Huang H, Sun Y, Yuan L, Pan Y, Gao Y, Ma C and Hu G (2016) Regulation of the Two-Component Regulator CpxR on Aminoglycosides and β-lactams Resistance in Salmonella enterica serovar Typhimurium. Front. Microbiol. 7:604. doi: 10.3389/fmicb.2016.00604 The two-component signal transduction system CpxAR is especially widespread in Gram-negative bacteria. It has been reported that CpxAR contributes to the multidrug resistance (MDR) in Escherichia coli. CpxR is a response regulator in the two-component CpxAR system. The aim of this study was to explore the role of cpxR in the MDR of S. enterica serovar Typhimurium. The minimal inhibitory concentrations (MICs) of various antibiotics commonly used in veterinary medicine for strains JS (a multidrug-susceptible standard strain of S. enterica serovar Typhimurium), JS△cpxR, JS△cpxR/pcpxR, JS△cpxR/pcpxR∗ , JS△cpxR△acrB, JS△cpxR△acrB/pcpxR, JS△cpxR△acrB/pcpxR∗ , 9 S. enterica serovar Typhimurium isolates (SH1–9), and SH1–9△cpxR were determined by the 2-fold broth microdilution method. The relative mRNA expression levels of ompF, ompC, ompW, ompD, tolC, acrB, acrD, acrF, mdtA, marA, and soxS in strains JS, JS△cpxR, and JS△cpxR/pcpxR were detected by real-time PCR. The results showed 2- to 4-fold decreases in the MICs of amikacin (AMK), gentamycin (GEN), apramycin (APR), neomycin (NEO), ceftriaxone (CRO), ceftiofur (CEF), and cefquinome (CEQ) for strain JS△cpxR, as compared to those for the parental strain JS. Likewise, SH1–9△cpxR were found to have 2- to 8-fold reduction in resistance to the above antibiotics, except for NEO, as compared to their parental strains SH1–9. Furthermore, 2- to 4-fold further decreases in the MICs of AMK, GEN, APR, and CEF for strain JS△cpxR△acrB were observed, as compared to those for strain JS△acrB. In addition, CpxR overproduction in strain JS△cpxR led to significant decreases in the mRNA expression levels of ompF, ompC, ompW, ompD, tolC, acrB, marA, and soxS, and significant increases in those of stm3031 and stm1530. Notably, after all strains were induced simultaneously by GEN to the 15th passage at subinhibitory concentrations, strain JS△cpxR/pcpxR showed significant increases in mRNA expression levels of the efflux pump acrD and mdtA genes, as compared to strain JS△cpxR. Our results indicate that the two-component regulator CpxR contributes to resistance of S. enterica serovar Typhimurium to aminoglycosides and β-lactams by influencing the expression level of the MDR-related genes.

Keywords: *S. enterica* serovar Typhimurium, CpxR, aminoglycosides, β-lactams, resistance, AcrD

## INTRODUCTION

Salmonella enterica serovar Typhimurium is a food-borne pathogen that causes gastroenteritis in humans (Scherer and Miller, 2001) and fowl typhoid in poultry (Barrow et al., 2004). The prevalence of multidrug-resistant (MDR) S. enterica species in many parts of the world has become a significant public health concern. Drug resistance in many cases is attributable to synergy between reduced drug intake (mainly due to low outer membrane permeability) (Pagès et al., 2008; Li and Nikaido, 2009) and active drug export (via efflux pumps) (Zgurskaya and Nikaido, 2000; Pagès et al., 2010). Resistance nodulation-cell division (RND) family efflux systems (including AcrAB, AcrAD, AcrEF, MdtEF, and MdtABC) are especially effective in generating resistance in Gram negative bacteria (Nikaido, 1996) and often have a wide substrate specificity (Nikaido and Pagès, 2012). In Escherichia coli, all five RND-family drug exporters confer resistance to βlactam antibiotics (Nishino et al., 2003), and acrD is also known to participate in the efflux of aminoglycosides (Rosenberg et al., 2000; Nishino and Yamaguchi, 2001a; Aires and Nikaido, 2005; Nishino et al., 2007). Some outer membrane proteins, especially OmpF, OmpC, and OmpW, have been shown to contribute to antibiotic resistance in E. coli and Salmonella typhimurium (Nikaido, 2003). In addition, OmpD, STM3031, and STM1530 are associated with ceftriaxone (CRO) resistance in S. enterica serovar Typhimurium (Hu et al., 2011), and OmpW participates in resistance to neomycin (NEO) and ampicillin (AMP) in E. coli (Wu et al., 2012).

Two-component signal transduction systems (TCSs) are key in the sensory response of bacteria (Parkinson and Kofoid, 1992). Studies have elucidated that the TCSs EvgA and BaeR contribute to MDR by modulating production of the multidrug transporter in E. coli (Nishino and Yamaguchi, 2001b; Baranova and Nikaido, 2002; Nishino and Yamaguchi, 2002). The Cpx envelope stress response is controlled by a TCS consisting of the membrane localized sensor kinase CpxA and the regulator CpxR. CpxR mediates the output response as a transcriptional regulator through phosphorylation of its receiver domain with an aspartate (D51) moiety (Stephenson and Hoch, 2002; MacRitchie et al., 2008). Phosphorylated CpxR (CpxR-P), which functions as a transcription factor, activates and, in a small number of cases, represses transcription of target genes by binding to the promoter of target genes at the consensus sequence 5′ -GTAAAN5GTAAA-3 ′ (De Wulf et al., 2002; Price and Raivio, 2009). In addition, the response regulator CpxR is also activated by some signals without the involvement of CpxA. For example, some cytoplasmic or growth signals, as well as excess carbon (glucose or pyruvate) in growth medium both activate CpxR independently of CpxA (Cuny et al., 2007; Wolfe et al., 2008).

In recent years, the CpxAR two-component system conferring resistance to antibacterial agent has received special attention. In E. coli, CpxR overproduction was found to confer resistance to β-lactams in an acrB-free background (Hirakawa et al., 2003a). CpxR-P also confers resistance to fosfomycin by directly repressing the expression of two genes, glpT and uhpT, in the enterohemorrhagic E. coli (EHEC) strain O157:H7 (Kurabayashi et al., 2014). Moreover, the CpxAR pathway contributes to E. coli resistance to antimicrobial peptides, such as ApoEdpl-W, polymyxin B, and melittin (Audrain et al., 2013) and protamine (Weatherspoon-Griffin et al., 2014). In Klebsiella pneumoniae, CpxR was able to directly bind to the promoter regions of ompCKPand kpnEF, which contribute to the K. Pneumoniae MDR phenotype (Srinivasan et al., 2012; Srinivasan and Rajamohan, 2013). In S. enterica serovar Typhimurium, studies about the effect of cpxR on the resistance are still very limited, only few reports showed CpxAR confers resistance to CRO (Hu et al., 2011) and the antimicrobial peptides protamine, magainin, and melittin (Weatherspoon-Griffin et al., 2011). However, whether CpxAR plays a role in resistance of S. enterica serovar Typhimurium especially clinical isolates to aminoglycosides and β-lactams and the molecular mechanisms underlying resistance to aminoglycosides and β-lactams remain unknown. In this study, we systematically investigated the role of cpxR in aminoglycoside and β-lactam resistance in both susceptible strains and clinical isolates of S. enterica serovar Typhimurium, and also explored the molecular mechanisms of CpxAR that confer resistance to aminoglycosides and β-lactams.

### MATERIALS AND METHODS

### Bacterial Strains, Plasmids, and Bacteriophage

The bacterial strains, plasmids, and bacteriophage used in this study are listed in **Table 1**. Salmonella enterica serovar Typhimurium strain CVCC541, a clinical susceptible strain isolated from chicken in Changchun City, China, was supplied by the China Institute of Veterinary Drug Control (Beijing, China) and designated as JS in this report. Strains JS△cpxR and JS△acrB were generated from JS using the one-step inactivation of chromosomal genes method. Strain JS△acrB△cpxR was constructed by the phage P22-mediated transduction method using strain JS△cpxR as the donor and JS△acrB as the recipient. In this study, nine S. enterica serovar Typhimurium isolates were isolated from chickens collected from nine different regions of Henan province in China and named SH1–9.

### Construction of the Expression Plasmids pBAD-CpxR and pBAD-CpxR∗

The complete open reading frame of cpxR was amplified by PCR with primers XholI-cpxR-F/HindIII-cpxR-R (**Table 2**) from the genomic DNA of strain JS. The mutation sequence cpxR∗ , which encodes a CpxR variant with an alanine residue at position 51 in place of aspartate, was engineered by overlapping PCR (Urban et al., 1997; Huang et al., 1999). The mutation site was generated through the design of primers Fm and Rm (**Table 2**). Three PCR reactions were performed to obtain the mutation sequence cpxR∗ . Primers XholI-cpxR-F/Rm were used for amplification of the anterior segment of cpxR, primers Fm/HindIII-cpxR-R were used for amplification of the second part of cpxR, and the primers XholI-cpxR-F/HindIII-cpxR-R were used for splicing by overlap extension PCR. Finally, the expression plasmids pBAD-CpxR and pBAD-CpxR∗ were generated by inserting the target fragment to the multiple cloning site of vector pBAD. The expression level of

#### TABLE 1 | Bacterial strains, plasmids, and phage used in this study.

target proteins were determined according to the concentration of the inducer L-arabinose (Guzman et al., 1995).

### Construction of *cpxR*-Deficient Mutants of *S. enterica* Serovar Typhimurium Isolates

The generation of strain JS△cpxR::kan was described in our previous study (Huang et al., 2015). The deletions were then transferred to nine S. enterica serovar Typhimurium isolates (SH1–9) by P22HT105/int transductions as previously described (Davis et al., 1980; Mann and Slauch, 1997). Nine cpxR-deficient mutants were designated as SH1–9△cpxR in this study.

#### Antibiotic Susceptibility Testing

The minimal inhibitory concentrations (MICs) of selected antibiotics for all strains were determined by the 2-fold broth microdilution method according to the CLSI guidelines (Clinical and Laboratory Standards Institute, 2008, 2012). The antibiotics used for susceptibility determination were gentamycin (GEN), amikacin (AMK), apramycin (APR), NEO, CRO, ceftiofur (CEF), CEQ. E. coli ATCC 25922 was used for quality control in all susceptibility tests. All tests were performed independently at least three times.

#### GEN Induction Testing

A single colony of each tested strain (JS, JS△cpxR, and JS△cpxR/pcpxR) was cultured in Luria-Bertani (LB) medium containing a 50% MIC of GEN at 37◦C for 18 h. After growth overnight at 37◦C, the cultures was diluted 1:100 in LB medium and cultured at 37◦C for 18 h, and simultaneously the inducer GEN was added at subinhibitory concentrations. GEN induction testing of the strains was performed for 15 generations in this way.

#### Expression Levels of MDR-Related Genes

Total RNA was isolated from bacterial cultures using the MiniBEST Universal RNA Extraction Kit (TaKaRa Bio, Inc. Shiga, Japan) according to the manufacturer's instructions. OD260/OD280 values of total RNA were detected using a trace nucleic acid protein analyzer spectrophotometer (NanoDrop; Thermo Fisher Scientific, Waltham, MA, USA). Bulk cDNA samples were synthesized from total RNA using the PrimeScriptTMRT reagent Kit with gDNA Eraser (TaKaRa Bio, Inc.). The synthesized cDNA was confirmed by PCR and stored at –20◦C until used. Real-time PCR was performed using the LightCycler R 480 System (Roche Diagnostics, Indianapolis, IN, USA) with specific primer pairs (**Table 2**), cDNA template, and TaKaRa SYBR Premix Ex Taq II (TaKaRa Bio, Inc.). The 16S rRNA gene was chosen as a housekeeping gene. To precisely test the relative expression level of the genes of interest, standard curves of the amplification of all detected genes were individually established. CT values tested came within the linearity range for PCR amplification. Each sample was independently run at least twice. The 2−△(△CT) method was used to calculate altered folds of the gene tested in the mutants, as compared to that in JS. Three independent experiments were performed under the same conditions.

#### Statistical Analysis

Statistical analysis was performed using SPSS version 17.0 software (IBM-SPSS, Inc., Chicago, IL, USA). Data were compared using the Student's t-test. A probability (p) value of > 0.05 was considered statistically significant.

#### RESULTS

#### Deletion of *cpxR* Increases Susceptibility of JS to aminoglycosides and β-lactams

To examine whether the response regulator CpxR contributes to the drug resistance of S. enterica serovar Typhimurium, a cpxR deletion mutant, JS△cpxR, was generated from strain JS, and the complementary strain JS△cpxR/pcpxR was prepared through the introduction of the expression plasmid pBAD-CpxR into

#### TABLE 2 | Sequences of primers used in this study.

The underlined bases are restriction sites.

JS△cpxR. The MICs of a number of antibiotics for strain JS and JS△cpxR were then determined. As shown in **Table 3**, strain JS△cpxR showed 2–4-fold decreases in the MICs of GEN, AMK, APR, NEO, CRO, CEF, and CEQ, as compared to the parental strain JS. The MICs of the above antibiotics increased by 4-fold for the complementary strain JS△cpxR/pcpxR, as compared to those for JS△cpxR. These results clearly suggest that cpxR plays an important role in conferring resistance of S. enterica serovar Typhimurium to aminoglycosides and β-lactams. In addition, JS△cpxR/pcpxR∗ exhibited the same susceptibility as JS△cpxR to the tested antibiotics except for CEQ, which demonstrates that the susceptibility changes of S. enterica serovar Typhimurium to the tested antibiotics was mediated by CpxR-P.

### Effects of Deletion of *acrB* on *cpxR*-Mediated Multidrug Resistance

In susceptible S. enterica serovar Typhimurium, the AcrAB efflux pump is constitutively expressed and plays a predominant role in intrinsic and acquired resistance (Mazzariol et al., 2000; Nishino et al., 2006). It has wild substrate spectrum and can capture substrates from the periplasm or the outer leaflet of the cytoplasmic membrane (Yu et al., 2003). Therefore, AcrAB may mask partial function of some efflux pumps located in the cytoplasmic membrane (Hirakawa et al., 2003a,b; Eaves et al., 2004; Nishino et al., 2007). To clarify the role of CpxR in resistance conferred by other efflux pumps, an acrB deletion mutant (JS△acrB) and a double deletion mutant (JS△acrB△cpxR) were generated from strain JS. The cpxR complementary strain JS△acrB△cpxR/pcpxR was prepared as described above. The MICs of various antibiotics for strains JS△acrB, JS△acrB△cpxR, and JS△acrB△cpxR/pcpxR were then determined. As shown in **Table 3**, strain JS△acrB△cpxR showed 2–4-fold decreases in the MICs of GEN, AMK, APR, NEO, and CEF, as compared to strain JS△acrB, while the complementary strain JS△acrB△cpxR/pcpxR exhibited 2–8-fold increases in the MICs of GEN, AMK, APR, NEO, CRO, CEF, and CEQ, as compared to strain JS△acrB△cpxR.

#### TABLE 3 | Susceptibility of *S. enterica* serovar Typhimurium to several antibiotics.

AMK, Amikacin; GEN, Gentamycin; APR, Apramycin; NEO, Neomycin; CRO, Ceftriaxone; CEF, Ceftiofur; CEQ, Cefquinome; ENR, Enrofloxacin; CIP, Ciprofloxacin.

NHigh NEO resistance is present in strains because of the replacement of cpxR gene by kanamycin-resistant gene (△cpxR::kan).

#### TABLE 4 | Susceptibilities of *S. enterica* serovar Typhimurium isolates to antibiotics after *cpxR* were deleted.

AMK, Amikacin; GEN, Gentamycin; APR, Apramycin; NEO, Neomycin; CRO, Ceftriaxone; CEF, Ceftiofur; CEQ, Cefquinome.

NHigh NEO resistance is present in strains because of the replacement of cpxR gene by the kanamycin-resistant gene (△cpxR::kan).

These results revealed that CpxR can modulate resistance of S. enterica serovar Typhimurium to aminoglycosides and β-lactams in both acrB and △acrB backgrounds.

### Role of *cpxR* in drug Resistance of *S. enterica* Serovar Typhimurium Isolates

To determinate the role of cpxR in regulating drug resistance of S. enterica serovar Typhimurium isolates, nine cpxR-deficient mutants (SH1–9△cpxR) derived from nine S. enterica serovar Typhimurium isolates (SH1–9) were constructed. The MICs for SH1–9 and SH1–9△cpxR to the above antibiotics were then determined. As shown in **Table 4**, among the nine cpxR deletion strains, all showed 2–4-fold decreases in the MICs of GEN, AMK, APR, and CEF, six revealed 2–4-fold decreases in the MIC of CRO, and six revealed 2–4-fold decreases in the MIC of CEQ, compared with their parental strains. These results indicate that cpxR also plays an important role in resistance of S. enterica serovar Typhimurium isolates to aminoglycosides and β-lactams.

#### Effects of *cpxR* on the expression Levels of a Series of MDR-Related Genes

In E. coli, it has been confirmed that cpxR can modulate the expression of the outer membrane proteins OmpF and OmpC (Batchelor et al., 2005), and the transporter MdtABC (Hirakawa et al., 2005). In S. enterica serovar Typhimurium, the expression of OmpD, STM3031, and STM1530 plays important roles in cpxR-mediated CRO resistance (Hu et al., 2011). In order to determine whether the drug resistance mediated by cpxR is due to altered expression levels of MDR-related genes, we detected the relative mRNA expression of a series of MDR-related genes. As shown in **Figure 1**, JS△cpxR showed no significant differences in the mRNA expression levels of all tested genes, as compared to strain JS, while the mRNA expression levels of ompF, ompC, ompW, ompD, acrB, tolC, marA, and soxS genes in strain JS△cpxR/pcpxR were significantly decreased (p < 0.01 or p < 0.05) relative to strain JS△cpxR (**Figures 1A,C,D**) and the mRNA levels of stm3031 and stm1530 in strain JS△cpxR/pcpxR were significantly increased (p < 0.01 or p < 0.05) relative to strain JS△cpxR (**Figure 1B**). There were no significant differences in mRNA expression levels of acrD and mdtA among strains JS, JS△cpxR, and JS△cpxR/pcpxR (**Figure 1C**). The expression levels of AcrF in these three strains were all very low and almost undetectable (data not shown). However, after all strains were induced by GEN at subinhibitory concentrations to the 15th passage simultaneously, strain JS△cpxR/pcpxR showed significant (p < 0.01) increases in the mRNA expression levels of mdtA and acrD, as compared to JS△cpxR (**Figure 1E**). These results suggest that the overexpression of cpxR can downregulate the expression levels of OmpF, OmpC, OmpW, OmpD, AcrB, TolC, MarA, and SoxS and upregulate those of STM3031 and STM1530 in susceptible S. enterica serovar Typhimurium strains,

15th passage at subinhibitory concentrations. \*p < 0.05, \*\*p < 0.01.

and it also upregulated the expression levels of the efflux pumps AcrD and MdtA under the pressure of GEN.

#### DISCUSSION

In this study, we analyzed the effect of CpxR on the drug resistance of a susceptible strain and nine clinical isolates of S. enterica serovar Typhimurium and found 2- to 4-fold decreases in resistance to aminoglycosides and β-lactams by deletion of cpxR (**Tables 3, 4**). These results are similar to those of previous studies reporting that the overexpression of cpxR in E. coli caused 2-fold increases in resistance to β-lactams (Hirakawa et al., 2003a), but different from the findings that the cpxA-cpxR deleted mutant R200(△cpxAR) showed more remarkable decreases (>2048-fold) than strain JS△cpxR in the MIC of CRO, as compared to their parental strain (Hu et al., 2011). Obviously, R200, generated by a multistep resistance selection method, is a CRO-resistant strain. Therefore, we concluded that the influence of cpxR on the drug resistance of resistant strains is greater than that of susceptible strains.

It is known that OmpF and OmpC are the most abundant outer membrane proteins of S. enterica serovar Typhimurium. Many antimicrobial agents have been found to alter the expression of these proteins. Moreover, it has been confirmed that decreased level of OmpD, and increased levels of STM3031 and STM1530 are associated with S. enterica serovar Typhimurium CRO resistance (Hu et al., 2009, 2011). In this study, we found significant reductions in the levels of OmpF, OmpC, OmpD, and OmpW, and significant increases in levels of STM3031 and STM1530 when cpxR was reverted to strain JS△cpxR. Thus, the altered levels of the above-mentioned outer membrane proteins influenced by CpxR may be closely associated with the CpxRmediated resistance of S. enterica serovar Typhimurium to βlactams.

In Gram-negative bacteria, transporters belonging to the RND family are particularly effective in generating resistance, and MDR often results from the overexpression of multidrug efflux transporters (Grkovic et al., 2002). In this study, before the strains were induced with GEN, CpxR overexpression led to significant reductions in levels of AcrB, TolC, MarA, and SoxS. MarA and SoxS are global regulatory factors (Wall et al., 2009). Once overexpressed, MarA further activates AcrAB/TolC efflux and alters the expression of some membrane proteins (Sulavik et al., 1997). To our knowledge, the influence of CpxR on the mRNA levels of marA and soxS genes has not been demonstrated. Our results can give two suggestions. One is that the decrease in AcrAB–TolC, mediated by the complementation of cpxR, is associated with the decrease of the regulatory factors MarA and SoxS. The other is the expression levels of AcrB and TolC do not play a decisive role in CpxR-mediated resistance of S. enterica serovar Typhimurium to aminoglycoside and βlactams. Our finding that CpxR can influence the susceptibility of S. enterica serovar Typhimurium to aminoglycosides and βlactams in both acrB and △acrB backgrounds also supports the second suggestion. Nevertheless, more studies should be carried out to elucidate the reciprocal relationship among CpxR, outer membrane protein genes, efflux genes, and regulative genes.

In this study, the up-regulatory effect of CpxR on the expression levels of AcrD and MdtA were observed in the GEN-induced strains. Aminoglycoside uptake in Gram-negative bacteria includes three consecutive steps. The first step is an electrostatic interaction between aminoglycosides and the bacteria cell envelope through displacement of Mg2+ and Ca2+ ions that link adjacent lipopolysaccharide molecules, which damages the bacteria outer membrane and enhances its permeability. The second step is energy-dependent phase I of uptake, which leads to a small quantity of antibiotic molecules transversing the cytoplasmic membrane. The third step is energy-dependent phase II of uptake, in which misfolded proteins are produced due to the binding of incoming antibiotics to the ribosome. Some of these proteins are incorporated in the cytoplasmic membrane leading to the loss of membrane integrity. Therefore, additional quantities of aminoglycosides are transported across the damaged cytoplasmic membrane (Taber et al., 1987). Thus, CpxR may be activated by GEN in the inducing experiment in vitro. It has been reported that the promoter regions of acrD and mdtABC harbor binding sites for the response regulator BaeR (Nishino et al., 2007). CpxR also can bind to the cpxR box located in the promoter region of target genes. In common, the consensus cpxR box includes a tandem repeated GTAAA sequence that is separated by a 5-bp space (Batchelor et al., 2005). The DNA binding feature of CpxR encouraged us to analyze the promoter region of acrD and mdtA in the chromosome of S. enterica serovar Typhimurium LT2 (accession number: AE006468) for the presence of putative CpxR binding sites. Interestingly, our analysis revealed the presence of two similar sequences located 173 bp (site 1: GTAAA-gaacg-GCAAA) and 106 bp (site2: GTAAA-agcgc-ATGAT) upstream of the acrD translational start site, respectively. Among them, site 1 was also found 328 bp upstream of the kpnEF translational start site. Furthermore, it has been confirmed that purified CpxR from a strain of K. Pneumoniae can directly bind to site 1 (Srinivasan and Rajamohan, 2013). Because CpxR of K. Pneumoniae exhibits the highest level of homology to CpxR of S. enterica serovar Typhimurium (96%), CpxR of S. enterica serovar Typhimurium may directly bind to the promoter region of acrD. As we know, AcrD participates in the efflux of aminoglycosides, thus our analysis indicates that CpxR contributes to AcrD-mediated resistance of S. enterica serovar Typhimurium to GEN, which belongs to aminoglycosides.

Moreover, in this study, there were no significant differences in the mRNA expression levels of all tested genes in strain JS△cpxR, as compared to strain JS. It has been demonstrated that histidine kinase (HK) also possess response regulator phosphatase activity, which may ensure that the response regulator remains inactive in the absence of activating signals (Raivio and Silhavy, 1997). Therefore, we think that the response regulator CpxR is always in a pre-stimulated resting state and does not modulate mRNA levels at physiological levels. Biochemical data suggest that CpxR can become phosphorylated by the low-molecular-weight phospho-donor acetyl phosphate and, further, that this form (CpxR-P) has a greater affinity for binding to the promoters of target genes (Pogliano et al., 1997). Similarly, it has been demonstrated that, in the absence of CpxA, CpxR can transcriptionally activate downstream target genes, suggesting that CpxR-P is responsible for transcriptional activation of target genes (Danese et al., 1995; De Wulf and Lin, 2000; Batchelor et al., 2005). In this scenario, we conclude that CpxR overproduction in JS△cpxR encourages the emergence of CpxR-P, which acts as a modulator of gene expression.

In summary, we have reported the first systematical and extensive study about the role of CpxR in aminoglycoside and βlactams resistance in both susceptible strains and clinical isolates of S. enterica serovar Typhimurium. Our results not only clearly confirmed that CpxR contributes to resistance of S. enterica serovar Typhimurium to aminoglycoside and β-lactams but also indicated that the effect of CpxR on the expression levels of MDRrelated genes is closely associated with CpxR-mediated resistance of S. enterica serovar Typhimurium to aminoglycoside and βlactams. This is the first time that the effect of CpxR on the expression levels of marA and soxS genes have been investigated in S. enterica serovar Typhimurium. Further studies are obviously required to investigate the reciprocal relationship among CpxR,

#### REFERENCES

MDR-related outer membrane protein genes, efflux pump genes and regulative genes including marA and soxS.

#### AUTHOR CONTRIBUTIONS

HH, YS, and GH conceived of the study, and participated in its design and coordination. YG, CM isolated the S. enterica Serovar Typhimurium isolates. HH carried out the antibiotics susceptibility testing and molecular biology studies, including gene deletion, construction of expression vector and RT-PCR. HH and YP performed the statistical analysis. HH drafted the manuscript. YS, LY, and GH revised the manuscript.

### FUNDING

This study was supported by grants from the National Natural Science Foundation of China (31372481) and the Key Research Program of Higher Education of Henan Province (15A230006).

### ACKNOWLEDGMENTS

We thank Professor Chenzhang Wang for assistance with the real-time PCR.

transcription of the gene specifying the stress-inducible periplasmic protease, DegP. Genes Dev. 9, 387–398. doi: 10.1101/gad.9.4.387

in Escherichia coli. J. Bacteriol. 184, 2319–2323. doi: 10.1128/JB.184.8.2319- 2323.2002

**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 Huang, Sun, Yuan, Pan, Gao, Ma and Hu. 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.

# Resistance Mutations in *gyrA* and *parC* are Common in *Escherichia* Communities of both Fluoroquinolone-Polluted and Uncontaminated Aquatic Environments

*Anna Johnning1,2, Erik Kristiansson2, Jerker Fick3, Birgitta Weijdegård1 and D. G. Joakim Larsson1\**

*1 Department of Infectious Diseases, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden, 2 Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden, 3 Department of Chemistry, Umeå University, Umeå, Sweden*

#### *Edited by:*

*Patrícia Poeta, University of Trás-os-Montes e Alto Douro, Portugal*

#### *Reviewed by:*

*Dinesh Sriramulu, Shres Consultancy (Life Sciences), India Xian-Zhi Li, Health Canada, Canada*

> *\*Correspondence: Joakim Larsson<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Antimicrobials, Resistance and Chemotherapy, a section of the journal Frontiers in Microbiology*

*Received: 13 July 2015 Accepted: 16 November 2015 Published: 09 December 2015*

#### *Citation:*

*Johnning A, Kristiansson E, Fick J, Weijdegård B and Larsson DGJ (2015) Resistance Mutations in gyrA and parC are Common in Escherichia Communities of both Fluoroquinolone-Polluted and Uncontaminated Aquatic Environments. Front. Microbiol. 6:1355. doi: 10.3389/fmicb.2015.01355*

Alterations in the target proteins of fluoroquinolones, especially in GyrA and ParC, are known to cause resistance. Here, we investigated environmental *Escherichia* communities to explore the possible link between the abundance of mutations, and the exposure to fluoroquinolones. Sediment samples were collected from a relatively pristine lake, up and downstream from a sewage treatment plant, and from several industrially polluted sites. The quinolone resistance-determining regions of *gyrA* and *parC* were analyzed using amplicon sequencing of metagenomic DNA. Five non-synonymous substitutions were present in all samples, and all of these mutations have been previously linked to fluoroquinolone resistance in *Escherichia coli*. In GyrA, substitutions S83L and D87N were on average detected at frequencies of 86 and 32%, respectively, and 31% of all amplicons encoded both substitutions. In ParC, substitutions S80I, E84G, and E84V were detected in 42, 0.9, and 6.0% of the amplicons, respectively, and 6.5% encoded double substitutions. There was no significant correlation between the level of fluoroquinolone pollution and the relative abundance of resistance mutations, with the exception of the most polluted site, which showed the highest abundance of said substitutions in both genes. Our results demonstrate that resistance mutations can be common in environmental *Escherichia,* even in the absence of a fluoroquinolone selective pressure.

Keywords: antimicrobial agents, mechanisms of resistance, antibiotics, microbial communities, next generation sequencing

## INTRODUCTION

Fluoroquinolones are a class of synthetic broad-spectrum antibiotics that target the type II topoisomerases (DNA gyrase and topoisomerase IV) involved in the maintenance of DNA topology. DNA gyrase and topoisomerase IV are both tetrameric enzymes composed of two X and two Y subunits (X2Y2). DNA gyrase is encoded by the genes *gyrA* and *gyrB*, and topoisomerase

IV is encoded by *parC* and *parE*. The enzymes are homologues, and there is a considerable sequence similarity between *gyrA* and *parC*, and between *gyrB* and *parE*. One of the main mechanisms of fluoroquinolone resistance is amino acid substitutions in the DNA gyrase and topoisomerase IV proteins, in particular in GyrA and ParC (Ruiz, 2003; Hopkins et al., 2005). Several resistance mutations have been characterized in *Escherichia coli*, and the majority of these are located in the quinolone resistancedetermining region (QRDR) defined as codons 67–106 in *gyrA* and 56–108 in *parC* (*E. coli* numbering). Certain single mutations in *gyrA* are sufficient to generate high-level resistance to nalidixic acid, a non-fluorinated first generation quinolone. Additional mutations in *gyrA* or other type II topoisomerase genes are, however, necessary for high-level resistance to later generations of fluoroquinolones, such as ciprofloxacin (Hopkins et al., 2005). Indeed, a study of 58 fluoroquinolone-resistant clinical *E. coli* isolates from two hospitals in Houston, TX, USA, found that all isolates had amino acid substitutions in GyrA and approximately 85% had additional substitutions in ParC (Morgan-Linnell et al., 2009), confirming chromosomal mutations as the main mechanism of clinically relevant fluoroquinolone resistance. The frequency of resistant invasive *E. coli* infections in Europe in 2012 ranged from 9.7% in Iceland to 42.0% in Cyprus (ECDC, 2013). Surveillance outside of Europe is less systematic, but a hospital in India reported that as many as 73% of uropathogenic *E. coli* infections were resistant to ciprofloxacin (Mandal et al., 2012).

*Escherichia coli* primarily propagate in the intestines of warm blooded animals, but also, to a limited extent, in the environment (Ishii and Sadowsky, 2008). Because fluoroquinolones are strictly synthetic antibiotics, it would be reasonable to assume that resistance mutations are not as common in environmental *E. coli* isolates as they are among clinical isolates. Accordingly, screening of environmental bacteria from an isolated cave for antibiotic resistance showed very few isolates that were resistant to a high concentration of ciprofloxacin (MIC *>*20 mg/l), whereas resistance to other classes of antibiotics were more common (Bhullar et al., 2012). Similarly, a recent study from our group found that only *<*1–6% of bacteria isolated from lakes with no documented history of fluoroquinolone pollution, in Sweden and India, were ciprofloxacin-resistant (MIC *>*2 mg/l) (Flach et al., 2015). A characterization of the QRDR of *gyrA* from 20 environmental *E. coli* isolates showed that there was considerable variability in the amino acid sequence (Waters and Davies, 1997), and a study of 38 highly ciprofloxacin-resistant (MIC 6–128 mg/l) soil-dwelling bacterial isolates of different species showed that nine isolates (24%) contained amino acid substitutions in this region (D'Costa et al., 2006). This suggests that mutations in the QRDR can be present in environmental bacteria even in the absence of fluoroquinolones. The methods used in previous studies have, however, been low throughput, making the estimation of the abundance of mutations unreliable. Previous studies have also been dependent on the culturability of the bacteria, and often focused on phenotypically fluoroquinolone-resistant bacteria (Adachi et al., 2013; Zurfluh et al., 2014). The characteristics and relative abundance of resistance mutations in the QRDRs in environmental bacterial communities, have, thus remained unknown.

Recently, concerns have been raised about the risks of resistance development due to antibiotic contamination of the external environment (Gaze et al., 2013; Pruden et al., 2013; Wellington et al., 2013). Antibiotics, including fluoroquinolones, can enter the environment through, for example, human sewage and use in animal farming (Kümmerer, 2009). The highest concentrations of fluoroquinolones detected in the environment are, however, the result of direct discharge from manufacturing (Larsson et al., 2007; Fick et al., 2009; Kristiansson et al., 2011). It is therefore important to assess the risks of the development and spread of resistant bacteria in contaminated environments. Furthermore, because the discharge of antibiotics may be intermittent and difficult to detect, acquired resistance characteristics of environmental bacteria may, given sufficient evaluation, serve as sentinels and biomarkers for antibiotic exposure. The presence and abundance of *qnr*-genes, a group of mobile fluoroquinolone resistance genes, in microbial communities have been shown previously to correlate with fluoroquinolone contamination of stream sediments (Kristiansson et al., 2011). However, horizontally transferred genes are not ubiquitous and may, therefore, not be optimal as biomarkers. In contrast, chromosomal resistance mutations can appear *de novo* and be enriched in a population under sufficient antibiotic selective pressure. Hence, we hypothesize that resistance mutations in *gyrA* and *parC* could serve as biomarkers for fluoroquinolone exposure in different environments.

The aim of the present study was to assess the abundance of chromosomal fluoroquinolone resistance mutations in environmental *Escherichia* communities and to investigate the potential link to fluoroquinolone pollution. Using massively parallel amplicon sequencing of metagenomic DNA, we determined the full genetic resistance characteristics of the QRDR of *gyrA* and *parC* in *Escherichia* communities without any prior culturing of bacteria. The studied environments included a range of selective pressures for fluoroquinolone resistance from a highly polluted Indian stream, samples taken up and downstream from a Swedish sewage treatment plant, and from a remote small Swedish lake under minimal human impact. This allowed us to investigate a possible correlation between fluoroquinolone pollution and the abundance of resistance mutations. Our analysis showed a high abundance of fluoroquinolone resistance mutations in both *gyrA* and *parC* in all investigated environments, but, interestingly, we did not find any significant correlation with the levels of fluoroquinolones detected.

### MATERIALS AND METHODS

#### Sample Collection

Samples were taken from an Indian stream and a Swedish stream both upstream (two in India, one in Sweden) and downstream (three in India, one in Sweden) of wastewater treatment plants (WWTPs) as described previously (Kristiansson et al., 2011). The Indian WWTP is situated in Patancheru near Hyderabad, India, and at the time of sampling, it received industrial effluent from approximately 90 pharmaceutical industries. The Swedish WWTP is located in Skövde and receives municipal wastewater, but with no input from pharmaceutical industries. These seven samples have previously been analyzed for the presence of mobile antibiotic resistance genes using metagenomic sequencing (Kristiansson et al., 2011), and *qnr* genes using qPCR (Rutgersson et al., 2014). For this study, three additional sediment samples were collected from an upland Swedish small lake, Valbergs öga, situated far from habitation, roads and farmland and with no apparent inflow of water (2012-07-25, GPS coordinates 57◦51 34.2N 12◦04 58.2E). Although few places on earth could be referred to as completely pristine, very few people, if any, are likely to walk near this small lake in a given year. Thus, it represents an environment at the very low end in terms of human impact. To determine the fluoroquinolone selective pressure at the samplings sites, the concentrations of ciprofloxacin, difloxacin, enoxacin, enrofloxacin, lomefloxacin, ofloxacin, pefloxacin, and norfloxacin were measured in all samples using liquid chromatography coupled to an ion trap mass spectrometer and electro spray interface (LC-ESI-IT-MSMS) described previously by Kristiansson et al. (2011), where the original chemical analysis data of all of the stream sediment samples can be found. The Swedish lake samples were analyzed at a different time point using the same method. Results were expressed per gram organic matter, rather than per total weight as some samples contained a large proportion of inorganic material (gravel). The detection limit was 0.02 µg/g organic matter for each measured substance.

#### DNA Extraction

The total DNA was extracted from the sediment samples and amplified using uniform whole genome amplification. A PowerSoilR DNA Isolation Kit (MO BIO Laboratories, Inc., Carlsbad, CA, USA) was used for the DNA extraction with the following modification to the manufacturer's protocol: to complete homogenization and cell lysis, the power bead tubes with sediment and solution C1 were incubated at 70◦C for 10 min with a brief vortex after 5 and 10 min. The DNA concentration was measured using a NanoDrop (Thermo Fisher Scientific Inc., Waltham, MA, USA), and the samples were stored at −80◦C until the whole genome amplification of purified genomic DNA was performed. Uniform whole genome amplification was done using the REPLI-g mini kit (QIAGEN, Hilden, Germany). The DNA (10 ng) was denatured by adding a denaturation buffer and incubating for 3 min at room temperature. The denaturation was interrupted by a neutralization buffer and a master mix containing a reaction buffer, and DNA polymerase was added. All buffers and enzyme mixtures were made according to the protocol. The amplification reaction was performed by incubating the samples at 30◦C for 16 h in a thermal cycler, after which the reaction was stopped by heating the sample for 3 min at 65◦C. The DNA concentration was measured using a NanoDrop, and the samples were stored at −20◦C before the PCR amplification of the target genes.

### PCR Amplification of *gyrA* and *parC*

The software Primer3 (Rozen and Skaletsky, 2000) was used through the web interface Primer3Plus (Untergasser et al., 2007) to design PCR primers targeting the regions of *gyrA* and *parC* that include all resistance mutations reported by Ruiz (2003). To avoid placing primers in variable regions, all annotated *gyrA* and *parC* nucleotide sequences belonging to *Escherichia* were downloaded from the Pathosystems Resource Integration Center (PATRIC) (Gillespie et al., 2011) and each gene was aligned using MUSLCE (Edgar, 2004). Because *Shigella* is indistinguishable from *Escherichia* in the targeted gene regions, this genus was also added to the multiple sequence alignment. All variable positions were given as excluded regions in Primer3, and the portions including all resistance mutations were given as the target regions. The product size range was set as 250–350 base pairs (bps) so that the amplicons would, to a large extent, be completely covered by a single 454 sequence read. The top 10 suggested primers were tested experimentally to determine the best primer pair, producing the largest amount of amplicons of the expected length, for each gene. The selected primers, targeted regions, and experimental design are shown in **Table 1**.

All of the samples were amplified using the selected primer pair for each gene and the set-up described in **Table 1**. The following was combined in sterile 0.2 ml tubes: 1xGotaqR Reaction buffer, 0.2 mM dNTP Mix, 0.4 µM forward primer, 0.4 reverse primer, 1.25 µ GoTaqR DNA polymerase (Promega, Madison, WI, USA), 50 ng template, and water up to 25 µl. The PCR amplification used an initial denaturation at 95◦C for 2 min, denaturation at 95◦C for 10 s, annealing at 57◦C for 30 s, extension at 72◦C for 1 min, and a final extension for 7 min. Each reaction was run for 40 cycles to maximize the amount of amplicon DNA. The PCR products were separated using 1.5% agarose gel electrophoresis and visualized with ethidium bromide. The DNA fragment of interest was excised from the agarose gel and placed in a microcentrifuge tube, and the GeneJETTM gel extraction kit (Fermentas International Inc., Vilnius, Lithuania) was used according to the enclosed protocol to obtain the DNA amplicons. The purified amplicons were pooled to enable sequencing in a single run, and therefore,

each sample contained amplicons of both *gyrA* and *parC* derived from the same sample site. The amplicons were stored at −20◦C before sequencing.

### DNA Sequencing and Bioinformatics Analyses

The samples were sent to GATC Biotech (Konstanz, Germany) for multiplexed massively parallel pyrosequencing (Margulies et al., 2005) using titanium chemistry on the GS FLX+ system. The sequencing of the Swedish lake samples was performed on a separate time point. The resulting sequence reads were aligned to their respective reference sequence belonging to *E. coli* K-12 MG1655 (RefSeq locus tags, *gyrA*: b2231; *parC*: b3019) using GS Amplicon Variant Analyzer from 454 (v2.5p1). The aligned reads were exported from the software as one FASTA alignment file per gene and sample site. To limit the risk of interpreting sequence variability between species as resistance mutations, reads too dissimilar to the *Escherichia* and *Shigella* sequences were discarded after matching all reads against all sequences annotated with the gene symbol *gyrA* and *parC*, respectively, in the Comprehensive Microbial Resource (CMR) (Peterson et al., 2001) using BLASTn (Altschul et al., 1990). Only reads with a hit against a *gyrA* or *parC* sequence from either *Escherichia* or *Shigella*, and with an *E*-value lower than 1 × 10−100 were retained in the subsequent analysis. To compensate for the issue of homopolymers, which are common in 454 sequencing, any positions in the multiple sequence alignments with insertions in the reference sequence were removed, and any remaining deletions in the reads were substituted with the reference sequence base of that position. The resulting gapless reads were translated using the EMBOSS tool Transeq (reading frame 1 for *gyrA* and 2 for *parC*) (Rice et al., 2000). The relative abundance of non-synonymous substitutions was recorded. The relative abundance of a certain mutation was defined as the percentage of reads encoding that particular amino acid substitution. The average relative abundance of mutations was defined as the percentage of reads encoding any amino acid substitution averaged over all samples. The computations were done for both individual substitutions, and pairs of substitutions occurring within the same read. The correlation between fluoroquinolone pollution – measured as the total amount of fluoroquinolones detected (log-transformed) – and the abundance of resistance mutations was measured using Pearson's correlation coefficient.

#### Nucleotide Sequence Accession Number

The raw sequence data have been submitted to the Short Read Archive (SRA) under BioProject accession number PRJNA239415.

## RESULTS

The measurements of the fluoroquinolone concentrations present in the sediments confirmed that the sampled environments represented a range of different fluoroquinolone selective pressures (see Supplementary Table S1). Ciprofloxacin, enrofloxacin, and pefloxacin were detected at all Indian sample sites, ofloxacin was detected only upstream from the Indian WWTP, and lomefloxacin and difloxacin were detected only at the Indian downstream sites. None of the analyzed fluoroquinolones were detected in any of the Swedish samples. The highest level of fluoroquinolones was detected in the Indian downstream samples, while the upstream samples contained moderately high levels, as reported previously (Kristiansson et al., 2011).

A total of 35,417 reads aligned to the *gyrA* reference sequence (1,453–6,339 reads per sample), and 51,933 reads aligned to the *parC* reference sequence (537–15,469 reads per sample) (**Table 2**). The filtering of reads dissimilar to known *Escherichia* and *Shigella* sequences retained on average 60% of the *gyrA* reads (45–91% per sample) and 78% of the *parC* reads (72–95% per sample), suggesting that the *parC* primer pair is more specific for the targeted genera in the sampled environments compared to the *gyrA* primers. For *gyrA*, a total of 21,295 reads were used in the subsequent analysis (790–3,104 reads per sample), and 40,521 reads were used for *parC* (509–12,006 reads per sample).

Out of all the non-synonymous substitutions detected, the variability in codon 83 and 87 in *gyrA* and in codon 80 in *parC* was considerably higher than at any other codon (**Figure 1**).

Three non-synonymous mutations in *gyrA* were detected in all samples and they encode the following amino acid substitutions: S83L, D87N, and D82G (see Supplementary Table S2a). The most common substitution, S83L, was detected in a majority of reads in all samples (61–97%), while D87N was less abundant (1– 62%). Almost all of the D87N substitutions (97%) occurred in reads also encoding the S83L substitution. Although the D82G substitution was detected in all samples, it was rare (≤1%), as were other resistance mutations detected in only some of the samples (0–2%). Three non-synonymous mutations in *parC* were detected in all samples and they encode the following amino acid substitutions: S80I, E84G, and E84V (see Supplementary Table S2b). S80I was the most common substitution encoded by the *parC* amplicons, and was detected in 0.4–63% of the reads in each sample. The mutations in codon 84 were far less common, but 98% of all reads carrying substitutions in codon 84 also carried mutations encoding the S80I substitution. Other resistance mutations in *parC*, which were detected in only some of the samples, were rare (0–7%).

The differences in terms of non-synonymous mutations between the environments were small, and there was no obvious link between the abundance of these mutations and the fluoroquinolone selective pressure for either *gyrA* or *parC* (**Figure 2**, also see Supplementary Figures S1 and S2). Pearson's correlation coefficient between the log-transformed detected amounts of total fluoroquinolones (samples with no detected fluoroquinolones were set to the detection limit 0.02 µg/g organic matter) and the abundance of the most commonly detected substitutions were as follows: S83L, −0.058 (*p* = 0.87); D87N, 0.098 (*p* = 0.79); and S83L+D87N in GyrA, 0.088 (*p* = 0.81); S80I, −0.25 (*p* = 0.49); E84G, 0.54 (*p* = 0.10); E84V, 0.28 (*p* = 0.42); and S08I+E84G/V in ParC, 0.34 (*p* = 0.26). However, the sample taken downstream from and closest to the discharge site of the Indian WWTP showed the highest abundance of all said substitutions (**Figure 2**, also see Supplementary Figures S1a and S2a).

### DISCUSSION

In this study, we measured the relative abundance of chromosomal fluoroquinolone resistance mutations in *Escherichia* communities residing in both uncontaminated and severely fluoroquinolone polluted aquatic environments. We detected a high abundance of resistance mutations in the chromosomal target genes of fluoroquinolones, *gyrA* and *parC*, in all sampled environments, including environments with no fluoroquinolone pollution or known history thereof. Interestingly, we found no association between the measured concentrations of fluoroquinolones at the samples sites and

(B) *parC*. Samples with no detected fluoroquinolones are indicated in the figure as 0.2 µg/g (i.e., the detection limit).

the abundance of resistance mutations, except for the most polluted site, which showed the highest abundance of the most commonly detected mutations. This suggests that chromosomal mutations conferring fluoroquinolone resistance only could be considered a potential biomarker for detecting very extensive fluoroquinolone pollution. Additionally, the high abundance of mutations previously linked to fluoroquinolone resistance and the low abundance of other mutations indicate that there could be selective advantages to carry the resistance mutations in the sampled environments, even in the absence of fluoroquinolone selective pressure. Note that the levels of fluoroquinolones detected in the sediment cannot be directly compared to those of water solutions, as some fluoroquinolones are known to sorb to soil particles (Girardi et al., 2011). The exact amount of bioavailable antibiotics is, therefore, unknown, but likely lower than the detected levels.

To our best knowledge, the lowest reported minimal selective concentration for any antibiotic and resistance mutation is 0.1 µg/l for ciprofloxacin and the S83L substitution in GyrA (Gullberg et al., 2011). This concentration is just above the ones found in treated Swedish sewage effluents (Lindberg et al., 2005; Fick et al., 2011). However, the concentration was determined through competition experiments in a lab setting, and therefore, comparisons to environmental conditions should be made with some caution. Although no fluoroquinolones were detected downstream from the Swedish sewage treatment plant in this study, bacteria leaving the plant could theoretically have encountered selective concentrations inside the treatment plant. In the investigated Swedish lake, however, there are no plausible sources for fluoroquinolone exposure, indicating that the mutations found here are not present because of a fluoroquinolone selection pressure. Furthermore, since there is little difference in mutation abundance between the severely polluted sites and the remote Swedish lake, the data implies that the mutation abundance is not connected to fluoroquinolone selection pressure, but is largely determined by other, unknown factors.

In *gyrA*, mutations encoding the amino acid substitutions S83L and D87N were detected in all samples, with almost all of the D87N substitutions occurring in reads also encoding the S83L substitution. Both substitutions have been associated with fluoroquinolone resistance for *E. coli* and confer higher levels of resistance than any other substitutions in the QRDR (Yoshida et al., 1991). In fluoroquinolone-resistant clinical *E. coli* isolates, S83 is the most frequently altered amino acid, and, moreover, S83L is the most common substitution (Hopkins et al., 2005). A single substitution at position 83 confers higher resistance than at position 87, but additional mutations in *gyrA* or other genes are necessary for the development of highlevel fluoroquinolone resistance. The S83L substitution alone, however, confers the same level of resistance to ciprofloxacin for *E. coli* as the combination of S83L and D87N (increased MIC of ciprofloxacin from 0.016 to 0.38 mg/l), while the D87N substitution alone confers slightly lower resistance (ciprofloxacin MIC = 0.25 mg/l) (Marcusson et al., 2009; Machuca et al., 2014). In *parC*, mutations causing the substitutions S80I, E84G, and E84V were detected in all samples, and these three substitutions have been previously linked to fluoroquinolone resistance in *E. coli*. In fluoroquinolone-resistant clinical isolates, the most commonly altered amino acid in ParC is S80 followed by E84, and, specifically, S80I is the most common substitution (Hopkins et al., 2005). Substitutions in ParC are often, if not always, found together with substitutions in GyrA in fluoroquinoloneresistant isolates (Hopkins et al., 2005; Morgan-Linnell et al., 2009), and substitutions of S80 or E84 alone do not affect the susceptibility to fluoroquinolones unless GyrA is also altered (Bagel et al., 1999). Because of the method used in this study, it is not possible to determine to what extent the detected mutations in *gyrA* and *parC* occur in the same bacterium, but it is worth mentioning that a combination of the substitutions S83L and D87N in GyrA with S80I in ParC confers a very high resistance to ciprofloxacin (ciprofloxacin MIC = 32 mg/l) (Marcusson et al., 2009). To set the MICs into perspective, an Enterobacteriaceae isolate is classified as ciprofloxacin-resistant if its MIC is higher than 1 mg/l according to the EUCAST clinical breakpoints (EUCAST, 2014). Isolates with a MIC lower than 0.5 mg/l are classified as sensitive. It is important to note that fluoroquinolone resistance can be caused by a number of different genetic mechanisms and combinations thereof. To extrapolate a level of resistance solely from mutations in the target genes is associated with a high level of uncertainty, therefore, the MICs given above are only included as a rough reference.

The only sampling site that stood out in terms of high abundance of resistance mutations was the site closest to downstream of the discharge site of the Indian WWTP. Here, we observed the highest abundance of the S83L and D87N substitutions in GyrA, the S80I, E84G, and E84V substitutions in ParC, and, consequently, also the highest abundance of the paired substitutions in both proteins. This is indeed the sample site with the highest total concentration of fluoroquinolones, which would be consistent with the hypothesis that there is a selective advantage for resistance mutations in fluoroquinolonepolluted environments, but only at locations with very high concentrations of fluoroquinolones. However, some reads from the most polluted site did not contain any mutations that resulted in amino acid substitutions in either *gyrA* (1.2%) or *parC* (30%), which suggests that some bacteria thriving there may carry additional resistance factors protecting them. Indeed, we have shown previously that mobile fluoroquinoloneresistance genes (*qnr*) are highly abundant in the stream sediment (Rutgersson et al., 2014). The *qnr* genes provide low to moderate resistance to fluoroquinolones [ciprofloxacin MIC up to 2 mg/l in *E. coli* transconjugants (Robicsek et al., 2006; Flach et al., 2013)]. Given the data presented here, it is possible that the presence of *qnr* genes in aquatic bacterial comminutes constitutes a better marker of fluoroquinolone exposure than chromosomal mutations. Or, there could be other mutations, outside the QRDR sequenced in this study, better suited as markers of exposure. Culturing-based methods will be required to fully elucidate the genetic mechanisms for how bacteria have adapted to survive the high concentrations of fluoroquinolones here.

A contributing factor to the high abundance of fluoroquinolone resistance mutations in the environment could be that there is little to no cost for the bacterium to carry these mutations. It has previously been shown that the substitutions S83L and D87N in GyrA and S80I in ParC occurring alone, or all three in the same organism, do not significantly alter the fitness of *E. coli in vitro*, nor do the pair of S83L in GyrA and S80I in ParC (Marcusson et al., 2009; Machuca et al., 2014). The pair S83L and D87N in GyrA has been shown to confer a fitness cost (measured relative fitness 0.97) when introduced in *E. coli* K-12 MG1655 (Marcusson et al., 2009), while the pair substitution was associated with a fitness gain in *E. coli* ATCC 25922 (relative fitness 1.14) (Machuca et al., 2014). In contrast, the pair of D87N in GyrA together with S80I in ParC introduce a slight fitness gain (measured relative fitness 1.02). Competition experiments with wild type *gyrA* in *E. coli* and mutants encoding either the S83L or the D87N substitution have shown that a ciprofloxacin concentration of 0.1 and 2.5 µg/l, respectively, is sufficient for the mutants to have a selective advantage (Gullberg et al., 2011). Furthermore, competitive i*n vivo* studies of other species – i.e., *Neisseria gonorrhoeae* in mice (Kunz et al., 2012) and *Campylobacter jejuni* in chickens (Luo et al., 2005) – have even found a fitness benefit associated with *gyrA* mutations corresponding to codon 83 in *E. coli*. In summary, a lack of fitness cost for these substitutions in the sampled environments could explain why they appear to be very common even in environments without any detectable fluoroquinolone pollutants or any known history thereof. As we do not yet understand the possible advantages these genotypes may have in the absence of fluoroquinolones, and because of the limited number and types of environments investigated in this study, we cannot generalize to the point of claiming that resistance mutations in *gyrA* and *parC* are common in all environmental *Escherichia* communities.

The abundance of resistance mutations in the Swedish samples stands in contrast to the frequency of fluoroquinolone-resistant infections in Sweden. On average, the S83L substitution in GyrA was detected in 87% of the Swedish reads, the combination of S83L and D87N in 33%, and the S80I substitution in ParC in 43%. In Sweden, only 11.6% of the clinical invasive *E. coli* isolates tested with ciprofloxacin were resistant in 2013 (ECDC, 2014). This is far below the abundance of resistance mutations detected in both the Swedish lake samples and the samples taken near a sewage treatment plant. The large difference between the abundance of fluoroquinolone resistance mutations in the environment and the frequency of resistant *E. coli* infections in Sweden is likely due to large differences between the pathogenic *E. coli* strains and the strains residing in the sampled environments. Indeed, the genome of *E. coli* is known to be highly variable (Lukjancenko et al., 2010). Furthermore, competition experiments testing the relative fitness of the resistance mutations is typically performed under optimal growing conditions, unlike environmental conditions. It is possible that there is a selective advantage not linked to fluoroquinolones for these mutations in the sampled environments. Indeed, our finding of how abundant the resistance mutations are even in unpolluted environments suggest that the sequence defined as wild-type for GyrA and ParC, respectively, in *E. coli* is only one of a number of common sequences within the species.

The method presented here proved useful to compare the abundances of mutations occurring within a short genomic region in an entire microbial community. Next generation sequencing techniques provide a cost-effective comprehensive approach to study entire bacterial communities without relying on the cultivation of individual isolates. To distinguish between resistance mutations and inter-species variability, it is important

to design the primers as specific for the targeted taxon as possible. If primers are not sufficiently specific, unwanted reads need to be filtered out by matching all reads to the target sequences and discarding reads of low resemblance. However, setting a similarity threshold for such a filtering where you allow for within species variability is not straight-forward. Here, we chose the threshold based on sequence alignments of different *Escherichia* and *Shigella* sequences and closely related genera. Additionally, we propose that amplicon sequencing could also be used to study resistance mutations in the ribosomal rRNA 23S gene that confer resistance to macrolides, lincosamides, and streptogramin B (Vester and Douthwaite, 2001). For future work in finding more suitable markers of fluoroquinolone exposure, we propose a more controlled experimental set up where different environments are dosed with various concentrations of fluoroquinolones for an extended period of time and the effect of the microbiota is studied using metagenomic sequencing.

In this study, we show that there is a significant abundance of fluoroquinolone resistance mutations in environmental *Escherichia* communities residing both in fluoroquinolonepolluted and pristine environments. This suggests that the mutations are not associated with a substantial fitness cost for the bacterium, even where there is no selective pressure for fluoroquinolone resistance. Regardless of whether the detected mutations are sufficient to provide clinically relevant resistance to fluoroquinolones, they are one or two mutations closer to obtaining a high level of resistance.

#### REFERENCES

### AUTHOR CONTRIBUTIONS

AJ, EK, and JL conceived of the study and participated in its design. AJ collected samples from the Swedish lakes. JF performed the chemical analyses of the sediments. BW prepared DNA from the samples and did the PCR amplifications. AJ designed the PCR primers, performed all data analyses, and drafted the manuscript. All authors read and approved the final manuscript.

### ACKNOWLEDGMENTS

We acknowledge Gamana for help with the sampling in India, and the following funding agencies that supported this study: the Swedish Research Council (K2011-56X-21750-01-6), the Swedish Foundation for Strategic Environmental Research Mistra (2004- 147), the Life Science Area of Advance at Chalmers University of Technology, and the Swedish Research Council Formas (244314727).

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal*.*frontiersin*.*org/article/10*.*3389/fmicb*.* 2015*.*01355

high levels of resistance and gene transfer elements. *PLoS ONE* 6:e17038. doi: 10.1371/journal.pone.0017038

**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 © 2015 Johnning, Kristiansson, Fick, Weijdegård and Larsson. 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.*

# Serotypes and Antibiotic Susceptibility of *Streptococcus pneumoniae* Isolates from Invasive Pneumococcal Disease and Asymptomatic Carriage in a Pre-vaccination Period, in Algeria

Hanifa Ziane1 , Vera Manageiro2, 3 \*, Eugénia Ferreira2 , Inês B. Moura2 , Soumia Bektache1 , Mohamed Tazir 1 and Manuela Caniça2

1 Service de Microbiologie Médicale, Centre Hospitalo-Universitaire Mustapha Bacha, Faculté de Médecine, Algiers, Algeria, 2 National Reference Laboratory of Antibiotic Resistances and Healthcare Associated Infections, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge, Lisbon, Portugal, 3 Centre for the Studies of Animal Science, Institute of Agrarian and Agri-Food Sciences and Technologies, University of Oporto, Oporto, Portugal

#### *Edited by:*

José Luis Capelo, University NOVA of Lisbon, Portugal

#### *Reviewed by:*

Atte Von Wright, University of Eastern Finland, Finland Pedro Ismael Da Silva Junior, Butantan Institute, Brazil

*\*Correspondence:* Vera Manageiro<EMAIL_ADDRESS>
#### *Specialty section:*

This article was submitted to Antimicrobials, Resistance and Chemotherapy, a section of the journal Frontiers in Microbiology

*Received:* 31 January 2016 *Accepted:* 11 May 2016 *Published:* 14 June 2016

#### *Citation:*

Ziane H, Manageiro V, Ferreira E, Moura IB, Bektache S, Tazir M and Caniça M (2016) Serotypes and Antibiotic Susceptibility of Streptococcus pneumoniae Isolates from Invasive Pneumococcal Disease and Asymptomatic Carriage in a Pre-vaccination Period, in Algeria. Front. Microbiol. 7:803. doi: 10.3389/fmicb.2016.00803 In Algeria, few data is available concerning the distribution of pneumococcal serotypes and respective antibiotic resistance for the current pre-vaccination period, which is a public health concern. We identified the most frequent Streptococcus pneumoniae serogroup/types implicated in invasive pneumococcal disease (IPD; n = 80) and carriage (n = 138) in Algerian children younger than 5 years old. Serogroup/types of 78 IPD isolates were identified by capsular typing using a sequential multiplex PCR. Overall, serotypes 14, 19F, 6B, 23F, 18C, 1, 5, 7F, 19A, and 3 (55% of PCV7 serotypes, 71.3% of PCV10, and 90% of PCV13) were identified. Additionally, 7.5% of the non-vaccine serotypes 6C, 9N/L, 20, 24F, 35B, and 35F, were observed. In the case of S. pneumoniae asymptomatic children carriers, the most common serogroup/types were 6B, 14, 19F, 23F, 4, 9V/A, 1, 19A, 6A, and 3 (42.7% of PCV7 serotypes, 44.2% of PCV10, and 58% of PCV13). For 6.1% of the cases co-colonization was detected. Serotypes 14, 1, 5, and 19A were more implicated in IPD (p < 0.01), whereas serotype 6A was exclusively isolated from carriers (p < 0.01). Deaths associated with IPD were related to serotypes 19A, 14, 18C, and one non-typeable isolate. Among IPD related to vaccine serotypes, the rates of penicillin non-susceptible isolates were higher in no meningitis cases (80%) than in meningitis (66.7%), with serotypes 14, 19A, 19F, and 23F presenting the highest MIC levels (>2µg/ml). Resistance to cefotaxime was higher in isolates from meningitis (40.5%); however, resistance to erythromycin and co-trimoxazole (>40%) was more pronounced in no-meningeal forms. Overall, our results showed that PCV13 conjugate vaccine would cover up to 90% of the circulating isolates associated with IPD in Algeria, highlighting the importance of monitoring the frequency of S. pneumoniae serogroups/types during pre- and post-vaccination periods.

Keywords: pneumococci serotype, antibiotic susceptibility, invasive disease, pneumococcal carriage, children, vaccine, Algeria

## INTRODUCTION

Streptococcus pneumoniae remains the leading cause of bacterial infection among children worldwide, being the most common cause of bacterial pneumonia, and an important cause of meningitis and bacteremia. Approximately 800,000 deaths per year occur among children as a result of pneumococcal infection (Johnson et al., 2010). The management of pneumococcal infections has been aggravated by the rapid worldwide increase of resistance to penicillin and other antibiotics, mostly related to the misuse of these drugs in respiratory pathogens (Song et al., 2012; Ginsburg et al., 2013).

Despite the diversity of capsular types, comprising at least 98 distinct serotypes, only some variants are associated with invasive pneumococcal disease (IPD; Caierão et al., 2014; Richter et al., 2014).

Pneumococcal disease is frequently preceded by asymptomatic nasopharyngeal colonization, which can be quite high in early childhood (Bogaert et al., 2004; Miernyk et al., 2011; Satzke et al., 2013). It is generally agreed that most serotypes recovered from IPD are also frequently identified in colonized healthy children (Bogaert et al., 2004; Dias and Caniça, 2007). However, serotype prevalence can change according to age, geography, time, and antibiotic resistance, among other factors (Finland and Barnes, 1977; Hausdorff et al., 2005; Ingels et al., 2012). IPD has also been related to recent respiratory viral infection (Weinberger et al., 2014).

In some countries, the use of effective pneumococcal conjugate vaccines (PCVs) during infancy have contributed to reduce morbidity and mortality associated to IPD, as well as nasopharyngeal colonization by vaccine serotypes (Ghaffar et al., 2004; Millar et al., 2006; Tan, 2012). Despite the availability of these vaccines, pneumococcal infections remain a global problem due to the replacement of vaccine by non-vaccine serotypes, mostly associated with the emergence of multidrug resistant serotypes, such as the serotype 19A (Dias and Caniça, 2007; Dagan et al., 2009; Richter et al., 2014). Thus, due to the widespread phenomena of serotype replacement, PCVs have been substituted by higher valence pneumococcal vaccines (from PCV7 and PCV10 to PCV13) across the world, according with the recommendations of the Centers for Disease Control and Prevention (CDC, 2013).

The monitoring of antibiotic resistance trends and serotype distribution in the pre- and post-vaccination periods is essential to assess the dynamic change of epidemiology. This way, the impact of vaccines and antibiotic use control programmes should be evaluated across countries.

In this study, we analyzed the frequency of serotypes associated to IPD and S. pneumoniae asymptomatic carriage among children younger than 5 years old in Algeria, before the introduction of the pneumococcal vaccine, and correlated the isolates antibiotic susceptibility with vaccine serotypes .

## MATERIALS AND METHODS

#### Bacterial Isolates

An overall of 218 S. pneumoniae isolates recovered from children <5 years old were collected and studied regarding the serotype. Briefly, 80 IPD isolates [children <1 year old (n = 44), 1–2 years old (n = 20), and 3–5 years old (n = 16)] were collected between the 1st January 2010 and the 31st December 2014. The isolates were recovered from routine microbiological cultures at Laboratory of Clinical Microbiology, at CHU Mustapha Bacha (LCM/CHU), Algiers, Algeria, and at cooperation laboratories in the north (n = 50), west (n = 12), south (n = 2), and northeast (n = 16) regions of the country that sent samples and/or isolates to LCM/CHU. Isolates were included if they were obtained from consecutive blood, and cerebrospinal, pleural, peritoneal, ascitic, bone, and joint fluids from patients with symptoms compatible with IPD. Only one isolate per patient was considered .

In addition, all nasopharyngeal cultures (n = 130) recovered at LCM/CHU between 2011 and in 2012, from asymptomatic children <5 years old were also included for serotyping evaluation. Each age group of <1 year, 1–2 years, and 3–5 years included 91, 20, and 27 S. pneumoniae isolates, respectively. Only one isolate per child was considered, except for eight cultures corresponding to carriers co-colonized with two pneumococcal serogroups/types (in a total of 138 isolates). Authorization for carriage study was approved by "The Direction de la Santé et de la Population de la Wilaya d'Alger," in Algeria.

Culture of sterile body fluids and nasopharyngeal samples at LCM/CHU was carried out by standard protocols. Pneumococcal isolates were identified using classic microbiological tests: colony morphology, optochin susceptibility, and bile solubility (**Figure 1**). Thirty seven S. pneumoniae isolates expressing different serogroups/types (1, 3, 4, 5, 6B, 6C, 7F, 7C, 8, 9V, 9N, 10A, 10F, 11A, 12F, 13, 14, 15A, 15B, 16F, 17F, 18C, 19F, 19A, 20, 21, 22F, 23A, 23B, 23F, 24F, 31, 33F, 34, 35A, 35B, and 35F), belonging to the collection of the National Reference Laboratory of Antibiotic Resistances and Healthcare Associated Infections, at National Institute of Health in Portugal, were also used as controls for serotype identification, as previously (Ziane et al., 2015).

### DNA Extraction and Multiplex PCRs

To extract DNA from clinical and control S. pneumoniae isolates, several colonies were picked from the culture plates. DNA was extracted by the heat lysis method and stored at −20◦C until further analysis. The serogroups, and whenever possible the serotypes, of 80 S. pneumoniae from IPD and of 138 recovered in asymptomatic carriers were determined by sequential multiplex groups (SMGs), as previously described (Ziane et al., 2015; **Figure 1**).

## Quellung Serotyping

In addition to multiplex PCR (Ziane et al., 2015), serogroups/types of all the 80 invasive isolates were determined at LCM/CHU by Quellung reaction with specific type antiserum [Statens-Serum Institute]. Concerning the isolates recovered from carriers, only those determined as serotype 6A/B or as non-typeable by the multiplex PCR method, were characterized by Quellung reaction (**Figure 1**).

### PCR Detection of Autolysin (*lytA*) Gene

A primer pair 5′ -TCCAGCCTGTAGCCATTTCG-3′ and 5′ - GCGGTTGAACTGATTGAAAG-3′ that specifically targeted a

472 bp internal region of the autolysin (lytA) gene was used to the identification of cps-negative S. pneumoniae. The amplification conditions were: initial denaturation at 94◦C for 5 min., followed by 30 cycles of denaturation at 94◦C for 30 s, annealing at 56◦C for 30 s and extension at 72◦C for 30 s, and a final extension at 72◦C for 5 min. Positive and negative controls were included in each PCR reaction.

#### Antibiotic Susceptibility Testing

Susceptibility testing of 72 IPD vaccine serotype isolates and of 8 IPD non-vaccine serotype was carried out by an agar disk diffusion method for four antibiotics (erythromycin, clindamycin, co-trimoxazole, tetracycline), and minimal inhibitory concentration (MIC) was determined using E-test method (AB Biodisk) for four β-lactam antibiotics (penicillin, amoxicillin, cefotaxime, and imipenem). Testing conditions and susceptibility interpretation followed the standards proposed by the Clinical and Laboratory Standards Institute (CLSI, 2014). S. pneumoniae ATCC 49619 was used as the quality control strain.

#### Statistical Analysis

OpenEpi software, version 3.03a (Dean et al., 2015), was used for statistical analysis. Fisher exact test was used to assess differences between IPD and carriers groups. One-tail P ≤ 0.05 were considered to be statistically significant.

### RESULTS

#### IPD Serogroup/Types

Between 2010 and 2014, a total of 207 episodes of IPD were registered at LCM/CHU. Among those, 80 (38.6%) corresponded to children <5 years old and were retained for this study. These 80 IPD cases (**Figure 2**) comprised 56.3% of occurrences in males and 43.7% in females, with 64 cases (80%) being reported to infants (≤2 years old). Overall, the serotypes were identified in 78 isolates, while two were non-typeable (**Table 1**).

Forty-eight (60%) of the total IPD episodes included cases of meningitis [of which 62.5% (30/48) were in infants <1 year old], while 40% (32/80) comprised cases of nonmeningitis [56.3% of

which were pleuropneumonia (18/32), including 55.5% (10/18) in infants from 1 to 2 of age; **Figure 2**]. The most frequent serotypes implicated in IPD in this study, which accounted for 87.5% (70/80) of the tested isolates, were in decreasing frequency (**Figure 3**): 14, 19A, 19F, and 1 (from 0 to 5 years old), 5 (from 0 to 2 years old), 6B (from 0 to 5 years old), 3 (from <1 year old), and 23F (from <1 year, and from 3 to 5 years old). Serotypes 14, 1, 19A, 19F, 5, 3, and 6B were the most common in meningitis cases. However, serotypes 14, 19A, 5, and 6B were also implicated in pleuropneumonia, and 19A, 19F, and 14 in bacteremia (**Figure 2**).

Deaths caused by S. pneumoniae infection were noticed in 7 IPD cases (7/80, 8.8%) associated with meningitis (6/7, 85.7%), and pneumonia (1/7, 14.3%). Serotypes 19A and 14 were cause of death in 3 (42.8%), and 2 (28.6%) cases, respectively. The two remaining death cases were caused by serotype 18C, and one non-typeable isolate.

A total of 44 pneumococcal isolates expressed the serotypes included in PCV7, which would reflect the coverage of 55% (44/80) (**Figure 4**; **Table 1**). The coverage of PCV10 would be of 71.3% (57/80), because there were 13 isolates expressing serotypes 1 (6/57, 10.5%), 5 (6/57, 10.5%), and 7F (1/57, 1.8%). The coverage of PCV13 would reach up to 90% (72/80) (**Figure 4**, **Table 1**). All PCVs would cover the three age groups included in the study. Non-vaccine serogroup/types were expressed in 7.5% (6/80) with one isolate of each: 6C/D, 9N/L, 20, 24F, 35B, and 35F.

### Serogroup/Types Characterization of Nasopharyngeal Isolates

The serogroup/type of 138 isolates, identified in 130 nasopharyngeal cultures from colonized children <5 years old, was determined by multiplex PCR method, using the same scheme as for IPD isolates (**Figure 1**): 117 (83.6%) S. pneumoniae were characterized at the serogroup/type level [101 (86.3%) children carried a single serogroup/type, whereas eight children (8/132, 6.1%) were co-colonized with pneumococci belonging to two different serogroup/types]. Furthermore, of the 18 isolates that remained non-typeable by multiplex PCR reactions, 3 were assigned to serogroup/type 15, 19A, and 20 by the Quellung reaction (**Table 1**). Serogroup 6A/B was differentiated by Quellung reaction into serotype 6B (n = 16) and serotype 6A (n = 13).

The most common serogroup/type was 6 (n = 31) [divided in 6A (n = 13), 6B (n = 16) (both included in PCV13 and PCV7, respectively), and 6C/D (n = 2)]; it was followed by serogroup/type 14 (n = 13), 19F (n = 12), and 23F (n = 11; **Figure 4**; **Table 1**). All these four serogroup/types were identified in the three age groups defined: <1 year, 1–2 years, and 3– 5 years (**Figure 3**). The remaining conjugate vaccine serotypes identified in asymptomatic children carriers of S. pneumoniae included 19A (n = 5), 4 (n = 4), 9V/A (n = 3), 1 (n = 2), and 3 (n = 1). Non-conjugate vaccine serotypes accounted for

TABLE 1 | *S. pneumoniae* conjugate vaccines PCV7, PCV10, and PCV13 and non conjugate vaccine serotypes implicated in IPD cases and in nasopharyngeal carriage, according to the age groups.

aOne-tail P ≤ 0.05 were considered to be statistically significant.

bFour isolates were serotyped by Multiplex PCR and one was serotyped by Quellung reaction.

c Isolates serotyped only by Quellung reaction.

dThree Multiplex PCR non-typeable isolates were serotyped only by Quellung reaction (serotypes 19Ab , 15c , and 20c ).

29% (40/138), identified by both PCR (n = 38) and Quellung reaction (n = 2). These serotypes were mostly identified as 15A/F, 15B/C, 34, 23B, 35B, and 11A/D. Globally, the section of the study that included the carrier patients allowed the identification of 120 isolates at serogroup/type level, and the evaluation of 18 non-typeable isolates.

Overall, 4.1% (09/218) of the isolates lacked the cpsA gene. However, the presence of the lytA gene confirmed the identification of S. pneumoniae specie. In addition, the sequential multiplex PCR scheme (**Figure 1**) used in our study demonstrated a specific identification of each serogroup/type in 90.8% (198/218) of the isolates analyzed: among the 80 IPD and the 138 nasopharyngeal S. pneumoniae isolates, 97.5% (78/80) and 86.9% (120/138) were positively serotyped by sequential multiplex PCR, respectively (p < 0.01; **Table 1**).

### Antibiotic Susceptibility and Vaccine Serotype

Among S. pneumoniae vaccine serotypes (n = 72) from meningitis (n = 39) we identified 66.7% isolates penicillin nonsusceptible (MIC ≥ 0.12 µg/ml) with 25.6% showing high level of resistance (MIC 2–4 µg/ml; **Table 2**). Isolates non-susceptible to cefotaxime and imipenem corresponded to 40.5 and 43.2%, respectively. However, high level of resistance was noticed for imipenem only in 5.4% isolates.

From no meningitis infections (n = 25), 80% of the isolates were penicillin non-susceptible with 12% of high level of resistance (MIC = 4–8 µg/ml). Intermediate resistance to amoxicillin and cefotaxime was 9.1 and 8.3%, respectively. High level of resistance to amoxicillin was observed in 4.5% isolates (MIC 8 µg/ml).

Non-susceptibility to erythromycin, clindamycin, cotrimoxazole, and tetracycline occurred in lower frequencies in isolates from meningitis (42.5, 40, 53.8, and 27.2%, respectively) than in isolates from no meningitis infections (74.1, 66.7, 75, and 46.2%, respectively).

High level of resistance for vaccine serotypes was observed in serotypes 14, 19A, 19F, and 23F. Overall, the vaccine serotypes 14, 19A, 19F, 23F, 6B, and 5 presented higher rates of resistance (90–100%) than the eight non-vaccine serotypes (6C, 9N, 20, 24F, 35B, 35F, non-typable; p < 0.05; data not shown).

#### DISCUSSION

S. pneumoniae remains the leading cause of bacterial infection among children worldwide, including numerous cases of invasive disease associated high morbidity and mortality rates (Harboe et al., 2010; Adegbola et al., 2014). The pneumococcal

epidemiology regarding capsular types and antibiotic resistance varies geographically and temporally in terms of origin of the isolates (infections or carriage), clinical presentation, pathogenicity (Hausdorff et al., 2005; Harboe et al., 2010; Ingels et al., 2012; Geno et al., 2015), and the methods used for serotyping (Turner et al., 2011; Song et al., 2012; Geno et al., 2015). Although antibiotic susceptibility and serotype data remains insufficient in many countries such as Algeria, its collection and evaluation is essential for the treatment of pneumococcal infections and for the usage of conjugate vaccines (Ramdani-Bouguessa and Rahal, 2003; Tali-Maamar et al., 2012; Ziane et al., 2012; Ramdani-Bouguessa et al., 2015).

Thus, the main goal of this study was to analyze the frequency of serotypes associated to IPD and S. pneumoniae asymptomatic carriage in Algeria, in children <5 years old before the introduction of the pneumococcal vaccine. To accomplish our purpose, we used the more recent IPD samples studied in the country (Ramdani-Bouguessa and Rahal, 2003; Tali-Maamar et al., 2012; Ziane et al., 2012; Ramdani-Bouguessa et al., 2015). It is worth mentioning that a molecular approach was here applied for the first time to isolates recovered in this country in the context of a monitoring survey of S. pneumoniae serogroup/types (Ziane et al., 2015).

In this study, meningitis represented 60% of the clinical presentation of IPD, with 79.2% registered in children younger than 2 years old. Pleuropneumonia was reported in 22.5% of the total IPD cases, with the majority being manifested in infants (88.8%, 16/18). Differently from bacteremia, mastoiditis, and abdominal infections, the bone and joint infections were noted exclusively in infants with up to 1 year old. Indeed, IPD occurs mostly in children under the age of 5 years, especially within the subgroup of those under 2 years of age (Tan, 2012). The prevalence of S. pneumoniae carriage in healthy children younger than 5 years old can fluctuate between 20 and 93.4% in low income countries, being superior than what is stated for lower-middle income countries (from 6.5 to 69.8%), as reported by Adegbola et al. (2014). In addition, the density of pneumococcal nasopharyngeal carriage seems to decrease in higher age groups, with the children being more competent than adults in the transmission of pneumococci (Roca et al., 2012).

Mortality rate of pneumococcal invasive diseases may range from 10 to 30%, according with the studies of Pebody et al. (2006), and Bravo (2009). Although it has been reported that the highest S. pneumoniae-associated morbidity and mortality rates are in Africa and Asia (Johnson et al., 2010; Turner et al., 2011), in our study the case fatality was 8.8%, mainly comprising meningitis related with vaccine serotypes (85.7%).

Overall, we identified serogroups 14, 19, 23, and 6 as the most common among IPD and nasopharyngeal carriers (**Figure 2**). Antibioticb, c site of infection Antibiotic susceptibility (%) Total no. of isolates (*n* = 72) Breakpointb, c (CLSI, 2014) S I R IR S≤ R≥ PENICILLIN G Meningitis 33.3 – 66.7 66.7 39 0.06 0.12 PARENTERAL PENICILLIN PG No meningitis 88.0 8.0 4.0 12.0 25 2 8 ORAL PENICILLIN No meningitis 20.0 32.0 48.0 80.0 25 0.06 2 AMOXICILLIN No meningitis 86.4 9.1 4.5 13.6 22 2 8 CEFOTAXIME Meningitis 59.5 40.5 0.0 40.5 37 0.5 2 No meningitis 91.7 8.3 0.0 8.3 24 1 4 IMIPENEM Meningitis 56.8 37.8 5.4 43.2 37 0.12 1 ERYTHROMYCIN Meningitis 57.5 0.0 42.5 42.5 40 ≥21 ≤15 No meningitis 25.9 0.0 74.1 74.1 27 ≥21 ≤15 CLINDAMYCIN Meningitis 60.0 0.0 40.0 40.0 40 ≥19 ≤15 No meningitis 33.3 0.0 66.7 66.7 27 ≥19 ≤15 CO-TRIMOXAZOLE Meningitis 46.2 2.6 51.2 53.8 39 ≥19 ≤15 No meningitis 25.0 0.0 75.0 75.0 24 ≥19 ≤15 TETRACYCLINE Meningitis 71.8 2.6 25.6 27.2 39 ≥28 ≤24 No meningitis 57.7 3.8 42.3 46.2 26 ≥28 ≤24

TABLE 2 | Antibiotic susceptibility of 72 isolates of vaccine serotypesa , according to site infection.

a Includes serogroups/types: 1 (n = 6), 3 (n = 3), 5 (n = 6), 6B (n = 6), 7 (n = 1), 14 (n = 26), 18C (n = 1), 19A (n = 12), 19F (n = 8), and 23F (n = 3).

bSusceptibility testing by E-test method (MIC determination), for penicillin, amoxicillin, cefotaxime, and imipenem.

cSusceptibility testing by agar disk diffusion method, for erythromycin, clindamycin, co-trimoxazole, tetracycline.

S, Susceptible; I, Intermediate; R, resistant; IR, non-susceptible.

Among IPD isolates, serotypes 14, 19A, 19F, 6B, 1, and 5 were the most frequent, which shows some differences from data described for other periods in Algeria. For instance, the serogroups/types 1 and 5 were the most common for the period of 1996–2000 (Ramdani-Bouguessa and Rahal, 2003), the serogroups/types 14, 19F, 23F, and 6B for the periods of 2001– 2010 and 2005–2011 (Tali-Maamar et al., 2012; Hecini-Hannachi et al., 2014), and serogroups/types 14, 19F, 6B, 1, and 19A for the period of 2005–2012 (Ramdani-Bouguessa et al., 2015). In Tunisia, the most prevalent serogroups for IPD in children were nearly the same: 19, 14, 23, and 4 (Charfi et al., 2012). Internationally, among the 98 known pneumococcal serotypes 11 of them account for more than 70% of IPD, in children younger than 5 years old, with serotypes 1, 5, 6A, 6B, 14, 19F, 23F being the most common (Johnson et al., 2010). Indeed, it has been described that a restricted number of serotypes is in the origin of the majority of the IPD cases worldwide. To summarize, since the report of the first studies concerning the distribution of IPD serotypes in Algeria, there was an emergence of serotype 19A, which is one of most common causes of invasive disease in developed countries in children (Geno et al., 2015). Furthermore, the studied isolates expressing serotype 19A were assigned to ST276 (M. Caniça, personal communication), which is one of the most predominant sequence-types within this serotype (Reinert et al., 2010; Ramos et al., 2014).

Some of the S. pneumoniae serotypes are more prone to successfully colonize the nasopharynx, being in advantage to cause invasive disease. The carriage of S. pneumoniae may play an important role in the pathogenesis of IPD and in the transmission of this bacterium (Roca et al., 2012). Indeed, vaccination often brings a decrease in the reduction of vaccine serotype S. pneumoniae isolates, and a raise in carriage of nonvaccine serotype isolates (Dias and Caniça, 2007).

In this study, it is essential not only to emphasize the differences in serotype distribution (in IPD and asymptomatic carriage), but also to consider the presence of non-vaccine types (such as 15, 35B, and 34), particularly in carriage, despite the unavailability of pneumococcal vaccines in Algeria (**Figure 2**). Thus, when comparing serotype rate for IPD and nasopharyngeal carriage, serotypes 14, 1, 5, and 19A were more implicated in IPD than in carriage (p < 0.01), whereas serotype 6A was exclusively isolated from carriers (p < 0.01; **Table 2**).

Non-typeable isolates by PCR methods should be typed by Quellung reaction in order to monitor and detect the emergence of S. pneumoniae serotype variants, and if this test is negative, the isolates should be sequenced for the cps locus to characterize variants (Bentley et al., 2006). In fact, the cpsA gene is common within most encapsulated S. pneumoniae, being a highly conserved region of the cps locus in all known pneumococcal cps operons (Bentley et al., 2006; Pai et al., 2006; Jin et al., 2009). However, the absence of cpsA amplification in the multiplex PCR scheme has been reported among rough strains, and pneumococci with mutated capsular genes, or without the cps locus (Pai et al., 2006; Ahn et al., 2012; Richter et al., 2013). Previous studies have also reported absence of cpsA gene by PCR-based serotyping of S. pneumoniae in 1–3% of the cases, particularly among serotypes 38 and 25F (da Gloria Carvalho et al., 2010; Jourdain et al., 2011). In thisstudy, 4.1% of the isolates lacked the cpsA gene.

Among the cpsA negative isolates, the detection of the lytA gene resolved the S. pneumoniae specie (Moreno et al., 2005). Thus, we propose the scheme in **Figure 1** for pneumococcal serotyping that will extend the application of multiplex PCR in laboratories, and concentrate the use of conventional method in reference laboratories only.

Similarly to other countries (Flasche et al., 2011; Ahn et al., 2012; Steens et al., 2013; von Gottberg et al., 2014), we noticed in Algeria an increase of serotypes covered by the different PCVs, particularly among IPD (**Figure 4**). These new data suggests an increase in the frequency of serotypes included in PCV13 in Algeria, in comparison with the 74.2% registered between 2005 and 2011 (Hecini-Hannachi et al., 2014), but similar to what was observed from 2005 to June 2012 (86.8%; Ramdani-Bouguessa et al., 2015).

Concerning the antibiotic resistance of S. pneumoniae from vaccine serotypes, the rates obtained were higher in no meningitis infections probably due to the large use of these antibiotics in the treatment of respiratory or urinary tract infections in Algeria. Tetracycline resistance rate might be explained by a lesser use of this antibiotic.

Rates of S. pneumoniae non-susceptible to penicillin vary in the country according to the study periods. Therefore, Algerian studies reported 34.6% of penicillin non-susceptible S. pneumoniae in 2003 (Ramdani-Bouguessa and Rahal, 2003), 25.2% in 2001–2010, mostly from meningitis, and 4.4% of high level resistance to cefotaxime (Tali-Maamar et al., 2012). A later study, conducted on invasive and non-invasive pneumococcal disease in children, identified 48% of penicillin non-susceptible isolates, mainly in no meningeal infections (Ramdani-Bouguessa et al., 2015). Rates of 48.5% and 45% have been reported in Morocco and Tunisia, respectively (Charfi et al., 2012; Elmdaghri et al., 2012).

In our study, the decreased susceptibility to penicillin is significantly associated with both vaccine serotypes and nonvaccine serotypes (p < 0.05; data not shown), but the vaccine serotypes 14, 19A, 19F, and 23F, showed the highest levels of penicillin resistance (MIC Peni G > 2µg/ml). These data is in agreement to earlier reports from Algeria (Ramdani-Bouguessa and Rahal, 2003; Hecini-Hannachi et al., 2014), Tunisia (Charfi et al., 2012), Morocco, (Elmdaghri et al., 2010), and France (Varon, 2012), where the serotypes 14, 19F, 23F, 6B were described as the most resistant. However, in France, after the introduction of PCV13, the serotypes 19A, 19F, 15A, 35B, and 24F emerged as those with higher resistance (Varon et al., 2015).

The fluctuations of S. pneumoniae circulating serotypes and its relation with antibiotic resistance and the PCVs coverage, reinforces the importance of S. pneumoniae serogroup/type identification and studies of antibiotic susceptibility, in preand post-vaccination periods, particularly in countries with few data, such as Algeria. These will help guide the treatment and will motivate the implementation of strategies for prevention of pneumococcal disease.

### AUTHOR CONTRIBUTIONS

HZ designed the study, performed experiments, analyzed the data, and wrote the manuscript. VM analyzed the data and reviewed the manuscript. EF performed experiments and reviewed the manuscript. IM performed experiments and reviewed the manuscript. SB performed experiments. MT reviewed the manuscript. MC designed the study, analyzed the data and reviewed the manuscript. All authors read and approved the final manuscript.

### FUNDING

HZ was supported by a grant from Ministère de l'Enseignement Superieur et de la Recherche Scientifique in Algeria. VM was supported by FCT fellowship (grant SFRH/BPD/77486/2011), financed by the European Social Funds (COMPETE-FEDER), and national funds of the Portuguese Ministry of Education and Science (POPH-QREN).

### ACKNOWLEDGMENTS

The authors thank D. Jones-Dias for her suggestions for the manuscript. Additionally, the authors thank to R. Touati, F. Z. Iles, N. Abdelaziz, S. Benada, N. Haddadi, and A. Mertani, for their technical assistance and support during the study. The authors also thank to all collaborators in the north, western, south and northeast regions of the country who sent isolates to LCM/CHU (S. Bekhoucha, S. Zouagui, Z. Guechi, S. Mahrane, A. Azzam, D. Haouchine, L. Oussadou, D. Touati, S. Azzoug, M. Naim, F. Z. Henniche, N. Aggoune, K. Lassas, S. Azrou, F. Lalaoui, F. Sahli) as well as to the clinical collaborators (T. Annane, N. Bouhafs, A. Laraba, S. Kermani, S. Bouziane, and M. Neggazi).

### REFERENCES

colonization by Streptococcus pneumoniae in the first 2 years of life. Clin. Infect. Dis. 39, 930–938. doi: 10.1086/423379

**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 Ziane, Manageiro, Ferreira, Moura, Bektache, Tazir and Caniça. 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.

#### *Edited by:*

*Patrícia Poeta, University of Trás-os-Montes e Alto Douro, Portugal*

#### *Reviewed by:*

*Atte Von Wright, University of Eastern Finland, Finland Carmen Losasso, Istituto Zooprofilattico Sperimentale delle Venezie, Italy*

#### *\*Correspondence:*

*Haihong Hao, National Reference Laboratory of Veterinary Drug Residues and MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, No. 1, Shizhishan Street, Hongshan District, 430070 Wuhan, China<EMAIL_ADDRESS>Zonghui Yuan, National Reference Laboratory of Veterinary Drug Residues and MOA Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, No. 1, Shizhishan Street, Hongshan District, 430070 Wuhan, China<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Antimicrobials, Resistance and Chemotherapy, a section of the journal Frontiers in Microbiology*

> *Received: 06 March 2015 Accepted: 01 June 2015 Published: 22 June 2015*

#### *Citation:*

*Kuang X, Hao H, Dai M, Wang Y, Ahmad I, Liu Z and Yuan Z (2015) Serotypes and antimicrobial susceptibility of Salmonella spp. isolated from farm animals in China. Front. Microbiol. 6:602. doi: 10.3389/fmicb.2015.00602*

# **Serotypes and antimicrobial susceptibility of** *Salmonella* **spp. isolated from farm animals in China**

*Xiuhua Kuang1, 2, Haihong Hao1, 2, 3\*, Menghong Dai 2, 3, Yulian Wang2, 3, Ijaz Ahmad3, Zhenli Liu1, 3 and Zonghui Yuan1, 2, 3\**

*1 MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, Wuhan, China, 2 Hubei Collaborative Innovation Center for Animal Nutrition and Feed Safety, Huazhong Agricultural University, Wuhan, China, 3 National Reference Laboratory of Veterinary Drug Residues and MOA Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan, China*

*Salmonella* spp. can indirectly infect humans via transfer from animals and animal-derived food products, and thereby cause potentially fatal diseases. Therefore, gaining an understanding of *Salmonella* infection in farm animals is increasingly important. The aim of this study was to identify the distribution of serotypes in *Salmonella* samples isolated from chickens (*n* = 837), pigs (*n* = 930), and dairy cows (*n* = 418) in central China (Henan, Hubei, and Hunan provinces) in 2010–2011, and investigate the susceptibility of strains to antimicrobial agents. *Salmonella* isolates were identified by PCR amplification of the *invA* gene, serotypes were determined by using a slide agglutination test for O and H antigens, and susceptibility to 24 antimicrobials was tested using the agar dilution method. In total, 248 *Salmonella* strains were identified: 105, 105, and 38 from chickens, dairy cows, and pigs, respectively. Additionally, 209 strains were identified in diseased pigs from the Huazhong Agricultural University veterinary hospital. Among these 457 strains, the dominant serotypes were Typhimurium in serogroup B, IIIb in serogroup C, and Enteritidis in serogroup D. In antimicrobial susceptibility tests, 41.14% of *Salmonella* spp. were susceptible to all antimicrobial agents, 48.14% were resistant to at least one, and 34.72% were resistant to more than three classes. Strains were highly resistant to sulfamethoxazole-trimethoprim (39.61%), nalidixic acid (39.17%), doxycycline (28.22%), and tetracycline (27.58%). Resistance to cephalosporins and fluoroquinolones ranged from 5.25 to 7.44% and 19.04 to 24.51%, respectively. Among penicillin-resistant and cephalosporin-resistant strains, 25 isolates produced extended-spectrum β-lactamases (ESBLs). The multidrug-resistant and ESBL-producing *Salmonella* strains identified in healthy animals here will present a challenge for veterinary medicine and farm animal husbandry, and could also pose a threat to public health. The level of antibiotic resistance observed in this study further highlights the need for careful and selective use of antibiotics.

**Keywords:** *Salmonella,* **farm animals, serotype, antibiotics, antimicrobial resistance**

### **Introduction**

*Salmonella* spp. are a common source of foodborne diseases that cause morbidity and mortality worldwide (Chiu et al., 2010). Treating *Salmonella* infection in humans is expensive; for example, in the USA, it causes illness in ∼1.2 million patients annually, resulting in estimated medical costs of \$365 million (Centers for Disease Control and Prevention, 2014). In the European Union (EU), salmonellosis is the second most commonly reported gastrointestinal infection, with a confirmed case rate of 20.4 cases per 100,000 individuals in 2011 (European Centre for Disease Prevention and Control, 2013). In China, *Salmonella* causes an estimated 22.2% of foodborne diseases (Wang et al., 2007), and salmonellosis ranks fourth among the most prevalent foodborne diseases caused by microbial agents (Zhu et al., 2012). Many *Salmonella* serotypes exist, with *>*2600 serovars classified based on the reactivity of antisera to O and H antigens (Stevens et al., 2009), and ∼292 identified in China between the 1980s and the end of 2000 (Yang, 2010). *Salmonella* also affects farm animals, and infections on farms can cause substantial economic damage in relation to, for example, loss of poultry stocks and costly animal husbandry. Numerous serotypes of isolated *Salmonella* have been found to overlap between farm animals and humans (Alcaine et al., 2006). Indeed, *Salmonella* not only directly infects humans but also causes indirect infections via transfer from animals and animal-derived food products such as pork and milk.

The use of antimicrobials is important for the control and treatment of *Salmonella*. However, since the early 1990s, antimicrobial- and multidrug-resistant *Salmonella* strains have emerged, leading to treatment failure. Researchers have reported a link between the use of antimicrobials in food animals and the emergence of antimicrobial resistance in pathogenic bacteria (Gong et al., 2013). Multidrug-resistant bacteria pose a severe threat to public health, particularly those that are resistant to β-lactams and fluoroquinolones (Lai et al., 2014). The increasing number of multidrug-resistant *Salmonella* strains is a global concern, with some countries and international organizations creating surveillance systems which include collaboration between human health, veterinary, and foodrelated sectors to monitor the spread of these and other foodborne bacteria. Examples include the Danish Integrated Antimicrobial Resistance Monitoring and Research Program, the European Food Safety Authority, the National Antimicrobial Resistance Monitoring System in the USA, and the Global Foodborne Infections Network run by the World Health Organization. These surveillance systems are also employed to monitor antimicrobial resistance, antimicrobial consumption in livestock, and serotype distribution, and data describing the current trend of increasing resistance to multiple drugs has been made available (European Centre for Disease Prevention and Control, 2013). In contrast, surveillance reports are unavailable in China; however, the National Monitoring Network for Bacteria of Animal Origin was launched as a surveillance system in 2008. Travel, migration, and the distribution of food between countries can also contribute to the spread of foodborne diseases and multidrug-resistant bacteria. Therefore, monitoring the distribution of *Salmonella* serotypes and levels of antibiotic resistance in animals and animal-food products is also important for maintaining safe travel and the commercial trade in food animals (Lai et al., 2014; Russell et al., 2014).

In central China, Henan, Hubei, and Hunan provinces are important residential and trade centers. These three areas are also the main producers of animal-derived foods in China; in 2012, their output of meat, eggs, and milk accounted for 19.14%, 19.45%, and 9.17% of total Chinese production, respectively (China Agriculture Statistical Report, 2012). Previous studies documented a phenotype for *Salmonella* serovars that was discovered in chickens and pigs, and in animal-derived foods, in China (Gong et al., 2013; Li et al., 2013; Lai et al., 2014; Wang et al., 2014). However, specific knowledge of the *Salmonella* serovars that exist in dairy cows and other farm animals in central China is currently lacking. Therefore, the aim of this study was to evaluate the prevalence of *Salmonella* in chickens, pigs, and dairy cows on farms in central China. Additionally, the diversity of *Salmonella* serovars on these farms was identified, and their susceptibility and resistance to antimicrobial agents was investigated. A diverse range of serotypes was observed in healthy and diseased farm animals, and several multidrugresistant and extended-spectrum β-lactamase (ESBL)-producing *Salmonella* strains were identified.

### **Materials and Methods**

#### **Samples and** *Salmonella* **Isolation**

Cloacal and anal swabs were collected from healthy animals on farms in Henan, Hubei, and Hunan provinces between March 2010 and July 2011. Each sampling site was visited only once. In total, 2185 samples were collected in a random manner from chickens (*n* = 837), pigs (*n* = 930), and dairy cows (*n* = 418). Farms were chosen based on their scale with the following requirements: for pigs, annual sales were *>*10,000 heads; for chickens, the breeding stock was *>*100,000 heads; and for dairy cows, the breeding stock was *>*1000 heads. The owners of each farm gave permission for swab samples to be to collected. The animals from which samples were extracted remained alive, did not undergo any surgery, and were not administered any drugs. Therefore, ethical approval was not required for the study because the sampling process did not harm the animals; however, their distress was considered and minimized at all times. All collected samples were stored at 4 ◦C and cultured at least 24 h before the isolation experiments were conducted.

The procedure for culture and isolation was based on standard laboratory protocol (WHO Global Foodborne Infections Network, 2010). Briefly, the samples were mixed with 5 mL of 0.85% saline solution for 30 min, and 1 mL of this mixture solution was added to buffered peptone water (BPW; Hopebiol, Qingdao, China) at a volume ratio of 1:10. The resultant mixture was incubated for 10 h at 37 ◦C for preenrichment. Approximately 500μL of this BPW mixture was then added to 5 mL selenite cystine broth (Hopebiol, Qingdao, China) and incubated at 37 ◦C for 20 h. The broth was streaked onto CHROMagar *Salmonella* (CHROMagar, France) and incubated at 37 ◦C for 24–48 h. Potential *Salmonella* colonies were transferred into Luria–Bertani agar for purification and enrichment, and then incubated for 20 h at 37 ◦C to facilitate identification.

Additionally, 209 strains of *Salmonella* were isolated from samples collected from diseased pigs in the Huazhong Agricultural University veterinary hospital (HAUvh) between 2008 and 2010.

#### *Salmonella* **Identification**

Biochemical testing and the *invA* gene were used to confirm the identity of isolates with typical *Salmonella* phenotypes. Biochemical testing was performed using a biochemical tube (Hangzhou Microbe Reagent Co., Ltd., China), and the results were interpreted based on Bergey's Manual of Systematic Bacteriology (Garrity et al., 2004). The *invA* gene was amplified by polymerase chain reaction (PCR) (Malorny et al., 2003). Positive results were randomly selected for sequencing. The obtained sequences were compared with the same gene registered in GenBank by using BLAST.

#### **Determination of** *Salmonella* **Serogroup and Serotype**

The serogroup and serovars of the *Salmonella* isolates were determined by slide agglutination tests with O antigen and H antigen antiserums obtained from Lansheng, Lanzhou Institute of Biology, China. The results were interpreted according to the Kauffmann-White scheme (Grimont and Weill, 2007).

#### **Antimicrobial Susceptibility Testing**

The agar dilution method with Mueller-Hinton agar (Oxoid Ltd., England) was used to test the susceptibility of *Salmonella* to 24 antibiotics (**Table 1**). These antimicrobials were classified based on their importance to human medicine (Government of Canada, 2005). *Escherichia coli* ATCC 25922 was used as the control microorganism. The results of the tests for ampicillin (AMP), amoxicillin (AMX), amoxicillin-clavulanic acid (AMC), ceftriaxone (CRO), imipenem (IPM), aztreonam (ATM), gentamicin (GEN), amikacin (AMK), tetracycline (TET), doxycycline (DOX), ciprofloxacin (CIP), levofloxacin (LEV), nalidixic acid (NAL), sulfamethoxazole-trimethoprim (SXT), chloramphenicol (CHL), and fosfomycin (FOS) were interpreted based on CLSI M100-S22 (Clinical and Laboratory Standards Institute, 2012), whereas those for ceftiofur (CEF), enrofloxacin (ENO), and florfenicol (FFC) were interpreted based on CLSI M31-A3 (Clinical and Laboratory Standards Institute, 2008). Interpretive CLSI criteria were not available for cefquinome (CEQ), polymyxin B (PB), azithromycin (AZM), olaquindox (OLA), and mequindox (MEQ); therefore, results with the following minimum inhibitory concentration (MIC) values were considered resistant for these antibiotics: CEQ ≥8μg/mL (using CEF as a reference); PB ≥4μg/mL (Kwa et al., 2007); AZM ≥16μg/mL (Sjölund-Karlsson et al., 2011); OLA and MEQ ≥64μg/mL (Sørensen et al., 2003).

Strains that were resistant to AMP, AMX, ATM, and/or CRO were examined for ESBLs by using the MIC values of ceftazidime, ceftazime-clavulanic acid, cefotaxime, and cefotaxime-clavulanic

acid. Results were interpreted based on CLSI M100-S22 (Clinical and Laboratory Standards Institute, 2012), and *Klebsiella pneumoniae* ATCC 700603 and *E. coli* ATCC 25922 were used as the control organisms.

#### **Statistical Analysis**

The isolated strains were categorized as sensitive (S), intermediary (I), or resistant (R) based on the MIC values and the CLSI interpretive criteria. MIC50 and MIC90 were calculated using previously described methods (Schwarz et al., 2010), and 95% confidence intervals were calculated using SPSS 16.0 software (IBM, USA).

#### **Results**

#### *Salmonella* **Isolates and Serotypes**

In total, 248 bacterial isolates taken from healthy chickens, pigs, and dairy cows, and 209 isolates from diseased pigs, were verified as *Salmonella* spp., and 457 strains identified as serotypes were tested for antimicrobial susceptibility. In all samples taken from healthy animals, the prevalence of *Salmonella* spp. was 11.35% (248/2185). The specific prevalence of *Salmonella* spp. in chickens, pigs, and dairy cows was 12.55% (105/837), 4.09% (38/930), and 25.12% (105/418), respectively.

After serotyping, all isolates were divided into three groups (**Table 2**). Thirty-four isolates did not cluster for

#### **TABLE 2 | Serovar distribution of isolated** *Salmonella* **(***n* **= 457).**

*aN, the total number of Salmonella isolates per serogroup.*

*bn, number of isolates with a given serotype of animals.*

self-agglutination in sterile saline. Twenty-eight isolates could self-agglutination in sterile saline, but such activity was not observed with O antigen. The serogroups of the remaining 395 strains were determined. Eight distinct serogroups and 41 distinct serotypes were identified, as shown in **Table 2**. Group B (*n* = 205, 44.86%) and group C1 (*n* = 141, 30.85%) were identified as the dominant serogroups. Typhimurium 12.47% (*n* = 57) and IIIb 4.81% (*n* = 22) were the dominant serovars. Detailed serotypes could not be determined for 208 *Salmonella* isolates using the available H antigen in the different serogroups. According to the species of animal tested, the dominant serotypes were Typhimurium and Enteritidis in chickens, IIIb and Typhimurium in pigs, and Typhimurium and Agona in dairy cows (**Table 2**).

#### **Antimicrobial Susceptibility Testing**

Results of antimicrobial susceptibility testing are summarized in **Table 3**. Among the 457 isolates, 188 (41.14%) were susceptible to all tested antimicrobials and 220 (48.14%) were resistant to at least one antibiotic. All strains showed susceptibility or intermediate susceptibility to imipenem. Strains were most commonly resistant to nalidixic acid (39.17%), sulfamethoxazoletrimethoprim (39.61%), doxycycline (28.22%), and tetracycline (27.58%). They also showed resistance to all specialist drugs used only in veterinary medicine, including enrofloxacin (24.51%), florfenicol (20.13%), ceftiofur (7.44%), and cefquinome (5.25%), and to drugs used in both veterinary and human medicine, such as ciprofloxacin (24.07%), gentamicin (19.69%), ceftriaxone (6.34%), and amoxicillin/clavulanate (4.38%). Resistance to azithromycin, which is one of the macrolides often used against gram-positive bacteria, was expressed at 16.19%. Although they are rarely used in clinical applications, resistance to polymyxin B (18.82%) and fosfomycin (12.04%) was also observed.

When antibiotic resistance was analyzed according to animal species, the resistance rates of *Salmonella* were different for the majority of the drugs tested (**Table 4**). Excluding imipenem, resistance to the other 23 drugs ranged from 1.90 to 49.52% in chickens and 0.40 to 48.18% in pigs. In comparison, *Salmonella* from dairy cows showed resistance to 12 types of drug, and resistance rates ranged from 0.95 to 10.48%.

In total, 159 strains (34.72%) exhibited varying degrees of multidrug resistance (MDR) (**Table 5**), defined as resistance to at least three different classes of antimicrobials. The *Salmonella* spp. that exhibited MDR consisted of 104 strains from pigs (including 15 and 89 strains from healthy and diseased pigs, respectively), 51 strains from healthy chickens, and 4 strains from healthy dairy cows. MDR isolates showed diverse resistance to different classes of antibiotics, but were most frequently resistant to penicillins, fluoroquinolones, and quinolones (each occurring 11 times). βlactam/β-lactamase inhibitor combinations appeared with the lowest frequency (five times) in *Salmonella* strains with MDR.

Based on analysis of MIC values and CLSI, 25 of the 457 isolates (5.47%) were confirmed as ESBL producers, with three suspected strains (**Table 6**). The ESBL-producing strains were obtained from different animals and areas as follows: two strains from chickens in Hubei, 15 strains from chickens in Henan, and eight strains from diseased pigs. Because the differences in MIC values between CAZ, CAZ/C and/or CTX, and CTX/C were not =3-fold based on CLSI, three strains from diseased pigs were suspected to be ESBL-producing strains.

The *Salmonella* serotypes of isolates differed in terms of their sensitivity to drugs (**Table 7**). Among all drug-sensitive isolates (*n* = 188), 80 isolates were identified in 17 specific serotypes. Typhimurium (*n* = 28) was the major serotype. Isolates of *Salmonella* strains with MDR showed 26 specific serotypes and the major serotypes were Enteritidis and IIIb (both *n* = 10). All serotypes were resistant to nalidixic acid, but differences were observed in the resistance profiles of *Salmonella* serotypes that exhibited MDR. The most common resistance profiles in *Salmonella* IIIb (*n* = 10) and Enteritidis isolates (*n* = 10) were AMP-AMX-SXT-NAL and SXT-OLA-MEQ-NAL, respectively. The resistance profile was AMP-AMX-TET-DOX-ENO-SXT-CHL-NAL in Typhimurium (*n* = 6), TET-DOX-CIP-ENO-SXT-CHL-FFC-NAL in Schwabach (*n* = 4), and PB-OLA-MEQ-NAL in Kouka (*n* = 4).

### **Discussion**

The prevalence of *Salmonella* spp. in the center of China were in agreement with those obtained from Sichuan province farm animals (Li et al., 2013), but differed from other areas.  Differences in isolation rates can be interpreted based on differences in region, sample types, collection seasons, culture methods, isolation methodologies, culture media, and local environmental conditions. For example, salmonellosis cases increased over the summer months, peaking in August and September, began decreasing thereafter (European Centre for Disease Prevention and Control, 2013). Therefore, a global perspective should ideally be adopted during sample collection, isolate separation, and, in particular, long-term monitoring.

The prevalence of *Salmonella* serotypes differed among animals and regions. Serogroup B and C1 were dominant, this result was consistent with in USA (Antunes et al., 2011). Serotype differ from other study. The dominant in chicken, pig, dairy cattle were Typhimurium and Enteritidis, IIIb and Typhimurium, Typhimurium and Agona in this study, respectively. The dominant serotype from chicken were Derby and Typhimurium in Sichuan province (Li et al., 2013), from pig were Enteritidis Indianain in Shandong province (Lai et al., 2014). The dominant from chicken, pig, cattle were Kentucky and Enteritidis, Adelaide and Johannesburg, Montevideo and Dublin in USA (National Antimicrobial Resistance Monitoring System, 2011); and from chicken, pig, cattle were Enteritidis and Infantis, Typhimurium and Typhimurium (monophasic), Typhimurium and Dublin in EU (European Food Safety Authority, 2014). This difference suggests serogroups and serotypes are varying according to geographical regions, and diversities and complexities. Certain serovars can emerge within a country or region for a certain period and then disappear with no evident cause or intervention.

**TABLE 3 | Susceptibility of** *Salmonella* **isolates (***n***=457) to antimicrobials.**

 *of high importance in human medicine,*

*f CLSI interpretative* *gCLSI interpretative* *hCLSI interpretative*

*cIncluding lower than this tested MIC value.*

*dCategory I: antimicrobials*

*used to treat a variety of infections, alternatives for resistance to category III antimicrobials;*

*Category IV: antimicrobials*

*eCLSI interpretative*

 *criteria for this*

 *criteria for this*

 *criteria for this*

 *criteria for this*

 *that are currently of limited use in human medicine.*

*bacterium/antimicrobial*

*bacterium/antimicrobial*

*bacterium/antimicrobial*

*bacterium/antimicrobial*

 *combination are not currently available. Reference R breakpoint of Ceftiofur.*

 *combination are not currently available. Isolates with an MIC*

 *combination are not currently available. Isolates with an MIC*

 *combination are not currently available. Isolates with an MIC*

 *of very high importance in human medicine, essential to the treatment of serious bacterial infections, no alternatives for resistant infections; Category II: antimicrobials*

 *Category III: antimicrobials*

 *of medium importance in human medicine, used as first-line drugs, alternatives for resistance are generally available;*

≥*4*μ*g/mL were reported as resistant.*

≥*16*μ*g/mL were reported as resistant.*

≥*64*μ*g/mL were reported as resistant.*

*AMP, Ampicillin; AMX, Amoxicillin; AMC, Amoxicillin-clavulanic acid; CRO, Ceftriaxone; CEF, Ceftiofur; CEQ, Cefquinome; IPM, Imipenem; ATM, Aztreonam; GEN, Gentamicin; AMK, Amikacin; TET, Tetracycline; DOX, Doxycycline; CIP, Ciprofloxacin; ENO, Enrofloxacin; LEV, Levofloxacin; NAL, Nalidixic acid; SXT, Sulfamethoxazole-trimethoprim; CHL, Chloramphenicol; FFC, Florfenicol; FOS, Fosfomycin; PB, Polymyxin B; AZM, Azithromycin; OLA, Olaquindox; MEQ, Mequindox.*

For instance, compared with data in 2010, the number of Enteritidis and Typhimurium decreased by 6% and 9% in 2011, respectively, (European Centre for Disease Prevention and Control, 2013); similar, compared with results in 2009, Enteritidis decreased, even disappeared from chicken and pig in 2012 from Shandong province (Lai et al., 2014).

The *Salmonella* serotypes isolated from farm animals overlapped with those that cause illnesses in humans, further highlighting the fact that *Salmonella* could be transmitted from animals to humans via the food chain (Alcaine et al., 2006; de Jong et al., 2009), such as Typhimurium and Enteritidis had identified from human in Henan and Hubei provinces (Cui et al., 2009; Xia et al., 2009). Some researchers have suggested that the differences in the dominant serotypes between animals and humans might be due to variations in their pathogenicity and corresponding resistance profiles (Volf et al., 2010), the strain containing Typhimurium and Enteritidis could acquired resistance to a large number of different antimicrobial compounds. At least two different serotypes existed from multiple-two strains to multiple-eleven strains, especially Enteritidis and Typhimurium, which were similar with other study from animals (Li et al., 2013; European Food Safety

**TABLE 5 | The number of multidrug-resistance** *Salmonella* **strains identified in sampled animals unit: strain.**

Authority, 2014; Lai et al., 2014), also with human (Cui et al., 2009; Xia et al., 2009). This may be related to the presence of the genetic structure known as *Salmonella* genomic island 1 (SGI1) and resistance genes (European Food Safety Authority, 2014). Therefore, monitoring of *Salmonella* should preferably focus more strongly on serovars that could, for example, be involved in a large outbreak.

Based on our MIC analysis, antibiotic-resistant bacteria, including multidrug-resistant bacteria, appeared in both healthy and diseased farm animals. These results were similar with other study (Gong et al., 2013; Li et al., 2013; Lai et al., 2014). One potential explanation is the use of antibiotics during breeding. Disease control and prevention in China during the breeding process mainly depends on the use of antibiotics (Gong et al., 2013). This arguably irrational use of antibiotics has contributed to the emergence of multidrug-resistant bacteria under selective antimicrobial pressure. Huazhong area (Henan, Hubei, and Hunan provinces) is one of the more concentrated areas of farm animals (China Agriculture Statistical Report, 2012), the demands and uses of drugs are huge, then inevitable there would be unreasonable use of drugs. These drugs, or the raw materials of the drugs, are inexpensive and easy to obtain; they have been widely used on animals in China. However, some steps have been taken to prevent the emergence of drug-resistant bacteria and promote food safety and public health with the Ministry of Agriculture of the People's Republic of China having formulated plans to ban or reduce the use of specific antimicrobials (Ministry of Agriculture of the People's Republic of China, 2002).

After the therapeutic effects of antimicrobials were confirmed in humans in the mid-1940s, they were soon introduced to veterinary medicine (McEwen, 2006). Even though some drugs were exclusively designed for veterinary use, the compounds administered are identical or very similar to those used in human medicine because they belong to the same antimicrobial classes (Heuer et al., 2009) such as β-lactams, cephalosporins, aminoglycosides, macrolides, tetracycline, sulfonamides, fluoroquinolones. Most of the antibiotic resistance to different classes has appeared in humans, animals, and/or animal

*HAUvh, Huazhong Agricultural University veterinary hospital.*

products. Ceftriaxone had showed resistance rates ≤13% and 4% from imported foods and humans (Akiyama and Khan, 2012; Wong et al., 2014). Similar, gentamicin had shown resistance in animals and humans (Lai et al., 2014; Wong et al., 2014). Overlapping resistance not only can lead to treatment failure, but also have negative consequences in both humans and animals.

ESBL-producing *Salmonella* strains were isolated from chickens and pigs in different areas in this study. Currently, the resistance genes were still on attempting to identify and sequencing from the samples. The emergence of producing-ESBLs bacteria in animals and animal products is of particular concern to public health, it allow bacteria to become resistant to a wide variety of penicillins and cephalosporins. ESBLproducing bacteria have appeared in poultry, pig, and cattle farms (Horton et al., 2011; European Food Safety Authority, 2014). In *Salmonella,* acquisition of resistance genes was likely to have occurred by conjugation, usually with other Enterobacteriaceae through the transfer of plasmids (European Food Safety Authority, 2014). Bacteria that develop resistance via ESBLs could become a reservoir of resistance genes, which may enter the food chain (European Food Safety Authority, 2012). When antibiotic resistance occurs during infection, the remaining treatment option is usually an antibiotic from the carbapenem family. While carbapenems were previously drugs of last resort, their use is now also contributing to resistance (Centers for Disease Control and Prevention, 2014). They are used to treat highly resistant infections in humans, and are not used in food-producing animals. However, carbapenemaseproducing organisms have been isolated from farm animals (Fischer et al., 2012). In China, monitoring strategies do not currently contain testing and identification of ESBL- or AmpCproducing organisms in isolates from animals and/or animalderived food products. It suggest that this should be established within surveillance procedures to anticipate possible changes in the status of ESBL enzymes.

*Salmonella* isolates showed multiple-resistance in results, it suggested the emergence of co-resistance and/or cross-resistance (Cantón and Ruiz-Garbajosa, 2011). For example, amikacin had showed low levels of resistance (0.67%); this may be due to cross-resistance among aztreonam, ciprofloxacin, and βlactams (Livermore, 2002). Co-resistance to fluoroquinolones and third- and fourth-generation cephalosporins has also been identified in *Salmonella* isolated from humans (Zhang et al., 2014). Considering these results, the prudent use of antibacterial

#### **TABLE 7 | Distribution of resistant** *Salmonella* **isolates according to serovars unit: strain.**

agents should be strongly recommended in clinical, veterinary, and agricultural settings in order to preserve antibiotic activity and avoid the development of cross-resistance.