations. PLoS

Pathogens 7:e1002158.

[56] Liu, A., Fong, A., Becket, E., Yuan, J., Tamae, C., et al. (2011) Selective

advantage of resistant strains at trace levels of antibiotics: a simple and

ultrasensitive color test for detection of antibiotics and genotoxic agents.

Antimicrob. Agents Chemother. 55:1204–1210.

[57] Le-Minh, N., Khan, S. J., Drewes, J. E., and Stuetz, R. M. (2010) Fate of anti-

biotics during municipal water recycling treatment processes. Water Res.

44:4295–4323.

[58] Michael, I., Rizzo, L., McArdell, C. S., Manaia, C. M., Merlin, C., et al. (2013)

Urban wastewater treatment plants as hotspots for the release of antibiotics

in the environment: a review. Water Res. 47:957–995.

[59] Manzetti, S. and Ghisi, R. (2014) The environmental release and fate of anti-

biotics. Mar. Pollut. Bull. 79:7–15.

[60] Hughes, D. and Karlen, A. (2014) Discovery and preclinical development of

new antibiotics. Upsala J. Med. Sci. 119:162–169.

HUGHES ET AL. 529