https://orcid.org/0000-0001-6609-0553
Figures
Abstract
Salmonella is a primary cause of foodborne diseases globally. Despite food contamination and clinical infections garnering substantial attention and research, asymptomatic Salmonella carriers, potential sources of infection, have been comparatively overlooked. In this study, we conducted a comparative analysis of serotype distribution, antimicrobial resistance phenotypes, and genetic profiles of archived Salmonella strains isolated from food (26), asymptomatic carriers (41), and clinical cases (47) in Shiyan City, China. Among the 114 Salmonella strains identified, representing 31 serotypes and 34 Sequence Types (STs), the most prevalent serovars included Typhimurium, Derby, Enteritidis, Thompson, and London, with the most predominant STs being ST11, ST40, ST26, ST34, and ST155. Antimicrobial resistance testing revealed that all strains were only sensitive to meropenem, with 74.6% showing antimicrobial resistance (AMR) and 53.5% demonstrating multidrug resistance (MDR). Strains resistant to five and six classes of antibiotics were the most common. Pearson’s chi-square test showed no statistically significant difference in the occurrence of AMR (p = 0.105) or MDR (p = 0.326) among Salmonella isolates from the three sources. Our findings underscore associations and diversities among Salmonella strains isolated from food, asymptomatic carriers, and clinical patients, emphasizing the need for increased vigilance towards asymptomatic Salmonella carriers by authorities.
Citation: Lv J, Geng L, Ye W, Gong S, Wu J, Ju T, et al. (2024) Antimicrobial resistance and genetic relatedness of Salmonella serotypes isolated from food, asymptomatic carriers, and clinical cases in Shiyan, China. PLoS ONE 19(5): e0301388. https://doi.org/10.1371/journal.pone.0301388
Editor: Csaba Varga, University of Illinois Urbana-Champaign College of Veterinary Medicine, UNITED STATES
Received: October 17, 2023; Accepted: March 11, 2024; Published: May 9, 2024
Copyright: © 2024 Lv et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The datasets generated during the current study are available in the NCBI GenBank repository, under accession numbers, aroC: OQ956257 - OQ956370; dnaN: OQ956371 - OQ956484; hemD: OQ956485 - OQ956598; sucA: OQ956599 - OQ956712; thrA: OQ956713 - OQ956826; hisD: OQ956827 - OQ956940; purE: OQ956941 - OQ957054.
Funding: This work was supported by the Hubei Province Health and Family Planning Scientific Research Project (No. WJ2023M168), the Principal Investigator Program (HBMUPI202104); the Science Research and Development Project of Shiyan (2021K20). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Salmonella, a member of the Enterobacteriaceae family, stands as a significant pathogenic bacterium that affects human and animal health. Defined by the Kauffmann-White scheme, Salmonella encompasses more than 2,600 serovars distinguished by three surface antigens: lipopolysaccharide, flagella, and capsular polysaccharide [1]. Globally, an estimated 115 million people, predominantly in developing nations, suffer from Salmonella infections annually, resulting in approximately 370,000 deaths [2]. The escalating antimicrobial resistance (AMR) of Salmonella poses a pressing threat to both clinical treatment and animal husbandry [3], with the prevalence of multidrug-resistant (MDR) Salmonella emerging as a significant concern worldwide [4].
Consumption of contaminated food stands out as the primary route of Salmonella infections, followed by person-to-person and animal contact transmission pathways.
The manifestation of symptomatic disease or asymptomatic persistence subsequent to Salmonella infection depends on various factors, including the infecting serovars, genetic background, and host immunity. Approximately 3–5% of patients transition into chronic carriers, characterized by prolonged fecal shedding despite the absence of overt signs of infection [5].
Symptomatic diseases disproportionately affect vulnerable populations, such as infants, the elderly, immunocompromised individuals, and those with underlying medical conditions. Asymptomatic patients are individuals who harbor the pathogen without exhibiting clinical symptoms [6,7]. Asymptomatic individuals are often challenging to detect unless they undergo proactive medical testing. Conversely, asymptomatic carriers can manifest symptoms and maintain their ability to transmit the disease. Therefore, the prevalence of carriers represents an urgent public health concern [8].
Several reports have highlighted the circulation of Salmonella spp. among animals, humans, and the environment [9]. Typing and tracing Salmonella subsequent to isolation and identification are crucial for epidemiological investigations, ensuring food safety, safeguarding public health, and optimizing livestock production [10]. Traditional serotyping and multilocus sequence typing (MLST) are the most commonly employed methods for phenotyping and genotyping, respectively [10].
To date, while some studies have linked foodborne Salmonella strains to clinical cases, the understanding of the source and impact of asymptomatic carriers remains limited. In this study, our aim was to investigate serotypes distribution, antimicrobial resistance patterns, and MLST profiles of Salmonella isolated from food, asymptomatic carriers, and clinical cases in Shiyan, China. By comparing and analyzing the differences and potential correlations among Salmonella isolates from diverse sources, we elucidate the current status of transmission and drug resistance of Salmonella in Shiyan. Our findings underscore the imperative for developing more precise and effective strategies to mitigate human Salmonella infections.
Materials and methods
Study design
This was a cross-sectional study. Archived Salmonella strains isolated from food, asymptomatic carriers, and clinical patients between 2018 and 2020 in Shiyan, China were collected and subjected to analysis to explore the associations and diversities in serotype distribution, antimicrobial resistance patterns, and gene profiles.
Ethical approval
The Salmonella strains examined in this article were archived isolates, and all clinical data were anonymized and unlinked. The research content did not entail the use of personal information or involve human blood, tissues, germ cells, embryos, reproductive cloning, chimerism, heritable gene manipulation, or similar activities. In accordance with national ethical review standards for life science and medical research, ethical approval and individual informed consent were deemed unnecessary and exempted.
Serotyping of Salmonella isolates
In our cross-sectional study, we examined 114 previously archived Salmonella isolates. Of these, 26 strains were obtained from livestock meat, aquatic products, and ready-to-eat food by foodborne disease inspectors at the Shiyan Center for Disease Control and Prevention. The remaining 88 strains were isolated by the clinical laboratory at Taihe Hospital. Among these, 41 strains were identified from anal swab samples of asymptomatic individuals, while 47 strains were identified from fecal samples of clinical patients. All isolates underwent identification using the VITEK-2 Compact system (bioMerieux Inc., France) and PCR [11,12]. Subsequently, classical serotyping of Salmonella isolates was conducted using slide agglutination with O, H, and Vi antigen-specific sera (Diagnostic antisera kit-60 vials, Statens Serum Institute, Denmark) in accordance with the White-Kauffmann-Le Minor scheme [13].
Antimicrobial susceptibility testing
All Salmonella isolates underwent susceptibility testing using Kirby-Bauer disk diffusion method, following the guidelines outlined by the Clinical and Laboratory Standards Institute (CLSI) guidelines [14]. Seventeen commercial antibiotic discs (Liofilchem, Ita) utilized, representing the following 12 classes: (i) aminoglycosides: amikacin (AK, 30 μg), gentamicin (GEN, 10 μg), kanamycin (KAN, 30 μg), streptomycin (STR, 10 μg); (ii) β-lactam combination agents: amoxicillin/clavulanic acid (AMC, 20/10μg); (iii) carbapenems: meropenem (MEM, 10 μg); (iv) cephalosporins: cefazolin (CZO, 30 μg), cefotaxime (CTX, 30 μg); (v) folate pathway inhibitors: trimethoprim/sulphamethoxazole (SXT 25 μg); (vi) monobactams: aztreonam (ATM, 30 μg); (vii) macrolides: azithromycin (AZM, 15 μg); (viii) nitrofurans: nitrofurantoin (NIT, 300 μg); (ix) penicillins: ampicillin (AMP, 10 μg); (x) phenicols: chloramphenicol (CHL, 30 μg); (xi) quinolones: ciprofloxacin (CIP, 5 μg), nalidixic acid (NAL, 30 μg); (xii) tetracyclines: tetracycline (TET, 30 μg).
The pure cultured Salmonella colonies were suspended in sterile phosphate-buffered saline to create a 0.5 McFarland inoculum. Subsequently, bacterial suspensions were evenly spread onto Mueller–Hinton agar (Oxoid Ltd., England) using a sterile cotton swab. Following the placement of antibiotic discs on the agar, the plates were allowed to stand for 5 minutes before being incubated at 36°C in ambient air for 18 hours Meanwhile, E. coli ATCC 25922 was used as a quality-control strain. The diameters of the inhibition zones were measured in millimeters (mm) using a caliper. Interpretation of susceptibility or resistance to each antibiotic adhered to CLSI standards. Multidrug resistance (MDR) was characterized by resistance to at least one drug in each of three or more classes of antimicrobial agents [15].
Heatmap drawing
A heatmap was generated using TBtools [16] with default parameters to visualize variations in antimicrobial resistances among Salmonella isolates from different sources.
MLST analysis
The total genomic DNA of Salmonella isolates were extracted from overnight cultures grown at 37°C in LB broth using a TIANamp Bacteria DNA Kit (TIANGEN, DP302, China) following the manufacturer’s instructions. Subsequently, the extracted DNA were quantified and temporarily stored at -20°C before PCR amplification as templates. MLST of Salmonella isolates was conducted according to previously established protocols [17]. Seven housekeeping genes (aroC, dnaN, hemD, hisD, purE, sucA, and thrA) were amplified using the primers listed in S1 Table, purified, and sent to Sangon Biotech (Sangon, Shanghai, China) for bidirectional sequencing. The allele sequences were then compared and analyzed using the Salmonella enterica MLST database (http://mlst.warwick.ac.uk/mlst/). Strains that share identical allele gene fragments are assigned to a common sequence type (ST). Furthermore, goeBURST analysis was performed to evaluate the genetic evolution among the different isolates (http://www.phyloviz.net/goeburst/).The primer sequences were obtained from the scheme published on the MLST home page (http://enterobase.warwick.ac.uk/species/senterica/allele_st_search) (S1 Table).
Statistical analysis
Statistical analysis was conducted using SPSS software, version 27. Differences in antimicrobial resistance and multidrug resistance among Salmonella isolated from food, asymptomatic carriers and clinical cases were assessed using Pearson’s chi-square test (χ2). A significance level of p < 0.05 was considered statistically significant.
Results
Distribution of serotypes
To gain a comprehensive understanding of the classification of these samples, we conducted an analysis of serotype distribution. Our findings revealed that among the 114 strains of Salmonella examined in this study, 31 serotypes were identified through slide agglutination (Table 1). Notably, Salmonella serovar Typhimurium (n = 17, 14.9%) emerged as the predominant serotype in Shiyan between 2018 and 2020, followed by Derby (n = 14, 12.3%), Enteritidis (n = 13, 11.4%), Thompson (n = 10, 8.8%), London (n = 9, 7.9%), Agona (n = 7, 6.1%), Goldcoast (n = 5, 4.4%) and Choleraesuis (n = 4, 3.5%). Senftenberg, Kentucky and Stanley each represented 2.7% (n = 3). Two strains were identified for typhoid, paratyphoid A, paratyphoid B, Bareilly, Liverpool, and Rison, respectively. However, only one isolate was recognized for Anatum, Albany, Corvallis, Give, Hadar, Havana, Lagos, Litchfield, Muenchen, Muenster, Montevideo, Newport, Oranienburg, and Wandsworth, respectively.
Thirteen, fifteen, and eighteen serotypes were identified among Salmonella strains isolated from food (n = 26), asymptomatic carriers (n = 41), and clinical cases (n = 47), respectively. Serovars Derby, Typhimurium, Agona, Thompson, and Goldcoast were detected across isolates from these three sources. Serovars Typhi, Paratyphi A, Paratyphi B, Choleraesuis, Litchfield, and Newport were exclusively isolated from clinical cases. Serovars Anatum, Albany, Give, Hadar, Lagos and Muenster were exclusively isolated from the food source. The five most commonly isolated serovars from food and humans were Typhimurium, Derby, Enteritidis, Thompson, and London. However, the top five prevalent serovars causing human infection were Typhimurium, Enteritidis, Thompson, London, and Agona. Typhimurium and Enteritidis were the most common serovars in humans. These data underscore the diversity of Salmonella serovars across the three sources.
Antimicrobial resistance phenotypes
As previously mentioned, monitoring phenotypic antimicrobial resistance is crucial to mitigate the overuse and misuse of antibiotics. We next assessed the susceptibility of Salmonella isolates to 17 antibiotics across 12 categories. Of the total, 29 strains (25.44%) exhibited susceptibility to all 12 antimicrobial classes, while 14 (12.28%) and 10 (8.77%) strains displayed resistance to one and two antimicrobial classes, respectively. Notably, the remaining 61 isolates (53.5%) demonstrated resistance to three or more antimicrobial classes, classifying them as MDR strains (Fig 1). Among these, resistance to five and six classes of antimicrobials was notably prevalent (S2 Table). Remarkably, the most resistant strain was S. Thompson isolated from clinical cases, exhibiting resistance to 10 classes of antimicrobials.
As shown, 53.5% of isolates exhibited resistance to three or more antimicrobial classes, defining multidrug resistance (MDR). Different numbers in the x-axis denote the numbers of antimicrobials. Blue, yellow, and orange columns represent susceptibility/intermediate susceptibility, antimicrobial resistance, and multidrug resistance, respectively.
The antimicrobial resistance patterns of Salmonella isolated from food, asymptomatic carriers, and clinical cases are depicted in Fig 2A. There was no statistically significant association between strain source and the occurrence of AMR (χ2 = 4.501, p = 0.105) or MDR (χ2 = 2.244, p = 0.326), suggesting that the source did not influence the resistance characteristics in this study. The antimicrobial resistance patterns of strains from food and asymptomatic carriers closely resembled each other, whereas those from clinical cases exhibited the most abundant MDR patterns (Fig 2B), indicating that MDR strains tend to be enriched in severe health conditions.
(A) The AMR and MDR characteristics of Salmonella isolated from food, asymptomatic carriers, and clinical cases are illustrated. Earthy yellow and orange-red columns indicate AMR and MDR, respectively. (B) The heatmap depicts the antimicrobial resistance of Salmonella strains from various sources to 17 antibiotics. The numbers in cells represent the percentage (%) of antimicrobial resistance isolates. The color bar is located in the upper right corner. Red indicates the resistance rate of Salmonella isolates, with darker shades denoting higher resistance rates. Abbreviations: TET: Tetracycline; AMP: Ampicillin; STR: Streptomycin; NAL: Nalidixic acid; SXT: Trimethoprim/sulphamethoxazole; CHL: Chloramphenicol; KAN: Kanamycin; CZO: Cefazolin; GEN: Gentamicin; CTX: Cefotaxime; AZM: Azithromycin; CIP: Ciprofloxacin; ATM:aztreonam; NIT: Nitrofurantoin; AMI:amikacin; AMC: Amoxicillin/clavulanic acid; MEM: Meropenem.
The MDR rates of the top five prevalent Salmonella serotypes exceeded the overall MDR rate (53.5%) (Table 1). S. Enteritidis (92.3%, 12/13) exhibited the highest MDR rate, followed by S. London (88.9%, 8/9), S. Derby (71.4%, 10/14), S. Typhimurium (64.7%, 11/17), and S. Thompson (60.0%, 6/10) (Table 1).
It is noteworthy that we evaluated their responses to 17 antimicrobials, revealing that all 114 isolates in this study demonstrated sensitivity to meropenem, a carbapenem drug utilized in treating symptomatic Salmonella infection [18] (Fig 3). Salmonella isolates exhibited the highest resistance rate to tetracycline (49.1%, 56/114), followed by ampicillin (48.2%, 55/114), streptomycin (35.1%, 40/114), trimethoprim/sulfamethoxazole (30.7%, 35/114), and nalidixic acid (28.1%, 32/114).
Light blue, gray, and orange columns represent sensitivity, intermediate sensitivity, and resistance, respectively. Column height is proportional to the ratio. Abbreviations: S: Susceptible; I: Intermediate susceptible; R: Resistant. TET: Tetracycline; AMP: Ampicillin; STR: Streptomycin; SXT: Trimethoprim/sulphamethoxazole; NAL: Nalidixic acid; CHL: Chloramphenicol; KAN: Kanamycin; CZO: Cefazolin; GEN: Gentamicin; CTX: Cefotaxime; AZM: Azithromycin; CIP: Ciprofloxacin; ATM:aztreonam; NIT: Nitrofurantoin; AMI:amikacin; AMC: Amoxicillin/clavulanic acid; MEM: Meropenem.
Antimicrobial resistance to the aforementioned three antibiotics was also observed in 26 food isolates and 41 asymptomatic carrier isolates. However, among the 47 isolates from clinical cases, ampicillin, tetracycline, and nalidixic acid demonstrated the highest antimicrobial resistance (Fig 4).
Blue, gray, and orange columns represent sensitivity, intermediate sensitivity, and resistance, respectively. Column length is proportional to the ratio. Abbreviations: S: Susceptible; I: Intermediate susceptible; R: Resistant. TET: Tetracycline; AMP: Ampicillin; STR: Streptomycin; SXT: Trimethoprim/sulphamethoxazole; NAL: Nalidixic acid; CHL: Chloramphenicol; KAN: Kanamycin; CZO: Cefazolin; GEN: Gentamicin; CTX: Cefotaxime; AZM: Azithromycin; CIP: Ciprofloxacin; ATM: Aztreonam; NIT: Nitrofurantoin; AMI: Amikacin; AMC: Amoxicillin/clavulanic acid; MEM: Meropenem.
MLST profiles
MLST, a standard bacterial genotyping method, was utilized to elucidate the genetic relationships among these Salmonella strains. From the MLST analysis, the 114 strains were categorized into 34 STs, with ST40, ST11, and ST26 emerging as the most frequent STs, accounting for 11.4% (13/114), 11.4% (13/114), and 8.8% (10/114) of the isolates, respectively (Table 1). It has been observed that S. Typhimurium comprises ST19 (7), ST34 (9), and ST36 (1), while S. Derby encompasses ST40 (13) and ST71 (1); other serotypes were identified unique STs. A minimum spanning tree, based on the STs obtained for Salmonella isolates, was depicted according to serotypes and sources, respectively (Fig 5). It has been shown that sixteen isolates, comprising either ST19 or ST34, were grouped into clonal complex 19, whereas the remaining 98 isolates belonged to 32 distinct clonal complexes. Each of these 32 clonal complexes was associated with only one ST (Fig 5A).
goeBURST diagrams of Salmonella isolates based on multilocus sequence typing of seven housekeeping genes presented by (A) serotype and (B) source, respectively. Each circle within the tree represents a single ST (Sequence Type). The size of the circle corresponds to the number of Salmonella strains represented. Links between circles are labeled with absolute distance.
The correlation of STs among strains from different sources is shown in Fig 5B. Five sequence types, namely ST13, ST26, ST34, ST40, and ST358 were identified in samples from in food, asymptomatic carriers, and clinical cases samples. ST11 was associated with both food and clinical cases samples, while ST14 was identified in both food and asymptomatic carriers. ST19, ST29, ST155 and ST469 were found in both clinical cases and asymptomatic carriers. ST33, ST64, ST71, ST292, ST321, ST516 and ST1889 were exclusively recovered from food samples. ST2, ST36, ST42, ST68, ST85, ST166 and ST214 were identified solely in clinical cases samples, while ST4, ST23, ST82, ST198, ST203, ST1498, ST1527, ST1541 and ST1959 were exclusively found in samples from asymptomatic carriers.
Discussion
Salmonellosis ranks as the third leading cause of death among food-transmitted diseases [19,20]. Animal-based foods, including pork, poultry, beef, and seafood, have been extensively implicated as the primary vehicles for the transmission of Salmonella spp. to humans. Despite the identification of more than 2600 serovars of S. enterica, human salmonellosis is primarily associated with limited serotypes of subspecies enterica. Among these, the top five serovars are Enteritidis, Typhimurium, Infantis, Stanley, and Newport [21]. According to Hendriksen et al., the most commonly isolated serovars exhibit considerable variation across different regions [22].
In this study, the five most commonly isolated serovars from both food and humans were Typhimurium, Derby, Enteritidis, Thompson, and London. However, the top five prevalent serovars causing human infection were Typhimurium, Enteritidis, Thompson, London, and Agona. Typhimurium and Enteritidis emerged as the most common serovars in humans, consistent with reports from numerous countries or regions [23,24]. It is noteworthy that S. Typhimurium strains from asymptomatic carriers and clinical cases numbered 9 and 6, respectively, whereas all 11 strains of S. Enteritidis were isolated from clinical cases, in accordance with the findings of Xu et al. [25].
The prevalence of serovars Derby, Thompson, and London among the predominant serotypes suggests a potentially high contamination rate in food. A study conducted in Hebei province, China, revealed that these serotypes were the top three Salmonella serovars isolated from chicken and pork [26]. While serovar Derby ranked as the most common serotype isolated from food, it only held the sixth position, alongside serovars Gold Coast and Choleraesuis, among the serotypes causing human diseases. Litrup et al. also reported similar observations and suggested that this phenomenon could be attributed to the absence of certain virulence-associated genes in the Salmonella pathogenicity island 3 (SPI-3), such as sugR (ATP binding protein) and rhuM (putative cytoplasmic protein) [27].
Compared with the predominant Salmonella serotypes in other provinces or cities in China [10,25], the most significant difference observed was the notable increase in serovar Thompson in Shiyan city. S. Thompson is seldom pathogenic to poultry; hence, food matrices derived from poultry could serve as vehicles for the transmission of S. Thompson to humans through fecal contamination [28]. The sudden surge of serovar Thompson in Shiyan city might indicate that poultry products produced and sold in this area have been significantly contaminated by Salmonella Thompson in recent years. The strains of serovar London were isolated from clinical cases (n = 3) and asymptomatic carriers (n = 6) but not from food, suggesting a potential association with insufficient frequency and coverage of food testing.
Significant differences exist in the AMR and MDR characteristics of Salmonella isolated from food, humans, and animals [29]. MDR Salmonella infections may result in worse outcomes compared to those caused by pan-susceptible strains [30]. In this study, 53.5% (61/114) of Salmonella isolates exhibited resistance to at least three classes of antimicrobials. The prevalence of MDR in food isolates (50%) was lower than that reported in Poland (53.8%) but higher than that in Italy (41.6%) [31,32]. The prevalence of MDR in human isolates (asymptomatic carriers, 46.3%, and clinical cases, 61.7%) was lower than that reported in Guizhou (82.9%) and Jiangsu (84.1%) in China but considerably higher than that reported in the European Union (25.4%) [25,33,34]. These variations among different countries may indicate that the abuse or overuse of antibiotics is more prevalent in China compared to European countries.
The antimicrobial resistance of Salmonella spp. is a naturally occurring phenomenon, which can be exacerbated by selection pressures stemming from the overuse of antibiotics in medical and livestock breeding practices [35]. In our study, the top five most frequently observed resistant antimicrobials were tetracycline (49.1%), ampicillin (48.2%), streptomycin (35.1%), trimethoprim/sulfamethoxazole (30.7%), and nalidixic acid (28.1%), all of which are commonly used in clinical treatments [36]. Moreover, historically, tetracycline and streptomycin have been widely employed as growth promoters in animal husbandry [37,38]. Meropenem was the only antibiotic observed to be sensitive to all Salmonella isolates in our study, consistent with reports from Nantong, China, and Southern Italy [25,39]. Third-generation cephalosporins and fluoroquinolones are the highest priority antibiotics for the treatment of human invasive salmonellosis [29]. Our results showed that among these two classes of antibiotics, Salmonella isolates exhibited the highest sensitivity to ciprofloxacin, which was recommended as the adaptive choice for empirical therapy [40,41].
The most resistant isolate was a strain of S. Thompson isolated from a clinical case, exhibiting resistance to 10 classes of antimicrobials. To mitigate the worsening Salmonella resistance problem, it is imperative to prioritize the rational use of antibiotics by strengthening antimicrobial stewardship in both clinical treatment and animal production [42].
MLST technology has emerged as an ideal tool for global epidemiological investigations owing to its exceptional accuracy, discriminability, and reproducibility [43]. As of February 2023, the PubMLST database (https://pubmlst.org/) had documented 8,818 STs, whereas approximately 2,600 traditional serotypes were reported. MLST analysis not only offers superior discriminatory power compared to serotyping but also enables the prediction of Salmonella serotypes [44,45].
The sequence types associated with prevalent serotypes of Salmonella have demonstrated geographic and host correlations [46]. In our study, 17 strains of S. Typhimurium were categorized into ST19, ST34, and ST36 using MLST, with ST19 and ST34 being the most prevalent, consistent with findings from Shandong and Hangzhou, China [47,48]. However, ST313 exhibits the highest incidence in S. Typhimurium infections in sub-Saharan Africa, while ST213 has supplanted ST19 as the predominant genotype of S. Typhimurium in Mexico [49,50]. Additionally, we observed that ST19 strains appeared to display higher antimicrobial resistance than ST34 strains, contrary to the findings of Wu et al. [51].
Salmonella serovars are categorized into typhoidal and non-typhoidal types. Typhoidal serovars, such as Typhi, Paratyphi, and Sendai, demonstrate high adaptation to humans. Conversely, non-typhoidal serovars possess varying zoonotic potential and can induce human salmonellosis through direct or indirect transmission from animals to humans [52]. Both humans and animals (including swine, cattle, chickens, dogs, cats, ornamental birds, reptiles, amphibians, and rodents) can become asymptomatic carriers following Salmonella infection. Serovars Typhimurium, Derby, London, Newport, and Senftenberg commonly cause asymptomatic infections in humans [7,53]. Asymptomatic carriers have the potential to contaminate the environment, water sources, and food by intermittently shedding bacteria in feces over extended periods, thereby posing infection risks to vulnerable populations in the community [54,55]. Research by Parisi et al. suggested that Salmonella isolates from asymptomatic individuals were more susceptible to antimicrobials [56]. However, in our study, no statistical difference was observed in the antimicrobial resistance patterns between isolates from food, asymptomatic carriers, and clinical cases.
This study also has limitations. Salmonella spp. primarily infects humans through contaminated food. However, due to inadequate frequency and coverage of food sampling, certain Salmonella serotypes isolated from human populations may not have been detected in food sources. Due to the relatively small sample size of archived Salmonella strains presented, statistical analysis was limited in our study. Instead, we predominantly relied on descriptive methods. In order to draw unbiased conclusions, we recommend conducting a larger sampling across various regions of the country. In the antimicrobial susceptibility test, we selected 17 commonly used antibiotics from 12 classes. If additional antibiotics were included, the antimicrobial resistance profiles of Salmonella isolates would likely be more complex. Whole Genome Sequencing (WGS) and Pulsed Field Gel Electrophoresis (PFGE) represent two optimal and efficient approaches for genotyping and exploring genetic relatedness [57]. However, in comparison, the MLST technique incurs lower costs and proved adequate for discriminating between different Salmonella strains in this study. With the support of future funding, we anticipate employing WGS to investigate a wider diversity of Salmonella strains in subsequent research endeavors.
Conclusions
This study compared and analyzed the correlation and divergence of serotypes, antimicrobial resistance phenotypes, and genetic profiles of Salmonella isolated from food, asymptomatic carriers, and clinical cases. The antimicrobial resistance (AMR) and multidrug resistance (MDR) status of Salmonella isolates from asymptomatic carriers was found to be as severe as those from food and clinical cases. Asymptomatic carriers of multidrug-resistant Salmonella pose a significant health threat to susceptible populations. Therefore, it is imperative to remind authorities to allocate more attention to asymptomatic Salmonella carriers.
Supporting information
S1 Table. Primers used for multilocus sequence typing of Salmonella isolates.
https://doi.org/10.1371/journal.pone.0301388.s001
(DOCX)
S2 Table. Antimicrobial resistance patterns of Salmonella isolates.
https://doi.org/10.1371/journal.pone.0301388.s002
(DOCX)
Acknowledgments
We thank members of the Zhang laboratory and the central laboratory of Taihe hospital for helpful discussions and technical assistance.
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