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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Microbiol.</journal-id>
<journal-title>Frontiers in Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Microbiol.</abbrev-journal-title>
<issn pub-type="epub">1664-302X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmicb.2020.554784</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Microbiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Multilocus Sequence Types and Antimicrobial Resistance of <italic>Campylobacter jejuni</italic> and <italic>C. coli</italic> Isolates of Human Patients From Beijing, China, 2017&#x2013;2018</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Zhang</surname> <given-names>Penghang</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/951352/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Zhang</surname> <given-names>Xiaoai</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/589641/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Liu</surname> <given-names>Yuzhu</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Jiang</surname> <given-names>Jinru</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Shen</surname> <given-names>Zhangqi</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/42995/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Chen</surname> <given-names>Qian</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Ma</surname> <given-names>Xiaochen</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c002"><sup>&#x002A;</sup></xref>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Beijing Center for Disease Prevention and Control, Institute for Nutrition and Food Hygiene</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Beijing Centers for Disease Preventive Medical Research</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agricultural University</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Frederique Pasquali, University of Bologna, Italy</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Yosra A. Helmy, The Ohio State University, United States; Marja-Liisa H&#x00E4;nninen, University of Helsinki, Finland</p></fn>
<corresp id="c001">&#x002A;Correspondence: Qian Chen, <email>cchenqian@263.net</email></corresp>
<corresp id="c002">Xiaochen Ma, <email>xiaoch-ma@126.com</email></corresp>
<fn fn-type="other" id="fn004"><p>This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>19</day>
<month>10</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="collection">
<year>2020</year>
</pub-date>
<volume>11</volume>
<elocation-id>554784</elocation-id>
<history>
<date date-type="received">
<day>23</day>
<month>04</month>
<year>2020</year>
</date>
<date date-type="accepted">
<day>22</day>
<month>09</month>
<year>2020</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2020 Zhang, Zhang, Liu, Jiang, Shen, Chen and Ma.</copyright-statement>
<copyright-year>2020</copyright-year>
<copyright-holder>Zhang, Zhang, Liu, Jiang, Shen, Chen and Ma</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>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) and the copyright owner(s) 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.</p></license>
</permissions>
<abstract>
<p><italic>Campylobacter</italic> species are zoonotic pathogens and the leading cause of bacterial enteritis worldwide. With the increase of antimicrobial resistance to fluoroquinolones and macrolides, they have been identified by the World Health Organization (WHO) as high-priority antimicrobial-resistant pathogens. There is currently little known about the prevalence and antimicrobial resistance characteristics of <italic>Campylobacter</italic> species in Beijing. In this study, we performed a 2-year surveillance of <italic>Campylobacter</italic> in Beijing, China. We used multilocus sequence typing (MLST) and antimicrobial susceptibility testing to analyze 236 <italic>Campylobacter</italic> isolates recovered from 230 clinical infectious cases in Beijing between 2017 and 2018. The <italic>Campylobacter</italic> isolation rate in diarrhea patients was 7.81%, with higher isolation rates in male patients than female patients and in autumn compared with other seasons. We identified 125 sequence types (STs) of 23 cloning complexes (CCs) among the 236 isolates, including four new alleles and 19 new STs. The most commonly isolated STs of <italic>Campylobacter jejuni</italic> were ST-22 and ST-760 (4.50%), and the most commonly isolated ST of <italic>Campylobacter coli</italic> was ST-9227 (16.67%). We also compared our isolates with clinical <italic>Campylobacter</italic> isolates from other countries in Asia, CC-353 of <italic>Campylobacter coli</italic> was found in eight countries, CC-1034 and CC-1287 of <italic>Campylobacter coli</italic> were found only in China. All <italic>C. jejuni</italic> isolates were resistant to at least one antimicrobial. <italic>C. jejuni</italic> showed the highest rate of resistance toward ciprofloxacin (94.50%), followed by tetracycline (93.50%), and nalidixic acid (92.00%), while <italic>C. coli</italic> showed highest resistance toward ciprofloxacin (94.44%) and tetracycline (94.44%) followed by nalidixic acid (88.89%). The most commonly observed MDR combination of <italic>C. jejuni</italic> were quinolone, phenicol and tetracycline (11.50%), while the most commonly observed MDR combination of <italic>C. coli</italic> were macrolide, quinolone, phenicol, tetracycline and lincosamide (30.56%). Surveillance of molecular characterization will provide important information for prevention of <italic>Campylobacter</italic> infection. This study enhances insight into <italic>Campylobacter</italic> infections in diarrheal patients, with relevance for treatment regimens in Beijing.</p>
</abstract>
<kwd-group>
<kwd><italic>Campylobacter</italic> spp.</kwd>
<kwd>human</kwd>
<kwd>MLST</kwd>
<kwd>antimicrobial susceptibility</kwd>
<kwd>China</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="57"/>
<page-count count="12"/>
<word-count count="0"/>
</counts>
</article-meta>
</front>
<body>
<sec id="S1">
<title>Introduction</title>
<p><italic>Campylobacter</italic> species are responsible for the greatest number of bacterial-mediated diarrhea outbreaks in the world (<xref ref-type="bibr" rid="B45">World Health Organization, 2013</xref>), with the thermophilic <italic>Campylobacter jejuni</italic> and <italic>Campylobacter coli</italic> being the most common pathogens. The European Food Safety Agency (EFSA) reports that <italic>C. jejuni</italic> has caused the most cases of bacterial foodborne diseases in the European Union for many years (<xref ref-type="bibr" rid="B13">European Food Safety Agency and European centre for Disease Prevention and Control, 2015</xref>). According to statistics on the number of foodborne pathogenic microorganisms in the United States by the United States Centers for Disease Control and Prevention (USA-CDC) in 2016, the number of cases caused by <italic>C. jej</italic>uni ranked highest (<xref ref-type="bibr" rid="B3">Centers for Disease Control and Prevention [CDC], 2017</xref>). In addition, <italic>Campylobacter</italic> infection can lead to extraintestinal complications and campylobacteriosis such as Guillain Barr&#x00E9; syndrome, reactive arthritis, and irritable bowel syndrome (<xref ref-type="bibr" rid="B25">Nachamkin et al., 1998</xref>; <xref ref-type="bibr" rid="B57">Zia et al., 2003</xref>; <xref ref-type="bibr" rid="B6">Connor, 2005</xref>). An outbreak of <italic>C. jejuni</italic> resulted in 32 Guillain Barr&#x00E9; syndrome patients in Shuangyang District, Changchun City, Jilin Province, China, during 2007 (<xref ref-type="bibr" rid="B52">Zhang et al., 2010b</xref>).</p>
<p><italic>Campylobacter</italic> can colonize poultry, swine, and ruminants (<xref ref-type="bibr" rid="B14">Gallay et al., 2007</xref>; <xref ref-type="bibr" rid="B11">Elhadidy et al., 2018</xref>); therefore, people are easily infected when handling and consuming raw and semi-raw contaminated foods, as well as contaminated water (<xref ref-type="bibr" rid="B19">Klein-J&#x00F6;bstl et al., 2016</xref>; <xref ref-type="bibr" rid="B20">Kovanen et al., 2016</xref>). Most <italic>Campylobacter</italic> infections are mild, self-limiting, and resolve within a few days. However, effective antimicrobial treatment is essential for people with severe or prolonged <italic>Campylobacter</italic> infections, and the elderly, young, or immunocompromised patients (<xref ref-type="bibr" rid="B34">Reddy and Zishiri, 2017</xref>). Clinical treatment of gastroenteritis caused by <italic>Campylobacter</italic> is usually performed with macrolides and fluoroquinolones; however, occasionally, severe systemic infection requires the use of aminoglycoside antimicrobials, such as gentamicin (<xref ref-type="bibr" rid="B2">Blaser and Engberg, 2008</xref>; <xref ref-type="bibr" rid="B30">Pernica et al., 2016</xref>). <italic>Campylobacter</italic> isolates from both developed and developing countries show resistance to several antimicrobials, including aminoglycosides, fluoroquinolones, macrolides, and tetracyclines (<xref ref-type="bibr" rid="B28">Padungton and Kaneene, 2003</xref>; <xref ref-type="bibr" rid="B36">Ruiz-Palacios, 2007</xref>; <xref ref-type="bibr" rid="B15">Ge et al., 2013</xref>; <xref ref-type="bibr" rid="B1">Abdi-Hachesoo et al., 2014</xref>; <xref ref-type="bibr" rid="B38">Shobo et al., 2016</xref>; <xref ref-type="bibr" rid="B34">Reddy and Zishiri, 2017</xref>), which led the World Health Organization in 2017 to list <italic>Campylobacter</italic> spp. as one of the six high-priority antimicrobial-resistant pathogens (<xref ref-type="bibr" rid="B46">World Health Organization, 2017</xref>). Therefore, identifying the molecular characteristics of resistant isolates and estimating their frequency in different populations is important for disease prevention aimed at controlling the emergence of resistant isolates and detecting resistant infections rapidly.</p>
<p>Molecular typing of bacteria plays an important role in the epidemiological investigation of pathogen transmission pathways by identifying outbreaks and diseases (<xref ref-type="bibr" rid="B26">O&#x2019;Mahony et al., 2011</xref>). However, only a few studies have investigated the isolation rate and molecular characterization of clinical <italic>Campylobacter</italic> spp. in China (<xref ref-type="bibr" rid="B51">Zhang et al., 2010a</xref>, <xref ref-type="bibr" rid="B53">2014</xref>; <xref ref-type="bibr" rid="B44">Wei et al., 2015</xref>; <xref ref-type="bibr" rid="B29">Pan et al., 2016</xref>; <xref ref-type="bibr" rid="B18">Ju et al., 2018</xref>). To understand the genotypes and antimicrobial resistance of clinical <italic>Campylobacter</italic> isolates in Beijing, we combined antimicrobial susceptibility tests and molecular subtyping analysis with epidemiological information.</p>
</sec>
<sec id="S2" sec-type="materials|methods">
<title>Materials and Methods</title>
<sec id="S2.SS1">
<title>Study Population and <italic>Campylobacter</italic> Isolation</title>
<p>From 2017 to 2018, <italic>Campylobacter</italic> isolates were obtained from 2,945 patients with acute diarrhea in 14 hospitals in pilot areas (Xicheng, Fengtai, Shunyi, Fangshan, Yanqing, and Mentougou Districts) of a <italic>Campylobacter</italic> surveillance program in Beijing. Patients were defined as having &#x2265;3 watery, loose, mucosal, or bloody stools over a 24-h period. Five milligrams of fresh stool sample was collected from each of the diarrheal patients. The samples were maintained in Cary-Blair medium (Oxoid CM0935), at 4&#x00B0;C and transported to the laboratory for bacterial isolation within 24 h. A <italic>Campylobacter</italic> isolation kit incorporating a membrane filter method (ZC-CAMPY-002, Qingdao Sinova Biotechnology Co., Ltd., Qingdao, China) was used to isolate <italic>Campylobacter</italic>. Briefly, 1 mL of fecal specimen suspension was transferred to 4 mL of enrichment medium provided in the kit. The main component of the enrichment medium was a modified Preston broth. The enrichment medium was then cultured at 42&#x00B0;C for 48 h in a microaerobic atmosphere (5% O<sub>2</sub>, 10% CO<sub>2</sub>, and 85% N<sub>2</sub>). Approximately 300 &#x03BC;L of enrichment medium was spotted on the membrane filter (Type: 0.45 &#x03BC;m) surface of the kit and spread onto Karmali and Columbia agar plates. Five (if less than 5, pick all) or more colonies resembling <italic>Campylobacter</italic> were picked after 48 h of incubation at 42&#x00B0;C in a microaerobic atmosphere. All isolates were firstly identified using matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry (Bruker, Leipzig, Germany) and further checked by PCR, according to a previously described method (<xref ref-type="bibr" rid="B41">Wang et al., 2002</xref>).</p>
</sec>
<sec id="S2.SS2">
<title>Epidemiological Data</title>
<p>Demographic and epidemiological data were managed using WPS Office (Kingsoft, China). All patients were residents of Beijing. Patients were divided according to age into child patients (&#x2264;5 years old), adolescent patients (6&#x2013;17 years old), adult patients (18&#x2013;64 years old), and elderly patients (&#x2265;65 years old). Seasons were classified according to the onset date of symptoms: spring (March, April, May), summer (June, July, August), autumn (September, October, November), and winter (December, January, February).</p>
</sec>
<sec id="S2.SS3">
<title>Multilocus Sequence Typing</title>
<p>MLST was performed by sequencing seven housekeeping loci (aspA, glnA, gltA, glyA, pgm, tkt, and uncA) according to a previously described method (<xref ref-type="bibr" rid="B8">Dingle et al., 2001</xref>). Briefly, genomic DNA was extracted using a commercial kit (QIAamp DNA mini kit, Germany). Amplification reactions were performed in a 20 &#x03BC;L mixture containing 10 &#x03BC;L of 2 &#x00D7; PCR master (Sangon Biotec., Shanghai, China), 0.5 &#x03BC;L of forward and reverse primer, 1 &#x03BC;L of DNA template, and 7.5 &#x03BC;L of pure water. PCR was performed as 1 cycle of 5 min at 94&#x00B0;C; 35 cycles of 1 min at 94&#x00B0;C, 2 min at 50&#x00B0;C, and 1 min at 72&#x00B0;C; and a final extension of 5 min at 72&#x00B0;C. After amplification, 2 &#x03BC;L of the PCR product was subjected to electrophoresis through a 1.5% agarose gel. The PCR products were then purified and sequenced (3730xl DNA Analyzer, Applied Biosystems, United States). The alleles of each gene were determined from a comparison of seven alleles in the MLST database<sup><xref ref-type="fn" rid="footnote1">1</xref></sup>. For each isolate, the number of alleles was assigned and sequence types (STs) and cloning complexes (CCs) were determined. New alleles and STs were submitted to the PubMLST database. A minimum spanning tree (MST) and dendrogram of MLST data was created using BioNumerics v.7.6 (bioM&#x00E9;rieux, Marcy-l&#x2019;&#x00C9;toile, France).</p>
</sec>
<sec id="S2.SS4">
<title>Antimicrobial Susceptibility Testing</title>
<p>The minimum inhibitory concentration (MIC) of all <italic>C. jejuni</italic> isolates was determined according to the agar dilution method recommended by CLSI using a commercial kit (Zhongchuang Biotechnology Ltd. Corp., Qingdao, China). Six classes of antimicribials were chosen for this study: macrolides, fluoroquinolones, aminoglycosides, chloramphenicols, tetracyclines, and lincosamides. The breakpoints for resistance used in this study were based on standards used in the National Antimicrobial Resistance Monitoring System (NARMS, Page last reviewed: March 15, 2019). The following MIC values were determined for C. jejuni: erythromycin (&#x2265;8 &#x03BC;g mL<sup>&#x2013;1</sup>), azithromycin (&#x2265;0.5 &#x03BC;g mL<sup>&#x2013;1</sup>), nalidixic acid (&#x2265;32 &#x03BC;g mL<sup>&#x2013;1</sup>), ciprofloxacin (&#x2265;1 &#x03BC;g mL<sup>&#x2013;1</sup>), gentamicin (&#x2265;4 &#x03BC;g mL<sup>&#x2013;1</sup>), streptomycin (&#x2265;16 &#x03BC;g mL<sup>&#x2013;1</sup>), chloramphenicol (&#x2265;32 &#x03BC;g mL<sup>&#x2013;1</sup>), florfenicol (&#x2265;8 &#x03BC;g mL<sup>&#x2013;1</sup>), tetracycline (&#x2265;2 &#x03BC;g mL<sup>&#x2013;1</sup>), telithromycin (&#x2265;8 &#x03BC;g mL<sup>&#x2013;1</sup>), and clindamycin (&#x2265;1 &#x03BC;g mL<sup>&#x2013;1</sup>). MIC values for C. coli were as follows: erythromycin (&#x2265;16 &#x03BC;g mL<sup>&#x2013;1</sup>), azithromycin (&#x2265;1 &#x03BC;g mL<sup>&#x2013;1</sup>), nalidixic acid (&#x2265;32 &#x03BC;g mL<sup>&#x2013;1</sup>), ciprofloxacin (&#x2265;1 &#x03BC;g mL<sup>&#x2013;1</sup>), gentamicin (&#x2265;4 &#x03BC;g mL<sup>&#x2013;1</sup>), streptomycin (&#x2265;16 &#x03BC;g mL<sup>&#x2013;1</sup>), chloramphenicol (&#x2265;32 &#x03BC;g mL<sup>&#x2013;1</sup>), florfenicol (&#x2265;8 &#x03BC;g mL<sup>&#x2013;1</sup>), tetracycline (&#x2265;4 &#x03BC;g mL<sup>&#x2013;1</sup>), telithromycin (&#x2265;8 &#x03BC;g mL<sup>&#x2013;1</sup>), and clindamycin (&#x2265;2 &#x03BC;g mL<sup>&#x2013;1</sup>). Multi-drug resistance (MDR) was defined as resistance to three or more classes of antimicrobials in this study. <italic>C. jejuni</italic> ATCC 33560 was used as a control.</p>
</sec>
<sec id="S2.SS5">
<title>Statistical Analysis</title>
<p>SPSS software, version 20.0 (SPSS, Inc.) was used to analyze any significant statistical differences in the results. Differences in the frequencies of <italic>Campylobacter</italic> isolation rate across STs, CCs, and MDR isolates, and other variables, including epidemiological data, were examined using &#x03C7;<sup>2</sup> and Fisher&#x2019;s exact tests for dichotomous variables; <italic>p</italic> &#x003C; 0.05 was considered significant.</p>
</sec>
</sec>
<sec id="S3">
<title>Results</title>
<sec id="S3.SS1">
<title>Description of <italic>Campylobacter</italic> Cases Identified and Prevalence of <italic>Campylobacter</italic> spp. in Beijing</title>
<p>We collected 2,945 stool samples from individual diarrhea patients in 14 hospitals in Beijing during 2017 and 2018; 236 <italic>Campylobacter</italic> isolates were recovered, comprising 200 isolates of <italic>C. jejuni</italic> (84.75%, 200/236) and 36 isolates of <italic>C. coli</italic> (15.25%, 36/236). There were 230 positive cases of <italic>Campylobacter</italic> infection, including five cases with co-infections. Among these, three cases were co-infected with <italic>C. jejuni</italic> and <italic>C. coli</italic>, one case was co-infected with two <italic>C. jejuni</italic> isolates, and one case was co-infected with two <italic>C. jejuni</italic> isolates and one <italic>C. coli</italic> isolate.</p>
<p>The isolation rate of <italic>Campylobacter</italic> in diarrhea patients was 7.81% (230/2945). Of these patients, 148 were male (64.35%) while 82 were female (35.65%). Patients ranged in age from 3 to 91 years old. <italic>Campylobacter</italic> isolation rate was higher in autumn than in other seasons (spring, &#x03C7;<sup>2</sup> = 3.4909, <italic>P</italic> &#x003C; 0.0682; summer, &#x03C7;<sup>2</sup> = 6.8528, <italic>P</italic> &#x003C; 0.0105; winter, &#x03C7;<sup>2</sup> = 6.7567, <italic>P</italic> &#x003C; 0.0130), and higher in male than in female (&#x03C7;<sup>2</sup> = 8.6054, <italic>P</italic> &#x003C; 0.0037) (<xref ref-type="table" rid="T1">Table 1</xref>). No statistically significant difference was found in the <italic>Campylobacter</italic> isolation rate between the child and other age groups (adolescent, &#x03C7;<sup>2</sup> = 0.9406, <italic>P</italic> &#x003C; 0.3321; adult, &#x03C7;<sup>2</sup> = 0.3216, <italic>P</italic> &#x003C; 0.5707; elderly, &#x03C7;<sup>2</sup> = 0.0012, <italic>P</italic> &#x003C; 0.9719).</p>
<table-wrap position="float" id="T1">
<label>TABLE 1</label>
<caption><p>Description of the patients (230, total number of studied 2,945) included in this study.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left">Epidemiological data</td>
<td valign="top" align="left">No. of cases (%)</td>
<td valign="top" align="left">No. of patients (percentage of isolation rate)</td>
<td valign="top" align="center">&#x03C7;<sup>2</sup></td>
<td valign="top" align="center">P</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><bold>Sex</bold></td>
<td/>
<td/>
<td valign="top" align="center">8.6054</td>
<td valign="top" align="center">0.0037</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">148 (64.35%)</td>
<td valign="top" align="center">148/1623 (9.12%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">82 (35.65%)</td>
<td valign="top" align="center">82/1322 (6.20%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>Age group</bold></td>
<td/>
<td/>
<td valign="top" align="center">6.1753</td>
<td valign="top" align="center">0.0983</td>
</tr>
<tr>
<td valign="top" align="left">Child</td>
<td valign="top" align="center">1 (0.43%)</td>
<td valign="top" align="center">1/29 (3.45%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Adolescent</td>
<td valign="top" align="center">12 (5.22%)</td>
<td valign="top" align="center">12/102 (11.76%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Adult</td>
<td valign="top" align="center">196 (85.22%)</td>
<td valign="top" align="center">196/2429 (8.07%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Elderly</td>
<td valign="top" align="center">21 (9.13%)</td>
<td valign="top" align="center">21/385 (5.45%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>Season</bold></td>
<td/>
<td/>
<td valign="top" align="center">11.0292</td>
<td valign="top" align="center">0.0116</td>
</tr>
<tr>
<td valign="top" align="left">Spring</td>
<td valign="top" align="center">51 (22.17%)</td>
<td valign="top" align="center">51/682 (7.48%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Summer</td>
<td valign="top" align="center">86 (37.39%)</td>
<td valign="top" align="center">86/1231 (6.99%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Autumn</td>
<td valign="top" align="center">82 (35.65%)</td>
<td valign="top" align="center">82/799 (10.26%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Winter</td>
<td valign="top" align="center">11 (4.78%)</td>
<td valign="top" align="center">11/233 (4.72%)</td>
<td/>
<td/>
</tr>
</tbody>
</table></table-wrap>
</sec>
<sec id="S3.SS2">
<title>Multilocus Sequence Typing</title>
<p>We identified 125 STs of 23 CCs among the 236 isolates, including four new alleles and 19 new STs. The new STs are shown in <xref ref-type="supplementary-material" rid="TS1">Supplementary Table S1</xref>. Thirty STs from 53 isolates did not belong to any known clonal complex. Among the 200 isolates of <italic>C. jejuni</italic>, we recovered 103 STs. The most commonly isolated STs were ST-22 and ST-760 (9/200, 4.50%), followed by ST-6500 (7/200, 3.50%), and ST-653 (6/200, 3.00%); 59 STs had only one isolate (<xref ref-type="fig" rid="F1">Figure 1</xref>). The most commonly isolated CC was CC-21 (42/200, 21.00%). Among 36 isolates of <italic>C. coli</italic>, we recovered 22 STs. The most commonly isolated was ST-9227 (6/36, 16.67%). CC-828 was the only CC found in <italic>C. coli</italic> (30/36, 83.33%), and six isolates did not belong to any known CC (<xref ref-type="fig" rid="F2">Figure 2</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption><p>Phylogenetic analysis. Minimum spanning tree (MST) of MLST data of 200 <italic>C. jejuni</italic> human isolates collected in 2017 and 2018 in Beijing, China. Each color represents one clonal complex (CC). Isolates are represented by circles, and the size of the circle is proportional to the number of isolates. Branches and numbers represent allelic differences between isolates.</p></caption>
<graphic xlink:href="fmicb-11-554784-g001.tif"/>
</fig>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption><p>Phylogenetic analysis. Minimum spanning tree (MST) of MLST data of 36 <italic>C. coli</italic> human isolates collected in 2017 and 2018 in Beijing, China. Green represents the ST-828 complex and red represents isolates that do not belong to any known clonal complex. Isolates are represented by circles, and the size of the circle is proportional to the number of isolates. Branches and numbers represent allelic differences between isolates.</p></caption>
<graphic xlink:href="fmicb-11-554784-g002.tif"/>
</fig>
</sec>
<sec id="S3.SS3">
<title>Comparison of Isolates From This Study With Those From Other Districts in China</title>
<p>We compared the distribution of <italic>Campylobacter</italic> isolates from diarrhea patients from Beijing with those from patients from other districts in China using MLST allelic profiles available from previous reports (<xref ref-type="bibr" rid="B51">Zhang et al., 2010a</xref>, <xref ref-type="bibr" rid="B53">2014</xref>, <xref ref-type="bibr" rid="B50">2015</xref>; <xref ref-type="bibr" rid="B44">Wei et al., 2015</xref>; <xref ref-type="bibr" rid="B29">Pan et al., 2016</xref>; <xref ref-type="bibr" rid="B18">Ju et al., 2018</xref>). We constructed dendrograms for <italic>C. jejuni</italic> (<xref ref-type="fig" rid="F3">Figure 3</xref>) and <italic>C. coli</italic> (<xref ref-type="fig" rid="F4">Figure 4</xref>) isolates. In total, 187 STs were recovered from 376 isolates of <italic>C. jejuni</italic>. There were no obvious regional characteristics for these STs: ST-5 (<italic>n</italic> = 6) was recovered from four districts while ST-22 (<italic>n</italic> = 14, most common), ST-51 (<italic>n</italic> = 8), ST-2328 (<italic>n</italic> = 7), ST-354 (<italic>n</italic> = 6), ST-2274 (<italic>n</italic> = 6), ST-1811 (<italic>n</italic> = 4), and ST-2132 (<italic>n</italic> = 4) were recovered from three districts of China. A total of 47 STs were recovered from 114 isolates of <italic>C. coli</italic>. Among these, nine STs were found in both Beijing and Shanghai City. CC-21 (57/376, 15.16%) and CC-828 (95/114, 83.33%) were the most commonly isolated CCs for <italic>C. jejuni</italic> and <italic>C. coli</italic>, respectively.</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption><p>Dendrogram of MLST data of C. <italic>jejuni</italic> human isolates collected from this study and other district of China, Showed the number of differences in MLST alleles. The similarity coefficient were calculated using the categorical (difference) and complete linkage for the cluster analysis.</p></caption>
<graphic xlink:href="fmicb-11-554784-g003.tif"/>
</fig>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption><p>Dendrogram of MLST data of <italic>C. coli</italic> human isolates collected from this study and other district of China, showed the number of differences in MLST alleles. The similarity coefficient were calculated using the categorical (difference) and complete linkage for the cluster analysis.</p></caption>
<graphic xlink:href="fmicb-11-554784-g004.tif"/>
</fig>
</sec>
<sec id="S3.SS4">
<title>Comparison of Isolates With Those From Other Countries in Asia</title>
<p>We compared our isolates with clinical <italic>Campylobacter</italic> isolates from other countries in Asia by selecting 1,454 <italic>Campylobacter</italic> isolates from patients with diarrhea from the PubMLST database (see text footnote 1) on January 18, 2019: 1336 <italic>C. jejuni</italic> and 118 <italic>C. coli</italic> isolates. The 1,536 human <italic>C. jejuni</italic> isolates were divided into 631 STs and 30 CCs, with 22 of these CCs found in this study. The most prevalent CCs were CC-21 (259/1536, 16.86%), CC-52 (105/1536, 6.84%), CC-353 (104/1536, 6.77%), CC-354 (102/1536, 6.64%), CC-574 (100/1536, 6.51%), CC-464 (67/1536, 4.36%), CC-257 (53/1536, 3.45%), and CC-22 (53/1536, 3.45%). CC-353 was found in eight countries, CC-21, CC-443 (41/1536, 2.67%), CC-45 (37/1536, 2.41%), and CC-574 were found in seven countries, and CC-206 (45/1536, 2.93%) and CC-257 were found in six countries. CC-1034 and CC-1287 were found only in China, CC-692 and CC-177 were found only in Thailand, and CC-41 and CC-446 were found only in Bangladesh and Israel, respectively (<xref ref-type="fig" rid="F5">Figure 5</xref>). The 154 human <italic>C. coli</italic> isolates were divided into 95 STs and 2 CCs. One hundred and thirty-one isolates belonged to CC-828, 3 isolates from different countries belonged to CC-1150, and the remaining isolates did not belong to any known CC (<xref ref-type="fig" rid="F6">Figure 6</xref>).</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption><p>Genetic relationships among the 200 clinical isolates <italic>C. jejuni</italic> in this study and 1,336 isolates <italic>C. jejuni</italic> from Asia in the pubmlst database (Data taken time: January 18, 2019). A minimum spanning tree was reconstructed based on CCs from this study and the MLST database. The size of circles is proportional to the number of isolates, and the sources of the isolates are colored as indicated. Shadow zones in different colors represent different clonal complexes.</p></caption>
<graphic xlink:href="fmicb-11-554784-g005.tif"/>
</fig>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption><p>Genetic relationships among the 36 clinical isolates <italic>C. coli</italic> in this study and 118 isolates <italic>C. coli</italic> from Asia in the pubmlst database (Data taken time: January 18, 2019). A minimum spanning tree was reconstructed based on CCs from this study and the MLST database. The size of circles is proportional to the number of isolates, and the sources of isolates are colored as indicated. Shadow zones in different color represent different clonal complexes.</p></caption>
<graphic xlink:href="fmicb-11-554784-g006.tif"/>
</fig>
</sec>
<sec id="S3.SS5">
<title>Antibacterial Susceptibility Testing</title>
<p>The MICs of the quality control isolate (<italic>C. jejuni</italic> ATCC 33560) were within the reference quality control range. No <italic>C. jejuni</italic> isolate was susceptible to all 11 antimicrobials tested; however, 179 <italic>C. jejuni</italic> isolates (89.50%) were resistant to three or more antimicrobials and two isolates were susceptible to only one antimicrobial (erythromycin and gentamicin, respectively). <italic>C. jejuni</italic> showed highest resistance to ciprofloxacin (94.50%), followed by tetracycline (93.50%), and nalidixic acid (92.00%) (<xref ref-type="table" rid="T2">Table 2</xref>). The most prevalent resistance pattern was a combination of nalidixic acid, ciprofloxacin, and tetracycline (33.33%) (<xref ref-type="supplementary-material" rid="FS1">Supplementary Figure S1</xref>). <italic>C. coli</italic> showed highest resistance to ciprofloxacin (94.44%) and tetracycline (94.44%), followed by nalidixic acid (88.89%). Thirty-five <italic>C. coli</italic> isolates (97.22%) were resistant to three or more antimicrobials, three isolates were resistant to all antimicrobials tested except chloramphenicol, and nine isolates were resistant to all antimicrobials except chloramphenicol and flofenicol; this was the most common resistance pattern. No <italic>C. coli</italic> isolates were resistant to chloramphenicol and one isolate was susceptible to all 11 antimicrobials (<xref ref-type="supplementary-material" rid="FS2">Supplementary Figure S2</xref>).</p>
<table-wrap position="float" id="T2">
<label>TABLE 2</label>
<caption><p>Resistance rates (percentages) and minimum inhibitory concentrations (MICs) of human <italic>Campylobacter</italic> spp. isolates in Beijng.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left"><italic>Campylobacter</italic> spp.</td>
<td valign="top" align="center">Antibiotic</td>
<td valign="top" align="center">Resistance rate (%)</td>
<td valign="top" align="center" colspan="3">MIC (&#x03BC;g/mL)</td>
</tr>
<tr>
<td valign="top" align="center"></td>
<td valign="top" align="center"></td>
<td valign="top" align="center"></td>
<td valign="top" align="center" colspan="3"><hr/></td>
</tr>
<tr>
<td/>
<td/>
<td/>
<td valign="top" align="center">Range</td>
<td valign="top" align="center">MIC<sub>50</sub></td>
<td valign="top" align="center">MIC<sub>90</sub></td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><italic>C. jejuni</italic> (<italic>n</italic> = 200)</td>
<td valign="top" align="center">Erythromycin</td>
<td valign="top" align="center">9.00</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">&#x003C;0.5</td>
<td valign="top" align="center">4</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Azithromycin</td>
<td valign="top" align="center">13.00</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">&#x003C;0.5</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Nalidixic acid</td>
<td valign="top" align="center">92.00</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">32</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Ciprofloxacin</td>
<td valign="top" align="center">94.50</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">32</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Gentamicin</td>
<td valign="top" align="center">13.00</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">&#x003C;0.5</td>
<td valign="top" align="center">64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Streptomycin</td>
<td valign="top" align="center">9.50</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">4</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Chloramphenicol</td>
<td valign="top" align="center">12.00</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">32</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Florfenicol</td>
<td valign="top" align="center">35.00</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">16</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Tetracycline</td>
<td valign="top" align="center">93.50</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">&#x003E;64</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Telithromycin</td>
<td valign="top" align="center">12.00</td>
<td valign="top" align="center">&#x003C;0.25&#x2013;&#x003E;32</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">8</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Clindamycin</td>
<td valign="top" align="center">33.50</td>
<td valign="top" align="center">&#x003C;0.25&#x2013;&#x003E;32</td>
<td valign="top" align="center">0.5</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left"><italic>C. coli</italic> (<italic>n</italic> = 36)</td>
<td valign="top" align="center">Erythromycin</td>
<td valign="top" align="center">44.44</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Azithromycin</td>
<td valign="top" align="center">44.44</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">&#x003C;0.5</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Nalidixic acid</td>
<td valign="top" align="center">88.89</td>
<td valign="top" align="center">4&#x2013;&#x003E;64</td>
<td valign="top" align="center">&#x003E;64</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Ciprofloxacin</td>
<td valign="top" align="center">94.44</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Gentamicin</td>
<td valign="top" align="center">50.00</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Streptomycin</td>
<td valign="top" align="center">72.22</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;&#x003E;64</td>
<td valign="top" align="center">64</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Chloramphenicol</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">1&#x2013;16</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">16</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Florfenicol</td>
<td valign="top" align="center">16.67</td>
<td valign="top" align="center">&#x003C;0.5&#x2013;16</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">8</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Tetracycline</td>
<td valign="top" align="center">94.44</td>
<td valign="top" align="center">1&#x2013;&#x003E;64</td>
<td valign="top" align="center">&#x003E;64</td>
<td valign="top" align="center">&#x003E;64</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Telithromycin</td>
<td valign="top" align="center">63.89</td>
<td valign="top" align="center">&#x003C;0.25&#x2013;&#x003E;32</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">&#x003E;32</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Clindamycin</td>
<td valign="top" align="center">44.44</td>
<td valign="top" align="center">&#x003C;0.25&#x2013;&#x003E;32</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">&#x003E;32</td>
</tr>
</tbody>
</table></table-wrap>
<p>The MIC<sub>50</sub> and MIC<sub>90</sub> values for <italic>Campylobacter</italic> are shown in <xref ref-type="table" rid="T2">Table 2</xref>. Statistical differences for antibacterial susceptibility between different antimicrobials are shown in <xref ref-type="supplementary-material" rid="TS2">Supplementary Table S2</xref>. Statistically, <italic>C. jejuni</italic> exhibited lower resistance rates to erythromycin (&#x03C7;<sup>2</sup> = 31.0821, <italic>P</italic> &#x003C; 0.0001), azithromycin (&#x03C7;<sup>2</sup> = 20.6197, <italic>P</italic> &#x003C; 0.0001), gentamicin (&#x03C7;<sup>2</sup> = 27.5356, <italic>P</italic> &#x003C; 0.0001), streptomycin (&#x03C7;<sup>2</sup> = 77.7753, <italic>P</italic> &#x003C; 0.0001), and telithromycin (&#x03C7;<sup>2</sup> = 51.5031, <italic>P</italic> &#x003C; 0.0001) than <italic>C. coli</italic>, while the <italic>C. coli</italic> resistance rate to florfenicol (&#x03C7;<sup>2</sup> = 4.6967, <italic>P</italic> = 0.0332) was lower than that of <italic>C. jejuni</italic>. In addition, among 8&#x2013;10 antimicrobial-resistant isolates, the isolation rate of <italic>C. coli</italic> was higher than that of <italic>C. jejuni</italic> (&#x03C7;<sup>2</sup> = 26.2338, <italic>P</italic> &#x003C; 0.0001).</p>
<p>For multi-drug resistance (MDR), 110 <italic>C. jejuni</italic> isolates (55.00%) were resistant to three or more classes of antimicrobials. Among these, 23 isolates (11.50%) were resistant to quinolone, phenicol and tetracycline, simultaneously 21 isolates (10.50%) were resistant to quinolone, phenicol, tetracycline and lincosamide. Seven isolates (3.50%) were resistant to all six classes of antimicrobials. We also recovered 27 MDR isolates of <italic>C. coli</italic> (75.00%), of which 11 isolates (30.56%) were resistant to macrolide, quinolone, phenicol, tetracycline, and lincosamide. Three isolates (8.33%) were resistant to all six classes of antimicrobials.</p>
<p>We detected 81 STs representing 19 CCs from 137 MDR isolates. Among these, ST-872, ST-1055, ST-2140, ST-9959, and ST-9976 were resistant to 10 antimicrobials (ST-872, ST-1055, and ST-9976 were sensitive to chloramphenicol. ST-2140 and ST-9959 were sensitive to gentamicin and erythromycin, respectively). Moreover, all ST-9226 isolates (<italic>n</italic> = 3) were resistant to 8&#x2013;9 antimicrobials (sensitive to streptomycin, chloramphenicol, and florfenicol). All ST-1811 isolates (<italic>n</italic> = 2) were resistant to six antimicrobials (both isolates were resistant to nalidixic acid, ciprofloxacin chloramphenicol, florfenicol, and tetracycline, however one isolate was resistant to clindamycin and the other was resistant to gentamicin). Eleven isolates of CC-828 (11/30, 36.67%) were resistant to 8&#x2013;10 antimicrobials, and three isolates (ST-403) of CC-403 (3/6, 50.00%) were resistant to eight antimicrobials. This suggested that the above STs and CCs are related to MDR of <italic>Campylobacter</italic> spp.</p>
</sec>
</sec>
<sec id="S4">
<title>Discussion</title>
<p><italic>Campylobacter</italic> is one of the major causes of gastroenteritis in the world. The transmission chain of <italic>Campylobacter</italic> spp. is not completely known but chickens are considered to be the major reservoir for transmission to humans. Additional sources of infection are likely to include red meat, unpasteurized milk, and contaminated water (<xref ref-type="bibr" rid="B24">Mylius et al., 2007</xref>; <xref ref-type="bibr" rid="B30">Pernica et al., 2016</xref>). The present study provides more complete and updated information about the prevalence, antimicrobial resistance, and genetic diversity of <italic>Campylobacter</italic> isolates during 2017 and 2018 in Beijing. <italic>Campylobacter</italic> infections can be fatal among very young children (<xref ref-type="bibr" rid="B47">World Health Organization, 2020</xref>). Several studies of <italic>Campylobacter</italic> prevalence in children have been conducted previously. For instance, <xref ref-type="bibr" rid="B56">Zhu et al. (2016)</xref> reported that 2.9% of children with diarrhea were infected by <italic>Campylobacter</italic> in Wuhan (southwest China). <xref ref-type="bibr" rid="B18">Ju et al. (2018)</xref> reported that 4.0% of child patients with diarrhea were infected by <italic>Campylobacter</italic> in Shenzhen (southern China). Our study revealed a <italic>Campylobacter</italic> prevalence of 3.45% (1/29) in child patients with diarrhea, which was not statistically significantly different from other age groups. Moreover, <xref ref-type="bibr" rid="B42">Wang et al. (2015)</xref> reported no <italic>Campylobacter</italic> infections in child patients with diarrhea in Beijing. The discrepancy in prevalence may be caused by the different choice of surveillance hospitals. Only one of the 19 hospitals selected in this study is a children&#x2019;s hospital. Our results indicated that the isolation rate of <italic>Campylobacter</italic> is higher in autumn than in other seasons. We suggest that attention should be paid to food hygiene in this season to reduce the risk of foodborne diseases.</p>
<p>In this study, we also highlighted the higher genetic diversity of <italic>Campylobacter</italic> isolates circulating in Beijing. We identified a total of 125 STs including 19 new STs, with the new STs reaching ST-10002 in this study. Data from an earlier study involving patient diarrheal isolates of <italic>Campylobacter</italic> collected in China revealed that the most commonly isolated ST in Hebei province is ST-22, consistent with our study. However, the most commonly isolated STs in Guizhou province, Henan province, Shanghai city, and Shenzhen city are ST-2274, ST-436, ST-6915, and ST-403, respectively (<xref ref-type="bibr" rid="B51">Zhang et al., 2010a</xref>; <xref ref-type="bibr" rid="B44">Wei et al., 2015</xref>; <xref ref-type="bibr" rid="B29">Pan et al., 2016</xref>; <xref ref-type="bibr" rid="B18">Ju et al., 2018</xref>). This difference in STs may be due to the low number of isolates. The most commonly isolated CCs in this study were CC-21 (42/200, 21.00%) and CC-828 (30/36, 83.33%) from <italic>C. jejuni</italic> and <italic>C. coli</italic>, respectively. Many studies have shown different major CCs of <italic>Campylobacter</italic> in different countries and regions, but CC-21, CC-45, CC-48, and CC-353 are the major CCs containing the largest number of isolates in many studies (<xref ref-type="bibr" rid="B26">O&#x2019;Mahony et al., 2011</xref>; <xref ref-type="bibr" rid="B19">Klein-J&#x00F6;bstl et al., 2016</xref>; <xref ref-type="bibr" rid="B20">Kovanen et al., 2016</xref>; <xref ref-type="bibr" rid="B30">Pernica et al., 2016</xref>; <xref ref-type="bibr" rid="B10">Dunn et al., 2018</xref>; <xref ref-type="bibr" rid="B35">Rokney et al., 2018</xref>). Studies have also shown that CC-21 is the most commonly isolated CC of <italic>C. jejuni</italic> in China (<xref ref-type="bibr" rid="B51">Zhang et al., 2010a</xref>, <xref ref-type="bibr" rid="B53">2014</xref>, <xref ref-type="bibr" rid="B50">2015</xref>; <xref ref-type="bibr" rid="B44">Wei et al., 2015</xref>; <xref ref-type="bibr" rid="B29">Pan et al., 2016</xref>; <xref ref-type="bibr" rid="B18">Ju et al., 2018</xref>), including human and chicken isolates. MLST analyses of <italic>Campylobacter</italic> in Asian diarrhea patients show that CC-21 is the most commonly isolated CC of <italic>C. jejuni</italic> in China, Israel, Iran, Japan, and South Korea. CC-1150 of <italic>C. coli</italic> has been found in Vietnam, Singapore, and China. These data highlight the diversity of <italic>Campylobacter</italic> spp. in Beijing and confirm previous MLST studies with <italic>C. jejuni</italic> and <italic>C. coli</italic> isolates from humans in China.</p>
<p>ST-2274 of <italic>C. jejuni</italic> and ST-9227 of <italic>C. coli</italic> caused outbreaks of foodborne diseases resulting in seven and three patients with diarrhea in Beijing, respectively (<xref ref-type="bibr" rid="B33">Qu et al., 2019</xref>; <xref ref-type="bibr" rid="B22">Li et al., 2020</xref>). ST-2274 was found in Thailand and Guizhou province and Shanghai city of China. ST-9227 has not been reported in the PubMLST database in Asia except in Beijing. An outbreak of Guillain Barr&#x00E9; syndrome caused by <italic>C. jejuni</italic> was previously reported in Changchun City, Jilin Province, China, and the strains isolated from patients were all ST-2993 (<xref ref-type="bibr" rid="B52">Zhang et al., 2010b</xref>). However, no other ST-2993 isolates in the PubMLST database were from other country of Asia.</p>
<p>Antimicrobial resistance of <italic>Campylobacter</italic> is receiving more attention. Infection with antimicrobial-resistant isolates is often associated with longer disease duration, higher risk of invasive disease, and higher healthcare costs (<xref ref-type="bibr" rid="B23">Lopes et al., 2019</xref>). The use of antimicrobials in animal agriculture and human medicine can affect the development of resistance in <italic>Campylobacter</italic>. It is believed that the unrestricted use of antimicrobials, especially in developing countries, has led to increased resistance to <italic>Campylobacter</italic> spp. (<xref ref-type="bibr" rid="B16">Gibreel and Taylor, 2006</xref>; <xref ref-type="bibr" rid="B7">Deng et al., 2015</xref>). In some countries, in contrast to therapeutic agents, antibacterial agents are still used as growth promoters (<xref ref-type="bibr" rid="B27">Osterlund et al., 2003</xref>; <xref ref-type="bibr" rid="B16">Gibreel and Taylor, 2006</xref>; <xref ref-type="bibr" rid="B32">Qin et al., 2011</xref>; <xref ref-type="bibr" rid="B43">Wang et al., 2014</xref>). Antimicrobial-resistant strains of <italic>Campylobacter</italic> are a zoonotic pathogens that can be transmitted to humans through contaminated food, water, or milk, seriously jeopardizing treatment (<xref ref-type="bibr" rid="B40">Smith et al., 1999</xref>; <xref ref-type="bibr" rid="B31">Piddock et al., 2000</xref>; <xref ref-type="bibr" rid="B12">Engberg et al., 2004</xref>; <xref ref-type="bibr" rid="B39">Smith and Fratamico, 2010</xref>; <xref ref-type="bibr" rid="B37">Schweitzer et al., 2011</xref>). Determination of the antimicrobial resistance level of <italic>Campylobacter</italic> isolates is crucial for the control and prevention of human infection, particularly for cases in which therapy is recommended. Macrolides and fluoroquinolones are the primary choice for treating campylobacteriosis (<xref ref-type="bibr" rid="B5">Chen et al., 2010</xref>). However, an increase in erythromycin-resistant <italic>Campylobacter</italic> in poultry has been observed in China recently (<xref ref-type="bibr" rid="B48">Zhang A. et al., 2016</xref>). In our study, 44.44% of <italic>C. coli</italic> were resistant to erythromycin. We also found that 75.00% of <italic>C. coli</italic> were MDR isolates and 11 isolates (30.56%) were resistant to macrolide, quinolone, phenicol, tetracycline, and lincosamide. Therefore, the clinical treatment of campylobacteriosis caused by <italic>C. coli</italic> should be carefully reconsidered. The overall resistance level of <italic>C. jejuni</italic> is not as high as that of <italic>C. coli</italic>, but it cannot be ignored. High resistance rates of <italic>C. jejuni</italic> to quinolone and tetracycline, with a high prevalence of MDR, has been reported in China previously (<xref ref-type="bibr" rid="B49">Zhang T. et al., 2016</xref>; <xref ref-type="bibr" rid="B21">Li et al., 2017</xref>). In our study, 55.00% of <italic>C. jejuni</italic> were MDR isolates, with quinolone, phenicols, and tetracycline the most commonly observed MDR combination (11.50%), followed by quinolone, phenicol, tetracycline and lincosamides (10.50%). A significant association between ST-464 and resistance to ciprofloxacin, nalidixic acid, and tetracycline (cip-nal-tet) has been reported (<xref ref-type="bibr" rid="B4">Cha et al., 2016</xref>). Five isolates of ST-464 were recovered in our study, all of which were resistant to cip-nal-tet. One study also claims that ST-403 has strong antimicrobial resistance (<xref ref-type="bibr" rid="B18">Ju et al., 2018</xref>), which was shown in our study. Some studies, such as in Michigan and Iran (<xref ref-type="bibr" rid="B4">Cha et al., 2016</xref>; <xref ref-type="bibr" rid="B9">Divsalar et al., 2019</xref>), reported low resistance rate of <italic>C. jejuni</italic> to florfenicol and clindamycin. However, Higher resistance rates of <italic>C. jejuni</italic> to these two antimicrobials have been reported in China. <xref ref-type="bibr" rid="B29">Pan et al. (2016)</xref> reported 21.8% of <italic>C. jejuni</italic> isolated from children with diarrhea were resistant to clindamycin. <xref ref-type="bibr" rid="B18">Ju et al. (2018)</xref> reported florfenicol resistance rate of <italic>C. jejuni</italic> close to 70%. A 17-year study of <italic>C. jejuni</italic> resistance in diarrhea patients of Beijing showed that the resistance rate of florfenicol and clindamycin is increasing (<xref ref-type="bibr" rid="B54">Zhou et al., 2016</xref>). Alarming was resistance of <italic>C. jejuni</italic> to florfenicol (35.00%) and clindamycin (33.50%) in our study. We found 17 ioslates resistant to florfenicol, clindamycin and chloramphenicol. At the same time, all 17 ioslates were resistant to cip-nal-tet, and belong to 17 different STs. The resistance pattern of these antimicrobials limits the choice of suitable antimicrobials for human <italic>Campylobacter</italic> disease. Thus, we suggest that clinicians should consider multi-drug treatment.</p>
<p>An isolate of <italic>C. coli</italic> (ST-825, CC-828) sensitive to all antimicrobials was isolated from an adult man who claimed to have eaten seafood at home (unpublished data). We are very curious about this result, because in addition to this isolate, other <italic>C. coli</italic> isolates were resistant to two or more classes of antimicrobials. Therefore, the detection of resistance genes in <italic>C. coli</italic> is the focus of our next research.</p>
<p>In China, a few studies have reported the prevalence of <italic>Campylobacter</italic> in food and animals (<xref ref-type="bibr" rid="B50">Zhang et al., 2015</xref>; <xref ref-type="bibr" rid="B17">Han et al., 2016</xref>; <xref ref-type="bibr" rid="B55">Zhu et al., 2017</xref>). However, descriptions of clinical <italic>Campylobacter</italic> are very limited. In this study, we described the characteristics of molecular typing and antimicrobial susceptibility profiles of clinical <italic>Campylobacter</italic> isolates in Beijing, the capital city of China. The clinical isolates analyzed in this study were recovered from a systematic surveillance program, which provided a unique opportunity to characterize <italic>Campylobacter</italic> spp. in Beijing.</p>
</sec>
<sec id="S5">
<title>Conclusion</title>
<p>Based on our results, attention should be drawn to the prevalence of isolates with high antimicrobial resistance rates and genetic similarity in Beijing and other districts of China. Food manufacturers should continually assess levels of contamination in food production and processing to effectively decrease <italic>Campylobacter</italic> infection and dissemination of resistant isolates in humans. Importantly, this study provides detailed insight into the phylogeny and antimicrobial resistance profiles of <italic>Campylobacter</italic> spp. in Beijing. Further surveillance is necessary to detect emerging resistance patterns and to assess the impact of strategies designed to mitigate antimicrobial resistance.</p>
</sec>
<sec id="S6">
<title>Data Availability Statement</title>
<p>All relevant data is contained within the article. All datasets generated for this study are included in the article/<xref ref-type="supplementary-material" rid="FS1">Supplementary Material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="S7">
<title>Ethics Statement</title>
<p>The protocol was approved by the ethics committee of Beijing Center for Disease Prevention and Control (Beijing CDC). Participants received information on the study&#x2019;s purpose and of their right to keep information confidential. Written consent was obtained from each participant and children&#x2019;s parents or their guardians.</p>
</sec>
<sec id="S8">
<title>Author Contributions</title>
<p>JJ and XM were involved in the collection of isolates and collected the clinical data. YL, XZ, and PZ performed the molecular subtyping and antibiotic susceptibility tests. XZ, JJ, and PZ performed the data analysis. PZ, XZ, ZS, XM, and QC designed the study, drafted, and revised this manuscript. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="conf1">
<title>Conflict of Interest</title>
<p>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.</p>
</sec>
</body>
<back>
<fn-group>
<fn fn-type="financial-disclosure">
<p><bold>Funding.</bold> This work was supported by the National Key Research and Development Program of China (Grant No. 2017YFC1601500) and the Cultivation Fund of Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine (Grant No. 2019-BJYJ-04).</p>
</fn>
</fn-group>
<sec id="S10" sec-type="supplementary material"><title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fmicb.2020.554784/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmicb.2020.554784/full#supplementary-material</ext-link></p>
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