Pigs are important reservoirs of Shiga toxin-producing *Escherichia coli* (STEC). The entrance of these strains into the food chain implies a risk to consumers because of the severity of hemolytic uremic syndrome. This study reports the prevalence and characterization of STEC throughout the pork production chain. From 764 samples, 31 (4.05%) were *stx* positive by PCR screening. At farms, 2.86% of samples were *stx* positive; at slaughter, 4.08% of carcasses were *stx* positive and at boning rooms, 6% of samples were *stx* positive. These percentages decreased in pork meat ready for sale at sales markets (4.59%). From positive samples, 50 isolates could be characterized. At farms 37.5% of the isolates carried *stx1/stx2* genes, 37.5% possessed stx2e and 25%, carried only stx2. At slaughter we detected 50% of isolates positive for stx2, 33% for stx2e, and 16% for stx1/stx2. At boning rooms 59% of the isolates carried stx1/stx2, 14% stx2e, and 5% stx1/stx2/stx2e. At retail markets 66% of isolates were positive for stx2, 17% stx2e, and 17% stx1/stx2. For the other virulence factors, *ehxA* and *saa* were not detected and *eae* gene was detected in 12% of the isolates. Concerning putative adhesins, *agn43* was detected in 72%, *ehaA* in 26%, *aida* in 8%, and *iha* in 6% of isolates. The strains were typed into 14 *E. coli* O groups (O1, O2, O8, O15, O20, O35, O69, O78, O91, O121, O138, O142, O157, O180) and 10 H groups (H9, H10, H16, H21, H26, H29, H30, H32, H45, H46). This study reports the prevalence and characterization of STEC strains through the chain pork suggesting the vertical transmission. STEC contamination originates in the farms and is transferred from pigs to carcasses in the slaughter process and increase in meat pork at boning rooms and sales markets. These results highlight the need to implement an integrated STEC control system based on good management practices on the farm and critical control point systems in the food chain.

 HUS is one of the most common etiologies for acute kidney injury and an important cause of acquired chronic kidney disease in children (Grisaru, 2014). This damage is produced by the action of cytotoxins Stx1 and Stx2, being Stx2 and their subtypes associated more frequently with HUS (Beutin et al., 2007). The ability to adhere to epithelial cells is an important virulence trait, because adherence presumably enables to deliver toxins efficiently to host organs (Tarr et al., 2000). Intimin, encoded by *eae* gene, is required for intimate bacterial adhesion to epithelial cells inducing a characteristic histopathological lesion defined as "attaching and effacing" (A/E) and has been considered as a risk factor for disease in human (Ethelberg et al., 2004). However, the presence of *eae* would not be essential for pathogenesis, considering that some *eae* negative STEC have been associated with severe disease in human (Paton et al., 2001). Some studies reported adherence factors other than intimin, such as Saa (Paton et al., 2001), AIDA and Agn43 (Restieri et al., 2007), EhaA (Wu et al., 2010), Iha (Tarr et al., 2000; Szalo et al., 2002). AIDA was identified in diffusely adhering diarrheagenic *E. coli* strain and is associated with edema disease and diarrhea in pigs (Niewerth et al., 2001), contributing to bacterial intercellular aggregation and biofilm formation (Restieri et al., 2007); *iha* encode for an outer membrane protein identified as a bacterial adherence conferring iron regulated gene (Tarr et al., 2000) and Agn43 and EhaA are autotransporter proteins of O157:H7 involved in adhesion and biofilm formation (Wells et al., 2008). Other factors are also involved in human pathogenicity such as a plasmid that encoded enterohemolysin (EhxA), among others (Feng and Reddy, 2013).

Argentina, where the HUS is endemic, hold the highest record worldwide of this syndrome with an incidence of 17/100,000 children less than 5 years old (Rivas et al., 2010). Although STEC O157:H7 is recognized as the most important serotype associated with human infection, there are more than 400 non-O157 serotypes that have been involved in human disease and isolated from different reservoirs including cattle, pigs, goats, sheep, cats, and dogs (Parma et al., 2000; Padola et al., 2004; Amézquita-López et al., 2014). STEC usually do not produce disease in animals, however, the Stx2e subtype is involved in edema disease in pigs, a peracute toxemia characterized by vascular necrosis, edema, neurological signs and that in some cases can be fatal (Niewerth et al., 2001). STEC strains have been isolated from pork products and have been associated with human infections as diarrhea and HUS, including strains harboring *stx2e* subtype (Sonntag et al., 2005; Kaufmann et al., 2006; Trotz-Williams et al., 2012); however, it is unknown if the contamination of pork- derivate food occurs during the processing or by cross contamination (Tseng et al., 2014).

There is an increase in worldwide demand for fast-growing species with efficient feed conversion rates, such as pigs, because they represent a major share in the growth in the livestock subsector (Food and Agriculture Organization [FAO], 2014). Because of the limited epidemiologic data of STEC in pork and the increasing role of non-O157 STEC in human illnesses, it is very important to study the role of pigs as reservoirs of STEC and the transmission to the swine production chain (Ercoli et al., 2015). Taking into account the data mentioned above, the aim of this study was to determine the prevalence and to characterize STEC throughout the pork production chain in Argentina.

#### MATERIALS AND METHODS

#### Management of Farms and Animals

The study was conducted in two pig production farm systems. Both farms are intensively organized in total confinement. The production stages are: gestation, farrowing, weaning, and growing/finishing (fattening), which are geographically separated from each other within the same farm. The usual group size varies between 10 and 30 pigs. Pigs and employees move from one building to others by corridors that are isolated from external traffic.

### Management of Carcasses Until Retails Markets

Pigs at finishing stage are transported to the slaughterhouses. After slaughtered, the pork carcasses are chilled during 24 to 48 h and sent to boning rooms in refrigerated trucks.

At the boning rooms the carcasses were boning to products such as meat and minced meat. Finally, the products are transferred to the retails markets.

#### Collection of Samples

Seven hundred and sixty four samples were collected from May, 2012 to November, 2014 from two pig production systems.

This study was carried out in accordance with the recommendations of the Animal Welfare Committee from the Veterinary Science Faculty, UNCPBA, Resolution 087/02.

#### Samples at Farms

Three hundred and forty eight samples were taken at farms. From these, 277 corresponded to rectal swabs, and 71 come from the environment obtained from water drink, feed and feces on the floor by swabbing.

#### Samples at Slaughterhouses

One hundred and forty seven samples were by swabbing. Off these, 22 were from rectal swabs after slaughter, 85 from carcasses, and 40 from the slaughterhouses environment (pre-washing, scalding, deharing, dressing, cooling, and knives).

Carcasses swabs were taken in concordance with circular No 3496/02 of Servicio Nacional de Sanidad y Calidad Agroalimentaria (SENASA, 2002). Five quarters areas of 100 cm2 each one were taken and processed separately, they are named heads (H), external rectum (ER), internal rectum (IR), external thoracic (ET), and internal thoracic (IT; **Figure 1**).

### Samples at Boning Rooms

One hundred and eighty one samples were taken. From these, 94 come from carcasses, 24 from meat, 23 from minced meat, and 40 from environmental samples (refrigerated trucks and meat contact surfaces such as meat tables, knives, meat mincing machine, and vertical band saw machine).

## Sampling at Retail Markets

Eighty seven samples were taken from retail markets (43 samples come from meat, 13 from minced meat, and 31 from the environment). The environmental samples were obtained from meat tables, knives, vertical band saw machine, and refrigerators.

### Sample Preparation and Isolation of STEC

Swabs were processed according to Etcheverría et al. (2010). Briefly, the swabs were cultured in Luria Bertani broth (LB) with shaking at 37◦C for 18 h, and then an aliquot was grown on MacConkey agar plates by incubating at 37◦C for 24 h.

Ten to fifty individual colonies were processed for amplification of Shiga toxin genes (*stx1*, *stx2*, and *stx2e*; **Table 1**). Each positive colony for either *stx* was tested for the presence of the *eae*, *ehxA*, and *saa* by multiplex polymerase chain reaction (PCR; Paton and Paton, 2002). Genes encoding adhesins (*ehaA, agn43, iha*, *aida*) were amplified using monoplex PCR. STEC strains used as positive control were *E. coli* O157:H7 EDL933 (*stx1*, *stx2*, *eae*, *ehxA*, *ehaA, agn43, iha*), *E. coli* O8 (stx2e), *E. coli* O91:H21 (*stx*1*, stx*2*, ehxA, saa*), and *E. coli* O157:H19 (*aida*).

Amplification products were separated by electrophoresis on 2% agarose gel containing 0.8 µg/ml of ethidium bromide in running buffer and were visualized by UV transillumination.

### Determination of Serotype

O and H types were determined by microagglutination technique in plates and tubes as described by Guinée et al. (1981) and modified by Blanco et al. (1996) using all available O (O1– O175) antisera plus six putative new O antigens (OX176 through OX181) and H (H1–H56) antisera (Pradel et al., 2000).

TABLE 1 | Genes, primers sequences, and size of amplified product of Shiga toxin-producing *Escherichia coli* (STEC).

## RESULTS

The results indicate that STEC occurrence is widespread throughout pork production chain. Among the 764 samples, 31 (4.05%) were positive for *stx*. In rectal swabs from the different pig categories, 2.86% were STEC positive, distributed 5.88% at fattening, 4.3% at growing, 2.38% at gestation and 1.51% at farrowing. STEC were not detected in feed, water, and fecal samples taken from farms. At slaughter, 4.08% of carcasses sampled were *stx* positive. The distribution in the different quarters of the carcasses was: 50% from ER, 16.6% from ET, 16.6% from IT, 16.6 % from heads. At boning rooms, 6% of samples were STEC positive, belonging 82% to carcasses, and 18% to pork meat. The distribution in the different quarters of the carcasses was: 33.3% from ER, 22.2% from IR, 22.2% from IT, 11.2% from ET and 11% from head. At sale markets 4.59% of STEC positive samples were detected in pork meat ready for sale.

#### Characterization of STEC

From positive samples, 50 isolates could be characterized by PCR. In samples from farms 6/16 (37.5%) of the isolates carried *stx1*/*stx2*, 6/16 (37.5%) possessed *stx2e*, and 4/16 (25%) carried *stx2*. At slaughter 3/6 (50%) of isolates were positive for *stx2,* 2/6 (33%) for *stx2e*, and 1/6 (16%) for *stx1/stx2*. At boning rooms 13/22 (59%) of the isolates carried *stx1*/*stx2*, 3/22 (14%) *stx2e*, and 1/22 (5%) *stx1*/*stx2*/*stx2e*. At retail markets 4/6 (66%) of isolates were positive for *stx2,* 1/6 (17%) for *stx2e*, and 1/6 (17%) for *stx1/stx2*. Other virulence factors such as *ehxA* and *saa* were not detected and *eae* was detected in 6/50 (12%) of samples. Concerning putatives adhesins, *agn43* was detected in 36/50 (72%), *ehaA* in 13/50 (26%), *aida* in 4/50 (8%), and *iha* in 3/50 (6%) of isolates. The most frequent virulence profiles found were *stx1, stx2*, or *stx2e* combined with *agn43* in 36 (72%) strains. The 50 isolates were typed into 14 *E. coli* O groups (O1, O2, O8, O15, O20, O35, O69, O78, O91, O121, O138, O142, O157, O180) and 15 were considered O non-typable (NT). Ten H antigens (H9, H10, H16, H21, H26, H29, H30, H32, H45, H46) were distributed among the 50 strains, while one isolate were non-motile (H–). **Table 2** indicates the relationships between virulence profiles, sites of samples and serotypes in isolated STEC strains.

### DISCUSSION

To our knowledge, this study is the first that reports the prevalence and characterization of STEC strains through the chain pork suggesting the vertical transmission of these pathogens. However, there are studies that demonstrate the prevalence in farms, finishing pigs, slaughter, and pork meat in sales markets, separately. The prevalence of STEC in pigs, carcasses, and pork meat at different stage of production from other countries is variable and it is necessary to take caution when comparing prevalence since the variation may be due to several factors, such as sampling method, samples processing, and season in which the study was performed. Different prevalence of STEC in pigs was reported previously, ranged from 2 to 31%, in agreement with our results (Parma et al., 2000; Kaufmann et al., 2006; Meng et al., 2014). In carcasses at slaughter and boning rooms, the prevalence found is in concordance with other studies whose prevalence ranged from 0.2 to 26% (Leung et al., 2001; Bouvet et al., 2002; Bohaychuk et al., 2011; Kolácková et al., 2014 ˇ ).

At slaughter some operations such as skinning, evisceration and handling are more likely than others to contaminate carcass and meat (Koohmaraie et al., 2005; Etcheverría et al., 2010). For this, some areas of carcasses are more prone than others to be exposure to potential or cross contamination, thus the suggestion of sampling at three or four sites on carcass, because contamination appears to vary considerably among different sites (Roberts et al., 1984). In addition, the ER is the area that involves

TABLE 2 | Relationships between virulence profiles, sites of samples, and serotypes in STEC strains.

a particular risk of contamination during early stages of dressing as our result in that the ER was the more contaminated area, in concordance with Bouvet et al. (2002). However, other areas sampled as IT and IR shown more contamination probably due to handling at the boning room.

In our study, the prevalence at sale market was less than that informed by Magwedere et al. (2013) in USA (50%), Martin and Beutin (2011) in Germany (14%) and Lee et al. (2009) Korea (15%). This could be due because these studies were performed in sale markets where meat from different origins were sold and cross contamination during handling can occur. In the present study the samples were obtained from sale markets where only meat pork was sold.

From 50 STEC isolates, *stx*1/*stx*2 and *stx*2 occurred more frequently than isolates carrying *stx1.* Epidemiologically, Stx2 producing strains are more often related with HUS than strains that produce Stx1 (Paton and Paton, 2002).

Regarding *stx*2e, its prevalence decreased from pigs at farms to pork meat. Although some authors have reported the presence of *stx2*e in STEC strains in human patients on a few occasions, STEC harboring *stx2*e are more likely to cause edema disease in pigs causing economic losses in pig production (Kaufmann et al., 2006). It is necessary to determine a rol of these strains in human infection.

The presence of *eae* detected in isolates that harbor too *stx2*, *stx2e, agn43* from boning rooms and sale markets implies a high risk for human health (Tseng et al., 2014). The most prevalent adhesin identified among all isolates and involved in adhesion and biofilm formation was Agn43, followed by EhaA in agreement with Biscola et al. (2011) and Tseng et al. (2014) which detected them in swine and different sources, respectively. In this study, 8% of strain harbored *AIDA*, similar to that found in South Africa (Mohlatlole et al., 2013) and China (Zhao et al., 2009). The *iha* was present in few isolates, but this gene has been detected over 70% of the *eae*-negative STEC strains associated with human clinical cases examined in studies in Germany (Hauser et al., 2013) and Argentina (Galli et al., 2010). The high prevalence of LEE negative STEC isolated from pigs in our study emphasizes the need of further work to better define the role that the attachment proteins outside the LEE may play in the adherence to both pork and human epithelial cells.

Although many serotypes isolated in this study have been detected with low incidence in human disease and rarely associated with outbreaks (Friedrich et al., 2002), they have been isolated from pigs, sheep, cattle and food in other countries

#### REFERENCES

(Beutin et al., 1993; Kaufmann et al., 2006; Beutin et al., 2007).

### CONCLUSION

The presented study investigated the tracking of STEC from the farm to table and indicates that the production of meat pork harbored STEC strains. STEC contamination originated in the farms is transferred from pigs to carcasses in the slaughter process and increase in meat pork at boning rooms and sales markets. Besides, the entrance of these strains into the food chain implies a risk to consumers because of severity of the illness they can cause. If STEC is present in any food product, it has the possibility of causing foodborne illness. In addition to public health problem, the presence of strains carrying the *stx2e* gene is a problem for the pig production because they can cause the edema disease causing important economic losses. In spite of the wealth of data available on this important disease, it is necessary to effectively prevent this contamination by educating employees, retailers and consumers on the appropriate handling and storage of meat. Further studies are needed to provide more systematic data in order to fuel the development of novel approaches for control of STEC in foods, including pork meat.

### AUTHOR CONTRIBUTIONS

RC conceived, designed, analyzed the experiments, and wrote the manuscript. MR, MS, and MC did some of the experiments. NP and AE designed some of the experiments, analyzed the data, and revised the manuscript.

#### ACKNOWLEDGMENTS

Authors thank Guillermo Arroyo for their collaboration during sampling collection, María Rosa Ortiz for her technical assistance. This work was supported by PICT 2010-1655, CIC, and SECAT from Argentina.

*Escherichia coli* from food by a combination of serotyping and molecular typing of Shiga toxin genes. *Appl. Environ. Microbiol.* 73, 4769–4775. doi: 10.1128/AEM.00873-07

*Escherichia coli* of genes encoding for putative adhesins of human EHEC strains. *Res. Microbiol.* 153, 653–658. doi: 10.1016/S0923-2508(02)01379-7

Shiga toxin-producing *Escherichia coli* strains isolated from healthy cattle and diarrheal patients in Japan. *J. Vet. Med. Sci.* 72, 589–597. doi: 10.1292/jvms.09- 0557

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2016 Colello, Cáceres, Ruiz, Sanz, Etcheverría and Padola. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

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# Inactivation of Uropathogenic Escherichia coli in Ground Chicken Meat Using High Pressure Processing and Gamma Radiation, and in Purge and Chicken Meat Surfaces by Ultraviolet Light

#### Christopher H. Sommers\*, O. J. Scullen and Shiowshuh Sheen

Eastern Regional Research Center, United States Department of Agriculture, Agricultural Research Service, Wyndmoor, PA, USA

#### Edited by:

Chitrita Debroy, The Pennsylvania State University, USA

#### Reviewed by:

Diego Garcia-Gonzalo, Universidad de Zaragoza, Spain Olin Silander, Massey University, New Zealand

#### \*Correspondence:

Christopher H. Sommers<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

Received: 25 November 2015 Accepted: 14 March 2016 Published: 14 April 2016

#### Citation:

Sommers CH, Scullen OJ and Sheen S (2016) Inactivation of Uropathogenic Escherichia coli in Ground Chicken Meat Using High Pressure Processing and Gamma Radiation, and in Purge and Chicken Meat Surfaces by Ultraviolet Light. Front. Microbiol. 7:413. doi: 10.3389/fmicb.2016.00413 Extraintestinal pathogenic Escherichia coli, including uropathogenic E. coli (UPEC), are are common contaminants in poultry meat and may cause urinary tract infections after colonization of the gastrointestinal tract and transfer of contaminated feces to the urethra. Three non-thermal processing technologies used to improve the safety and shelf-life of both human and pet foods include high pressure processing (HPP), ionizing (gamma) radiation (GR), and ultraviolet light (UV-C). Multi-isolate cocktails of UPEC were inoculated into ground chicken which was then treated with HPP (4◦C, 0–25 min) at 300, 400, or 500 MPa. HPP D10, the processing conditions needed to inactivate 1 log of UPEC, was 30.6, 8.37, and 4.43 min at 300, 400, and 500 MPa, respectively. When the UPEC was inoculated into ground chicken and gamma irradiated (4 and −20◦C) the GR D10 were 0.28 and 0.36 kGy, respectively. The UV-C D10 of UPEC in chicken suspended in exudate and placed on stainless steel and plastic food contact surfaces ranged from 11.4 to 12.9 mJ/cm2 . UV-C inactivated ca. 0.6 log of UPEC on chicken breast meat. These results indicate that existing non-thermal processing technologies such as HPP, GR, and UV-C can significantly reduce UPEC levels in poultry meat or exudate and provide safer poultry products for at-risk consumers.

Keywords: UPEC, high pressure processing, gamma radiation, ultraviolet light, chicken

## INTRODUCTION

Escherichia coli are classified as commensal (natural microflora), or variants that cause disease such as intestinal pathogenic E. coli (iPEC) or extraintestinal (ExPEC) types. Groups of ExPEC include Neonatal Meningococcal E. coli (NMEC), Avian Pathogenic E. coli, (APEC), Sepsisassociated Pathogenic E. coli (SEPEC) and Uropathogenic E. coli (UPEC) (Mitchell et al., 2015). E. coli such as ExPEC (UPEC) are responsible for 75–95% of urinary tract infections (UTI) and uncomplicated cystitis and pyelonephritis (Nordstom et al., 2013). Fifty percent of women will contract one UTI in their lifetime, and 25% will have a recurrent UTI (Minardi et al., 2011; Bao et al., 2014). The number of UTI in the US is ca. 6–8 million annually, with ca. 100, 000 hospitalizations, ca. 23,000 deaths, and a health care burden fmicb-07-00413 April 12, 2016 Time: 15:33 # 2

of ca. \$3.5 billion (Nordstom et al., 2013). The mechanism for contraction of a UTI is transfer of contaminated feces from the gastrointestinal tract to the urethra, and isolates associated with UTI invariably match the individual's fecal microflora (Moreno et al., 2008).

The idea that extraintestinal foodborne pathogens such as the ExPEC might be responsible for UTI in humans is relatively new, and it has long been suspected they may be associated with illness outbreaks (Markland et al., 2015). The presence of ExPEC in poultry meat has been firmly established (Johnson et al., 2005; Mitchell et al., 2015). Studies have compared ExPEC isolates from food animals, food, and those from women with UTI and the incidence of ExPEC in poultry meat and have demonstrated both genetic similarity and identity between ExPEC from animals and food with those from humans with UTI (Cortes et al., 2010; Jakobsen et al., 2010a,b, 2012; Vincent et al., 2010; Bergeron et al., 2012; Mora et al., 2013). More importantly ExPEC isolated from animals and food can cause UTI in mouse model systems (Jakobsen et al., 2012).

Three non-thermal intervention technologies of interest to the meat and poultry processing industry, which are used commercially to improve food safety and extend shelf life, include high pressure processing (HPP), ionizing (gamma) radiation (GR) and ultraviolet light (UV-C) (Salvage, 2014). HPP subjects food to an elevated pressure of 100–1000 MPa typically at temperatures below 60◦C. The mechanism by which HPP inactivates foodborne pathogens includes cell membrane and structure damage, ribosome dissociation, dissociation of DNA, and enzyme inactivation (Campus, 2010; Simonin et al., 2012). GR inactivates microorganisms by damaging their DNA indirectly through radiolysis of water and induction of oxidative damage or direct damage through breakage of the phosphodiester backbone in addition to oxidative damage to proteins and cell membranes (Taub et al., 1979; Diehl, 1995). UV-C kills microorganisms through induction of cyclobutane pyrimidine dimmers and 6-4 photoproducts in addition to protein damage (Krisko and Radman, 2010; Rastogi et al., 2010).

The purpose of this study was to determine the HPP and GR inactivation kinetics for ExPEC (UPEC) inoculated in ground chicken as well as the UV-C inactivation kinetics on poultry meat surfaces and in chicken purge on food contact surfaces. To the authors knowledge this is the first study to examine the inactivation kinetics of ExPEC in a food system.

### MATERIALS AND METHODS

#### Chicken

Ground chicken (92% lean) was freshly prepared and purchased at a local wholesaler (Lansdale, PA, USA) and evenly portioned into 90 g aliquots in polynylon pouches (Uline, Inc., Philadelphia, PA, USA), vacuum sealed to 50 millibars using a Multi-Vac A300 packager (Multi-Vac Inc., Kansas City, MO, USA) and then frozen (−70◦C). The ground chicken was tested for presence of E. coli as described below and it was <1 CFU/g. Multiple chicken lots were tested and one with low E. coli levels was selected.  Chicken purge was obtained from a local poultry processor and frozen (−70◦C) until ready for use.

### E. coli Isolates

The E. coli isolates were obtained from the American Type Culture Collection (Manassas, VA, USA). These include 700414, 700415, 700416, 700417, 700336, and BAA-1161 (http://www. atcc.org), which were isolated from women with UTI. Multiisolate cocktails of the pathogens were used as recommended for appropriate validation of non-thermal processing technologies (National Advisory Committee on Microbiological Criteria for Food [Nacmcf], 2006). The individual isolates were prescreened for resistance to HPP, GR and UV prior to use, and the D10 were consistent with results for our previous studies with iPEC (Sheen et al., 2015; Sommers et al., 2015; Sommers et al., unpublished data).

#### E. coli Growth and Inoculation

The E. coli were cultured independently in 20 ml Tryptic Soy Broth (TSB) without dextrose to avoid development of acid resistance (BD-Difco, Sparks, MD, USA) using 50 ml sterile tubes at 37◦C (150 rpm) for 18–24 h using a New Brunswick Model G34 Environmental Shaker (New Brunswick, Edison, NJ, USA). The bacteria were then sedimented by centrifugation (1,200 × g, Hermle Model Z206A, Hermle Labortechnik, Germany) and resuspended as a cocktail in 20 ml sterile 0.1% peptone water (SPW, BD-Difco).

Thawed ground chicken (10 g) was aliquoted into 2 oz. Nasco (Ft. Atkinson, WI, USA) Whirl-Pak bags, inoculated with 0.1 ml of UPEC, mixed manually for 1 min, and then sealed using the Multi-Vac A300 Packager. The final concentration of UPEC in the ground chicken was ca. 8–9 log CFU/g. The sample bags were then sealed in a second bag and stored at 4◦C until HPP treatment or gamma radiation (ca. 2 h).

#### High Pressure Processing Treatment

High pressure processing was performed using a laboratory scale pressure unit (Mini Food lab FPG5620, Stansted Fluid Power Ltd., Essex, UK), comprised of a double-jacketed thick-wall stainless steel cylinder (approximate volume of 0.3 L) having an internal stainless steel sample holder of 25.4 mm × 254 mm (diameter × length). The thick-wall cylinder was maintained at a set-point temperature in which heat transfer fluid continuously circulated from a refrigerated liquid chiller (Proline RP 855, Lauda, Germany). The pressure come-up rate was 100 MPa per 15 s (or 6.7 MPa/s) and the release rate was 100 MPa per 9 s (or 11.1 MPa/s). Samples were pressure-treated at 500, 400, and 300 MPa (4◦C) at 5 min intervals for up to 25 min. The initial temperature in the processing chamber was ca. 4◦C and did not exceed a maximum of 35◦C during the HPP treatment. Keeping the chamber temperature low (ca. 4◦C) prevents compression heating induced thermal effects from interfering with HPP inactivation kinetic determination (Sheen et al., 2015). The chamber temperature was monitored by the built-in sensor (a T-type thermal couple device). The thermal sensor was immersed in the working chamber near food samples filled with the recirculation fluid.

#### Gamma Radiation

fmicb-07-00413 April 12, 2016 Time: 15:33 # 3

A Lockheed Georgia Company (Marietta, GA, USA) selfcontained 137Cs irradiator, with a dose rate of 0.065 kGy/min, was used for all exposures. The radiation source consisted of 23 individually sealed source pencils in an annular array. The 22.9 cm × 63.5 cm cylindrical sample chamber was located central to the array when placed in the operating position. Inoculated samples were placed vertically and centrally in the sample chamber, using a 4 mm thick polypropylene bucket, to ensure a good dose uniformity (DUR < 1.1:1.0). The temperature during irradiation (4◦C) was monitored by thermocouple and maintained (4 or −20◦C) by introduction of the gas phase from a liquid nitrogen source directly into the top of the sample chamber. The radiation doses were at 0.3 and 0.6 kGy increments at 4 or −20◦C, respectively. The absorbed dose was verified using temperature tempered 5 mm alanine pellets that were then measured using a Bruker eScan EPR Analyzer (Bruker, Billerica, MA, USA).

### Exposure to Ultraviolet Light

A custom built UV-C apparatus (2 mW/cm2 ) (Sommers et al., 2010) was used to treat chicken purge inoculated with UPEC on stainless steel (304 L), High Density Polypropylene (HDPP) and High Density Polyethylene (HDPE) coupons (5 × 10 cm), and the foods themselves. Chicken purge was thawed in a refrigerator overnight and 0.5 ml of UPEC cocktail inoculated into 4.5 ml chicken exudates was then mixed by vortexing for 30 s. One hundred microliter of inoculated purge was placed on the coupons which were then spread to a 4 cm × 4 cm area using an inoculating loop. The coupons were placed in a refrigerator for 30 min and then placed on a cold pack (4◦C) for UV-C exposure. The UV-C intensity exposure times were 0, 10, 20, 30, 40, 50, and 60 s for UV-C doses of 20, 40, 60, 80, 100, and 120 mJ/cm2 .

For chicken meat and skin 4 × 4 cm sections (ca. 1 mm thick) of boneless skinless chicken breast were placed in sterile petri dishes and inoculated with 0.1 ml of chicken purge which was then spread onto the surface (4 cm × 4 cm) using an inoculating loop, and then incubated for 30 min in a refrigerator (4◦C) prior to treatment with UV-C. The samples were placed on cold packs prior to UV-C treatment. The UV-C intensity exposure times were 0, 10, 20, 30, 40, 50, and 60 s for UV-C doses of 20, 40, 60, 80, 100, and 120 mJ/cm2 .

UV-C intensity was monitored using a calibrated UVX Radiometer (UVP Inc., Upland, CA, USA). The temperature of the room was approximately 20◦C during the exposure to UV-C, and the food temperature did not increase to more than 30◦C at the end of the process as measured using an infrared thermometer.

### Recovery of the Surviving E. coli

The individual ground chicken samples were added to 90 ml of 0.1% PW and then stomached for 2 min (Model Bag Mixer 100W, Inter science Co., France). The coupons with 0.1 ml exudate were placed in stomacher bags with 9.9 ml SPW and hand massaged for 1 min. For recovery of UPEC 1.0 mL, after proper decimal dilutions, was placed on duplicate E. coli/coliform PetrifilmTM (3M Microbiology Products Co., St. Paul, MN, USA). The films were maintained at room temperature for 4 h to allow the injured cells to recover (Hsu et al., 2014) and then incubated at 37◦C for 24 h. Colonies (CFU) were enumerated for determination of log reduction and D10. Incubation for longer periods did not result in changes to the colony counts, an indicator of injured cell recovery.

### Statistical Analysis

The mean plate counts of the treated samples (N) were divided by the average control plate counts (No) to give a survivor ratio (N/No). The log10 (N/No) of the ratios was then used for determination of D10-values and other statistical analyses. D10-values were determined by the reciprocal of the slope following linear regression as determined by least squares analysis (Diehl, 1995). Each experiment (D10 determination) was conducted independently three times. A minimum of five time points were used for determination of D10. Statistical analysis functions of MS Excel (Microsoft Corp., Redmond, WA, USA) were used for routine calculations (D10 determination), descriptive statistics, analysis of variance (ANOVA, 95% confidence).

## RESULTS AND DISCUSSION

#### High Pressure Processing

The HPP inactivation kinetics for the UPEC multi-isolate cocktail is shown in **Table 1** and **Figure 1**. As we have found previously for STEC the inactivation kinetics was first order in nature. The HPP D10 of the UPEC in refrigerated (4◦C) ground chicken was ca. 30.6, 8.37, and 4.43 min at 300, 400, and 500 MPa, respectively. HPP treatment using 300 MPa was ineffective as a treatment as ca. 1 log was inactivated at that pressure. When we compare the results of this study with those from previous HPP studies for

TABLE 1 | D10 values for uropathogenic Escherichia coli in ground chicken and chicken purge.

D10 for HPP, GR, and ultraviolet light are shown with the standard error of the mean in parenthesis. Each experiment was conducted independently three times (n = 3). Each HPP D10 was significantly different than the others, as were the GR D10 (ANOVA, p < 0.05). There was no difference (p > 0.05) between the UV-C D10 for food contact surfaces.

fmicb-07-00413 April 12, 2016 Time: 15:33 # 4

inactivation of STEC the results are similar. Sheen et al. (2015) found the mean HPP D10 (350 MPa) of 39 STEC isolates from illness outbreaks to be ca. 9.25 min while those from animals and environmental sources was ca. 10.4 min when suspended in 80% lean ground beef (350 MPa, 4◦C). Hsu et al. (2014) found that 450 MPa (15 min, 4◦C) inactivated 5.5–6.9 log of STEC in 77% lean ground beef while 350 MPa inactivated ca. 3.2–4.7 log. Jiang et al. (2015) was able to inactivate 3–4 log of STEC with HPP using multiple 1 min cycles at 400 MPa. Our results obtained using the UPEC were similar to those we have and others have obtained in the STEC suspended in ground beef.

#### Gamma Radiation

When the UPEC cocktail was suspended in ground chicken and treated with gamma radiation the GR D10 was ca 0.28 kGy at refrigeration (4◦C) temperature (**Figure 1**, **Table 1**). These results are similar to those obtained by Sommers et al. (2015) which found the GR D10 of STEC associated with illness outbreaks to be ca. 0.27 kGy when suspended in refrigerated 80% lean ground beef. Sommers and Fan (2012) reviewed the studies for inactivation of E. coli O157:H7 in refrigerated ground beef in which the GR D10 ranged from 0.013 to 0.37 kGy. GR D10 for microorganisms irradiated in frozen foods are typically higher than that in refrigerated foods due to the limitation of indirect DNA damage through immobility of hydroxyl radicals produced by the radiolysis of water in the frozen state (Bruns and Maxcy, 1979; Taub et al., 1979). Lopez-Gonzalez et al. (1999) found the D10 for E. coli O157:H7 suspended in frozen beef (−15◦C) beef to be 0.62 kGy. Thayer and Boyd (2001) found the GR D10 of E. coli O157:H7 in frozen ground beef (−20◦C) to be 0.98 kGy. Black and Jaczynski (2006) obtained D10 of 0.33 and 0.35 kGy for E. coli O157:H7 in frozen (−20◦C) ground beef and chicken, respectively. It appears the radiation doses needed to inactivate STEC in refrigerated and frozen meat and poultry products should also control the UPEC.

### Ultraviolet Light

In this study our objective was to calculate a UV-C D10 value for the UPEC suspended in chicken exudate on SS, HDPP, and HDPE surfaces. The UV-C D10 for UPEC is shown in **Table 1** and **Figure 1**. The D10 was calculated from the linear portion of the survival curve (0–60 mJ/cm2 ) and ranged from 11.4 to 12.9 mJ, cm2 (p > 0.05, ANOVA). As with previous studies complete inactivation of microorganisms with UV-C is difficult because of shadowing by particulates in purge. The D10 for UPEC in purge obtained were very similar to those obtained with STEC suspended in veal purge (Sommers et al., unpublished data), as well as other foodborne pathogens (Sommers et al., 2012; Sommers and Sheen, 2015). A relatively low UV-C dose of 100 mJ/cm2 should be able to inactivate ≥5 log of UPEC in chicken purge on food contact surfaces.

When we inoculated the UPEC onto skinless chicken meat we obtained ca. 0.6 (±0.19), respectively, which was significantly reduced from the untreated controls (p < 0.05) which is consistent with previous results from our group as well as other researchers (Stermer et al., 1987; Sumner et al., 1996; Sommers et al., 2010). When the UPEC were inoculated onto chicken skin we did not obtain a significant reduction, which is again consistent with results we have obtained using other foodborne pathogens on chicken skin (Stermer et al., 1987; Sumner et al., 1996; Sommers et al., 2010). The reduced inactivation of the UPEC on skin and meat surfaces is expected due to the surface topology and shielding of the UPEC from UV-C (Gardner and Shama, 2000).

## CONCLUSION

Our results indicate the HPP, GR, and UV-C inactivation kinetics of the UPEC are similar to our historical results for the STEC in meat and meat purge. The processing conditions used to control STEC should have similar effects on the UPEC.

### DISCLAIMER

fmicb-07-00413 April 12, 2016 Time: 15:33 # 5

Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

### AUTHOR CONTRIBUTIONS

SS contributed to collection of high pressure processing data. OS was responsible for collection of UV-C data, CS was study director and designed the study, was responsible for data

#### REFERENCES

collection and analysis, and was responsible for manuscript completion.

### FUNDING

This Project was funded by USDA-ARS National Program 108 Food Safety Project No. 8072-42000-073-00D.

### ACKNOWLEDGMENT

We would like to thank Jennifer Cassidy for editing this manuscript.

fmicb-07-00413 April 12, 2016 Time: 15:33 # 6

Barbosa-Cánovas, V. M. Bala Balasubramaniam, C. P. Dunne, D. F. Farkas, J. T. C. Yuan (Hoboken, NJ: Wiley-Blackwell), 236–246.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Sommers, Scullen and Sheen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Surveillance of Extended-Spectrum Beta-Lactamase-Producing *Escherichia coli* in Dairy Cattle Farms in the Nile Delta, Egypt

Sascha D. Braun1, 2 \*, Marwa F. E. Ahmed3 , Hosny El-Adawy 4, 5, Helmut Hotzel 4 , Ines Engelmann1, 2, Daniel Weiß1, 2, Stefan Monecke1, 2, 6 and Ralf Ehricht 1, 2

*1 Alere Technologies GmbH, Jena, Germany, 2 InfectoGnostics Research Campus, Jena, Germany, 3 Department of Animal Hygiene and Zoonoses, Faculty of Veterinary Medicine, Mansoura University, Mansoura, Egypt, 4 Institute of Bacterial Infections and Zoonoses, Friedrich-Loeffler-Institut, Jena, Germany, 5 Department of Poultry Disease, Faculty of Veterinary Medicine, Kafrelsheikh University, Kafr El-Sheikh, Egypt, 6 Institute for Medical Microbiology and Hygiene, Technical University of Dresden, Dresden, Germany*

#### *Edited by:*

*Chitrita Debroy, The Pennsylvania State University, USA*

#### *Reviewed by:*

*Amy J. Mathers, University of Virginia, USA Brandon Luedtke, United States Department of Agriculture, USA*

*\*Correspondence:*

*Sascha D. Braun<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology*

*Received: 25 February 2016 Accepted: 15 June 2016 Published: 04 July 2016*

#### *Citation:*

*Braun SD, Ahmed MFE, El-Adawy H, Hotzel H, Engelmann I, Weiß D, Monecke S and Ehricht R (2016) Surveillance of Extended-Spectrum Beta-Lactamase-Producing Escherichia coli in Dairy Cattle Farms in the Nile Delta, Egypt. Front. Microbiol. 7:1020. doi: 10.3389/fmicb.2016.01020* Introduction: Industrial livestock farming is a possible source of multi-resistant Gram-negative bacteria, including producers of extended spectrum beta-lactamases (ESBLs) conferring resistance to 3rd generation cephalosporins. Limited information is currently available on the situation of ESBL producers in livestock farming outside of Western Europe. A surveillance study was conducted from January to May in 2014 in four dairy cattle farms in different areas of the Nile delta, Egypt.

Materials and Methods: In total, 266 samples were collected from 4 dairy farms including rectal swabs from clinically healthy cattle (*n* = 210), and environmental samples from the stalls (*n* = 56). After 24 h pre-enrichment in buffered peptone water, all samples were screened for 3rd generation cephalosporin-resistant *Escherichia coli* using BrillianceTM ESBL agar. Suspected colonies of putatively ESBL-producing *E. coli* were sub-cultured and subsequently genotypically and phenotypically characterized. Susceptibility testing using the VITEK-2 system was performed. All suspect isolates were genotypically analyzed using two DNA-microarray based assays: CarbDetect AS-1 and *E. coli* PanType AS-2 kit (ALERE). These tests allow detection of a multitude of genes and their alleles associated with resistance toward carbapenems, cephalosporins, and other frequently used antibiotics. Serotypes were determined using the *E. coli* SeroGenotyping AS-1 kit (ALERE).

Results: Out of 266 samples tested, 114 (42.8%) ESBL-producing *E. coli* were geno- and phenotypically identified. 113 of 114 phenotypically 3rd generation cephalosporin-resistant isolates harbored at least one of the ESBL resistance genes covered by the applied assays [*bla*CTX-M15 (*n* = 105), *bla*CTX-M9 (*n* = 1), *bla*TEM (*n* = 90), *bla*SHV (*n* = 1)]. Alarmingly, the carbapenemase genes *bla*OXA-48 (*n* = 5) and blaOXA-181 (*n* = 1) were found in isolates that also were phenotypically resistant to imipenem and meropenem. Using the array-based serogenotyping method, 66 of the 118 isolates (55%) could be genotypically assigned to O-types. Conclusion: This study is considered to be a first report of the high prevalence of ESBL-producing *E. coli* in dairy farms in Egypt. ESBL-producing *E. coli* isolates with different underlying resistance mechanisms are common in investigated dairy cattle farms in Egypt. The global rise of ESBL- and carbapenemase-producing Gram-negative bacteria is a big concern, and demands intensified surveillance.

Keywords: ESBL, carbapenemases, *Escherichia coli*, Egypt, dairy cattle, microarray, genotype, CRE

#### INTRODUCTION

Extended-spectrum beta-lactamases (ESBLs) are mainly plasmidencoded enzymes providing resistance to 3rd generation (3G) cephalosporins. These enzymes can be produced by a variety of different bacteria, such as Enterobacteriaceae or non-fermenting bacteria (Bradford, 2001; Giamarellou, 2005; Rawat and Nair, 2010; Shaikh et al., 2015). The most frequently found ESBLproducing species is Escherichia coli which often causes urinary tract infections, pneumonia or even sepsis in humans (Abraham et al., 2012). ESBL-producing E. coli has been broadly recognized in veterinary medicine as causative agents of mastitis in dairy cattle since the 2000s (Brinas et al., 2003; Haftu et al., 2012), but only a few studies exist that investigated the prevalence of ESBLproducing bacteria in livestock, showing their existence in sick and/or healthy cattle (Valentin et al., 2014; Dahms et al., 2015).

Unfortunately, there is no legislation in Egypt regulating the use of antibiotics (Dahshan et al., 2015). Antimicrobials such as tetracycline, quinolones, and beta lactams are still used in Egypt for growth promotion in animal feed and by veterinarians for the treatment and prevention of zoonotic diseases (WHO, 2013).

The CTX-M beta-lactamases, named for their greater activity against cefotaxime, are the most frequently detected ESBLs in livestock, and have been reported from different food-producing animals (Schmid et al., 2013; Brolund, 2014; Hansen et al., 2014). These animals also represent a source and/or a reservoir for ESBL-producing E. coli (Carattoli, 2008). Several studies indicate that these resistance genes are disseminated through the food chain or via direct contact between humans and animals (Schmid et al., 2013; Dahms et al., 2015). Data on ESBL-producing bacteria in food animals from Egypt are very limited. Therefore, the current study was conducted on four dairy cattle farms in different districts of Northern Egypt to assess the prevalence of ESBL-producing E. coli in dairy cattle and their environment.

#### MATERIALS AND METHODS

#### Farm Description and Sampling

In 2014, four dairy farms, three in Gamasa (GF1, GF2, GF5), and one in Damietta (D), were investigated (**Figure 1**). These farms were located in Nile Delta, Egypt in two different governorates (Damietta; Latitude N. 31◦ 19′ , Longitude E. 31◦ 81′ and Dakahlia Latitude N. 31◦ 25′ , Longitude E. 31◦ 32′ ). The herd size ranged from 400, 600, 650, and 800 in GF1, GF2, GF5, and D, respectively. The cattle enrolled in this study were between 2 and 10 years old. Half of the farms housed dairy cattle in free-stall barns and half of them in tie-stall barns. In total, 266 samples were collected from these farms. This included rectal swabs and milk samples from apparently healthy dairy cattle (n = 210), and environmental swab samples from water trough, feed and bedding (n = 56).

#### Bacterial Strains, Isolation, Identification, and Genomic DNA Extraction

All collected samples were enriched in buffered peptone water and cultivated on BrillianceTM ESBL agar (Oxoid, Wesel, Germany) for preliminary analysis for ESBL-producing E. coli. For further investigations, all suspected E. coli that grew on the selective medium were cultivated on tryptone yeast agar (Oxoid, Wesel, Germany). Presumptive characteristic E. coli isolates were identified by Gram staining and motility, and confirmed using a panel of biochemical tests (Triple Sugar Iron (TSI) agar, catalase, oxidase, H2S production and sugar fermentation) and API 20 E systems (bioMérieux, France; ISO, 2001). All confirmed isolates were subsequently re-tested using an automated microdilution technique (VITEK-2, bioMérieux, Nürtingen, Germany) that covered the following antibiotics: imipenem, meropenem, cefotaxime, ceftazidime, cefuroxime-axetil, cefuroxime, piperacillin/tazobactam, ampicillin/sulbactam, ampicillin, gentamicin, tobramycin, ciprofloxacin, moxifloxacin, tetracycline, tigecycline, co-trimoxazol, and fosfomycin (VITEK-2 test card: AST-N289). Susceptibility tests for chloramphenicol, kanamycin, streptomycin, erythromycin and colistin were not performed in this study.

Genomic DNA from clonal isolates was extracted using the DNeasy Blood & Tissue kit (Qiagen GmbH, Hilden, Germany) according to manufacturer's instructions. When necessary, DNA was concentrated to at least 100 ng/µl using a SpeedVac centrifuge (Eppendorf, Hamburg, Germany) at room temperature with 1400 rpm and for 30 min. Five microliters of recovered genomic DNA were used directly for biotin-labeling and subsequent hybridization.

### GenoSeroTyping and Antimicrobial Resistance Genotype

For all ESBL-producing E. coli, the serotype was determined using the E. coli SeroGenoTyping AS-1 kit. The antimicrobial resistance (AMR) genotype was detected by the CarbDetect AS-1 kit and all other resistance genes were detected by the E. coli PanType AS-2 kit (Alere Technologies GmbH, Jena, Germany). The data were automatically summarized by the "result collector," a software tool provided by Alere Technologies. An antibiotic resistance genotype was defined as a group of genes which have been described to confer resistance to a family of antibiotics (e.g.,

the genotype "blaCTX-M1/15, blaTEM" confers resistance to 3G cephalosporins) (**Table 2**).

### Multiplex Labeling, Hybridization, and Data Analysis

Extracted DNA was labeled by primer extension amplification using E. coli SeroGenoTyping AS-1, CarbDetect AS-1 or E. coli PanType AS-2 kits according to manufacturer's instructions. The procedure for multiplex labeling, hybridization and data analysis was described in detail by Braun et al. (2014). Briefly, internal labeling of the synthesized single stranded DNA resulted from the primer elongation of previously hybridized primers to the target genomic DNA, by using dUTP linked biotin as dideoxynucleotide triphosphate to be incorporated during synthesis. This procedure allowed site-specific internal labeling of the corresponding target region. The PCR protocol included 5 min of initial denaturation at 96◦C, followed by 50 cycles with 20 s of annealing at 50◦C, 40 s of elongation at 72◦C, and 60 s of denaturation at 96◦C (used device: Eppendorf Mastercycler gradient, Eppendorf, Hamburg, Germany). This reaction resulted in a multitude of specific linearly amplified, single-stranded, biotin-labeled DNA molecules for subsequent hybridization and detection using the DNA microarrays.

For hybridization procedures, the CarbDetect AS-1 and the E. coli PanType AS-2 kit were used according to manufacturer's instructions. CarbDetect ArrayStrips were placed in a thermomixer with an Alere ArrayStrip adapter (Quantifoil Instruments, Jena, Germany) and subsequently washed with 200 µl of deionized water at 50◦C with 550 rpm for 5 min and with 100 µl hybridization buffer C1 at 50◦C with 550 rpm for 5 min. Liquids were always completely removed using a soft plastic pipette (e.g., BRANDT, #612-2856) to avoid any scratching of the chip surface. In a separate tube, 10 µl of previously labeled, single-stranded DNA was dissolved in 90 µl hybridization buffer C1. The hybridization was carried out at 50◦C and 550 rpm for 1 h. After hybridization, the ArrayStrips were washed twice using 200 µl washing buffer C2 at 45◦C for 10 min, shaking at 550 rpm. Peroxidase-streptavidin conjugate C3 was diluted 1:100 in buffer C4. A total of 100 µl of this mixture was added to each well of the ArrayStrip and subsequently incubated at 30◦C and 550 rpm for 10 min. Thereafter, two washing steps with 200 µl C5 washing buffer were carried out at 550 rpm at 30◦C for 5 min. The visualization was achieved by adding 100 µl of staining substrate D1 to the ArrayStrips, and signals were detected using the ArrayMate device (Alere Technologies GmbH). Finally, an automatically generated HTML-report was provided giving information on the presence or absence of antimicrobial resistance genes and the affiliation to one of the more common species.

#### Ethic Statement

An Ethic Statement is not necessary. The isolates were obtained by noninvasive rectal swabs and no animal experiments were carried out for this study.

### RESULTS

### Antimicrobial Resistance Genotype and Phenotype

Rectal swabs samples (n = 210) yielded 98 (46.6%) cultures and environmental samples (n = 56) yielded 16 (28.6%) cultures of putatively ESBL-producing E. coli. All 114 isolates were Gramnegative, motile, catalase positive, oxidase negative and indoleproducing bacteria. Additionally, all isolates caused a decrease of pH and a color change of the TSI agar indicator and gas formation in the bottom of the test tube, and were therefore assigned as E. coli. In total, 113 (99.1%) phenotypically 3G cephalosporin-resistant isolates harbored at least one of the ESBL genes covered by the microarray (blaCTX-M15, blaCTX-M9, blaTEM, blaSHV; **Figure 2**). The carbapenemase gene blaOXA-48 was detected in five isolates (3.4%) and the carbapenemase gene blaOXA-181 (0.8%) was detected in one isolate (**Table 1**, **Figure 2**). These isolates showed a phenotypic resistance to imipenem and meropenem (**Table 2**). The total number of detected resistance genes is listed in **Table 1** and an overview to each isolate is given in **Figure 2**. The ESBL gene blaCTX-M1/15 was found in 103 isolates whereas blaCTX-M9 was only found in 9 isolates. Consensus sequences for blaTEM and blaSHV were found in 89 and 1 isolate, respectively. For all detected beta-lactamase genotypes, the phenotype was analyzed using the VITEK-2 instrument. The results are shown in **Table 2**. The concordance for the carbapenem resistance and ESBL genotype was 100%. In one phenotypic ESBL positive isolate, only the narrow spectrum beta-lactamase (NSBL) gene blaOXA-1 was found. Due to this unexpected phenotype the concordance for the NSBL genotype was only 60%.

Nine different aminoglycoside resistance genes were detected by the E. coli PanType AS-1 kit (**Table 1**). The combinations of these genes resulted in 14 different genotypes, whereas the most prevalent genotype was aac(6′ )-Ib in combination with aadA4 (n = 25). All isolates harboring this genotype were resistant to tobramycin, but three of them were susceptible to gentamicin (**Table 2**). Therefore, the concordance between genotype and phenotype was 94%. Five isolates, which harbored only aac(6′ )-Ib, were resistant to all tested aminoglycosides. The second most frequent genotype was aac(3)-lVa (n = 20). All isolates harboring this gene were resistant to gentamicin and tobramycin and corresponded to 100% of the expected phenotype (**Table 2**). Six isolates harboring the gene aphA were susceptible to tobramycin and gentamicin. The detected phenotype corresponded 100% with the genotype, as the enzyme AphA does not mediate resistance against both aminoglycoside antibiotics tested (Ramirez and Tolmasky, 2010).

The most prevalent genotype for fluoroquinolone resistance was qnrA1 followed by qepA. One isolate harboring qnrA1 was sensitive to both quinolone antibiotics tested (97.0% concordance), but all isolates with detected qepA gene were resistant (100% concordance). Overall, 86 of 114 isolates were resistant to ciprofloxacin and 92 against moxifloxacin. Only in 56 ciprofloxacin resistant isolates a corresponding genotype was detected. Similar results were observed for the 92 moxifloxacin resistant isolates, where only in 68 isolates a corresponding genotype was detected. The overall concordance of the detection of genes mediating fluoroquinolone resistance with phenotypic resistance was 79.0% (**Table 2**).

Resistance to co-trimoxazole is associated with sul and dfrA genes. All isolates with this gene combination were resistant to co-trimoxazole (**Table 2**). From 45 isolates without this gene combination, 34 were resistant. Therefore, the concordance of genotype and phenotype was 80.0%.

Of 114 isolates, one was resistant to fosfomycin. Such resistance is caused by mutations in ubiquitous genes (e.g., murA or glpT) or the loss of entire genes (e.g., uhpA) rather than by acquisition of distinct resistance markers and therefore the genotypes were not included into the test panel (Takahata et al., 2010; Li et al., 2015).

In summary, the overall concordance among all genotypes to expected phenotypes was 82.6% (**Table 2**).

#### Serotyping

For all 114 ESBL-producing E. coli isolates, the O- and Htypes were identified using the E. coli SeroGenotyping AS-1 kit (**Figure 3**). For 63 (55.3%) isolates, genes encoding both O and H antigens were detected and for 51 isolates (44.7%) only the gene encoding the H antigen could be detected. The most prevalent serotype was O101:H10. This serotype was found in locations D, GF1, and GF2 and isolated mainly from rectal swabs, as one isolate belonging to this group was found in a water trough. The AMR genotype for O101:H10 isolates was rather uniform (**Figure 3**). Isolates of serotype O53:H18 with the carbapenemase gene blaOXA-48 were only found in farm GF1 and were isolated from rectal swabs. All isolates belonging to this group were identical with regard to their phenotype and genotypes (**Table 2**, **Figures 2**, **3**). The serotype O8:H9 with blaOXA-181 was found only once in farm D from a rectal swab. For isolates where only the H-antigen H6 was found, a very similar AMR genotypes was detected. Such isolates were found in all investigated farms and sample types.

#### DISCUSSION

In 2014, four dairy farms in northern Egypt were investigated for ESBL-producing E. coli. In total, 210 clinically healthy dairy cattle were sampled using rectal swabs. Additionally, 56 environmental swabs were taken from different stall objects and screened for multi-drug resistant bacteria. All swabs were precultured on BrillianceTM ESBL Agar, and in 114 of 266 samples (42.8%), ESBL-producing E. coli were detected. To analyze the underlying molecular AMR mechanism, all 114 isolates were genotyped using the multiplex microarray technique. The most frequently detected gene which mediated resistance against 3G cephalosporins was blaCTX-M1/15 (90.4%). The genes blaCTX-M9 (5.3%) and blaTEM (78%), which also mediate resistance to 3G cephalosporins, were also detected. However, both were usually found in combination with blaCTX-M1/15. BlaCTX-M9 was related to resistance to 3G cephalosporins in just one isolate as well as blaTEM in four isolates. A comparison to data similar to data from this study is difficult due to missing reports from Egypt. Recently, two reports from Germany are known describing the

FIGURE 2 | Overview of antimicrobial resistance pattern. Antimicrobial resistant genes of all *E. coli* isolates obtained from swab samples (healthy dairy cattle and/or environment). Also given are the farm IDs, sample sources and sampling dates.

#### TABLE 1 | Antimicrobial resistance genes and their frequency in *E. coli* isolates detected by microarray.

**93**

TABLE 2 | Continued

*bAK amikacin, CN gentamicin,*

*c3G cephalosporin*

 *– 3rd generation cephalosporin.*

 *TOB tobramycin,*

 *FEP cefepime, CTX cefotaxime,*

 *CAZ ceftazidime,*

 *MEM meropenem,*

 *IMP imipenem, TE tetracycline,*

 *TGC tigecycline, STX co-trimoxazole,*

 *CIP ciprofloxacin,*

 *MXF moxifloxacin.*

FIGURE 3 | Overview of microarray-based serotyping. Serotype of all *E. coli* isolates obtained from swab samples (healthy dairy cattle and/or environment). Also given are the farm IDs, sample sources and sampling dates.  Like in the present study, in both reports the most prevalent ESBL group was CTX-M. Schmid et al. (2013) collected a total of 598 samples that yielded 196 ESBL-producing E. coli (32.8%). The high percentage of ESBL-producing E. coli in healthy animals shows the high zoonotic risk for people working in close contact to animals. With this background Dahms et al. (2015) investigated different farms for ESBL-producing bacteria in samples collected from livestock and also from farm workers. In total, 70.6% of the tested farms and 5.8% of the farm workers were positive for ESBL-producing bacteria. In contrast, a study from Burgundy in France in 2012 showed only a low prevalence, of about 5%, of ESBL-producing bacteria in feces samples from different farms (Hartmann et al., 2012).

Due to the preselection of all samples on BrillianceTM ESBL agar, carbapenem resistant isolates were also retrieved. In six isolates, carbapenemase genes were detected using the CarbDetect AS-1 kit. In five isolates from a stall on farm GF1, blaOXA-48 was found. These isolates were phenotypically and genotypically identical. Interestingly, another isolate was found containing blaOXA-181, a gene belonging to the blaOXA-48 like family. Both genes are also widely distributed in human pathogens that cause hospital-acquired infection (Poirel et al., 2012). Carbapenems are last-line antibiotics with a broad spectrum and a high efficacy, and are stable against ESBLs. As they can only be administered intravenously, carbapenems are used exclusively in the clinical environment, and are not known to be used in animal husbandry. While carbapenemaseproducing Enterobacteriaceae (CPE) are mostly described in hospitalized humans (Nordmann et al., 2011; Abdallah et al., 2015b), the current study shows conclusively that such CREs are also found in farm animals including apparently healthy dairy cattle. The detection of carbapenem resistant isolates in such an environment and the threat that such multi-drug resistance bacteria ends up in consumer food (e.g., milk or dairy products), raises serious concerns about public health. Carbapenemaseproducing isolates have been detected in poultry farms (Abdallah et al., 2015a), but there are to date no reports describing finding of these multi-drug resistant bacteria in dairy cattle farms in Egypt.

Given that the majority of samples that contained ESBL/carbapenemase-producing bacteria originated from rectal swabs, this raises the question of how the potentially contaminated feces are disposed of. Normally, dung is used as fertilizer in agriculture. Via this route, multi-drug resistant pathogens might get into the food chain, either directly through

#### REFERENCES

consumption of meat, or indirectly from cattle grazing on fertilized pasture. Another major problem raises up in this context, the resistance genes described in this paper are usually found on plasmids (Chanawong et al., 2001; Paterson and Bonomo, 2005; Duan et al., 2006; Wittum et al., 2010; Brolund, 2014; Hansen et al., 2014; Valentin et al., 2014) and such mobile elements can be easily transferred to and between environmental bacteria (Aminov, 2011; Berglund, 2015), as well as to other human pathogens (Pitout et al., 2015). This poses a high risk to the environment, and the human population.

#### CONCLUSION

To the best of our knowledge, this study is the first report which analyses the prevalence of ESBL-producing E. coli in Egyptian dairy farms based on genotyping and phenotyping data. The high percentage of ESBL-positive isolates and even of carbapenemase-producing bacteria was alarming given the relevance of 3G cephalosporins and carbapenems in modern medicine. Additionally, the isolates had a highly diverse genetic background with regard to serotype, virulence and antimicrobial resistance markers (**Figures 2**, **3**). Experiments showed a high degree of concordance between genotype and phenotype.

Strict hygiene measures are mandatory to control the spread, the transmission dynamics and potential zoonotic risk factors of ESBL- and carbapenemase-producing bacteria in dairy farms.

#### AUTHOR CONTRIBUTIONS

SB, HE, and HH conceived of the study, and participated in its design and coordination. SB, IE, and DW carried out the genotyping and serotyping. SB and IE carried out the antimicrobial resistance pattern by VITEK-2. MA and HE participated in sampling. HE, HH, and MA participated in preliminary design as well as bacteriological analysis of part of the study. SB, SM, HE, HH, and RE drafted the manuscript. All authors read and approved the final manuscript.

#### ACKNOWLEDGMENTS

We thank Keri Clack (Alere Technologies, Jena, Germany) for proof reading the manuscript, Annett Reißig (Alere Technologies, Jena, Germany) and Elke Müller (Alere Technologies, Jena, Germany) for excellent technical support, Christina Braun for continuous support as well as for proof reading of the manuscript.

and carbapenemase-producing Enterobacteriaceae isolated from Egyptian patients with suspected blood stream infection. PLoS ONE 10:e0128120. doi: 10.1371/journal.pone.0128120

**Conflict of Interest Statement:** SB, DW, SM, IE, and RE are employees of Alere Technologies GmbH, the company that manufactures the microarrays also used in this study. This has no influence on study design, data collection and analysis, and this does not alter the authors' adherence to all the Frontiers policies on sharing data and materials.

The other authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Braun, Ahmed, El-Adawy, Hotzel, Engelmann, Weiß, Monecke and Ehricht. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Development of a High Resolution Virulence Allelic Profiling (HReVAP) Approach Based on the Accessory Genome of *Escherichia coli* to Characterize Shiga-Toxin Producing *E. coli* (STEC)

Valeria Michelacci 1 \*, Massimiliano Orsini 2 , Arnold Knijn3 , Sabine Delannoy 4 , Patrick Fach4 , Alfredo Caprioli 1 and Stefano Morabito1

#### *Edited by:*

Pina Fratamico, United States Department of Agriculture-Agricultural Research Service, USA

#### *Reviewed by:*

James L. Bono, United State Department of Agriculture- Agricultural Research Service, USA Erin R. Reichenberger, United States Department of Agriculture, USA

> *\*Correspondence:* Valeria Michelacci<EMAIL_ADDRESS>
#### *Specialty section:*

This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

*Received:* 26 November 2015 *Accepted:* 05 February 2016 *Published:* 23 February 2016

#### *Citation:*

Michelacci V, Orsini M, Knijn A, Delannoy S, Fach P, Caprioli A and Morabito S (2016) Development of a High Resolution Virulence Allelic Profiling (HReVAP) Approach Based on the Accessory Genome of Escherichia coli to Characterize Shiga-Toxin Producing E. coli (STEC). Front. Microbiol. 7:202. doi: 10.3389/fmicb.2016.00202 1 European Reference Laboratory for Escherichia coli, Dipartimento di Sanità Pubblica Veterinaria e Sicurezza Alimentare, Istituto Superiore di Sanità, Rome, Italy, 2 Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Teramo, Italy, 3 Servizio Informatico, Documentazione, Biblioteca e Attività Editoriali, Istituto Superiore di Sanità, Rome, Italy, 4 Platform IdentyPath, Food Safety Laboratory, ANSES, Université Paris-Est, Maisons-Alfort, France

Shiga-toxin producing Escherichia coli (STEC) strains possess a large accessory genome composed of virulence genes existing in multiple allelic variants, which sometimes segregate with specific STEC subpopulations. We analyzed the allelic variability of 91 virulence genes of STEC by Real Time PCR followed by melting curves analysis in 713 E. coli strains including 358 STEC. The 91 genes investigated were located on the locus of enterocyte effacement (LEE), OI-57, and OI-122 pathogenicity islands and displayed a total of 476 alleles in the study population. The combinations of the 91 alleles of each strain were termed allelic signatures and used to perform cluster analyses. We termed such an approach High Resolution Virulence Allelic Profiling (HReVAP) and used it to investigate the phylogeny of STEC of multiple serogroups. The dendrograms obtained identified groups of STEC segregating approximately with the serogroups and allowed the identification of subpopulations within the single groups. The study of the allelic signatures provided further evidence of the coevolution of the LEE and OI-122, reflecting the occurrence of their acquisition through a single event. The HReVAP analysis represents a sensitive tool for studying the evolution of LEE-positive STEC.

Keywords: accessory genome, allelic variants, STEC subtyping, phylogenesis, bioinformatics

## INTRODUCTION

Human infections with Shiga-toxin producing Escherichia coli (STEC) cause a wide range of symptoms including uncomplicated diarrhea, hemorrhagic colitis, and the life-threatening hemolytic uremic syndrome (HUS) (Caprioli et al., 2005). The main virulence feature of STEC is the ability to produce Shiga-toxins (Stx), which interfere with the protein synthesis in the target cells, eventually causing their death (O'Brien and Holmes, 1987). The capacity to produce Stx is acquired through infection with bacteriophages conveying the stx genes, which can remain stably integrated into the bacterial chromosome (O'Brien et al., 1984).

In spite of the striking biological effect exerted by the Stx, their sole production seems not to be sufficient for causing the disease, at least the most severe forms. As a matter of fact, only a few STEC serogroups are usually isolated from human cases of severe disease (Nataro and Kaper, 1998; Karmali et al., 2003), which share the presence in the genome of mobile genetic elements (MGEs) encoding robust machineries for the colonization of the host gut (McDaniel and Kaper, 1997; Paton et al., 2001; Morabito et al., 2003; Imamovic et al., 2010; Michelacci et al., 2013). Three Pathogenicity Islands (PAIs) have been described in the genome of such STEC serogroups: the locus of enterocyte effacement (LEE) (McDaniel and Kaper, 1997), the OI-122 (Karmali et al., 2003; Morabito et al., 2003), and the OI-57 (Imamovic et al., 2010).

The LEE locus governs the ability to induce the typical "attachment and effacement" (A/E) lesion on the enterocyte. It encodes a type three secretion system, effectors subverting the cell functions related with the cytoskeleton assembly and maintenance, and factors mediating the intimate adhesion of the bacterium to the enterocyte, including the adhesin intimin (McDaniel and Kaper, 1997). The other two PAIs carry genes whose products are also involved in the mechanism of colonization, such as Efa1/LifA, encoded by a gene present in the OI-122 (Morabito et al., 2003), and AdfO (Ho et al., 2008), whose genetic determinant is conveyed by the OI-57 (Imamovic et al., 2010).

During the last decades different authors deployed schemes for the classification of the different STEC types (Griffin and Tauxe, 1991; Nataro and Kaper, 1998; Karmali et al., 2003). One of these schemes groups the STEC strains based on the serogroup, relative incidence of human infections, ability to cause severe diseases, association with outbreaks and presence of virulence-associated MGEs in the genome (Karmali et al., 2003). According to this classification, STEC are divided into seropathotypes (SPTs), identified with letters from A to E in a decreasing rank of pathogenicity. SPT A comprises STEC O157, while SPT B includes the STEC belonging to serogroups different from O157 but causing both sporadic cases and outbreaks of HUS, namely O26, O103, O111, O145, and O121. SPTs A and B share the presence of the LEE, OI-57, and OI-122 PAIs in their genome. The SPT C includes a number of STEC serogroups, including O113 and O91, which apparently do not harbor the LEE locus but are sporadically isolated from severe infections. Finally, STEC included in the SPTs D and E have rarely or never been associated with human disease respectively (Karmali et al., 2003). For the last three SPTs the information on the presence and integrity of the three PAIs are scanty.

The complexity of the STEC virulome is an important source of strain genomic variability, which is further augmented by the existence of multiple allelic variants of the virulence genes. Some of the subtypes of stx2 have been significantly associated with the most severe infection (Friedrich et al., 2002), while some other subtypes of both stx1 and stx2 seemed to be primarily associated with a milder course of the disease or confined to animal hosts (Friedrich et al., 2002; Bielaszewska et al., 2006; Persson et al., 2007; Scheutz et al., 2012). A considerable heterogeneity has also been identified in the DNA sequence of the intimin-coding gene eae, leading to the identification of at least 18 intimin types

In the present study we developed an approach to simultaneously identify the presence and the allelic types of a large panel of genes carried by the LEE locus, OI-122, and OI-57 PAIs and used it to study the phylogeny of STEC belonging to SPT A, B and C.

## MATERIALS AND METHODS

### Bacterial Strains

A total of 713 E. coli strains positive for at least one of the three pathogenicity islands LEE, OI-122, and OI-57 were selected among the isolates present in the culture collections of the Istituto Superiore di Sanità (ISS, Rome, Italy) and the Agence Nationale de Sécurité Sanitaire de l'Alimentation, de l'Environnement et du travail (ANSES, Maisons Alfort, France) and used to identify the alleles of the genes harbored by the three PAIs. The panel comprised 358 STEC strains belonging to serogroups O157 (n = 81), O26 (n = 32), O111 (n = 36), O103 (n = 8), O145 (n = 8), O121 (n = 3), and others (n = 190) isolated from unrelated human cases of human infections and from food in Italy and France in the period 2008–2011. Additional 355 stx-negative E. coli of multiple serogroups and isolated from human, food and animal sources in the same countries and period were included in the study. The O157 STEC strain EDL933 was used as positive control (Supplementary Table 1, Sheet 1).

A population of 318 unrelated STEC strains, part of the panel of strains described above, was used to assess the performance of the HReVAP approach. These included 161 isolates of SPTs A and B and belonging to serogroups O157 (n = 81), O26 (n = 32), O111 (n = 33), O103 (n = 5), O145 (n = 7) and O121 (n = 3) and 157 eae-negative strains, of serogroups O91 (n = 14), O174 (n = 10), O113 (n = 9), O104 (n = 6), O101 (n = 3), O153 (n = 3), O21 (n = 3), and others (n = 109). The study population also included a panel of 36 stx-negative eae-positive E. coli, altogether referred to as EPEC, including the following serogroups: O26 (n = 12), O127 (n = 5), O55 (n = 4), O128 (n = 3), O125 (n = 3), O111 (n = 2), O86 (n = 2), and others (n = 5).

Finally, 39 out of the 161 SPTs A and B STEC were also subjected to whole genome sequencing, followed by Multi Locus Sequence Typing (MLST) and Whole genome SNP analysis with the aim of comparing HReVAP results with those obtained using these DNA-sequence-based methods. The latter isolates included strains belonging to serogroups O157 (n = 16), O26 (n = 12), O111 (n = 7), O103 (n = 2), O145 (n = 1), and O121 (n = 1).

### Real-Time PCR and Melting Curves Analysis

Ninety-one primer pairs were deployed to amplify 100–300 bp fragments from as many genes harbored on the three PAIs LEE, OI-122, and OI-57 (38, 12, and 41 genes from each island, respectively). The genomic sequence of the O157 STEC strain EDL933 (Acc. no. AE005174) was used to design the primer pairs using the Primer-BLAST web-tool available on the NCBI webserver. Some of the primers were degenerated to amplify the target genes in all the STEC strains for which a sequence was available in GenBank. The sequences of primers used in this study and their annealing position on the genomic sequence of EDL933 strain are reported in **Table 1**.

Total DNA was extracted from overnight cultures of the strains with the Nucleospin Tissue extraction kit (Macherey-Nagel, Düren, DE).

The Real-Time PCR reactions were performed on the high throughput BioMark Real Time PCR system with 96.96 Genotyping Dynamic Array Chips (Fluidigm, San Francisco, CA), using the EvaGreen DNA binding dye (Biotium Inc., Hayward, CA). The thermal profile was 95◦C for 10 min (enzyme activation) followed by 35 cycles of 95◦C for 15 s and 60◦C for 1 min (amplification step). Finally, a denaturation step was performed and the melting curves of the amplified products were registered. Eight array chips were used to perform the whole panel of reactions, each including a positive template control consisting in the DNA extracted from an overnight culture of the EDL933 strain. In addition to the 91 genes, each sample was also subjected to amplification of the stx genes (Perelle et al., 2004) and the wecA housekeeping gene, used as marker for E. coli species (Forward primer: 5′ -CTTTATCTCAGTAGCCTGGG-3′ , Reverse primer: 5′ -AGGAAGTAACCAAACGGTCC-3′ ).

### High Resolution Virulence Allelic Profiling Analysis (HReVAP)

The melting temperatures (Tm) of the amplicons were normalized using the Tm of the PCR products amplified from the positive control strain EDL933 present in each array chip. Normalization values were obtained for each array chip minimizing the mean of the Tm standard deviations for the eight normalized Tm measurements over each gene as well as the overall maximum value of the normalized Tm ranges of all genes.

The Tm frequency distributions for each gene have been calculated by grouping values in 0.05◦C intervals. The frequency distributions were then analyzed with the "mix" function of the "mixdist" package in the R software (RTeam, 2014). This function finds Maximum Likelihood estimates for the proportions, means, and standard deviations of a mixture distribution by applying a Newton-type iterative method (RTeam, 2014). The number of Gaussians and the starting parameters were adjusted upon evaluation of several fitting results. In order to limit the degrees of freedom, prior knowledge was applied to the model: in each model fit, the standard deviations (σ) of the Gaussian curves were left variable but constrained to be equal. The following command was used for the analysis: mix[Tm\_dat, Tm\_par, dist = "norm," mixconstr(conmu = "NONE," consigma = "SEQ")], where Tm\_dat is the data frame of the grouped Tm data and Tm\_par a data frame of the starting values for the parameters of the distributions. Several normal distributions were observed for each gene at different intervals of temperatures. Before clustering, Tm values were aggregated into numbered classes utilizing the model fitting results to define temperature intervals for distinct alleles. The interval limits were calculated as the points of intersection between two adjoining Gaussian curves with the same standard deviation according to the following equation:

$$T\_{\text{int}}\left(^{\circ}\text{C}\right) = \frac{\mu\_1^2 - \mu\_2^2 - 2\,\sigma^2 \ln\left(\frac{\pi\_1}{\pi\_2}\right)}{2\mu\_1 - 2\,\mu\_2} \text{ (1)}$$

Tint = Temperature at the point of intersection between Gaussian 1 and 2

µi = Mean temperature of the Gaussian curve i = 1, 2

σ = Standard deviation of the Gaussian curves

πi = Amplitude of the Gaussian curve i = 1, 2

The model fitting used did not prove optimal for allele assignment due to the proximity of many Gaussian curves, with consequent overlap. Therefore, all fits have been revised trying to keep the maximum number of Gaussian curves in the model while aggregating those heavily overlapping. With this procedure, the resolution of the method (capacity of allele distinction) has been lowered in benefit of the precision of the method (convergence of assignments). The Tm intervals identified by peaks in the distributions obtained from the analysis of each gene were used to identify the alleles, which were labeled with numbers in ascending order according to the position of the peak in the temperature distribution (Supplementary Table 2). Each strain was given a numeric allelic signature comprising the alleles of all the genes analyzed.

The neighbor software of the Emboss package for samples clustering with default parameters (Rice et al., 2000) was used to compare the allelic signatures and to obtain distance matrices.

Each step of the above described procedure has been implemented in dedicated python classes, including the neighbor software that was wrapped together with the TreeGraph software (Stover and Muller, 2010) for graphical trees representation.

The HReVAP software package was deployed and used on the public computational framework ARIES operating on the servers of the Istituto Superiore di Sanità and based on the Galaxy bioinformatics platform (Giardine et al., 2005; Blankenberg et al., 2010; Goecks et al., 2010) (https://w3.iss.it/site/aries/).

The tree files (.tre) produced with the HReVAP clustering algorithm were downloaded and visualized using the FigTree program version 1.4.0 (Drummond et al., 2012).

### Whole Genome Sequencing of STEC and Phylogenetic Analyses

Thirty-nine out of the 161 STEC strains used for the HReVAP typing were subjected to whole genome sequencing using the Library Preparation Kit by Kapa Biosystems (Wilmington, MA, USA) and a paired end 100 bp protocol on an Illumina HiSeq2500 instrument in fast run mode according to manufacturers' instructions. The sequencing reads have been uploaded in the EMBL-ENA sequence database (EMBL European Nucleotide Archive Study accession no. PRJEB11886). The raw reads were trimmed to remove the adaptors and to accept 27 as the lowest Phred value and assembled using the de novo assembly tool Edena v3 (Hernandez et al., 2008). The contigs were subjected to in silico Multi Locus Sequence Typing (MLST) with the protocol described by Wirth and colleagues (Wirth et al., 2006). Whole genome Single Nucleotide Polymorphism (WG-SNP) analysis was performed using the ksnp3 pipeline (Gardner et al., 2015), using 19 as kmer size. The optimum value for the kmer size was selected as that producing the highest number of unique kmers of the median length in all the genomes of the dataset and it was calculated by using the kchooser tool included in the ksnp3 pipeline. All the bioinformatics analyses were performed through the ARIES webserver (https://w3.iss.it/site/aries/).

### RESULTS

## HReVAP: Identification of the Alleles

The analysis of the 91 genes conveyed by the three pathogenicity islands LEE, OI-122, and OI-57 allowed identifying a total of 476 alleles (Supplementary Table 1, Sheet 1 and Supplementary Table 3). Each gene displayed 2 to 10 different alleles in the study population.

The eae-positive strains included in the panel exhibited the presence of 32 out of the 38 LEE-harbored genes on average, while the strains positive for the marker of OI-122, efa1-lifA, were positive for the majority of the 12 genes selected on this PAI (10.8 genes on average). The OI-57 showed the widest variability. As a matter of fact, 10.4% of the isolates proved positive for 1 to 10 genes of PAI OI-57, 30.6% were positive for 11–20 genes, 26% fell in the range of 21–30 genes detected and 33% gave positive result for more than 31 out of the 41 targets considered (Supplementary Table 1, Sheet 1).

The genes conveyed by the LEE and the OI-122 islands showed a mean number of alleles of 4.79 (range: 2–8 alleles; median = 5) and 4.17 (range: 3–8 alleles; median = 4) for each gene, respectively, while those part of the OI-57 were the most variable, displaying a mean value of 5.95 alleles each (range: 3– 10 alleles; median = 6) (**Figure 1** and Supplementary Table 3). Interestingly, the LEE locus displayed a uniform allelic variation throughout its whole length while the OI-122 and the OI-57 appeared to have a slightly higher number of alleles in the leftmost part (**Figure 1**).

### HReVAP Performance: Amplification of the LEE, OI-122, and OI-57 Targets in STEC and EPEC

All the LEE-genes could be amplified in the vast majority of the STEC strains belonging to SPTs A and B (**Figure 2A** and Supplementary Table 1, Sheet 2). In detail, no negative results were obtained for all the O157 and O145 strains tested, with the only exception of one O145 strain, negative for eight targets. Nine LEE-borne genes, namely the open reading frames (ORF) Z5101, Z5107, Z5111, Z5112, Z5114, Z5117, Z5121, Z5122, and Z5127 were more variable in the STEC serogroups other than the O157 and O145, with more than 60% of the STEC O26 strains tested producing no amplicons. The same nine targets could not be amplified in all the STEC O103 and O121 strains, with a few exceptions (**Figure 2A**). Four of these nine gene targets (Z5107, Z5112, Z5114, and Z5122) could not be amplified from the whole

OI-122. (C) Results of the ORFs harbored by the OI-57.

panel of the STEC O111, while ORF Z5101 gave positive result in only two strains of this serogroup.

As for the OI-122 PAI, all the 12 ORFs selected were detected in the whole panel of STEC O157, O111, and O121 strains, with the only exception of one O157 strain, which was negative for the three ORFs Z4331, Z4332, and Z4333 (**Figure 2B** and Supplementary Table 1, Sheet 2).

The STEC strains belonging to serogroups O145, O103, and O26 showed different amplification profiles, with the four ORFs Z4318, Z4320, Z4321, and Z4322 negative in 60% of the O103 strains and in the majority of O145 and O26 strains (**Figure 2B**).

The HReVAP typing of the STEC and EPEC confirmed the highest degree of variation of PAI OI-57. In particular, ORFs Z2112, Z2114, and Z2116 could not be amplified in many STEC O26, O157, and O145 while ORFs Z2090 and Z2091 were not detected in all the STEC O111, in the majority of STEC O26 strains, and in some STEC O145 and O157. Finally, the ORF Z2085 was frequently negative in STEC O111 and O26 (**Figure 2C** and Supplementary Table 1, Sheet 2).

Unexpectedly, the eae-negative STEC strains tested also showed positivity to many targets of the PAI OI-57 (**Figure 2** and Supplementary Table 1, Sheet 3). In particular, two ORFs, Z2054, and Z2101, were positive in more than 95% of the strains tested, while genes Z2037, Z2039, Z2056, Z2057, Z2060, Z2069, Z2071, Z2084, Z2086, Z2096, Z2118, Z2131, and Z2146, were positive in more than 50% of the population assayed.

As a whole, a mean of 15.9 targets out of the 41 selected for OI-57 were present in the panel of eae-negative STEC strains (range: 5–39; median = 15) (Supplementary Table 1, Sheet 3).

The EPEC strains assayed provided different amplification patterns (**Figure 2** and Supplementary Table 1, Sheet 4). As expected, the LEE-borne ORFs and the OI-122 targets followed a pattern of positivity to PCR similar to that displayed by the STEC belonging to SPTs A and B, although with some variation. The OI-57 was present in all the EPEC strains tested but showed two regions of major variability encompassing the ORFs Z2090-Z2093 (negativity range: 72.2–83.3%) and Z2112-Z2116 (negativity range: 75–77.78%) (**Figure 2** and Supplementary Table 1, Sheet 4).

#### HReVAP Typing: Allelic Variability of the LEE, the OI-122, and the OI-57

The allelic variability of the genes harbored by the three pathogenicity islands LEE, OI-122, and OI-57 has been investigated in the same study population used to assess the HReVAP performance.

The clustering of the allelic signatures of the STEC strains of SPTs A and B produced a dendrogram whose branches segregated with the serogroups, with a few exceptions (**Figure 3A**). In particular, the cluster formed by STEC O157 strains appeared clearly distinct from the others and much more homogeneous, while the strains belonging to O111 and O26 serogroups were divided in two and three distinct clusters, respectively. Similar results were obtained when the cluster analysis was carried out separately using the allelic signatures produced with the ORFs of the LEE locus (**Figure 3B**) and of the PAI OI-122 only (**Figure 3C**). Such dendrograms displayed the same topology of that produced when the alleles of the complete ORFs panel were used but showed a lower intra-cluster resolution. More complex results were instead obtained from the HReVAP analysis of the genes conveyed by the OI-57, reflecting the highest variability observed in the ORFs of this PAI (**Figure 3D**). Even if the main groups corresponding to STEC serogroups O157, O111, and O26 could still be detected, the overall topology showed wider and less defined branches.

The topology of the dendrograms obtained with the EPEC isolates resembled that of those produced with the STEC of SPTs A and B allelic signatures. However, the higher variability of EPEC, together with the lower number of isolates tested, caused the output to be less definite (**Figure 4**).

As for the eae-negative STEC strains, the cluster analysis of the allelic signatures was carried out exploiting the observed positivity to many of the ORFs of the OI-57. Although based on a smaller number of targets, this analysis showed a massive variability in the allelic signatures, yet able to distinguish and group different populations of strains (**Figure 5**).

### Comparison between HReVAP and the DNA Sequence-Based MLST and Whole Genome-SNP Analyses

Thirty-nine STEC strains were used to compare the results of the HReVAP with those produced by DNA sequence-based typing techniques. The strains were either analyzed with the HReVAP or their genomes subjected to in silico MLST and WG-SNP analysis. The comparison showed that the HReVAP (**Figure 6A**) had a much higher discriminatory power than the MLST (**Figure 6B**) and produced a dendrogram similar

labeled according to the following color legend: dark blue for O157, red for O26, green for O111, pale blue for O103, purple for O145, and black for O121. (A) Dendrogram of the allelic signatures from all the 91 ORFs. (B) Dendrogram of the allelic signatures obtained with the ORFs of the LEE locus. (C) Dendrogram of the allelic signatures obtained with the ORFs of the OI-122. (D) Dendrogram of the allelic signatures obtained with the ORFs of the OI-57.

#### TABLE 1 | List of primers used in this study.

#### TABLE 1 | Continued

#### TABLE 1 | Continued

TABLE 1 | Continued

to that produced with the WG-SNP (**Figure 6C**). Apparently, the topology of the HReVAP dendrogram allowed identifying differences within the serogroups, that were not visible in the WG-SNP-based dendrogram.

#### DISCUSSION

The detection of the enzyme isoforms or of the polymorphisms in the genomes of pathogenic microorganisms has been for a long time the basis for the identification of molecular profiles of isolates. Bacterial subtyping has been largely used in research studies on the evolution of bacterial pathogens since the first development of typing methods such as the multi locus enzyme electrophoresis (Selander and Levin, 1980; Selander et al., 1986; Donkor, 2013) and the pulsed field gel electrophoresis (Arbeit et al., 1990), followed by the elaboration of schemes for the identification of the allelic forms of genes as in the multi-locus sequence typing (MLST) (Maiden et al.,

1998). Moreover, molecular typing of microorganisms soon demonstrated its great potential in the control of infectious diseases through the implementation of surveillance programs aiming at limiting the burden of infections (Swaminathan et al., 2001). Nowadays, molecular subtyping of bacteria can benefit from cutting edge technologies such as the next generation sequencing (NGS) allowing the detection of whole genome single nucleotide polymorphism (SNP) (WG-SNP) (Kuroda et al., 2010; Vogler et al., 2011; Joensen et al., 2014; Dallman et al., 2015b).

WG-SNP has been successfully used to define a typing scheme for the surveillance of Listeria monocytogenes infections (Commission Decision, 2010). However, its application to bacterial pathogens such as E. coli, although advisable, is still under debate given the extensive genomic variability of this bacterial species. The development of WG-SNP-based typing concepts for E. coli has been attempted by several authors and proved successful for some STEC serogroups such as O157 and, to a lesser extent, O26 (Dallman et al., 2015a,b,c; Holmes et al., 2015; Jenkins et al., 2015). However, a single approach successfully applicable to all the STEC serogroups has not been developed yet.

We have deployed a typing scheme for STEC based on the evaluation of polymorphisms in the sequence of a large panel of virulence genes through the determination of the melting temperature of Real-Time PCR amplicons. Such an approach originated from multiple considerations. The virulence genes, part of the accessory genome, have a higher variability than the rest of the genome. Such an increased variability would reduce the number of targets needed for the phylogenetic analysis.

Additionally, comparing the allelic combinations of the fraction of genome shared by all the members of a pathotype (e.g., STEC) should overcome the need of finding an appropriate reference or setting a threshold for the diversity, which would introduce a bias in the evaluation of clusters. These aspects both represent limitations of the currently described whole genome sequence-based methods for E. coli (Dallman et al., 2015a,b,c; Holmes et al., 2015; Jenkins et al., 2015). Finally, the use of the widely diffused Real Time PCR to obtain the strains' signatures makes it not necessary to resort to NGS, which is only available in reference laboratories and requires skills and knowledge of the downstream bioinformatics applications that might be unavailable in most of the front-line laboratories.

The rationale behind the proposed concept resides in the many studies published on the allelic variants of known virulence genes of STEC, such as the Shiga-Toxin-coding genes (Friedrich et al., 2002; Bielaszewska et al., 2006; Persson et al., 2007; Scheutz et al., 2012) and the eae gene (Oswald et al., 2000; Tarr et al., 2002; Ito et al., 2007; Madic et al., 2010), as well as the more recently described subAB and toxB genes (Tozzoli et al., 2010; Michelacci et al., 2013, 2014). All the mentioned papers described the association between specific alleles and sub-populations of STEC strains. We investigated the allelic forms of 91 virulence genes conveyed by the three main MGEs associated with STEC pathogenicity, namely the LEE, the OI-122, and the OI-57 (McDaniel and Kaper, 1997; Karmali et al., 2003; Imamovic et al., 2010) and used the obtained allelic signatures to investigate the phylogenesis of STEC.

The whole process, termed High Resolution Virulence Allelic Profiling (HReVAP), allowed us to identify a range of 2–10 allelic forms for each of the 91 ORFs, resulting in the impressive number of 476 total alleles generating a high number of unique allelic signatures.

The HReVAP clustered the LEE-positive STEC strains into groups approximately segregating with the serogroup, providing an indication that the allelic signatures were not randomly assigned to the isolates. Additionally, the analysis identified different subpopulations within the serogroups and also showed variability within each of the populations identified (**Figure 3**). This finding was not unexpected, since all the strains used in the test panel were epidemiologically unrelated, and at the same time provided an indication that the HReVAP might also be successful in identifying clusters of related strains such as those derived from an outbreak.

The HReVAP produced allelic signatures also with eaenegative STEC. However, the dendrogram obtained with these strains had a less resolved topology (**Figure 5**). An explanation of this result resides either in the lower number of genes these isolates are positive for or in the low number of strains in each serogroup, which in some cases only included one isolate. Nevertheless, the finding that at least part of this PAI

was frequently present in eae-negative STEC is interesting and constitutes the first report of the presence of this PAI, or its remnants, in this group of STEC.

The HReVAP analysis also proved useful in following the evolution of the single MGEs considered for the typing scheme. As a matter of fact, we could visualize a similar pattern of variation in the allelic signatures obtained considering the ORFs of the LEE locus and the OI-122 (**Figures 3B,C**). This result indicates that the two MGEs underwent similar evolutionary pathways and supports the previous hypothesis about their common acquisition through a single event of horizontal gene transfer in certain STEC and EPEC strains (Morabito et al., 2003).

Our results showed that the OI-57 had the greatest genetic variability, displaying the highest number of alleles on average for all the ORFs considered (**Figure 1C** and Supplementary Table 3). Additionally, the analysis of the allelic signatures obtained considering the OI-57 ORFs produced dendrograms with the most dispersed topology (**Figures 3D**, **4D**). These observations suggest that this MGE could have been acquired at an early stage of the evolutionary pathway that led to the emergence of STEC. Additionally, since the LEE-negative STEC investigated were also positive for many of the OI-57-related ORFs considered in this study, it can be hypothesized that such an island could be a common heritage of STEC independently of the presence of the LEE locus.

Finally, the comparison of the performance of the HReVAP with that obtained with other comparative genomic tools such as the MLST and the WG-SNP analysis substantiates the robustness of the HReVAP in identifying LEE-positive STEC populations with a much higher resolution with respect to the MLST and a comparable level of discrimination to that of the WG-SNP.

In conclusion, the HReVAP approach demonstrated good sensitivity and high resolution in the molecular characterization of STEC, particularly for the LEE-positive strains. Moreover, the incredibly large virulome of pathogenic E. coli offers the opportunity to refine the HReVAP typing strategy for other STEC groups, such as the LEE-negative isolates, or even to extend it to other E. coli pathotypes by integrating the panel of targets.

Further work is in progress to assess the use of HReVAP as an effective tool for the surveillance of STEC infections and to obtain the allelic signatures from whole genome sequences in order to make this technique a cross-generational tool connecting the Real-Time PCR and the NGS-based applications.

#### AUTHOR CONTRIBUTIONS

VM conceived the experimental design and drafted the manuscript, MO developed the scripts for HReVAP clustering, and critically revised the manuscript, AK developed and applied the scripts for the extraction of the allelic signatures of the HReVAP and critically revised the manuscript, SD and PF designed the Real Time PCR primers, performed the amplifications and melting curve analyses and participated in the revision of the manuscript, AC contributed to the revision of the draft manuscript for important intellectual content, SM conceived the study and thoroughly revised the manuscript. Finally, all the authors approved the manuscript to be published.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00202

## REFERENCES

detection and epidemiological surveillance. J. Clin. Microbiol. 53, 3565–3573. doi: 10.1128/JCM.01066-15

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Michelacci, Orsini, Knijn, Delannoy, Fach, Caprioli and Morabito. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Revisiting the STEC Testing Approach: Using *espK* and *espV* to Make Enterohemorrhagic *Escherichia coli* (EHEC) Detection More Reliable in Beef

Sabine Delannoy 1 , Byron D. Chaves 2 , Sarah A. Ison2 , Hattie E. Webb2 , Lothar Beutin3 , José Delaval 4 , Isabelle Billet 5 and Patrick Fach1 \*

1 Food Safety Laboratory, Université Paris-Est, Anses (French Agency for Food, Environmental and Occupational Health and Safety), Platform IdentyPath, Maisons-Alfort, France, 2 Department of Animal and Food Sciences, Texas Tech University, Lubbock, TX, USA, 3 Division of Microbial Toxins, National Reference Laboratory for Escherichia coli, Federal Institute for Risk Assessment, Berlin, Germany, 4 Laboratoire de Touraine, (LDA37) Conseil Départemental, Tours, France, 5 SAS Charal Groupe Bigard, Cholet, France

#### *Edited by:*

Pina Fratamico, United States Department of Agriculture, Agricultural Research Service, USA

#### *Reviewed by:*

James L. Smith, United States Department of Agriculture, USA George Carl Paoli, United States Department of Agriculture, USA

> *\*Correspondence:* Patrick Fach<EMAIL_ADDRESS>
#### *Specialty section:*

This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

*Received:* 30 October 2015 *Accepted:* 05 January 2016 *Published:* 22 January 2016

#### *Citation:*

Delannoy S, Chaves BD, Ison SA, Webb HE, Beutin L, Delaval J, Billet I and Fach P (2016) Revisiting the STEC Testing Approach: Using espK and espV to Make Enterohemorrhagic Escherichia coli (EHEC) Detection More Reliable in Beef. Front. Microbiol. 7:1. doi: 10.3389/fmicb.2016.00001

Current methods for screening Enterohemorrhagic Escherichia coli (EHEC) O157 and non-O157 in beef enrichments typically rely on the molecular detection of stx, eae, and serogroup-specific wzx or wzy gene fragments. As these genetic markers can also be found in some non-EHEC strains, a number of "false positive" results are obtained. Here, we explore the suitability of five novel molecular markers, espK, espV, ureD, Z2098, and CRISPRO26:H11 as candidates for a more accurate screening of EHEC strains of greater clinical significance in industrialized countries. Of the 1739 beef enrichments tested, 180 were positive for both stx and eae genes. Ninety (50%) of these tested negative for espK, espV, ureD, and Z2098, but 12 out of these negative samples were positive for the CRISPRO26:H11 gene marker specific for a newly emerging virulent EHEC O26:H11 French clone. We show that screening for stx, eae, espK, and espV, in association with the CRISPRO26:H11 marker is a better approach to narrow down the EHEC screening step in beef enrichments. The number of potentially positive samples was reduced by 48.88% by means of this alternative strategy compared to the European and American reference methods, thus substantially improving the discriminatory power of EHEC screening systems. This approach is in line with the EFSA (European Food Safety Authority) opinion on pathogenic STEC published in 2013.

Keywords: STEC, O157, non-O157, *espK*, *espV*, *ureD*, *Z2098*, CRISPR

## INTRODUCTION

Shiga toxin-producing Escherichia coli (STEC) are important zoonotic pathogens comprising more than 400 serotypes (Beutin and Fach, 2014). A fraction of these serotypes are able to cause bloody diarrhea and may progress to hemolytic uremic syndrome (HUS). This subset of STECs is termed Enterohemorrhagic E. coli (EHEC) (Beutin and Fach, 2014). STEC O157:H7 has been the first pathogenic E. coli whose presence in foodstuffs was regulated. Today, non-O157 STEC infections have increased greatly, sometimes accounting for up to 70% of notified STEC infections (Brooks et al., 2005; Johnson et al., 2006; Gould et al., 2013; EFSA, 2014). Consequently, regulations in the US and in the EU have evolved to include some non-O157 STEC serogroups together with serotype O157:H7.

Successful implementation of these regulations in the food industry across the world requires effective detection methods that are both specific and sensitive. Detection of non-O157 STEC in foods is particularly challenging because these bacteria lack phenotypic characteristics that distinguish them invariably from the large number of non-STEC flora that share the same habitat. Additionally, they may be present in very low numbers, with a heterogeneous distribution in the food matrices. The environment of the food matrix may also trigger stress responses from the STEC strains and induce latent physiological states that further complicate detection (Wang et al., 2013).

In the absence of a clear definition of virulent STEC strains, the ISO/CEN 13136:2012 Technical Specification (ISO, 2012) and US MLG5B.05 (USDA-FSIS, 2014) use a stepwise approach, comprising an initial screening step for virulence genes (Shiga toxin genes, stx, and intimin gene, eae), followed by testing of Oserogroup specific gene markers. Because the stx and eae genes can be independently present in a number of non-pathogenic strains of E. coli and other Enterobacteriaceae, the first screening step generates numerous signals from samples that do not necessarily contain a true EHEC strain. These stx/eae positive enrichments must then be subjected to a second screening targeting the O-group gene markers. As testing is completed on enrichment broths that contain a mixture of different cells, the different target gene signals (i.e., stx, eae, and the O-group markers) may arise from different individual non-pathogenic strains. Lastly it is necessary to perform an isolation step to confirm the presence of the different markers in a single isolate by PCR.

We have previously shown that combining the detection of espK with either espV, ureD, or Z2098 is a highly sensitive and specific approach for identifying the top seven clinically important EHEC serotypes in industrialized countries (Delannoy et al., 2013a). These markers were shown to be preferentially associated with E. coli strains carrying stx and eae genes, known as typical EHEC, and could be used in conjunction with stx/eae screening to better identify samples that may be more likely to contain a true EHEC.

Recently, a new clone of STEC O26:H11 harboring stx2a and strongly associated with HUS has emerged (Bielaszewska et al., 2013). Characterization of O26:H11 stx2 circulating in France (Delannoy et al., 2015a,b) demonstrated that some stx2a or stx2d positive strains do not have any of the espK, espV, ureD, or Z2098 markers. Hence, such clones would evade a first detection step solely based on stx/eae and a combination of those genetic markers. Therefore, we identified a CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) sequence specific for this O26:H11 EHEC French clone (Delannoy et al., 2015a). Detection of this CRISPR sequence would advantageously be combined with stx and eae in the first screening step to identify this new O26:H11 clone. Furthermore, we have previously developed CRISPR-based real-time PCR assays able to detect the top seven EHEC serotypes and the German O104:H4 STEC clone responsible for a very large European STEC outbreak in 2011 (Delannoy et al., 2012a,b; Miko et al., 2013). These CRISPR PCR assays proved highly sensitive and specific when tested on a large collection of E. colistrains comprising various E. coli pathogroups (Delannoy et al., 2012a,b). Such CRISPR markers may substitute O group testing in a more targeted second step.

Different approaches have been tested to refine the detection systems for EHEC. Some involve detection of ecf1, a plasmid gene highly associated with E. coli strains that are positive for stx, eae, and ehxA (Livezey et al., 2015); while others involve detection of specific eae-subtypes (Bugarel et al., 2010). The top seven EHEC serotypes are exclusively associated with certain eae-subtypes (Oswald et al., 2000; Bugarel et al., 2010; Madic et al., 2010). Indeed, O157:H7 and O145:H28 serotypes are associated with the eae-gamma subtype; O26:H11 are associated with the eae-beta subtype; O103:H2, O121:H19, and O45:H2 are associated with the eae-epsilon subtype; and O111:H8 are associated with the eaetheta subtype. Real-time PCR targeting these eae-subtypes were previously developed and tested in raw milk cheese (Madic et al., 2011) and cattle feces (Bibbal et al., 2014). These could also be used as targets in a more targeted second step.

We attempted to develop an alternative real-time PCR-based approach to improve the detection of the clinically important EHEC by reducing the number of potential positive samples that require further confirmation of the O-antigen markers. We also aimed at reducing the number of samples for which isolation is attempted, as the isolation step is laborious, time-consuming, and not always successful (Wang et al., 2013). The objective of this project was to evaluate the discriminatory power of these various genetic markers to predict the presence of the top seven EHEC serogroups compared to that of the strategy proposed by the ISO/CEN TS13136:2012 (ISO, 2012) and MLG5B.05 (USDA-FSIS, 2014).

#### MATERIALS AND METHODS

### *E. coli* Control Strains

E. coli control strains used for this study (**Table 1**) comprised a panel of ATCC E. coli strains (n = 42) and E. coli reference strains derived from the BfR and Anses collections (n = 13). The origin and characteristics of the E. colistrains from BfR and Anses have been previously described (Delannoy et al., 2012a, 2013a). Cultivation of bacteria and preparation of DNA was performed as previously described (Delannoy et al., 2012a, 2013a).

### Beef Samples, Enrichment, and DNA Extraction

A set of 1739 beef samples composed of ground beef and carcasses were collected from routine screening using the GeneDisc array (Pall GeneDisc, Bruz, France) at the Veterinary Departmental Laboratory of Touraine, France during a 1-year period as well as in meat production plants. For this study, sampling was biased to get greater numbers of DNA samples positive for stx alone (n = 306), positive for stx and eae (n = 180), positive for eae alone (n = 200), and negative for both stx and eae (n =

#### TABLE 1 | PCR-screening of the genetic markers in STEC isolates used as reference.

1053). This sampling scheme does not represent the prevalence of STEC and EHEC in French beef. All samples were incubated in buffered peptone water (BioMerieux, Marcy l'étolie, France) for 18–24 h at 37◦C. After enrichment, DNA was extracted from 1 ml of enriched sample using the InstaGene matrix (Bio-Rad Laboratories, Marnes-La Coquette, France) following manufacturer's instruction and DNA was stored at −20◦C until use. When samples were found positive for stx, eae, and rfbEO157, isolation of strains was attempted by local laboratories for confirmation of EHEC O157:H7. Following the recommendation of the French ministry of agriculture the appropriate sanitary measures were taken in positive cases of EHEC O157:H7. Unfortunately, because this study was performed several months after the samples were collected, the original samples were not conserved to attempt isolation from presumptive positives with the alternate methods described in this study.

#### High-Throughput Real-Time PCR

A LightCycler R 1536 (Roche, Meylan, France) was used to perform high throughput real-time PCR amplifications as described previously (Delannoy et al., 2012a), except that 1µl of sample DNA was used in each reaction for a final reaction volume of 2µl. The thermal profile was modified as follows: 95◦C for 1 min, followed by 45 cycles of 95◦C for 0 s, and 58◦C for 30 s. All ramp rates were set to 2◦C/s. E. coli gene targets used for the real-time PCR amplification and all primers and probes that have previously been described are reported in **Table 2**. An inhibition control (IC) was performed on each sample to check for potential inhibition of the PCR reaction due to intrinsic characteristics of the sample. The IC is a recombinant pBluescript IISK+ plasmid containing the dsb gene from Ehrlichia canis (Michelet et al., 2014). The plasmid was added to each sample at a concentration of approximately 0.3 pg/µl. Primers and probe specific for the E. canis dsb gene were used to detect the IC (Michelet et al., 2014).

#### RESULTS

#### Presence of *stx1*, *stx2*, *eae*, *espK*, *espV*, *Z2098*, and *ureD* in *E. coli* Strains

The presence of stx1, stx2, eae, espK, espV, Z2098, and ureD was tested by PCR in a panel of E. coli strains obtained from culture collections (**Table 1**). All E. coli strains used in this study were positive for the stx and eae genes and therefore can be considered as typical EHEC strains. Strains were associated with the following eae variants: eae-beta (O26:H11, O26:HND, O103:H11, O5, O118:H16, O123:H11), eae-gamma (O145:H28, O145:HND, O157:H7, O55:H7), eae-epsilon (O121:H19, O45:H2, O103:H2, O103:H11), and eae-theta (O111:H8, O111:HND, O103:H25). The eae subtype of strain CB10528 (O172:H25) could not be determined. Distribution of the genetic markers espK, espV, Z2098, and ureD in the 55 EHEC strains is shown in **Table 1**. Overall, the genetic markers investigated were detected in most of the EHEC strains examined. With the exception of the new O26:H11 stx2-positive strain (CB14699) and one strain of serotype O157:H7 (CDC-C984), all of the strains were positive for espK. The espV gene was not detected in two E. coli O26:H11 strains (ATCC2196 and CB14699), in O45:H2, O118:H16, O5, or in O123:H11 isolates. The Z2098 gene marker tested negative in only a few strains: the new O26:H11 stx2 positive clone (strain CB14699) and in the O55:H7 strains. The ureD gene was absent in the new O26:H11 stx2 positive clone (strain CB14699) and in the O55:H7 strains. It was also absent from a few O103:H2 isolates (strains PMK5, CB12062, CB12092). In summary, all of the strains were positive for one or more of the genes espK, espV, Z2098, and ureD, with the exception of the new O26:H11 stx2 positive clone (CB14699).

#### Screening Beef Enrichments for *stx1*, *stx2*, *eae*, *espK*, *espV*, *Z2098*, and *ureD*

A set of 1739 beef samples was screened for the presence of stx1, stx2, eae, espK, espV, Z2098, and ureD. The stx genes were detected in 27.95% of the samples (486/1739). The eae gene was detected in 21.85% of the samples (380/1739). The two genes were simultaneously present in 10.35% of the samples (180/1739). The genes espK and/or Z2098 were detected in 7.42% of the samples (129/1739) (**Figure 1A**), while espK and/or espV were found in 130 samples (7.48%) (**Figure 1B**) and espK and/or ureD was recorded in 145 samples (8.34%) (**Figure 1C**).

By using the stx and eae genes for screening beef samples, following the ISO/CEN TS13136 and MLG5B.05 methods, 180 samples (10.35%) were recorded as stx/eae positive and should, therefore, be subjected to a second screening step for EHECserogroups. Pre-screening of stx/eae positive samples for espK with either Z2098 (alternate method A), or ureD (alternate method C), provided a 60% reduction of the number of samples that should be submitted to a second screening targeting the Ogroup gene markers (n = 71). Using the alternate method B (stx/eae/espK/espV), 80 of the 1739 samples (4.6%) needed to be submitted to a further screening for serogroup determination,

which represents a reduction by 55% of the number of samples subjected to a second screening.

**Figure 2** shows the comparison of the alternative methods A–C with the 180 beef samples that tested positive for both the stx and eae genes. A total of 90 stx and eae positive beef samples tested negative for espK, espV, Z2098, and ureD (sector 8, **Figure 2**). However, the inclusion of the CRISPRO26:H11 PCR revealed 12 espK, espV, Z2098, and ureD negative samples that were positive for both the new CRISPRO26:H11 clone and eaebeta, the variant of the intimin gene carried by EHEC O26:H11 (see below).

### Screening Beef Samples for *stx1*, *stx2*, *eae*, and CRISPRO26:H11

The 180 beef samples that are positive for stx and eae were also tested by the CRISPRO26:H11 PCR test (SP\_O26-E, as described in Delannoy et al., 2015a), that detects the new EHEC O26:H11 French clone (stx2 and eae positive, espK, espV, Z2098, ureD negative). Among the 180 samples tested, 20 stx/eae positive samples were also found to be positive for SP\_O26-E and should therefore be submitted to a further screening for serogroup determination. Interestingly, most of them (16/20) were found positive for stx2, 2 samples were positive for stx1 only and 2 had an unknown stx subtype. Twelve of these 20 were also negative for espK, espV, Z2098, and ureD (**Figure 2**, sector 8). Finally, when combining the use of CRISPRO26:H11 (SP\_O26-E PCR test) with alternate method A, 85 samples should be submitted to a second screening targeting the O-group gene markers. When using alternate methods B and C with the CRISPRO26:H11 PCR test, 92 and 86 samples should be submitted to the second step, respectively.

#### Screening Beef Samples for *stx1*, *stx2*, *eae*, and the Top Seven EHEC Serogroups

As recommended in the ISO/TS 13136 (EU) and MLG5B.05 (US) reference methods, the 180 stx and eae positive samples were tested for the top seven EHEC serogroups. Among these, 115 samples were positive for at least one of the top seven US regulated EHEC serogroups and 99 were positive for at least one of the top five EHEC serogroups screened by the European ISO/TS 13136 method (data not shown). The most frequently found serogroup was O103 (n = 71), followed by O26 (n = 45), O121 (n = 38), O157 (n = 18), O45 (n = 14), O145 (n = 6), and O111 (n = 1). Interestingly, 30 samples were positive for 2 serogroups, 11 were positive for 3 serogroups, and 7 for more than 4 serogroups. In final, 41.74% (48/115) of the beef samples tested positive for more than one O-group marker.

#### Screening Beef Samples for *stx1*, *stx2*, *eae*, and the *eae* Subtypes

The 180 stx and eae positive beef samples were further tested for the eae subtypes gamma, beta, epsilon and theta, which are associated with one or more of the top seven EHEC serogroups. Among these 180 stx and eae positive samples, 135 tested positive for at least one of the four eae-subtypes: gamma, beta, epsilon and theta (data not shown). The most frequently detected eaesubtypes were eae-beta (n =94) and eae-theta (n = 65), followed by eae-epsilon (n = 15), and eae-gamma (n = 5). Trying to correlate the eae subtype with the serogroup, we identified 51 beef samples for which at least one serogroup was associated with the corresponding related eae-subtype. Among these 51 samples, 6 were positive with multiple serogroups.

### Comparison of Alternative Methods A–C for Screening Beef Samples

We identified 62 samples that were recorded positive with the three alternative methods A–C (sector 3, **Figure 2**) and therefore must be submitted to a second screening targeting the O-group gene markers. These samples are strongly suspected to contain typical EHEC and five of these are also suspected to contain the new CRISPRO26:H11 clone. In addition we found 28 samples (sectors 1, 2, 4, 5, 6, 7 from **Figure 2**) that were positive by one or

two alternative methods only. PCR results obtained for these 28 samples for eae subtypes and top seven O-groups were as follows: only one sample among the 5 samples of sector 1 (**Figure 2**) was positive for the association of O26 and eae-beta, but it tested negative for the different CRISPRO26:H11 assays targeting EHEC O26:H11 [SP\_O26-C, SP\_O26-D, and SP\_O26-E, as described in Delannoy et al., 2012a, 2015a (data not shown)]. The only sample from sector 4 (**Figure 2**) and each of the four samples from sectors 6 and 7 (**Figure 2**) were found negative by the association of the top seven serogroups and the corresponding eae-subtypes. From sector 2 (**Figure 2**), only one out of three samples was found positive for the new CRISPRO26:H11 clone (this sample tested positive by PCR for O26, eae-beta, SP\_O26-E; and was also stx2 positive which is consistent with the new clone). The two other samples were not suspected as "presumptive positive" based on the eae-subtypes and top seven EHEC serotypes determination. In sector 5 (**Figure 2**), out of eleven samples three were found "presumptive positive" for EHEC O26 (among them two were suspected to be positive for the new O26:H11 clone). Finally, "presumptive positive" samples were recorded in sectors 2, 3, and 5 which lead to consider the alternate method B as the best one among the other alternate methods for screening EHEC strains. In order to complete the screening of EHEC and not to exclude the new virulent O26 clone, the alternate method B should include the screening of the new CRISPRO26:H11 assay.

## DISCUSSION

A STEC seropathotype classification has been based upon the serotype association with human epidemics, bloody diarrhea, and HUS, and has been developed as a tool to assess the clinical and public health risks associated with non-O157 EHEC and STEC strains (Karmali et al., 2003). This approach has been of considerable value in defining pathogenic STEC serotypes of importance in cases of human infection (EFSA, 2007; Coombes et al., 2011); however it does not resolve the underlying problem with strains that have not yet been fully serotyped. Furthermore, classification based solely on the presence of seropathotype is inadequate with illnesses linked to STEC serotypes other than O157:H7 that are on the rise worldwide, indicating that some of these organisms may be emerging pathogens. In 2013, the Panel on Biological Hazards (BIOHAZ) of the European Food Safety Authority (EFSA) published a Scientific Opinion on "VTECseropathotype and scientific criteria regarding pathogenicity assessment" (EFSA, 2013). This document has focused attention on the applicability of the Karmali seropathotype concept. The document does not provide a scientific definition of a pathogenic STEC but states that the seropathotype classification of Karmali et al. (2003) does not define pathogenic STEC nor does it provide an exhaustive list of pathogenic serotypes. It is not possible to fully define human pathogenic STEC or identify factors for STEC that absolutely predict the potential to cause human disease, but

#### TABLE 2 | Primer and probe sequences used in this study.

(Continued)

#### TABLE 2 | Continued

aF, forward primer; R, reverse primer; P, probe.

bAll probes were labeled with 6-HEX or 6-FAM and BHQ1 (Black Hole Quencher).

cOligonucleotide described by Perelle et al. (2004).

dOligonucleotide described by Nielsen and Andersen (2003).

eOligonucleotide described by Delannoy et al. (2013a).

fOligonucleotide described by Delannoy et al. (2013b).

gOligonucleotide described by Delannoy et al. (2012a).

hOligonucleotide described by Delannoy et al. (2015a).

iOligonucleotide described by Perelle et al. (2005).

jOligonucleotide described by Bugarel et al. (2010).

kOligonucleotide described by Fratamico et al. (2009).

strains positive for Shiga-toxin (in particular the stx2 genes) and eae (intimin production) genes are associated with a higher risk of more severe illness than other virulence factor combinations (EFSA, 2013). Severe disease, and particularly HUS, is linked to certain serotypes and strains and this link must be the result of particular genetic factors or combinations of factors that have to be determined. A new molecular classification scheme has been proposed by the EFSA Panel on Biological Hazards (BIOHAZ) that relies more on virulence factors than seropathotypes. It is proposed that STEC serogroups O157, O26, O103, O145, O111, and O104 in combination with stx and eae or stx and both aaiC (secreted protein of EAEC) and aggR (plasmid-encoded regulator) genes should be considered as presenting a potentially higher risk for bloody diarrhea and HUS, such strains are categorized in group I (EFSA, 2013). For any other serogroups in combination with the same genes, the potential risk is regarded as high for diarrhea, but currently unknown for HUS, such strains are categorized in group II. The inclusion of aaiC and aggR genes in the proposed molecular approach is due to the O104:H4 outbreak, which was caused by a highly virulent strain (Frank et al., 2011). This appears to be an exceptional event (Prager et al., 2014) and future surveillance will provide data that may be used to review the inclusion of these virulence factors but a recent study showed that French cattle are not a reservoir of the highly virulent enteroaggregative Shiga toxin-producing E. coli of serotype O104:H4 (Auvray et al., 2012).

Following the EFSA opinion, several laboratories have attempted to develop detection and identification methods for strains of groups I and II, and although substantial progress has been made, a practical method of pathogenic STEC detection has yet to be validated. Molecular methods for screening EHEC O157 and non-O157 in beef products rely currently on the molecular detection of stx, eae, and the top five or top seven EHEC serogroups in mixed bacterial enrichments as described in the ISO/TS 13136 (EU) and MLG5B.05 (US) reference methods (ISO, 2012; USDA-FSIS, 2014), followed by attempted isolation of the correct strain. These approaches bear the disadvantage that Delannoy et al. Screening EHEC in Beef Samples