MINIREVIEW
1
Progress towards understanding the fate of plasmids in bacterial
communities
Frances R. Slater1,2, Mark J. Bailey1, Adrian J. Tett1 & Sarah L. Turner1
1
The Centre for Ecology and Hydrology, Oxford, UK; and 2King’s College London, Pharmaceutical Sciences Research Division, London, UK
Correspondence: Sarah L. Turner, The
Centre for Ecology and Hydrology, Mansfield
Road, Oxford OX1 3SR, UK. Tel.: 144 0 1865
281 630; fax: 144 0 1865 281 696; e-mail:
[email protected]
Received 16 November 2007; revised 20 March
2008; accepted 20 March 2008.
First published online 28 May 2008.
DOI:10.1111/j.1574-6941.2008.00505.x
Editor: Jan Dirk van Elsas
Keywords
horizontal gene transfer; plasmid ecology;
fitness trade-offs; facultative symbionts.
Abstract
Plasmid-mediated horizontal gene transfer influences bacterial community structure and evolution. However, an understanding of the forces which dictate the fate
of plasmids in bacterial populations remains elusive. This is in part due to the
enormous diversity of plasmids, in terms of size, structure, transmission, evolutionary history and accessory phenotypes, coupled with the lack of a standard
theoretical framework within which to investigate them. This review discusses how
ecological factors, such as spatial structure and temporal fluctuations, shape both
the population dynamics and the physical features of plasmids. Novel data indicate
that larger plasmids are more likely to be harboured by hosts in complex
environments. Plasmid size may therefore be determined by environmentally
mediated fitness trade-offs. As the correlation between replicon size and complexity of environment is similar for plasmids and chromosomes, plasmids could be
used as tractable tools to investigate the influence of ecological factors on
chromosomes. Parallels are drawn between plasmids and bacterial facultative
symbionts, including the evolution of some members of both groups to a more
obligate relationship with their host. The similarity between the influences of
ecological factors on plasmids and bacterial symbionts suggests that it may be
appropriate to study plasmids within a classical ecological framework.
Introduction
The horizontal gene pool
The horizontal gene pool (HGP) refers to genetic information that may be accessible to more than one bacterial
species, potentially resulting in phenotypes of one being
acquired by another. It includes the constituent genes of
mobile genetic elements (MGEs) and also genes that, whilst
not mobile themselves, may be mobilized by MGEs. Examples of MGEs include plasmids, bacteriophages, conjugative
transposons and integrative conjugative elements. The HGP
may have profound effects on both the ecology and the
evolution of bacteria. Successful horizontal transfer of
sequences that confer adaptive traits can significantly alter
the ecology of the recipient bacterium, allowing colonization of otherwise hostile niches. An important example of
this is the acquisition of antibiotic resistance as a result of
plasmid transfer, which has been demonstrated for numerous bacterial genera in diverse habitats, such as wastewater
FEMS Microbiol Ecol 66 (2008) 3–13
(Mach & Grimes, 1982), animal products (Jayaratne et al.,
1989), and the guts of mice (Mus musculus) (DoucetPopulaire et al., 1992) and house flies (Musca domestica L.)
(Petridis et al., 2006). Horizontal transfer is also responsible
for dissemination of other potentially ecologically significant traits, such as virulence. For example, benign strains of
Xanthomonas citri may become pathogenic via acquisition
of the plasmid pXcB, to cause citrus canker disease (El
Yacoubi et al., 2007). Horizontally transferred sequences
that persist also affect bacterial diversity and evolution
(Doolittle, 1999; Ochman et al., 2000; Jain et al., 2002;
Gogarten & Townsend, 2005). Evidence for widespread
acquisition and persistence of horizontally transferred genes
comes from regions of genomes that have a discontinuous
distribution between closely related species and genera. This
may be apparent from unusual G1C content or patterns of
codon usage; these are reasonably uniform within species
but show significant variation between species. Marked
differences in isolated regions of genomes indicate recent
horizontal acquisition from distantly related species
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(Lawrence & Ochman, 1997). Using these methods, Lawrence & Ochman (1998) estimated that up to 18% of the
extant chromosome of Escherichia coli may have been
acquired via horizontal transfer since its divergence from
Salmonella 100 million years ago. That is not to say that 18%
of the genetic content of E. coli is currently mobile.
Horizontally transferred sequences that become fixed in a
chromosome lose their ecological relevance as MGEs and are
no longer considered components of the HGP.
F.R. Slater et al.
(a) Vegetative segregation
(b) Horizontal transfer
(c) Reduced vertical transfer
(d) Increased vertical transfer
Selection for
plasmid encoded
traits results in
high relative host
growth rates
Plasmids
Plasmids are amongst the best characterized and most
widely recognized members of the HGP. They are a broad
class of extrachromosomal elements, capable of horizontal
transmission and also of regulating their copy number
independently of the host chromosome. Replication is
usually via one of two general strategies, rolling circle or
theta and strand displacement (del Solar et al., 1998), and
horizontal transmission proceeds either via conjugation,
transformation or transduction (Thomas & Nielsen, 2005).
Other characteristic survival functions of plasmids include
loss prevention strategies, such as copy number control and
multimer resolution (Summers, 1998), active partitioning
systems (Ebersbach & Gerdes, 2005) and postsegregational
killing (Hayes, 2003). Plasmids are ubiquitous entities,
found in most bacterial species, as well as some archaeal
and eukaryotic species, and in virtually all ecosystems, from
hydrothermal vents (Prieur et al., 2004) to arctic soils
(Fagerli & Svenning, 2005). They have been termed ‘individuality replicons’ (Chain et al., 2006) due to their propensity
to encode accessory phenotypes that render their host better
able to survive in atypical environments. Examples include
virulence, resistance to antimicrobials and heavy metals and
the ability to catabolize xenobiotics and other complex
carbon sources. However, plasmid carriage is only beneficial
to the host if environmental conditions are such that there is
positive selection for these plasmid-encoded phenotypes.
Also, any fitness advantage is countered by a potentially
small but permanent fitness cost associated with plasmid
carriage. The combination of these factors dictates the
survival, spread or demise of a plasmid in a population.
Stable maintenance of plasmid numbers can only be
achieved if rates of plasmid loss, via vegetative segregation
and/or fitness disadvantages due to the fitness costs of
plasmid carriage, are at least equalled by rates of plasmid
gain, via horizontal transfer and/or fitness advantages due to
plasmid-encoded beneficial phenotypes (Fig. 1).
Plasmid population dynamics
Quantitative mathematical approaches to population
biology, devised for higher organisms (e.g. Lotka, 1925;
Volterra, 1926), were first applied to plasmid population
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c
No selection for
plasmid encoded
traits results in
low relative host
growth rates
Number of plasmids in population
Decrease
Increase
Fig. 1. Plasmid survival, spread or demise is dictated by the combined
rates of transmission processes (a, b) and selection processes (c, d).
Plasmids will only be stably maintained in a population if rates of loss, via
vegetative segregation (a) and negative effects on host growth rate due
to the fitness costs associated with plasmid carriage (c), are at least
equalled by rates of gain, via horizontal transfer (b) and positive effects
on host growth rate due to plasmid-encoded beneficial phenotypes (d).
dynamics in the 1970s. Stewart & Levin (1977) produced the
first theoretical investigation of the ability of plasmids to
establish and spread in natural populations and provided a
basis for many subsequent studies (Levin et al., 1979; Levin
& Stewart, 1980; Freter et al., 1983; Lundquist & Levin, 1986;
Simonsen et al., 1990; Bergstrom et al., 2000). Many of the
empirical estimates of process rates used in these models
were determined experimentally in batch or chemostat
culture using laboratory strains and plasmids constructed
using recombinant DNA technology as well as novel host
–plasmid combinations. These approaches fail to take into
account some of the physiological and ecological complexities of plasmids and their hosts in natural environments.
For example, horizontal transfer rates may vary according to
the growth stage and physiological state of the bacterium. In
log phase, rates may be reasonably approximated by a mass
action model but in lag or stationary phase, they may not
(Levin et al., 1979). Transitory derepression of conjugative
pili synthesis may occur in newly formed transconjugants,
increasing rates of horizontal transfer and the potential for
plasmids to establish and spread through a population
(Lundquist & Levin, 1986). To complicate matters further,
the goodness of fit of the mass action model and the effect of
transitory derepression is different for bacteria colonizing
surfaces than for bacteria in liquids (Simonsen, 1990).
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Fate of plasmids in bacterial communities
Moreover, horizontal transfer rates of some plasmids are
affected by external cues, such as cell density or stress.
For example, specific opines, which are small carbon
compounds produced by crown gall tumours, and a quorum-sensing signal, the acyl-homoserine lactone ligand Agrobacterium autoinducer (AAI), produced by the bacterium
itself, regulate conjugal transfer of Ti plasmids in Agrobacterium spp. (Oger & Farrand, 2002). Similarly, enterococcal
mating pheromones allow donor cells to regulate expression
of conjugal transfer of the plasmid pCF10 in response to
recipient cell density (Kozlowicz et al., 2006). R27 and other
IncI1 plasmids have an unusual, thermosensitive mode of
conjugation, with transfer occurring optimally between 22
and 28 1C but inhibited above 37 1C (Sherburne et al., 2000).
Different estimates of context-dependent parameters, such
as rates of horizontal transfer, will probably have dramatic
effects on plasmid population model predictions.
Since Stewart & Levin’s seminal paper, there has been a
great deal of work to identify relevant parameters and
incorporate more accurate, quantitative estimates of process
rates into models of plasmid dynamics in natural environments. Here, we review recent observational, experimental
and theoretical studies that have brought us closer to
understanding how ecological parameters influence the fate
of plasmids in bacterial populations. The focus is particularly on the effect of selection processes (Fig. 1c and d) as
these are a frequently overlooked component of plasmid
population dynamics (Eisen, 2000), and transmission processes (Fig. 1a and b) have been reviewed comprehensively
by others (van Elsas & Bailey, 2002; Sorensen et al., 2005).
We will instead take more of an overview of the survival and
spread of a plasmid through a recipient population following
transfer. We also discuss how the physical form of plasmids,
including plasmid size and gene content, is influenced by
ecological features. Parallels are drawn between plasmids
and a similarly diverse group of biological entities, the
facultative bacterial symbionts, and comparisons are
made between sizes of plasmid genomes from different
environments.
What makes a plasmid a plasmid?
There are three interlinked and defining features of plasmids: separateness (i.e. the potential to be physically distinct
and to replicate autonomously) from the chromosome,
transmissibility (i.e. the ability to transfer or be transferred
as a discrete molecule) and dispensability (i.e. lack of
essential genes). Plasmids tend to have discontinuous distributions in their host population (which may be composed of clones or different species and/or genera) due to
two of these three general features: they can be horizontally
transferred to novel hosts and, as dispensable entities,
physically lost from individual hosts.
FEMS Microbiol Ecol 66 (2008) 3–13
The enormous diversity of plasmids, in terms of size,
structure, transmission, evolutionary history and accessory
phenotypes, in many ways mirrors that of another group,
the facultative bacterial symbionts. This group of bacteria is
capable of either a free-living or a host-associated lifestyle.
Well-known examples include Wolbachia spp. in arthropods
and Rhizobium and Frankia spp. in plants. The facultative
symbionts share all three of the general features of plasmids:
horizontal transmission, dispensability and separateness.
They similarly have a discontinuous distribution in host
populations. For example, although rhizobia have a worldwide distribution, unique Rhizobium spp. occur in isolated geographical regions (Martinez-Romero & CaballeroMellado, 1996). Symbionts also have complicated fitness
impacts on their host; although they are generally considered to be beneficial, symbiont–host relationships may be
mutualistic or pathogenic depending on host identity and
environment (Dale & Moran, 2006). Rhizobium spp. and
Frankia spp. benefit their leguminous and actinorhizal plant
hosts by fixing nitrogen (Postgate, 1978) and Hamiltonella
defensa defends its pea aphid host (Acyrthosiphon pisum)
against parasitic wasps (Aphidius ervi) (Oliver et al., 2003).
However, Wolbachia pipientis can cause reproductive abnormalities in a number of insect host species (Stouthamer
et al., 1999) and Serratia symbiotica may reduce fecundity in
pea aphids that are ‘superinfected’ with both S. symbiotica
and H. defensa (Oliver et al., 2006). Also, just as for
plasmid–host relationships, these symbioses have probably
evolved multiple times, with examples from many different
bacterial genera in many different host lineages (Thao et al.,
2000; Moran et al., 2005).
There is considerable variety in the degree of dependency
of a host on its symbiont; facultative symbionts, as noted
previously, are dispensable whereas obligate symbionts are
absolutely required for host survival. For example, female
tsetse flies (Glossina spp.) undergo a loss of fertility when
cured of their symbionts, Wigglesworthia glossinidia (Hill
et al., 1973). Obligate symbionts are usually descended from
ancient associations whereas facultative symbionts are more
modern, implying that obligate relationships may be the
evolutionary endpoints of facultative ones (Ochman &
Moran, 2001; Moran, 2002). Further evidence for this comes
from extant symbionts, such as the tsetse fly endosymbiont
Sodalis glossinidius, which appear to be in transition from
facultative to obligate status. The genome of S. glossinidius is
characterized by a high proportion of pseudogenes for
functions associated with a free-living lifestyle, such as
defence and transport and metabolism of diverse carbohydrates (Toh et al., 2006). Similarly, plasmid hosts may be
more or less dependent on their plasmids for survival. Some
bacteria even have ‘obligate’ plasmid-like replicons which
encode essential functions, the secondary chromosomes (for
reviews see Mackenzie et al., 2004; Maclellan et al., 2004;
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Egan et al., 2005). There is some ambiguity in the definition
of an essential function and there are a number of large
replicons for which the designation of plasmid or secondary
chromosome is not straightforward. For example, the
legume symbiont Sinorhizobium meliloti 1021 has a composite genome comprising a chromosome (3.65 Mb) and two
megaplasmids, pSymA (1.35 Mb) and pSymB (1.68 Mb),
both with distinctive repABC plasmid replication genes
(Galibert et al., 2001). However, as pSymB carries the only
copy of an essential gene, the arginine tRNA, ArgtRNACCG, it
is probably more appropriately termed a secondary chromosome. pSymA does not carry any essential genes and
pSymA segregants have been demonstrated to grow under
laboratory conditions (Oresnik et al., 2000). It is difficult to
make definitive statements about the transferability of
pSymA and pSymB because, although transfer has not been
detected under laboratory conditions, this may not be
relevant to transfer in the rhizosphere. For example, there is
evidence that pSymA is self-transmissible but that transfer is
repressed by expression of the pSymA-encoded rctA gene
under laboratory conditions (Perez-Mendoza et al., 2005).
One interpretation of the S. meliloti 1021 genome (Galibert
et al., 2001) is that pSymB has lost all transfer genes, except
for a paralogue of the pSymA traA and an oriT sequence, and
gained an essential gene, the ArgtRNACCG, and is now
‘locked’ within its host, like W. glossinidia within tsetse flies.
pSymA contains putative conjugative transfer genes
(traACDG) and a putative oriT sequence but lacks the
traIRMBF and trbDJKLFH genes found on other rhizobial
plasmids and so, like S. glossinidius within tsetse flies, may be
in transition from being facultative to being tightly associated with its host. Just as the evolutionary path from
facultative to obligate symbioses seems to be a common one,
it is also likely that the transition from plasmids to secondary chromosomes has occurred in multiple lineages on
separate occasions. Mackenzie et al. (2004) list 44 species of
bacteria, predominantly from the Alphaproteobacteria, but
also from the Beta- and Gammaproteobacteria, spirochetes
and deinococci, as having replicons that could be designated
secondary chromosomes. Furthermore, phylogenetic relationships of the ParA ATPases of chromosomes, secondary
chromosomes and plasmids from these species show that
the secondary chromosome protein sequences cluster with
plasmid-associated proteins rather than their chromosomal
counterparts (Maclellan et al., 2004). Genomics has therefore highlighted an additional parallel between plasmids and
the facultative bacterial symbionts: the potential to evolve
from a facultative to an obligate symbiosis.
Does size matter?
Plasmids occupy an enormous size range, with an c. 2500fold difference between the smallest and largest published
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F.R. Slater et al.
bacterial plasmid sequences. These range from the 0.85 kb of
pRKU1 from the obligate anaerobic heterotroph Thermotoga petrophila RKU1 (Nesbo et al., 2006) to the 2.09 Mb of
megaplasmid pGMI100 from the soil-borne plant pathogen
Ralstonia solanacearum GMI100 (Salanoubat et al., 2002).
This size difference is far larger than the c. 80-fold difference
between the smallest and largest published bacterial genome
sequences, from the 160.00 kb of the psyllid endosymbiont
Carsonella rudii PV (Carsonella-PV) (Nakabachi et al.,
2006) to the 13.00 Mb of the myxobacterial strain Sorangium
cellulosum So ce56, an important producer of secondary
metabolites (Schneiker et al., 2007). There is substantial
evidence to suggest that total genome size is related to
ecological factors, with residents of stable environments,
such as obligate parasites or symbionts, having smaller
genomes and residents of complex, variable environments,
such as soil-dwelling, facultative symbionts, having larger
genomes (Bentley & Parkhill, 2004; Raes et al., 2007).
We have investigated the relationship between ecological
factors and plasmid genome size for 980 bacterial plasmids,
including megaplasmids, from the Plasmid Genome Database (http://www.genomics.ceh.ac.uk/plasmiddb/) (Molbak
et al., 2003). The plasmids were binned according to:
(1) size (0–25, 25–50, 50–100, 4 100 kb) and (2) the environment from which the plasmid and/or host was isolated
(animal, including animal products such as milk or faeces,
or nonanimal with nonanimal further subdivided into
aquatic and terrestrial for the two largest plasmid size
fractions) (Fig. 2). Host environment was determined from
metadata within the primary literature and/or project data
from sequencing centres. In instances where the provenance
of the plasmid and/or host was not apparent from these
sources, isolation environment was recorded as unknown.
Generally, there were less metadata available for plasmids
belonging to the smaller size fractions, which prevented a
meaningful subdivision of nonanimal into aquatic and
terrestrial. Of all plasmids, over half were from animal(55.20%) and approximately one-third from nonanimal(32.86%) associated hosts with the remainder (11.94%)
unknown. The higher proportion of plasmids from animalthan nonanimal-associated hosts in the database is presumably a reflection of sampling bias, with more studies
focusing on microbial communities of human, animal and
food products than of terrestrial and aquatic environments.
This trend held for all but the largest size fraction, 4 100 kb,
where the trend was significantly different, with far fewer
plasmids from animal- (27.56%) than nonanimal- (71.15%)
associated hosts (w2 = 67.99, P o 0.0005). Of the 4 100-kb
plasmids from nonanimal-associated hosts, almost twothirds were from terrestrial environments (65.77%) with
fewer than one-third from aquatic environments (27.03%).
This bias was less marked in the 50–100-kb size range of
plasmids from nonanimal-associated hosts, where almost
FEMS Microbiol Ecol 66 (2008) 3–13
7
Fate of plasmids in bacterial communities
0 – 25 kb
n = 592
25 – 50 kb
n = 122
50 – 100 kb
n = 110
> 100 kb
n = 156
Fig. 2. In total, 980 bacterial plasmids from the Plasmid Genome Database (http://www.genomics.ceh.ac.uk/plasmiddb/) were binned according to
size: 0–25, 25–50, 50–100 and 4 100 kb; and host environment: animal including animal products, e.g. milk and faeces (blue), nonanimal (green) and
unknown (yellow). Of the 156 large plasmids ( 4 100 kb), more were from nonanimal- (71.15%) than animal- (27.56%) associated hosts with the
remainder unknown (1.28%). This is significantly different from the proportions in the total data set, where more were from animal- (55.20%) than
nonanimal- (32.86%) associated hosts with the remainder unknown (11.94%) (w2 = 67.99, P o 0.0005). Of the 111 large plasmids from nonanimalassociated environments, 65.77% were from terrestrial (bright green) and 27.03% were from aquatic (mid green) environments with 7.21% unknown
(light green). Of the 110 plasmids in the 50–100-kb size range, 45.95% were from terrestrial and 32.43% were from aquatic environments with
21.62% unknown.
half (45.95%) were from terrestrial environments and
approximately one-third (32.42%) from aquatic environments. With only 980 plasmid genomes available on the
Plasmid Genome Database at the time of writing, these data
are from what is clearly a limited and potentially biased
sample of plasmids. However, these data do raise the possibility that plasmid size is under the same ecological constraints
as chromosome size, with larger genomes associated with
more complex, heterogeneous environments, such as soil. It
may be that this similarity between plasmid and chromosome
responses to ecological pressures extends to other genomic
features, such as physical architecture and gene content and
distribution. Therefore, insights into the ecological forces that
shape plasmids may inform our understanding of the ecological forces that shape chromosomes.
In complex environments, there may be selection for large
plasmids if they encode traits that render the host bacterium
better able to survive in multiple niches. Is there also,
however, a counter selection that limits the size of plasmids?
The mechanisms by which the fitness costs of plasmid
carriage operate are unclear. It has been variously suggested
that costs are related to plasmid-encoded protein expression
levels (Rozkov et al., 2004), replication and maintenance of
plasmid DNA (Bjorkman & Andersson, 2000) or disruption
of cellular regulatory status (Ricci & Hernandez, 2000).
There are little data available on the influence of plasmid
size and copy number on fitness costs for environmental
plasmids and hosts. One study did investigate the effect of
carriage of 101 antibiotic resistance plasmids isolated from
medical material on the growth rate of E. coli K12 921 (Zund
& Lebek, 1980). Although the authors reported no clear
relationship between host population generation time and
plasmid size, they did note that plasmids that extended host
generation times by more than 15% tended to be large
(4 80 kb). Preliminary experiments conducted in our
laboratory using the pQBR collection of plasmids (Lilley
et al., 1996) have similarly shown an increase in fitness cost
to the host with plasmid size (unpublished data). Further
FEMS Microbiol Ecol 66 (2008) 3–13
research is clearly needed to determine exactly which
environmental, host and plasmid factors dictate the magnitude of the fitness costs associated with plasmid carriage.
Initial indications are, however, that fitness trade-offs of
plasmid carriage are environmentally mediated and are a
determinant for plasmid size.
Are plasmids selfish or altruistic
elements?
The perceptible fitness costs associated with carriage of
many plasmids coupled with examples of plasmids that
apparently confer no benefit on host cells has led to them
being dubbed ‘selfish’ or ‘parasitic’ elements (Kado, 1998).
Any benefit conferred on the host may also be viewed as a
selfish strategy as survival of the host ensures survival of the
plasmid. However, a number of common traits borne by
plasmids are examples of cooperative social, or altruistic,
behaviour, i.e. they benefit not only the host but also other
members of the population. Examples include nodulation,
catabolism of complex carbon sources and degradation of
xenobiotic compounds. As with any cooperative social
behaviour, there is the capacity for individuals to cheat and
reap the benefits of the ‘public good’ while avoiding the
metabolic cost of the behaviour. If these cheaters gain
sufficient fitness advantages then they are liable to spread
rapidly through a population, creating a tragedy of the
commons (Hardin, 1968). If plasmids are indeed selfish,
why do they carry public good genes? And how do public
good plasmids persist when there is a net fitness benefit to
cheating and plasmids may be physically lost via vegetative
segregation?
Horizontal transfer has been proposed as a potential
strategy for limiting the prevalence of cheating strains.
Smith (2001) produced a mathematical model of the
population dynamics of pathogenic bacteria that secrete
virulence factors into the extracellular environment (cooperators) and their nonsecreting (cheating) counterparts. The
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model predicted that horizontal transfer of virulence factors
would reduce the number of cheaters and result in a larger
peak bacterial population size. It is difficult to comment on
the adequacy of this model as the author did not compare
model predictions with any experimental results. It is,
however, an interesting hypothesis that warrants further
investigation.
Another potential mechanism for limiting the prevalence
of cheating strains is negative, or stabilizing, frequencydependent selection, i.e. the fitness of a particular phenotype
increases as it becomes less common in a population.
Negative frequency-dependent selection is important in
many eukaryotic systems for maintaining genetic polymorphisms (i.e. multiple alleles). Examples include foraging
gene alleles in larvae of the common fruitfly (Drosophila
melanogaster) (Fitzpatrick et al., 2007) and self-incompatibility alleles in plants (de Nettancourt, 1977). Negative
frequency-dependent selection is also important for maintaining genetic variation in bacteria (Levin, 1988; Rainey &
Travisano, 1998). The coexistence of plasmid-carrying and
plasmid-free strains in a population may be thought of as a
bacterial dimorphism. Negative frequency-dependent selection for plasmid-encoded genes has been experimentally
demonstrated for a number of host–plasmid systems and
therefore may be an important determinant for plasmid
persistence. Dugatkin et al. (2005) performed competition
experiments with cooperators (E. coli carrying an ampicillin
resistance plasmid) and cheaters (plasmid-free E. coli protected from ampicillin in the vicinity of cooperators) in
mixed liquid culture. The cheaters maintained frequencies
of 5–12% in the presence of ampicillin. Also, when cheaters
arose via vegetative segregation from pure cultures of
cooperators in the presence of ampicillin, they were similarly maintained at frequencies of c. 10%. More recently,
Ellis et al. (2007) demonstrated coexistence between environmental isolates of cooperators (Pseudomonas fluorescens
SBW25 carrying the mercury resistance plasmid pQBR103)
and cheaters (plasmid-free P. fluorescens protected from
mercury in the vicinity of cooperators). It may be that these
mechanisms, whereby selection for plasmid-encoded traits
is influenced by community structure, are responsible for
the stable persistence of some plasmids. The propensity for
plasmids to be physically lost and horizontally transferred
makes them suitably responsive agents for frequencydependent processes.
Environmental variation
The vast majority of bacteria in natural environments
colonize surfaces, such as rocks, soil particles, plant leaves
and roots, gut linings, skin and liquid–air interfaces (Costerton et al., 1994). These environments are all spatially and
temporally heterogeneous and some, such as soil, are
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F.R. Slater et al.
extremely so (Young & Crawford, 2004). Almost 20 years
ago, Eberhard (1990) proposed that sporadic selection for
plasmid-encoded genes, typical of that in heterogeneous
environments, was an important determinant for plasmid
persistence. Bergstrom et al. (2000) subsequently produced
a mathematical proof that demonstrated sporadic selection
alone was not sufficient to ensure plasmid persistence but
further conditions, such as selective sweeps (Turner et al.,
1998), were also required. However, there have been few
attempts to test Eberhard’s hypothesis experimentally. This
is due to the difficulties of both quantifying changes in
physical, chemical and biological conditions in natural
environments at the microscale and also predicting their
effects on parameters such as horizontal transfer rates (van
Elsas et al., 2003). Recently, however, there has been some
progress, for example with the development and implementation of stochastic models (discussed below), towards
identifying the role of environmental variation in plasmid
persistence.
Spatial structure
The spatial structuring of bacterial populations in natural
surface environments can affect plasmid persistence. For
example, the dynamics of horizontal transfer differ between
populations on surfaces and in liquids (for a review see
Molin & Tolker-Nielsen, 2003). Also, the degree to which
selection for plasmids is frequency-dependent may differ
between surface and liquid environments. Chao & Levin
(1981) very elegantly demonstrated this in competition
experiments using E. coli B carrying the colicinogenic
plasmid ColE3 and plasmid-free E. coli B. The colicinogenic
phenotype is a particularly extreme form of cooperative
behaviour as the metabolic cost of colicin production is
death (lethal synthesis). At any one time, only a small
proportion of the colicinogenic population produces colicin; both these producing cells and sensitive, plasmid-free
cells are killed whereas the remaining colicinogenic, nonproducing cells are immune. Surviving cells are then able to
utilize nutrients released from the dead, lysed cells. In mixed
environments (liquid serial batch culture), colicinogenic
populations were at an overall fitness advantage relative to
sensitive populations, increasing in frequency over successive cultures, only when the initial frequency of colicinogenic cells was high. In spatially structured environments
(soft agar matrix), however, colicinogenic populations were
at an overall fitness advantage relative to sensitive populations even at far lower initial cell densities. As the colicinogenic cells were found to have a lower intrinsic growth rate
than the sensitive cells, these differences must be understood
in terms of the effects of spatial structure on the distribution
of colicin and nutrients from dead cells. In mixed environments, colicin and nutrients will be distributed equally to
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Fate of plasmids in bacterial communities
colicinogenic, nonproducing cells and sensitive cells. If
colicin concentrations are at sublethal levels, sensitive cells
will have a fitness advantage due to their higher intrinsic
growth rate. In spatially structured environments, however,
colicin and nutrients will be at higher concentrations in
areas around colicinogenic colonies. The colicinogenic,
nonproducing cells that are able to survive in these areas
will therefore benefit from the higher concentrations of
nutrients. The influence of spatial structure on frequencydependent selection has also been demonstrated for plasmids harbouring other cooperative traits. The negative
frequency-dependent selection for P. fluorescens SBW25
carrying the mercury resistance plasmid pQBR103 demonstrated by Ellis et al. (2007) was found to differ between
mixed and spatially structured environments. In mixed
environments, coexistence of plasmid-carrying and plasmid-free strains occurred over a narrower range of higher
mercury toxicity levels when the initial cell density was high.
In spatially structured environments, the initial cell density
had no effect. The findings of both these studies suggest
that spatial structure increases the range of environmental
conditions in which coexistence of plasmid-carrying and
plasmid-free strains can occur. Spatial structure may therefore facilitate plasmid persistence and play a role in maintaining discontinuous distributions of plasmids in bacterial
populations.
With the exception of a few recent studies, most mathematical models of plasmid population dynamics have not
incorporated a spatial component. However, Lagido et al.
(2003) did produce a model for horizontal transfer of
plasmids on surfaces where donor and recipient cells were
considered to initiate separate colonies which grew exponentially until nutrient exhaustion. Horizontal transfer
through conjugation occurred instantaneously when donor
and recipient colonies met. Experimental results were reasonably well described by the model, although it tended to
overestimate instances of conjugation. When conjugation
was set to not occur instantaneously, model predictions
were improved. However, the authors conceded that a
number of model assumptions, such as conjugation occurring every time a donor and recipient met and the exponential growth of all cells in a colony, were biologically
unrealistic. More recently, Krone et al. (2007) produced a
spatially explicit, stochastic individual-based model (IBM)
of plasmid persistence on surfaces that incorporated plasmid loss as well as horizontal transfer. Spatially explicit
IBMs simulate the behaviour of individuals occupying sites
according to their interactions with other individuals in
local neighbourhoods of proximal sites. In the model of
Krone et al., local effects were captured by allowing the
replication rate of an individual (bacterial cell) to vary
according to: (1) cell type, i.e. donor, recipient or transconjugant, of the individual; and (2) nutrient level in a specified
FEMS Microbiol Ecol 66 (2008) 3–13
local neighbourhood. Similarly, horizontal transfer rates
for donors were allowed to vary according to numbers
of different cell types within another specified local neighbourhood of a donor. Stochastic effects were captured by
updating sites asynchronously, i.e. at each time step, randomly chosen individuals were allowed to behave, i.e.
replicate, transfer or lose plasmid etc., according to the
constraints specified. The model was given a ‘hint’ of threedimensional (3D) structure by allowing up to two individuals to occupy any one site. Experimental results were
mostly well described by the model, except for dynamics of
plasmid R1 in E. coli K12 from Simonsen (1990). This
plasmid undergoes transitory derepression following transfer and so transfers at different rates according to residence
time in the host cell. The authors predicted that not
accounting for this variation in the model may have reduced
the accuracy of its predictions. They also predicted that the
lack of real 3D structure in the model would reduce its
accuracy in capturing the behaviour of long-term experiments. Importantly, both models predicted features of
plasmid persistence on surfaces consistent with experimental findings that were not predicted by the mass-action
models after Stewart & Levin (1977). These models have
provided a theoretical framework within which to investigate the dynamics of plasmids in spatially structured environments. The application of IBMs is in its infancy but there
is the potential for making predictions as to the effects of
realistic ecological variables, such as sporadic selection
(Eberhard, 1990) and disturbance events (Buckling et al.,
2000), on plasmid persistence.
Temporal fluctuations
Selection acting on plasmids changes over time according to
variation in extrinsic (i.e. environmental) and intrinsic (i.e.
plasmid and host) factors. There is often a correlation
between plasmid prevalence and selection. For instance,
greater numbers of mercury-resistant plasmids have been
isolated from mercury-impacted soils than from pristine
soils (Dronen et al., 1998; Smit et al., 1998). However,
antibiotic resistance plasmids have been shown to persist in
the absence of antibiotic selection (Chaslusdancla et al.,
1987; Johnsen et al., 2005) so the cause and effect relationship is obviously not a simple one. Amelioration of the
fitness costs associated with plasmid carriage may be partially responsible for this, either by adaptation of the host
in the presence of selection (Bouma & Lenski, 1988) or
by host–plasmid coadaptation in the absence of selection
(Modi & Adams, 1991; Dahlberg & Chao, 2003). Some
of the variations that influence plasmid persistence may be
of a stochastic nature. Plasmid loss, for instance, has been
noted to be a rather unpredictable event (Corchero &
Villaverde, 1998).
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10
Most models of plasmid persistence to date have ignored
the potential influence of these temporal variations. However, Ponciano et al. (2007) recently devised a stochastic
model for the dynamics of plasmid persistence that included
the relative fitness of plasmid-free cells as a random variable
influenced by environmental fluctuations (where ‘environment’ referred to the host itself as well as the environment
surrounding the host). This model was then applied to seven
plasmid–host combinations (of the broad host range IncP1b plasmid pB10, and alpha-, beta- and gammaproteobacterial hosts) that showed plasmid loss over up to 600
generations in serial batch culture (De Gelder et al., 2007).
Plasmid loss was better explained by this model than
deterministic models in four of seven plasmid–host associations. Although the model was not mechanistic and could
therefore not predict the cause of the stochasticity, we might
speculate that it was due to environmental heterogeneity or
genetic drift in the host and/or plasmid. Given these interesting initial results, greater exploration of the importance
of stochasticity for plasmid persistence in natural environments seems pertinent. A comparison of the degree to which
stochasticity explains plasmid persistence in heterogeneous
(natural) environments and homogeneous (batch culture)
environments would delineate the influence of extrinsic
(environment) and intrinsic (host and plasmid) factors.
Concluding remarks
The focus of plasmid ecology research to date has been on
plasmid population dynamics. In the future, there is likely to
be increased emphasis on ecological factors that influence
physical features of plasmids, such as size. This type of
analysis is made vastly more powerful by the amount of
genomics data now available; as of June 2007, the 1000th
bacterial plasmid genome was logged on the Plasmid
Genome Database. Genomics resources such as this will
prove to be of enormous value for testing hypotheses about
ecological influences on plasmid genomes. It may be that
features such as physical architecture and gene composition
will, like genome size, be similarly ecologically constrained
for plasmids and chromosomes. If there are indeed universal
truths that describe the influence of ecological factors on
genomes, then plasmids are useful tools for investigating
them. They are, by the simple virtue of being smaller, more
tractable replicons than chromosomes.
As for most sequenced bacterial genomes, plasmid genomes often contain a significant proportion of genes of
unknown function. It appears that our knowledge of plasmid-encoded gene function is more limited than that of
chromosomally-encoded gene function as a number of
composite genome-sequencing projects have found higher
proportions of genes of unknown function on plasmids
than chromosomes. In R. solanacearum GMI100, a greater
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F.R. Slater et al.
proportion were found on the mega plasmid (18.7%) than
on the chromosome (12.6%) (Salanoubat et al., 2002).
Similarly, in S. meliloti 1021, a greater proportion were
found on pSymA (11.5%) and pSymB (12.3%) than on the
chromosome (5.0%) (Galibert et al., 2001). The mercury
resistance plasmid pQBR103, the subject of over a decade of
research and referred to earlier in this review, also has an
exceptional degree of novelty; 80% of its 478 putative coding
sequences could not be ascribed a function (Tett et al.,
2007). Understanding of ecological factors that impact on
plasmids will remain incomplete until knowledge of gene
function is more comprehensive.
Although genome sequences may tell us a lot about
plasmids, they are not a panacea for the problem of
investigating plasmids in situ. As just mentioned, plasmid
gene sequences are only meaningful in the context of gene
function, plasmid gene functions are only meaningful in the
context of gene expression, gene expression is only meaningful in the context of a host, and host bacteria are only
meaningful in the context of their environment. Therefore, a
variety of experimental, observational and theoretical approaches, at different scales, are needed. There has recently
been a call to explore whether classical ecological theory
might provide a framework within which to investigate
microbial communities (Prosser et al., 2007). Given the
parallels between plasmids and a group of microorganisms,
the facultative bacterial symbionts, it seems appropriate to
extend application of these tools to the ecology of plasmids.
Acknowledgements
We are grateful to Dawn Field for helpful discussions and to
four anonymous reviewers and the editor for considered and
constructive comments on early versions of the manuscript.
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