# Antibiotic-resistant Escherichia coli in karstic systems: a biological indicator of the origin of fecal contamination?

A.F. Ribeiro, E. Laroche, G. Hanin, Matthieu Fournier, L. Quillet, Jean-Paul Dupont, B. Pawlak

► To cite this version:

A.F. Ribeiro, E. Laroche, G. Hanin, Matthieu Fournier, L. Quillet, et al. Antibiotic-resistant Escherichia coli in karstic systems: a biological indicator of the origin of fecal contamination?. FEMS Microbiology Ecology, 2012, 81 (1), pp.267-280. 10.1111/j.1574-6941.2012.01382.x. hal-00737393

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# Antibiotic-resistant *Escherichia coli* in karstic systems: a biological indicator of the origin of fecal contamination?

Angela Flores Ribeiro¹, Emilie Laroche¹,², Guillaume Hanin¹,³, Matthieu Fournier¹, Laurent Quillet¹, Jean-Paul Dupont¹ & Barbara Pawlak¹

¹UMR CNRS 6143, Morphodynamique Continentale et Côteière (M2C), Mont Saint Aignan, France; ²Agri'Terr, BioSol Laboratory, Mont Saint Aignan, France; and ³Burgeap, Le Petit-Quevilly, France

**Correspondence:** Angela Flores Ribeiro,
UMR CNRS 6143, Morphodynamique
Continentale et Côteière (M2C), Place Emile
Blondel, bâtiment IRESE B, 76821 Mont Saint
Aignan, France. Tel.: (+33)2 35 14 64 54;
fax: +33 235 147 022; e-mail:
angela.floresribeiro@etu.univ-rouen.fr

Received 21 October 2011; revised 21 March
2012; accepted 3 April 2012.
Final version published online 10 May 2012.

DOI: 10.1111/j.1574-6941.2012.01382.x

Editor: Christian Griebler

**Keywords**

antibiotic-resistant *E. coli*; karst; fecal contamination; integrons; drinking water resources.

## Abstract

Occurrences of antibiotic-resistant *Escherichia coli* in two springs of a karstic system (NW France) providing drinking water were determined to study the role of aquifers in the dissemination of the resistance genes. Water samples were collected during wet and dry periods and after a heavy rainfall event to investigate *E. coli* density, antibiotic resistance patterns, and occurrences of class 1, 2, and 3 integrons. By observing patterns of the resistant isolates (i.e. number and type of resistances) and their occurrences, we were able to define two resistant subpopulations, introduced in the aquifer via surface water: (1) R1-2, characterized by one or two resistance(s), essentially to chloramphenicol and/or tetracycline (96.5%), was always found during the heavy rainfall event; (2) R3-10, characterized by three or more resistances, mostly resistant to tetra-cycline (94.1%) and beta-lactams (86%), was found transiently. Class 1 and 2 integrons were detected, mostly in the R3-10 subpopulation for class 1 integrons. The characteristics of these two subpopulations strongly suggest that the contamination originates from pasture runoff for the R1-2 subpopulation and from wastewater treatment plant effluents for the R3-10 subpopulation. These two subpopulations of *E. coli* could be used as biological indicators to determine the origin of groundwater contamination.

## Introduction

Surface water and groundwater are our major drinking water resources, but also the final destination of fecal contamination originating from humans (wastewater treatment plants, WWTP, and septic systems) and/or animals (field runoff) (Nwosu, 2001; Baquero et al., 2008; Taylor et al., 2011). Various chemical and/or physical treatments, ranging from simple chlorination to membrane filtration (Shannon et al., 2008), are applied to purify these waters before human consumption. Thus, to ensure drinking water quality, monitoring the standards established for a water resource is essential, but identification of emerging hazards of water, such as bacterial antibiotic resistance, is also crucial (Pruden et al., 2006; Taylor et al., 2011).

According to microbiological criteria, water quality is defined by the occurrence of fecal indicators, that is,

*Escherichia coli* and *Enterococcus* spp. In addition to indicating the potential presence of pathogens, these fecal bacteria raise the problem of the spread of antibiotic resistance, a major health concern today. Some authors consider water to be the preponderant link between the four major ecosystems – human, animal, soil, and aquatic – involved in the circulation of antibiotic resistance (Nwosu, 2001; Baquero et al., 2008). Antibiotic-resistant bacteria, selected in the intestines of humans and/or animals undergoing treatment, are transferred between these ecosystems via fecal discharges (Reinthaler et al., 2003; Moura et al., 2007; Saptoka et al., 2007; Servais & Passerat, 2009; Oberlé et al., 2012). In some conditions, these fecal bacteria might then exchange resistance genes by horizontal transfers with other bacterial populations (allochtonous and/or autochtonous). Antibiotic-resistant genes entering into environmental ecosystems could increase the latent hazard for human health and have an
ecological impact on bacterial communities (changes in the population dynamics and in their interactions) (Martinez, 2009). The dissemination of antibiotic-resistant genes is facilitated when they are carried by genetic structures that are frequently associated with each other, such as plasmids, transposons, and resistance integrons (Cambray et al., 2010; Davies & Davies, 2010). Integrons have been identified as a mechanism used by bacteria to capture antibiotic resistance cassettes, and are known to express up to eight resistance phenotypes (Cambray et al., 2010). They are characterized by (1) a gene *intI* encoding an integrase, (2) a promoter to express cassettes, and (3) an *attI* recombination site. Several gene cassettes can be integrated into the integron by *IntI*-catalyzed recombination (Partridge et al., 2009). Five classes of resistance integrons, defined by their integrase protein sequences, have been documented (Cambray et al., 2010). Studies concerning integron occurrences in *E. coli* populations isolated from aquatic environments have mainly focused on surface water. They have reported predominantly class 1 and 2 integrons (Tennstedt et al., 2003; Ferreira da Silva et al., 2007; Moura et al., 2007; Laroche et al., 2009). Little is known about integrons and antibiotic-resistant bacteria in groundwater (Saptoka et al., 2007; Laroche et al., 2010), even though it is a major drinking water resource worldwide and forms a potential return pathway to humans for resistance genes (Xi et al., 2009; Taylor et al., 2011).

Karstic aquifers are highly vulnerable to contamination, and notably to bacterial contamination, as a result of their hydrogeological characteristics (Mahler et al., 2000; Dussart-Baptista et al., 2003, 2007). Microbiological contaminants undergo only limited attenuation in karst systems owing to fast direct transfer of surface water (several hundreds of m h⁻¹) to karst springs via fractured media (Göppert & Goldscheider, 2008; Pronk et al., 2009). The microbiological quality of a water resource can thus be affected by surface water contaminated by human activities in the catchment area (i.e. agriculture or treatment of wastewaters), mainly during or after rainfall events (run-off). These events generate an increase of turbidity and a fall of electrical conductivity in the spring waters, caused by surface water arrivals in the karstic systems (Mahler et al., 2000; Pronk et al., 2007, 2009). Turbidity is the standard indicator of the quantity of suspended matter in water and could have two potential origins: (1) an allochtonous origin corresponding to the direct transfer of surface water affected by the products of soil erosion and WWTP and then (2) an autochtonous origin, which is related to resuspension of intrakarstic sediments previously deposited within the karstic network, and particles coming from conduits and fissures (Massei et al., 2003). Electrical conductivity is a parameter indicating the

quantities of minerals dissolved in water. A fall of electrical conductivity is indicative of surface water arrivals in the karstic systems as the highly mineralized groundwater is diluted by the weakly mineralized surface water. Turbidity-electrical conductivity curves (T-EC curves) calculated with these two parameters allow us to observe the process of resuspension, transfer, and deposition in the karstic systems as has already been reported (Valdes et al., 2006; Fournier et al., 2007).

The aim of our study was to investigate the contamination of two springs of a karstified chalk system by antibiotic-resistant *E. coli* and the conditions promoting this contamination. We determined *E. coli* density, antibiotic resistance patterns, and occurrences of class 1, 2, and 3 integrons in the isolates during a dry period and a wet period, and after a heavy rainfall event. The comparison of antibiotic resistance patterns (number and type of resistances) and the definition of two different resistant subpopulations (R1-2 and R3-10) have allowed us to make assumptions about the origins of groundwater contamination. These two subpopulations could help to describe surface water transfer through a karst aquifer and thus to better understand the aquifer's vulnerability to bacteria.

## Materials and methods

### Study site

The study site is a karstified chalk aquifer, located in Haute-Normandie (France), on the north side of the Seine estuary (Fig. 1). The aquifer supplies drinking water to about 125 000 inhabitants, mainly via the exploitation of two karstic springs, Bruisseresse and Moulin B, which are overflow springs at the interface between the chalk and estuarine infilling. The mean annual discharges are 720 m³ h⁻¹ for Bruisseresse spring and 540 m³ h⁻¹ for Moulin B spring. The springs drain an 84-km² catchment area (Fig. 1), which is 81% agricultural, 11% forest, and 8% urban. In this area, 3 WWTP, many septic tanks, and manure pits and about two swallow holes per km² have been inventoried. The mean transit time of water in the catchment area is between 8 and 27 h according to the distance. The mean transit velocity ranges between 198 and 218 m h⁻¹, as shown by tracer tests experiments (Fig. 1). This velocity can reach 333 m h⁻¹. After rainfall, turbidity in the springs can reach 180 NTU.

### Hydrological parameters

Turbidity, electrical conductivity, and water height were monitored with a YSI 6920 datasonde (YSI Inc, Letch worth, UK) every 15 min. For the heavy rainfall event,
<figure><img src="image_2.png" /><figcaption>**Fig. 1.** Location of the study site. Moulin B (Mb) and Bruisseresse (Br) are the main outputs of a karstifed chalk aquifer.</figcaption></figure>

water height data were normalized to obtain the variations of water height, which are known to represent the variations of discharge. The relationship between turbidity and electrical conductivity gives improved understanding of the transport of dissolved and suspended matters in response to rainfall events by highlighting the hydrosedimentary processes. The Turbidity-electrical conductivity curves (T-EC curves) were determined after normalization of the data as follows:

$$T_{\text{normalized}} = \frac{(T - T_{\text{min}})}{(T_{\text{max}} - T_{\text{min}})}$$

<table><caption>**Table 1.** Hydrological features of the three sampling periods</caption><thead><tr><th>Sampling periods</th><th>Sampling date (month/year)</th><th>Cumulative rainfall 5 days before sampling (mm)</th><th>Effective rainfall 5 days before sampling (mm)*</th><th>Turbidity at the springs (NTU)†</th></tr></thead><tbody><tr><td>Wet period</td><td>05/2008</td><td>12.9</td><td>3</td><td>Moulin B = 1.5<br>Bruisseresse = 1.4</td></tr><tr><td>Dry period</td><td>06/2009</td><td>0.1</td><td>0</td><td>Moulin B = 0.8<br>Bruisseresse = 1.3</td></tr><tr><td>After the heavy rainfall event</td><td>03/2010</td><td>38.9</td><td>20.7</td><td>Moulin B = [6.2–109.1]<br>Bruisseresse = [3.5–107.9]</td></tr></tbody></table>

$$EC_{\text{normalized}} = \frac{(EC - EC_{\text{max}})}{(EC_{\text{min}} - EC_{\text{max}})}$$

Thus, the slope of the curve indicates the following processes: direct transfer (slope of the curve ≈ 1), resuspension of intrakarstic sediments (slope > 1), or deposition of suspended matter (slope < 1), as adapted for karstic systems by Valdes *et al.* (2006) and Fournier *et al.* (2007).

An Isco 674 tipping bucket rain gauge (Teledyne Isco Inc, Lincoln) in the catchment area (close to the springs) recorded the rainfall. The effective rainfall was calculated on the 5 days before sampling using the SGS model (USDA, Soil Conservation Service, 1972).

## Sample collection

Water samples were collected over 24 h in the two springs during three contrasting hydrological periods (i.e. with or without runoff): on 1 March 2010, after a heavy rainfall event; on 4 May 2008, to represent a wet period; and on 22 June 2009, to represent a dry period (Table 1). About 1 L of water was collected every hour during 24 h with Isco 6700 automatic samplers (Teledyne Isco Inc).

For the wet and dry periods, 300 mL of each sample was mixed together to obtain a sample representing the 24 h of sampling, as is usual in microbiological water analysis. For the heavy rainfall event, however, some hourly samples showed extreme turbidity peaks, so we chose to analyze some of the water samples individually (minimum, maximum, and intermediate turbidity). All microbiological analyses were carried out within 8 h, after collecting the last sample.

## Bacterial enumeration and isolation

*Escherichia coli* were enumerated using membrane filtration (0.45 µm HA047 Millipore, Billerica) with a selective medium specific for *E. coli* (RAPID'E. coli 2 Medium;

<footnote>*Effective rainfall was calculated based on the SGS model and represents the rainfall that is not absorbed by the plants and soils and consequently leads to runoff.</footnote>

<footnote>†During the heavy rainfall event, sampling and measurements were carried out every hour; minima and maxima of turbidity are presented in square brackets, for details see Fig. 2.</footnote>
Biorad, Marnes-la Coquette, France), complemented with a selective supplement for water samples (RAPID'E. coli 2 Supplement; Biorad) and incubated for 24 h at 44 °C. The E. coli were then isolated directly from the characteristic violet colonies on the chromogenically enumerated medium and were then randomly picked out and purified on the same medium. All the purified E. coli isolates were stored at -80 °C with the cryo-bead system (AES laboratory, Bruz, France).

## Antibiotic resistance testing

Antibiotic resistance of E. coli isolates was determined by the agar diffusion method (Comité de l'Antibiogramme de la SFM, 2010) using 16 antibiotic disks (BioMerieux, Craponne, France) corresponding to the drugs most commonly used in veterinary and human medicine against infections caused by gram-negative bacilli: amoxicillin (AMX, 25 µg), amoxicillin+clavulanic acid (AMC, 20 + 10 µg), ticarcillin (TIC, 75 µg), ticarcillin+clavulanic acid (TIM, 75 + 10 µg), imipenem (IPM, 30 µg), cefalotin (CEF, 30 µg), ceftazidim (CAZ, 30 µg), cefotaxim (CTX, 30 µg), gentamycin (GEN, 10 µg), kanamycin (KAN, 30 µg), streptomycin (STR, 10 µg), chloramphenicol (CHL, 30 µg), tetracycline (TET, 30 µg), trimethoprim/sulfamethoxazol (SXT, 75 + 1.25 µg), nalidixic acid (NAL, 30 µg), ciprofloxacin (CIP, 5 µg). After 24 h at 37 °C, the bacteria were classified as sensitive, intermediate, or resistant according to French national guidelines (Comité de l'Antibiogramme de la SFM, 2010). The E. coli CIP 7624 (ATCC 25922) is sensitive for all the antibiotics tested here and so was used as a control. The data were converted into a binary code (resistant or nonresistant, the latter corresponding to sensitive and intermediate phenotypes).

## PCR amplification of integrase genes

intI1, intI2, and intI3 genes were detected by multiplex real-time PCR on a Chromo 4 Real-Time PCR Detector (Biorad) using specific primer pairs previously described by Skurnik *et al.* (2005). Dissociation temperatures for the amplification products obtained with the primer pairs targeting *intI1*, *intI2*, and *intI3* genes were, respectively, 85, 80, and 90 °C. PCR reactions were performed in a final volume of 25 µL containing 1× of MESA Blue qPCR MasterMix Plus for SYBR Assay (Eurogentec, Sering, Belgium) with 250 ng of each primer and 2 µL of bacterial suspension. A denaturation cycle of 10 min at 95 °C was followed by 30 cycles of 15 s at 95 °C and 60 s at 60 °C. When the *intI1* and/or *intI2* genes were detected by real-time PCR, classic PCR was carried out to confirm the results with other specific primers: intI1.F/

intI1.R (Bass *et al.*, 1999) for the class 1 integrase and intI2.F/intI2.R (Mazel *et al.*, 2000) for the class 2 integrase, as described by the authors.

## Amplification and sequencing of gene cassette regions

The variable regions of class 1 and class 2 integrons were amplified as previously described by Laroche *et al.* (2009). Single-stranded DNA sequencing of all PCR products was carried out by GATC Society (Konstanz, Germany) and Genoscreen (Lille, France). Nucleotide sequences were deposited in GenBank under the accession number mentioned in Table 6.

## Statistical analyzes

All statistical analyzes were performed using XL-STAT (version 6.0, Addinsoft), and a P-value below 0.10 (*), 0.5 (**), and 0.1 (***), was considered significant (details in Tables). Fisher's exact chi-squared-test was performed to determine whether the percentages of E. coli resistant to 1, 2...10 antibiotics were similar or not in the individual samples. The chi-squared test was then performed again to determine whether the proportion of each subpopulation was significantly different in the samples.

## Results

### Fecal contamination of the springs

#### E. coli densities during wet and dry periods

During the wet period, E. coli density reached 22 and 59 CFU for 100 mL at Moulin B and Bruisseresse springs, respectively (Table 2). During the dry period, the E. coli densities for these springs were much lower: 1.7 CFU for 100 mL (Moulin B spring) and < 1 CFU for 100 mL (Bruisseresse spring). These results indicate that, even if there is a permanent circulation of E. coli, hydrological conditions play a major role in the occurrence of E. coli in spring waters.

#### Turbidity, electrical conductivity, water height variations, and E. coli data for the heavy rainfall event

In addition to E. coli density, turbidity and electrical conductivity were also monitored in the samples from the heavy rainfall event, and their variations were found to be complex (Fig. 2). Here, we first notice an increase in the water height in the two springs, suggesting an increase in the discharge and consequently that surface water had
<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Temporal evolution of turbidity, electrical conductivity, water height variations and *Escherichia coli* density during the heavy rainfall event in Moulin B (a) and Bruisseresse (b) springs. The turbidity is shown as (—), the electrical conductivity as (—), water height variations as (—) the rainfall as (||), and *E. coli* density as (-●-). The vertical black lines delimit the 24-h sampling period. T-EC curves were calculated as already reported by Fournier et al., 2007, and are represented as (→) and the samples analyzed are represented as (▲). H5, H7...represent the sample collected 5, 7... h after the beginning of collection.</figcaption></figure>

<table><caption>**Table 2.** Antibiotic resistance and multiresistance of *Escherichia coli* isolated from wet and dry periods</caption><thead><tr><th rowspan="2">Sampling periods</th><th rowspan="2">Springs</th><th rowspan="2">E. coli density<br>(CFU 100 mL<sup>-1</sup>)</th><th rowspan="2">Percentage of<br>antibiotic-resistant<br>isolates (%) (n*/n<sup>‡</sup>)</th><th colspan="9">Distribution of resistant E. coli isolates (n<sup>‡</sup>/n*) (%)</th></tr><tr><th>1R</th><th>2R</th><th>3R</th><th>4R</th><th>5R</th><th>6R</th><th>7R</th><th>8R</th><th>9R</th></tr></thead><tbody><tr><td rowspan="2">Dry period</td><td>Moulin B</td><td>1.67</td><td>6.2 (1/16)</td><td>100.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>Bruisseresse</td><td>&lt; 1</td><td>0 (0/11)</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td rowspan="2">Wet period</td><td>Moulin B</td><td>22</td><td>65.4 (17/26)</td><td>47.1</td><td>23.5</td><td>11.8</td><td>0.0</td><td>5.9</td><td>5.9</td><td>5.9</td><td>0.0</td><td>0.0</td></tr><tr><td>Bruisseresse</td><td>59</td><td>53.1 (26/49)</td><td>53.8</td><td>0.0</td><td>0.0</td><td>3.8</td><td>0.0</td><td>19.2</td><td>3.8</td><td>7.7</td><td>11.5</td></tr></tbody></table>

arrived in the system. We observe a faster and greater turbid response in the Moulin B spring with a small decrease in electrical conductivity, and then a decline in the height of the turbidity peaks. In the case of the

Bruisseresse spring, the maximum turbidity can be seen at the second peak of turbidity, with the greatest decrease in electrical conductivity. Comparison of the normalized T-EC curves shows differences in the hydrological functioning

<footnote>*No. of *E. coli* resistant to one or more antibiotic(s).</footnote>

<footnote>†No. of *E. coli* isolates analyzed.</footnote>

<footnote>‡No. of *E. coli* isolates resistant to 1, 2, 3...9 antibiotic(s).</footnote>
of the two springs. Overall, in the Bruisseresse spring, there is a major contribution of direct transfers, while in the Moulin B spring, we see significant resuspension at the beginning of the sampling period.

During the sampling period at the Bruisseresse spring site, the increase in the *E. coli* density to 1.4.10³ CFU per 100 mL is consistent with the increased turbidity (Fig. 2 and Table 3). This relationship is less evident in the sampling conducted in the Moulin B spring, where we notice a high density of *E. coli* (up to 4.2.10² CFU per 100 mL) only during the fourth peak of turbidity. Thus, sample H21 does not present the greatest turbidity, but corresponds to the maximum contribution of surface waters.

## Antibiotic resistance and multiresistance of the *E. coli* populations

### Wet and dry periods (averaged daily samples)

Among the 27 *E. coli* isolated from the two springs during the dry period only one resistant isolate was found, and this was resistant to a single antibiotic (Table 2). In contrast, during the wet period, a high level of resistance was observed in the *E. coli* population. Indeed, the percentages of *E. coli* isolates resistant to at least one antibiotic reached 65.4% and 53.1% for Moulin B and Bruisseresse springs, respectively. These resistant isolates were characterized by between 1 and 9 resistances to the antibiotics tested. We observed that 29.5% (Moulin B spring) and 46% (Bruisseresse spring) of the antibiotic-resistant *E. coli* carried resistances to three or more antibiotics, reaching nine resistances for three isolates (Table 2).

### Evolution of the antibiotic resistance of *E. coli* populations isolated after the heavy rainfall event (individual samples)

After the heavy rainfall event, we analyzed some of the individual samples collected over 24 h, and the results are presented in Table 3. In all analyzed water samples, *E. coli* isolates resistant to one or more antibiotics were present, representing between 29.2% and 60.0% of the isolates for Moulin B spring and between 17% and 66.7% for Bruisseresse spring. The percentages of antibiotic-resistant isolates were highest at the beginning of the sampling period for the two springs, as shown in samples H5 (60.0%) and H7 (66.7%), and so did correspond neither to the density maxima nor to the electrical conductivity minima.

More precisely, the results show that most of the resistant isolates carried only 1 or 2 antibiotic resistances (Table 3). This subpopulation, which we define as the R1-2 subpopulation, was found throughout the sampling period in all the water samples of the two springs,

<table><caption>**Table 3.** Antibiotic resistance and multiresistance of the *Escherichia coli* isolated after the heavy rainfall event</caption><thead><tr><th rowspan="2">Springs</th><th rowspan="2">Sampling hour<sup>†</sup></th><th rowspan="2">E. coli density<br>(CFU 100 mL<sup>-1</sup>)</th><th rowspan="2">Percentage of<br>antibiotic-resistant<br>isolates (n<sup>†</sup>/n<sup>‡</sup>)</th><th colspan="9">Distribution of resistant E. coli isolates (n<sup>†</sup>/n<sup>‡</sup>) (%)</th></tr><tr><th>1R</th><th>2R</th><th>3R</th><th>4R</th><th>5R</th><th>6R</th><th>7R</th><th>8R</th><th>9R</th><th>10R</th></tr></thead><tbody><tr><td rowspan="7">Moulin B</td><td>H5</td><td>1.4 x 10<sup>2</sup></td><td>60.0** (18/30)</td><td>38.9**</td><td>16.7</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>11.1</td><td>0.0</td><td>16.7**</td><td>16.7**</td><td>0.0</td></tr><tr><td>H7</td><td>3.7 x 10<sup>2</sup></td><td>56.0 (5/9)</td><td>80.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H12</td><td>1.9 x 10<sup>2</sup></td><td>36.7 (11/30)</td><td>81.8</td><td>18.2</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H21</td><td>4.2 x 10<sup>2</sup></td><td>48.0 (11/23)</td><td>90.9</td><td>9.1</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H24</td><td>3.0 x 10<sup>2</sup></td><td>36.0 (12/36)</td><td>75.0</td><td>8.3</td><td>0.0</td><td>0.0</td><td>0.0</td><td>8.3</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H72</td><td>2.1 x 10<sup>2</sup></td><td>29.2 (7/24)</td><td>42.9</td><td>42.9</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>14.3</td></tr><tr><td>H4</td><td>1.0 x 10<sup>2</sup></td><td>44.9 (22/49)</td><td>36.4</td><td>9.1***</td><td>13.6*</td><td>22.7**</td><td>4.5</td><td>9.1</td><td>0.0</td><td>4.5</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td rowspan="7">Bruisseresse</td><td>H7</td><td>1.7 x 10<sup>2</sup></td><td>66.7*** (32/48)</td><td>43.8</td><td>40.6</td><td>0.0</td><td>9.4</td><td>0.0</td><td>3.1</td><td>3.1</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H9</td><td>3.5 x 10<sup>2</sup></td><td>41.5 (17/41)</td><td>23.5</td><td>70.6***</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.9</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H11</td><td>1.4 x 10<sup>2</sup></td><td>17.0*** (8/47)</td><td>87.5**</td><td>12.5</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H16</td><td>7.1 x 10<sup>2</sup></td><td>31.9 (15/47)</td><td>40.0</td><td>46.7</td><td>6.7</td><td>0.0</td><td>0.0</td><td>6.7</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H24</td><td>7.1 x 10<sup>2</sup></td><td>31.9 (15/47)</td><td>33.3</td><td>46.7</td><td>6.7</td><td>6.7</td><td>0.0</td><td>6.7</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>H72</td><td>1.3 x 10<sup>2</sup></td><td>27.3 (6/22)</td><td>100.0**</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr></tbody></table>

Significant differences between percentages of resistance from samples of each spring, determined by the chi-square test of Fisher (*α* = 10%, **α* = 5%, ***α* = 1%).

†H5, H7... represent the sample collected 5, 7... h after the beginning of collection.

‡No. of *E. coli* resistant to one or more antibiotic(s).

§No. of *E. coli* isolates analyzed.

¶% of *E. coli* isolates resistant to 1, 2, 3...9 antibiotic(s).
representing from 45.5% (Bruisseresse spring, sample H4) to 100% (various samples) of the antibiotic-resistant population (Table 3). Another antibiotic-resistant subpopulation, characterized by between 3 and 10 and which we call the R3-10 subpopulation, was also found after the rainfall event, but transiently (Table 3). The proportion of this multiresistant subpopulation was significantly higher in the first samples of the sampling period in the two springs. Of the antibiotic-resistant *E. coli* populations isolated from Moulin B spring, sample H5, and Bruisseresse spring, sample H4, 44.5% and 54.4%, respectively, were resistant to between 3 and 9 antibiotics (Table 3). This R3-10 subpopulation decreased gradually as *E. coli* density increased; at maximum density, it disappeared completely. Low percentages were then found in some of the later samples, at the end of the sampling period, representing 16.6% (sample H24) and 14.3% (sample H72) of antibiotic-resistant *E. coli* for Moulin B spring and 13.4% (sample H16) and 20.1% (sample H24) for Bruisseresse spring.

## Antibiotic resistance patterns

The antibiotic resistance patterns of the *E. coli* isolated during the wet period and the heavy rainfall event are presented in Table 4. The R1-2 subpopulation of *E. coli* is characterized almost exclusively by resistances to only two antibiotics: tetracycline and/or chloramphenicol. Indeed, among the 171 *E. coli* of the R1-2 subpopulation isolated during the wet period and after the heavy rainfall event in Moulin B and Bruisseresse springs, 165 were resistant to chloramphenicol and/or tetracycline (96.5%). The occasionally found resistances were to ciprofloxacin (only one isolate), to streptomycin (only one isolate), and to sulfamethoxazol/trimethoprim (for four isolates). The only antibiotic-resistant *E. coli* isolated from the dry period was resistant to chloramphenicol.

In the R3-10 subpopulation, resistances to all tested antibiotic classes were observed. The highest occurrences were to tetracycline, amoxicillin, and ticarcillin. Indeed, among the 51 *E. coli* isolates of this R3-10 subpopulation, 48 carried the tetracycline resistance (94.1%) and 43 carried both amoxicillin and ticarcillin resistances (86%). These major resistances were sometimes associated with resistances to aminosides, quinolones, sulfamides, and/or chloramphenicol. This multiresistant subpopulation is characterized by a great diversity of antibiotic resistance patterns, but always with one or more of the three major antibiotic resistances defined above.

## Detection of class 1, 2, and 3 integrons

For this purpose, we tested all the 297 *E. coli* isolated from the averaged dry period sample, the averaged wet

period sample, and three of the individual samples collected at each spring after the heavy rainfall event (at the beginning and at the end of the sampling period, and when *E. coli* density was maximal), regardless of their resistance profiles (Table 5). No integrons were present in the strains isolated from the dry period sample. Occurrences of class 1 integrases in the *E. coli* population from the wet period and after the heavy rainfall event ranged between 2.0% (1 isolate/50, Bruisseresse spring, sample H11) and 18.4% (9 isolates/49, Bruisseresse spring, wet period) (Table 5). Only one class 2 integrase was detected in one sample of the heavy rainfall event, at the Bruisseresse spring, sample H11 (2%). No class 3 integrons were detected among the 297 *E. coli* tested in this study.

## Characteristics of the class 1 and 2 integrons identified

The presence of gene cassettes in the variable region was investigated for the 16 class 1 integrons and the class 2 integron. The variable regions of class 1 integrons were characterized by short sizes, and we found only one or two cassettes (Table 6). The size of the variable regions was estimated at about 1500 bp for 10 of the class 1 integrons and at 900 bp for two others. As shown in Table 6, all the amplified variable regions carried the *aadA1* gene encoding an aminoglycoside adenyltransferase and conferring resistance to streptomycin/spectinomycin, often associated with the *dfrA1* gene encoding dihydrofolate reductase, which confers resistance to trimethoprim. For the remaining four class 1 integrons, we were unable to amplify the variable region. The variable region of the class 2 integron was largest (4700 bp), a size similar to that reported by Laroche *et al*. (2009), who also found the three cassettes characteristic of class 2 integrons in the transposon *Tn7* (*dfrA1*, *satI*, and *aadA1*).

Class 1 integrons were mainly detected in the R3-10 subpopulation isolates (93.7%), which carried between 3 and 10 antibiotic resistances, except for one, which was sensitive to all the antibiotics tested. However, for this sensitive isolate, no variable region was amplified in the class 1 integron, although the presence of the *intI1* integrase gene was confirmed with the primers described by Bass *et al*. (1999). The class 2 integron was detected in an R1-2 *E. coli* isolate carrying resistances to streptomycin associated with tetracycline.

## Discussion

In this work, we studied fecal contamination in two springs of a karstified chalk system by investigating *E. coli* density and determining the antibiotic resistance patterns of the isolates during three different hydrological periods.
<table><caption>**Table 4.** Antibiotic resistance patterns of the *Escherichia coli* isolated during the sampling periods</caption><thead><tr><th rowspan="3">Study site</th><th rowspan="3">Sampling period</th><th rowspan="3">Sampling Hour</th><th colspan="3">Antibiotic-resistant <i>E. coli</i> subpopulations</th><th rowspan="3">Percentage of isolates carrying the pattern (n†/n‡)</th><th rowspan="3">Antibiotic resistance pattern</th><th rowspan="3">Percentage of isolates carrying the pattern (n†/n‡)</th></tr><tr><th colspan="2">R1-2</th><th>R3-10*</th></tr><tr><th>Antibiotic resistance pattern</th><th>Percentage of isolates carrying the pattern (n†/n‡)</th><th>Antibiotic resistance pattern</th></tr></thead><tbody><tr><td rowspan="10">Moulin B</td><td>Dry period</td><td>–</td><td>CHL</td><td>100 (1/1)</td><td>CHL-TET-CIP</td><td>11.8 (2/17)</td><td></td></tr><tr><td rowspan="4">Wet period</td><td>–</td><td>CHL</td><td>35.3 (6/17)</td><td>CHL-TET-NAL-CIP-STR</td><td>5.9 (1/17)</td><td></td></tr><tr><td>–</td><td>TET</td><td>11.8 (2/17)</td><td>AMX-AMC-TIC-TIM-CHL-TET</td><td>5.9 (1/17)</td><td></td></tr><tr><td>H5</td><td>CHL-TET</td><td>17.6 (3/17)</td><td>AMX-AMC-TIC-TIM-CHL-TET-SXT</td><td>5.9 (1/17)</td><td></td></tr><tr><td>CHL-TET</td><td>CHL-TIC-TIM-CHL-TET-NAL-CIP-STR</td><td>5.9 (1/17)</td><td>AMX-AMC-TIC-TET-NAL-CIP-STR</td><td>11.1 (2/18)</td><td></td></tr><tr><td>Heavy rainfall</td><td>H5</td><td>CHL</td><td>11.1 (2/18)</td><td>AMX-AMC-TIC-TIM-TET-NAL-CIP-STR</td><td>11.1 (2/18)</td><td></td></tr><tr><td rowspan="2">event</td><td>TET</td><td>CHL-TET</td><td>27.8 (5/18)</td><td>AMX-AMC-TIC-TIM-TET-NAL-CIP-STR</td><td>5.5 (1/18)</td><td></td></tr><tr><td>H7</td><td>CHL</td><td>16.7 (3/18)</td><td>AMX-AMC-TIC-TIM-KAN-CHL-TET-STR</td><td>16.7 (3/18)</td><td></td></tr><tr><td>H12</td><td>CHL-TET</td><td>20.0 (1/5)</td><td></td><td></td><td></td><td></td></tr><tr><td>H21</td><td>CHL-TET</td><td>60.0 (3/5)</td><td></td><td></td><td></td><td></td></tr><tr><td>H24</td><td>CHL-TET</td><td>20.0 (1/5)</td><td></td><td></td><td></td><td></td></tr><tr><td>H72</td><td>CHL-TET</td><td>81.8 (9/11)</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>TET</td><td>18.2 (2/11)</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>TET</td><td>45.4 (5/11)</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>TET</td><td>45.4 (5/11)</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>CHL-TET</td><td>9.1 (1/11)</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>TET</td><td>75.0 (9/12)</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>CHL-TET</td><td>8.3 (1/12)</td><td></td><td>KAN-TET-SXT</td><td>8.3 (1/12)</td><td></td></tr><tr><td></td><td>CHL</td><td>28.6 (2/7)</td><td></td><td>AMX-AMC-TIC-TIM-CHL</td><td>8.3 (1/12)</td><td></td></tr><tr><td></td><td>TET</td><td>14.3 (1/7)</td><td></td><td>AMX-AMC-TIC-TIM-GEN-KAN-CHL-TET-SXT-STR</td><td>14.3 (1/7)</td><td></td></tr><tr><td></td><td>CHL-TET</td><td>42.8 (3/7)</td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>**Table 4. Continued**</caption><thead><tr><th rowspan="3">Study site</th><th rowspan="3">Sampling period</th><th rowspan="3">Sampling Hour</th><th colspan="3">Antibiotic-resistant E. coli subpopulations</th><th rowspan="3">Percentage of isolates carrying the pattern (n†/n‡)</th><th rowspan="3">Antibiotic resistance pattern</th><th rowspan="3">Percentage of isolates carrying the pattern (n†/n‡)</th></tr><tr><th colspan="2">R1-2</th><th rowspan="2">R3-10*</th></tr><tr><th>Antibiotic resistance pattern</th><th>Percentage of isolates carrying the pattern (n†/n‡)</th></tr></thead><tbody><tr><td rowspan="10">Bruisseresse</td><td rowspan="10">Wet period</td><td>—</td><td>CHL</td><td>46.1 (12/26)</td><td>AMX-AMC-TIC-TIM</td><td>3.8 (1/26)</td></tr><tr><td rowspan="10">Heavy rainfall event</td><td rowspan="10">H4</td><td>TET</td><td>7.7 (2/26)</td><td>AMX-TIC-TET-SXT-NAL-STR</td><td>15.3 (4/26)</td></tr><tr><td>CHL</td><td>13.6 (3/22)</td><td>AMX-AMC-TIC-TIM-TET-STR</td><td>3.8 (1/26)</td></tr><tr><td>TET</td><td>22.7 (5/22)</td><td>AMX-TIC-TET-SXT-NAL-CIP-STR</td><td>3.8 (1/26)</td></tr><tr><td>CHL-TET</td><td>9.1 (2/22)</td><td>AMX-AMC-TIC-TIM-TET-NAL-CIP-STR</td><td>7.7 (2/26)</td></tr><tr><td>CHL</td><td>13.6 (3/22)</td><td>AMX-AMC-TIC-TIM-TET-SXT-NAL-CIP-STR</td><td>3.8 (1/26)</td></tr><tr><td>TET</td><td>22.7 (5/22)</td><td>AMX-AMC-TIC-TIM-TET-SXT-NAL-STR</td><td>7.7 (2/26)</td></tr><tr><td>TET-SXT-STR</td><td>4.5 (1/22)</td><td>TET-NAL-CIP</td><td>4.5 (1/22)</td></tr><tr><td>TET-TIC-TET</td><td>4.5 (1/22)</td><td>AMX-TIC-TIC-KAN-TET-STR</td><td>4.5 (1/22)</td></tr><tr><td>CHL-TET</td><td>22.7 (5/22)</td><td>AMX-TIC-KAN-TET-SXT-STR</td><td>4.5 (1/22)</td></tr><tr><td rowspan="10">H7</td><td rowspan="10">H9</td><td>CHL</td><td>15.6 (5/32)</td><td>AMX-TIC-KAN-TET-SXT-STR</td><td>4.5 (1/22)</td></tr><tr><td>TET</td><td>28.1 (9/32)</td><td>AMX-TIC-GEN-KAN-TET-EXT-STR</td><td>4.5 (1/22)</td></tr><tr><td>CHL-TET</td><td>40.6 (13/32)</td><td>AMX-TIC-KAN-TET-SXT-STR</td><td>4.5 (1/22)</td></tr><tr><td>TET</td><td>11.8 (2/17)</td><td>AMX-TIC-KAN-TET-SXT-STR</td><td>4.5 (1/22)</td></tr><tr><td>TET</td><td>11.8 (2/17)</td><td>AMX-AMC-TIC-TIM-CEF-KAN-TET-STR</td><td>4.5 (1/22)</td></tr><tr><td>CHL-TET</td><td>70.6 (12/17)</td><td>AMX-TIC-CHL-TET</td><td>9.4 (3/32)</td></tr><tr><td>TET</td><td>75.0 (6/8)</td><td>AMX-TIC-KAN-TET-SXT-STR</td><td>3.1 (1/32)</td></tr><tr><td>TET</td><td>12.5 (1/8)</td><td>AMX-TIC-GEN-KAN-TET-EXT-STR</td><td>3.1 (1/32)</td></tr><tr><td>TET-STR</td><td>12.5 (1/8)</td><td>AMX-TIC-KAN-TET-SXT-STR</td><td>5.8 (1/17)</td></tr><tr><td>H16</td><td>H11</td><td>CHL</td><td>6.7 (1/15)</td><td>CHL-TET-SXT</td><td>6.7 (1/15)</td></tr><tr><td rowspan="10">H24</td><td rowspan="10">H72</td><td>CHL</td><td>26.6 (4/15)</td><td>AMX-TIC-KAN-TET-SXT-STR</td><td>6.7 (1/15)</td></tr><tr><td>TET</td><td>6.7 (1/15)</td><td>CHL-TET-SXT</td><td>6.7 (1/15)</td></tr><tr><td>TET</td><td>6.7 (1/15)</td><td>AMX-TIC-CHL-TET</td><td>6.7 (1/15)</td></tr><tr><td>CHL-TET</td><td>26.6 (4/15)</td><td>AMX-TIC-CHL-TIM-CEF-KAN-TET-STR</td><td>6.7 (1/15)</td></tr><tr><td>CHL-TET</td><td>46.6 (7/15)</td><td>CHL-TET-SXT</td><td>6.7 (1/15)</td></tr><tr><td>CHL</td><td>26.6 (4/15)</td><td>AMX-TIC-CHL-TET</td><td>6.7 (1/15)</td></tr><tr><td>SXT</td><td>6.7 (1/15)</td><td>AMX-TIC-CHL-TET</td><td>6.7 (1/15)</td></tr><tr><td>CHL-TET</td><td>46.6 (7/15)</td><td>CHL-TIC-TIC-KAN-TET-EXT-STR</td><td>6.7 (1/15)</td></tr><tr><td>CHL</td><td>26.6 (4/15)</td><td>CHL-TIC-TIC-KAN-TET-SXT-STR</td><td>6.7 (1/15)</td></tr><tr><td>CHL-SXT</td><td>20.0 (3/15)</td><td>CHL-TIC-TIC-KAN-TET-SXT-STR</td><td>6.7 (1/15)</td></tr><tr><td>CHL</td><td>83.3 (5/6)</td><td>CHL-TIC-TIC-KAN-TET-SXT-STR</td><td>6.7 (1/15)</td></tr><tr><td>TET</td><td>16.7 (1/6)</td><td>CHL-TIC-TIC-KAN-TET-SXT-STR</td><td>6.7 (1/15)</td></tr></tbody></table>

*R3-9 for the wet period and R3-10 for the heavy rainfall event (see text for abbreviations).

†No. of E. coli carrying this pattern.

‡No. of E. coli resistant to one or more antibiotic(s).
<table><caption>**Table 5.** Occurrences of class 1, 2, and 3 integrons</caption><thead><tr><th rowspan="2">Sampling periods</th><th rowspan="2">Site and sampling hour</th><th rowspan="2">No. of isolates</th><th colspan="3">Percentages of isolates carrying genes of</th></tr><tr><th>intl</th><th>intl2</th><th>intl3</th></tr></thead><tbody><tr><td rowspan="2">Dry period</td><td>Moulin B</td><td>16</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>Bruisseresse</td><td>11</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td rowspan="2">Wet period</td><td>Moulin B</td><td>26</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>Bruisseresse</td><td>49</td><td>18.4*</td><td>0.0</td><td>0.0</td></tr><tr><td rowspan="6">After the heavy rainfall event</td><td>Moulin B H5</td><td>30</td><td>6.7</td><td>0.0</td><td>0.0</td></tr><tr><td>Moulin B H21</td><td>22</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>Moulin B H72</td><td>24</td><td>4.2</td><td>0.0</td><td>0.0</td></tr><tr><td>Bruisseresse H4</td><td>47</td><td>6.4</td><td>0.0</td><td>0.0</td></tr><tr><td>Bruisseresse H11</td><td>50</td><td>2.0</td><td>2.0</td><td>0.0</td></tr><tr><td>Bruisseresse H72</td><td>22</td><td>0.0</td><td>0.0</td><td>0.0</td></tr></tbody></table>

Results show that fecal contamination and the presence of resistant *E. coli* are strongly dependent on surface water arrivals in the system, especially during and after rainfall events.

For the dry period, a very low *E. coli* density was observed in the two springs, but this still shows that there is a permanent circulation of *E. coli* in the groundwater, as previously reported (Leber *et al.*, 2011). Of the 27 *E. coli* isolated from the two springs during this period, only one was resistant, indicating that when no runoff occurs, the *E. coli* population circulating permanently in the karstic system remains sensitive to the 16 antibiotics

tested. This sensitive fecal population could come from contamination that is independent of human or breeding activities, that is, from organisms such as wildlife not submitted to veterinary and human medicine.

For the wet period, *E. coli* density was slightly higher on average, but the highest density was observed after the heavy rainfall event. This fecal contamination was associated with an increase in turbidity and water height and a decrease in electrical conductivity in the two springs, indicating surface water arrivals in the karstic system. During the wet period and the heavy rainfall event, occurrences of antibiotic-resistant *E. coli* in the two springs were very high. Moreover, some isolates carried up to 10 resistances. These results are consistent with previous work carried out by Laroche *et al.* (2010). In a small rural karstified chalk system, the authors studied the contamination of a well and a spring by antibiotic-resistant *E. coli*. They showed that the resistant population was observed only after runoff phenomena, but multiresistant *E. coli* were isolated only when turbidity and *E. coli* density reached their maximal value. This observation is in contrast to the present study in which the multiresistant isolates were associated neither with maximal turbidity nor with the highest *E. coli* density. These differences indicate that *E. coli* density alone cannot discriminate between the different fecal populations, whereas resistance patterns could show the origins of fecal contaminations and their kinetics of arrivals in the karsts. So, according to the number and the type of resistances carried, we characterized two sub-populations: the R1-2 and R3-10.

<table><caption>**Table 6.** Characteristics of class 1 and 2 integrons detected in *Escherichia coli* isolated from groundwater</caption><thead><tr><th colspan="2">Antibiotic resistances tested</th><th colspan="5">Variable region of the integron</th></tr><tr><th>No of resistances</th><th>Resistance patterns</th><th>No of isolates</th><th>intl gene</th><th>Size of amplicon (bp)</th><th>Gene cassette array</th><th>GenBank accession number</th></tr></thead><tbody><tr><td>10</td><td>AMX-AMC-TIC-TIM-GEN-KAN-CHL-TET-SXT-STR</td><td>1</td><td>1</td><td>ND</td><td>–</td><td></td></tr><tr><td>9</td><td>AMX-AMC-TIC-TIM-TET-SXT-NAL-CIP-STR</td><td>1</td><td>1</td><td>1500</td><td>dfrA1 – aadA1</td><td>JN814912</td></tr><tr><td>9</td><td>AMX-AMC-TIC-TIM-CHL-TET-SXT-NAL-STR</td><td>2</td><td>1</td><td>1500</td><td>dfrA1 – aadA1</td><td>JN814913/JN814918</td></tr><tr><td>9</td><td>AMX-AMC-TIC-TIM-CHL-TET-NAL-CIP-STR</td><td>1</td><td>1</td><td>900</td><td>aadA1</td><td>JN814923*</td></tr><tr><td>8</td><td>AMX-AMC-TIC-TIM-TET-SXT-NAL-STR</td><td>2</td><td>1</td><td>1500</td><td>dfrA1 – aadA1</td><td>JN814917</td></tr><tr><td>8</td><td>AMX-AMC-TIC-TIM-TET-NAL-CIP-STR</td><td>1</td><td>1</td><td>ND</td><td>–</td><td></td></tr><tr><td>7</td><td>AMX-TIC-TET-SXT-NAL-CIP-STR</td><td>1</td><td>1</td><td>1500</td><td>dfrA1 – aadA1</td><td>JN814915</td></tr><tr><td>6</td><td>AMX-TIC-TET-SXT-NAL-STR</td><td>3</td><td>1</td><td>1500</td><td>dfrA1 – aadA1</td><td>JN814919/JN814920/JN814914</td></tr><tr><td>6</td><td>AMX-TIC-KAN-TET-SXT-STR</td><td>1</td><td>1</td><td>ND</td><td>–</td><td></td></tr><tr><td>5</td><td>AMX-TIC-KAN-TET-STR</td><td>1</td><td>1</td><td>900</td><td>aadA1</td><td>JN814922*</td></tr><tr><td>3</td><td>TET-SXT-STR</td><td>1</td><td>1</td><td>1500</td><td>dfrA1b – aadA1b</td><td>JN814921†</td></tr><tr><td>2</td><td>TET-STR</td><td>1</td><td>2</td><td>4700</td><td>dfrA1 – sat1 – aadA1</td><td>JQ480156</td></tr><tr><td>0</td><td>–</td><td>1</td><td>1</td><td>ND</td><td>–</td><td></td></tr></tbody></table>

We cannot amplify the variable region of these integrons.

ND, not determined.

<footnote>*Significant difference between percentages of integrons, determined by the chi-square test of Fisher (α = 1%).</footnote>

<footnote>*Type In2, Integrall database (Moura *et al.*, 2009).</footnote>

<footnote>†Type In369, Integrall database. *dfrA1b* and *aadA1b* are gene variants of *dfrA1* and *aadA1*.</footnote>
The R1-2 subpopulation carried one or two resistance (s), mainly to tetracycline and chloramphenicol, and was present during the wet period and throughout the heavy rainfall event, representing at least a half of the antibiotic-resistant *E. coli* population. These patterns of resistance to only one or two antibiotics have already been reported by several authors and are often linked to agricultural areas. Servais & Passerat (2009) focused on the antibiotic resistance of *E. coli* isolated in the river Seine and in various sources of contamination, such as hospital wastewater or agricultural runoff. The authors reported that 84% of the *E. coli* isolated from agricultural runoff were sensitive, while most of the resistant isolates carried only one or two resistances. Furthermore, in their study on *E. coli* isolated from various animal fecal samples, human septic, and surface water, Sayah *et al.* (2005) found chloramphenicol-resistant isolates only in fecal samples from animals and in the farm environment. Similar resistance patterns were found in *E. coli* isolated from bovine dung (Laroche *et al.*, 2010). The high occurrence of chloramphenicol resistance must be pointed out because this antibiotic is no longer used in veterinary medicine. Nevertheless, this result could be explained by (1) previous use of chloramphenicol to treat bacterial infections in animals, this antibiotic being rarely used for human therapy, (2) the potential selection for chloramphenicol resistance by florphenicol, a fluorinated derivative of chloramphenicol currently used in veterinary medicine (Schwarz *et al.*, 2004; Agence Française de Sécurité Sanitaire des Aliments, 2005), or (3) coselection of resistance genes carried by the same genetic support. All these results strongly suggest that the R1-2 subpopulation is introduced into the karstic system by runoff from pasture occupied by ruminants.

The R3-10 subpopulation was observed only during the wet period and after the heavy rainfall event and was present in lower proportions. Nevertheless, about half the antibiotic-resistant *E. coli* were multiresistant in the Moulin B spring, sample H5, and Bruisseresse spring, sample H4. The multiresistant isolates were characterized by a large diversity of resistances, but tetracycline and β-lactam resistances were always found. These major resistances were always associated with at least one other resistance, and sometimes several: quinolones, aminosides, sulfamides, chloramphenicol, in any combination. These resistance patterns and this high number of resistances are always found in WWTP effluents and in the aquatic environments contaminated by these effluents (Reinthaler *et al.*, 2003; Ferreira da Silva *et al.*, 2007; Laroche *et al.*, 2009; Luczkiewicz *et al.*, 2010; Ibekwe *et al.*, 2011). Reinthaler *et al.* (2003) reported that the most frequent resistances found in *E. coli* isolated from WWTP effluents were to tetracycline, cephalotin, and ampicillin. In the

Seine estuary, which is strongly contaminated by WWTP effluents, Laroche *et al.* (2009) found that the major resistances of multiresistant *E. coli* were to amoxicillin, ticarcillin, and tetracycline. Luczkiewicz *et al.* (2010) also confirmed all the previous results, showing that *E. coli* isolated from a municipal WWTP were mostly resistant to tetracycline (23%), ampicillin (34%), piperacillin (24%), sulfamethoxazol/trimethoprim (11.1%), and ciprofloxacin (10.5%). Thus, the most likely hypothesis for the origin of the R3-10 subpopulation is a contamination by WWTP effluents. Nevertheless, because of the lack of information in the literature concerning septic tanks and manure pits, we cannot exclude the possibility that the origin could be a reservoir containing a high quantity of feces from many individuals (humans and/or animals), allowing horizontal bacterial gene transfers.

The proportions of the two resistant *E. coli* subpopulations were not identical throughout the sampling period in Moulin B and Bruisseresse springs, especially for the multiresistant subpopulation. The R3-10 subpopulation was found at high percentages in the first samples, was absent when *E. coli* density was maximal (Moulin B spring, sample H21, and Bruisseresse spring, sample H11), and was recovered in lower proportions at the end of the sampling period, whereas the R1-2 subpopulation was always present in high proportions. Thus, the relative changes between the two subpopulations could be due to (1) continuous contamination by wastewater effluents, diluted by a large volume of water introduced into the karstic aquifer after pasture runoff during periods of rain, (2) transient activation, in some particular discharge conditions, of a connection with surface water contaminated by a WWTP or septic tank that is not functioning properly, or (3) resuspension of resistant *E. coli* present in the karstic drains, previously deposited by very recent outputs of suspended matter (autochthonous turbidity). In the T-EC curves, for the Moulin B spring, we observed resuspension to begin with and then direct transfers, whereas for the Bruisseresse spring, there was very little, if any, resuspension, and we noticed only direct transfers. However, in both springs, the highest proportions of the R3-10 subpopulations were observed at the beginning of the sampling period when the water height increased. So, this result indicates that the multiresistant subpopulation was not introduced in the springs by resuspension, but rather via direct transfers. Reischer *et al.* (2008) showed that the major source of contamination could be linked to the ruminants during a rainfall event. They used quantification of *Bacteroidetes* markers as well as the *E. coli* count to track the source of contamination in a catchment area and reported that 80% of the variations of the *E. coli* count during the rainfall event could be explained by variations of ruminant-specific markers.
The use of bacterial antibiotic resistance as a specific
marker to probe the origin of fecal contamination is con-
troversial because of resistance gene coselection, genetic
transfers, and the diversity in the use of antibiotics (Scott
et al., 2002; Field & Samadpour, 2007). However, the
present study suggests that the analysis of resistance pat-
terns could distinguish the fecal bacteria originating from
(1) areas of extensive feces mixtures (WWTP, septic
tanks, manure pits) allowing horizontal transfers and
facilitating the emergence of multiresistant bacteria
(R3-10 subpopulation), (2) runoff from pasture (R1-2
subpopulation), or (3) animals not submitted to antibi-
otic treatment (an exclusive or predominant sensitive
phenotype of the bacterial population studied).

We investigated class 1, 2, and 3 integrons to evaluate
their involvement in the construction of the multiresis-
tant isolates and their occurrences in the two subpopula-
tions. The occurrences of class 1 integrons in the E. coli
population tested are close to the results generally
reported in WWTP effluents or in aquatic environments
contaminated by these effluents (Ferreira da Silva et al.,
2007; Laroche et al., 2009). Most of these integrons were
detected in the multiresistant subpopulation, which is
consistent with many studies that have shown the correla-
tion between the carriage of integrons and the multiresis-
tance of isolates (Zhang et al., 2009; Zhao et al., 2011).
Nevertheless, in the variable region of these integrons, we
found *dfrA1* and *aadA1* gene cassettes, which explain only
the phenotypes of resistance to streptomycin and trimeth-
oprim. Indeed, these two gene cassettes are commonly
found, either together or separately, in the integrons
detected in *E. coli* isolated from various environments
(Ferreira da Silva et al., 2007; Vinué et al., 2008; Zhang
et al., 2009; Zhao et al., 2011) and often do not fully cor-
respond to the resistance patterns of the isolates.

Conclusion

In this study, we have demonstrated that drinking water
resources taken from karstic groundwater are sensitive to
contamination by antibiotic-resistant fecal bacteria,
mostly during periods of rain. We propose here to use
the antibiotic resistance patterns (number and type of
resistances) of *E. coli* as a biological indicator to help
determine the origin of groundwater contamination cir-
culating through karstic systems. Two resistant subpopu-
lations were defined linked to WWTP or septic tank
effluents (R3-10 subpopulation) or runoff from pasture
(R1-2 subpopulation). During high-risk events, antibi-
otic-resistant genes could be incorporated in the drinking
water distribution system by (1) transport of fecal bacte-
ria through failure of water treatment and/or (2) transfer
of resistance genes to autochtonous bacteria that are

present in the water resources and that colonize the dis-
tribution system. Thus, antibiotic resistance can be con-
sidered as an emerging contaminant of water, which could
contribute to the global dissemination of resistance genes.

Acknowledgments

This work was supported by the Agence de l'Eau Seine-
Normandie (AESN, Honfleur, France) and the COmmu-
nauté D'Agglomération Havraise (CODAH, Le Havre,
France). The authors wish to thank Jean Duchemin
(AESN) for his help in the scientific discussions, Sylvaine
Buquet and Michel Simon for their technical assistance,
and Dilys Moscato for helpful comments on the manu-
script.

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