Copenhagen 2014 1 FACULTY OF SCIENCE UNIVERSITY OF COPENHAGEN PhD thesis Frederik Boëtius Hertz ESBL-Producing Escherichia coli: Antibiotic Selection, Risk Factors and Population Structure. This thesis has been submitted to the PhD School of The Faculty of Science, University of Copenhagen’ Academic advisor: Anders Løbner-Olesen Academic advisor: Niels Frimodt-Møller Submitted: 29-09-2014
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F A C U L T Y O F S C I E N C E UNIVERSITY OF COPENHAGEN
As indicated in the group criteria all isolates from the susceptible group were fully susceptible to all
tested antibiotics. Susceptibility patterns and distribution of phylogroups are shown in Figure 6 and
Table 4, respectively. We found phylogroup B2 and D to be the dominating phylogroups in all three
case groups, representing 41-58% and 22-28% respectively.
Percentage of Isolates Resistant to antibiotics
0 20 40 60 80 100
Ampicillin
Cefuroxime
Gentamycin
Aztreonam
Ciprofloxacin
*Sulfamethoxazole
Trimethroprim
*Tetracycline
Ceftazidime
Ampicillin/Clavulanic acid
Tobramycin
Nitrofurantoin
*Piperacillin/Tazobactam
Mecillinam
*Fosfomycin
Meropenem
ESBLResistant
Percentage of Isolates
Ant
ibio
tics
Figure 6. Antibiotic susceptibility pattern for E.coli isolates in the ESBL-producing and the resistant (non-ESBL)
groups.
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Table 4. Distribution of phylogroups as found by use of the early Clermont et al. methodology amongst all
collected E.coli isolates. # = Number of isolates.
ESBL ISOLATES n = 98 RESISTANT ISOLATES n = 174 SUSCEPTIBLE ISOLATES n = 177
Phylogr. # Percent # Percent # Percent
A 9 9% 20 11% 19 11%
B1 6 6% 5 3% 2 1%
B2 57 58% 71 41% 91 51%
D 22 22% 49 28% 42 24%
Non-Type 4 4% 29 17% 22 12%
ESBL Genotypes
The distribution of ESBL genotypes are shown in figure 7.
Figure 7. Distribution of major ESBL Genotypes amongst the ESBL-producing E.coli isolates.
For the ESBL population 73% carried a blaCTX-M group 1 and 24% a blaCTX-M group 9. For the
remaining two isolates we were not able to detect a blaCTX-M and found blaTEM only. A total of 54%
of the isolates belonged to CTX-M-15 with CTX-M-14 and CTX-M-27 as two other large groups of
12% and 12%, respectively. Fifteen isolates also had an AmpC phenotype, but no plasmid-borne
AmpC gene was found in any of the strains.
TEM
CT-X-M Gr. 9
CTX-M Gr. 1
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5.2.3. Statistical Analysis of Risk Factors and Population Data
In the following paragraphs results of statistical analysis for risk factors are briefly listed.
Results from the initial univariate t-tests are not shown. Patient demographics and exposure to
antibiotics, defined as prescriptions one year prior to sampling, are found in Appendix 1.
Appropriate p-values from chi-square and Fisher´s exact test are found Appendix 2 and 3 in
combination with the results of the multivariate logistic regression analyses.
5.2.3.1. Multivariate Logistic Regression Models
The most important findings will be stated below.
Patient characteristics
Classifications as COI, HCAI and complicated UTI have been done according to previously stated
criteria defined in Manuscript II. Exposures to antibiotics are depicted in Appendix 1 as number of
individuals who received prescriptions and total number of prescriptions prescribed.
Patients included in the three case groups proved to be significantly older than the uninfected
controls (P<0.0001). We found, however, no significant difference between ages in the case groups
(P>0.05). Interestingly there were more men among the uninfected group than in the resistant and
the susceptible groups, but no significant difference in the number of men between the case groups.
Nonetheless, in the multivariate analysis, we found a significant difference between gender as well
as age for all case groups (P<0.005 and P<0.0001).
Epidemiological features for case groups compared to the uninfected group
The multivariate logistic regression analyses are shown in Appendix 2. We performed the
multivariate analyses for the time periods 365 days, 90 days and 30 days before and 30 days and 90
days after sampling. We have, nevertheless, decided to describe findings for 90 days and 30 days
prior to sampling and briefly included selected interesting results from the other time periods.
In the 90 days prior to sampling we found limited antibiotics and diagnoses to be independent risk
factors. For antibiotics, only use of penicillin in the backward elimination analysis was significant
for the ESBL group (P=0.015). Conversely, exposure to five and two specific antibiotics proved to
be independent risk factors for the resistant and susceptible groups, respectively (all P<0.05).
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Looking at 30 days prior to sampling, exposure to antibiotics in general proved statistically
significant for all three case groups, when analysed by chi-square (P<0.0001). Yet, just mecillinam
(P<0.0001) was a risk factor for the two resistant groups with mecillinam and sulfamethoxazole
(P=0.003 and P=0.03) being independent risk factors in the susceptible group. For the ESBL group,
diagnoses “kidney infections” and “urosepsis” were risk factors (P=0.01 and P=0.03). Of note, only
for the susceptible group use of antibiotics was an independent risk factor (data not shown).
When looking, in particular, at the backward stepwise elimination procedure, only including
variables with P<0.1, use of antibiotics increased in significance for all three groups. The significant
antibiotics have been added to Appendix 2.
Among the E.coli case groups we found no significant difference in number of community- and
healthcare-associated infections, as defined by us (P>0.05, results not shown).
In the period of 90 days after sampling, use of sulfamethizole was significant in all case groups
(P=0.03, P=0.007 and P=0.001) and mecillinam in the ESBL group (P=0.006) with use of
nitrofurantoin showing significance in the two other case groups (P=0.008 and P=0.04).
Epidemiological features for the ESBL case group compared to the other case groups
These results are found in Appendix 3. When calculated by chi-square there were significantly more
HCAI patients in the ESBL group compared to the susceptible group (P=0.006).
The number of patients receiving antibiotics and total number of prescriptions made did not clearly
show that the ESBL group had a higher use of antibiotics before the index sample (Appendix 1).
The multivariate analyses in the two runs, identified the total use of antibiotics as a risk factor for
the ESBL group 90 days prior to index sample (P=0.0049 and P=0.0029). Hospital admission 30
days prior was likewise an independent risk factor for ESBL (P=0.0073 and P=0.0216).
Finally, we saw that 90 days after infection, the use of penicillin/beta-lactamase inhibitors were
significantly higher in the ESBL group compared to the resistant group (P=0.02) and the use of
penicillins with effect on Gram-negatives and specifically the use of mecillinam were higher in the
ESBL than in the susceptible group (P=0.04 and P=0.002).
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5.3. Characterization of E.coli populations (Manuscript III)
Objective III
To investigate if the population structure of uropathogenic E.coli populations is predominantly
composed of related isolates, regardless of resistance profile.
The phylogroup and ESBL genotype distributions as well as the susceptibility patterns of the E.coli
populations included here were very similar to what was found during the case control study (Table
5 and Manuscript III). Briefly, antibiotic resistance for the resistant group was found with 84%
being resistant to ampicillin and 46-68% being resistant to trimethoprim, tetracycline and
sulphonamides.
Table 5. Distribution of phylogroups amongst E.coli isolates included in the characterization study. # =
number of isolates.
ESBL n = 98 Resistant n = 94 Susceptible n = 94
Phylogroups # Percent # Percent # Percent
A 9 9% 7 7% 9 10%
B1 6 6% 3 3% 1 1%
B2 57 58% 42 45% 52 55%
D 22 22% 30 32% 22 23%
Non-Type 4 4% 12 13% 10 11%
5.3.1. Distribution of Serogroups, MLVA codes and Sequence Types
Distribution of serogroups, a-MLVA codes and Sequence Types is found in Figure 8-11 and in
detail in Appendix 4-6.
Of the ESBL-producing isolates 94 were sent for serogrouping accompanied by 49 resistant (non-
ESBL) isolates and 51 susceptible E.coli. We found a variety of serogroups amongst the selected
isolates, with 53 different serogroups. For three isolates (two in the ESBL and one in the susceptible
group) it was not possible to distinguish between two serogroups.
There were 17% of the ESBL isolates, 12% of the resistant isolates and 14% of the susceptible
isolates which were classified as either “Negative” or “Multiple” after serogrouping.
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PCR amplification of the six MLVA alleles was done as previously described and this abbreviated
MLVA was used to type the three strain collections. All isolates (100%) were typable by a-MLVA
and all isolates except for one, selected for MLST, had alleles successfully sequenced. One isolate
with a unique a-MLVA code was not sent for sequence typing.
In these three populations we found a total of 83 a-MLVA-codes and 72 sequence types. Of these
13 a-MLVA´s and 13 ST´s were found in two out of three populations and six a-MLVA´s and seven
ST´s were found in all three populations. Overall 10 a-MLVA codes were classified as unique
“unknown” sequence types, here classified as “New STs”. Generally, ST131 constituted 23% of all
isolates, ST69 constituted 10% and ST73 a total of 9%. Of the found a-MLVA codes 74 identified
just one sequence type. However, there were quite a few situations where one specific ST was
subdivided by more than one a-MLVA code, but also more complex situations where several
different ST´s were assigned the same a-MLVA code.
As result:
- ST 10 were subdivided by three different a-MLVA codes
- ST38 by three codes
- ST69 by three codes
- ST73 by ten codes
- ST95 by three codes
- ST141 by three codes
- ST357 by two codes
- ST405 by two codes
- ST648 by two codes and lastly
- ST131 were subdivided by four different codes.
Likewise, we found that the a-MLVA method could not distinguish certain sequence types and in
particular eight a-MLVA-codes did not classify unique sequence types. As such
- ST58, ST101 and ST448 shared one a-MLVA code. ST58 and ST448 are double-locus
variants.
- ST998 and one of the a-MLVA codes for ST141 were identical, were ST141 and ST998 are
single-locus variants.
- It was not possible to discriminate between on isolate of ST14 and ST1193 which are also
single-locus variants.
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- ST38, ST117 and ST1177 were assigned a single a-MLVA code. Here ST38 and ST1177
are single locus variant with ST117 being unrelated.
- One a-MLVA code for ST10 also identified ST746, ST1598 and one New ST. Here ST10
and ST746 are single-locus variants while the new ST is a double-locus variant of ST10.
- A different ST10 a-MLVA code was identical to codes for ST93, ST540, ST617, ST2279
and a New ST where only ST617 belonged to ST Complex 10 and was a double-locus
variant of ST10.
- Also ST354 and a New ST had the same code.
- Finally ST88, ST410 and one New ST had a common code with ST88 and ST410 being
double locus variants and belonging to ST Complex 23.
The ESBL-producing E.coli Population
In this ESBL population we found a total of 26 serogroups, 20 a-MLVA codes and 20 different
sequence types. We found no New ST´s in this population. In the serogroups we found one large
cluster with 38% belonging to group O25 and some minor clusters with 6% being serogroup O153,
5% serogroup O16 and 4% serogroup O15 (Appendix 4).
As described above, we saw different a-MLVA codes recognized as identical ST´s and found
different ST´s with indistinguishable a-MLVA codes. Among these isolates there were seven
clusters of a-MLVA codes and five clusters of ST´s. The population was clearly dominated by a
few ST´s as 50 isolates belonged to ST131. These ST131 isolates were identified by three a-MLVA
codes, where the largest of these (153562) contained 44 isolates. Of the 44 isolates, 35 belonged to
the serogroup O25 with 2 isolates belonging to serogroup O77 and O97. The remaining isolates had
no specific serogroup identified. The two other ST131 a-MLVA codes were comprised of 5 and 1
isolates, respectively, all of which belonged to serogroup O16.
The Resistant E.coli Population
Here 19 serogroups, 36 a-MLVA codes and 30 ST´s were identified. Among the isolates there were
three larger clusters with serogroup O25, O75 and O73 totalled 16%, 14% and 10%, respectively. In
addition, there were some minor clusters with serogroup O6, O11 and O15 representing 6-8%
(Appendix 5).
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The a-MLVA codes and ST´s were composed of eight MLVA clusters and eight clusters of ST´s
and the population was, like the ESBL-population, dominated by few clusters of ST´s. Hence,
ST69, ST73 and ST131 comprised the largest ST cluster with 17, 10 and 14 isolates, respectively.
The Susceptible E.coli Population
In the population of susceptible isolates we found two larger clusters of serogroups and numerous
very small collections or single-isolate serogroups. The two clusters were serogroup O2 and O6
with 18% and 10% (Appendix 6).
Among the susceptible isolates 29 serogroups, 54 a-MLVA codes and 44 ST´s were found. We saw
seven a-MLVA clusters and eight clear ST clusters. Here ST73, as identified by multiple codes and
ST95 dominated, but also a-MLVA codes for ST10/93/540 and ST141/ST998 were frequent. This
population was comprised of a more diverse and heterogeneous group of E.coli.
Percentage of identifed a-MLVA codes,STs and O-groups
MLVAMLST
Serogro
ups0
50
100
150 Susceptible
Resistant
ESBL
Typing methods
Figure 8. Shown are the percentages of a-MLVA codes, STs and O-serogroup found in each of the three
populations.
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Figure 9. Distribution of major serogroups among the three E.coli populations. We show groups with 4% or more of isolates. Groups with <4% are found among singe isolates serogroup.
O25
Single Isolate Serotypes
Multiple
O153
Negative
O16O15ESBL
O25
O75
Single Isolate Serotypes
O73
O6
O15
Multiple
O11
O2NegativeResistens
Single Isolate Serotypes
O2
O6
Multiple
O1
O4
O18
O88Negative
Susceptible
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153562
Single Isolate
173050
132251
131261
173277
163562
161160
131250 224665131291
ESBL
Single Isolate
224665132251
276655
223653
131250
173277
101261
131261124645264953266655
131281152365
204665
224743253263 254665 266562
Susceptible
Single Isolate
173277
153562
276655
132251
131261
124645
132261
163562
131250254575
223653
173050121250
124643 162562 173270
Resistent
Figure 10. Distribution of major clusters of a-MLVA codes among three E.coli populations. We show codes with 2% or more of isolates. Codes with <2% are found among singe isolates.
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ST131
Single Isolate ST
ST38
ST69
ST10
ST101
ST648
ST998 ST2852
ESBL
Single Isolate ST
ST69
ST131ST73
ST10
ST1193
ST58
ST405
ST95
ST88 ST80 ST1597
Resistent
ST73
ST998
ST95
ST141ST10
ST69
ST127
ST93
ST223
ST357
ST14
ST38
ST101
ST12ST48
ST59ST540
ST4235ST131Susceptible
Figure 11. Distribution of major clusters of sequence types among three E.coli populations. We show STs with 2% or more of isolates, except for ST131 which only constituted 1% of isolates.
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6. Discussion
6.1. Selection of CTX-M-producing E.coli in vivo
One of the advantages of using animal models is the relatively rapid study of large populations. In
addition, animal experiments can be repeated and are reproducible (195). Testing on animals, however,
can give an estimation of effects only and there are the obvious limitations of extrapolating from animals
to humans.
We developed a mouse model for the investigation of intestinal colonization without the need for
prior suppression of the indigenous flora by antibiotics. It was hereby possible to illustrate the
selective ability of common antibiotics with different spectra, when an ESBL-producing, virulent
E.coli lineage was introduced into the intestines. We confirmed that an antibiotic, clindamycin,
suppressing the Bacteroides population, with no activity against Enterobacteriaceae, allows for
overgrowth of an ESBL-producing E.coli in the mouse gut. Conversely, antibiotics active against
the colonizing strain will not promote overgrowth. Beta-lactam antibiotics with no inhibiting effects
on the ESBL-producing E.coli showed diverse levels of selection. Interestingly, dicloxacillin
promoted proliferation of the ESBL-producing E.coli, even with no apparent impact on the Gram-
negative anaerobic flora or other Gram-negative bacteria. On the other hand, and very surprisingly,
ciprofloxacin, with known effect on Enterobacteriaceae, had no selective abilities. Yet, treatment
with fluoroquinolones can in some instances reach faecal concentrations above MIC of even
resistant strains, a feature not measured by us (93). There are several other limitations concerning
our mouse model, besides possible problems regarding extrapolation from mice to humans. Most
importantly however, we did not investigate antibiotic impact on the total microflora of the
intestines. We could therefore not study shifts in dominating phyla or changes in the bacterial
species. Finally, it was not possible to observe alterations in the Enterobacteriaceae population
which could potentially describe features influencing colonization.
Nonetheless, we found that the indigenous microflora provides an important protection by
inhibiting colonization. Our findings strongly indicate that other parts of the flora than Gram-
negative anaerobes play an important part upholding colonization resistance. Antibiotics may
therefore disrupt the indigenous microflora, inhibiting colonization resistance and promoting
proliferation. This disturbance may be caused by a variety of antibiotics, and level of selection is
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unforeseen by spectra. Antibiotic with limited impact on Gram-negative bacteria can select for
resistant E.coli, as seen for penicillin and dicloxacillin (196).
Disruption of the anaerobic flora, or at least the Bacteroides population, seems to play a particularly
important part in preventing prolonged colonization by MDR pathogenic E.coli.
6.2. Investigations of epidemiological factors
The case-control study performed here is, to our knowledge, the first triple-case-control study of
epidemiological characteristics for UTI caused by E.coli. It has, however, been designed with
several limitations. First, the study exclusively includes non-hospitalized patients of all ages with no
knowledge on antibiotic treatment given in hospitals. Secondly, as we included patients with
previous UTI we might be collecting and investigating patients in the middle of a course of
infection, posing an apparent cause for antibiotic prescriptions. It would have been ideal, if we had
selected only cases where the E. coli infection was the first UTI with at least one year lapse to
previous UTI. The lack of data on nursing home residence as well as outpatient contacts will lead us
to underestimate the significance of healthcare exposures and make it impossible to truly identify
the impact of these locations as reservoirs for ESBL-producing E.coli.
Nevertheless, in this unique triple-case control study we found exposure to antibiotics to be
associated with UTI in general. Healthcare contact and previous UTI infection by ESBL-producing
E.coli were associated with community-onset UTI with ESBL-producing E. coli. This is not
surprising based on previous studies of epidemiological features (15,17,18,70,73,197,198).
However, the new aspects of the epidemiology identified here were the very few differences found
between the UTI case groups. There was no clear difference in exposure to antibiotics and no
significant difference in age or gender, nor was there a significant difference (P>0.05) between the
percentages of HCAI infections in the age group 18-64 and >65 (Appendix 1). There was,
conversely, an association between hospital admissions and ESBL infection when comparing the
case groups. This confirms hospital contacts as an independent risk factor for ESBL-producing
E.coli infections (15,17,18,70,73,197). The ESBL group had significantly more UTIs caused by
CPD-R E.coli, in all investigated time periods. Antibiotics found to select in the mouse intestinal
colonisation model were not identified as risk factors in this present case-control study.
Nevertheless, in Denmark cephalosporins are prescribed in hospital setting only, data we did not
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investigate. Furthermore, very few patients were exposed to dicloxacillin and clindamycin which
might be the reason we did not find them as risk factors.
In conclusion, we found exposure to antibiotics to be an unreliable predictor of UTI with resistant
E.coli. We could not link specific diagnoses to the ESBL group, except kidney infections and
urosepsis. The combination of our finding with previous studies suggests that, in low prevalent
countries at least, exposure to antibiotics, comorbidity, age and gender are not necessarily decent
predictors of risk, but healthcare association, travelling and previous carriage of, and infection by,
ESBL-producing E.coli are features which needs to be explored by GPs (17–19,73,93,179).
6.3. Characterization of E.coli populations
We characterized three E.coli populations with different susceptibility patterns by use of an easily
performed and fast typing method. The abbreviated MLVA could assign 71% of isolates to
corresponding sequence types, simply comparing this novel method to a gold standard method with
known nomenclature. Data can furthermore be reproduced and compared to other laboratories. In
this study we chose to apply different typing methods on parts of our collection of isolates. This
increases the discriminatory power enabling us to identify the diversity of different UPEC
populations (190). With the availability of whole genome sequencing, at lower costs and with high
discriminatory power, new methods are at risk of being typing methods with no real impact, unless
price and speed overcomes lack of power (181). There is, however, still need for cheap analytic
tools for surveillance of resistant lineages and detection of outbreaks, a need persistently nourished
by the dissemination of MDR E.coli (11).
MLST and MLVA schemes analyse a small portion of the genome only, and these genes might be
subject to lateral transfer between strains, leading to somewhat incongruent phylogenetic trees, not
correlating with the genome content of a bacterium (20). Changes in VNTR regions will not
necessarily mean a change in ST, and vice versa. There is a higher rate of sustainable genetic
alterations within the VNTR regions, than in the housekeeping genes used for MLST. This might be
the reason for incomplete separation of all STs, but it provides a high discriminatory power and the
ability to separate closely related ST-lineages (187,188). The limitation of the abbreviated MLVA
was the inability to distinguish specific STs, which has been previously described for many of the
MLVA codes. Often the indistinguishable isolates were closely related STs, perhaps indicating a
kinship not recognized by MLST. By use of serogrouping and a-MLVA we described the STs as
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extremely heterogeneous lineages. We found, as has previously been seen, that ESBL-producing
E.coli are clustered in homogenous populations dominated by few lineages (199). We identified a
high level of diversity among susceptible E.coli isolates, a level of diversity which, to our
knowledge, has not previously been described (9,131,136,142). The successful lineage of ST131
was similar to other studies dominating this Danish ESBL-producing E.coli population.
Interestingly, a-MLVA seemed to sub-divide ST131 isolates based on O-serogroup, showing the
abilities to survey minor differences in E.coli lineages. The study is of course limited by the
relatively small number of isolates characterized and by the fact that the collection of isolates within
a very limited time period does not allow us to identify the fluctuation in dominant lineages of non-
ESBL populations.
We do, nonetheless, conclude based on serogroups, a-MLVA and MLST, that in this collection of
uropathogenic E.coli from general practices the populations were dominated by different
serogroups, MLVA-codes and ST´s and that the susceptible E.coli population was a much more
diverse group of isolates. Within a dominating ST-lineage, like ST73, we could sub-divide isolates
by a-MLVA. Conversely, the resistant E.coli populations and in particular the ESBL-producing
E.coli are disseminated as related lineages, indicating that the success of resistant lineages is mainly
due to positive selection of UPEC with gained resistance and limited loss of fitness.
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7. Conclusion and Perspectives
Our knowledge on the mechanisms behind antibiotic disruption of the microbiota is limited. We
know that antibiotic therapy alters the composition of the microflora and healthy volunteers
undergoing a 5-day course of ciprofloxacin had changes in the flora not resettling for months (3,12).
Antibiotic treatment changes the microbiota and selects for antibiotic resistant pathogens increasing
the risk of dissemination of resistant clones, subsequently increasing risk of infection (11,200). Our
first objective was to evaluate the ability of common antibiotics, to select for a CTX-M-15-
producing E.coli isolate belonging to ST131 in vivo. This was successfully done in a mouse
intestinal colonisation model developed and tested as part of this research. We found that antibiotics
with variation in spectra of activity can select for MDR, virulent E.coli lineages, making new
studies on antibiotic impact on the microflora a necessity to understand selection.
The current increase in faecal carriage of ESBL-producing E.coli, seen in healthy individuals and
returning traveller’s, strongly suggests a rapid dissemination of ESBL-producing isolates in the
community (104,107,108,201). Reports of carriers with no recent hospitalization or antibiotic
treatment indicate long-term carriage proposing a further risk for person-to-person transmission
(108). To what extent ESBL-producing E. coli will spread in the community is unknown, but the
potential for dissemination of resistant lineages like ST131 has proven exceptionally high
(104,199,202). Especially the combination of virulent E.coli lineages and the CTX-M type ESBL,
often showing resistance to ciprofloxacin, shows that the dissemination could be related to the
selective pressure exerted by cephalosporins or fluoroquinolones (104). However, since different
CTX-M types differ in resistance, it might reflect the various antibiotics pressure and reservoirs
involved (104).
Our second objective was to investigate epidemiological factors associated with acquiring UTI with
ESBL-producing E.coli, in general practices. We conducted a case-control study and identified new
aspects of which risk factors are associated to COI UTI in Denmark. The results of our triple-case
control study, in concordance with previous findings, raises the question if COI ESBL infections are
in fact healthcare-associated, at least in countries of low ESBL prevalence (42). Previous antibiotic
treatment was a risk factor for UTI as has previously been seen for UTI in general and for UTI
resistant bacteria (11). We found that patients in the ESBL group were more likely to belong to this
particular group, prior to our sampling but also after sampling, than the non-ESBL case groups.
These individuals might be periodic low-level carriers or treatment can correctly eradicate ESBL-
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producing E. coli, why we found significantly less ESBL-producing E.coli during the 90 days after
sampling (93). Yet, strictly COI with ESBL-producing E.coli are being reported and true clusters of
cases in the community, and among family members, are described (42). Overestimating the risk of
ESBL-producing E.coli can lead to the use of broad-spectrum antibiotics leading to a higher
selection pressure hereby preserving existing isolates and allowing for the emergence of novel
resistant strains (179).
As our third objective we wished to investigate if the population structure of uropathogenic E.coli
populations is predominantly composed of related isolates, regardless of resistance profile. Such a
characterization is of great interest to help determine if ST-lineages producing and spreading ESBL
are successful UPEC adapting to environments with antibiotics or if plasmids, carrying ESBL, are
taken up by less prevalent UPEC gaining a new advantage.
This characterization of E.coli populations was successfully done by typing of the three
susceptibility groups by use of a-MLVA, MLST and serogrouping. The a-MLVA method was here
efficient in the characterization of resistant E.coli populations and could possibly help sub-divide
MLST-lineages (57,187,203). In non-clonal populations, there is no lineage structure why such
populations are a bigger challenge when it comes to bacterial typing, than typing of highly clonal
populations (181). Information from a single locus or few loci can be unreliable in identifying
genetic relatedness, why the use of multiple loci is essential to achieve the resolution required
(181,184). Generally it can be more efficient to examine genes displaying more diversity especially
in population investigations (181). This makes the combination of MLVA and MLST a potential
robust method for surveillance. When studying heterogenic E.coli populations by MLST only,
community ExPEC are classified as clonal groups of E. coli, regardless of drug resistance (8). This
would advocate that antibiotic resistance is not a requirement for related dissemination and suggests
that susceptible E. coli strains do disseminate clonally (8). Yet, when such E.coli populations are
described by more than one typing method, the susceptible isolates are found to be a heterogonous
group, as previously determined by fimH-typing and as determined by us in this thesis. We
conclude that the susceptible E.coli populations are not disseminated as related lineages in nearly
the same degree as ESBL-producing E.coli. Reports from other research groups, suggests that some
E.coli lineages acquire different types of mobile resistance genes, as seen with ST69 and especially
ST131, while other lineages remain fairly susceptible and rarely take up plasmids (8,204). It is
therefore very likely that antibiotic selection pressure creates this clonal-like population structure
while antibiotic free environments allows for competition and subsequent non-related population
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structure (138,181). As an example, ST393 has become more frequent as its resistance profile
increases, with no change in virulence and we still see common non-ESBL and non-MDR E.coli
lineages on a global scale as we also detected a clear difference in dominating lineages (7,130). The
lineage ST69 has been found as the dominant faecal E. coli in healthy individuals. Thus, ExPEC are
well adapted to the gut of humans (11,104). As the abundance of faecal ESBL-producing E.coli is a
predictor of infection and antibiotic exposure increases ESBL-producing E.coli faecal count,
constraining use of antibiotics might maintain ESBL count at low levels, hereby minimizing the
probability of infection (93). However, ST131 must be a specialized UPEC, present in all
populations, capable of surviving in the community once present. Thus, ST131 could be one of the
UPEC lineages which are able to effectively colonize the human gut, causing UTI simply since they
dominate the microflora after antibiotic exposure (11). We speculate if resistance in E.coli is
defined by intrinsic differences in different E. coli lineages, allowing for a limited number of UPEC
ST-lineages to obtain and carry blaCTX-M.
The identified distribution of MDR E.coli indicates the existence of reservoirs for ESBL-producing
E.coli. It does, likewise, raise the question if plasmids carrying ESBL genes or not that easily transferred
between E.coli strains, why plasmids require certain E.coli lineages combined with selection pressure to
effectively spread. The likely existence of reservoirs of ESBL-producing E.coli creates a need for reliable,
cheap and fast characterization of pathogenic E.coli, to identify these reservoirs and lessen subsequent
distribution (203). Nonetheless, since not all ESBL-producing E.coli belong to known and identical
lineages, and as plasmids can be acquired by horizontal gene exchange, restraining ST131 and lineages
alike will not completely stop the spread of ESBL-producing E. coli (115). Virulence factors do not
necessarily influence abundance of faecal ESBL-producing E.coli and faecal dominance has previously
been found to be more important than virulence in the pathogenesis of UTI (93). It is therefore likely that,
even with the VFs conferring transmissibility and colonization of global lineages, other less resistant but
“classic” ExPEC as well as commensal E.coli could be adequate colonizing competitors, without
antibiotic selection pressure (115,138).
In future studies, we must identify external reservoirs of ESBL-producing E.coli, which could be nursing
homes, long-term care facilities and hospitals as previously stated, but impossible for us to determine
(205). However, a Swedish study did not find increased level of resistance in nursing homes from 2003-
12 and only very few cases of ESBL-producing E.coli with recent antibiotic treatment and hospitalisation
PhD Dissertation
during the last six months predicted higher resistance rates (206). Therefore, we must understand how
patients acquire MDR E.coli, how antibiotics affect the intestinal flora and creates a possible reservoir,
how long they carry MDR E.coli and finally discover if ESBL-producing E.coli are more likely to cause
disease than susceptible E.coli. ESBL-producing E.coli might simply be the pathogens found since they
dominate the flora. Such studies would require survey of numerous individuals of different ages and with
no history of ESBL carriages. However, carrier studies could be performed as mice colonisation
experiments with treatment given for more than three days and more than once a day. Such studies could
be prolonged to see impact on time of carriage or mice could be re-treated as CFU counts drop to detect
non-countable presence of resistant E.coli. The mouse intestinal colonisation model could furthermore be
used with different resistant UPEC or the level of conjugation between STs in the mouse gut could be
investigated. Finally, it would be of great interest to see the impact of antibiotic on the microflora,
performed as studies of the microbiome of mice, before and after antibiotic treatment. Here shifts in
domination phyla, anaerobic and aerobic and Gram-positive and –negative would be interesting to
investigate. The combination of such mice studies would help to clarify features involved in colonisation
and the dissemination of ESBL-producing E.coli.
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9. Appendix
Appendix 1. Patient demographics. Community-onset infection (COI) and Healthcare associated infections (HCAI) have been divided into age groups and patients have been classified a complicated UTI. These classifications have been done according to previously defined criteria as stated in Manuscript II. Prescr. = Prescriptions.
Penicillins with effect on Gram-negative 69 193 187 267 125 228 71 (36) 127
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Appendix 2. Results of the Multivariate Logistic Regression Analysis comparing case groups with the uninfected group. We performed the multivariate analysis based on the initial student´s t-test, with all variables with P<0.1. Subsequently we did a simple manual backward step analysis including variables with P<0.1 in the multivariate analysis. The second multivariate analysis was not possible to perform in full for the ESBL group due to lack of goodness of fit. Therefore we have included results from 30 days after sampling. *P-values found by chi-square analysis. Empty squares means estimates not computed by SAS. OD = Odds Ratio.
Multivariate Logistic Regression. First run.
ESBL, n=96 Resistant, n=171 Susceptible, n=175
Variables OR 95 CI P-Value OR 95 CI P-Value OR 95 CI P-Value
Appendix 3. . Results of multivariate logistic regression analyses comparing the ESBL group to other case groups. These tests were performed as previously described in Table 6. *P-values found by chi-square analysis. OR = Odds Ratio.
Multivariate Logistic Regression. First run.
ESBL vs. Resistant ESBL vs. Susceptible
Variables OR 95 CI P-Value OR 95 CI P-Value
COI vs. HCAI 1.5 0.8 2.8 0.1660* 2.4 1.3 4.6 0.0058*
Appendix 4. Distribution of sequence type (STs) in relation to assigned a-MLVA codes and serogroups among ESBL-producing E.coli. We show the serogroups found for the given a-MLVA-code. M = Multiple serogroups, N = serogroup negative. Isolates with a written ST are the isolates tested by MLST.
ST a-MLVA Serogroup Phylogroup ESBL Genotype
ESBL 14 123645 75 B2 TEM-1
ESBL 224 131271 M B1 CTX-M-15
ESBL 2852 131291 8 B1 CTX-M-15
ESBL 131291 25 B2 CTX-M-15
ESBL 120 132271 N Non-Type CTX-M-15
ESBL 131 103562 16 B2 CTX-M-14
ESBL 131 153562 25 B2 CTX-M Gr. 1
ESBL 131 153562 25 B2 CTX-M-15
ESBL 131 153562 77 B2 CTX-M-15
ESBL Unsuccessful 153562 97 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-28
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-14
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-28
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-28
ESBL 153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M 79/55
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
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ESBL 153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL 153562 M B2 CTX-M-27
ESBL 153562 M B2 CTX-M-15
ESBL 153562 M B2 CTX-M-15
ESBL 153562 M B2 CTX-M-15
ESBL 153562 MISSING B2 CTX-M-28
ESBL 153562 MISSING B2 CTX-M-27
ESBL 153562 N B2 CTX-M-28
ESBL 131 163562 16 B2 CTX-M-15
ESBL 131 163562 16 B2 CTX-M-15
ESBL 163562 16 B2 CTX-M-15
ESBL 163562 16 B2 CTX-M-1
ESBL 163562 153 B2 CTX-M-15
ESBL 648 161160 1 D CTX-M-15
ESBL 648 161160 102,130 D CTX-M-15
ESBL 161160 153 D CTX-M-15
ESBL 161160 MISSING D CTX-M-15
ESBL 62 161370 MISSING D CTX-M-14
ESBL 69 173277 15 D CTX-M Gr. 1
ESBL 173277 15 D CTX-M Gr. 1
ESBL 173277 15 D CTX-M-79/55
ESBL 173277 15 D CTX-M-27
ESBL 173277 44 D TEM-1
ESBL 173277 73 D CTX-M-14
ESBL 315 173552 25 B2 CTX-M-14
ESBL 428 252365 117 B2 CTX-M-1
ESBL 354 151170 153 D CTX-M-14
ESBL 998 224665 2 B2 CTX-M-15
ESBL 998 224665 M B2 CTX-M-1
ESBL 88 132261 119 A CTX-M-1
ESBL 636 293852 21 B2 CTX-M-15
ESBL 101 131261 N B1 CTX-M-1
ESBL 448 131261 111 B1 CTX-M-15
ESBL 131261 170 NT CTX-M Gr. 9
ESBL 131261 81 B1 CTX-M-79/55
ESBL 131261 100 NT CTX-M-1
ESBL 131261 M B1 CTX-M-15
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ESBL 617 132251 12 A CTX-M-15
ESBL 132251 69 A CTX-M-28/15
ESBL 132251 N A CTX-M-15
ESBL 132251 116,162 A CTX-M-15
ESBL 132251 N A CTX-M-79/55
ESBL 132251 N A CTX-M-15
ESBL 132251 12 A CTX-M-15
ESBL 746 131251 21 A CTX-M-28
ESBL 1598 131251 9 NT CTX-M-15
ESBL 38 173050 2 D CTX-M-14
ESBL 38 173050 M D CTX-M-14
ESBL 38 173050 M D CTX-M-14
ESBL 38 173050 153 D CTX-M-14
ESBL 173050 M D CTX-M-14
ESBL 173050 M D CTX-M-14
ESBL 173050 161 D CTX-M-14
ESBL 173050 86 D CTX-M-14
ESBL 173050 153 D CTX-M-14
ESBL 173050 153 D CTX-M-14
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Appendix 5. Distribution of sequence type (STs) in relation to assigned a-MLVA-codes and serogroups, for the resistant group. Not all resistant isolates were characterized by serogroup. Here we show the serogroups found for the given a-MLVA-code. M = Multiple serogroups, N = serogroup negative. Isolates with a written ST are the isolates tested by MLST.
ST a-MLVA Serogroup Phylogroup
Resistant 405 121250 M D
Resistant 121250 D
Resistant 405 131250 D
Resistant 131250 D
Resistant 14 123645 75 B2
Resistant 362 143250 D
Resistant 131 143562 B2
Resistant 131 153562 25 B2
Resistant 131 153562 B2
Resistant 153562 25 B2
Resistant 153562 25 B2
Resistant 153562 25 B2
Resistant 153562 B2
Resistant 153562 B2
Resistant 153562 B2
Resistant 153562 B2
Resistant 153562 B2
Resistant 131 163562 B2
Resistant 163562 B2
Resistant 163562 B2
Resistant 648 161150 1 D
Resistant 62 161370 D
Resistant 457 161371 11 D
Resistant 1597 162562 39 B2
Resistant 1597 162562 B2
Resistant 1193 124645 75 B2
Resistant 1193 124645 6 B2
Resistant 124645 B2
Resistant 124645 D
Resistant 124645 B2
Resistant 124645 75 B2
Resistant 393 171577 D
Resistant 69 173270 73 D
Resistant 173270 D
Resistant 69 173277 15 D
Resistant 69 173277 25 D
PhD Dissertation
Resistant 173277 11 D
Resistant 173277 11 D
Resistant 173277 15 D
Resistant 173277 15 D
Resistant 173277 25 D
Resistant 173277 68 D
Resistant 173277 73 D
Resistant 173277 73 D
Resistant 173277 73 D
Resistant 173277 73 D
Resistant 173277 M D
Resistant 173277 D
Resistant 173277 D
Resistant 95 223643 2 B2
Resistant 95 223653 2 Non-Type
Resistant 223653 Non-Type
Resistant 372 224563 18 B2
Resistant 978 226565 83 B2
Resistant 80 254575 75 B2
Resistant 80 254575 75 B2
Resistant 88 132261 8 NT
Resistant 132261 NT
Resistant 127 264953 6 B2
Resistant 117 173050 M D
Resistant 1177 173050 D
Resistant 135 225661 B2
Resistant 141 124665 B2
Resistant 73 176655 Non-Type
Resistant 73 266655 6 B2
Resistant 73 276655 6 B2
Resistant 73 276655 25 B2
Resistant 73 276655 B2
Resistant 276655 M B2
Resistant 276655 B2
Resistant 276655 B2
Resistant 276655 B2
Resistant 276655 B2
Resistant 10 124643 75 B2
Resistant 124643 75 B2
Resistant 10 132251 A
Resistant 132251 3 A
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Resistant 132251 A
Resistant 132251 A
Resistant 132251 A
Resistant 132251 N A
Resistant 2279 132251 15 A
Resistant 38 173051 25 D
Resistant 58 131261 19 B1
Resistant 131261 B1
Resistant 131261 NT
Resistant 131261 N NT
Resistant 131261 69 B1
Resistant 131261 NT
Resistant New ST 123552 B2
Resistant New ST 131251 NT
Resistant New ST 132261 NT
Resistant New ST 162438 NT
Resistant MISSING 266561 NT
PhD Dissertation
Appendix 6. Distribution of sequence type (STs) in relation to assigned a-MLVA-codes and serogroups for the susceptible group. Not all susceptible isolates were characterized by serogroup. Here we show the serogroups found for the given a-MLVA-code. M = Multiple serogroups, N = serogroup negative. Isolates with a written ST are the isolates tested by MLST.
ST a-MLVA Serogroup Phylogroup
Susceptible 223 101261 B2
Susceptible 101261 Non-Type
Susceptible 101261 B2
Susceptible 69 103277 B1
Susceptible 69 173277 D
Susceptible 173277 D
Susceptible 173277 D
Susceptible New ST 112871 D
Susceptible 1161 124675 B2
Susceptible 405 131250 2 D
Susceptible 48 131281 Non-Type
Susceptible 131281 119 Non-Type
Susceptible 357 150365 B2
Susceptible 357 152365 73 B2
Susceptible 152365 M B2
Susceptible 538 152363 13 B2
Susceptible 131 153562 B2
Susceptible 62 161370 D
Susceptible 501 163777 D
Susceptible New ST 171250 D
Susceptible 95 203653 B2
Susceptible 95 223653 1 B2
Susceptible 223653 1 B2
Susceptible 223653 M B2
Susceptible 223653 B2
Susceptible 223653 Non-Type
Susceptible 73 176655 18 B2
Susceptible 73 203655 2 D
Susceptible 73 206653 B2
Susceptible 73 206655 B2
Susceptible 73 226655 B2
Susceptible 73 256653 D
Susceptible 73 266655 2 B2
Susceptible 266655 B2
Susceptible 73 276555 25 B2
Susceptible 73 276655 6 B2
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Susceptible 73 276655 22 B2
Susceptible 73 276655 M B2
Susceptible 276655 2 B2
Susceptible 276655 B2
Susceptible 73 276665 120 B2
Susceptible 162 211251 95 A
Susceptible 681 224452 8 D
Susceptible 1858 224645 6 B2
Susceptible 4235 224743 88 B2
Susceptible 224743 88 B2
Susceptible 3672 226962 B2
Susceptible New ST 232251 105 A
Susceptible 59 241370 D
Susceptible 59 251380 D
Susceptible 80 254575 B2
Susceptible 127 264953 B2
Susceptible 264953 6 B2
Susceptible 127 274953 6 B2
Susceptible 12 266562 4 B2
Susceptible 12 266562 B2
Susceptible New ST 272275 133 B2
Susceptible 1444 273673 4 B2
Susceptible 582 274242 B2
Susceptible 1331 274655 6 D
Susceptible 589 287572 B2
Susceptible 714 473050 D
Susceptible 3846 254665 B2
Susceptible 420 254665 82 B2
Susceptible 10 131251 109 A
Susceptible 10 131251 M A
Susceptible 131251 107,117 A
Susceptible 10 132251 81 A
Manuscript I to III
Published Ahead of Print 4 August 2014. 10.1128/AAC.03021-14.
2014, 58(10):6139. DOI:Antimicrob. Agents Chemother. Frimodt-MøllerFrederik Boetius Hertz, Anders Løbner-Olesen and Niels Colonization ModelSequence Type 131 in a Mouse Intestinal Antibiotic Selection of Escherichia coli
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Antibiotic Selection of Escherichia coli Sequence Type 131 in a MouseIntestinal Colonization Model
Frederik Boetius Hertz,a,b,c Anders Løbner-Olesen,b Niels Frimodt-Møllera
Department of Clinical Microbiology, Hvidovre University Hospital, Hvidovre, Denmarka; Department of Biology, University of Copenhagen, Copenhagen, Denmarkb;Statens Serum Institut, Copenhagen, Denmarkc
The ability of different antibiotics to select for extended-spectrum �-lactamase (ESBL)-producing Escherichia coli remains atopic of discussion. In a mouse intestinal colonization model, we evaluated the selective abilities of nine common antimicrobials(cefotaxime, cefuroxime, dicloxacillin, clindamycin, penicillin, ampicillin, meropenem, ciprofloxacin, and amdinocillin) againsta CTX-M-15-producing E. coli sequence type 131 (ST131) isolate with a fluoroquinolone resistance phenotype. Mice (8 pergroup) were orogastrically administered 0.25 ml saline with 108 CFU/ml E. coli ST131. On that same day, antibiotic treatmentwas initiated and given subcutaneously once a day for three consecutive days. CFU of E. coli ST131, Bacteroides, and Gram-posi-tive aerobic bacteria in fecal samples were studied, with intervals, until day 8. Bacteroides was used as an indicator organism forimpact on the Gram-negative anaerobic population. For three antibiotics, prolonged colonization was investigated with addi-tional fecal CFU counts determined on days 10 and 14 (cefotaxime, dicloxacillin, and clindamycin). Three antibiotics (cefo-taxime, dicloxacillin, and clindamycin) promoted overgrowth of E. coli ST131 (P < 0.05). Of these, only clindamycin suppressedBacteroides, while the remaining two antibiotics had no negative impact on Bacteroides or Gram-positive organisms. Only clin-damycin treatment resulted in prolonged colonization. The remaining six antibiotics, including ciprofloxacin, did not promoteovergrowth of E. coli ST131 (P > 0.95), nor did they suppress Bacteroides or Gram-positive organisms. The results showed thatantimicrobials both with and without an impact on Gram-negative anaerobes can select for ESBL-producing E. coli, indicatingthat not only Gram-negative anaerobes have a role in upholding colonization resistance. Other, so-far-unknown bacterial popu-lations must be of importance for preventing colonization by incoming E. coli.
Escherichia coli is a versatile and ubiquitous species that is regu-larly represented in the commensal flora of the gut. The species
includes nonpathogenic, intestinal pathogenic, and extraintesti-nal pathogenic E. coli (ExPEC), all of which can be variably presentin the human gut. ExPEC can cause a wide range of infections,from uncomplicated cystitis to life-threatening sepsis (1–3). Ma-jor sources for resistance in E. coli are plasmid-borne extended-spectrum �-lactamases (ESBL), which are enzymes capable of hy-drolyzing, and thus conferring resistance toward, most �-lactamantibiotics, except for the cephamycins and carbapenems. In ad-dition, ESBLs are inhibited by �-lactamase inhibitors, such as cla-vulanic acid, sulbactam, and tazobactam (1, 4). Plasmids carryingESBL genes often carry various other genes that cause resistance toother classes of antibiotics (e.g., aminoglycosides) (1, 4, 5). One ofthe most common types of ESBLs identified in the world is CTX-M-15, and the spread of its areas of endemicity seems to be asso-ciated with a few E. coli sequence types (ST), such as ST131. ST131is most frequently linked to quinolone resistance and CTX-M-15,but it also harbors specific virulence genes coding for factors suchas adhesins (fimH, papEF), toxins (sat), and capsules (kpsM II),contributing to its ability to colonize the human gut (2, 4–7). Thepossible human colonization is of great concern, since ST131 iso-lates often are resistant to several antibiotics and are known tocause urosepsis to a higher degree than non-ST131 isolates. Inclinical settings, multiresistance, including production of ESBL,delays appropriate treatment, leading to extended hospital stays aswell as increased mortality and morbidity (8–10). Finally, urinarytract infections are primarily caused by E. coli present in the pa-tient’s own microbiota, making knowledge on colonization byresistant E. coli of great importance (1, 4, 11).
Several case-control studies have identified recent antibiotic
exposure, especially to cephalosporins and fluoroquinolones, andhospitalization as significant risk factors for acquiring an infectionwith an ESBL-producing Enterobacteriaceae (within 30 days) (10,12–14). A systematic study of the selective ability of all antibioticclasses has been lacking. In this study, we wished to evaluate theability of nine common antimicrobials, including antibiotics usedfor Gram-positive infections, to select for a CTX-M-15-producingE. coli ST131 isolate in a mouse intestinal colonization model.
(This work was presented as a poster at the 52nd InterscienceConference on Antimicrobial Agents and Chemotherapy, SanFrancisco, CA, 9 to 12 September 2012.)
MATERIALS AND METHODSStrain. For the colonizing pathogen, we used a clinical blood isolate of E.coli that belongs to the lineage B2-O25b-ST131. This isolate (65-Ec-09)carries some of the virulence factors previously seen in ST131 isolatesfound throughout Denmark in 2009, and it is similarly resistant towardmany commonly used antibiotics (MICs when resistant: cefotaxime, �32�g/ml; cefuroxime, �256 �g/ml; ceftazidime, 32 �g/ml; ampicillin, �256�g/ml; aztreonam, 32 �g/ml; amoxicillin-clavulanate, �256 �g/ml; cip-rofloxacin, �32 �g/ml; cloxacillin, �256 �g/ml; clindamycin, �256 �g/ml. MICs when susceptible are as follows: amdinocillin, 2 �g/ml; trim-ethoprim-sulfamethoxazole, �0.125 �g/ml; gentamicin, �0.5 �g/ml;
Received 8 April 2014 Returned for modification 24 May 2014Accepted 31 July 2014
Published ahead of print 4 August 2014
Address correspondence to Frederik Boetius Hertz, [email protected].
piperacillin-tazobactam, 2 �g/ml; meropenem, �0.064 �g/ml; nitrofu-rantoin, 13 millimeters in zone diameter [mm]; trimethoprim, 27 mm)(15). Pheno- and genotypic characterizations were performed by usingthe MAST-test, PCR, and DNA sequence analysis according to methodsused at the clinical laboratory of Department of Clinical Microbiology,Hvidovre Hospital, Denmark (HVH) or at Statens Serum Institut (SSI) aspreviously described (15). Sequence type verification was performed viafull multilocus sequence typing (MLST, using the Achtmann scheme[http://mlst.warwick.ac.uk/mlst/dbs/Ecoli]) by SSI, who also found thatthe isolate harbored the virulence factors kpsM II and iutA (15–17).
Media. To test bacterial growth in collected fecal samples from mice,we used selective agar plates, all from SSI Diagnostica, Hilleroed, Den-mark. For the CTX-M-15-producing E. coli population, ID Flexicult agarcontaining cefotaxime at 32 mg/liter and vancomycin at 6 mg/liter wereused. The Gram-positive aerobic population was selected on 5% bloodagar plates containing gentamicin at 5 mg/liter, and the Gram-negativeanaerobic population was selected on anaerobic plates containing genta-micin at 32 mg/liter and vancomycin at 16 mg/liter. Culturing of anaero-bic species were performed under anaerobic conditions in GasPak EZcontainers and an anaerobic atmosphere created by using AnaeroGen(Oxoid) (18).
MIC determinations. Antibiotic susceptibility testing was performedas Etests when possible and as disc diffusion tests where no Etest wasavailable (the MIC for dicloxacillin was found by using an Etest for clox-acillin, since neither Etest nor disks for dicloxacillin were available). Thediffusion test methodology has been described elsewhere (15), and a sim-ilar Etest methodology was used according to guidelines from the Depart-ment of Clinical Microbiology, Hvidovre Hospital. All results were inter-preted according to current recommendations from the EuropeanCommittee on Antimicrobial Susceptibility Testing (http://www.eucast.org/clinical_breakpoints/).
Antibiotics used for treatment. Commonly used antibiotics werechosen for this study. These included different �-lactam antibiotics, cip-rofloxacin, and clindamycin. All mouse dosages were calculated based onhuman doses (in mg per kg of body weight) from pharmacokinetic (PK)studies performed at SSI or from previously published mouse studies(Table 1) (19–26). Doses were chosen to mimic the serum antibiotic con-centrations achieved in humans on standard doses. All antibiotics wereadministered subcutaneously once each day for 3 consecutive days. Con-centrations of antibiotics in mouse feces had been measured in a previ-ously published study for a �-lactam antibiotic, an expanded-spectrumcephalosporin, a carbapenem, clindamycin, and ciprofloxacin (19). Thedoses used in this study were similar or higher.
Mouse intestinal colonization model. (i) Mice. The animal experi-ment was approved by the Danish Centre for Animal Welfare and carried
out at Statens Serum Institut in Copenhagen, Denmark. In all studies, 7-to 10-week-old female albino, outbred NMRI mice (Harlan, the Nether-lands) weighing 26 to 30 g were used. The mice used in each study were allfrom the same litter and were brought simultaneously to the stable andhoused in pairs of two per cage. At the end of the study, all mice weresacrificed to ensure that no mice were kept alive with no immediate pur-pose. Animals were housed, treated, and sacrificed according to currentguidelines.
(ii) The mouse model. The mouse intestinal colonization model wasan experimental model where all mice were kept in pairs of two per cage.Two cages constituted one group and each group received one antibiotic.Thus, each antibiotic was given to a total of four mice in two differentcages, and a total of 20 to 22 cages were included in the study. Treatmentwas given subcutaneously in the neck once a day for three consecutivedays (day 1 to day 3). Inoculation of mice with the bacterial strain wasdone through a stainless steel orogastric feeding tube on day 1 prior toinitiation of treatment. The intestinal flora was unaltered prior to thestudy, and no mice were anesthetized during the study. The experimentwas conducted from day 1 to day 8, and cages were changed daily. At theend of day 8 all mice were sacrificed.
(iii) Experimental study. We executed our full experimental study byusing the described mouse intestinal colonization model. The study wasconducted from day 1 to day 8 with feces collected prior to inoculation onday 1 and on days 2, 4, and 8. On day 1, mice were inoculated once with0.25 ml of saline containing 108 CFU/ml of 65-Ec-09. Thus, each mousewas given an inoculum of 2.5 � 107 CFU.
The mice were left for 3 h before the first doses of antibiotics wereadministered subcutaneously. Each treatment group, consisting of fourmice housed in two different cages, received cefotaxime, cefuroxime, am-picillin, dicloxacillin, amdinocillin, meropenem, clindamycin, cipro-floxacin, or benzylpenicillin (Table 1). A control group received 65-Ec-09but no antibiotic treatment. The complete selection study of E. coli ST131CTX-M-15 (65-Ec-09) in the mouse intestinal colonization model wasperformed twice, with the exception of CFU counts of the Gram-positiveaerobic flora, which were only studied in the second run. The controlgroup receiving 65-Ec-09 only was included in both runs. Furthermore, agroup of mice that received treatment with cefotaxime without receivingthe ESBL-producing strain was included in the first run only.
(iv) Prolonged presence of resistant pathogen after completed anti-biotic treatment. Additionally, the prolonged presence of the E. coliST131 after completed antibiotic treatment was studied in the first run forthree antibiotics (cefotaxime, dicloxacillin, and clindamycin). These threeantibiotics were chosen based on their selective abilities found in thestudy. Treatment stopped, for all groups, on day 3. Cages were changed
Cefuroxime 1.5 65 120 50–60 4Cefotaxime 1 40 60 100 2Ampicillin 1 40 50 75 1.5Dicloxacillin 1 30–40 60 90 2Benzylpenicillin 2 mill. IEb 60 70 60 2Amdinocillin 0.4 30–40 60 30 2Meropenem 0.5 26 50 50 1.5Clindamycin 1.8 6 36 8 1.4Ciprofloxacin 0.4 4 15 2 0.5a All doses were administered subcutaneously once a day, and the needed doses were calculated based on the expected average weight of the mice (weights given by provider), asdescribed in previously published studies (18–25). All mouse dosages were calculated based on human doses from PK studies performed at SSI or from previously published mousestudies (19–26). i.v., intravenous.b Benzylpenicillin (1.2 grams � 2 millions units � 2 mill. IE) was administered intravenously.
Boetius Hertz et al.
6140 aac.asm.org Antimicrobial Agents and Chemotherapy
daily from days 1 to 14, and feces samples were collected on days 10 and14. On day 14, the study was terminated and mice were killed.
Detection and quantification of bacteria in feces. On specified days,0.5 g of feces was collected from each cage. Feces were dissolved in 5 ml ofsaline and further diluted 10-fold in saline for a total of 6 times. Dilutionswere plated on the different selective agar plates, and the log CFU per 0.5g of stool for 65-Ec-09, the Gram-negative anaerobic flora, and the Gram-positive aerobic flora were calculated for each cage and two or three col-onies from each day frozen. Each CFU count was performed on two agarplates and calculated as the average CFU count for the two plates. Toensure no presence of cefotaxime-resistant E. coli prior to inoculation,dilutions of feces from day 1, from each cage, were spotted on selectiveplates and this showed no growth of resistant E. coli. The lower detectionlimit was 10 CFU per 0.5 g of feces.
Molecular tests. To ensure that the E. coli found in feces was identicalto the isolate given through inoculation, we tested a total of 17 cefotaxime-resistant E. coli isolates found in feces during treatment and 4 E. coliisolates from day 1 for the presence of a CTX-M group 1 gene. Samplesfrom both experimental runs were included (see below). Three to fourisolates per frozen sample were used for DNA purification. As these testswere performed on isolates from both study runs, they were not per-formed until both runs had been completed. Thus, isolates tested wereisolated from frozen samples. We were therefore likely to isolate the dom-inating E. coli strain and thereby determine if 65-Ec-09 had become thedominating E. coli of the microbiota (11, 27).
All of these 21 isolates were identified as E. coli by matrix-assisted laserdesorption–time of flight analysis as described elsewhere (28). All resis-tant E. coli isolates contained a CTX-M group 1 gene, whereas none of theisolates from day 1 contained a CTX-M group 1 gene.
Isolates from the following groups were tested: cefotaxime (day 2 fromboth study runs and day 1 from the first run), cefuroxime (day 2 fromboth study runs and day 1 from the first run), ampicillin (day 2 from bothstudy runs), dicloxacillin (days 1, 2, 4, and 8 from the first run and days 2and 8 from the second run), clindamycin (days 1, 2, 4, and 10 from the firstone and days 2 and 8 from the second run), and benzylpenicillin (day 2from second run).
Additionally, five of the cefotaxime-resistant E. coli isolates and oneisolate from day 1 were characterized by MLST (cefotaxime, cefuroxime[day 2], dicloxacillin [days 1 and 4], and clindamycin [days 4 and 10]).The five resistant E. coli were identified as ST131 and the one isolate fromday 1 belonged to ST602.
Statistical analysis. Data were analyzed with the use of SAS software,version 9.3 (SAS Institute). When just one group receiving one antibioticwas compared to the control group, this was done via a one-way analysisof variance (ANOVA). When multiple CFU counts were compared, it wasdone as a multiple variant analysis, adjusted for multiple comparisonswith the Bonferroni correction. The conservative Bonferroni correction
was used to avoid multiple comparisons. A P value of �0.05 was consid-ered significant.
RESULTS
Results of fecal bacteriology were calculated as the log CFU/0.5 gof feces, and the mean CFU of four cages (two cages for Gram-positive aerobic flora) were used for statistical calculations. Forgraphic depictions, means and standard deviations (SD) wereused. Data for the selective abilities of the different antibiotics on65-Ec-09 are shown in Table 2 and Fig. 1 and 2 for E. coli, Gram-negative anaerobic flora, and Gram-positive flora, respectively.
Effect of antibiotic treatment on establishment of resistantpathogens and on the indigenous microflora. Data for the effectson colonization of 65-Ec-09 by the different antibiotics are shownin Fig. 1. Cefotaxime, dicloxacillin, and clindamycin promotedthe colonization and overgrowth of 65-Ec-09 from day 2 throughday 8 (P � 0.01 for dicloxacillin and clindamycin; P � 0.05 forcefotaxime). Benzylpenicillin and cefuroxime showed less over-growth but selective abilities on days 2 and 4 (P � 0.05). Dicloxa-cillin and clindamycin showed the highest selective abilities (P �0.01 for dicloxacillin on days 2 and 4 and P � 0.01 for clindamycinon all days). After treatment was completed on day 3, there was adecline in the colonization of 65-Ec-09 from day 4 to 8. In com-parison, neither ampicillin, amdinocillin, meropenem, nor cipro-floxacin promoted overgrowth of 65-Ec-09 beyond day 2 (P �0.05).
Data for the impact on the original microbiota as Gram-nega-tive anaerobic flora, represented by Bacteroides, and Gram-posi-tive flora, respectively, are shown in Fig. 2. None of the antibioticsused had an inhibiting or promoting impact on the Gram-positiveflora (P � 0.05). Only clindamycin had an impact on the Gram-negative anaerobic flora, as it completely eliminated the Gram-negative anaerobic flora during treatment (P � 0.05). After treat-ment, the CFU counts for the Gram-negative anaerobic floraincreased to counts equal to those before treatment.
Prolonged presence of 65-Ec-09 after completed antibiotictreatment. Data for CFU of 65-Ec-09 on all sampling days arefound in Fig. 1. After the initial increase, the CFU decreased for allthree groups of antibiotics. For dicloxacillin and cefotaxime, theCFU counts dropped below the detection limit on day 10. Forclindamycin, the CFU was measurable until day 14, the last day ofthe study. There were no significant differences in fecal CFU of65-Ec-09 over time among the three antibiotics (P � 0.05).
TABLE 2 Results of the CFU counts for E. coli ST131
Antibiotic
Log CFU � SD (P value) ona:
Day 2 Day 4 Day 8 Day 10 Day 14
Cefotaxime 7.75 � 4.33 (�0.01) 5.25 � 6.54 (�0.01) 3.61 � 2.5 (0.011) 1.5 � 1.5 (0.98) 0.5* � 3.55 (1)Clindamycin 8.5 � 1 (�0.01) 7.75 � 0.87 (�0.01) 5.75 � 0.87 (�0.01) 2.5 � 3.55 (0.44) 1* � 1.41 (1)Dicloxacillin 8.5 � 1 (�0.01) 9 � 5.35 (�0.01) 3 � 3.74 (�0.01) 0 (1) 0 (1)Cefuroxime 7.5 � 3 (�0.01) 4.25 � 5.89 (0.015) 1.75 � 4 (0.07)Penicillin 6.25 � 3.57 (0.02) 3.75 � 6.76 (0.03) 0 (1)Amdinocillin 2.25 � 2.96 (0.3) 1.25 � 5.55 (0.5) 0 (1)Meropenem 3.5 � 2.96 (1) 0 (1) 0 (1)Ciprofloxacin 2.25 � 2.6 (0.3) 0 (1) 0 (1)Ampicillin 3.25 � 4.33 (0.8) 2.5 � 6.33 (0.14) 0.75* � 2.6 (0.4)Control 3.5 � 1.73 0 0a P values for days 2 to 8 were determined via an ANOVA, while P values from days 10 and 14 were found by a multiple variant analysis with the Bonferroni correction.*, below thelower detection limit.
To our knowledge, this is the first study to experimentally evaluatein vivo selection in the gut of a CTX-M-15-producing E. coli ST131isolate by a range of commonly used antibiotics, including antibi-otics with no activity against Gram-negative bacteria. With themouse intestinal colonization model, we were able to illustrate theselective abilities of different antibiotics on the intestinal florawhen a virulent isolate of CTX-M-15-producing E. coli ST131 wasintroduced. We found several interesting aspects of selection.First, we confirmed that antibiotics with activity against the colo-nizing strain did not promote proliferation, since neither amdi-nocillin nor meropenem resulted in colonization. Second, ourfindings confirmed that an antibiotic, clindamycin, that elimi-nates the Gram-negative anaerobic flora with no in vitro activityagainst Enterobacteriaceae promotes proliferation of ESBL-pro-ducing E. coli. It has been shown that antimicrobial impact on thetotal anaerobic population is proportional to the impact on theBacteroides population (19). Third, of the �-lactams with no in-hibiting effects on the ESBL-producing E. coli, cefotaxime showedthe highest level of selection. Cefuroxime and benzylpenicillin did,however, show higher selection propensities than ampicillin, inagreement with what has previously been seen for high doses ofpenicillin (29). Furthermore, we discovered that dicloxacillin,with no obvious influence on either the Gram-negative anaerobicflora or other Gram-negative bacteria, promoted colonizationwith the ESBL-producing E. coli, while ciprofloxacin, with a lim-ited in vitro effect on the Gram-negative anaerobic bacteria but aneffect on Enterobacteriaceae, showed no abilities to select. Theseresults could indicate that not only Gram-negative anaerobes havea key responsibility upholding colonization resistance. It appearsthat, as for penicillin (29), an antibiotic with limited impact onGram-negative bacteria can select for a resistant E. coli isolate,suggesting that other bacterial populations, not measured in ourstudy, such as certain anaerobic Gram positives, are of importancefor preventing colonization from an incoming E. coli strain.
Finally, we found that the antibiotic with the highest impact on
the anaerobic population, here represented by the Bacteroidespopulation, seems to give room for prolonged colonization, i.e.,clindamycin showed high to medium levels of 65-Ec-09 until day14, compared to dicloxacillin and cefotaxime. This points to thepossibility that even if unknown Gram-positive populations, an-aerobic or aerobic, display colonization resistance, the Bacteroidespopulation seems to play a role in preventing prolonged coloni-zation.
Our study suggests that selection of E. coli ST131 is not derivedalone by the antibiotic impact on the major population, such asanaerobes, as seen with dicloxacillin versus ampicillin and cipro-floxacin. This finding could potentially alter the perception ofwhich antibiotics drive the spread of ESBL-producing E. coli, in-cluding ST131, even if clindamycin was the antibiotic that showedthe highest level of selection and longest duration of colonization.
The model has some limitations, since it does not include clin-ical aspects of selection, such as treatment with multiple antimi-crobials or long-term treatment, nor does it take into accountreexposure to resistant pathogens or retreatment after exposure.Also, we did not investigate the antibiotics’ effects on the totalbacterial population of the intestines, including shifts in the dom-inating phyla. Such an investigation of changes in species andchanges in the total Enterobacteriaceae population could poten-tially have described, in detail, factors influencing colonization.Future studies of the microbiota should be designed to fully de-scribe antibiotic impacts on the different phyla. The lack of selec-tive ability seen from ciprofloxacin on the CTX-M-15-producingE. coli ST131 isolate was not expected and was surprising. We havenot tested the mice used in this study for the presence of cipro-floxacin-resistant strains, and such a presence could explain thelack of selection seen here. Furthermore, extrapolation of resultsfrom the model is limited by the physiological differences betweenmice and humans, even though studies have shown that subcuta-neous treatment once a day in mice gives fecal antibiotic concen-trations equivalent to those of humans (19). Finally, we studiedonly the fecal—and not the mucosal—microflora of mice. Yet, it
FIG 1 The mean and SD of the log CFU/0.5 g of feces for 65-Ec-09 from day 1 to day 14. The arrow indicates treatment from day 1 to day 3.
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6142 aac.asm.org Antimicrobial Agents and Chemotherapy
has been postulated that, first, the mouse fecal flora is a mixture ofmucosal and luminal flora and, second, the intestinal microfloraof laboratory mice is comparable to the intestinal flora in humans(30, 31). We have no obvious explanation for the selective abilityof dicloxacillin, since this drug had no impact on the Gram-neg-ative anaerobic or the aerobic Gram-positive flora. More detailedevaluation of the mouse and human intestinal microbiomes mayprovide the reason for the change in intestinal flora imposed bydicloxacillin. A study of antibiotics’ general impacts on the micro-flora of mice and men would further illustrate the elements in-volved in selection.
In summary, our study confirms that antibiotics with an im-pact on Gram-negative anaerobes support overgrowth and colo-nization of a CTX-M-15 producing E. coli ST131 isolate. None-theless, our study shows that selection could be driven byantibiotics with limited effect on anaerobes and no effect on com-peting Gram negatives, but not by other antimicrobials with abroader spectrum of activity. The results indicate a need for inves-tigation of selective mechanisms of different drugs, to fully de-velop rules and guidelines for stewardship of antibiotics.
ACKNOWLEDGMENTS
This study was performed with financial support from PAR, an EU FP7-Health-2009-Single-Stage project. Additionally, the work was supportedby The Danish Council for Strategic Research (DanCARD project 09-
067075/DSF), Roskilde University, the Aase & Ejnar Danielsens Founda-tion, and the SSAC Foundation.
Furthermore, the work was performed in cooperation between StatensSerum Institut, Hvidovre University Hospital, Roskilde University, andCopenhagen University. We are grateful to and thank Anette M. Ham-merum and Frank Hansen from SSI, who provided strain 65-Ec-09.
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Figure 1. Here we show the percentages of found a-MLVA codes, STs and O-serogroups found in each of the three populations.
Percentage of identifed a-MLVA codes,STs and O-groups
MLVA
MLST
Serogro
ups0
20
40
60
80
100
120
140
160 Susceptible Resistant ESBL
Typing methods
21
Figure 2.
Percentage of Isolates Resistant to antibiotics
Ampicillin
Cefuroxime
Aztreonam
Ciprofloxacin
*Sulfamethoxazole
Trimethroprim
*Tetracycline
Ampicillin/Clavulanic acid
Gentamicin
*Piperacillin/Tazobactam
Nitrofurantoin
Mecillinam
*Fosfomycin
Meropenem ESBLResistant
22
Figure 3. Percentages of isolates resistant to chosen antibiotics used for oral administration. We show resistance patterns for three common UPEC ST lineages, here all isolates are non-ESBL-producers but present in either the susceptible or resistant population. N: ST131 = 17, ST73 = 25, ST69 = 20.
Resistance patterns for non-ESBL UPEC lineages
0 20 40 60 80 100 120 140 160 180 200
Ampicillin
Ciprofloxacin
*Sulfamethoxazole
Trimethroprim
Nitrofurantoin
Mecillinam
*Fosfomycin
Resistance to >3 antibiotics
Fully susceptible
ST131ST73ST69
23
Table 1. Distribution of sequence types (STs) in relation to assigned a-MLVA codes and serogroups among ESBL-producing E.coli. We show the serogroups found for the given a-MLVA code. M = Multiple serogroups, N = serogroup negative. Isolates with a written ST are the isolates tested by MLST.
ST a-MLVA Serogroup Phylogroup ESBL Genotype
ESBL 14 123645 75 B2 TEM-1
ESBL 38 173050 2 D CTX-M-14
ESBL 38 173050 M D CTX-M-14
ESBL 38 173050 M D CTX-M-14
ESBL 38 173050 153 D CTX-M-14
ESBL 173050 M D CTX-M-14
ESBL
173050 M D CTX-M-14
ESBL 173050 161 D CTX-M-14
ESBL
173050 86 D CTX-M-14
ESBL 173050 153 D CTX-M-14
ESBL 173050 153 D CTX-M-14
ESBL 62 161370 MISSING D CTX-M-14
ESBL 69 173277 15 D CTX-M Gr. 1
ESBL
173277 15 D CTX-M Gr. 1
ESBL 173277 15 D CTX-M-79/55
ESBL
173277 15 D CTX-M-27
ESBL 173277 44 D TEM-1
ESBL 173277 73 D CTX-M-14
ESBL 88 132261 119 A CTX-M-1
ESBL 120 132271 N Non-Type CTX-M-15
ESBL 131 103562 16 B2 CTX-M-14
ESBL 131 153562 25 B2 CTX-M Gr. 1
ESBL 131 153562 25 B2 CTX-M-15
ESBL 131 153562 77 B2 CTX-M-15
ESBL Unsuccessful 153562 97 B2 CTX-M-27
24
ESBL 153562 25 B2 CTX-M-27
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-28
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-14
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-28
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-27
ESBL
153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 25 B2 CTX-M-28
ESBL 153562 25 B2 CTX-M-27
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M 79/55
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 25 B2 CTX-M-27
ESBL 153562 25 B2 CTX-M-15
25
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 25 B2 CTX-M-15
ESBL 153562 25 B2 CTX-M-15
ESBL
153562 M B2 CTX-M-27
ESBL 153562 M B2 CTX-M-15
ESBL
153562 M B2 CTX-M-15
ESBL 153562 M B2 CTX-M-15
ESBL
153562 MISSING B2 CTX-M-28
ESBL 153562 MISSING B2 CTX-M-27
ESBL 153562 N B2 CTX-M-28
ESBL 131 163562 16 B2 CTX-M-15
ESBL 131 163562 16 B2 CTX-M-15
ESBL 163562 16 B2 CTX-M-15
ESBL
163562 16 B2 CTX-M-1
ESBL 163562 153 B2 CTX-M-15
ESBL 224 131271 M B1 CTX-M-15
ESBL 315 173552 25 B2 CTX-M-14
ESBL 354 151170 153 D CTX-M-14
ESBL 428 252365 117 B2 CTX-M-1
ESBL 617 132251 12 A CTX-M-15
ESBL 132251 69 A CTX-M-28/15
ESBL
132251 N A CTX-M-15
ESBL 132251 116,162 A CTX-M-15
ESBL
132251 N A CTX-M-79/55
ESBL 132251 N A CTX-M-15
ESBL 132251 12 A CTX-M-15
ESBL 636 293852 21 B2 CTX-M-15
ESBL 648 161160 1 D CTX-M-15
26
ESBL 648 161160 102,13 D CTX-M-15
ESBL
161160 153 D CTX-M-15
ESBL 161160 MISSING D CTX-M-15
ESBL 998 224665 2 B2 CTX-M-15
ESBL 998 224665 M B2 CTX-M-1
ESBL 2852 131291 8 B1 CTX-M-15
ESBL 131291 25 B2 CTX-M-15
ESBL 101 131261 N B1 CTX-M-1
ESBL 448 131261 111 B1 CTX-M-15
ESBL
131261 170 NT CTX-M Gr. 9
ESBL 131261 81 B1 CTX-M-79/55
ESBL
131261 100 NT CTX-M-1
ESBL 131261 M B1 CTX-M-15
ESBL 746 131251 21 A CTX-M-28
ESBL 1598 131251 9 NT CTX-M-15
Table 2. Distribution of sequence types (STs) in relation to assigned a-MLVA codes and serogroups, for the resistant group. Not all resistant isolates were characterized by serogroup. Here we show the serogroups found for the given a-MLVA code. M = Multiple serogroups, N = serogroup negative. Isolates with a written ST are the isolates tested by MLST.
ST a-MLVA Serogroup Phylogroup
Resistant 14 123645 75 B2
Resistant 38 173051 25 D
Resistant 58 131261 19 B1
Resistant
131261
B1
Resistant
131261
NT
Resistant
131261 N NT
27
Resistant
131261 69 B1
Resistant
131261
NT
Resistant 62 161370
D
Resistant 69 173270 73 D
Resistant
173270
D
Resistant 69 173277 15 D
Resistant 69 173277 25 D
Resistant
173277 11 D
Resistant
173277 11 D
Resistant
173277 15 D
Resistant
173277 15 D
Resistant
173277 25 D
Resistant
173277 68 D
Resistant
173277 73 D
Resistant
173277 73 D
Resistant
173277 73 D
Resistant
173277 73 D
Resistant
173277 M D
Resistant
173277
D
Resistant
173277
D
Resistant 73 176655
Non-Type
Resistant 73 266655 6 B2
Resistant 73 276655 6 B2
Resistant 73 276655 25 B2
Resistant 73 276655
B2
Resistant
276655 M B2
Resistant
276655
B2
Resistant
276655
B2
Resistant
276655
B2
28
Resistant
276655
B2
Resistant 80 254575 75 B2
Resistant 80 254575 75 B2
Resistant 88 132261 8 NT
Resistant 132261 NT
Resistant New ST 132261
NT
Resistant 95 223643 2 B2
Resistant 95 223653 2 Non-Type
Resistant
223653
Non-Type
Resistant 127 264953 6 B2
Resistant 131 143562
B2
Resistant 131 153562 25 B2
Resistant 131 153562
B2
Resistant
153562 25 B2
Resistant
153562 25 B2
Resistant
153562 25 B2
Resistant
153562
B2
Resistant
153562
B2
Resistant
153562
B2
Resistant
153562
B2
Resistant
153562
B2
Resistant 131 163562
B2
Resistant
163562
B2
Resistant
163562
B2
Resistant 135 225661
B2
Resistant 141 124665
B2
Resistant 362 143250
D
Resistant 372 224563 18 B2
29
Resistant 393 171577
D
Resistant 405 121250 M D
Resistant
121250
D
Resistant 405 131250
D
Resistant
131250
D
Resistant 457 161371 11 D
Resistant 648 161150 1 D
Resistant 978 226565 83 B2
Resistant 1193 124645 75 B2
Resistant 1193 124645 6 B2
Resistant 124645 B2
Resistant 124645 D
Resistant
124645
B2
Resistant
124645 75 B2
Resistant 1597 162562 39 B2
Resistant 1597 162562
B2
Resistant New ST 123552
B2
Resistant New ST 131251
NT
Resistant New ST 162438
NT
Resistant MISSING 266561
NT
Resistant 10 124643 75 B2
Resistant 124643 75 B2
Resistant 10 132251 A
Resistant 132251 3 A
Resistant 132251 A
Resistant
132251
A
Resistant
132251
A
Resistant
132251 N A
30
Resistant 2279 132251 15 A
Resistant 117 173050 M D
Resistant 1177 173050 D
Table 3. Distribution of sequence types (STs) in relation to assigned a-MLVA codes and serogroups for the susceptible group. Not all susceptible isolates were characterized by serogroup. Here we show the serogroups found for the given a-MLVA code. M = Multiple serogroups, N = serogroup negative. Isolates with a written ST are the isolates tested by MLST.