The evolution of antibiotic susceptibility and resistance during the formation of Escherichia coli biofilms in the absen...

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Title:
The evolution of antibiotic susceptibility and resistance during the formation of Escherichia coli biofilms in the absence of antibiotics
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English
Creator:
Tyerman, Jabus G.
Ponciano, Jose M.
Joyce, Paul
Forney, Larry J.
Harmon, Luke J.
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BioMed Central (BMC Evolutionary Biology
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Abstract:
Background: Explanations for bacterial biofilm persistence during antibiotic treatment typically depend on non-genetic mechanisms, and rarely consider the contribution of evolutionary processes. Results: Using Escherichia coli biofilms, we demonstrate that heritable variation for broad-spectrum antibiotic resistance can arise and accumulate rapidly during biofilm development, even in the absence of antibiotic selection. Conclusions: Our results demonstrate the rapid de novo evolution of heritable variation in antibiotic sensitivity and resistance during E. coli biofilm development. We suggest that evolutionary processes, whether genetic drift or natural selection, should be considered as a factor to explain the elevated tolerance to antibiotics typically observed in bacterial biofilms. This could be an under-appreciated mechanism that accounts why biofilm populations are, in general, highly resistant to antibiotic treatment. Keywords: Evolution, Antibiotic resistance, Bacterial biofilms, Mutations, Diversity
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Publication of this article was funded in part by the University of Florida Open-Access publishing Fund. In addition, requestors receiving funding through the UFOAP project are expected to submit a post-review, final draft of the article to UF's institutional repository, IR@UF, (www.uflib.ufl.edu/UFir) at the time of funding. The institutional Repository at the University of Florida community, with research, news, outreach, and educational materials.
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Tyerman et al. BMC Evolutionary Biology 2013, 13:22 http://www.biomedcentral.com/1471-2148/13/22; Pages 1-7
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doi:10.1186/1471-2148-13-22 Cite this article as: Tyerman et al.: The evolution of antibiotic susceptibility and resistance during the formation of Escherichia coli biofilms in the absence of antibiotics. BMC Evolutionary Biology 2013 13:22.

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ui 1471-2148-13-22
ji 1471-2148
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dochead Research article
bibl
title
p The evolution of antibiotic susceptibility and resistance during the formation of it Escherichia coli biofilms in the absence of antibiotics
aug
au id A1 ce yes snm Tyermanmi Gfnm Jabusinsr iid I1 I2 I6 email jabustyerman@gmail.com
A2 PoncianoMJoséI3 josemi@ufl.edu
A3 JoycePaulI4 I5 joyce@uidaho.edu
A4 ForneyJLarrylforney@uidaho.edu
A5 ca HarmonJLukelukeh@uidaho.edu
insg
ins Department of Biological Sciences, University of Idaho, Campus Box 3051, Moscow, ID, 83843, USA
Initiative for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, 83844, USA
Department of Biology, University of Florida, Gainesville, FL, USA
Departments of Mathematics, University of Idaho, Moscow, Moscow, ID, 83844, USA
Departments of Statistics, University of Idaho, Moscow, ID, 83844, USA
Current address: Genomatica, Inc., 10520 Wateridge Circle, San Diego, CA, 92121, USA
source BMC Evolutionary Biology
section Experimental evolutionissn 1471-2148
pubdate 2013
volume 13
issue 1
fpage 22
url http://www.biomedcentral.com/1471-2148/13/22
xrefbib pubidlist pubid idtype doi 10.1186/1471-2148-13-22pmpid 23356665
history rec date day 18month 6year 2012acc 1112013pub 2812013
cpyrt 2013collab Tyerman et al.; licensee BioMed Central Ltd.note This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
kwdg
kwd Evolution
Antibiotic resistance
Bacterial biofilms
Mutations
Diversity
abs
sec
st
Abstract
Background
Explanations for bacterial biofilm persistence during antibiotic treatment typically depend on non-genetic mechanisms, and rarely consider the contribution of evolutionary processes.
Results
Using Escherichia coli biofilms, we demonstrate that heritable variation for broad-spectrum antibiotic resistance can arise and accumulate rapidly during biofilm development, even in the absence of antibiotic selection.
Conclusions
Our results demonstrate the rapid de novo evolution of heritable variation in antibiotic sensitivity and resistance during E. coli biofilm development. We suggest that evolutionary processes, whether genetic drift or natural selection, should be considered as a factor to explain the elevated tolerance to antibiotics typically observed in bacterial biofilms. This could be an under-appreciated mechanism that accounts why biofilm populations are, in general, highly resistant to antibiotic treatment.
bdy
Background
Bacteria that form biofilms have been shown to be highly resistant to antimicrobial therapy
abbrgrp
abbr bid B1 1
B2 2
B3 3
and contribute to the chronic nature of many bacterial infections in humans because cells in biofilms are highly resistant to antibiotic treatment (e.g.
B4 4
B5 5
). Developing effective treatments for biofilm-related infections requires an understanding of the processes that lead biofilms to persist in the face of antimicrobial treatment
B6 6
.
There are multiple hypotheses to explain biofilm persistence during antibiotic treatment
B7 7
B8 8
B9 9
B10 10
. Physical factors, like diffusion limitation, may prevent antibiotic concentrations from reaching inhibitory or lethal levels within biofilms
B11 11
B12 12
. However, several studies report biofilm persistence despite substantial antibiotic diffusion (e.g.
B13 13
B14 14
, reviewed in
1
B15 15
). Another hypothesis posits that non-genetic phenotypic heterogeneity, including the plastic expression of phenotypes that are resistant to antibiotics, may occur in biofilms. For example, resource gradients may lead cells to experience different microenvironments and thus express distinct phenotypes in different parts of a biofilm
1
9
. In particular, a “persister” phenotype has been hypothesized to arise in biofilms and provide immunity against antibiotics
B16 16
. These persister cells are postulated to have the ability to reconstitute biofilms upon release from antibiotic threat
16
B17 17
B18 18
B19 19
.
Alternatively, bacteria cultured as biofilms may evolve heritable variation for resistance to antibiotics de novo
7
. We know that evolutionary change can occur rapidly within tens to hundreds of generations
B20 20
, which are time scales relevant to medical treatment of infectious diseases
B21 21
. Furthermore, bacteria in biofilms have huge population sizes so that many new mutations will arise over relatively short time scales. It is possible that antibiotic resistance might arise in bacterial biofilms through straightforward population genetic processes. We suggest that, given enough time, variation in antibiotic resistance may arise in biofilms even in the absence of antibiotic selection. This could happen due to the accumulation of neutral variation or as a result of selection for phenotypes that by happenstance are correlated with antibiotic resistance (e.g.
B22 22
).
Evolutionary change in biofilms is plausible since recent studies have shown tremendous phenotypic variation among cells isolated from biofilms growing in patients
B23 23
B24 24
B25 25
and demonstrated heritable variation in traits within experimentally cultured biofilm populations
B26 26
B27 27
B28 28
B29 29
B30 30
B31 31
B32 32
. However, few hypotheses about antibiotic resistance in biofilms invoke evolutionary change as an alternative explanation for biofilm persistence during antibiotic treatment (but see
7
8
27
). Evolution could involve mutations that convey resistance to single antibiotics (specialized resistance) or to whole suites of antibiotics (broad-spectrum resistance
8
). The occurrence of variants resistant to antibiotics may provide an “insurance effect”
30
32
B33 33
by creating subpopulations of cells that can survive or even proliferate should the biofilm come under antibiotic assault. Resistant variants could thus facilitate reconstitution of bacterial biofilm populations following cessation of antibiotic treatment.
Documenting whether genetic variation for antibiotic resistance arises during the course of biofilm development is an important first step to exploring biofilm persistence in the face of antibiotic treatment. As we suggest, evolutionary explanations predict that genetic variation in the susceptibility to antibiotics will arise in biofilms, and that the frequency of antibiotic resistant cells will increase through time. Here we demonstrate the rapid evolution of heritable variation for broad-spectrum antibiotic resistance during the course of biofilm development by E. coli. We tested three hypotheses in this work: (1) heritable variation for antibiotic resistance evolves during biofilm development; (2) this variation includes both resistant and susceptible mutants to a range of antibiotics; and (3) phenotypic variation in biofilms increases through time. We found evidence for both (1) and (2) but not (3). Variation in antibiotic resistance emerged within 15 days of biofilm growth, a time frame that is consistent with many common bacterial infections. Thus, these findings have important implications for the development of treatments for bacteria that form biofilms during infection.
Results and discussion
We cultured Escherichia coli K12 MG1655 as biofilms in the absence of antibiotics. Briefly, we inoculated E. coli into flow-cells and cultured biofilms using minimal medium with glucose as a sole carbon source. We sampled biofilm populations at 15, 30 and 60 days and isolated ten bacterial clones from three replicate flow cells at each time point. Using the Kirby-Bauer disc diffusion method
B34 34
, we characterized each bacterial clone for resistance to twelve antibiotics by measuring the diameters of zones of (growth) inhibition (ZOI) for each clone on each antibiotic (Table
tblr tid T1 1; see detailed methods below).
table
Table 1
caption
b Summary of the antibiotics used in this study
tgroup align left cols 3
colspec colname c1 colnum 1 colwidth 1*
c2 2
c3
thead valign top
row rowsep
entry
Antibiotic class
Antibiotic
Abbreviation
sup
1
tfoot
1Based on Sensi-disks from BD. Numbers following letters indicate ug of antibiotic applied to each disk.
tbody
Aminoglycoside
Streptomycin
S10
Gentamicin
GM10
Kanamycin
K30
Quinolone
Naladixic acid
NA30
Ciprozone
CIP5
Beta-lactam
Ampicillin with Sulbactam
SAM20
Cefoperazone
CFP75
Semi-synthetic (rifamycin group)
Rifampin
RA5
Cationic basic protein
Polymyxin B
PB300
Macrolide
Erythromycin
E15
Glycopeptide
Vancomycin
VA30
Polyketide
Tetracycline
TE30
We tested whether heritable variation for antibiotic resistance evolved during biofilm development by assessing change in mean ZOI for the biofilm-derived clones relative to the ancestor. We observed the evolution of statistically significant differences in antibiotic resistance in biofilms (one-way MANOVA across all levels of biofilm replicate × time, Wilks’ = 0.016, P < 0.0001; Figure
figr fid F1 1), with clones that were more sensitive or more resistant appearing independently in each of our replicates (Figure
F2 2; see Additional file
supplr sid S1 1: Figure S1 for evidence that this variation is heritable, and Additional file
1: Table S1 for an analysis of correlations across different antibiotics). The data used for the analysis was formatted to create a balanced design matrix. Using a set of nine planned contrasts, we found significant changes in the mean evolved resistance for several antibiotics through time (Table
T2 2). Many evolved clones also showed increased susceptibility to antibiotics. Although resistant clones were uncommon in our experiments, when they appeared in evolved biofilms, they did so at notable frequencies (Figure
2). For some combinations of antibiotics and sampling times, multiple samples from evolved biofilms showed higher variability than seen among multiple samples from the ancestral clone (Figure
F3 3). These findings support hypotheses 1 and 2; genetic variation in levels of resistance to antibiotics evolves during biofilm development in the absence of antibiotics, and this variation includes both resistant and sensitive clones. There was no evidence of increased variation through time in our data (hypothesis 3; linear regression of total multivariate phenotypic variation [disparity] among clones vs. biofilm age, P > 0.05; number of resistant or sensitive clones vs. biofilm age, P > 0.05).
suppl
Additional file 1: Figure S1.
text
Analysis of the heritability of the resistance phenotype across clones. If the phenotype is stably inherited, then it would be expected that across all treatments, the two cultures would show the same resistance phenotype (i.e. a difference in mean ZOI diameter of 0) despite experiencing slightly different growth. The figure below depicts the histogram of the difference in the mean resistance phenotype (diameter of ZOI) between two independent overnight cultures for each clone, across all treatments. The mean difference was not significantly different from 0 [mean = -0.035, P = 0.52, n = 3147, confidence interval for the mean = (-1.07, 0.94)], which strongly suggests that the diversity in resistance phenotypes is due to heritable changes. Table S1. Spearman rank correlations of antibiotic resistance across different antibiotics (see Additional file 1: Table S1 for abbreviations). Correlations were calculated across all individual clones pooled across time intervals (n = 90; 3 replicates x 10 clones / replicate x 3 time points). Significant (p < 0.05) correlations are noted, with P < 0.05, ** P < 0.01, *** P < 0.001.
file name 1471-2148-13-22-S1.doc
Click here for file
fig Figure 1Mean diameter (in pixels) of the zone of inhibition (ZOI), a measure of antibiotic resistance, across ancestor (time zero) and bacteria isolated from biofilms at 15, 30, and 60 days
Mean diameter (in pixels) of the zone of inhibition (ZOI), a measure of antibiotic resistance, across ancestor (time zero) and bacteria isolated from biofilms at 15, 30, and 60 days. Individual replicates appear as distinct colors connected with a line. The ZOI of the ancestor is plotted at time 0 as an open circle.
graphic 1471-2148-13-22-1
Figure 2Raw data for zone of inhibition, a measure of antibiotic resistance, across ancestor (time zero) and bacteria isolated from biofilms at 15, 30, and 60 days
Raw data for zone of inhibition, a measure of antibiotic resistance, across ancestor (time zero) and bacteria isolated from biofilms at 15, 30, and 60 days. Individual clones appear as dots. Red or green squares denote sensitive and resistant forms, respectively, determined as datapoints that are more than two standard deviations above or below the mean. Means for each replicate are marked with black bars and overall means connected with a dotted line. Antibiotics in the same class are followed by matching symbols.
1471-2148-13-22-2
Table 2
Results of planned contrasts following one-way MANOVA on mean ZOI across biofilm replicates and time
Contrast
Antibiotics that differ significantly
Symbols denote direction of change: ↓ = smaller ZOI for latter group, ↑ = larger ZOI for latter group.
Ancestor vs. 15 days
CFP75↓, PB300↓
Ancestor vs. 30 days
CFP75↓, GM10↓, PB300↓, SAM20↓, TE30↓
Ancestor vs. 60 days
none
15 days vs. 30 days
GM10↑
15 days vs. 60 days
CIP5↓, E15↓, GM10↓, K30↓, NA30↓, PB300↓, S10↓, TE30↓
30 days vs. 60 days
CIP5↓, GM10↓, K30↓, PB300↓, S10↓, SAM20↓, TE30↓
Biofilm 1 vs. biofilm 2
none
Biofilm 1 vs. biofilm 3
PB300↑
Biofilm 2 vs. biofilm 3
none
Figure 3Standard deviation (in pixels) of the diameters of zones of inhibition (ZOI) across ancestor (time zero) and bacteria isolated from biofilms at 15, 30, and 60 days
Standard deviation (in pixels) of the diameters of zones of inhibition (ZOI) across ancestor (time zero) and bacteria isolated from biofilms at 15, 30, and 60 days. Individual replicates appear as distinct colors connected with a line. The variance across ZOI measurements of the ancestor is plotted at time 0 as an open circle.
1471-2148-13-22-3
Our results suggest that antibiotic resistance and susceptibility can rapidly evolve in biofilms over relatively short time scales (<15 days), which begs the question of how these rates of mutation accumulation compare to those in well-mixed liquid cultures that support exponential growth. Such a comparison is difficult because estimating the “mutation rate” in the spatially structured bacterial cells of biofilms is problematic. Mutation rates are almost always calculated and compared on a “per-generation” basis (e.g.
B35 35
B36 36
), but rates of bacterial cell division in biofilms vary widely depending on location within the biofilm matrix. This variation in cellular growth rates is a consequence of nutrient depletion and the creation of strong gradients of substrates, electron acceptors and other resources within the spatially structured environment of biofilms
B37 37
B38 38
. These gradients cause growth rates to vary tremendously within biofilms, such that cells deep within the biofilm matrix may not divide at all
B39 39
. Because of this, mutation frequency cannot be expressed in the same terms, i.e., per generation, as in well-mixed liquid cultures; nor can one calculate a meaningful population-wide average growth rate for cells in biofilms. One can imagine applying models that account for differential growth in biofilms (e.g.,
B40 40
), and then using current data to calculate mutation rates that can be compared to rates in well-mixed cultures. However, such calculations require data about mutation rates in in non-growing bacterial cells that is largely lacking, so direct and simple comparisons between biofilms and well-mixed cultures are not possible at this time.
The evolution of antibiotic resistance and susceptibility in bacterial biofilms involves the interaction between mutation, selection, genetic drift, and spatial structure
26
40
. The data presented here cannot determine the importance of these multiple explanatory factors. It seems likely that evolution in biofilms typically occurs under conditions contrary to what is typically assumed in standard population genetics theory (e.g. strong selection and weak mutation) and rather involves strong mutational mechanisms typical in bacteria under stress
B41 41
coupled with weak selection (see also
26
). Future work combining spatially explicit models for biofilm growth (e.g.
40
B42 42
) with model-based estimates of mutation rates and effect sizes for bacteria (e.g.
B43 43
) would provide more insight into the details of evolution in biofilms.
Conclusions
These data show the rapid de novo evolution of heritable variation in antibiotic sensitivity and resistance during E. coli biofilm development. We suggest that evolutionary processes, whether genetic drift or natural selection, should be considered as a factor to explain the elevated tolerance to antibiotics typically observed in bacterial biofilms. We do not yet know whether evolution of antibiotic resistance requires high rates of mutation as can arise in biofilms (e.g.
B44 44
) or can be explained by normal mutation rates in bacteria. In either case, biofilms quickly evolve high levels of variation in antibiotic resistance. We hypothesize that rare, highly resistant variants may allow biofilms to regrow following antibiotic treatment. This mechanism is an important potential explanation for why biofilm populations are, in general, highly resistant to antibiotic treatment.
Methods
Strain, media and growth conditions
Bacterial biofilms were grown as described by Ponciano et al.
26
. Escherichia coli K12 MG1655 was grown in minimal salts media (M9) augmented with vitamins and trace elements with 0.05% glucose as the carbon source. The inoculum for flow cells was prepared by inoculating 10 ml of minimal medium with a scraping from a -80°C freezer stock and incubating the culture for 24 h at 37°C. Biofilms were cultured in flow-cells that had been sterilized by flowing 5% bleach for >24 h, followed by rinsing with minimal medium for 24 h. A 100 ul inoculum was introduced to each flow cell using a sterile syringe and needle. Bacterial cells were allowed to settle for 6 h before the flow was restarted (with a mean hydraulic retention time of 2.5 h). The biofilms were cultured for 15, 30 or 60 days prior to sampling them through a port on the upper surface of the flow-cell using a syringe and needle. Each sample was vortexed for 1 minute, then serially diluted in saline and plated on minimal medium solidified with agar. Ten randomly chosen clones were obtained from each of three replicate biofilms sampled at four times: 0, 15, 30 or 60 days. The 0d samples are referred to as “ancestors”. All clones were grown overnight in minimal medium and archived as glycerol stock cultures at -80°C.
Antibiotic sensitivity
We determined the sensitivity of ancestral and biofilm clones (15, 30 and 60 days old) to 12 antibiotics using the Kirby-Bauer disk method. The antibiotics (Table
1) were selected to target a range of cellular processes. Individual clones were grown in minimal medium for 24 h (final optical density at 600 nm = 0.15-0.2) and spread on Mueller-Hinton agar using sterile cotton swabs to form a lawn. After allowing the plate to dry for about 10 minutes, antibiotic-infused disks (Sensi-Disks, BD, New Jersey) were placed on the plates, which were then incubated for 18 h at 37°C. We photographed plates from a standard distance and measured the zones of (growth) inhibition (ZOI) for each antibiotic disk using ImageJ software available for download from NIH (http://rsbweb.nih.gov/ij/).
Antibiotic resistance was quantified as the diameter (in pixels) of the ZOI around the antibiotic-infused disks. Susceptible clones had relatively larger ZOI, while resistant clones had relatively smaller ZOI. For each bacterial clone, we replicated the resistance score for each antibiotic three times by growing three independent cultures from the frozen stock of that clone. For each independent replicate, we used the mean ZOI from two antibiotic disks. For each antibiotic disk, we scored the ZOI as the mean of three arbitrarily drawn diameters across the ZOI. Thus, each resistance score represents a mean of 3 × 2 × 3 = 18 individual measurements. Finally, at each time point we measured two replicates of the ancestor as a control. At each sampling time we standardized scores by dividing each by the mean score of the control to reduce variation introduced by day-to-day fluctuations in media (i.e., agar thickness, dryness, concentration, etc.).
Analysis
To test the hypothesis that heritable variation for antibiotic resistance arose during biofilm development, we carried out a one-way MANOVA across all biofilms and time points simultaneously (Table
1). This MANOVA used ZOI diameter across all antibiotics as a response variable, and a concatenated variable of biofilm identity and time as predictor variable (the 10 levels of the predictor variable were then: ancestral line at 0 days, Biofilm replicate 1 at 15, 30, and 60 days, Biofilm replicate 2 at 15, 30, and 60 days, and biofilm replicate 3 at 15, 30, and 60 days). We also subjected these data to a set of nine planned contrasts (all paired comparisons of the ancestral population and all biofilms from 15, 30, and 60 days, as well as all paired comparisons between the three biofilm replicates; see Table
2). To account for an inflated Type I error associated with multiple comparisons, we computed the conservative simultaneous confidence intervals for each contrast
B45 45
.
We identified sensitive and resistant forms, respectively, as clones whose mean ZOI was more than two standard deviations above or below the mean of the ancestor. To test for increasing variation through time, we used linear regression to compare both total multivariate phenotypic variation [disparity] among clones and the number of resistant or sensitive clones to biofilm age.
All analyses were conducted using R (version 2.12.2
B46 46
).
Competing interests
The authors declare no competing interests.
Authors’ contributions
JGT, PJ, LJF, and LJH designed the study; JGT collected the data; JGT and JMP analyzed and interpreted results; and JGT, JMP, LJF, and LJH wrote the paper. All authors read and approved the final manuscript.
bm
ack
Acknowledgements
We thank A. Spangler and M. Yarger for technical assistance, and H.J. La for advice on cultivation of biofilms. This work was supported by grant P20 RR16448 from the National Center for Research Resources of the National Institutes of Heath and NSF DEB-0919499.
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RESEARCHARTICLEOpenAccessTheevolutionofantibioticsusceptibilityand resistanceduringtheformationof Escherichiacoli biofilmsintheabsenceofantibioticsJabusGTyerman1,2,6 †,JosMPonciano3 †,PaulJoyce2,4,5,LarryJForney1,2andLukeJHarmon1,2*AbstractBackground: Explanationsforbacterialbiofilmpersistenceduringantibiotictreatmenttypicallydependon non-geneticmechanisms,andrarelyconsiderthecontributionofevolutionaryprocesses. Results: Using Escherichiacoli biofilms,wedemonstratethatheritablevariationforbroad-spectrumantibiotic resistancecanariseandaccumulaterapidlyduringbiofilmdevelopment,evenintheabsenceofantibioticselection. Conclusions: Ourresultsdemonstratetherapid denovo evolutionofheritablevariationinantibioticsensitivityand resistanceduring E.coli biofilmdevelopment.Wesuggestthatevolutionaryprocesses,whethergeneticdriftor naturalselection,shouldbeconsideredasafactortoexplaintheelevatedtolerancetoantibioticstypicallyobserved inbacterialbiofilms.Thiscouldbeanunder-appreciatedmechanismthataccountswhybiofilmpopulationsare,in general,highlyresistanttoantibiotictreatment. Keywords: Evolution,Antibioticresistance,Bacterialbiofilms,Mutations,DiversityBackgroundBacteriathatformbiofilmshavebeenshowntobehighly resistanttoantimicrobialtherapy[1-3]andcontributeto thechronicnatureofmanybacterialinfectionsinhumans becausecellsinbiofilmsarehighlyresistanttoantibiotic treatment(e.g.[4,5]).Developingeffectivetreatmentsfor biofilm-relatedinfectionsrequiresanunderstandingofthe processesthatleadbiofilmstopersistinthefaceofantimicrobialtreatment[6]. Therearemultiplehypothesestoexplainbiofilmpersistenceduringantibiotictreatment[7-10].Physicalfactors, likediffusionlimitation,maypreventantibioticconcentrationsfromreachinginhibitoryorlethallevelswithin biofilms[11,12].However,severalstudiesreportbiofilm persistencedespitesubstantialantibioticdiffusion(e.g. [13,14],reviewedin[1,15]).Anotherhypothesisposits thatnon-geneticphenotypicheterogeneity,includingthe plasticexpressionofphenotypesthatareresistanttoantibiotics,mayoccurinbiofilms.Forexample,resource gradientsmayleadcellstoexperiencedifferentmicroenvironmentsandthusexpressdistinctphenotypesin differentpartsofabiofilm[1,9].Inparticular,a “ persister ” phenotypehasbeenhypothesizedtoariseinbiofilmsand provideimmunityagainstantibiotics[16].Thesepersister cellsarepostulatedtohavetheabilitytoreconstitute biofilmsuponreleasefromantibioticthreat[16-19]. Alternatively,bacteriaculturedasbiofilmsmayevolve heritablevariationforresistancetoantibiotics denovo [7].Weknowthatevolutionarychangecanoccurrapidly withintenstohundredsofgenerations[20],whichare timescalesrelevanttomedicaltreatmentofinfectious diseases[21].Furthermore,bacteriainbiofilmshave hugepopulationsizessothatmanynewmutationswill ariseoverrelativelyshorttimescales.Itispossiblethat antibioticresistancemightariseinbacterialbiofilms throughstraightforwardpopulationgeneticprocesses. Wesuggestthat,givenenoughtime,variationinantibiotic resistancemayariseinbiofilmsevenintheabsenceof antibioticselection.Thiscouldhappenduetotheaccumulationofneutralvariationorasaresultofselectionfor *Correspondence: lukeh@uidaho.edu†Equalcontributors1DepartmentofBiologicalSciences,UniversityofIdaho,CampusBox3051, Moscow,ID83843,USA2InitiativeforBioinformaticsandEvolutionaryStudies(IBEST),Universityof Idaho,Moscow,ID83844,USA Fulllistofauthorinformationisavailableattheendofthearticle 2013Tyermanetal.;licenseeBioMedCentralLtd.ThisisanOpenAccessarticledistributedunderthetermsoftheCreative CommonsAttributionLicense(http://creativecommons.org/licenses/by/2.0),whichpermitsunrestricteduse,distribution,and reproductioninanymedium,providedtheoriginalworkisproperlycited.Tyerman etal.BMCEvolutionaryBiology 2013, 13 :22 http://www.biomedcentral.com/1471-2148/13/22

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phenotypesthatbyhappenstancearecorrelatedwithantibioticresistance(e.g.[22]). Evolutionarychangeinbiofilmsisplausiblesincerecent studieshaveshowntremendousphenotypicvariation amongcellsisolatedfrombiofilmsgrowinginpatients [23-25]anddemonstratedheritablevariationintraits withinexperimentallyculturedbiofilmpopulations[26-32]. However,fewhypothesesaboutantibioticresistanceinbiofilmsinvokeevolutionarychangeasanalternativeexplanationforbiofilmpersistenceduringantibiotictreatment (butsee[7,8,27]).Evolutioncouldinvolvemutationsthat conveyresistancetosingleantibiotics(specializedresistance)ortowholesuitesofantibiotics(broad-spectrum resistance[8]).Theoccurrenceofvariantsresistanttoantibioticsmayprovidean “ insuranceeffect ” [30,32,33]by creatingsubpopulationsofcellsthatcansurviveoreven proliferateshouldthebiofilmcomeunderantibioticassault.Resistantvariantscouldthusfacilitatereconstitution ofbacterialbiofilmpopulationsfollowingcessationofantibiotictreatment. Documentingwhethergeneticvariationforantibiotic resistancearisesduringthecourseofbiofilmdevelopmentisanimportantfirststeptoexploringbiofilm persistenceinthefaceofantibiotictreatment.Aswe suggest,evolutionaryexplanationspredictthatgenetic variationinthesusceptibilitytoantibioticswillarisein biofilms,andthatthefrequencyofantibioticresistant cellswillincreasethroughtime.Herewedemonstrate therapidevolutionofheritablevariationforbroadspectrumantibioticresistanceduringthecourseof biofilmdevelopmentby E.coli .Wetestedthreehypothesesinthiswork:(1)heritablevariationforantibiotic resistanceevolvesduringbiofilmdevelopment;(2)this variationincludesbothresistantandsusceptiblemutants toarangeofantibiotics;and(3)phenotypicvariationin biofilmsincreasesthroughtime.Wefoundevidencefor both(1)and(2)butnot(3).Variationinantibioticresistanceemergedwithin15daysofbiofilmgrowth,atime framethatisconsistentwithmanycommonbacterial infections.Thus,thesefindingshaveimportantimplicationsforthedevelopmentoftreatmentsforbacteriathat formbiofilmsduringinfection.ResultsanddiscussionWecultured Escherichiacoli K12MG1655asbiofilmsin theabsenceofantibiotics.Briefly,weinoculated E.coli into flow-cellsandculturedbiofilmsusingminimalmedium withglucoseasasolecarbonsource.Wesampledbiofilm populationsat15,30and60daysandisolatedtenbacterial clonesfromthreereplicateflowcellsateachtimepoint. UsingtheKirby-Bauerdiscdiffusionmethod[34],wecharacterizedeachbacterialcloneforresistancetotwelveantibioticsbymeasuringthediametersofzonesof(growth) inhibition(ZOI)foreachcloneoneachantibiotic(Table1; seedetailedmethodsbelow). Wetestedwhetherheritablevariationforantibiotic resistanceevolvedduringbiofilmdevelopmentbyassessingchangeinmeanZOIforthebiofilm-derivedclones relativetotheancestor.Weobservedtheevolutionof statisticallysignificantdifferencesinantibioticresistance inbiofilms(one-wayMANOVAacrossalllevelsof biofilmreplicatetime,Wilks ’ =0.016,P<0.0001; Figure1),withclonesthatweremoresensitiveormore resistantappearingindependentlyineachofourreplicates(Figure2;seeAdditionalfile1:FigureS1for evidencethatthisvariationisheritable,andAdditional file1:TableS1forananalysisofcorrelationsacrossdifferentantibiotics).Thedatausedfortheanalysiswas formattedtocreateabalanceddesignmatrix.Usinga setofnineplannedcontrasts,wefoundsignificant changesinthemeanevolvedresistanceforseveralantibioticsthroughtime(Table2).Manyevolvedclonesalso showedincreasedsusceptibilitytoantibiotics.Although resistantcloneswereuncommoninourexperiments, whentheyappearedinevolvedbiofilms,theydidsoat notablefrequencies(Figure2).Forsomecombinations ofantibioticsandsamplingtimes,multiplesamplesfrom evolvedbiofilmsshowedhighervariabilitythanseen amongmultiplesamplesfromtheancestralclone (Figure3).Thesefindingssupporthypotheses1and2; geneticvariationinlevelsofresistancetoantibiotics evolvesduringbiofilmdevelopmentintheabsenceof antibiotics,andthisvariationincludesbothresistantand sensitiveclones.Therewasnoevidenceofincreasedvariationthroughtimeinourdata(hypothesis3;linearregressionoftotalmultivariatephenotypicvariation[disparity] amongclonesvs.biofilmage,P>0.05;numberofresistant orsensitiveclonesvs.biofilmage,P>0.05). Table1SummaryoftheantibioticsusedinthisstudyAntibioticclassAntibioticAbbreviation1AminoglycosideStreptomycinS10 GentamicinGM10 KanamycinK30 QuinoloneNaladixicacidNA30 CiprozoneCIP5 Beta-lactamAmpicillinwith Sulbactam SAM20 CefoperazoneCFP75 Semi-synthetic (rifamycingroup) RifampinRA5 CationicbasicproteinPolymyxinBPB300 MacrolideErythromycinE15 GlycopeptideVancomycinVA30 PolyketideTetracyclineTE301BasedonSensi-disksfromBD.Numbersfollowinglettersindicateugof antibioticappliedtoeachdisk.Tyerman etal.BMCEvolutionaryBiology 2013, 13 :22 Page2of7 http://www.biomedcentral.com/1471-2148/13/22

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Ourresultssuggestthatantib ioticresistanceandsusceptibilitycanrapidlyevolveinbiofilmsoverrelativelyshort timescales(<15days),whichbegsthequestionofhow theseratesofmutationaccumulationcomparetothosein well-mixedliquidculturestha tsupportexponentialgrowth. Suchacomparisonisdifficultbecauseestimatingthe “ mutationrate ” inthespatiallystructuredbacterialcellsofbiofilmsisproblematic.Mutationratesarealmostalways calculatedandcomparedona “ per-generation ” basis(e.g. [35,36]),butratesofbacterial celldivisioninbiofilmsvary widelydependingonlocationwithinthebiofilmmatrix. Thisvariationincellulargrowthratesisaconsequenceof nutrientdepletionandthecreationofstronggradientsof substrates,electronacceptor sandotherresourceswithin thespatiallystructuredenvi ronmentofbiofilms[37,38]. Thesegradientscausegrowthratestovarytremendously withinbiofilms,suchthatcellsdeepwithinthebiofilm matrixmaynotdivideatall[39].Becauseofthis,mutation frequencycannotbeexpressedinthesameterms,i.e.,per generation,asinwell-mixedliquidcultures;norcanone calculateameaningfulpopulation-wideaveragegrowthrate forcellsinbiofilms.Onecanimagineapplyingmodelsthat accountfordifferentialgrowthinbiofilms(e.g.,[40]),and thenusingcurrentdatatocalculatemutationratesthatcan becomparedtoratesinwell-mixedcultures.However,such calculationsrequiredataaboutmutationratesininnongrowingbacterialcellsthatis largelylacking,sodirectand simplecomparisonsbetweenbiofilmsandwell-mixedculturesarenotpossibleatthistime. Theevolutionofantibioticresistanceandsusceptibilityin bacterialbiofilmsinvolvest heinteractionbetweenmutation,selection,geneticdrift, andspatialstructure[26,40]. Thedatapresentedherecannotdeterminetheimportance ofthesemultipleexplanatoryfactors.Itseemslikelythat evolutioninbiofilmstypicallyoccursunderconditionscontrarytowhatistypicallyassumedinstandardpopulation geneticstheory(e.g.strongselectionandweakmutation) andratherinvolvesstrongmutationalmechanismstypical 15304560 195205215 CefoperazoneTime (days)Mean Diameter (pixels) 15304560 205215 CiprozoneTime (days)Mean Diameter (pixels) 15304560 5565 ErythromycinTime (days)Mean Diameter (pixels) 15304560 135 145 GentamicinTime (days)Mean Diameter (pixels) 15304560 135145 KanamycinTime (days)Mean Diameter (pixels) 15304560 154 160166 Naladixic acidTime (days)Mean Diameter (pixels) 15304560 909498104 Polymyxin BTime (days)Mean Diameter (pixels) 15304560 60 657075 RifampicinTime (days)Mean Diameter (pixels) 15304560 110120 StreptopmycinTime (da y s)Mean Diameter (pixels) 15304560 145 155 AmpicillinTime (da y s)Mean Diameter (pixels) 15304560 145155 TetracyclineTime (da y s)Mean Diameter (pixels) 15304560 465054 58 VancomycinTime (da y s)Mean Diameter (pixels) Figure1 Meandiameter(inpixels)ofthezoneofinhibition(ZOI),ameasureofantibioticresistance,acrossancestor(timezero)and bacteriaisolatedfrombiofilmsat15,30,and60days. Individualreplicatesappearasdistinctcolorsconnectedwithaline.TheZOIofthe ancestorisplottedattime0asanopencircle. Tyerman etal.BMCEvolutionaryBiology 2013, 13 :22 Page3of7 http://www.biomedcentral.com/1471-2148/13/22

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inbacteriaunderstress[41]coupledwithweakselection (seealso[26]).Futureworkco mbiningspatiallyexplicit modelsforbiofilmgrowth(e.g.[40,42])withmodel-based estimatesofmutationratesandeffectsizesforbacteria(e.g. [43])wouldprovidemoreinsightintothedetailsofevolutioninbiofilms.ConclusionsThesedatashowtherapid denovo evolutionofheritable variationinantibioticsensitivityandresistanceduring E. coli biofilmdevelopment.Wesuggestthatevolutionary processes,whethergeneticdriftornaturalselection, shouldbeconsideredasafactortoexplaintheelevated tolerancetoantibioticstypicallyobservedinbacterialbiofilms.Wedonotyetknowwhetherevolutionofantibiotic resistancerequireshighratesofmutationascanarisein biofilms(e.g.[44])orcanbeexplainedbynormalmutationratesinbacteria.Ineithercase,biofilmsquickly evolvehighlevelsofvariationinantibioticresistance.We hypothesizethatrare,highlyresistantvariantsmayallow biofilmstoregrowfollowingantibiotictreatment.This mechanismisanimportantpotentialexplanationforwhy biofilmpopulationsare,ingeneral,highlyresistanttoantibiotictreatment. 0.9 1.1 1.0RifampinZone of Inhibition (pixels, relative scale) 0.9 1.1 1.0Polymyxin B0.9 1.1 1.0Erythromycin 0.9 1.1 1.0Vancomycin 0.9 1.1 1.0Streptomycin Naladixic acid0.9 1.1 1.0 Cefoperazone0.9 1.1 1.0 Ciprozone0.9 1.1 1.0 Kanamycin0.9 1.1 1.0 Ampicillin0.9 1.1 1.0 Gentamicin0.9 1.1 1.0 Tetracycline0.9 1.1 1.0Time (days) 0153060 0153060 0153060 0153060 Figure2 Rawdataforzoneofinhibition,ameasureofantibioticresistance,acrossancestor(timezero)andbacteriaisolatedfrom biofilmsat15,30,and60days. Individualclonesappearasdots.Redorgreensquaresdenotesensitiveandresistantforms,respectively, determinedasdatapointsthataremorethantwostandarddeviationsaboveorbelowthemean.Meansforeachreplicatearemarkedwithblack barsandoverallmeansconnectedwithadottedline.Antibioticsinthesameclassarefollowedbymatchingsymbols. Tyerman etal.BMCEvolutionaryBiology 2013, 13 :22 Page4of7 http://www.biomedcentral.com/1471-2148/13/22

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MethodsStrain,mediaandgrowthconditionsBacterialbiofilmsweregrownasdescribedbyPonciano etal. [26]. Escherichiacoli K12MG1655wasgrownin minimalsaltsmedia(M9)augmentedwithvitaminsand traceelementswith0.05%glucoseasthecarbonsource. Theinoculumforflowcellswaspreparedbyinoculating 10mlofminimalmediumwithascrapingfroma-80C freezerstockandincubatingtheculturefor24hat37C. Biofilmswereculturedinflow-cellsthathadbeen Table2Resultsofplannedcontrastsfollowingone-wayMANOVAonmeanZOIacrossbiofilmreplicatesandtimeContrast Antibioticsthatdiffersignificantly Ancestorvs.15daysCFP75 ,PB300 Ancestorvs.30daysCFP75 ,GM10 ,PB300 ,SAM20 ,TE30 Ancestorvs.60daysnone 15daysvs.30daysGM10 15daysvs.60daysCIP5 ,E15 ,GM10 ,K30 ,NA30 ,PB300 ,S10 ,TE30 30daysvs.60daysCIP5 ,GM10 ,K30 ,PB300 ,S10 ,SAM20 ,TE30 Biofilm1vs.biofilm2none Biofilm1vs.biofilm3PB300 Biofilm2vs.biofilm3noneSymbolsdenotedirectionofchange: =smallerZOIforlattergroup, =largerZOIforlattergroup. 15304560 81216 CefoperazoneTime (days)Diameter Std. Dev. (pixels) 15304560 6 8 12 CiprozoneTime (days)Diameter Std. Dev. (pixels) 15304560 4 8 12 ErythromycinTime (days)Diameter Std. Dev. (pixels) 15304560 46812 GentamicinTime (days)Diameter Std. Dev. (pixels) 15304560 46812 KanamycinTime (days)Diameter Std. Dev. (pixels) 15304560 246 8 Naladixic acidTime (days)Diameter Std. Dev. (pixels) 15304560 02468 Polymyxin BTime (days)Diameter Std. Dev. (pixels) 15304560 4 812 RifampicinTime (days)Diameter Std. Dev. (pixels) 15304560 4 812 StreptopmycinTime ( da y s ) Diameter Std. Dev. (pixels) 15304560 46812 AmpicillinTime ( da y s ) Diameter Std. Dev. (pixels) 15304560 2468 TetracyclineTime ( da y s ) Diameter Std. Dev. (pixels) 15304560 05 10 VancomycinTime ( da y s ) Diameter Std. Dev. (pixels) Figure3 Standarddeviation(inpixels)ofthediametersofzonesofinhibition(ZOI)acrossancestor(timezero)andbacteriaisolated frombiofilmsat15,30,and60days. Individualreplicatesappearasdistinctcolorsconnectedwithaline.ThevarianceacrossZOI measurementsoftheancestorisplottedattime0asanopencircle. Tyerman etal.BMCEvolutionaryBiology 2013, 13 :22 Page5of7 http://www.biomedcentral.com/1471-2148/13/22

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sterilizedbyflowing5%bleachfor>24h,followedbyrinsingwithminimalmediumfor24h.A100ulinoculum wasintroducedtoeachflowcellusingasterilesyringe andneedle.Bacterialcellswereallowedtosettlefor6h beforetheflowwasrestarted(withameanhydraulicretentiontimeof2.5h).Thebiofilmswereculturedfor15, 30or60dayspriortosamplingthemthroughaporton theuppersurfaceoftheflow-cellusingasyringeandneedle.Eachsamplewasvortexedfor1minute,thenserially dilutedinsalineandplatedonminimalmediumsolidified withagar.Tenrandomlychosencloneswereobtainedfrom eachofthreereplicatebiofilmssampledatfourtimes:0,15, 30or60days.The0dsamplesarereferredtoas “ ancestors ” .Allclonesweregrownovernightinminimalmedium andarchivedasglycerolstockculturesat-80C.AntibioticsensitivityWedeterminedthesensitivityofancestralandbiofilm clones(15,30and60daysold)to12antibioticsusingthe Kirby-Bauerdiskmethod.Theantibiotics(Table1)were selectedtotargetarangeofcellularprocesses.Individual clonesweregrowninminimalmediumfor24h(finalopticaldensityat600nm=0.15-0.2)andspreadonMuellerHintonagarusingsterilecottonswabstoformalawn. Afterallowingtheplatetodryforabout10minutes, antibiotic-infuseddisks(Sensi-Disks,BD,NewJersey)were placedontheplates,whichwerethenincubatedfor18hat 37C.Wephotographedplates fromastandarddistance andmeasuredthezonesof(growth)inhibition(ZOI)for eachantibioticdiskusingImageJsoftwareavailablefor downloadfromNIH(http://rsbweb.nih.gov/ij/). Antibioticresistancewasquantifiedasthediameter (inpixels)oftheZOIaroundtheantibiotic-infused disks.SusceptiblecloneshadrelativelylargerZOI,while resistantcloneshadrelativelysmallerZOI.Foreachbacterialclone,wereplicatedtheresistancescoreforeach antibioticthreetimesbygrowingthreeindependentculturesfromthefrozenstockofthatclone.Foreachindependentreplicate,weusedthemeanZOIfromtwo antibioticdisks.Foreachantibioticdisk,wescoredthe ZOIasthemeanofthreearbitrarilydrawndiameters acrosstheZOI.Thus,eachresistancescorerepresentsa meanof323=18individualmeasurements.Finally, ateachtimepointwemeasuredtworeplicatesoftheancestorasacontrol.Ateachsamplingtimewestandardizedscoresbydividingeachbythemeanscoreofthe controltoreducevariationintroducedbyday-to-day fluctuationsinmedia(i.e.,agarthickness,dryness,concentration,etc.).AnalysisTotestthehypothesisthatherit ablevariationforantibiotic resistancearoseduringbiofilmdevelopment,wecarried outaone-wayMANOVAacrossallbiofilmsandtime pointssimultaneously(Table1).ThisMANOVAusedZOI diameteracrossallantibioticsasaresponsevariable,anda concatenatedvariableofbiofilmidentityandtimeaspredictorvariable(the10levelsofthepredictorvariablewere then:ancestrallineat0days,B iofilmreplicate1at15,30, and60days,Biofilmreplicate2at15,30,and60days,and biofilmreplicate3at15,30,and60days).Wealsosubjectedthesedatatoasetofnineplannedcontrasts(all pairedcomparisonsoftheancestralpopulationandallbiofilmsfrom15,30,and60days,aswellasallpairedcomparisonsbetweenthethreebiofilmreplicates;seeTable2).To accountforaninflatedTypeI errorassociatedwithmultiplecomparisons,wecomputedtheconservativesimultaneousconfidenceintervalsforeachcontrast[45]. Weidentifiedsensitiveandresistantforms,respectively,ascloneswhosemeanZOIwasmorethantwo standarddeviationsaboveorbelowthemeanoftheancestor.Totestforincreasingvariationthroughtime,we usedlinearregressiontocomparebothtotalmultivariate phenotypicvariation[disparity]amongclonesandthe numberofresistantorsensitiveclonestobiofilmage. AllanalyseswereconductedusingR(version2.12.2[46]).AdditionalfileAdditionalfile1:FigureS1. Analysisoftheheritabilityofthe resistancephenotypeacrossclones.Ifthephenotypeisstablyinherited, thenitwouldbeexpectedthatacrossalltreatments,thetwocultures wouldshowthesameresistancephenotype(i.e.adifferenceinmean ZOIdiameterof0)despiteexperiencingslightlydifferentgrowth.The figurebelowdepictsthehistogramofthedifferenceinthemean resistancephenotype(diameterofZOI)betweentwoindependent overnightculturesforeachclone,acrossalltreatments.Themean differencewasnotsignificantlydifferentfrom0[mean=-0.035,P=0.52, n=3147,confidenceintervalforthemean=(-1.07,0.94)],whichstrongly suggeststhatthediversityinresistancephenotypesisduetoheritable changes. TableS1. Spearmanrankcorrelationsofantibioticresistance acrossdifferentantibiotics(seeAdditionalfile1:TableS1for abbreviations).Correlationswerecalculatedacrossallindividualclones pooledacrosstimeintervals(n=90;3replicatesx10clones/replicatex 3timepoints).Significant(p<0.05)correlationsarenoted,with *P<0.05,**P<0.01,***P<0.001. Competinginterests Theauthorsdeclarenocompetinginterests. Authors ’ contributions JGT,PJ,LJF,andLJHdesignedthestudy;JGTcollectedthedata;JGTand JMPanalyzedandinterpretedresults;andJGT,JMP,LJF,andLJHwrotethe paper.Allauthorsreadandapprovedthefinalmanuscript. Acknowledgements WethankA.SpanglerandM.Yargerfortechnicalassistance,andH.J.Lafor adviceoncultivationofbiofilms.Researchreportedinthispublicationwas supportedbyanInstitutionalDevelopmentAward(IDeA)toLJFfromthe NationalInstituteofGeneralMedicalSciencesoftheNationalInstitutesof HealthundergrantnumberP20RR16448,agrandfromtheNationalScience Foundation(NSFDEB-0919499),andagrantfromProctor&GambleCo. Authordetails1DepartmentofBiologicalSciences,UniversityofIdaho,CampusBox3051, Moscow,ID83843,USA.2InitiativeforBioinformaticsandEvolutionaryTyerman etal.BMCEvolutionaryBiology 2013, 13 :22 Page6of7 http://www.biomedcentral.com/1471-2148/13/22

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Studies(IBEST),UniversityofIdaho,Moscow,ID83844,USA.3Departmentof Biology,UniversityofFlorida,Gainesville,FL,USA.4Departmentsof Mathematics,UniversityofIdaho,Moscow,Moscow,ID83844,USA.5DepartmentsofStatistics,UniversityofIdaho,Moscow,ID83844,USA.6Currentaddress:Genomatica,Inc.,10520WateridgeCircle,SanDiego,CA 92121,USA. Received:18June2012Accepted:11January2013 Published:28January2013 References1.CostertonJW,StewartPS,GreenbergEP: Bacterialbiofilms:acommon causeofpersistentinfections. Science 1999, 284: 1318 – 1322. 2.CostertonJW: Microbialecologycomesofageandjoinsthegeneral ecologycommunity. ProcNatlAcadSciUSA 2004, 49: 16983 – 16984. 3.FuxCA,CostertonJW,StewartPS,StoodleyP: Survivalstrategiesof infectiousbiofilms. TrendsMicrobiol 2005, 13: 34 – 40. 4.ThomassenMJ,BoxerbaumB,DemkoCA,KuchenbrodPJ,DearbornDG, WoodRE: Inhibitoryeffectofcysticfibrosisserumonpseudomonas phagocytosisbyrabbitandhumanalveolarmacrophages. 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JEvolBiol 2011, 11: 2496 – 2504. 41.TenaillonO,ToupanceB,LeNagardH,TaddeiF,GodelleB: Mutators, populationsize,adaptivelandscapeandtheadaptationofasexual populationsofbacteria. Genetics 1999, 152: 485 – 493. 42.ChangI,GilbertES,EliashbergE,KeaslingJD: Athree-dimensional, stochasticsimulationofbiofilmgrowthandtransport-relatedfactors thataffectstructure. Microbiology2003, 149: 2859 – 2871. 43.PerfeitoL,FernandesL,MotaC,GordoI: AdaptiveMutationsinBacteria: HighRateandSmallEffects. Science 2007, 317: 813 – 815. 44.BarrickJE,YuDS,YoonSH,JeongH,OhTK,SchneiderD,LenskiRE,KimFJ: Genomeevolutionandadaptationinalong-termexperimentwith Escherichiacoli. Nature 2009, 461: 1243 – 1247. 45.JohnsonRA,WichernDW: AppliedMultivariateAnalysis .NewJersey:Prentice Hall;2002. 46.DevelopmentCoreTeamR: R:Alanguageandenvironmentforstatistical computing .Vienna,Austria:RFoundationforStatisticalComputing;2012. URLhttp://www.R-project.org.ISBN3-900051-07-0.doi:10.1186/1471-2148-13-22 Citethisarticleas: Tyerman etal. : Theevolutionofantibiotic susceptibilityandresistanceduringtheformationof Escherichiacoli biofilmsintheabsenceofantibiotics. BMCEvolutionaryBiology 2013 13 :22.Tyerman etal.BMCEvolutionaryBiology 2013, 13 :22 Page7of7 http://www.biomedcentral.com/1471-2148/13/22


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Background
Explanations for bacterial biofilm persistence during antibiotic treatment typically depend on non-genetic mechanisms, and rarely consider the contribution of evolutionary processes.
Results
Using Escherichia coli biofilms, we demonstrate that heritable variation for broad-spectrum antibiotic resistance can arise and accumulate rapidly during biofilm development, even in the absence of antibiotic selection.
Conclusions
Our results demonstrate the rapid de novo evolution of heritable variation in antibiotic sensitivity and resistance during E. coli biofilm development. We suggest that evolutionary processes, whether genetic drift or natural selection, should be considered as a factor to explain the elevated tolerance to antibiotics typically observed in bacterial biofilms. This could be an under-appreciated mechanism that accounts why biofilm populations are, in general, highly resistant to antibiotic treatment.
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Tyerman, Jabus G
Ponciano, José M
Joyce, Paul
Forney, Larry J
Harmon, Luke J
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Appendix 1: Figure S1. Analysis of the heritability of the resistance phenotype across clones. If the phenotype is stably inherited, then it would be expected that across all treatments, the two cultures would show the same resistance phenotype (i.e. a di fference in mean ZOI diameter of 0) despite experiencing slightly different growth. The figure below depicts the histogram of the 5 difference in the mean resistance phenotype (diameter of ZOI) between two independent overnight cultures for each clone, acros s all treatments. The mean difference was not significantly different from 0 [mean = 0.035, P = 0.52, n=3147, confidence interval for the mean = ( 1.07, 0.94)], which strongly suggests that the diversity in resistance phenotypes is due to heritable change s. 10 Table S1. Spearman rank correlations of antibiotic resistance across different antibiotics (see Table S1 for abbreviations). Correlations were calculated across all individual clones pooled

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across time intervals (n = 90; 3 replicates x 10 clones / replicate x 3 time points). Significant (p<0.05) correlations are noted, with P < 0.05, ** P < 0.01, *** P < 0.001. CFP75 CIP5 E15 GM10 K30 NA30 PB300 RA5 S10 SAM2 0 TE3 0 VA3 0 CFP75 CIP5 0.70* E15 0.38 0.34 G M10 0.79** 0.86*** 0.22 K30 0.89*** 0.77** 0.56 0.81** NA30 0.39 0.43 0.62* 0.33 0.56 PB300 0.75** 0.75** 0.34 0.58 0.73** 0.29 RA5 0.73** 0.67* 0.06 0.73** 0.78** 0.35 0.69* S10 0.84** 0.81** 0.21 0.87*** 0.71* 0.32 0.67* 0.69* SAM2 0 0.87*** 0.82** 0.12 0.81** 0.73** 0.25 0.74** 0.69* 0.84** TE30 0.75** 0.76** 0.59* 0.73** 0.82** 0.72* 0.54 0.62* 0.74** 0.62* VA30 0.13 0.31 0.39 0.22 0.04 0 .22 0.04 0.24 0.31 0.13 0.48 5