Evolving Populations in Biofilms Contain More Persistent
Plasmids
Thibault Stalder,1,2,3 Brandon Cornwell,1 Jared Lacroix,1 Bethel Kohler,1 Seth Dixon,1 Hirokazu Yano,5Ben Kerr,3,4 Larry J. Forney,1,2 and Eva M. Top*,1,2,3,4
1

Department of Biological Sciences, University of Idaho, Moscow, ID
Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID
3
BEACON Center for the Study of Evolution in Action
4
Department of Biology, University of Washington, Seattle, WA
5
Graduate School of Life Sciences, Tohoku University, Sendai, Japan
Associate editor: Miriam Barlow
All sequencing data pertaining to this project have been made available at the National Center for Biotechnology Information (SRA
accession number PRJNA531499). Other raw data are available upon request.
*Corresponding author: E-mail: evatop@uidaho.edu.
2

Key words: plasmid, biofilm, experimental evolution, spatial structure, antibiotic resistance, horizontal gene transfer.

Introduction
Plasmids are major agents shaping bacterial evolution
through horizontal exchange of genetic information between
bacteria (Ochman et al. 2000; Frost et al. 2005; Wiedenbeck
and Cohan 2011). This exchange of adaptive traits is especiallyfostered by conjugative plasmids (Norman et al. 2009).
Unfortunately, plasmids are increasingly shown to be vectorsof the spread of resistance to so-called “last resort” antibiotics(Liu et al. 2016; McGann et al. 2016), resulting in antibiotic
treatment failures (McCollister et al. 2016; Chen 2017).
Indeed, plasmids increasingly make the headlines with alarming reports on their role in the spread of resistance to antimicrobials (World Health Organization 2014; White House
2015; European Centre for Disease Prevention and Control2016). The development of strategies to abate the spread ofantibiotic resistance may well depend on a better

understanding of processes that promote the spread andpersistence of resistance plasmids in bacteria.
Newly acquired resistance plasmids are not always stably
maintained. Hereafter, we define “plasmid persistence” as theability of a plasmid to maintain itself in a population in theabsence of known selection for the plasmid. The improvement of such plasmid persistence over time is coined“plasmid stabilization.” The low persistence of plasmids
in vitro is reflected in the rapid loss of plasmid-containing
bacteria in serially transferred batch cultures (De Gelder et al.
2007). Selection for a plasmid-encoded trait such as antibiotic
resistance has been shown to rapidly select for improved
plasmid persistence. Such adaptive evolution is the result ofgenetic changes in the bacterial host, the plasmid, or both.
The underlying mutations either ameliorate the plasmid fitness cost or decrease the plasmid loss rate during cell division(Sota et al. 2010; Hughes et al. 2012; San Millan et al. 2014;! The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://
creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium,provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

Open AccessMol. Biol. Evol. 37(6):1563–1576 doi:10.1093/molbev/msaa024 Advance Access publication February 6, 2020

1563

ArticleBacterial plasmids substantially contribute to the rapid spread of antibiotic resistance, which is a crisis in healthcare
today. Coevolution of plasmids and their hosts promotes this spread of resistance by ameliorating the cost of plasmidcarriage. However, our knowledge of plasmid–bacteria coevolution is solely based on studies done in well-mixed liquid
cultures, even though biofilms represent the main way of bacterial life on Earth and are responsible for mostinfections. The spatial structure and the heterogeneity provided by biofilms are known to lead to increased genetic
diversity as compared with well-mixed liquids. Therefore, we expect that growth in this complex environment could
affect the evolutionary trajectories of plasmid–host dyads. We experimentally evolved Shewanella oneidensis MR-1
with plasmid pBP136Gm in biofilms and chemostats and sequenced the genomes of clones and populations. Biofilm
populations not only maintained a higher diversity of mutations than chemostat populations but contained a few
clones with markedly more persistent plasmids that evolved via multiple distinct trajectories. These included theacquisition of a putative toxin–antitoxin transposon by the plasmid and chromosomal mutations. Some of thesegenetic changes resulted in loss of plasmid transferability or decrease in plasmid cost. Growth in chemostats led to ahigher proportion of variants with decreased plasmid persistence, a phenomenon not detected in biofilms. We suggestthat the presence of more stable plasmid–host dyads in biofilms reflects higher genetic diversity and possibly unknown selection pressures. Overall, this study underscores the importance of the mode of growth in the evolution of
antibiotic-resistant bacteria.

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Abstract

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persistence in evolved biofilms clones was not higher thanin the ancestor, but as expected, biofilm populations contained a small proportion of unique variants in which theplasmid was more persistent than in any clone evolved inchemostats. In contrast, chemostat growth led to variants
that showed decreased plasmid persistence, something thatwas not detected in the biofilms. The various evolutionary
and ecological processes that differ between biofilms andwell-mixed systems, such as spatial structure and heterogeneity and selective pressures, are discussed. Our study showsthat biofilm growth can lead to more persistent antibioticresistance plasmids that would probably be overlooked in the
traditional liquid culture evolution experiments.

Results
To study how biofilm growth affects the evolutionary trajectories of a plasmid–host dyad, we evolved Shewanella oneidensis MR-1 with plasmid pBP136Gm for 28 days both as
biofilms in four continuously fed flow cells (B1–4) and as
well-mixed cultures in four chemostats (C1–4) (fig. 1A).
This was done under antibiotic selection for the plasmid.
The flow cells gradually produced a thick biofilm that covered
the entire interior surface of the chamber (fig. 2). It was notpossible to calculate the number of generations in the biofilms because the growth rates are known to vary throughout.
Based on viable counts, the population densities in the biofilms and the chemostats were similar after 28 days: 1.606
0.03!108 and 1.7260.17!108 cfu ml"1, respectively (the total culture volume was 12 ml in both).

Evolutionary Outcomes of Plasmid Persistence
To test our hypothesis that evolution in biofilms allows the
emergence of a few clones that show higher plasmid persistence as compared with evolution in well-mixed environments, we first measured plasmid persistence in evolved
biofilm and chemostat clones (fig. 1C). These clones wererandomly chosen from three of the four replicate populations(biofilms B1, B2, and B3 and chemostats C1, C2, and C3), andcompared with the ancestor (fig. 3). They were named after
their environment (B or C) followed by I (for isolated clone)
and a clone number, for example, B2I3. Plasmid persistence
was assayed by determining the fraction of cells with plasmids
over time as the clones were passaged in serial batch cultures.
This assay took the clones out of the environment they were
evolved in (biofilm or chemostat), and placed them into acommon environment (batch culture) to enable direct comparison of evolved plasmid persistence under similar conditions. By using this single “common garden” design,dependencies of evolved plasmid persistence on the local
environment cannot be detected here. On an average, thepersistence of plasmids in clones from biofilms was not significantly different from that of the ancestral plasmid–hostdyad (fig. 3). However, when individual biofilm clones werecompared with the ancestor, two stood out as showing amarkedly higher plasmid persistence. Hereafter, we refer tothese as “stabilized clones.” In contrast, the persistence ofplasmids in bacteria evolved in chemostats was on an averagesignificantly lower than in the ancestor, and no stabilized

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Harrison et al. 2015; Loftie-Eaton et al. 2016, 2017; Porse et al.
2016; Yano et al. 2016; Stalder et al. 2017). Some of thesestudies showed that plasmid cost reduction was linked directly or indirectly to chromosomally encoded helicases ortranscriptional regulators, suggesting these proteins could betargets for future alternative drug therapies to reduce antibiotic-resistance spread. Thus, in the presence of antibiotics,
bacteria and antibiotic resistance plasmids are known to rapidly adapt to each other, resulting in stabilization of theplasmid.
Unfortunately, almost all experimental evolution studies
with plasmids have entirely been done using well-mixed liquid cultures that poorly mimic the habitat in which bacteria
usually reside. In nature and the human body, bacteria typically grow in biofilms that are the source of many recalcitrant
infections (Lewis 2001; Donlan 2012; Flemming and Wuertz
2019). Biofilms are populations or communities of microorganisms that grow on a surface in a matrix of extracellularpolymeric substances (Hall-Stoodley et al. 2004; Lewandowski
and Beyenal 2014). One intrinsic characteristic of biofilms isthat they are spatially organized habitats in which individuals
interact more frequently with neighbors than with more distant individuals. This spatial structure allows for habitat heterogeneity in which individuals at different locations
experience different selection pressures. Both spatial structureand habitat heterogeneity are known to substantially impact
evolution of microbial populations (Korona et al. 1994; Rainey
and Travisano 1998; Kerr et al. 2002, 2006; Perfeito et al. 2008;
Nahum et al. 2015; France et al. 2018, 2019). For example, byimpeding global competition between cells, spatially structured environments protract selective sweeps of beneficial
mutations and slow down the rate of adaptation (Perfeito
et al. 2008; Nahum et al. 2015; France and Forney 2019). This
promotes the coexistence of genetically distinct individuals,
which would not coexist in a well-mixed environment, andresults in the maintenance of genetic diversity allowing biofilm populations to harbor multiple distinct evolutionary outcomes (Boles et al. 2004; Ponciano et al. 2009; Eastman et al.
2011; Santos-Lopez et al. 2019). In addition, the intrinsic structure within biofilms generates environmental gradients ofnutrients and electron acceptors creating habitat heterogeneity that drives local adaptation of subpopulations, further
contributing to diversity. Extensive analysis of the mechanisms behind this diversification in biofilms was recently
reviewed (Martin et al. 2016; Steenackers et al. 2016; France
et al. 2018). The effect of biofilm growth on the evolutionary
outcomes of bacteria that carry plasmids needs to be identified to gain insight into the spread and persistence of antibiotic resistance plasmids in natural or clinical settings.
Here, we addressed the role biofilms play in the evolutionof a plasmid–host dyad that initially showed poor plasmid
persistence. Because biofilms maintain genetic diversity, wehypothesized that biofilm growth allows for the emergence ofsome clones that show higher plasmid persistence than any
clones evolved in well-mixed environments. To test our hypothesis, we conducted an experimental evolution study inbiofilms and chemostats using Shewanella oneidensis MR-1
containing plasmid pBP136Gm. On an average, plasmid

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Evolving Populations in Biofilms Contain More Persistent Plasmids . doi:10.1093/molbev/msaa024

S. oneidensis MR-1 (pBP136Gm)
Chromosome

Plasmid pBP136Gm
Native plasmids

Flowcell (Biofilm)
Lineages B1 to B4(Fig. 2)

ChemostatLineages C1 to C4(Fig. 2)B1 B2 B3 B4Clone isolation

B2I1-5

B3I1-5Fraction ofplasmid-bearing cells

B1I6-35

B- Whole-population
sequencing- Frequency ofmutations (Fig. 6)

Clone isolation

C- Plasmid persistence*of five clones (Fig.3)

C1I1-5

C2I1-5

C3I1-5

C1I6-35
D- Plasmid persistence*of 30 additional isolates
from lineage 1 (Fig. 4)*Plasmid persistence:

1
Ancestor

0
Days

...

0

12 daysFraction ofplasmid-bearing cells

B1I1-5C1 C2 C3 C4

1Ancestor

0Days

E- Genotyping of clones with:- improved persistence(Biofilms; Table 1)- decreased persistence(Chemostats; Table 2)

F- Plasmid cost estimations (Fig. 5)

FIG. 1. Diagram depicting the experimental design, sampling, and analyses of the Shewanella oneidensis evolution experiment. The isolated clones
were named after their environment (B for biofilm and C for chemostat), and then numbered I1–5 (e.g., B2I3), as well as I6–35 for the first biofilm
and chemostat, B1, and C1.

clones were observed in these populations. In fact, the opposite was true, as two chemostat clones showed significantly
lower plasmid persistence than the ancestral dyad.
To further explore the presence of a low proportion ofstabilized clones in biofilms, we sampled one biofilm (B1) and
one chemostat (C1) population more deeply by determining
plasmid persistence for 30 evolved clones from each population (figs. 1D and 4). As before, the average plasmid persistence in biofilm clones was not different from the ancestral
dyad, but there were now three biofilm clones that stood out
as showing higher plasmid persistence. Their final fraction ofplasmid-bearing cells at the end of plasmid persistence assays
exceeded 0.8 (vs. #0.65 in the ancestral population, fig. 4). We
verified the persistence by repeating the plasmid persistence

assay for these three clones in triplicate (data not shown). We
then calculated the probability of observing a plasmid persisting at a fraction of 0.84 after 12 days (i.e., the lowest of thethree high values in fig. 4) given the mean and SD of theplasmid persistence observed in the ancestral clones. This
probability was 0.0047, thus less than 1 in 200, whereas we
observed 3 clones out of 30 that showed a persistence $0.84.
In contrast, none of the 30 clones evolved in the chemostat
population showed plasmid persistence that exceeded that of
the ancestor and three clones even showed a significantly
lower plasmid persistence (fig. 4). These results suggest biofilms allow the emergence of a small proportion of clones thatshow clearly increased plasmid persistence. In contrast, noplasmid stabilization was observed among the chemostat
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A- Evolution - 28 days
with plasmid-selective
antibiotic

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0.8

●●

●
●

***

**

●

0.6

●●
●●
●●

●

● ●
●

●

0.4

0.2

at
m
or
Biofil Chemost Ancest

FIG. 2. Photograph depicting biofilm growth over time in two replicate flow cells (time in days is indicated above each picture) andchemostats (bottom right). The bottom flow cell image shows thedimensions.

clones, suggesting that mutations conferring higher plasmid
persistence were not beneficial enough to sweep through thechemostat population in that time period. Thus, out of morethan 40 evolved clones tested from each environment, 12%from biofilms, but none from chemostats, were found tomuch better retain their plasmid than the ancestor.

Evolutionary Pathways in Biofilms
Genotypes Suggest Different Evolutionary Trajectories in
Biofilms
To determine if the five stabilized biofilm clones followed
the same or different evolutionary trajectories, we compared their genome sequences (see red dots in figs. 3 and4, and table 1). In addition, we sequenced three randomly
chosen biofilm clones that showed no change in plasmid
persistence (fig. 1E and table 1). Overall, there were as
many as 7 unique genotypes among these 8 biofilm
clones, and the mutations were in or near 20 distinct
genes. The five stabilized biofilm clones had distinctly different genotypes, with three to six mutations per clone.
Moreover, 18 of the 19 mutations were unique to eachclone (table 1). Strikingly, none of these mutations waspresent in the three clones that did not show increased
plasmid persistence. Only one of them, a mutation
1566

FIG. 3. The persistence of plasmids in clones evolved in either biofilms
or chemostats was compared with that in ancestral clones in 12-day
plasmid persistence assays. For both biofilms and chemostats, weassayed the plasmid persistence of five clones from evolved populations 1 and 2, and three clones from population 3, compared with fiveancestral clones (as two clones from biofilm B3 were lost, only threeclones were analyzed for both biofilm B3 and chemostat C3, for consistency). The three filled symbols represent clones from biofilm (circle), chemostat (square), and ancestral (triangle) populations, witheach point showing the average value from triplicate persistence
assays for one clone. The open circles represent the overall averagefor each evolution environment and for the ancestor. The red filled
symbols at the top or bottom denote clones in which plasmid persistence was markedly different from the ancestor (t-test P values;
B1I3 < 0.01, B3I2 < 0.05, C3I1 < 0.05, and C3I5 < 0.01; tests were performed against the same sample size of randomly picked ancestor
values). Boxes represent the median and the first and third quartiles,
and the whiskers the lower and upper 1.5 interquartile range. No
significant difference was observed between the biofilm and ancestral
populations.

upstream of mxdA, was also found in a chemostat clone(see below, and tables 1 and 2).
In three of the five stabilized biofilm clones, plasmid
pBP136Gm had acquired the transposon Tn6374 from a native plasmid. These were three independent transposition
events. In one (B3I2), the transposon was inserted in a noncoding region 39 bp upstream of an operon composed of two
putative proteins of unknown function (XF1597 and XF1596).
In the two other clones (B1I25, B1I19), the transposon insertion disrupted two different plasmid transfer genes, trbJ andtrbO, respectively. Only the latter disruption caused loss ofthe plasmid’s ability to transfer by conjugation (data notshown). Interestingly, such transposition events have been
observed by us previously in the same strain, where they
were shown to increase plasmid persistence (Stalder et al.
2017). The chromosomal mutations found in these threeclones were not directly linked to mechanisms known toaffect plasmid persistence. Instead, they were related to cell
membrane composition and diffusion (SO4680), cell motility

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Fraction of plasmid−containing
bacteria

1.0

Evolving Populations in Biofilms Contain More Persistent Plasmids . doi:10.1093/molbev/msaa024

1.0
●
●

0.8
●
●●●
● ●
●●
●●●●
●
●● ●
●
●●
●●●

●

0.6

●

●

●

● ●
●

0.4

0.2

m
at
stor
Biofil Chemost
Ance

FIG. 4. Plasmid persistence in 30 clones isolated from a single evolved
biofilm population (B1), a single chemostat population (C1), and theancestor. The three filled symbols depict clones from biofilm (circle),chemostat (square), and ancestral (triangle) populations, with eachpoint representing a single measurement. The open circles represent
the average for each environment. The red filled symbols at the top
and bottom represent the clones for which plasmid persistence differed from the ancestor. Plasmid persistence in these clones wasverified by repeating the assay in triplicate and the four values werecompared with the same sample size of randomly picked ancestor
values (t-test P values for the six clones were B1I22 < 0.1, B1I19 < 0.05,
B1I25 < 0.01, C1I27 < 0.1, C1I25 < 0.01, C1I17 < 0.01). Boxes represent the median and the first and third quartiles, and the whiskers thelower and upper 1.5 interquartile range.

and chemotaxis (cheR and fliP), sulfur metabolism (SO2290
and SO4628), quorum sensing (aaiD), production of cyclic-diGMP (mxdA), and the O-antigen synthesis pathway (wbqC)(table 1).
Of the remaining two stabilized clones, clone B1I22 had
three chromosomal mutations in genes involved in cell membrane composition and diffusion (SO2045), chemotaxis(cheR), and an O-antigen synthesis pathway (SO3185).
Finally, clone B1I3 also showed three chromosomal mutations, one of them in an intergenic region distant from its
adjacent genes (>500 bp), and the other two in genes wbqC
and rpoA. RpoA is the essential a subunit of the RNA polymerase. Interestingly, four of the five stabilized clones showedmutations in genes involved in the O-antigen synthesis pathway, which is part of the lipopolysaccharide and related tobiofilm formation (Lau et al. 2009). We currently do not know
which of these mutations is responsible for improved plasmid
persistence, but the diversity of unique mutations in the five
biofilm clones clearly indicates that each of them followed adifferent evolutionary trajectory.
As a few clones evolved in chemostats showed a lower
plasmid persistence than the ancestor, a quite unusual

observation, we analyzed the genome sequences of five ofthem (see red dots in figs. 3 and 4, and table 2) in addition
to three clones with no change in plasmid persistence (table 2). Among these eight clones, there were five uniquegenotypes with mutations present in or near only ten genes.
Seven of these eight clones, including those with no change inplasmid persistence, showed again at least one mutation in
the chemotaxis signaling pathway che (cheR and cheC), andsix clones had mutations within or upstream of genes involved in cyclic-di-GMP metabolism (SO0569 and mxdA).
Cyclic-di-GMP has a prominent role in the switch between
motile and biofilm forming cells. For example, inPseudomonas aeruginosa, c-di-GMP controls the enzymatic
activity of the methyltransferase CheR (Yan et al. 2018), andin Shewanella oneidensis MR-1, the (cyclic-di-GMP)-forming
enzyme MxdA controls biofilm formation (Thormann et al.
2006). These data suggest that in the chemostats mutations
linked to chemotaxis were beneficial.
Plasmid Stabilization through Multiple Mechanisms
Plasmid stabilization could result from mutations that affectone of at least three biological parameters: 1) the fitness costof the plasmid, 2) the plasmid loss rate during cell division,and 3) horizontal plasmid transfer rate by conjugation (DeGelder et al. 2007). To gain insight into which of these parameters was affected by mutations in the five evolved stabilizedbiofilm clones, we estimated the cost of their plasmids(fig. 1F). This was done by measuring the fitness (W) of
each evolved plasmid-bearing clone relative to its plasmidfree counterpart in competition experiments. These results
were then compared with the relative fitness of the ancestral
plasmid-bearing versus plasmid-free host (plasmid cost of theancestral plasmid in the ancestral host was c ¼ 1"W ¼ 0.03;
see fig. 5). The two evolved clones in which the transposon
Tn6374 inserted in one of the plasmid’s transfer genes (B1I19,
B1I25) showed a slightly but not significantly lower plasmid
cost than the ancestor. To verify if the relative fitness (W) was
significantly different from 1 meaning there is no plasmid
cost, we changed the hypothesis of the t-test to W ¼ 1.
Interestingly, the plasmid cost in the clones B1I19 andB1I25 was no longer significantly different from zero, suggesting that the cost was ameliorated. Remarkably, the fitness ofclone B1I25 tended to be even higher than that of its plasmidfree counterpart (W > 1 or c < 0) (t-test P value <0.1), suggesting the plasmid had become slightly beneficial. In contrast, the plasmid cost did not significantly change in clones
B1I22 and B3I2, and became even larger in clone B1C3.
Therefore, either the plasmid loss rate or horizontal transfer
rate must have changed in these clones. For example, thethree clones that acquired Tn6374 in pBP136Gm, including
B3I2, may well have evolved a decreased plasmid loss rate.
This transposon encodes a putative toxin–antitoxin that caninhibit the growth of plasmid-free bacteria generated during
cell division, and a cointegrate resolution system that canhelp resolve plasmid multimers and thus improve proper
plasmid segregation (Stalder et al. 2017). Our findings showthat plasmid stabilization mechanisms were not the same
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Fraction of plasmid−containing
bacteria

●

MBE

6

xd
3

c

b

4

x

x

x

xc

SO4628
SO4680
trbJ
trbO
klcA</>XF1597

x

x

x

x

x

x

x
xc

mxdA</<SO4181

3

x

SO2045
SO4822</ id="564">SO2290
tnpA
wbqC

SO3185
rfbB
fliP
flgL
cheR

x

x

rpoA
pncC
aaiD
SO1092
SO1278>/<SO1281

x
4

x

x

x

2

x

x

2

x

x

3

xd

xd

x

Deletion 6 bp
A>G
A>C (T63T)(T)7>6tnpAb(A)5>4
C>A (R88L)
deletion 1 bp
1T
tnpAb
G>A (A144V)(A)6>7

A>T (E272D)
Tn6374b
C>T (A212V)
G>C (A105A)
9 bp>G

MutationEnzyme for biosynthesis of dTDP Qui4N
dTDP-glucose-4,6-dehydratase
Flagellar export protein
Flagellar hook-associated protein
Chemotaxis signal transduction system MCP methyltransferase

RNA polymerase alpha subunit
Nicotinamide deamidase
Acyl homoserine lactone acylase
Transcriptional regulator AraC family
Chemotaxis signal transduction system methyl accepting sensorytransducer/hypothetical protein
Cation efflux protein CDF family
Hypothetical protein/rhodanese domain protein UPF0176 family
ISSod4 transposase
Putative glycine transferase in O-antigen biosynthesis cluster

Description

Diguanylate cyclase-like protein/RNA pseudouridylate synthasefamily protein
4824623
2 bp>AA
Membrane sulfatase HI1246 family
4879232
tnpAb
CDP-glycerol glycerophosphotransferase family protein
Mating pair formation and entry exclusion
10326
Tn6374b (TTTTT)
14314 Tn6374b (CAAGTGGG) Transfer gene, unknown function
40107
Tn6374b (CTAAAT) Possible anti-restriction system/hypothetical protein

2143919240357324053963323205
3323304
3323634
33267823358060
3377938
33891923389247435400825857827601594702111309851332729

B1I3 B1I19 B1I22 B1I25 B3I2 B1I1a B1I2 B1I5 Position

Gray shading highlights the evolved clones with no change in plasmid persistence.
The insertion of a transposable element at that position.
Silent mutation.
d
Detected in the marginal prediction.

aTotal numberof mutations

pBP136Gm

Chromosome(NC 004347)

Gene

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RepliconTable 1. Summary of the Mutations in the Isolated Clones of Shewanella oneidensis MR-1 (pBP136Gm) Evolved in Biofilms.

Stalder et al. . doi:10.1093/molbev/msaa024

MBE

SOA0112; SOA0115

metB
MxdA</<SO4181

wbpA
cheR

SO1699phoP

SO0569cheC
SO1278>/<SO1281

Gene

x
x
4

x
x

C1I17

2

xb

xb

C1I25

3

xb
xb,d
xb

C3I1

3

xb
xb,d
xb

C3I5

b

2

x

x

b

C1I27

3

x
xb
x

C1I16a

2

x

x

b

C1I26

2

xe

x

b

C1I12

332891733889243389346338937242120224354008
4354022
91763
91703

178946320496195904785907871332264

Position

tnpAc
tnpAc
G>A (A111V)
tnpAc
C>A (A137A)(A)6>7(A)5>6
C>G (R1384G)
G>T (D2775Y)

A>T (L127Q)
C>A (G59C)

C>T (G39D)
C>T (R274H)
1ATGCCATCTCTG

Mutation

Description

Cystathionine gamma-synthase
Diguanylate cyclase-like protein/RNA pseudouridylate
synthase family protein
Putative lipoprotein

Diguanylate cyclase
Chemotaxis signal transduction system
Chemotaxis signal transduction system methyl
accepting sensory transducer/hypothetical protein
Transmembrane transcriptional regulator
Two component signal transduction system response
regulator
UDP-N-acetyl-D-glucosamine 6-dehydrogenase
Chemotaxis signal transduction system MCP
methyltransferase

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Gray shading highlights the evolved clones with no change in plasmid persistence.
Mutation detected by the whole-population sequencing approach.
c
The insertion of a transposable element at that position.
dSilent mutation.
e
Detected in the marginal prediction.

aTotal numberof mutations

pMR-1L

Chromosome(NC 004347)

RepliconTable 2. Summary of the Mutations in the Isolated Clones of Shewanella oneidensis MR-1 (pBP136Gm) Evolved in Chemostats.

Evolving Populations in Biofilms Contain More Persistent Plasmids . doi:10.1093/molbev/msaa024

MBE

1569

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1.00

1.1

●

0.75

●

1.0

●

●
●

0.9

●

●

●

*

●
●

0.50

●

●

●

B3I2

B1I25

B1I22

B1I19

B1I3

Ancestor

0.8
0.25

●

●

●
●●
●●
● ●●
●
●
●
●●
●●●●
●●●●
●
●●
●
●
●●●
●●●
●

Clone
FIG. 5. Fitness (W) of the ancestral plasmid–host dyad and five plasmid-bearing biofilm clones that showed the highest plasmid persistence, relative to their respective plasmid-free counterparts. Eachpoint shows the average of three competition assays. As the plasmid
cost equals 1"W, only clone B1I3 had a plasmid cost that had become
statistically different from that of the ancestor (increased cost,
P < 0.1). Plasmid-free counterparts of evolved hosts were obtained
as one of the first segregants during the persistence assay protocol(>100 colonies were replica-plated on selective and nonselective
media).

among the clones, supporting the conclusion that the biofilm
clones followed different evolutionary trajectories.

Whole-Genome Whole-Population Sequencing
Because we hypothesized that growth in biofilms would leadto greater genetic diversity, we also compared the frequency
of genomic changes in all four evolved biofilm populations
with those in the four evolved chemostat populations(fig. 1B). This was done using a whole-genome whole-population sequencing approach by sequencing DNA extracted
from the evolved populations and from the ancestral strain.
Henceforth, we refer to this approach as “whole-population
sequencing.” A total of 45 unique mutations were detected in
the four biofilm populations and only 22 in the four chemostat populations (fig. 6 and supplementary fig. S1,
Supplementary Material online). On an average, the diversityof unique mutations measured by the Shannon diversity index (H) was higher in the biofilms than the chemostats(Hbiofilm ¼ 2.24, HChemostat ¼ 1.47, t-test P value <0.05; thisindex ranges from 0 for a population with only a single genotype to high values for populations that have many mutations, with each unique mutation found in a few reads). This
supports the hypothesis that spatially structured biofilms
maintain a higher diversity of mutations than well-mixed
populations. We then tracked the frequencies of these genetic
changes in the populations (i.e., equivalent to frequencies of
new alleles). A frequency of 1 means that a mutation swept
through the population, since every sequence read coveringthat locus had that genetic change. Values <1 represent the
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●●
●● ●●

m

Biofil

ostat

Chem

FIG. 6. Frequency of mutations identified in biofilm and chemostat
populations. Boxes represent the median (horizontal line) and thefirst and third quartiles, and the whiskers the lower and upper 1.5
interquartile range. The open circles represent the average frequency
for each environment, which was lower for the biofilms than for thechemostats (P < 0.05).

fraction of reads in which the new mutation was observed.
On an average, the frequency of these mutations was significantly lower in the biofilm populations than in the chemostats, indicating proportionally fewer sweeps to fixation of
beneficial mutations in biofilms (fig. 6). This is consistent
with the finding that none of the mutations in the five biofilm
clones was detected in any of the biofilms by wholepopulation sequencing, suggesting these five mutants were
present at a rather low frequency. Indeed, average sequencing
depth for the whole-population sequencing was only #100!,and each sequenced clone from biofilm B1 was present at
only roughly 3% (1 out of 35 clones analyzed). It is thus
plausible that their mutations were not observed among
the whole-population sequence reads. This stands in contrast
to the chemostat populations, where 50% of the mutations
found in the sequenced clones were also detected by thewhole-population sequencing approach, suggesting they
were common as expected after a selective sweep (Table 2
and Figure S1). This population sequencing approach showsthat bacterial evolution led to a higher diversity of detectable
mutations in biofilms compared with chemostats, where a
few mutations tended to sweep to fixation.

Discussion
Very few studies have addressed the effect of biofilm growthon the coevolution of plasmids and their bacterial hosts(Ridenhour et al. 2017). Here, we postulated that the environment provided by biofilms affects the evolutionary outcomes of a plasmid-bacterium dyad by maintaining a higher

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Frequency

Relative fitness (W)1.2

Evolving Populations in Biofilms Contain More Persistent Plasmids . doi:10.1093/molbev/msaa024

underlying mechanisms of plasmid stabilization. Different
mutations that promote plasmid persistence were thus competing in the same population, supporting the idea of clonalinterference. Furthermore, none of these mutations swept tofixation. For the biofilm population from which 35 clones
were analyzed, the frequency of each unique genotype witha higher plasmid persistence was <3% (1/35). Strikingly themutations in these clones were not detected through wholepopulation sequencing, confirming that they were present at
a rather low frequency. These results suggest that in biofilms
there were a greater number of slower paced increases in new
putative beneficial mutations to detectable frequencies,
which led to a greater detectable standing diversity. It is precisely because these increases are not traditional selective
sweeps that the diversity pattern in biofilms would appear
as it does here. In some sense, the clonal interference inchemostats may have been shorter-lived as the very best
mutation drove other good mutations to extinction (see below); whereas many different good mutations can coexist for
longer in biofilms (Traverse et al. 2013)—that is, clonal interference is longer-lived in biofilms. Nevertheless, to fully understand the evolutionary dynamics of plasmid–bacteria
dyads in biofilms, future studies should sample biofilm populations over time and space, and test the persistence ofplasmids across a range of conditions, including those experienced by the evolving populations.
The diversity explanations above do not fully clarify why
we did not observe individuals with less persistent plasmids inthe biofilms, and why in chemostat we only detected clones
with plasmid persistence similar or lower than in the ancestor.
The former could be explained by positive selection on plasmid persistence and detection limits, but the latter requires
an additional explanation. In the biofilms, one can argue thatthe presence of the antibiotic selected, however weakly, forindividuals who better retained their resistance plasmid, thus
slowly outcompeting less-stabilized clones. Even if theseclones were present at just slightly lower frequency than
the stabilized ones, we would not have found them by screening only 35 clones among #109 cfu per biofilm. Nevertheless,there are at least two more possible explanations for why inbiofilms we found a few genetically distinct individuals withmarkedly higher plasmid persistence than in the ancestor, but
not in chemostats. The first one is that plasmid-persistenceenhancing mutations could have had a higher selective value
in biofilms than in chemostats, as supported by earlier findings that some plasmids can promote biofilm formation(Ghigo 2001; Madsen et al. 2012). Alternatively, other mutations beneficial to biofilm growth (not affecting plasmid persistence) may have had a relatively smaller selective value, incontrast to chemostat-selected mutations. Secondly, mutations beneficial to biofilm growth might have had unknown
positive pleiotropic effects on plasmid persistence. The opposite observation that evolution in chemostats negatively affected the ability of the plasmid to persist (figs. 3 and 4)
suggests antagonistic pleiotropy of mutations beneficial tochemostat growth. Indeed, the nature and high frequencyof the mutations found in chemostat clones suggest thatthe motile–sessile transition pathway was under selection.
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diversity of genotypes, including clones with more persistentplasmids than in well-mixed environments. In line with otherstudies on bacterial evolution, we found a higher diversity ofgenotypes in bacterial biofilms than in mixed liquids, andmost importantly, we showed that some of these evolved
biofilm clones contained very persistent plasmids. Although
the maintenance of a higher genetic diversity in biofilms can
explain these findings, it seems that selection and pleiotropic
effects also may have been at play.
We observed a higher diversity of mutations in populations that had evolved in biofilms compared with well-mixed
chemostats. Such a result was expected as microbial evolution
in biofilm populations is known to generate and preserve
genetic diversity (Boles et al. 2004; Ponciano et al. 2009;
Traverse et al. 2013). This observed diversification process inbiofilms is also in line with other studies from our group,
which showed higher diversity in plasmid persistence dynamics and corresponding genotypes after evolution in biofilms
than in well-mixed liquid cultures for an Acinetobacter baumannii strain with a similar plasmid (Ridenhour et al. 2017;
Metzger GA, Ridenhour BJ, France M, Forney LJ, Gliniewicz K,
Millstein J, Settles ML, Stalder T, Top EM, personal communication). Diversification of biofilm populations also means
there is a higher likelihood of discovery of mutants. Indeed, we
showed here for the first time that in biofilms and not inchemostats a few genetically distinct individuals arose with amarkedly more persistent plasmid than the ancestor or otherclones of the same populations. Nevertheless, one could argue
that if only genetic diversity was driving evolutionary outcomes this would translate in phenotypic diversity including
both high- and low plasmid persistence phenotypes, as observed by (Ridenhour et al. 2017). Here, we did not detect lesspersistent variants in the biofilms. Hereafter, we discuss several scenarios that could explain such observations, each not
being mutually exclusive but opening the way to further
disentangling evolutionary trajectories of plasmid–host dyads
in biofilms.
Several evolutionary and ecological processes have been
proposed to explain patterns of diversification in biofilms, andare extensively reviewed in (Steenackers et al. 2016; France
et al. 2018). For example, it has been suggested that populations evolving in biofilms may have a higher mutation rate
(Ryder et al. 2012; Steenackers et al. 2016), which could increase the mutation supply of a biofilm compared with achemostat population. In addition, local adaptation due tothe environmental heterogeneity probably drives diversification of biofilm populations (Rainey and Travisano 1998).
Greater heterogeneity in biofilms would thus lead to simultaneous evolutionary trajectories in multiple adaptive landscapes, leading to greater diversity. Furthermore, because
biofilm populations are spatially structured, and can be divided into small subpopulations or microcolonies, genetic
drift is likely to affect the exploration of the mutation landscape, and clonal interference is expected to be prolonged
due to the protraction of selective sweeps (Wright 1932;
Habets et al. 2006; Hallatschek et al. 2007; France andForney 2019). Interestingly, the five clones showing increased
plasmid persistence each had unique mutations and different

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Stalder et al. . doi:10.1093/molbev/msaa024

Materials and Methods
Bacteria and Plasmid
The plasmid host in this experimental evolution study was
S. oneidensis MR-1 ATCC 700550. The plasmid used was
pBP136Gm, which was derived from pBP136, a cryptic IncP1b plasmid isolated from the human pathogen Bordetella
pertussis (Kamachi et al. 2006). The plasmid pBP136Gm wasconstructed by replacing the kanamycin-resistance gene cassette in pBP136Km (Kamachi et al. 2006) with the gentamycin (Gm)-resistance cassette using the lambda-Red
recombinase expressed from pKD46 (Datsenko andWanner 2000), and the PCR-amplified Gm-resistance gene
(aacC1) cassette from pUC18-mini-Tn7T-LAC (Choi et al.
2005) using the primers set TraNup50aacC1 (50 CAGGCCCGCATAAAAACGAAGCCCGGCGGTCGCCGGG
CTTTTTTCTAGACCTTTGTCAACAGCAATGGATC-30 ) andTraMdn50barA (50 -CAGCCCCCCCTCGGCGGGCCTCCCT
1572

CGCCAGAAATGGCGATGCTCTAGAAGTTCTGCTTTGCC
TTCTCCAGCTTCT-30 ). Briefly, the PCR-amplified Gm-resistance gene cassette containing fragments homologous to theflanking regions of the kanamycin-resistance gene cassette in
pBP136Km was transformed into Escherichia coli EC100 containing the plasmids pBP136Km and pKD46 grown in 0.2%
arabinose at 30 & C. Recombinant cells were selected on Gm
and cured from pKD46 by growing the recombinant cells at
37 & C. Correct insertion of the Gm cassette was confirmed by
PCR and Sanger sequencing. The ancestral plasmid–hostdyad was constructed by electroporation of pBP136Gm
into S. oneidensis MR-1, which had been preadapted for#100 generations in the culture medium (see below).

Culture Media and Conditions
All evolution and plasmid persistence assays were carried out
in lactate mineral medium (Paulick et al. 2009) supplemented
with 0.015 M sodium fumarate (LMF). Sodium fumarate wasadded as an alternative electron acceptor because oxygen canbe limiting in our system. Experimental evolution was performed in LMF supplemented with 10 mg/l of Gm selecting
for the retention of the plasmid pBP136Gm, and the plasmid
persistence assays were done in the same medium without
Gm. Dilution plating to obtain individual clones was doneusing LMF agar. All cultures were incubated at 30 & C.

Experimental Evolution
Evolution experiments were performed using an ancestral
population that contained as little genetic diversity as possible. This was done by using an extinction-dilution procedureof the ancestral population (Ridenhour et al. 2017), wherein
the highest dilution that showed growth was archived inglycerol stocks and used as inoculum for evolution
experiments.
Shewanella oneidensis MR-1 (pBP136Gm) was evolved inparallel in four biofilms and four chemostat cultures for
28 days. We initiated the experiment by adjusting the opticaldensity (OD600) of the ancestral culture to 0.01 using a spectrophotometer (BioMate 3, Thermo Fisher Scientific), andinoculated the flow cells and the chemostats with 12 ml ofthis cell suspension. The description of the setup of the flow
cells is detailed in Ponciano et al. (2009) except that the flow
cells were made of polycarbonate plastic and the 12-ml chambers were sealed in-between two slides using silicone adhesive.
The chemostats were made of 21-ml glass tubes. After 4 h theflow of fresh medium was initiated (6 ml/h) and the chemostat culture volume was maintained at 12 ml. The flow cells,
chemostats, media, and waste bottles were kept at 30 & C in an
incubator, and media and waste bottles were changed approximately every 7 days. Flow cells and chemostats werechecked daily for overgrowth into the tubing supplying themedia and for leaks. Tubing and filters with substantial overgrowth were replaced as needed. To minimize biofilm growthon the chemostat walls, magnetic stir bars were used to keep
the cells in suspension as much as possible. However, after
20 days, wall growth resulted in a thin visible biofilm layer on
the chemostat walls. To avoid excessive wall growth, thechemostat populations were harvested on day 20, and cells

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Selection for wall growth formation in chemostats is wellknown (Hope et al. 2017), and may have resulted in a sweepof mutations linked to cell motility and attachment.
It should be noted that growth in a single biofilm resulted
in more evolutionary solutions to plasmid stabilization thanobserved in our previous experimental evolution studies
done in well-mixed serial batch cultures with a similar strain
and plasmid (Sota et al. 2010; Hughes et al. 2012; Stalder et al.
2017). In those studies, mutations in the plasmid replication
initiation protein TrfA1 were repeatedly observed, and insertion of the transposon Tn6374 into pBP136Km was seen in
only one of six clones (Stalder et al. 2017) and never in its
mini-replicon pMS0506 (Sota et al. 2010; Hughes et al. 2012).
Here, transposition of Tn6374 was the only plasmid mutation
observed in clones evolved in biofilms. Genome rearrangement and transposable elements have been suggested to playa critical role in the evolution of the S. oneidensis MR-1 genome (Romine et al. 2008), and more generally, in bacterial
and plasmid evolution (Cohen 1976). By carrying out experimental evolution in biofilms instead of mixed liquids, we may
thus have a better chance at observing the natural evolutionary trajectories of plasmid–host dyads.
This study illustrates how evolutionary dynamics in bacterial biofilms differ from those in well-mixed cultures. Given
that 40–80% of cells on our planet live in biofilms or otherforms of spatially structured communities (Flemming andWuertz 2019), and that most of infections are caused bybiofilms (Costerton et al. 1999; Hall-Stoodley et al. 2004;
Lebeaux et al. 2014), it suggests that future studies on theevolution of clinically relevant antibiotic-resistance plasmids
should include biofilms. Specifically, our findings show thatgrowth in biofilms can result in the evolution of a small proportion of bacteria with more persistent self-transmissible
antibiotic-resistance plasmids than expected from studies
with well-mixed liquids. As many such resistance plasmids
are ubiquitous in the clinic today (Mathers et al. 2015), thishigher plasmid persistence could accelerate the spread ofresistance among pathogens, which is of great medical
concern.

Evolving Populations in Biofilms Contain More Persistent Plasmids . doi:10.1093/molbev/msaa024

Plasmid Persistence Assays
Individual clones were isolated from the glycerol stocks generated at the end of the evolution experiment. Clones from
biofilm B4 and chemostat C4 were not analyzed; only wholepopulation sequencing analyses were performed on thesefourth replicates. The persistence of plasmids in clonal populations was quantified as follows. Tubes containing 5 ml ofLMF (without antibiotics) were inoculated with 4.9 ml of precultures which were grown overnight in LMF-Gm from archived clones (representing day 0 of the plasmid persistence
assays). For the next 12 days, these cultures were serially transferred daily to fresh media without antibiotics selecting forthe plasmid (4.9 ml into 5 ml, resulting in about ten doublings
per day). The final overnight culture was serially diluted andaliquots were spread onto LMF agar plates. After overnightincubation, 52 single colonies were randomly selected andreplica-plated onto LMF and LMF-Gm agar. The ratio of
the number of colonies grown on LMF-Gm and LMF on
day 12 was calculated and represents the fraction ofplasmid-bearing bacteria in the population at the end of
the serial transfer series.

Conjugative Plasmid Transfer Assays
Transmissibility of the plasmid by conjugation from the plasmid donors (D) to a plasmid-free recipient (R), resulting intransconjugants (T), was determined in filter matings. To
distinguish R from D, R was a streptomycin (Sm)-resistantmutant of MR-1. Briefly, both D and R were grown fromglycerol stocks in LB Miller broth using appropriate antibiotics
for the selection of the plasmid-containing (Gm, 10 mg/l) andplasmid-free bacteria (Sm, 50 mg/l). After 24 h incubation,
1 ml of bacterial cultures were centrifuged (3 min, 8,000!g)and the pellets were rinsed by suspending in the same volumeof phosphate-buffered saline pH 7.4 (PBS). Bacteria were harvested a second time by centrifugation and suspended in 0.1
volume of PBS, and 50 ml of D and R were mixed, harvested bycentrifugation, and suspended in 50 ml of PBS. The mixture, as

well as the same volumes of D and R separately, was placed on
a 0.45-mm HTBP filter on a LB Miller agar plate, left to dry, andincubated. The filters were collected after 24 h, and for eachthe entire cell biomass was suspended in 2 ml of PBS. The
population densities (CFU ml"1) of T, R, and D were determined by plate counting using selective LB Miller agar supplemented with the appropriate antibiotics.

Estimation of Plasmid Cost
Competition experiments were performed to estimate theplasmid cost. Each strain to be competed was inoculated
from its glycerol stock into test tubes with 5 ml of LMF brothand grown for 16 h. Culture media were supplemented with
Gm when appropriate. Cultures (1.5 ml) were harvested bycentrifugation (10,000!g, 3 min) and the pellets were suspended in 1.5 ml of sterile PBS. Equal volumes of each competitor (100 ll) were mixed, and 4.9 ml was used to inoculate
5 ml of LMF broth. After 24 h of growth, 4.9 ml was transferred
once again to 5 ml of LMF broth and incubated for 24 h. The
number of CFU of the initial and final mixtures was determined by spread plating onto LMF agar. The fractions ofplasmid-containing and -free bacteria were determined byreplica plating 52 randomly selected colonies on LMF and
LMF-Gm agar. The relative fitness (W) of the plasmidcontaining relative to the plasmid-free bacteria was calculated
according to (Lenski et al. 1991): Wpþ/p" ¼ ln(Pþt2/Pþt0)/ln(P"t2/P"t0), where Pþt0 and P"t0 are the numbers ofplasmid-containing and -free bacteria at the start of the 2day assay, and Pþt2 and P"t2 the final numbers. A plasmid
cost of zero should result in a Wpþ/p" of 1.

DNA Extractions and Sequence Analysis
For the whole-population sequencing approach, total genomic DNA was extracted from the biofilm and chemostat
populations using the Power Biofilm DNA isolation kit(MoBio) on previously frozen cell pellets that were thawedon ice. The protocol was followed according to manufacturer’s instructions, except that during the lysis step the samples were vortexed by pulsing for 1 min instead of using thehorizontal vortex adapter. For the genomic analyses of individual clones, total genomic DNA was extracted from 2 ml ofan overnight culture using the GenEluteTM Bacterial
Genomic DNA kit (Sigma-Aldrich, St. Louis, MO). The quality
and the integrity of the gDNA were assessed on a 1% agarose
gel and the concentrations were determined fluorometricallyusing Quant-iT PicoGreen dsDNA Reagent (ThermoFisher
Scientific, Waltham, MA) with the TBS-380 MiniFluorometer (Turner BioSystems) (Molecular Devices,
Sunnyvale, CA).
Full-genome sequencing was performed by the IBEST
Genomics Resources Core using an Illumina MiSeq platform(Illumina, San Diego, CA) and 300-bp Paired-End Sample
Preparation Kits (Illumina, San Diego, CA). Prior to analysis,
the reads were preprocessed through the read-cleaning pipeline HTStream (https://github.com/ibest/HTStream; lastaccessed February 11, 2020) consisting of the following steps: 1) duplicate read pairs (possibly resulting from multicycle
PCR reactions carried out as part of library preparation) were1573

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were resuspended and transferred to new chemostats. Thiswas repeated on day 26 as new wall growth became visible.
The chemostat populations were grown for a total of 485
generations (28 days).
After 28 days, the biofilms were harvested by breaking theseal between the lid and body of a flow cell using a sterile
scalpel blade and the cover was set aside. The cell mass was
suspended in the overlying media and mixed by repeatedly
pipetting up and down. The resulting suspensions were thentransferred to 50-ml centrifuge tubes and vortexed for 1 min
to disperse the cells. A comparable procedure was done forchemostat cultures (both planktonic cells and cells growing
on the walls were harvested). Aliquots of these cell suspensions were used to determine total bacterial counts byspreading dilution series on LMF and LMF-Gm agar. In addition, 0.5- and 1-ml aliquots of biofilms and chemostats cultures, respectively, were harvested by centrifugation (10 min,
10,000!g). Cell pellets were stored at "20 & C for total DNA
extraction. Another aliquot was archived in glycerol stocks at"70 & C.

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Stalder et al. . doi:10.1093/molbev/msaa024

Statistics
Statistical tools were applied to the data set using R version
3.4.2. Pairwise comparisons were carried out using both the ttest and the nonparametric Mann–Whitney test, and whencomparing more than two samples, we used the function
aov() to fit an analysis of variance model. In cases where we
combined the results from clones isolated from three distinct
population (i.e., results in fig. 1), we nested the random factor“population” into the fixed factor “environment” (i.e., biofilm,
chemostat, or ancestor), and considered the ancestor as one
population. For all the models, we ran a post hoc analysis with
Tukey’s test (all pairwise comparisons) or Dunnett’s test(when the means were compared with a control group), using the function glht() of the multcomp package. The P values
are reported as *<0.1, **<0.05, and ***<0.01.
For the unbalanced design of the data in figure 1, we confirmed the analysis using a linear mixed-effect model approach using the nlme package. Using such a model, we
1574

nested the random factor “population” into the fixed factor“environment” and analyzed the variance tables for themodel. To correct for the unbalanced design, we tested fora difference in the weighted marginal means (instead of the
grand mean) using the option “type ¼ ‘marginal’” in thefunction anova() or “type¼‘c(‘III’)’” in the function Anova().
The corrected and uncorrected analyses of variance had almost same results (probably because the imbalance had aminor effect), and suggested that the means of the plasmid
persistence were different between environments. We thenperformed a post hoc analysis on the model as describedearlier.

Supplementary Material
Supplementary data are available at Molecular Biology and
Evolution online.

Acknowledgments
This work was supported by the National Science Foundation
BEACON Center for the Study of Evolution in Action(Cooperative Agreement Number DBI-0939454), theNational Institute of Allergy and Infectious Diseases (Grant
No. R01 AI084918) of the National Institutes of Health (NIH),
and the Institutional Development Award (IDeA) from the
National Institute of General Medical Sciences of the NIH(Grant No. P20GM103408). The genome sequencing was carried out by the IBEST Genomic Resources Core, and madepossible thanks to NIH NIGMS (Award No. P30 GM103324).
We thank Ben Ridenhour for his advice on statistical analyses,
Michael France for his advice on the chemostat and biofilm
setup, and James Soderling and Alexandra Gal for technicalassistance.

Author Contributions
E.M.T., L.J.F., and B.Kerr conceived the project. T.S. and E.M.T.
wrote the article and L.J.F. and B.Kerr provided thoroughrevisions. T.S. led the project and did the genomic analyses.
T.S. and B.K. ran the evolution experiment. B.C. performed theplasmid persistence assays and growth kinetics. J.L. performed
additional persistence assays. S.D. significantly contributed tothe competition and conjugation assays. H.Y. constructed
pBP136Gm.

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