Prevalence, genetic analysis and CRISPR typing of Cronobacter spp. isolated from meat and meat products in China

International Journal of Food Microbiology 321 (2020) 108549

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International Journal of Food Microbiology journal homepage: www.elsevier.com/locate/ijfoodmicro

Prevalence, genetic analysis and CRISPR typing of Cronobacter spp. isolated from meat and meat products in China

T

Haiyan Zenga,b,1, Chengsi Lia,b,1, Na Linga,b, Jumei Zhanga,b, Moutong Chena,b, Tao Leia,b, Shi Wua,b, Xiaojuan Yanga,b, Dandan Luoa,b, Yu Dingc, Juan Wangd, Shuhong Zhanga,b, ⁎ Qingping Wua,b, a

Guangdong Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbiology Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangzhou 510070, China c Department of Food Science &Technology, Jinan University, Guangzhou, China d College of Food Science, South China Agricultural University, Guangzhou, China b

ARTICLE INFO

ABSTRACT

Keywords: Cronobacter Prevalence Antibiotic resistance Meat and meat products Multilocus sequence typing CRISPR

Cronobacter spp. are important foodborne pathogens that infections occur in all age groups, especially cause serious life-threatening diseases in infants. This study aimed to acquire data on Cronobacter spp. contamination of meat and meat products (n = 588) in China during 2011 to 2016, and investigated the use of CRISPR typing technology as an approach for characterizing the genetics of Cronobacter spp. The overall contamination rate for Cronobacter spp. was determined to be 9.18% (54/588). Of the positive samples, 90.74% (49/54) had < 10 MPN/g, with duck samples had a relatively high contamination rate (15.69%, 8/51) and highest contamination level (28.90 MPN/g). Four species and nine serotypes were identified among 69 isolates, of which C. sakazakii was the major species (n = 50) and C. sakazakii serogroup O1 and O2 (n = 17) were the primary serotypes. The majority of Cronobacter spp. strains were found to be susceptible to most antibiotics except exhibited high resistance to cephalothin (76.81%, 53/69), and total two multi-drug resistant C. sakazakii strains were isolated from duck. The genetic diversity of Cronobacter spp. was remarkably high, as evidenced by the identification of 40 sequence types (STs) and 60 CRISPR types (CTs). C. sakazakii ST64 (n = 7) was the predominant genotype and was further divided into two sub-lineages based on CRISPR diversity, showing different antibiotic resistance profile. These results demonstrate that CRISPR typing results have a good correspondence with bacterial phenotypes, and it will be a tremendously useful approach for elucidating inter-subtyping during molecular epidemiological investigations while interpreting the divergent evolution of Cronobacter. The presence of Cronobacter spp. in meat and meat product is a potential threat to human public health.

1. Introduction Cronobacter spp. are important food-borne pathogens that are ubiquitous in food and the environment. While infections occur in all age groups, greater incidences have been reported in the very young or elderly, who are typically more immunocompromised (Fei et al., 2018; Forsythe, 2018; Lu et al., 2019; Miranda et al., 2017; Ueda, 2017).This genus comprises seven species: C. sakazakii, C. malonaticus, C. turicensis, C. universalis, C. muytjensii, C. dublinensis, and C. condimenti (Forsythe et al., 2014; Iversen and Forsythe, 2007; Joseph and Forsythe, 2012). Clinical symptoms of infection in infants include meningitis,

bacteraemia, and necrotizing enterocolitis with mortality rates of 40%–80% (Friedemann, 2009). Cronobacter spp. infecting infants are generally believed to be derived from infant milk formulas (van Acker et al., 2001), although polluted breast milk has been suspected in some cases (Bowen et al., 2017; McMullan et al., 2018; Stoll et al., 2004). Despite strides in research, the source of infections in adults is still unidentified (Joseph and Forsythe, 2012). Some research reports indicate that the principal sources of this organism might be associated with water, soil, and vegetables (Ueda, 2017; Zeng et al., 2018b). Recent studies on the molecular characterization of Cronobacter strains isolated from soil and water showed that major species and STs were

Corresponding author. E-mail address: [email protected] (Q. Wu). 1 These authors contributed equally to this work. ⁎

https://doi.org/10.1016/j.ijfoodmicro.2020.108549 Received 3 December 2019; Received in revised form 10 January 2020; Accepted 2 February 2020 Available online 04 February 2020 0168-1605/ © 2020 Elsevier B.V. All rights reserved.

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The nine-tube method was employed to calculate the most probable number (MPN). The MPN was determined on the basis of the number of positive tube(s) in each of the three sets and the MPN table (GB 4789.7–2013, National Standard of the People's Republic of China, 2013). Green or blue-green colonies in chromogenic Enterbacter sakazakii Agar Plate were considered as presumptive Cronobacter spp. and were selected for analysis using API 20E diagnostic strips (BioMérieux, Marcy-l'Étoile, France). Species identification of these isolates was conducted by fusA sequencing (Joseph and Forsythe, 2012).

different from those in food, it seemed that the environmental reservoirs could be excluded as a source of Cronobacter infection (Hu et al., 2019). Up until now, a clear understanding about the epidemiology and reservoirs of Cronobacter spp. is still lacking (Holy and Forsythe, 2014). An in-depth understanding of the genetic diversity of Cronobacter spp. can effectively promote reliable source tracking of contaminated foods and enhance the resolution of surveillance. CRISPR-Cas is an adaptive immune system that provides bacteria with sequence-specific, acquired defense against phages and plasmids (Barrangou, 2013; Westra et al., 2014). Given the temporal organization of spacers, the sequencing of CRISPR arrays is a tremendously useful tool that can be used to genotype pathogenic bacteria (Bugarel et al., 2018; Cui et al., 2008; Fricke et al., 2011; Li et al., 2014; Li et al., 2018; Li et al., 2017a; Yin et al., 2013). In our previous studies, we characterized the signature of CRISPR-Cas systems in Cronobacter and developed the CRISPR typing method for C. sakazakii, C. malonaticus, and C. dublinensis, a method that could also be used for other species of Cronobacter (Zeng et al., 2019b; Zeng et al., 2017; Zeng et al., 2018b). Multilocus sequence typing (MLST) has been proven a powerful tool to effectively identify and discriminate different Cronobacter species. The application of this tool has accelerated our understanding of the STs and outbreaks of these bacteria species (Chaves et al., 2018; Joseph and Forsythe, 2012; Joseph et al., 2012b; Zeng et al., 2018a). Compared to MLST, CRISPR typing method is superior at distinguishing similar strains, a feature that could be useful for microbial risk assessments during food processing (Zeng et al., 2019b). Previous studies have reported the contamination levels and genetic characteristics of Cronobacter in powdered infant formula (PIF), readyto-eat foods, vegetables and edible mushrooms etc. (Berthold-Pluta et al., 2017; Li et al., 2019; Ling et al., 2018; Xu et al., 2015; Zhang et al., 2017). Meat and meat products are an important reservoir for some foodborne pathogens, as supported by recent studies that reported the contamination of foodborne pathogens in this food type (Chen et al., 2019; Wu et al., 2018). However, risk assessments and investigations into the genetic characteristics of Cronobacter in meat and meat products has been limited. Although meat and meat products are not ready-to-eat foods, they can potentially cause cross-contamination of the food processing environment and other foods (Kilonzo-Nthenge et al., 2012). The global concern over food safety and control necessitates the need for substantial data regarding prevalence and characteristics of Cronobacter in meat and meat products. Therefore, this study aims to investigate the contamination levels Cronobacter spp. in meat and meat products in China while identifying the molecular features of these isolates, and introducing the CRISPR typing method as a novel approach.

2.3. PCR-based O-antigen serotyping and antimicrobial susceptibility testing Genomic DNA was extracted with the HiPure Bacterial DNA Kit (Magen Technologies, Guangzhou, China). The serotypes of Cronobacter spp. isolates were identified according to previously reported Cronobacter molecular serotyping schemes (Blazkova et al., 2015; Jarvis et al., 2011; Sun et al., 2011; Sun et al., 2012). Combined with the fusA allele and PCR-based O-antigen serotyping results, we distinguished the identical isolates from one sample. The susceptibility profiles of Cronobacter spp. isolates were determined by antimicrobial dilution and disk susceptibility testing using Mueller-Hinton agar (Huankai, Guangzhou, China), following the protocols of the Clinical and Laboratory Standards Institute (Jorgensen, 2015). Sixteen antimicrobials (AMs) (Oxoid, Hampshire, United Kingdom) recommended for Enterobacteriaceae were tested, as previously reported (Li et al., 2019). 2.4. Multi-locus sequence typing and CRISPR typing Seven housekeeping genes were exemplified for MLST analyses as previously reported (Joseph et al., 2012a). The designation of new alleles and STs was verified by Stephen J. Forsythe (https://pubmlst.org/ cronobacter/), the MLST database curator. PCR analysis was used to detect the CRISPR arrays in all of the C. sakazakii, C. malonaticus, and C. dublinensis isolates as newly reported (Zeng et al., 2019b). The CRISPR arrays of C. muytjensii isolates were amplified using the primers and PCR protocol for C. sakazakii (Zeng et al., 2019b). The extraction of CRISPR spacers were performed using CRISPRCasFinder (Couvin et al., 2018). The similarity search of the identified spacer sequences was performed by blastn tool as previously described (Zeng et al., 2017). The redundancy spacers were removed from the unique spacer library by CD-hit (Fu et al., 2012). Novel spacers were then assigned new numbers, and all the unique spacer sequences were shown in Supplemental Dataset 1. It included all unique spacers sequences of C. sakazakii, C. malonaticus, C. dublinensis and C. muytjensii strains corresponding to CRISPR1, CRISPR2, CRISPR3 and CRISPR6 arrays. CRISPR typing was performed as described in a previous study (Zeng et al., 2019b). According to the CRISPR typing nomenclature, the code of CRISPR types and the order of CRISPR array spacers were shown in Supplemental Dataset 2. The number of specific spacer sequence can be found in Supplemental Dataset 1, the number of specific CRISPR array with specific order of spacers and the final CT of isolates can be determined by searching the information in Supplemental Dataset 2.

2. Materials and methods 2.1. Sampling A total of 588 samples of meat and meat products, including pork (n = 232), Beef (n = 121), Chicken (n = 99); Bacon/Sausage (n = 63), Duck (n = 51), and Lamb (n = 22), were collected between 2011 and 2016 from traditional retail markets and supermarkets in 44 cities that are geographically spread over China. The samples were placed in sterile plastic bags, sealed, transferred under low temperature conditions (below 4 °C) to the laboratory, and analyzed immediately.

2.5. CRISPR phylogenetic analysis To depict the clustering of subtypes determined by CRISPR diversity, the binary distribution (presence as “1” or absence as “0”) of every spacer in each CRISPR locus was profiled for each strain. The binary distribution patterns of spacers from all isolates were then combined and placed into the phylogenetic tree using clustering with the unweighted pair group method with arithmetic mean (UPGMA) analysis using BioNumerics version 7.6.3 (Applied Maths, Belgium). The spacer comparison and conversions to HEX color code were performed using CRISPRStudio software (Dion et al., 2018).

2.2. Isolation and identification of Cronobacter spp. Quantitative detection was conducted by an isolation and enrichment method in according to the National Food Safety Standard of China Food microbiological examination: Enterobacter sakazakii (GB 4789.40-2010; National Standard of the People's Republic of China, 2010) for PIF, with some modifications as show in Supplemental Fig. 1. 2

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Table 1 Prevalence and contamination level of Cronobacter spp. in fresh meat & meat products. Samplea

Pork Beef Chicken Bacon/sausage Duck Lamb Total a

No. of samples

No. (%) of positive samples

232 121 99 63 51 22 588

16 10 8 12 8 0 54

6.90% 8.26% 8.08% 19.05% 15.69% 0.00% 9.18%

No. of positive samples by quantitative methods by MPN/g range MPN < 10

10 ≤ MPN < 110

MPN ≥ 110

14 10 7 12 6 0 49

0 0 0 0 0 0 0

2 0 1 0 2 0 5

Positive sample contamination level (MPN/g)

15.62 0.42 14.54 1.48 28.90 0.00 15.62

Pork includes pork, meat chop, and meat filling; beef includes beef, beef chop, and beef filling; bacon/sausage includes bacon, sausage, and preserved duck leg.

3. Results

exhibited resistance to cephalothin, trimethoprim/sulfameth-oxazole, tetracycline, chloramphenicol, and ampicillin, respectively. Seven isolates were resistant to two or more antibiotics, five of which were isolated from duck. Most notably, two C. sakazakii strains, cro586C2–1 and cro1874W, isolated from duck were all resistant to five antibiotics, including ampicillin, cephalothin, trimethoprim/sulfameth-oxazole, chloramphenicol, and tetracycline.

3.1. Presence and contamination levels of Cronobacter spp. on meat and meat products As shown in Table 1, the overall prevalence of Cronobacter spp. was determined to be 9.18% (54/588). The bacteria were detected in 12 (19.05%) bacon/sausage samples, 8 (15.69%) duck, 10 (8.26%) beef, 8 (8.08%) chicken, and 16 (6.90%) pork samples. There were no positive lamb samples. Based on the MPN analysis, the contamination level of Cronobacter spp. was < 10 MPN/g in 90.74% (49/54) of the samples, exceeding 110 MPN/g in 5 samples. Furthermore, the contamination level in the positive samples was determined to be 15.62 MPN/g. Among the positive samples, duck (28.90 MPN/g) showed the highest contamination level. Thus, the 69 Cronobacter isolates from the 54 positive samples were identified as comprised of four species (Table 2). The majority (72.46%, 50/69) of the isolates were identified as C. sakazakii, followed by C. malonaticus (24.64%, 17/69), C. muytjensii (1.45%, 1/69), and C. dublinensis (1.45%, 1/69).

3.3. MLST and CRISPR typing Fifty C. sakazakii isolates were divided into 27 STs, belonging to 13 clonal complex (CC) and 12 singletons. Among these STs, six were novel and 14 were unique to only one isolate (Table 4). ST64 was the dominant ST (n = 7), followed by ST4 (n = 4). Eleven STs belonged to 4 CCs, while 5 singletons were found in 17C. malonaticus isolates. Of this, one was a novel ST, seven were unique to only one isolate, and ST60 (n = 4) was the major ST. The C. dublinensis and C. muytjensii isolates were novel ST703 and ST705, respectively. As shown in Table 4, fifty C. sakazakii isolates were divided into 44 CTs, of which 41 were novel. Forty-two CTs were unique to only one isolate; CT137 and CT158 were the major CT (n = 3). Fourteen CTs were included in 17 C. malonaticus isolates, nine of which were novel CTs with the exception of CT3, CT11, and CT49 that were found in two isolates. Other CTs were unique to only one isolate. One C. dublinensis isolate was novel, CT32, and one C. muytjensii isolate was first assigned to CRISPR type as CT1.

3.2. Serotyping and antimicrobial susceptibility testing O-antigen serotyping according to the size of the target gene was employed to evaluate the distribution of O-antigen serotypes among the 69 Cronobacter spp. isolates. As shown in Table 2, five C. sakazakii serotypes were detected, of which O1 and O2 were the dominant serotypes (17 isolates), followed by serotype O7 (8 isolates). In addition, 17C. malonaticus isolates were classified into serotypes O1 (8 isolates), O2 (5 isolates), and O3 (4 isolates). One C. muytjensii serotype O1 isolates was identified. The 69 Cronobacter spp. isolates were subjected to 16 antimicrobial susceptibility tests (Table 3). All isolates were susceptible to cefepime, ceftriaxone, gentamicin, ciprofloxacin, imipenem, and aztreonam. The tests revealed that 76.81%, 8.70%, 8.70%, 4.35%, 2.90% of isolates

3.4. Genetic relationship among CRISPR types In order to examine the relationship of all the detected CRISPR types, we constructed the phylogenetic tree based on the spacer binary pattern of each CRISPR type (Fig. 1). Both MLST and CRISPR types showed a good correspondence with serotypes, while strains belonging to the same ST or CC are usually located on the neighbored branch, such as C. sakazakii ST4, ST73, C. malonaticus CC7, and ST60. Interesting, two small divergent phylogenetic clusters were observed in C. sakazakii ST64 strains based on the CRISPR polymorphism. Four strains in cluster a were all isolated from duck, three strains in cluster b were isolated from beef, pork and sausage, respectively. More importantly, three CT137 strains in cluster a were all resistant to trimethoprim/ sulfameth-oxazole and tetracycline, while two strains in cluster b were resistant to cephalothin. The different phenotypes of these strains supported the inter-genotype divergent evolution phenomenon inferred by CRISPR diversity. To better understand the divergent dynamics of these strains, we examined the phylogeny information conserved in the iterative spacer acquisition process (Fig. 2). All ST64 strains were found to have the same CRISPR3 pattern. Both CT137 in cluster a and CT138 in cluster b, CT141 in cluster a and CT142 in cluster b had the same

Table 2 Species and serotypes of Cronobacter spp. isolates in this study. Species

No. of isolates

Serotype

No. of isolates

C. sakazakii

50

C. malonaticus

17

C. dublinensis C. muytjensii

1 1

O1 O2 O3 O4 O7 O1 O2 O3 Uncertain O1

17 17 5 4 8 8 5 4 1 1

3

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Table 3 Antimicrobial resistance profiles of 69 Cronobacter spp. isolates. Antimicrobial group

Antibiotic

Penicillins

Ampicillin Ampicillin/sulbactam Amoxicillin/clavulanic Cefepime Ceftriaxone Cefazolin Cephalothin Gentamicin Tobramycin Amikacin Ciprofloxacin Imipenem Trimethoprim/sulfameth-oxazole Aztreonam Chloramphenicol Tetracycline

Cephalosporins

Aminoglycosides Quinolones Carbapenems Sulfonamides Monobactams Amphenicols Tetracyclines a

Disk code

AMP SAM AMC FEP CRO KZ KF CN TOB AK CIP IPM SXT ATM C TE

Antimicrobial classa according to the WHO

No. (%) of Cronobacter spp. (n = 69) Resistant

Intermediate

Susceptible

CI CI CI CI CI HI HI CI CI CI CI CI HI HI HI HI

2(2.90%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 53(76.81%) 0(0%) 0(0%) 0(0%) 0(0%) 0(0%) 6(8.70%) 0(0%) 3(4.35%) 6(8.70%)

0(0%) 2(2.90%) 1(1.45%) 0(0%) 0(0%) 18(26.09%) 10(14.49%) 0(0%) 2(2.90%) 3(4.35%) 0(0%) 0(0%) 1(1.45%) 0(0%) 0(0%) 0(0%)

67(97.10%) 67(97.10%) 68(98.53%) 69(100.00%) 69(100.00%) 51(73.91%) 6(8.70%) 69(100.00%) 67(97.10%) 66(95.65) 69(100.00%) 69(100.00%) 62(89.85%) 69(100.00%) 66(95.65%) 63(91.30%)

CI, critically important; HI, highly important; I, important.

CRISPR1 pattern, respectively. However, there was a significant difference of CRISPR2 arrays between cluster a and cluster b. Compared with CT138 in cluster b, there were 30 spacers from spacer 143 to 171 lost in all strains of cluster a. It was the main reason for the occurrence of two sub-lineages in C. sakazakii ST64 strains.

Table 4 The comparison of MLST and CRISPR types of the 69 Cronobacter isolates. Species

Clonal complex (No.)

ST (No.)

CT (No.)

C. sakazakii

CC1 CC3 CC4 CC8

1(3) 3(2) 4(4) 8 (2) 608 (1) 148(2) 21(2) 156 (1) 23(2) 37 (1) 64(7) 73(3) 219(2) 264(1) 475(1) 12(1) 145(2) 327(1) 178 (1) 405(2) 654(1) 700(3) 702(1) 706(1) 707(1) 708(1) 709(1) 7 (1) 201(1) 312(2) 211(2) 313(1) 679(1) 60(4) 286(2) 438(1) 567(1) 701(1) 703(1) 705(1)

90(1), 168(1), 169(1) 159(1), 163(1) 7(1), 8(1), 132(1) 150(1), 172(1) 149(1) 145(1), 161(1) 134(1), 135(1) 147 (1) 148(1), 104(1) 165(1) 137(3),138(2), 141(1), 142(1) 143(1), 151(1), 167(1) 160(1), 170(1) 136(1) 146(1) 140(1) 153(1), 166(1) 157(1) 76 (1) 154(1), 164(1) 162(1) 158(3) 139(1) 156(1) 144(1) 152(1) 155(1) 12(1) 11(1) 11(1), 45(1) 3(2) 48(1) 6(1) 23(1), 43(1), 44(1), 47(1) 49(2) 50(1) 51(1) 46(1) 32(1) 1(1)

(3) (2) (4) (3)

CC16 (2) CC21 (3) CC23 (2) CC37 (1) CC64 (7) CC73 (3) CC155 (2) CC264 (1) CC475 (1) Singletons (16)

C. malonaticus

CC7 (4) CC200 (2) CC300 (1) CC679 (1) Singletons (9)

C. dublinensis C. muytjensii

Singleton (1) Singleton (1)

4. Discussion In this long-term and large-scale study, 588 meat and meat product samples were analyzed. The overall prevalence of Cronobacter spp. was determined to be 9.18%. Compared with the investigations of other food types in China, the prevalence of Cronobacter spp. on meat and meat products is lower than that in ready-to-eat foods (18.6%) (Xu et al., 2015), raw vegetables (30.27%) (Ling et al., 2018), and edible mushroom (13.32%) (Li et al., 2019). Fei et al. reported that Cronobacter spp. were detected in 7 (7%, 7/100) chilled fresh pork samples (Fei et al., 2018). In this study, the prevalence of Cronobacter spp. in pork was 6.90% (16/232) which was similar to that of this historical paper. Molloy et al. detected one positive samples from five beef primal cuts and two positive samples from five pork cuts in beef and pork abattoir (Molloy et al., 2009). In retail process, they detected three positive samples from 10 beef burgers but no positive samples from 11 pork chops. For the limited number of samples, it was difficult to make a comparison with our results. Previous papers were mainly focus on the prevalence of Cronobacter spp. in powered infant milk, vegetable, fruit and ready-to-eat food etc. (Berthold-Pluta et al., 2017; Fei et al., 2015; Li et al., 2017b; Ling et al., 2018; Lu et al., 2019; McMullan et al., 2018; Pan et al., 2014; Ueda, 2017; Xu et al., 2015). The systematic investigation on the pollution of Cronobacter spp. in meat and meat products is very limited and more research in this area is needed in the future. Our present study showed that while the prevalence of Cronobacter spp. in bacon/sausage (19.05%) was highest among meat and meat products, the contamination level (1.48 MPN/g) was comparatively low. It implied that the pollution of Cronobacter spp. in bacon/ sausage maybe occurred during food transportations or sales. The second highest prevalence of Cronobacter spp. was shown in duck, which had the highest contamination level (28.90 MPN/g) compared with that of the positive samples (15.62 MPN/g) (Table 1). All these samples were collected from traditional retail markets and supermarkets in cities that are geographically spread over China. The

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Fig. 1. Phylogentic relationship of C. sakazakii and C. malonaticus CRISPR types. The genetic relationship of C. sakazakii (A) and C. malonaticus (B) were constructed using BioNumerics version 7.6.3 software based on the CRISPR spacers arrangement for each type. The CT, ST, O serotype, city, source and antibiotic profiles are listed adjacent to the corresponding strains.

probable origin of the difference in different meat and meat products were still unknown based on our existed information and it was necessary to be investigated in future studies. C. sakazakii O1 and C. sakazakii O2 were the most prevalent. These results are in agreement with previous surveys (Li et al., 2019; Li et al.,

2017b; Ling et al., 2018; Xu et al., 2015). Previous studies also reported that most Cronobacter spp. isolates are susceptible to commonly used antibiotic agents. However, some isolates from food have been reported to be resistant to more than three antibiotics, and the strains causing clinical infections were typically multi-drug resistant (Cui 5

International Journal of Food Microbiology 321 (2020) 108549

Fig. 2. CRISPR spacer arrangements of C. sakazakii ST64 strains. Color schemes were provided at the spacer level to visualize differences among isolates based on the software CRISPRStudio. Spacers are shown in the order of predicted acquisition in the locus (right, ancestral spacers; left, newly acquired spacers).

H. Zeng, et al.

et al., 2017; Li et al., 2019; Ling et al., 2018; Shi et al., 2018; Zeng et al., 2018a). In this study, the Cronobacter spp. strains were also susceptible to most antibiotics. Five out of seven (71.43%) strains were shown to be resistant to two or more antibiotics that were isolated from duck. Additionally, total two multi-drug resistant strains that were isolated from duck were shown to be resistant to five antibiotics. The identification of nine new STs and 52 new CTs in this study indicates the extremely high diversity of Cronobacter spp. in meat and meat products. Some pathogenic STs were also observed, such as C. sakazakii ST4, ST1 and ST12, and C. malonaticus ST7 etc. Indeed, our study showed that the major pathogenic Cronobacter spp. are limited to particular STs and CCs. The ubiquity of Cronobacter in the environment and in food reservoirs, coupled with the high genetic diversity, presents an important challenge for the biological control on food factory such as bacteriophage (Moye et al., 2018; Zeng et al., 2019a). The results from this study demonstrated that CRISPR typing has a higher discrimination power than MLST. Most notably, CRISPR diversity can be used to unfold a complete evolutionary story of strain divergence and relatedness, thereby showing unique advantages compared to other genotyping methods (Zeng et al., 2019b). Based on CRISPR diversity, seven C. sakazakii ST64 strains could be divided into two sub-lineages, a and b. There was a for remarkable 30 spacers loss in cluster a compared with cluster b in CRISPR2 array. Strains in cluster a were all isolated from duck and displayed an antibiotic resistance profile that was different from that of cluster b, thereby supporting the inter-genotype result of CRISPR typing. The remarkable discriminatory power of CRISPR diversity promises to be an essential tool for tracing the origin and evolution trait of Cronobacter strains. Notwithstanding, the construction of phylogenetic trees based on the binary pattern of CRISPR spacers was limited, because it does not account for some important positional and order information such as rearrangement, insertion, and repetition. This information is important for the adaptive evolutionary interpretation of pathogenic and foodborne bacteria. Developed software to streamline and standardize the visual rendition of spacer content became a useful tool that would compensate for this defect (Dion et al., 2018; Nethery and Barrangou, 2019), however, it was not convenient for big data analyses. Therefore, it would be meaningful to develop a more powerful mathematical method and software that would enable the construct of a phylogenetic tree, thereby making full use of the diversity and ordering information of CRISPR spacers. In conclusion, we reported a long-term and systematic investigation of Cronobacter contamination of meat and meat products in China, and herein present data based on the novel approach of using the CRISPR typing method for identifying sources of contamination. Our results demonstrate that the CRISPR typing method is a more powerful approach for determining inter-subtyping during molecular epidemiological investigations of Cronobacter and have a good correspondence with bacterial phenotype. Although the discriminatory power of MLST is weaker than that of CRISPR typing, the clonal complex is nonetheless useful for understanding the pathogen community. Therefore, we recommend that future studies employ a combination of MLST and CRISPR typing to investigate food contamination and infection outbreak. Based on the comparatively high prevalence, contamination level, and antibiotic resistance of Cronobacter spp. strains observed in duck, further studies are recommended to investigate the genetic characteristics and resistance profile of Cronobacter in the breeder farm environment and subsequent effects of the pathogens on humans. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ijfoodmicro.2020.108549.

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Declaration of competing interest

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