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Microbiology (2016), 162, 610–621
DOI 10.1099/mic.0.000259
The O-antigen mediates differential survival
of Salmonella against communities of natural
predators
Aletheia Atzinger, Kristen Butela3 and Jeffrey G. Lawrence
Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
Correspondence
Jeffrey G. Lawrence
[email protected]
Antigenically distinct members of bacterial species can be differentially distributed in the
environment. Predators known to consume antigenically distinct prey with different efficiencies
are also differentially distributed. Here we show that antigenically distinct, but otherwise
isogenic and physiologically indistinct, strains of Salmonella enterica show differential survival in
natural soil, sediment and intestinal environments, where they would face a community of
predators. Decline in overall cell numbers is attenuated by factors that inhibit the action of
predators, including heat and antiprotozoal and antihelminthic drugs. Moreover, the fitness of
strains facing these predators – calculated by comparing survival with and without treatments
attenuating predator activity – varies between environments. These results suggest that relative
survival in natural environments is arbitrated by communities of natural predators whose feeding
preferences, if not species composition, vary between environments. These data support the
hypothesis that survival against natural predators may drive the differential distribution of
bacteria among microenvironments.
Received 20 November 2015
Accepted 15 February 2016
INTRODUCTION
Bacteria are dominant members of every ecosystem, their
1030 individuals outnumbering all other cellular life
forms (Whitman et al., 1998). Bacteria are major constituents of soil (Trevors, 2010), sediment (Dale, 1974) and
marine and fresh waters (Watson et al., 1977). In addition,
they colonize both external and internal surfaces of multicellular eukaryotes – where bacterial cells may be 10-fold
more abundant than cells of their host (Human
Microbiome Consortium, 2012) – and serve as intracellular
symbionts to diverse taxa (Baumann, 2005). Turnover of
bacteria in natural environments occurs within days
(Luna et al., 2002; Roszak & Colwell, 1987), indicating
that mortality rates are higher than expected given the
natural rate of senescence (Nyström, 2002, 2007). Major
arbiters of population control are bacteriophages and
amoebae, which limit bacterial population growth in
numerous environments (Jjemba, 2001; Peduzzi &
Schiemer, 2004; Pernthaler, 2005; Rønn et al., 2002);
additional grazers (such as nematodes) may be present as
well (Trevors, 2010).
Many predators (including components of immune
systems) recognize their prey by virtue of the antigenic
3Present address: Division of Natural and Health Sciences, Seton Hill
University, Greensburg, PA, USA.
Four supplementary figures
Supplementary Material.
610
are
available
with
the
online
molecules on the surface of bacterial cells. As the most
abundant molecule on the cell surface, the O-antigen LPS
is a likely candidate used in prey recognition. In enteric
bacteria, LPS is synthesized by enzymes encoded by the
rfb operon; this region is hypervariable among serovars of
Salmonella (Grimont & Weill, 2007). LPS components
are potent activators of immune responses (Reeves,
1995), including the induction of predatory white blood
cells upon systemic infection of a eukaryotic host by
pathogenic bacteria. Therefore, it is not surprising that
the structure of O-antigen polysaccharides is hypervariable
within many species of pathogenic bacteria (Butela &
Lawrence, 2010). Often, frequency-dependent selection
mediated by the host immune system is invoked as a
mechanism maintaining this diversity (Levin et al., 1988;
Yuste et al., 2002). Here, the fitness of a variant allele is
inversely proportional to its frequency, preventing both
the fixation of common alleles and the loss of rare ones.
Yet, diverse O-antigens are also found in species not associated with eukaryotic hosts (Wildschutte et al., 2010).
Predators found in natural environments could serve as
the selective agents for maintaining antigenic diversity in
these cases. In this model, predators in different microenvironments vary in their ability to recognize different
antigenic types, thereby conferring high fitness to genotypes they avoid consuming, but only within their resident
environment. Consistent with this model, diverse
amoebae discriminate among bacterial prey on the basis
of their O-antigen polysaccharides (Wildschutte et al., 2004;
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Differential survival against predator communities
Wildschutte & Lawrence, 2007). Moreover, predators
found in different environments have different feeding preferences (Wildschutte et al., 2004; Wildschutte & Lawrence,
2007). Regardless of their phylogenetic relatedness, predators isolated from the same environment share feeding
preferences (Wildschutte & Lawrence, 2007), so that unrelated predators dwelling in the same environment avoid
consuming the same antigenic classes of prey. A model
was presented whereby these preferences were driven by
molecular mimicry (Wildschutte & Lawrence, 2007).
Here, predators may recognize environmental epitopes
for adhesion; bacterial cells whose antigens resemble these
epitopes would not be recognized as potential prey.
While these results are limited to only a few cultivable
amoebae, they suggest that bacterial strains could outcompete conspecific, but antigenically different, strains in natural environments by virtue of their ability to avoid being
eaten by the communities of resident predators, as opposed
to any physiological or metabolic adaptations they might
carry. This model stands in contrast to those that cite
such physiological traits as the basis for differential distribution of bacterial strains among environments (Gordon
& FitzGibbon, 1999; Gordon & Cowling, 2003; Walk
et al., 2009). We tested this hypothesis by competing
physiologically identical, but antigenically distinct bacteria
within natural environments.
METHODS
Bacteria. Except for strains SARB2 and SARB36, all strains were
derived from Salmonella enterica serovar Typhimurium strain LT2
(Table 1) and in most cases differed from the WT only in carrying a
plasmid expressing a fluorescent protein, and/or having the rfb
operon replaced so that a different O-antigen was made. A deletion of
the rfb operon – D(rfbP-rfbB)3302 – was created by replacing the
region between the gnd and galF genes with the cat chloramphenicol
resistance gene, all within a galE2841 : : aatA hisD9953 : : MudJ
phs-209 : : Tn10dGn background. This parental strain was transduced
to histidine prototrophy using bacteriophage P1 grown on
galE6866 : : aph derivatives of antigenically distinct strains of the
SARB collection (Salmonella Reference Collection B) (Boyd et al.,
1993); these derivatives were created using the method of Butela &
Lawrence (2012). Retention of the upstream phs-209 : : Tn10dGn
marker limited the introduction of DNA from upstream of the his
operon. This strain was back-crossed twice to the parental Drfb-3302
strain, selecting as above, and the galE mutation was repaired via P1
transduction from a Gal+ Drfb strain. The identity of the O-antigen
in the isogenic strains was verified by antibody agglutination tests.
Plasmids pEGFP, pEYFP, pECFP, pDsRed-Express2 and pKAB9
(Lawrence et al., 2013) were introduced by electroporation and
express fluorescent proteins GFP, YFP, CFP, DsRed-Express2 and
mKalama1, respectively.
Media and antibiotics. Bacteria were propagated at 37 uC in LB with
200 mg ml21 ampicillin to maintain plasmids. MacConkey agar
(Difco) was cast with xylose added to 1 % final concentration after
sterilization. Kligler iron agar (Difco) was incubated at 37 uC in a
Forma anaerobic chamber under 85 % N2, 10 % CO2, 5 % H2. For
competitions in natural environments, drugs were added 1 h
before and 24 h after the start of the experiment: metronidazole
(Sigma-Aldrich) was used at 100 mg ml21, tetramisole HCl (SigmaAldrich) at 500 mM, and ivermectin (Sigma-Aldrich) at 20 ng ml21.
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Table 1. Strains of bacteria used
Strain
Genotype
LT2
LD901
LD902
Salmonella enterica Typhimurium LT2
rfb SARB1 DrfcC3303 : : cat pEGFP
rfb SARB1 DrfcC3303 : : cat
pDsRed-Express2
rfb SARB1 DrfcC3303 : : cat pEYFP
rfb SARB1 DrfcC3303 : : cat pKAB9
rfb SARB1 DrfcC3303 : : cat pECFP
rfb SARB52 pEGFP
rfb SARB36 pDsRed-Express2
rfb SARB2 pEYFP
rfb SARB20 pKAB9
rfb SARB30 pCFP
rfb SARB52 pKAB9
rfb SARB36 pEYFP
rfb SARB2 pEGFP
rfb SARB20 pECFP
rfb SARB30 pDsRed-Express2
rfb SARB59 pDsRed-Express2
Salmonella enterica Agona (Xyl2)
Salmonella enterica Newport (Xyl+)
rfb SARB3 phs-209 : : Tn10dGn
rfb SARB4
rfb SARB20 phs-209 : : Tn10dGn
pdu-219 : : Tn10dCm
D(orgC-prgH)4301 : : yfp,zeo pEGFP
LD903
LD904
LD905
LD906
LD907
LD908
LD909
LD910
LD911
LD912
LD913
LD914
LD915
LD917
SARB2
SARB36
HW31
HW19
LD916
O-serotype*
1,4,[5],12
1,4,12
1,4,12
1,4,12
1,4,12
1,4,12
1,9,12
6,8
3,10
8,20
6,7
1,9,12
6,8
3,10
8,20
6,7
1,3,19
1,4,12
6,8
1,4,12
6,7
8,20
*For strains constructed by moving the rfb operon from SARB strains
into strain LT2, O-serotype is designated according to the serotype of
the donor strain.
Propagation of Caenorhabditis elegans. C. elegans strain N2
Bristol was propagated at 22 uC on nematode growth medium
(NGM) plates (Cold Spring Harbor) using Escherichia coli as a feeding
strain. For Salmonella competition, strains were grown overnight in
LB with 0.01 % glucose, rinsed and mixed in equal proportions prior
to spreading 50 ml (*108 c.f.u. total) on NGM plates. An aliquot of
several hundred nematodes was introduced via an agar chunk. Plates
were incubated for 4 days at 22 uC, allowing the nematodes to consume most of the Salmonella lawn. To retrieve remaining Salmonella,
the agar in contact with the introduced piece was discarded and cells
were eluted in 0.9 % NaCl, plated on indicator media and grown at
37 uC to discriminate between the two strains. The high temperature
of incubation prevented growth of eluted C. elegans.
Soil, sediment and fish. Sediment was obtained from Panther
Hollow Lake (40.436883 uN, 79.947188 uW) and Homewood
Cemetery Pond (40.440249 uN, 79.911991 uW); sites were close to
shore but under both leaf litter and *8 feet (2.4 m) of water.
Sediment was filtered through *0.5 mm nylon mesh. Soil was
obtained from the Fruit Room (40.438949 uN, 79.948101 uW) and
Desert Room (40.438535 uN, 79.947509 uW) of the Phipps
Conservatory, Pittsburgh, PA; these areas have had the same plant
species growing in them for many years, and have experienced no
outside animal traffic. Predators were extracted by passing an equal
volume of water through the soil and filtering as above.
Comet goldfish (Carassius auratus) were obtained from Carolina
Biological and propagated for 1 month in a community tank at 30 uC
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A. Atzinger, K. Butela and J. G. Lawrence
until 5–7 cm in length. All animal work was performed in accordance
with approved Institutional Animal Care and Use Committee protocols. Fish were sacrificed by overdose of tricaine methylsulfonate.
Intestinal contents were released into PBS (135 mM NaCl, 2.7 mM
KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4 pH 7.4) and filtered
through nylon mesh. Intestine contents from four fish of approximately equal cumulative mass (*10 g) were pooled. Heat treatment
was performed by submerging 30 ml (soil and sediment extracts) or
7 ml (intestinal contents) aliquots in boiling water for 45 min, cooling
on ice and equilibrating to room temperature.
Competition in complex environments. Overnight cultures of
strains were grown at 37 uC in LB with 200 mg ml21 ampicillin, rinsed
and resuspended in 0.9 % NaCl and then added as a mixture to
environmental samples to a final concentration of 107 cells ml21.
Samples were taken by thoroughly mixing the suspension, removing
2 ml and allowing it to gravity-filter through a 5 mm pore-size mesh.
A 0.012 U aliquot of biotin-conjugated rabbit anti-Salmonella antibody (Gene Tex) was added and the sample was incubated at 4 uC for
30 min. Samples were pelleted at 10 000 g for 5 min, washed in PBS,
pelleted again, and resuspended in an equal volume of PBS before
adding washed beads from the CELLection Biotin Binder kit
(Invitrogen) and following the indirect technique for cell pulldown
recommended by the manufacturer. Samples were fixed in 1 %
paraformaldehyde and stored at 4 uC.
Flow cytometry. The samples were run on a Beckman-Coulter CyAn
ADP flow cytometer with a 0.3 neutral density filter controlled by
Summit 4.3 software (Dako), or on a BD LSRFortessa cell analyser
controlled by BD FACSDiva software (BD Biosciences). SYTO 62
nucleic acid dye (Invitrogen) was added at a final concentration of
50 nM 15 min before cytometry. Flow rate was maintained at
approximately 1000 events s21. Bacteria-only controls were used to
differentiate bacteria from debris and larger cells. Data were analysed
using Ferdinand (Lawrence et al., 2013); Z-scoring was used to reduce
miscounting events that arose from non-bacterial sources (Fig. S1,
available in the online Supplementary Material).
Measuring fitness. Conventional methods for calculating fitness
determine relative growth rates between different genotypes in the
same environment [e.g. as dP/dt5sP(12P)]; here, the proportion of
cells (P) is measured over time to calculate the selection coefficient (s).
In our case, we wished to measure relative cell fitness of a strain in
different environments (with and without predators). To do this, we
examined the proportions of each strain at the beginning and end of
experimental treatments. The frequency (F) of a strain in its
environment was calculated as
F i ¼ C i =N
ð1Þ
where Ci is the count of cell type i and N is the sum of all countable
cell types in the experiment, here fluorescently tagged cells. Relative
recovery for strain i was defined as
R i ¼ F N =F 0
ð2Þ
where F0 and FN are the frequencies of the cell type at the beginning
and end of the experiment, respectively. Fitness in the face of predators can be calculated as
W i ¼ Rp =R A
ð3Þ
where RP and RA are the relative recoveries in the presence and
absence of predators, respectively.
612
Variance of both relative recovery and fitness was calculated by
resampling. Estimates of genotype frequency using multiple replicates
were used to infer a mean and variance, assuming a Gaussian distribution. These distributions were resampled 1000 times and used to
estimate the variance of relative recovery and fitness.
RESULTS AND DISCUSSION
Salmonella is removed from natural environments
by biological agents
Many studies have documented the action of predators in
the decline of bacterial populations in natural environments (Hahn & Höfle, 2001; Rodrı́guez-Zaragoza, 1994;
Rønn et al., 2002; Sørensen et al., 1999). To establish the
time frame of predation in our system, we followed the disappearance of Salmonella within a sediment sample from
Homewood Cemetery Pond. This strain was discriminated
from other bacterial cells by GFP-fluorescence and resistance to chloramphenicol, gentamicin and zeomycin. Prior
to strain addition, sediment was either left untreated, treated with heat or treated with a cocktail of three antibiotics
targeting eukaryotic predators. Samples were recovered
over time and the number of tagged Salmonella cells
remaining was determined by plating on selective media;
resulting colonies were verified by fluorescent signal from
GFP; no colonies were detected from samples that did
not receive Salmonella aliquots.
As expected, the numbers of introduced cells recovered
from untreated sediment decreased over time (Fig. 1a),
with fewer than 2 % remaining after 48 h. However, populations showed no significant decline in sediment exposed
to either high temperature or a mixture of antiprotozoal
and antihelminthic drugs (Fig. 1a). These data suggest
that biological agents are responsible for the decline of
Salmonella added to the untreated samples. Since drugs targeting eukaryotic predators greatly increased survivorship,
we suspect that these organisms are dominant predators in
these environments; other environments, such as sea water
(Chibani-Chennoufi et al., 2004; Wommack & Colwell,
2000), have dominant bacteriophage predators. Since
bacteriophage would be unaffected by antiprotozoal and
antihelminthic drugs, they cannot be responsible for the
decline in Salmonella numbers in untreated samples.
Diverse antigenic types can be recovered by
antibody binding
For high-throughput enumeration of Salmonella, cells were
first recovered from natural environments by binding to
biotin-conjugated anti-Salmonella antibody. To determine
if all antigenic types used in this study could be recovered
efficiently by this antibody, a mixture of five strains – each
expressing a different O-antigen and a different fluorescent
protein, but otherwise isogenic – was assembled. Ratios of
cell types were determined by flow cytometry for samples
collected both before and after binding to the antibody
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Microbiology 162
Differential survival against predator communities
(a)
cells may reflect differences in the longevity of fluorescent
proteins rather than changes in relative abundance of the
cell types within the original sample. To test the effect of
the fluorescent tags on recovery and enumeration of
Salmonella, strains expressing one of five fluorescent proteins (strains LD901–905) were introduced into sediment
from Homewood Cemetery Pond; except for the plasmid
expressing different fluorescent proteins, cells were otherwise isogenic. After either 0 or 24 h incubation, cells were
recovered using Salmonella-specific antibodies and counted
via flow cytometry. The same proportions of the five fluorescent strains were found at both time points (Fig. 2a);
these results indicate that the half-life of the fluorescent
proteins did not significantly differ. Similar results were
obtained after 48 h incubation (data not shown), the maximum duration of experiments described here. Fluorescent
signal was never found in samples lacking added
fluorescent cells.
108
Cell count
107
106
105
104
48
24
Time in sediment (h)
0
Pellet/supernatant frequency
(b)
2.0
Nature of the O-antigen affects relative
recovery and enumeration
1.5
1.0
0.5
(L
D
91
0)
6,
7
(L
D
90
9)
8,
20
(L
D
91
7)
1,
3,
19
(L
D
90
8)
3,
10
1,
9,
12
(L
D
90
6)
0
O-antigen serotype (strain)
Fig. 1. (a) Survivorship of Salmonella strain LD916 in Homewood
Cemetery Pond sediment. Cell count on selective medium is plotted against time. White bars, untreated; black bars, heat-treated;
grey bars, drug-treated. (b) Recovery of antigenically distinct
strains of S. enterica by antibody pulldown. The recovery of each
serotype following antibody binding (pellet) is shown relative to
its frequency in a mixed liquid culture (supernatant) for replicates.
and recovery using avidin beads. While subtle differences
(about twofold) were seen in the efficiency of binding to
the antibody among strains expressing different O-antigens
(Fig. 1b), these did not prevent robust recovery and
enumeration of the different serovars of Salmonella. This
antibody recovery protocol was used in all competition
experiments.
Fluorescent tags do not affect enumeration of
cells via flow cytometry
High-throughput enumeration of bacterial cells used flow
cytometry, where strains were tagged with different fluorescent proteins. Differential enumeration of fluorescent
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To determine if the identity of the O-antigen affects relative
survival of bacteria in natural environments, we added a
mixture of fluorescently tagged, antigenically distinct, but
otherwise isogenic strains of Salmonella (LD906–910) to a
sediment sample collected from the Homewood Cemetery
Pond. Cells were recovered by binding to biotin-conjugated
rabbit anti-Salmonella antibody after 0 and 24 h incubation
and enumerated by flow cytometry. While the nature of the
fluorescent tag did not influence relative recovery (Fig. 2a),
this was not true for the nature of the O-antigen (Fig. 2b).
There were large differences in relative recovery after 24 h
(Fig. 2b; P52.26|10210, ANOVA). For example, strains
bearing the O-antigens originating from SARB52
(O : 1,9,12) and SARB2 (O : 3,10) both increased in abundance over 24 h, while those bearing O-antigens originating from SARB20 (O : 8,20), SARB30 (O : 6,7) and
SARB36 (O : 6,8) decreased. Because the strains were
isogenic at all loci except the region containing the
O-antigen-encoding rfb operon, the identity of the
O-antigen appears to affect relative recovery of Salmonella
serovars within natural environments during a time frame
when cell numbers decrease (Fig. 1a).
Relative survival of antigenically distinct strains is
affected by heat-labile factors
Differences in relative recovery of antigenically distinct
strains after 24 h incubation in natural environments
could be driven by differential binding to silicates or interaction with other, non-biotic aspects of the environment.
Alternatively, because predation affects overall survival
(Fig. 1a), interaction with predators may lead to differences
in cell numbers over time. If heat treatment of the environment influences relative recovery of Salmonella, then biotic
elements would likely be responsible for differential survival of Salmonella, rather than simply differential recovery.
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A. Atzinger, K. Butela and J. G. Lawrence
Relative recovery (f24/f0)
(a)
(b)
2.0
1.5
1.0
0.5
Fluorescent tag (strain)
0)
91
D
(L
7
6,
(L
D
90
9)
7)
8,
20
90
D
(L
6,
8
(L
D
90
8)
3,
10
(L
D
90
6)
1,
9,
12
Ka
l(
LD
90
4)
C
FP
(L
D
90
5)
m
(L
D
90
2)
D
SR
ed
(L
D
90
3)
YF
P
G
FP
(L
D
90
1)
0
O-antigen serotype (strain)
Fig. 2. Relative recovery of S. enterica from Homewood Cemetery Pond sediment. (a) Relative recovery of strains of S. enterica
LT2 (LD901–905) expressing different fluorescent proteins after 24 h incubation in sediment. Relative recovery was calculated as the ratio of the fractions of recovered cells expressing each fluorophore after 24 h to those at 0 h incubation ( f24/f0).
(b) Relative recovery of S. enterica LT2 expressing different O-antigens and different fluorescent proteins (LD906–910).
Relative recovery of each serotype was adjusted for the differential expression of fluorophores as determined in Fig. 1(a).
For clarity, the fraction of serovar 1,9,12 is plotted at 10 % of its measured value.
To test this hypothesis, five fluorescently tagged, antigenically distinct but otherwise isogenic strains of Salmonella
(LD906–910) were competed within sediment samples
collected from Homewood Cemetery Pond. The sediment
samples either were left untreated or had been heat-treated
before equilibration to 25 uC. The mixture of Salmonella
cells was introduced, and cells were recovered by antibody
binding after either 0 or 40 h of incubation; cells were
enumerated by flow cytometry.
As expected, the fractions of each cell type were the same
for untreated and heat-treated sediment at the start of
the experiment (Fig. 3a; P50.18, ANOVA), indicating
that heat treatment did not affect any contribution of
differential binding to substances within the sample.
However, fractions of each cell type significantly differed
between untreated and heat-treated sediment after 40 h
(Fig. 3b; P51.1|1029, ANOVA). While strain LD906,
bearing the O : 1,9,12 serotype, strongly outcompeted
other strains in untreated, predator-bearing samples,
this advantage was eliminated when the samples were
heat-treated prior to competition, thereby eliminating the
predators (Fig. 3b). This suggests that LD906 effectively
escaped predation in the untreated samples, while other
serotypes were consumed more readily.
These differences in abundance over time led to differences
in relative recovery between strains (Fig. 3c; P54.0|1026,
ANOVA). However, the nature of those changes was
strongly influenced by heat treatment (Fig. 3c). If we
posit that differences in relative recovery between untreated
and heat-treated samples reflect the presence and absence
of predators, then the difference between these samples
614
represents the fitness against these predators. We can
estimate fitness w as the ratio of a strain’s relative recovery
in the presence or absence of predators (equation 3)
(Fig. 3d), using the variability between the four replicates
to calculate a variance (error bars represent 2 SD ). Here,
LD906 has the highest fitness, meaning it had the greatest
increase in relative abundance in the untreated sample
relative to the heat-treated sample.
Heat treatment does not release nutrients
allowing growth
While the decline in bacterial numbers over time in
untreated samples is conventionally attributed to the
action of predators (e.g. Fig. 1), one could propose that
treatment with heat or anti-predator drugs releases nutrients that allow cell growth. If so, then one may observe
differences in relative recovery because of differentially
enhanced growth. While the strains LD906–910 are isogenic except for the region of the O-antigen-encoding rfb
locus (Table 1), one may posit that those differences
could be sufficient to utilize differentially any nutrients
released by boiling.
To test this hypothesis, we gathered four sets of soil
samples (from two locations) and four sets of sediment
samples (from two locations); samples were heat-treated
as above, with an equal volume of water being added to
soil samples before boiling. The environmental sample or
water control (both buffered to pH 7) was inoculated to
107 c.f.u. ml21 with LD907. We monitored change in bacterial numbers in each sample or sterile water control in
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Microbiology 162
Differential survival against predator communities
0.08
0.85
0.04
0.75
(e)
1.0
0.6
(L
D
90
6)
1,
9,
12
(L
D
91
0)
6,
7
(d) 1.4
Fitness, RU/RH
0.95
(L
D
90
9)
(L
D
90
8)
3,
10
(L
D
90
6)
1,
9,
12
(L
D
91
0)
6,
7
(L
D
90
9)
8,
20
(L
D
90
7)
6,
8
(L
D
90
8)
3,
10
(c) 0.12
1.2
0.8
0.4
0.2
0.65
(L
D
90
6)
0
0
0.4
0.8
f40–U/f40–H
0.12
1,
9,
12
(L
D
91
0)
6,
7
(L
D
90
9)
8,
20
(L
D
90
7)
6,
8
3,
10
(L
D
90
8)
0
3,
10
6,
8
8,
20
6
1, ,7
9,
12
Fraction each serovar, f40
0.1
0.60
0
0.4
8,
20
0.66
0.06
1.0
(L
D
90
7)
0.12
4.0
6,
8
0.72
Relative recovery, f40/f0
(b)
0.18
Fitness, RU/RH
Fraction each serovar, f0
(a)
Fig. 3. Differential fitness of Salmonella serovars (LD906–910) against heat-labile agents in natural environments. (a) Recovery
of Salmonella serovars from sediments after 0 h incubation ( f0). White bars, heat-treated; grey bars, untreated. P50.18
(ANOVA). Values for LD906 are plotted using the right axis. (b) Recovery of Salmonella serovars after 40 h incubation ( f40).
P54.0610–6. (c) Relative recovery was calculated as the ratio of fractions of cells recovered. P51.1610–9. (a–c) Grey bars,
treated; white bars, untreated. (d) Fitness was calculated as the ratio of relative recovery for each serovar without (U) and with (H)
heat treatment. Error bars represent 2 SD , which was calculated using the variances of each relative recovery coefficient. (e) Comparison of fitness and relative recovery. R 250.9972.
eight replicate experiments. Two aliquots were removed
from each replicate after either 0 or 48 h incubation at
25 uC; each aliquot was independently diluted and plated
to estimate c.f.u. The mean change in cell numbers between
0 and 48 h was then computed for each of the eight replicates grown in either environmental extract or water. The
significance of any difference between environmental
sample and water was determined by a t-test. This was a
conservative test in two ways. First, we were testing for
any growth advantage for boiled environmental samples
compared with water, which measured any nutrients
released by boiling as well as any present in the sample
prior to boiling. Second, we were measuring growth in
an inoculum of 107 c.f.u. ml21, instead of the 108 c.f.u.
ml21 added during effective competition experiments
(e.g. Fig. 3); with 10-fold fewer cells being added, each
cell has 10 times the potential nutrients available for
growth.
http://mic.microbiologyresearch.org
As shown in Table 2, even under these conditions designed
to maximize our ability to detect cell growth, bacterial cells
did not show any growth difference between heat-treated
environmental samples and water controls, neither of
which showed any significant gain or loss of cell numbers
during the course of the experiment. Therefore, we conclude that there was no significant release of nutrients
due to heat treatment of either soil samples or sediment
samples under our experimental conditions.
Relative survival is affected by drugs targeting
eukaryotic predators
Heat treatment could affect numerous classes of predators,
including bacteriophages, bacteria, unicellular eukaryotes
such as amoebae, and multicellular eukaryotes such as
nematodes. The effect of antiprotozoal and antihelminthic
drugs in increasing overall survival (Fig. 1a) suggests that
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A. Atzinger, K. Butela and J. G. Lawrence
Table 2. Test of growth differences in buffered water or environmental samples
Environmental sample*
Environment
Homewood Cemetery
Phipps (Fern Room)
Phipps (Desert Room)
Panther Hollow Lake
All locations
Water control
m
s2
N
m
s2
N
t
df
P
0.164
0.380
20.205
20.033
0.075
0.457
0.239
0.402
0.284
0.457
14
15
15
15
59
0.227
0.403
20.193
0.081
0.134
0.467
0.315
0.302
0.137
0.467
15
16
15
15
61
1.124
0.504
0.253
0.518
0.947
25.8
20.9
27.9
28.0
112.4
0.272
0.620
0.802
0.609
0.346
*Growth is reported as log2(N40/N0), where N0 and N40 are cell counts after 0 and 40 h incubation, respectively. Mean values are shown for replicate
experiments for each environmental site paired with water controls using the same bacterial inoculum.
eukaryotic predators are primary consumers of bacteria
in this system.
To examine the effects of antiprotozoal and antihelminthic
drugs on relative survival of Salmonella, five fluorescently
tagged, antigenically distinct but otherwise isogenic strains
of Salmonella were competed within sediment samples collected from Panther Hollow Lake (Fig. 4); three replicate
experiments were performed. Two treatments were used
to attenuate predators: either the sample was heat-treated
before equilibration to 25 uC, or the sample was exposed
to the antiprotozoal drug metronidazole. Drugs used to
attenuate eukaryotic predators do not affect growth or
recovery of any genotype of Salmonella in a laboratory
setting (Figs S2 and S3). The mixture of Salmonella was
introduced and cells were recovered by antibody binding
after either 0 or 30 h of incubation; cells were enumerated
by flow cytometry.
As expected, the fractions of each cell type were the same
between untreated, heat-treated and drug-treated sediment
at the start of the experiment, but were significantly different between untreated and heat-treated or drug-treated
sediment after 30 h incubation. As expected from Fig. 3(c),
relative recovery differed strongly between untreated and
heat-treated samples (Fig. 4a; P59.3|1026, ANOVA).
Notably, relative recovery also differed strongly between
untreated and drug-treated samples (Fig. 4a; P51.2|
1025, ANOVA), indicating that the addition of metronidazole also allowed the survival of strains that were otherwise
rapidly removed in the untreated sample. We can calculate
fitness in the face of predation by comparing relative recovery in untreated versus heat-treated samples, or by comparing untreated versus drug-treated samples. As seen in
Fig. 4b–d, the use of heat treatment or metronidazole treatment resulted in similar patterns of relative survival, indicating that both treatments attenuated predators in similar
ways (Pearson R50.794). Metronidazole inhibits anaerobic
amoebae, suggesting that amoebae affect relative survival of
antigenically distinct Salmonella.
This result was recapitulated in other soil and sediment
samples (Fig. S4). In all cases, fitness in the face of predation was similar when using either heat or metronidazole to
616
incapacitate predators in either soil (Fig. S4a) or sediment
samples (Fig. S4b). In addition, treatment with tetramisole
and ivermectin also led to differential survival of antigenically distinct Salmonella (Fig. S4c); both ivermectin and
tetramisole are broad-spectrum antihelminthic drugs,
suggesting that nematodes both are major predators of
bacteria in this environment and can mediate differential
survival among antigenically distinct strains. Interestingly,
the two classes of anti-eukaryote drugs led to similar fitness
profiles (Fig. S4c), suggesting that amoebae and nematodes
may share feeding preferences, or that these drugs both
target a single class of predator.
Nematodes discriminate between antigenically
distinct strains of Salmonella
To test the hypothesis that nematodes differentiate among
prey, we grew a mixture of two antigenically distinct strains
of Salmonella on solid media in the presence or absence of
C. elegans. As expected, the fractions of each strain did not
differ between plates bearing or lacking nematode predators at the start of the experiment (Pw0.05 at 0 h,
Fig. 5). However, the ratios of bacterial strains differed
after 4 days growth with or without C. elegans (Pv1023
at 96 h, Fig. 5). When competing WT strains SARB2
(O : 3,10) and SARB36 (O : 6,8), SARB2 increased abundance to a greater degree in the absence of predators,
suggesting that C. elegans preferentially consumed that
serovar. These results were validated in a replicate
experiment (Fig. 5).
To determine if C. elegans was discriminating based on the
O-antigen, we competed near-isogenic strains HW31
(O : 1,4,12) and HW19 (O : 6,7), which differ only at
their O-antigens and at the phs marker gene. In two replicate experiments, strain HW31 decreased in relative abundance in the absence of predators (Fig. 5), suggesting that
C. elegans consumed it preferentially. Taken together,
these data suggest that the action of antihelminthic drugs
in conferring differential survival of Salmonella was consistent with nematodes differentially preying upon antigenically distinct strains of Salmonella. We discounted
any role of nematode chemotaxis (Moens et al., 1999;
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Differential survival against predator communities
Relative recovery, f30/f0
(a)
1.6
1.2
0.8
0.4
0
3,10
(LD908)
(b) 1.2
6,8
(LD907)
8,20
(LD909)
(c)
6,7
(LD910)
1,9,12
(LD906)
(d)
0.4
Fitness (drug)
0.8
Fitness, RU/RH
Fitness, RU/RH
1.0
0.6
LD
9
L D 08
9
L D 07
9
L D 09
9
L D 10
90
6
0
LD
9
L D 08
9
L D 07
9
L D 09
9
L D 10
90
6
0.8
0.4
0.2
0.5
0.8
Fitness (heat)
1.1
Fig. 4. Fitness of antigenically distinct strains of S. enterica (LD906–910) in natural environments calculated using different
treatments to attenuate predators. Fitness was calculated after 30 h incubation in sediment collected from Panther Hollow
Lake. (a) Relative recovery was calculated as the ratio of fractions of cells recovered after 0 or 30 h; predators were
attenuated by heat treatment (grey bars) or exposure to metronidazole (white bars). Black bars, untreated. (b) Fitness was
calculated as the ratio of relative recovery for each serovar without and with heat treatment. Error bars represent 2 SD , which
was calculated using the variances of each relative recovery coefficient. (c) Fitness was calculated as the ratio of relative
recovery for each serovar without and with treatment with metronidazole. (d) Comparison of fitness values calculated using
either heat or metronidazole to attenuate predators. R50.794.
Ward, 1973) toward particular serovars because the two
serovars were well mixed and abundant on the plates;
strains HW31 and HW19 are also nearly isogenic, and
would not differentially produce chemoattractants
(Chaisson & Hallem, 2012; Prot, 1980) or cAMP (Ward,
1973).
Fitness of Salmonella against predation varies
between natural environments
We have shown previously that amoebae isolated from
different environments show different feeding preferences
http://mic.microbiologyresearch.org
(Wildschutte et al., 2004), though predators isolated from
the same environment show similar feeding preferences
(Wildschutte & Lawrence, 2007). Those results predict
that Salmonella should show differential fitness when introduced into different natural environments, facing communities of predators with different sets of collective feeding
preferences. To test this hypothesis, we repeated these competition experiments across soil and sediment collected
from different locations, as well as the intestinal tract of a
vertebrate host (Fig. 6). In each case, four replicates were
performed for each experimental regime. Predators were
attenuated using either heat treatment, exposure to the
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617
P = 9.9×10–4
40
20
Time (h):
P = 0.36
P=
P = 0.25
P = 0.46
SARB2 or HW31 (%)
60
3.1×10–5
P = 2.5×10–3
P = 4.5×10–6
A. Atzinger, K. Butela and J. G. Lawrence
0
96
0
96
SARB2 vs SARB36
0 96
0
96
HW31 vs HW19
Fig. 5. Differential survival of Salmonella serovars against predation
by C. elegans. Two strains of Salmonella were co-plated with
(black bars) and without (white bars) C. elegans; the fraction of
each strain was determined at 0 (start) and 96 h (stop). Ratios of
SARB2 and SARB36 were assessed by plating on MacConkey–
xylose medium. Ratios of HW31 and HW19 were assessed by
plating on Kligler iron agar. P values are shown for ANOVAs testing
differences between replicates with and without predators.
antiprotozoal drug metronidazole, or exposure to a cocktail
of metronidazole, ivermectin and tetramisole. To begin, we
expected Salmonella competed within replicate samples
collected from the same location to show similar fitness
values (e.g. Fig. 3); this was upheld for competitions
performed in numerous environmental samples, indicating
that the method was robust. Because the nature of the
fluorescent tag did not affect fitness (Fig. 2a), we expected
a set of strains with the same O-antigens, but tagged with
different fluorescent proteins, to show the same sets of
fitnesses. This was tested using strains LD906–910 and
strains LD911–916. Here, congruent fitness values (Pearson
correlation R50.945) were obtained for sets of antigenically
distinct, but otherwise isogenic Salmonella strains tagged
with different sets of fluorescent proteins in experiment 3
Apr (Fig. 6).
We also expected samples collected from the same location,
but exposed to predators for different periods of time, to
show congruent fitness patterns. This was observed in
experiments 8 Aug, 2 Feb and 15 Mar (Fig. 6). As predicted
by Fig. 4, we expected similar fitnesses for strains competed
in experiments using one environmental sample wherein
predators were attenuated using either heat or metronidazole; this is seen in experiments 3 Jul, 21 Sep, 2 Feb and
15 Mar (Fig. 6). These results bespeak the robustness of
the data, as fitness values were strongly correlated, with a
mean Pearson correlation of 0.748 in experiments at the
same location using the same treatment for different
times, or different treatments for the same time (Table 3).
618
However, fitness values for antigenically distinct, but otherwise isogenic, Salmonella strains were very different when
they were competed in samples drawn from different
locations (mean Pearson correlation 0.030; Fig. 6,
Table 3), or from the same location at different times
(mean Pearson correlation 20.091; Fig. 6, Table 3). The
samples collected from the same pond location, but at
different times, showed very different temperature profiles
and different collections of leaf litter; therefore, it was not
unexpected that predator communities would be quite
different, leading to different relative fitness of Salmonella
strains facing those predators. Taken together, these data
demonstrate that communities of predators show an aggregate feeding preference.
Predator identities are unclear, even though they
share feeding preferences
Soil and sediment environments harbour many predators of
bacteria, including amoebae, ciliates, bacteriophage, predatory bacteria and nematodes. Heat treatment, which would
eliminate all of these predators, increased bacterial survival
(Fig. 1a) and revealed differential survival of antigenically distinct strains in the face of the predator communities (Figs 3
and 6). Treatment with antiprotozoal as well as antihelminthic
drugs also increased bacterial survival (Fig. 1a), and all
methods of attenuating predators revealed congruent patterns
of differential survival (Figs 4 and 6). One conclusion that can
be drawn is that the action of heat treatment in increasing survival (Fig. 1a) did not operate by removing bacteriophages, as
neither antiprotozoal nor antihelminthic drugs would affect
bacteriophages. The similarity of effects between antiprotozoal and antihelminthic drugs suggests that either both
protozoa and nematodes share feeding preferences, or that
the drugs affect a class of predators susceptible to both classes
of drug. Metronidazole targets anaerobic protozoa by interfering with ferredoxin-mediated H2 production (Edwards &
Mathison, 1970; Quon et al., 1992). In contrast, antihelminthic drugs act on multicellular eukaryotes. Ivermectin
binds to glutamate-gated chloride channels, increasing their
permeability to chloride (Cully et al., 1994; Vassilatis et al.,
1997); this leads to hyperpolarization. Tetramisole acts as an
acetylcholine receptor agonist, disrupting acetylcholine receptors in muscles and neurons (Martin & Robertson, 2007). It is
not clear what organism would respond to all compounds.
While metronidazole could impact some bacterial taxa,
neither tetramisole nor ivermectin is known to affect prokaryotes. Since these drugs have similar effects on attenuating
predators (Fig. 5), we conclude that the antibacterial effects
of metranidazole were not responsible for the fitness differences between Salmonella serovars in our experiments.
We propose that the amoebae and nematode predators within
specific environments share feeding preferences. The strains
competed herein were isogenic save for the genes encoding
the O-antigen biosynthetic proteins; therefore, we conclude
that predators recognize prey by virtue of their O-antigen
polysaccharides. Yet other structures in these environments,
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Microbiology 162
Differential survival against predator communities
1.2
Relative fitness
1.0
0.8
0.6
0.4
0.2
0
Time (h)
Treatment
Date
Location
1,9,12
3,10
6,8
8,20
6,7
24S1 24S2
H
H
48
H
3 Apr
6 Jun
40
H
40
M
3 Jul
30
H
30
C
20
H
21 Sep
30
H
8 Aug
Sediment A
30
H
24 Sep
Sediment B
24
H
48
H
48
M
24
H
48
H
48
M
24
H
2 Feb
15 Mar
31 May
Soil A
Soil B
Fish
Fig. 6. Relative fitness of isogenic, antigenically distinct strains of S. enterica in natural environments. Fitness against predation
was calculated by attenuating predator by either heat treatment (H), exposure to metronidazole (M), or exposure to a cocktail (C)
of metronidazole, ivermectin and tetramisole. All strains were LD906–910 except for 3 Apr set S2, which used LD911–915.
Sediments A and B were collected from Panther Hollow Lake and Homewood Cemetery Pond, respectively; soils A and B were
collected from the Fruit and Desert Rooms, respectively, at the Phipps Conservatory. Error bars represent two SD s calculated via
resampling.
including intestinal mucins and decaying plant matter,
present surface polysaccharides. These structures are not
viable food sources for these predators, and attempts at their
ingestion would be fruitless. If the predators recognized
such structures as environmental attachment sites rather
than as food items, then bacteria with surface antigens resembling those structures would be conferred high fitness. This
model of molecular mimicry was discussed previously to
explain the similarity in feeding preferences shared between
amoebae of different phyla (Wildschutte & Lawrence, 2007).
Does differential predation lead to diversifying
selection and bacterial speciation?
Different strains of a single bacterial species are often found
in different environments. For example, different genotypes
of E. coli are found associated with different species of
Table 3. Correlation in relative fitness values for competition
among Salmonella serovars
Pearson correlation
Data subset
Mean
Same experiment, same treatment,
0.748
different time point
Same experiment, different
0.748
treatment, same time point
Same location, same treatment,
20.091
different date
Different experiment
0.030
http://mic.microbiologyresearch.org
Deviation Count
0.175
16
0.186
12
0.574
7
0.543
944
mammalian hosts (Gordon & FitzGibbon, 1999; Gordon
& Cowling, 2003) or even different age groups in the
same host species (Gordon et al., 2005). In such cases,
the differential distribution of genotypes may reflect
physiological differences between strains that adapt them
to each environment. Here we provide evidence that predator escape may also drive the differential distribution of
natural isolates between environments.
The relative contributions of predator escape and physiological adaptation in arbitrating the differential distribution of
genotypes among environments is unclear. We suggest that
antigenic variability may allow bacteria to persist in novel
environments by assisting in predator escape. This would
allow the accumulation of physiological adaptations to
permit more effective competition. Thus antigenic variability
may provide the keystone adaptations that allow bacterial
invasion of novel environments and, ultimately, speciation.
Here, diversifying selection would maintain high antigenic
diversity at the O-antigen-encoding rfb operon, counterselecting recombination in the region; this has been observed
in enteric bacteria, where sequence divergence is high in the
region flanking the rfb operon (Butela & Lawrence, 2009;
Milkman et al., 2003). Therefore, selection for antigenic diversity at the rfb operon would represent the first step in fragmented speciation (Retchless & Lawrence, 2007), where
adaptation to different environments imparts genetic isolation to a locus within the bacterial chromosome.
ACKNOWLEDGEMENTS
We thank Jessica Madden, Bryan Goddard and Alexis Fitzgerald for
technical assistance, and Lewis Jacobson both for supplying C. elegans
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619
A. Atzinger, K. Butela and J. G. Lawrence
and for assistance with their husbandry. This work was supported by
National Institutes of Health grant GM077548 to J. G. L.
Luna, G. M., Manini, E. & Danovaro, R. (2002). Large fraction of dead
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