Minireview
The role of antibiotics and antibiotic resistance
in natureemi_1972 2970..2988
Rustam I. Aminov*
University of Aberdeen, Rowett Institute of Nutrition and
Health, Greenburn Road, Aberdeen AB21 9SB, UK.
Summary
Investigations of antibiotic resistance from an environmental
prospective shed new light on a problem
that was traditionally confined to a subset of clinically
relevant antibiotic-resistant bacterial pathogens. It
is clear that the environmental microbiota, even in
apparently antibiotic-free environments, possess an
enormous number and diversity of antibiotic resistance
genes, some of which are very similar to the
genes circulating in pathogenic microbiota. It is difficult
to explain the role of antibiotics and antibiotic
resistance in natural environments from an anthropocentric
point of view, which is focused on clinical
aspects such as the efficiency of antibiotics in clearing
infections and pathogens that are resistant to
antibiotic treatment. A broader overview of the role of
antibiotics and antibiotic resistance in nature from
the evolutionary and ecological prospective suggests
that antibiotics have evolved as another way of intraand
inter-domain communication in various ecosystems.
This signalling by non-clinical concentrations
of antibiotics in the environment results in adaptive
phenotypic and genotypic responses of microbiota
and other members of the community. Understanding
the complex picture of evolution and ecology of antibiotics
and antibiotic resistance may help to understand
the processes leading to the emergence and
dissemination of antibiotic resistance and also help
to control it, at least in relation to the newer antibiotics
now entering clinical practice.
Introduction
Antibiotics are probably one of the most successful forms
of chemotherapy in the history of medicine. They have
saved many millions of lives and placed the majority of
infectious diseases that plagued human history for many
centuries under control. Initially, on their introduction into
clinical practice in the 1940s, antibiotics were extremely
efficient in clearing pathogenic bacteria leading many to
believe that infectious diseases would become a problem
of the past and would be wiped out from all human populations
eventually. However, the emergence and rapid
dissemination of antibiotic-resistant pathogens, especially
multi-drug-resistant bacteria, during recent decades,
exposed our lack of knowledge about the evolutionary
and ecological processes taking place in microbial ecosystems.
It is now evident that microbial populations
possess enormous metabolic diversity, from which they
may deploy protective mechanisms allowing them to withstand
the selective pressures imposed by their natural
environment as well as human interventions such as antibiotics.
Revealing the nature and functional role played by
antibiotics and antibiotic resistance in various natural ecosystems
may help to understand the processes leading to
the emergence of antibiotic-resistant pathogens. Finally,
armed with knowledge accumulated through many years
of genetic, genomic and metagenomic studies and with
new concepts about antibiotics and antibiotic resistance,
can we now predict the emergence and dissemination of
resistance to newly introduced antibiotics?
This review will focus mainly on areas that have contributed
to re-evaluation of our conceptual framework
about antibiotics and the problem of antibiotic resistance.
In particular, the contribution of evolutionary, ecological
and functional aspects of antibiotics and antibiotic resistance
will be reviewed. In the final section, the practical
implications of an attempt to apply these new concepts to
the prediction of resistance to a novel antibiotic will be
made.
Evolution of antibiotic resistance genes
On an evolutionary scale, the massive explosion of
antibiotic-resistant phenotypes in human and animal
pathogens is a very recent event that has followed the
large-scale production and use of antibiotics in clinical
and veterinary medicine, agriculture, aquaculture,
Received 14 March, 2009; accepted 21 May, 2009. *For correspondence.
E-mail r.aminov@abdn.ac.uk; Tel. (+44) 1224 716643;
Fax (+44) 1224 716687.
Environmental Microbiology (2009) 11(12), 2970–2988 doi:10.1111/j.1462-2920.2009.01972.x
© 2009 Society for Applied Microbiology and Blackwell Publishing Ltd
horticulture and other human activities. It was thought,
initially, that the genetic variability of material in bacterial
populations for selection by antibiotics to operate would
be through mutations and, as a such, antibiotic resistance
would be based largely on target modification and so
remain clonal. Indeed, this mechanism is still dominant in
the case of resistance to quinolones, rifampin and fosfomycin
and it drives the structural evolution of horizontally
transferred antibiotic resistance genes such as extendedspectrum
beta-lactamases (ESBLs). Mutation-driven antibiotic
resistance, however, happens mainly during in-host
evolution such as in chronic infections (Maciá et al., 2005)
while the purpose of this review is to discuss antibiotic
resistance from a broader environmental prospective. The
vast majority of antibiotic resistance mechanisms are
acquired through horizontal gene transfer from other,
often taxonomically very distant, bacteria. Phylogenetic
analysis of several groups of antibiotic resistance genes
has suggested that genetic material for present-day antibiotic
resistance has had a long history of selection and
diversification well before the current ‘antibiotic era’
(Aminov and Mackie, 2007).
Probably the best-documented case of the ancient evolution
of antibiotic resistance genes comes from the analysis
of b-lactamases. b-Lactams are the most widely used
antibiotics in clinical medicine and resistance to b-lactams
may become a severe threat because they have low
toxicity and are used to treat a broad range of infections
(Livermore, 1996). The primary resistance mechanism
is enzymatic inactivation through the cleavage of the
b-lactam ring by b-lactamases. These enzymes are represented
by two unrelated groups, one comprising of
three classes of serine b-lactamases, with an active-site
serine, and another – of two classes of metallo-blactamases,
which require a bivalent metal ion to catalyse
the hydrolysis (Bush, 1998). Both groups are very ancient
and the classes within the groups are diversified to the
extent that all traces of homology between the classes at
the sequence level are lost (Hall and Barlow, 2004; Garau
et al., 2005). Structure-based phylogeny was, however,
able to reconstruct the evolution of both b-lactamase
groups and establish that these ancient enzymes originated
more than two billion years ago, with some serine
b-lactamases being present on plasmids for millions of
years, well before the modern use of antibiotics (Hall and
Barlow, 2004; Garau et al., 2005). Recent work on the
evolutionary history of b-lactamase genes in Klebsiella
oxytoca has suggested that these genes have been
evolving for over 100 million years in this host, without
concomitant evolution of the antimicrobial resistance
phenotype and with the phylogenies of b-lactamase
and housekeeping genes being highly congruent in this
organism (Fevre et al., 2005). Molecular analysis of
b-lactamases in a metagenomic library from ‘cold-seep’
sediments also showed that most of the diversity of these
enzymes is not the result of recent evolution, but is that of
ancient evolution (Song et al., 2005). Our own, limited,
phylogenetic analysis of class A b-lactamases, with the
inclusion of sequences from antibiotic producers such as
Amycolatopsis lactamdurans and streptomycetes as well
as from the environmental bacteria, essentially confirmed
these findings (data not shown). Interestingly, the
unknown evolutionary forces in apparently antibiotic-free
environments may also contribute to the generation of
novel diversity in antibiotic resistance genes (Allen et al.,
2009). This metagenomic study of Alaskan soil not only
uncovered a diverse and ancient collection of b-lactamase
genes, but also revealed a novel gene encoding a bifunctional
b-lactamase that has never been encountered
before.
Recently, we subjected several groups of antibiotic
resistance genes conferring resistance to structurally
unrelated antibiotics, with different mechanisms of action,
to rigorous phylogenetic analyses (Aminov and Mackie,
2007). In general, the history of antibiotic resistance genes
can be divided into the macro- and microevolutionary
periods, which can also be defined as the
‘pre-antibiotic’ and ‘antibiotic’ periods. The former is
characterized by a long history of diversification in natural
ecosystems, mostly through duplications and mutations,
with a limited contribution of horizontal gene transfer to the
processes. What is not known is if these processes have
been involved in providing an antibiotic resistance function
per se or might have served some other metabolic function.
The antibiotic era, in fact, was (and still is) a fairly brief
evolutionary experimentation that was conducted during
the past 70 years with large-scale production of antibiotics
and exertion of a strong selective pressure towards bacteria
in various ecosystems. Relatively rare genes that
happened to confer antibiotic resistance were once
involved in other cellular functions but were selected for
the resistance phenotype and mobilized from the environmental
genomic reservoirs, with the rapid dissemination
into taxonomically divergent commensal and pathogenic
bacteria. The process was very rapid on an evolutionary
scale and horizontal gene transfer, mediated by mobile
genetic elements, played a prominent role in it.
Based on the historical evolutionary background, the
next question to ask is what possible functional role is
played by antibiotics and antibiotic resistance in natural
ecosystems?
Ecology of antibiotics and antibiotic resistance
The question of how antibiotic resistance genes are maintained
in the environment is contradictory. If the sole functional
role of these genes is to confer protection against
the lethal concentrations of antibiotics, then selection and
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dissemination of antibiotic resistance genes should be
linked to anthropogenic factors since environmental concentrations
of antibiotics in unaffected areas are normally
below detection limits and certainly not in the minimum
inhibitory concentration (MIC) range for the majority of
environmental bacteria. Indeed, this assumption may be
supported by cases of detectable antibiotic resistance
gene flow from facilities that use antibiotics into the environment
(Chee-Sanford et al., 2001; 2009; Koike et al.,
2007; Baquero et al., 2008). On the other hand, there are
many cases of persistence of antibiotic resistance genes
in apparently antibiotic-free environments. In the metagenomic
studies of ‘cold-seep’ sediments and remote
Alaskan soil, the presence of diverse b-lactamase genes
in both locations has been demonstrated (Song et al.,
2005; Allen et al., 2009). Judging by the total amount of
environmental DNA sampled and the number of b-lactamresistant
clone encountered, about 5% of average-sized
bacterial genomes in this type of undisturbed soil may
carry the b-lactamase genes that are readily expressed in
Escherichia coli. In another example of antibiotic resistance
in unaffected environments, the phenotype of more
than 60% of the Enterobacteriaceae isolates from the
pristine freshwater environment was found to be multidrug-resistant
(Lima-Bittencourt et al., 2007).
It is now generally recognized that the natural environment
harbours a vast diversity of antibiotic resistance
genes and some soil bacteria may even subsist on antibiotics
using them as their sole source of carbon
(D’Costa et al., 2006; 2007; Wright, 2007; Martínez,
2008; Dantas et al., 2008). What, then, is the functional
role played by these genes in the environment? The
term ‘antibiotics’ is commonly referred to their therapeutic
use and the ultimate goal of any antibiotic therapy
is clearing up an infection. Is the same role, in a
Darwinian natural selection sense, played by antibiotics
and antibiotic resistance in the environment? Indeed,
certain strains of fluorescent pseudomonads colonizing
euthrophic econiches such as the rhizosphere may suppress
soil-born pathogens through the production of
diffusible or volatile antibiotics such as phenazines, phloroglucinols,
pyoluteorin, pyrrolnitrin, cyclic lipopeptides
and hydrogen cyanide (Haas and Défago, 2005). At the
same time, several lines of evidence collected in recent
years indicate that antibiotic concentrations occurring in
natural oligothrophic environments may be too low to
exert any lethal effects and, instead, they may play signalling
and regulatory roles in microbial communities
(Davies et al., 2006; Linares et al., 2006; Yim et al.,
2006; Martínez, 2008). If antibiotics are indeed involved
in signalling, then what kind of signals they convey? If
the signals are related to the environmental conditions,
physiological state or other regulatory networks? The
most appropriate models to discuss these questions
would be the antibiotic producers and regulation of antibiotic
synthesis in these bacteria.
Antibiotics as yet another language of
communication
The vast majority of commercially available antibiotics are
produced by Streptomyces spp. (Weber et al., 2003) and
the pioneering studies of antibiotic synthesis regulation in
the representatives of this genus has resulted in identification
of a g-butyrolactone or A-factor that induces antibiotic
production and differentiation in Streptomyces griseus
(Khokhlov et al., 1967).Apathway forA-factor biosynthesis
has been recently proposed (Kato et al., 2007). This group
of molecules, represented by three major types, namely
6-keto (6R)-hydroxy and (6S)-hydroxy types (Nishida
et al., 2007), belongs to the quorum-sensing (QS) system,
the best-studied prototype of which is the Vibrio fischeri QS
network (Fuqua et al., 1996). The QS is widespread among
bacteria and serves as a language of communication, not
only between the bacteria but also in inter-kingdom signalling
(Shiner et al., 2005). Similarly to the LuxI/LuxR system
of Gram-negative bacteria, the g-butyrolactone signalling
system in Streptomyces consists of the g-butyrolactone
synthase, AfsA, and the receptor protein, ArpA (Nishida
et al., 2007). During growth, g-butyrolactones are gradually
accumulated in the media and, when they reach critical
concentrations, interact with the DNA-binding cytoplasmic
receptor proteins, ArpA and its homologues, releasing
them and allowing transcription from target genes. The
target genes are transcriptional factors that are involved in
the production of secondary metabolites such as antibiotics
and/or in morphological differentiation (Horinouchi,
2007).
The availability of many sequenced bacterial genomes
allowed to search for proteins with homology to
g-butyrolactone synthases and receptors. Interestingly,
only 10 or 11 probable g-butyrolactone synthases, all from
the representatives of the Streptomyces genus, were
found while 37–42 putative g-butyrolactone receptors
were found in genomes of bacteria not only from the
Streptomyces but also from Kitasatospora, Brevibacterium,
Saccharopolyspora, Mycobacterium, Rhodococcus,
Anabaena, Nocardia and Nostoc genera (Takano, 2006;
Nishida et al., 2007). Thus the behaviour of bacteria in a
community may be orchestrated through a small number
of g-butyrolactone producers, with a much larger and
diverse audience of signal receivers. Consistent with this,
the evolution of g-butyrolactone synthases and its receptors
was not congruent (Nishida et al., 2007). Besides, the
ancestral receptors, initially, functioned as regulatory
DNA-binding proteins and only later in evolution acquired
the g-butyrolactone-sensing capability (Nishida et al.,
2007). As this example demonstrates, the well-known QS
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signalling network initiates a set of metabolic changes in
the community leading to a number of events including
differentiation, synthesis of secondary metabolites such
as antibiotics and probably other cellular processes.
With few exceptions, such as simple microbiota that
occupy extreme ecological niches, functional redundancy
is built into many microbial ecosystems to ensure homeostasis
and continuous operation even in the case of an
acute external stress. The signalling systems in various
ecosystems also have a similar level of redundancy,
through multiple regulatory networks. The QS system represents
one such signalling network and its role in intraand
inter-species communication, as well as in regulation
of many aspects of metabolism, virulence, physiology,
competence, motility, symbiosis and other functions is
described in many excellent reviews. There are a number
of other regulatory networks such as two-component
systems and various sensors that convey the environmental
information to the cell. The languages used in this
type of communication, however, have many dialects and
are quite specific because they require specific receptors
for the signals to be correctly perceived, and only a limited
number of microbiota members (roughly fourfold bigger
than the original signal producers in the case of antibiotic
synthesis; see the ratio of g-butyrolactone synthases and
receptors above) may adequately respond to these
signals by reorganizing their cellular processes. Is it that
the synthesis of antibiotics is also a signalling mechanism?
Then what is the function of this mechanism? Is it in
amplification of the initial weak and rapidly decaying
signal in the environment to make it stronger and less
specific so it is perceived by other members of the community
that are not capable of sensing and deciphering
the environmental signals themselves? In support of this
notion, indeed, the acyl-homoserine lactone quorum
signal very rapidly decays in many soil types (Wang and
Leadbetter, 2005). In this scenario, the function of antibiotic
resistance may be in attenuating signal intensity
similar to quorum quenching in the QS communication
(Dong et al., 2001). Indeed, removal of the initial QS
signal renders bacteria more sensitive to antibiotics
(Ahmed et al., 2007). The negative feedback loop of the
secondary signalling system, antibiotics, may then suppress
the primary QS signalling network (Tateda et al.,
2004; Skindersoe et al., 2008) thus providing the finetuning
between the two signalling networks.
If antibiotics do indeed play a universal signalling role
in natural ecosystems then we would expect to see
examples of convergent evolution, for example, in production
of the same type of signalling molecules by taxonomically
different bacteria employing different biosynthetic
pathways. For historical reasons, the search for antibiotic
producers was largely confined to streptomycetes (from
which the first antibiotics were successfully developed)
and, probably because of this, the list of known antibiotic
producers is heavily biased towards this group of bacteria.
Antibiotic biosynthesis may be a much broader phenomenon
in nature and the inclusion of other groups of
bacteria and methods of testing in antibiotic screening
programmes may uncover the true extent of the environmental
antibiome. For instance, b-lactams are a ubiquitous
group of antibiotics and are produced by a wide
range of bacteria. For the sake of brevity, only the carbapenem
group of b-lactams, one of the most therapeutically
potent antibiotics currently available (Nicolau, 2008), will
be discussed in the context of convergent evolution and
signalling and regulation in microbial ecosystems.
The first carbapenem-producing bacterium identified
was Streptomyces cattleya (Kahan et al., 1972). Structurally
similar antibiotics were later described in other Streptomyces
species as well as in Gram-negative bacteria
belonging to the Serratia and Erwinia genera (Parker
et al., 1982). Carbapenem compounds are also produced
by a luminescent entomopathogenic bacterium Photorhabdus
luminescens (Derzelle et al., 2002). Carbapenems
are synthesized via a different metabolic pathway
from that employed in the classical b-lactam biosynthesis
route for penicillins, cephamycins and cephalosporins
(Williamson et al., 1985). The genes involved in the
synthesis of carbapenems are organized into clusters
(McGowan et al., 1997; Cox et al., 1998; Derzelle et al.,
2002; Núñez et al., 2003) and although the biosynthetic
pathways share some similar enzymes in Gram-positive
and Gram-negative producers, they are substantially different
(Coulthurst et al., 2005). These enzymes probably
evolved from primary metabolic enzymes in corresponding
producers and represent an example of convergent
evolution.
The regulation of carbapenem biosynthesis in Gramnegative
bacteria also represents an interesting example
of its dependence on environmental factors, in particular
of QS. Despite the structural similarity between the carbapenems
from streptomycetes and a range of Gramnegative
bacteria, its regulation is governed by QS signals
specific for a given group of bacteria. In Erwinia
carotovora (recently reclassified as Pectobacterium
carotovorum) its biosynthesis is regulated by a classical
autoinducer, N-(3-Oxohexanoyl)-L-homoserine lactone
(Bainton et al., 1992). Despite less dependence on antibiotic
production from the growth phase and cell density in
Serratia, antibiotic production is also under a QS control
in these bacteria (Thomson et al., 2000). However, a
number of other signals are also integrated into the regulatory
network in Serratia (Slater et al., 2003; Fineran
et al., 2005). The complexity of this regulation may reflect
the fine-tuning mechanisms regulating the level of antibiotic
production in response to the multiple signals
perceived by these bacteria from the environment.
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Interestingly, cryptic carbapenem antibiotic production
genes are widespread in E. carotovora and, in laboratory
conditions, this phenotype can be suppressed by multiple
copies of the apparently mutant transcriptional activator
(Holden et al., 1998). It is possible, however, that the
antibiotic is synthesized in natural ecosystems but the
environmental factors governing its expression are not
known. Another possibility might be that if an antibiotic
serves as a signalling molecule then the concentrations
produced in the environment may be too low to be
detected in the MIC and instrumental assays. Much less
information is available regarding the regulation of
carbapenem biosynthesis in S. cattleya but a recent publication
suggests that there is an additional, low-level,
cross-talk between the thienamycin and cephamycin C
pathways in this bacterium (Rodríguez et al., 2008). In
another cephamycin C-producing bacterium, Streptomyces
clavuligerus, antibiotic synthesis is regulated at the
primary regulatory level by g-butyrolactone (Liras et al.,
2008). Therefore, the case with carbapenems also
supports the hypothesis that cells respond to the initial
QS signals and other environmental clues such as
N-acetylglucosamine (Rigali et al., 2008) and nutrient
depletion (Hesketh et al., 2007; Lian et al., 2008), possibly
integrating them, by the second level of signalling,
through antibiotics. Continuing with the carbapenems as
an example, the second-level signalling by the representative
of this class of antibiotics, imipenem, at subinhibitory
concentrations, involves changes in global gene
expression, including b-lactamase and alginate production,
in Pseudomonas aeruginosa biofilms (Bagge et al.,
2004). In Gram-positive bacteria, low-concentration carbapenems
are potent inhibitors of L,D-transpeptidases
that catalyse the formation of 3→3 peptidoglycan crosslinks
and bypass the 4→3 cross-links formed by the
D,D-transpeptidase activity of penicillin-binding proteins
(PBPs) (Mainardi et al., 2007; Lavollay et al., 2008). In
E. coli, the L,D-transpeptidase homologue is involved in
attachment of the Braun lipoprotein to peptidoglycan
(Magnet et al., 2007). The lack of the lipoprotein in E. coli
leads to sensitivity to EDTA, cationic dyes and detergents
but no vital cellular functions are affected (Hirota et al.,
1977). The question is, how other antibiotic signals are
perceived and what kind of phenotypic and genotypic
responses they may evoke in other systems?
Phenotypic responses to antibiotic signalling
The question about what range of antibiotic concentrations
is effective for cross-talk to occur in natural ecosystems
remains open. The concentrations of antibiotics that
occur in natural, unaffected, environments are unknown
and, in a few cases, these environments have actually
served as control/zero points for measuring the impact of
human activity on natural ecosystems, with no detectable
antibiotics present (Yang and Carlson, 2003; Kim and
Carlson, 2006; Pei et al., 2006). The natural ecosystems
sampled were, however, river and sediment environments,
which are probably not the most appropriate
ecosystems to investigate antibiotic communication.
There is a substantial literature, however, describing
concentration-dependent bacterial responses to antibiotics
in laboratory conditions, which was recently reviewed
within the frames of hormesis concept (Davies et al.,
2006; Fajardo and Martínez, 2008). In this concept, low
antibiotic concentration regulates a specific set of genes
in target bacteria, while increasingly higher concentrations
elicit a stress response and even higher concentrations
are lethal. It has been suggested that antibiotics play
a role in the environment at low concentrations unlike the
lethal concentrations used in clinical therapy.
The subinhibitory antibiotic effects have been studied in
a number of bacteria, mostly pathogens and in relation to
virulence and pathogenic properties. The best-studied
model among them is the opportunistic pathogen
P. aeruginosa, infection with which is often fatal for cystic
fibrosis patients. The central role in regulation of pathogenic
properties of P. aeruginosa belongs to the QS
system and infection with QS-deficient mutants results in
less severe outcome in animal models (Girard and Bloemberg,
2008). It has been demonstrated in vitro that the
subinhibitory levels of a macrolide antibiotic azithromycin
suppress one of the pathogenic properties of P. aeruginosa
as alginate overproduction and biofilm formation
(Ichimiya et al., 1996). In addition to macrolide antibiotic
azithromycin, the subinhibitory concentrations of other
antibiotics such as ceftazidime (b-lactam) and ciprofloxacin
(fluoroquinolone) also appeared to be effective in
decreasing the expression of a range of QS-regulated
virulence factors (Skindersoe et al., 2008). The authors
hypothesized that the effect of antibiotics is due to
changes in membrane permeability affecting the flux of
N-3-oxo-dodecanoyl-L-homoserine lactone. On the other
hand, exposure of P. aeruginosa to subinhibitory concentrations
of another b-lactam, imipenem, results in the
increase of alginate production and biofilm volume
(Bagge et al., 2004). Another fluoroquinolone, norfloxacin,
also induces biofilm formation at subinhibitory concentrations
(Linares et al., 2006). These contradictory results
suggest that antibiotics of the same class, which share the
same molecular targets to execute their lethal activity,
may have different targets in the cell when functioning as
signal molecules. Indeed, subinhibitory concentrations of
the macrolide-lincosamide-streptogramin antibiotics demonstrate
the dual effects, interacting with the ribosomes
and modulating transcription (Tsui et al., 2004). At the
same time, blocking the known target of lethal activity of
azithromycin may abolish its QS modulatory properties
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(Köhler et al., 2007). Since the ribosome is a target for
many different antibiotics, then can it serve as a multiligand
sensor? Protein synthesis is the most expensive
biosynthetic activity in the cell; is it because of this the
antibiotic signals are aimed at this regulatory target when
the resources become scarce? The notion that cellular
targets for the lethal and subinhibitory actions of antibiotics
may differ is further supported by the effect of subinhibitory
concentrations of an aminoglycoside antibiotic
tobramycin, which induces biofilm formation in P. aeruginosa
and E. coli (Hoffman et al., 2005). In P. aeruginosa,
molecular target for subinhibitory tobramycin is not the
ribosome but aminoglycoside response regulator, an
inner-membrane phosphodiesterase whose substrate,
cyclic di-guanosine monophosphate, is a bacterial second
messenger that regulates cell surface adhesiveness.
Identification of targets for other subinhibitory antibiotics
therefore remains a priority.
In Staphylococcus aureus, virulence is largely regulated
by two-component regulatory systems, such as the
agr, saeRS, srrAB, arlSR and lytRS systems (Bronner
et al., 2004) and regulatory RNA such as RNAIII (Boisset
et al., 2007). For the sake of brevity, only one of these
system, SaeRS, will be discussed in the context of subinhibitory
antibiotics. This system is strongly involved in
the tight temporal control of virulence factor expression
(Rogasch et al., 2006) and its inactivation eliminates
adherence and attenuates virulence of S. aureus in a
murine infection model (Liang et al., 2006). The sensor
molecule of this system, SaeS, is activated by alteration
within the membrane allowing the pathogen to react to
phagocytosis-related effectors (Geiger et al., 2008). Subinhibitory
b-lactam concentrations are able to induce the
SaeRS system, thus enhancing the virulence of S. aureus
(Kuroda et al. 2007). At 0.5¥ MIC, florfenicol as well,
increases the expression of saeRS up to fivefold, with the
concomitant increase in the expression of genes coding
for adhesins (Blickwede et al., 2005a). Interestingly, this
ribosome-targeting antibiotic contributes to the stabilization
of the respective mRNAs thus suggesting a mechanism
for the SaeRS system activation by subinhibitory
florfenicol. The mRNA stabilization effect of subinhibitory
concentrations is also documented for another ribosometargeting
antibiotic, tetracycline (Wei and Bachhofer,
2002). Although a subinhibitory concentration of clindamycin
likewise leads to the stabilization of mRNA of
S. aureus adhesins this is not reflected in the phenotype
(Blickwede et al., 2005b).
In general, bacterial transcriptional responses to subinhibitory
antibiotics, assessed with microarrays, are not
consistent and seem to depend on a variety of factors
such as experimental conditions, the nature and concentration
of antibiotic used, taxonomy and genotype
of bacteria, and others (Davies et al., 2006). Also, the
extent of transcriptional response does not necessarily
mean that it is automatically converted into the corresponding
phenotype. Given the complexity of regulatory
networks and circuits, with which subinhibitory antibiotics
may interact, and the dynamic nature of responses, the
number of variables in this type of experiments must be
minimized and standardized in order for the results to be
comparable.
The details of subinhibitory antibiotics signalling in
eukaryotes were mainly uncovered through the observation
of antibiotic effects in animal models, tissue cultures,
and in clinical trials. Tetracyclines, macrolides and
ketolides display potent anti-inflammatory activities
(Tamaoki et al., 2004; Weinberg, 2005; Del Rosso, 2007;
Webster and Del Rosso, 2007; Leiva et al., 2008a,b) while
rifampin exerts the opposite effect (Yuhas et al., 2008).
The macrolide antibiotic-binding human p8 protein was
recently cloned and identified using the phage display
library approach (Morimura et al., 2008). This is a nuclear
DNA-binding protein, which is strongly activated in
response to several stresses, and, on the basis of functional
similarity to HMG-I/Y-like proteins, it was suggested
that p8 may be involved in transcription regulation
(Encinar et al., 2001; Hoffmeister et al., 2002). Since
clarithromycin, erythromycin and azithromycin inhibit the
binding of recombinant p8 protein to double-stranded
DNA (Morimura et al., 2008), the anti-inflammatory effect
of macrolides may be explained by the downregulation of
transcription of genes involved in the pro-inflammatory
network. Interestingly, the same inhibitory effect was
observed with a structurally unrelated antifungal antibiotic
dechlorogriseofulvin (Morimura et al., 2008) suggesting a
potential overlap in recognition of structurally different
antibiotic ligands by a single human molecular sensor.
These antibiotic activities that are beyond their intended
antibacterial use lead to several implications. First, the
choice of antibiotics for treatment of infections in patients
with chronic inflammatory diseases should take into
account potential side-effects such as upregulation of
the inflammatory network as in the case with rifampin.
Second, antibiotics that have been approved for human
and animal use can be screened for clinical activities
other than antibacterial, such as functioning as ligands for
targets and receptors involved in human and animal
disease and pathology. Third, could the immunomodulatory
effects of antibiotics be explained by long-term
co-evolution of host–microbe cross-talk mechanisms?
One of the attempts to explain a dramatic increase in the
number of allergies and asthma in more developed countries
suggests that these diseases are the result of the
limited exposure to the environmental antigens in the
modern world (Strachan, 1989). Continuous exposure of
humans to environmental bacteria synthesizing a plethora
of metabolites including QS molecules and antibiotics
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may have evolved as a crucial factor for proper development
of immune system. Finally, the beneficial effects of
subinhibitory antibiotics such as reduced mortality and
morbidity, reduced subclinical disease, improved health
and better efficiency of feed conversion in animals may be
also viewed from the antibiotic signalling point of view.
One of the possible explanations that has been proposed
is supression of subclinical infections. The concentrations
of antibiotics used, however, are not in the lethal range for
bacteria and it is unlikely that pathogens, if any, are killed
by low concentrations of antibiotics. It is likely that the
effect of subinhibitory growth-promoting antibiotics is
complex and involves pleiotropic regulation of the physiology
and metabolic state of an entire microbiota as well
as of the regulatory mechanisms operating in the host
animal. The mechanisms of subinhibitory antibiotics may
be through the modulation of the QS networks operating
within the gut bacterial community resulting in suppression
of virulence factors, redistribution of metabolic fluxes
for better feed conversion and other regulatory effects.
In the host, subinhibitory antibiotics may modulate the
immunity and, through the anti-inflammatory activities,
suppress subclinical chronic inflammation draining the
host resources. Since this effect is pleotropic, it is probably
difficult to reproduce it through the use of pre and/or
probiotics. Other multifunctional ligands mimicking these
properties of antibiotics may be tried as the alternatives
for subinhibitory antibiotics.
A huge number of signalling and regulatory networks
operate at every level of organization of living matter, from
the cell to ecosystems. We are only beginning to reveal
the role played by antibiotics in these processes. Another
aspect of antibiotic role in natural ecosystems is the
involvement in processes happening at the genetic level.
While phenotypic responses are essentially reversible,
changes at the genotype level, once they successfully
passed through the sieve of natural selection, may
become fixed in populations and may even rapidly
increase in frequencies if they confer a sufficient selective
advantage. In this regard, the effect of antibiotics on
genetic processes may have a long-term impact, which is
difficult, if not possible, to reverse.
Genotypic responses to antibiotic signalling
Unlike the situation with physiological responses, the
effect of low-dose antibiotics, if any, is almost uniform and
results in enhanced antibiotic resistance gene transfer,
often conferring resistance to structurally unrelated antibiotics.
It was found, for example, that subinhibitory concentrations
of b-lactam antibiotics increase the transfer of
tetracycline resistance plasmids in S. aureus by up to
1000-fold (Barr et al., 1986). Pre-growth of a donor
Bacteroides strain on a low concentration of tetracycline
also appears to accelerate the mobilization of a resident
non-conjugative plasmid by chromosomally encoded tetracycline
conjugal elements (Valentine et al., 1988). The
exposure of donor Bacteroides cells to low concentration
of tetracycline appears to be a prerequisite for the excision
of the CTnDOT family of conjugative transposons
from the chromosome and conjugal transfer of the
excised elements; virtually no gene transfer occurs
without tetracycline induction of donor cells (Stevens
et al., 1993; Whittle et al., 2002). Incorporation of tetracycline
at subinhibitory concentrations in the mating medium
also substantially enhances Tn916-mediated conjugal
transfer (Showsh and Andrews, 1992). The similar stimulatory
effect of tetracycline on conjugation transfer was
also demonstrated for the conjugative transposon Tn925
(Torres et al., 1991). These in vitro results have also been
reproduced using in vivo models. In gnotobiotic mice, for
example, the presence of a low concentration of tetracycline
in drinking water increased the frequency of transfer
of conjugative transposon Tn1545 from Enterococcus
faecalis to Listeria monocytogenes in the digestive tracts
by about 10-fold (Doucet-Populaire et al., 1991). In gnotobiotic
rats, selection for the resistant phenotype was the
major factor causing higher numbers of Tn916 transconjugants
in the presence of tetracycline (Bahl et al., 2004).
Therefore, the enhancement of conjugal transfer of antibiotic
resistance-carrying transposons in the presence of
subinhibitory concentration of antibiotics is not only an in
vitro laboratory phenomenon but also takes place in gut
ecosystems of animal models. In the environment as well,
exposure to a low-dose antibiotic may lead to the mobile
element-mediated dissemination of antibiotic resistance
genes (Knapp et al., 2008).
Among the best-studied mechanisms involved in the
enhancement of gene transfer are those mediated
through the translational attenuation by tetracycline
(Moon et al., 2005). According to this model, this attenuation
results in increased production of RteA and RteB,
leading to activation of rteC transcription. In turn, RteC
activates transcription of excision genes of CTnDOT and
other mobile elements (Moon et al., 2005). At subinhibitory
tetracycline concentration, the excision is not associated
with growth phase (Song et al., 2009). Another, less
specific mechanism of gene transfer enhancement
operates through the structurally unrelated but the
SOS response-inducing antibiotics. In particular, DNAdamaging
agents such as mitomycin C and antibiotics
such as fluoroquinolones and dihydrofolate reductase
inhibitors may increase the rate of horizontal gene transfer
more than 300-fold (Beaber et al., 2004). More importantly,
the use of the SOS response-inducing antibiotics
may co-select other antibiotic resistance genes that are
physically linked in a mobile genetic element (Hastings
et al., 2004). Although it was initially assumed that the
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SOS response is triggered exclusively by DNA-damaging
agents, other classes of antibiotics, not interfering with
DNA metabolism, may also induce the genuine SOS
response. This was demonstrated for the action of
b-lactam antibiotics on S. aureus (Miller et al., 2004). The
consequences of this response were elevated rates of
horizontal transfer of the staphylococcal virulence genes
(Ubeda et al., 2005; Maiques et al., 2006). In broader
terms, control of horizontal transfer of integrative and
conjugative elements, which are found in many bacterial
genomes and which encode a variety of properties
besides the antibiotic resistance and virulence, may also
be regulated through the SOS response and environmental
signals (Auchtung et al., 2005; Bose et al., 2008).
The general conclusion from the publications discussed
above is that antibiotics may have a signalling function
stimulating horizontal gene exchange in microbial ecosystems.
This signalling function is unlikely to be limited
exclusively to the enhancement of gene transfer processes
but may also have a wider implication affecting the
genetic variability of microbiota in general. For instance,
exposure of Mycobacterium fortuitum to subinhibitory
concentrations of fluoroquinolone significantly increases
mutation rates (Gillespie et al., 2005). The components of
the SOS response, UmuD(2) and RecA, may regulate the
mutagenic activity of the error-prone DNA polymerase
DinB (Godoy et al., 2007). It is not clear, however,
whether the exposure to subinhibitory antibiotic concentrations
does indeed introduce DNA damage to elicit the
complete SOS response, or it results in ovexpression of
DinB, which contributes to the enhanced mutagenesis in
the absence of DNA damage (Kim et al., 1997). In addition
to the SOS response, there are probably a number of
other mechanisms by which the subinhibitory antibiotics
may increase mutation rates. In pneumococci, exposure
to quinolones, aminoglycosides and penicillin at subinhibitory
concentrations may result in increased mutability,
without the apparent involvement of SOS-response
components (Henderson-Begg et al., 2006; Cortes et al.,
2008).
It is not entirely clear why this mechanism of accelerated
genetic variability and gene exchange by low-dose
antibiotics has been selected in the course of evolution.
One of the explanations may be that this is a mechanism
for exploring new niches in an existing ecosystem or
expanding into an entirely new ecosystem when an
ecosystem operates close to the limits of the carrying
capacity. Probably this mutation-and-gene exchange
acceleration mechanism has been one of the major
driving forces shaping very complex microbial ecosystems,
with almost every possible niche employed, as we
know them today. This mechanism probably also contributes
to the ability of microbiota to probe the environment
in the search for new opportunities to expand. One of
such examples is P. aeruginosa, which may be encountered
in many natural ecosystems as well as in clinical
settings (Khan et al., 2007). Genetic adaptation of
P. aeruginosa to the niche in the airways of cystic fibrosis
patients includes numerous genome-wide mutations thus
making it systematically different from the wild-type bacterium
(Smith et al., 2006; Mena et al., 2008) and resulting
in specific changes of metabolism (D’Argenio et al.,
2007). Since the chronic infection is very difficult, if not
possible, to eradicate, maintenance antibiotic therapy is
required to slow the decline in pulmonary function, which
may be one of the factors contributing to the appearance
of the genome-wide adaptive mutations in P. aeruginosa.
The extent and consequences of human intervention
with the large-scale production and release of antibiotic
substances that normally operate at low concentrations in
natural ecosystems are largely unknown. The only consequence
we know definitely is the dramatic increase in
frequencies of antibiotic resistance gene carriage by
pathogenic and commensal microbiota. Can this trend be
reversed? Although it is generally thought that due to the
fitness cost of antibiotic resistance will be subjected to
negative selection once the antibiotic selective pressure
is removed, there are many examples demonstrating
how the remarkable plasticity of bacteria allows them to
ameliorate this cost (Lenski, 1997; Enne et al., 2005;
Ramadhan and Hegedus, 2005; Andersson, 2006;
Nilsson et al., 2006). Moreover, the acquisition of the antibiotic
resistance genotype may actually increase the
fitness of certain bacteria in the absence of antibiotic
selective pressure thus allowing the rapid emergence and
dissemination on a worldwide scale (Enne et al., 2004;
Luo et al., 2005). It is not known to what extent the level of
antibiotic resistance in natural ecosystems has been
affected by the human use of antibiotics. If to the same
level as it is seen in pathogens and commensals, then the
antibiotic-mediated cross-talk in natural ecosystems may
be seriously compromised, especially if the mechanisms
of resistance include modification or degradation of antibiotic
ligands.
Antibiotics and resistance to them: selection of
combinations
In this review, resistance to antibiotics has been discussed
mainly from an ecological point of view as ‘natural’
mechanisms of regulating antibiotic cross-talk. In some
groups of enzymes conferring antibiotic resistance, it is
still possible to track structure-and-function relationships
that eventually lead to the development of antibiotic resistance
properties. For instance, the therapeutic action of
b-lactams is achieved through the binding to PBPs thus
disrupting the growth and structural integrity of bacterial
cell walls. Structurally, b-lactamases are similar to PBPs
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that play an important role in bacterial cell cycle
(Macheboeuf et al., 2006). The transpeptidation reaction
performed by PBPs serves to stabilize the cell wall by
cross-linking the glycan strands during peptidoglycan synthesis.
The structure modifications during the evolution of
the intermediate antibiotic resistance enzyme were apparently
through the loss of interaction with the peptidoglycan
moieties (Meroueh et al., 2003). Given the extended evolutionary
history and diversity, wide distribution in the environment
and efficient catalytic properties of b-lactamases,
they have probably served as ‘moderators’ in b-lactam
cross-talk for a long time. It is not surprising therefore that
these genes were rapidly picked up from the environmental
genetic reservoirs and disseminated into commensal
and pathogenic microbiota following the introduction
of b-lactam antibiotics into clinical, veterinary and other
practices.
It is unlikely that antibiotic resistance genes and
enzymes, as we know them today, all have evolved from
the antibiotic cross-talk mechanism. This, apparently,
cannot be the case with synthetic antibiotics that have no
natural analogues such as quinolones. The bactericidal
activity of quinolones is mediated through the formation of
DNA gyrase–quinolone–DNA ternary complex thus arresting
replication fork progression and leading to the cell
death (Hiasa and Shea, 2000). The acquired resistance to
quinolones is due to the qnr gene, which encodes a
218 aa protein belonging to the pentapeptide repeat
family, with sequence homology with the immunity protein
McbG (Tran and Jacoby, 2002). The protection mechanism
operates through the binding of Qnr to DNA gyrase
in the early stages of gyrase–DNA complex formation
and, by lowering gyrase binding to DNA, Qnr may reduce
the amount of holoenzyme-DNA targets for quinolone
inhibition (Tran et al., 2005). The genes encoding the
pentapeptide repeat family proteins are widespread in
nature and cloning and phylogenetic reconstruction suggested
that the qnr genes have been acquired from the
environmental bacteria (Poirel et al., 2005; Sánchez
et al., 2008). The three-dimensional structure of the MfpA
protein from Mycobacterium tuberculosis is remarkably
similar to DNA in terms of size, shape and electrostatic
properties and these properties may explain its inhibitory
effect on DNA gyrase and quinolone resistance (Hegde
et al., 2005). It was suggested that the original function of
MfpA is in providing DNA topological assistance when
needed, but maintaining a condensed chromosome and
preventing undesired topological changes during periods
of replicative senescence (Hegde et al., 2005). Thus the
enzyme possibly involved in DNA metabolism in environmental
bacteria appeared to be also protective against a
synthetic antibiotic and, once a strong selective pressure
has been applied, the corresponding gene was picked up
from the environmental pool and rapidly penetrated into
pathogenic microbiota (Aminov and Mackie, 2007). It still
can be argued that due to the enormous metabolic diversity
of environmental microbiota, the structurally similar
compounds can be found in nature. Pseudomonads and
other bacteria produce a quorum-signalling molecule,
2-heptyl-3-hydroxy-4-quinolone, which belongs to the
family of 2-alkyl-4-quinolones (Dubern and Diggle, 2008).
These molecules have been initially described for their
antibiotic activities (Hays et al., 1945). Another P. aeruginosa
QS molecule, N-(3-oxododecanoyl) homoserine
lactone, and its non-enzymatically formed product,
3-(1-hydroxydecylidene)-5-(2-hydroxyethyl)pyrrolidine-2,
4-dione, both display potent antibacterial activities (Kaufmann
et al., 2005). These observations suggest that the
functions of the known QS molecules and antibiotics
overlap thus further supporting the hypothesis about the
concentration-dependent effects of small molecules and
the possible function of antibiotics as signal mediators.
The acquisition of metabolic genes by bacteria from
their environment to provide an unrelated function, such
as antibiotic resistance, is not limited to protection against
synthetic antibiotics. Even in the case of natural antibiotics
in the tetracycine family, the mechanisms of resistance
may include ion pumps that are involved in a number of
other cellular functions such as Na+ and K+ exchange for
protons (Krulwich et al., 2001) or the expression of genes
involved in biosynthesis of extracellular lipopolysaccharides
and capsular polysaccharides (Kazimierczak et al.,
2009). The horizontal gene transfer step may be not necessary
if the cellular metabolic mechanisms affected have
a sufficiently broad specificity to cope with novel substrates
such as antibiotics. For example, the natural functions
of bacterial multi-drug efflux pumps, which are
usually chromosomally encoded and are implicated in
antibiotic resistance, may include detoxification, virulence,
cell homeostasis and intercellular signal trafficking
(Piddock, 2006; Martínez et al., 2009). These observations
can be integrated within the concept of co-optation in
which the enormous metabolic diversity of microbiota may
provide the concomitant functions such as resistance to
antibiotics.
Practical implications: prediction of antibiotic
resistance
Initially, experimental approaches to predict the evolution
of antibiotic resistance genes have included in vitro
evolution modelling and screening for cryptic antibiotic
resistance genes (Hall, 2004). A broader conceptual
framework to predict antibiotic resistance was proposed
that included many variables such as the estimates of
potentiality and probability affecting the actuality, e.g. the
actual antibiotic resistance in bacterial populations
(Martínez et al., 2007). Genetic mechanisms that may
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contribute to evolution of antibiotic resistance were also
discussed (Courvalin, 2008). No formalized theorethical
framework for prediction of antibiotic resistance, however,
presently exists due to the lack of knowledge in several
key areas such as the true extent of microbial metabolic
diversity that may contribute to novel antibiotic resistance,
the rates of mutation and horizontal gene transfer (HGT)
in natural ecosystems, and the extent of genetic interaction
between different ecosystems. In the face of the growing
antibiotic resistance problem, however, even the scenarios
of antibiotic resistance development that are based on
incomplete knowledge can be of value in an attempt to
preserve the efficacy of novel antibiotics. Potentiality, probability
and actuality (Martínez et al., 2007) for tigecycline
resistance will be discussed in this section.
The first- and second-generation tetracylines have
gradually lost their efficiency due to the widespread resistance
conferred mainly by the ribosomal protection and
efflux mechanisms (Chopra and Roberts, 2001; Roberts,
2005). The first representative of the third generation of
tetracyclines (collectively called glycylcyclines), tigecycline
(the minocycline derivative 9-tert-butyl-glycylamidominocycline,
GAR-936), was approved by the US Food
and Drug Administration (FDA) in 2005 and in 2006 in the
European Union. This antibiotic was shown to be effective
against bacterial isolates containing the two major
determinants responsible for tetracycline resistance
(Petersen et al., 1999), clinical isolates of Acinetobacter
(Henwood et al., 2002), non-tuberculous mycobacteria
(Wallace et al., 2002), enterococci (Mercier et al., 2002;
Lefort et al., 2003; Nannini et al., 2003), S. aureus (Mercier
et al., 2002; Petersen et al., 2002), Legionella pneumophila
(Edelstein et al., 2003), Stenotrophomonas maltophilia
(Betriu et al., 2002), and other clinical isolates (Betriu
et al., 2002; Abbanat et al., 2003; Milatovic et al., 2003).
Thus it is a valuable therapeutic option when dealing
with hard-to-treat multi-drug-resistant infections such
as methicillin-resistant Staphylococcus aureus (MRSA),
vancomycin-resistant enterococci (VRE), penicillinresistant
Streptococcus pneumoniae and the b-lactamaseproducing
Enterobacteriaceae. It can be concluded that
the penetration of tigecycline resistance into pathogenic
microbiota is very low at this time.
Still, there are examples of resistance to tigecycline that
is conferred by two mechanisms, efflux from the cell
and drug modification. In P. aeruginosa, the mechanism
of decreased susceptibility to tigecycline is through the
resistance nodulation division (RND) family of efflux
pumps, in particular, the MexXY–OprM complex (Dean
et al., 2003). However, the compensatory mechanisms of
P. aeruginosa against tigecycline in the absence of
MexXY–OprM included two other efflux pumps, MexAB–
OprM and MexCD–OprJ, which, in norm, are ‘specialized’
in the efflux of second-generation semisynthetic tetracyclines,
doxycycline and minocycline. In Proteus mirabilis,
reduced susceptibility to tigecycline is also mediated by
another representative of the RND family of efflux pumps,
encoded by the acrAB homologue of E. coli, the AcrAB–
TolC system (Visalli et al., 2003; Ruzin et al., 2005). In
clinical isolates of Acinetobacter baumannii the reduced
susceptibility to tigecycline was also attributed to an
elevated expression of the RND family of efflux pumps,
namely the AdeABC and AdeIJK systems (Peleg et al.,
2007; Damier-Piolle et al., 2008). Elevated expression of
another efflux pump in the RND family, AcrAB, was implicated
in reduced tigecycline susceptibility in Enterobacter
cloacae and E. coli (Keeney et al., 2007; 2008). Thus, this
post factum determined potentiality involves non-specific
efflux mechanisms, which are overexpressed most probably
due to mutations in the regulatory system (Peleg et al.,
2007). Because of the chromosomal localization and the
involvement of several genes, the probability of immediate
dissemination of this mechanism of resistance is low.
Another mechanism of glycylcycline resistance,
through chemical transformation, is encoded by tet(X).
The gene was detected in anaerobic Bacteroides species
more than two decades ago (Guiney et al., 1984). Paradoxically,
in the original host it is cryptic and does not
confer resistance to tetracyclines because the encoded
enzyme is a flavin-dependent monooxygenase that
requires molecular oxygen in order to transform the tetracycline
substrates (Yang et al., 2004). It appears that
under aerobic condition and aerobic host this enzyme has
a broad specificity and can degrade virtually all tetracyclines
including tigecycline (Yang et al., 2004; Moore
et al., 2005).
To access the evolutionary origin of tet(X), the similarity
search was performed against databases, which produced
the highest scoring matches with the TetX proteins
as well as with the flavoprotein monooxygenases (data
now shown), a diverse group of enzymes that catalyse
region-selective hydroxylation of organic substrates and
which are found in many metabolic pathways in all three
domains of life (Harayama et al., 1992). These enzymes
are divided into six classes, from A to F, based on
sequence and three-dimensional structural data (van
Berkel et al., 2006). The class A monooxygenases, to
which TetX belongs, are usually involved in the microbial
degradation of aromatic compounds by ortho- or parahydroxylation
of the aromatic ring (Moonen et al., 2002).
Phylogenetic analyses demonstrated that these enzymes
display quite extraordinary diversity and are highly incongruent
with the 16S rRNA gene-based trees suggesting
extensive horizontal gene transfer events in the evolution
of this class of flavoprotein monooxygenases (data not
shown). Another prominent feature of these genes is that
duplication played a substantial role in their evolution. The
ecology of bacteria that harbour these genes encomRole
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passes various environmental niches, including soil,
water and intestinal ecosystems, while some of them are
known to be opportunistic pathogens. The range of biochemical
reactions performed by this class of enzymes is
quite broad and, interestingly, includes modification of
other than tetracycline aromatic polyketides such as
rifampin (Andersen et al., 1997), mithramycin (Prado
et al., 1999), griseorhodin (Li and Piel, 2002), chromomycin
(Menendez et al., 2004) and auricin (Novakova et al.,
2005).
For more accurate and sensitive analysis of the evolutionary
branch that has led to the appearance of tet(X),
sequence databases were searched with the protein
translation of the original tet(X) gene query (GenBank
Accession No. M37699 against translated nucleotide
databases including environmental DNA and the highscoring
(E-values < 5e-53
) hits were used in phylogenetic
reconstruction using the corresponding nucleotide
sequences (Fig. 1). The sequences with the highest
similarity to tet(X) were found predominantly in bacteria
belonging to the Bacteroidetes phylum (Fig. 1). This
analysis confirmed the gene duplication events in some
bacterial genomes (e.g. Flavobacterium johnsoniae
UW101 or Pedobacter sp. BAL39). The ancestor clade
leading to the emergence of tet(X) was localized in the
genome sequence of the fish pathogen Flavobacterium
psychrophilum (Duchaud et al., 2007; Fig. 1). The highly
similar (Ն 99%) tet(X) nucleotide sequences form a tight
cluster including the sequences from intestinal Bacteroides
species (Speer et al., 1991; Whittle et al., 2001), environmental
Sphingobacterium sp. (Ghosh et al., 2009),
human gut metagenome (Kurokawa et al., 2007), and the
metagenome of biological phosphorus removal sludge
community (García Martín et al., 2006) (Fig. 1). The functional
tigecycline resistance is experimentally confirmed
only for tet(X) from Tn4351 (Moore et al., 2005) but,
because of the virtual identity of sequences in the cluster,
all of them must confer resistance to tigecycline. More
distant sequences are from an opportunistic pathogen
P. aeruginosa (AB097942), which is resistant to minocycline,
and from an environmental plasmid (FJ012881),
which expresses tetracycline resistance in E. coli. Thus,
tet(X) can be encountered in several ecosystems including
the human gut, clinical settings, soil and a sludge
bioreactor. We have also detected its presence in the pig
intestinal microbiota using tet(X)-specific primers (data
not shown). It is not clear what kind of selection has
contributed to the widespread dissemination of tet(X). In
anaerobic Bacteroides, where the gene is cryptic, this was
probably a result of co-selection by aminoglycosides and
macrolides due to the genetic linkage with addS and ermF
in a mobile element (Whittle et al., 2001), while in aerobic
bacteria the additional selective forces involved could
include direct selection by older-generation tetracyclines.
The genetic context of the tet(X) orthologue in the
genome of F. psychrophilum JIP02/86 is associated with a
Fig. 1. A neighbour-joining tree of tet(X) and flavoprotein monooxygenase-encoding genes. Numbers above each node show the percentage
of tree configurations that occurred during 1000 bootstrap trials. The scale bar is in fixed nucleotide substitutions per sequence position.
GenBank accession numbers of nucleotide sequences used in this analysis are given in parenthesis. The cases of confirmed functionality of
tet(X) in E. coli or in original hosts (resistance to the first- and second-generation tetracyclines) are shown in bold and the case of
heterologous tigecycline resistance expression in E. coli is underlined.
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putative 28.5 kb mobile element (AM398681, analysis not
shown). Of particular interest is the linkage of the TetX and
XerD ORFs with the homologue of the regulatory protein
RteC, which is essential for self-transfer of conjugative
transposons and mobilization of co-resident plasmids in
Bacteroides species and which is regulated by tetracycline
(Stevens et al., 1993). In the genome of F. johnsoniae
UW101, RteC is located within a putative
transposon, whose ORFs share homology with Bacteroides
conjugative transposons (CP000685). The first heterologously
functional but cryptic in the original host tet(X)
genes were found to be located on large Bacteroides
plasmids, pBF4 and pCP1, which can be transferred to
E. coli by conjugation and express the resistance phenotype
in this host (Guiney et al., 1984). Further investigations
established that these genes are also the part
of Bacteroides conjugative transposons, Tn4351 and
Tn4400 (Robillard et al., 1985; Shoemaker et al., 1985).
The mobility of conjugative transposon Tn4351 was confirmed
for at least among the bacterial genera in the
Bacteroidetes phylum (McBride and Baker, 1996). TetX1and
TetX2-encoding sequences were initially identified on
a CTnDOT transposon from a human gut commensal
bacterium Bacteroides thetaiotaomicron but presumably
this transposon and its derivatives, with the ermF region
that contain these two tetracycline resistance genes, may
present in many other intestinal Bacteroides species as
well (Whittle et al., 2001). The environmental Sphingobacterium
sp. isolate carries tet(X) on a transposon-like
element, Tn6031, which is very similar to CTnDOT
(Ghosh et al., 2009). Our analysis of the limited regions of
sequence data available that surround tet(X) in the human
gut metagenome (BABB01000902) also demonstrated a
synteny with CTnDOT (data not shown). And finally, the
gene was discovered on a large 58 kb plasmid, which was
transferred from soil microbiota to E. coli recipient by conjugation
(Heuer et al., 2008). The Acinetobacter spp. are
probably putative hosts for these low G+C plasmids in soil
ecosystem, which is of concern because the closely
related multi-drug-resistant A. baumannii is one of the
currently emerging threats in hospitals (Dijkshoorn et al.,
2007). Tigecycline is currently proposed as a new treatment
choice against A. baumannii (Bosó-Ribelles et al.,
2008) but this bacterium already poses a significant
problem with the easily emerging resistance during tigecycline
therapy, albeit conferred by a mechanism other
than TetX (Peleg et al., 2007; Damier-Piolle et al., 2008).
Thus, the horizontal gene transfer potentials of tet(X) are
much higher than that of the RND-mediated resistance
making the former a more likely candidate for the possible
emergence of tigecycline resistance among pathogens.
Unlike the indiscriminate use of earlier tetracyclines, the
current use of tigecycline is restricted and, based on successful
results of large clinical trials, it is prescribed mostly
for the treatment of complicated skin and skin structure
infections and intra-abdominal infections in humans
as intravenous infusions (Babinchak et al., 2005; EllisGrosse
et al., 2005). During the tigecycline treatment of
healthy volunteers, the serum concentration of the drug
was less than 1 mg ml-1
but intestinal concentrations were
much higher, on average 6 mg per gram of faeces on day
8, which is consistent with the biliary elimination of the
drug (Nord et al., 2006). The tigecycline-resistant bacteria
selected in the human gastrointestinal system during this
treatment included two Klebsiella pneumoniae and five
E. cloacae strains (Nord et al., 2006), with the mechanism(s)
of resistance requiring further investigation.
In summary: (i) originating from the widespread
flavoprotein monooxygenase family, TetX possesses
efficient tigecycline inactivation capability, (ii) the gene
encoding TetX is located on multiple mobile genetic elements,
(iii) the gene was possibly pre-selected by the
older tetracyclines and can be detected in several ecosystems
including the human gut, and (iv) strong selective
pressure is expected in the gut of patients undergoing
tigecycline therapy. These prerequisites make TetX as a
most likely mechanism and the human gut as a most likely
ecosystem for the emergence of tigecycline-resistant
pathogens. The limiting factor in tet(X) dissemination is an
anaerobic metabolism of potential bacterial hosts, which
is unable to support its expression and therefore the gene
cannot be selected once the antibiotic pressure is applied.
Concluding remarks
A broader overview of the role of antibiotics and antibiotic
resistance in different environments has changed current
paradigms. Armed with this knowledge, an attempt was
made to model a scenario based on information we have
about resistance to a novel antibiotic. Future developments
will determine if present-day knowledge is sufficient
to predict resistance to novel antibiotics. The areas
that merit further investigations include the evolutionary,
environmental and regulatory aspects of antibiotics and
antibiotic resistance. We still have very little idea about the
impact of the large-scale antibiotic synthesis and release
on natural microbiota. Increased frequencies of antibiotic
resistance gene carriage by pathogens and some commensal
bacteria are well documented but what about
other ecosystems? While good progress has been made
in identification of environmental reservoirs of antibiotic
resistance, almost nothing is known about the environmental
concentrations of antibiotics. Regulatory and signalling
aspects that include identification of molecular
targets of subinhibitory antibiotics in all three domains of
life and how they interact with other regulatory networks
remain a priority. In bacteria, due to the complexity of
regulatory networks integrating multiple environmental
Role of antibiotics and antibiotic resistance 2981
© 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 2970–2988
signals and the dynamic nature of responses, the experimental
variables must be standardized in order for the
results to be comparable. Among the eukaryotic organisms,
some progress has been made in target identification
but still the signalling mechanisms of antibiotics that
are beyond their intended antibacterial use remain largely
unknown. The availability of the large number of antibiotics,
already approved for human use, makes them a valuable
source for treatment of other, than infectious,
diseases in humans and animals. Almost nothing is
known about the effects of subinhibitory antibiotics on
archaea despite that they are prominent members in
many microbial communities. Research in these areas will
not only help to understand more about antibiotics and
antibiotic resistance in natural ecosystems but also will
aid in making responsible choices when interacting with
these ecosystems in the course of clinical or agricultural
use of antibiotics.
Acknowledgements
I thank the Scottish Government Rural and Environment
Research and Analysis Directorate (RERAD) and the Department
for Environment, Food and Rural Affairs (DEFRA, Grant
OD2014) for support and Dr A.J. Travis for proof-reading the
manuscript.
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