Annals of Clinical Microbiology, The official Journal of the Korean Society of Clinical Microbiology
Eun-Young Kim1,2 
, Su Man Kim1,2 , Si Hyun Kim3 , Jeong Hwan Shin1,2
1Department of Laboratory Medicine, Inje University Busan Paik Hospital, Inje University College of Medicine, Busan, Korea
2Paik Institute for Clinical Research, Inje University College of Medicine, Busan, Korea
3Department of Biomedical Laboratory Science, Inje University, Gimhae, Korea
Ann Clin Microbiol 2026;29(3):14. https://doi.org/10.5145/ACM.2026.29.3.14
Received on 21 July 2026, Revised on 1 September 2026, Accepted on 10 September 2026, Published on 20 September 2026.
Copyright © Korean Society of Clinical Microbiology.
This is an Open Access article which is freely available under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Background: Monophasic Salmonella enterica serovar Typhimurium variants, particularly the serotype I 4,[5],12:i:-, have globally emerged as important foodborne pathogens associated with multidrug resistance. However, their molecular epidemiology and clonal distribution in South Korea remain unclear. This study investigated the distribution, clonal characteristics, and antimicrobial resistance profiles of S. Typhimurium variants circulating in South Korea.
Methods: In total, 173 S. Typhimurium variant strains were collected from 18 university hospitals between 2019 and 2020. Isolates were identified and serotyped according to the Kauffmann〝White scheme. Gene patterns were determined based on seven phase 1 and 2 flagellar antigen-associated genes. Antimicrobial susceptibility was examined using broth microdilution.
Results: The monophasic variant I 4,[5],12:i:- (n = 131) was the most prevalent, followed by I 4,[5],12:i:1,2 (n = 38) and I 4,[5],12:-:- (n = 4). Gene patterns dominant among monophasic isolates included P5 (n = 72), P8 (n = 29), and P9 (n = 28). The P5 pattern corresponded to the typical Spanish clone. Monophasic variants showed higher resistance rates to ampicillin and third-generation cephalosporins than those of other variants, with higher cephalosporin resistance observed in P8 than in P5.
Conclusion: Among the isolates included in this study, the monophasic variant I 4,[5],12:i:- was more frequently identified than typical S. Typhimurium. Most I 4,[5],12:i:- isolates showed gene patterns previously associated with the Spanish clone and high rates of antimicrobial resistance. Overall, these findings highlight the need for continued surveillance of I 4,[5],12:i:- and its antimicrobial resistance patterns.
Drug Resistance, Bacterial; Molecular epidemiology; Salmonella Typhimurium
Salmonella enterica is one of the leading causes of foodborne bacterial illness worldwide [1], with > 2,500 serotypes identified using the Kauffmann–White scheme [2]. The epidemiology and clinical severity of salmonellosis vary with serotype, and certain serotypes are associated with specific reservoirs and severe disease in humans [3,4].
Salmonella enterica serovar Typhimurium (antigenic formula: I 4,[5],12:i:1,2) is one of the most prevalent serotypes worldwide. However, human infections caused by its variants, including monophasic variant (I 4,[5],12:i:-), have increased [5–7]. Accurately identifying these variants is important as they may differ in antimicrobial resistance and transmission patterns.
To improve the identification of S. Typhimurium variants, the European Food Safety Authority (EFSA) has proposed the molecular approaches targeting the phase 1 and phase 2 flagellar genes by Tennant et al. [8]. Further, Bugarel et al. [9] have proposed a refined polymerase chain reaction (PCR)-based classification system that defined 11 gene patterns (P1–P11).
S. Typhimurium variants, including I 4,[5],12:i:-, are increasing in Asia including Japan and South Korea [5–7]; however, the data on their molecular epidemiology and clonal distribution are limited.
This study aimed to investigate the distribution and molecular epidemiological characteristics of S. enterica serovar Typhimurium variants in South Korea.
This retrospective surveillance study was based on laboratory investigations. The study was undertaken according to the Microbiology Investigation Criteria for Reporting Objectively (MICRO) framework for the reporting and interpretation of clinical microbiology data [10].
Bacterial isolates
In total, this study included 173 S. Typhimurium variant strains collected from 18 hospitals across South Korea between 2019 and 2020. The participating hospitals were located in Seoul, Incheon, Gyeonggi, Gangwon, Chungcheong, Daegu, Ulsan, Busan, Gwangju, Jeolla, and Jeju. All isolates were recovered from clinical specimens submitted for diagnostic testing and were not obtained through non-diagnostic surveillance or screening. The specimen sources included stool (n = 126), blood (n = 36), and other specimens (n = 11).
At each participating hospital, isolates recovered from clinical specimens were stored in 10% skim milk at −70°C and transported frozen to Inje University Busan Paik Hospital, where all subsequent experiments were performed.
The analysis included only the first isolate of each Salmonella enterica serovar Typhimurium variant obtained from each patient during the study period. Duplicate isolates from the same patient were excluded.
Identification and serotyping
All isolates were confirmed as S. enterica using the VITEK MS system with database version 3.0 (bioMérieux SA). Serotyping was performed using slide agglutination with somatic (O) and flagellar (H) antisera (BD Difco™, Becton, Dickinson and Company), and antigenic formulas were determined according to the Kauffmann–White scheme [11]. Phase inversion was performed to assess phase 2 H-antigen expression and to distinguish the monophasic variants from biphasic S. Typhimurium.
Gene pattern analysis
All isolates were screened for seven molecular markers associated with phase 1 and 2 flagellar antigens, including the fljAB operon, and gene patterns were assigned accordingly (Table 1 and 2). P5 and P8 were considered Spanish clone-associated patterns, whereas P7 and P9 were considered U.S. clone-associated patterns [9].
Genomic DNA was extracted using InstaGene Matrix (Bio-Rad Laboratories). PCR amplification was performed using AccuPower® PCR PreMix (BIONEER) according to the manufacturer’s instructions. Primers targeting the fliA–fliB intergenic region were used at 20 pmol per reaction, whereas all other primers were used at 10 pmol per reaction.
The PCR conditions comprised an initial denaturation step at 95°C for 5 min, and a final extension at 72°C for 7 min. The detailed cycling conditions and primer sequences are provided in Table 1 [8,9,12].
Table 1. Primers and polymerase chain reaction conditions used in this study
| Targets | Name | Primer sequence (5′–3′) | Size (bp) | Cycling profile |
|---|---|---|---|---|
| Intergenic region of fliA–fliB | FFLIB | CTG GCG ACG ATC TGT CGA TG | 964 | (30 cycles) 94℃, 30 s/54℃, 30 s/72℃, 90 s |
| RFLIA | GCG GTA TAC AGT GAA TTC AC | |||
| fljB | Sense-59 | CAA CAA CAA CCT GCA GCG TGT GCG | 1389 | (30 cycles) 94℃, 30 s/62℃, 30 s/72℃, 30 s |
| Antisense-83 | GCC ATA TTT CAG CCT CTC GCC CG | |||
| fliC | Sense-60 | ACT CAG GCT TCC CGT AAC GC | 550 | (30 cycles) 94℃, 40 s/58℃, 20 s/72℃, 20 s |
| Antisense-i | ATA GCC ATC TTT ACC AGT TCC | |||
| STM2757 | STM2757-F | AAC CGT ACA GGG TTT ATA CGC C | 91 | (35 cycles) 95℃, 15 s/60℃, 1 min/72℃, 30 s |
| STM2757-R | TTA TCG TGC CGC CGA ATT ATG G | |||
| mdh | mdh-F | TGC CAA CGG AAG TTG AAG TG | 260 | (30 cycles) 94℃, 30 s/55℃, 30 s/72℃, 30 s |
| mdh-R | CGC ATT CCA CCA CGC CCT TC | |||
| fljA | fljA-F | TCC GAA GCC AGA ATC AAA TTT TCC | 105 | (35 cycles) 95℃, 15 s/60℃, 1 min/72℃, 30 s |
| fljA-R | TAC GTT TTA ATG ATA TCC CTG TTC G | |||
| hin | hin-F | CGC CCC GGC CTG AAA CGA | 334 | (35 cycles) 95℃, 15 s/60℃, 1 min/72℃, 30 s |
| hin-R | CGA CTA ATC TGT TCC TGT TCA TGT T |
Table 2. Antigenic formula and gene pattern of Salmonella Typhimurium variants
| Gene patterna) | Antigenic formula (n, %) | Total | ||
|---|---|---|---|---|
| I 4,[5],12:-:- | I 4,[5],12:i:- | I 4,[5],12:i:1,2 (Typhimurium) | ||
| P1 (+/+/+/+/+/+/+) | 4 (100.0) | 2 (1.5) | 32 (84.2) | 38 (22.0) |
| P2 (+/+/−/+/+/+/+) | − | − | 6 (15.8) | 6 (3.5) |
| P5 (+/+/+/+/−/−/−) | − | 72 (55.0) | − | 72 (41.6) |
| P8 (−/+/+/+/−/−/−) | − | 29 (22.1) | − | 29 (16.8) |
| P9 (−/+/+/+/−/−/+) | − | 28 (21.4) | − | 28 (16.2) |
| Total | 4 (100.0) | 131 (100.0) | 38 (100.0) | 173 (100.0) |
a)(STM2757/mdh/fliA–fliB/fliC/fljB/fljA/hin); +, positive; −, negative.
Antimicrobial susceptibility testing
Sensititre KRCDC2F MIC plates (Thermo Fisher Scientific) were used for antimicrobial susceptibility testing. The following antimicrobials were tested: amikacin, ampicillin, azithromycin, cefotaxime, cefoxitin, ceftazidime, ceftriaxone, chloramphenicol, ciprofloxacin, colistin, gentamicin, imipenem, nalidixic acid, streptomycin, tetracycline, and trimethoprim–sulfamethoxazole (SXT).
Minimum inhibitory concentrations were determined according to the Clinical and Laboratory Standards Institute (CLSI) M100 ED36:2026 guidelines [13]. CLSI breakpoints were not available for amikacin, cefoxitin, ceftazidime, gentamicin, nalidixic acid, and streptomycin; therefore, susceptibility to these antimicrobials was interpreted based on the National Antimicrobial Resistance Monitoring System criteria [14]. Colistin susceptibility was interpreted according to the European Committee on Antimicrobial Susceptibility Testing (version 16.0) [15].
ACT/S resistance was defined as resistance to ampicillin, chloramphenicol, and SXT. The ACSSuT resistance profile indicated resistance to ampicillin, chloramphenicol, streptomycin, sulfonamides, and tetracycline [16].
Statistical analysis
Statistical analyses were performed to evaluate differences in antimicrobial resistance rates according to the antigenic formula and gene patterns. Categorical variables were expressed as numbers and percentages.
For the antimicrobial resistance analysis presented in Table 3, resistance rates between P5 and P8 isolates were compared using the chi-square test or Fisher’s exact test, as appropriate. Statistical analyses were performed using SPSS version 29.0 (IBM Corp.). Statistical significance was defined as a two-tailed P-value < 0.05.
Table 3. Antimicrobial resistance and gene patterns of Salmonella Typhimurium variants
| Antimicrobial agent | I 4,[5],12:i:1,2 (Typhimurium) | I 4,[5],12:-:- | I 4,[5],12:i:- | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| P1 (n = 32) | P2 (n = 6) | Total (n = 38) | P1 (n = 4) | P1 (n = 2) | P5 (n = 72) | P8 (n = 29) | P9 (n = 28) | Total (n = 131) | P-value (P5 vs. P8) | |||
| Amikacina) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | − | ||
| Ampicillin | 46.9 | 50.0 | 47.4 | 25.0 | 0 | 91.7 | 79.3 | 3.6 | 68.7 | 0.098 | ||
| Azithromycin | 0 | 0 | 0 | 0 | 0 | 2.8 | 0 | 0 | 1.5 | 1.000 | ||
| Cefotaxime | 3.1 | 0 | 2.6 | 0 | 0 | 13.9 | 41.4 | 3.6 | 17.6 | 0.006 | ||
| Cefoxitina) | 3.1 | 0 | 2.6 | 0 | 0 | 4.2 | 0 | 0 | 2.3 | 0.555 | ||
| Ceftazidimea) | 0 | 0 | 0 | 0 | 0 | 4.2 | 37.9 | 0 | 10.7 | < 0.001 | ||
| Ceftriaxone | 3.1 | 0 | 2.6 | 0 | 0 | 11.1 | 41.4 | 3.6 | 16.0 | 0.002 | ||
| Chloramphenicol | 25.0 | 50.0 | 28.9 | 25.0 | 0 | 31.9 | 41.4 | 0 | 26.7 | 0.489 | ||
| Ciprofloxacin (Intermediate rates, %) | 6.3 (40.6) | 16.7 (50.0) | 7.9 (42.1) | 0 (100) | 0 (0) | 0 (27.8) | 6.9 (31.0) | 0 (0) | 1.5 (22.1) | 0.080 | ||
| Colistinb) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7.1 | 1.5 | − | ||
| Gentamicina) | 28.1 | 0 | 23.7 | 25.0 | 0 | 8.3 | 0 | 0 | 4.6 | 0.178 | ||
| Imipenem | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | − | ||
| Nalidixic acida) | 43.8 | 0 | 36.8 | 100 | 0 | 0 | 3.4 | 0 | 0.8 | 0.287 | ||
| Streptomycina) | 21.9 | 33.3 | 23.7 | 25.0 | 0 | 86.1 | 79.3 | 3.6 | 65.6 | 0.385 | ||
| Tetracycline | 34.4 | 33.3 | 34.2 | 0 | 0 | 84.7 | 75.9 | 0 | 63.4 | 0.389 | ||
| Trimethoprim–sulfamethoxazole | 12.5 | 50.0 | 18.4 | 0 | 0 | 27.8 | 0 | 0 | 15.3 | < 0.001 | ||
Values are presented as percentages of resistant isolates unless otherwise indicated.
a)Clinical and Laboratory Standards Institute (CLSI) breakpoints have not been established for these antimicrobial agents; the interpretive standards used are the National Antimicrobial Resistance Monitoring System (NARMS)-established breakpoints for resistance monitoring, which should not be used to predict clinical efficacy.
b)European Committee on Antimicrobial Susceptibility Testing, 2026.
Among 173 S. Typhimurium variant isolates, the monophasic variant I 4,[5],12:i:- (n = 131, 75.7%) was the most prevalent, followed by typical S. Typhimurium I 4,[5],12:i:1,2 (n = 38, 22.0%), and the non-motile variant I 4,[5],12:-:- (n = 4, 2.3%). The monophasic variant I 4,[5],12:-:1,2 was not detected.
Gene pattern analysis revealed five patterns (P1, P2, P5, P8, and P9) based on the presence or absence of seven target genes (STM2757, mdh, intergenic regions of fliA–fliB, fliC, fljB, fljA, and hin) (Table 2). P5 was the most prevalent (n = 72), followed by P1 (n = 38), P8 (n = 29), P9 (n = 28), and P2 (n = 6).
P1 included 32 typical S. Typhimurium isolates, four I 4,[5],12:-:- isolates, and two I 4,[5],12:i:- isolates. P2 exclusively consisted of six typical S. Typhimurium isolates. P5, P8, and P9 were only detected in I 4,[5],12:i:- isolates. Both P5 and P8 lacked fljA, fljB, and hin, whereas P8 additionally lacked STM2757. P9 was positive for hin, but lacked fljA, fljB, and STM2757.
Among the I 4,[5],12:i:- isolates, 77.1% were classified as Spanish clones (P5, 55.0%; P8, 22.1%), whereas 21.4% corresponded to a U.S. clone (P9).
Resistance to ampicillin, streptomycin, and tetracycline was numerically more frequent in P5 and P8 than in the other gene patterns. The resistance rates at P5 and P8 were as follows: ampicillin (91.7% and 79.3%); streptomycin (86.1% and 79.3%); and tetracycline (84.7% and 75.9%), respectively (Table 3).
P8 showed significantly higher resistance to third-generation cephalosporins compared with that of P5 (cefotaxime: 41.4% vs. 13.9%; ceftazidime: 37.9% vs. 4.2%; ceftriaxone: 41.4% vs. 11.1%; P < 0.05). Among 72 P5 isolates, 23 (31.9%) were concurrently resistant to ampicillin, chloramphenicol, streptomycin, and tetracycline, corresponding to four of the five components of the characteristic ACSSuT resistance profile of the Spanish clone. Because sulfamethoxazole alone was not tested, the complete ACSSuT phenotype could not be determined. Twenty-three P5 isolates were resistant to four ACSSuT components (ampicillin, chloramphenicol, streptomycin, and tetracycline) and 18 of these were additionally resistant to SXT.
Typical S. Typhimurium (P1 and P2) and I 4,[5],12:-:- (P1) strains demonstrated high rates of intermediate resistance to ciprofloxacin (42.1% and 100%, respectively). Further, high rates of nalidixic acid resistance were observed in P1 isolates of typical S. Typhimurium (43.8%) and I 4,[5],12:-:- (100%).
In contrast, P9 isolates showed low rates of resistance to most antimicrobials, with resistance to colistin observed in 7.1% of isolates and resistance to other antimicrobials occurring at rates below 4%.
Overall, 25 isolates (14.5%) were classified as ACT/S-resistant isolates. These included seven typical S. Typhimurium isolates (P1, n = 4; P2, n = 3) and 18 I 4,[5],12:i:- isolates (all P5). No ACT/S-resistant isolates were identified among the P9 strains.
Among the isolates collected in South Korea during the study period, I 4,[5],12:i:- was more frequently identified compared with typical S. Typhimurium. P5, P8, and P9 were the predominant gene patterns among I 4,[5],12:i:- isolates, with P5 and P8 previously associated with the Spanish clone and P9 with the U.S. clone. These gene patterns showed substantially different antimicrobial resistance profiles, with P8 isolates showing particularly high resistance to third-generation cephalosporins. These findings reveal the molecular epidemiological diversity of I 4,[5],12:i:- and the association between gene patterns and antimicrobial resistance profiles.
Salmonella serotypes are determined using a combination of somatic (O) and flagellar (H) antigens. Phase variation in S. Typhimurium is regulated by the coordinated expression of two flagellar proteins, FliC (phase 1 antigen) and FljB (phase 2 antigen). Expression switching occurs through inversion of the promoter region, which is mediated by the DNA invertase Hin. This results in fliC suppression by fljA and the subsequent expression of fljB [17, 18]. Gene disruption or deletion within the fljAB operon or associated regulatory regions can result in monophasic variants.
Salmonella Typhimurium (I 4,[5],12:i:1,2) expresses both phase 1 and phase 2 H antigens. However, based on differences in H antigen expression, three variants have been described: monophasic variant I 4,[5],12:i:-, the uncommon variant I 4,[5],12:-:1,2, and the non-motile variant I 4,[5],12:-:- [19–21].
The Centers for Disease Control and Prevention and the EFSA report that I 4,[5],12:i:- ranks among the top five most-detected serotypes in human clinical isolates. The I 4,[5],12:i:- variant is increasingly reported in North America, Europe, Asia, Oceania, and South America and is frequently associated with pork, poultry, and cattle products [6, 22–28].
A previous nationwide human surveillance in South Korea (2016–2017) reported that I 4,[5],12:i:- accounted for 16.7% of the isolates, surpassing the typical Typhimurium isolates (9.9%) [5]. In the present study, the ratio of I 4,[5],12:i:- to typical Typhimurium increased from 1.7:1 to 3.4:1, indicating that I 4,[5],12:i:- was more frequently identified than typical Typhimurium during the study period. However, this comparison was limited to these two serotypes and does not indicate predominance among all Salmonella serotypes. A recent nationwide surveillance from 2022 to 2024 identified S. Enteritidis (29.7%) as the most common serotype, whereas I 4,[5],12:i:- accounted for 10.5% of the isolates [29].
To improve S. Typhimurium variant identification, the EFSA has proposed molecular approaches targeting the phase 1 and phase 2 flagellar genes. Tennant et al. [8] analyzed genetic variations in fljB, the fliB–fliA intergenic region, and the phase 1 “i” antigen gene using PCR-based methods. However, inconsistent findings, including the unexpected absence or presence of certain flagella-associated genes, were occasionally observed. Subsequently, Bugarel et al. [9] proposed a refined PCR-based classification system defining 11 gene patterns (P1–P11) using additional markers, such as fljA, fliC, hin, STM2757, and mdh. This approach enabled improved molecular epidemiologic investigations and facilitated the differentiation of epidemic clones, including the Spanish (P5 and P8) and U.S. (P7 and P9) clones of I 4,[5],12:i:-.
In terms of clonal lineages, I 4,[5],12:i:- has been categorized into several epidemic lineages, including Spanish, U.S., and European clones [19, 27, 28, 30]. In the present study, most isolates showed P5 and P8 patterns, which have been associated with the Spanish clone, whereas P9 has been associated with the U.S. clone. However, as the P1–P11 classification is based on a limited set of PCR markers, these patterns do not allow definitive assignment of isolates to specific clonal lineages. In particular, presence or absence of the European clone, characterized by features such as ST34 and the ASSuT resistance phenotype, could not be determined using the methods employed in this study.
The Spanish monophasic clone, first reported in Spain in 1997, was predominantly associated with phage type U302 and a multidrug resistance profile including resistance to ampicillin, chloramphenicol, sulfonamides, gentamicin, streptomycin, tetracycline, and SXT [9, 31]. This clone is distinct from the classical multidrug-resistant S. Typhimurium DT104 lineage that emerged in the mid-1980s and is characterized by the ACSSuT resistance profile [32]. In the current study, 23 of 72 P5 isolates (31.9%) were resistant to four of the five ACSSuT components (ampicillin, chloramphenicol, streptomycin, and tetracycline) and 18 of these isolates were additionally resistant to SXT. However, because sulfamethoxazole alone was not tested, the complete ACSSuT phenotype could not be determined. These findings should therefore be interpreted as overlapping resistance characteristics rather than evidence of the classical ACSSuT phenotype. Interestingly, P8 isolates, although genetically related to the Spanish clone, showed markedly higher rates of resistance to third-generation cephalosporins than those of P5 isolates. This may limit the treatment options for invasive infections and pose critical clinical and public health challenges. This finding suggests the possible acquisition of additional resistance determinants, underscoring the need for continuous monitoring.
In contrast, the U.S. clone (P9) exhibits low levels of antimicrobial resistance [7]. Consistent with previous reports, the P9 isolates in this study showed low resistance rates, and no ACT/S-resistant isolates were identified. However, detection of colistin resistance in a subset of P9 isolates warrants further investigation into the genetic mechanisms underlying this phenotype.
Overall, three major gene patterns (P5, P8, and P9), previously associated with the Spanish and U.S. clones, were identified among the I 4,[5],12:i:- isolates in South Korea. Predominance of the Spanish clone suggests potential transmission through livestock reservoirs, particularly pork and poultry, as observed in Europe and North America. This finding raises concerns regarding foodborne transmission and highlights the need for integrated surveillance across the food production chain. Furthermore, significant differences in antimicrobial resistance profiles according to gene patterns highlight the epidemiological importance of molecular subtyping.
Considering the increasing prevalence of I 4,[5],12:i:- and its association with the ACT/S resistance phenotype, continued molecular surveillance is essential. Gene pattern-based subtyping may serve as a practical tool for epidemiological investigations and the development of antimicrobial treatment strategies. Overall, these findings highlight the importance of continuous national surveillance under the One Health framework and support the implementation of genomic surveillance and antimicrobial stewardship programs for mitigating the spread of high-risk clones.
This study has a few limitations. First, isolates were collected only from university hospitals, which may not fully represent the nationwide epidemiology. Second, whole-genome sequencing was not performed to confirm the clonal relationships and resistance determinants.
Monophasic S. Typhimurium I 4,[5],12:i:- was more frequently identified than typical S. Typhimurium among the isolates included in this study. Most I 4,[5],12:i:- isolates presented gene patterns previously associated with the Spanish clone, whereas a small proportion showed patterns associated with the U.S. clone. Distinct gene patterns were associated with pronounced differences in antimicrobial resistance profiles; particularly, the P8 isolates demonstrated increased resistance to third-generation cephalosporins. These findings highlight the epidemiological and public health relevance of I 4,[5],12:i:- and the importance of continued surveillance. Moreover, they indicate the practicality of gene pattern-based molecular subtyping for epidemiological surveillance and antimicrobial resistance monitoring in resource-limited settings. Overall, this study provides important evidence for public health policies and infection control strategies.
This study was approved by the Institutional Review Board of Inje University Busan Paik Hospital, with a waiver of informed consent (Approval No. BPIRB NON2024-001).
No potential conflicts of interest relevant to this article were reported.
The research was supported by a fund (2020E540600) from the Research Program of Korea Disease Control and Prevention Agency and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), Ministry of Health & Welfare, Korea (grant number: HR21C1003).
Data are available upon reasonable request.
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22. Proroga YTR, Capuano F, Carullo MR, La Tela I, Capparelli R, Barco L, et al. Characterization of Salmonella Typhimurium and its monophasic variant 1,4,[5],12:i:- isolated from different sources. Folia Microbiol (Praha) 2019;64:711-8.
23. Cevallos-Almeida M, Figueroa A, Rojas D, López S, Montalvo T, Llorente P, et al. Colonization of pigs experimentally infected with a monophasic variant of Salmonella Typhimurium. Foodborne Pathog Dis 2018;15:576-82.
24. Merlotti A, Manfreda G, Munck N, Hald T, Litrup E, Nielsen EM, et al. Network approach to source attribution of Salmonella enterica serovar Typhimurium and its monophasic variant. Front Microbiol 2020;11:1205.
25. Canning M, Birhane MG, Dewey-Mattia D, Lawinger H, Cote A, Gieraltowski L. Salmonella outbreaks linked to beef, United States, 2012-2019. J Food Prot 2023;86:100071.
26. Trachsel JM, Bearson BL, Brunelle BW, Bearson SMD. Relationship and distribution of Salmonella enterica serovar I 4,[5],12:i:- strain sequences in the NCBI Pathogen Detection database. BMC Genomics 2022;23:268.
27. Cuenca-Arias P, Montaño LA, Villalobos-Rodríguez AP, Wiesner M, Hidalgo AM. Molecular and phenotypic characterization of Salmonella Typhimurium monophasic variant (1,4,[5],12:i:-) from Colombian clinical isolates. Biomedica 2020;40:722-33.
28. Vazquez X, García V, Fernández J, Rodicio R, Rodicio MR. Insights into the evolution of IncR plasmids found in the Southern European clone of the monophasic variant of Salmonella enterica serovar Typhimurium. Antibiotics (Basel) 2024;13:334.
29. Jeong HJ, Shin E, Kim J, Yoo J. Trends in the serotype distribution of Salmonella enterica isolated from patients with diarrhea in the Republic of Korea from 2022 to 2024. Jugan Geongang Gwa Jilbyeong 2025;18:1790-812.
30. Mourao J, Machado J, Novais C, Antunes P, Peixe L. Characterization of the emerging clinically-relevant multidrug-resistant Salmonella enterica serotype 4,[5],12:i:- (monophasic variant of S. Typhimurium) clones. Eur J Clin Microbiol Infect Dis 2014;33:2249-57.
31. de la Torre E, Zapata D, Tello M, Mejía W, Frías N, García Peña FJ, et al. Several Salmonella enterica subsp. enterica serotype 4,5,12:i:- phage types isolated from swine samples originate from serotype Typhimurium DT U302. J Clin Microbiol 2003;41:2395-400.
32. Carattoli A, Tosini F, Visca P. Multidrug-resistant Salmonella enterica serotype Typhimurium infections. N Engl J Med 1998;339:921-2.
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27. Cuenca-Arias P, Montaño LA, Villalobos-Rodríguez AP, Wiesner M, Hidalgo AM. Molecular and phenotypic characterization of Salmonella Typhimurium monophasic variant (1,4,[5],12:i:-) from Colombian clinical isolates. Biomedica 2020;40:722-33.
28. Vazquez X, García V, Fernández J, Rodicio R, Rodicio MR. Insights into the evolution of IncR plasmids found in the Southern European clone of the monophasic variant of Salmonella enterica serovar Typhimurium. Antibiotics (Basel) 2024;13:334.
29. Jeong HJ, Shin E, Kim J, Yoo J. Trends in the serotype distribution of Salmonella enterica isolated from patients with diarrhea in the Republic of Korea from 2022 to 2024. Jugan Geongang Gwa Jilbyeong 2025;18:1790-812.
30. Mourao J, Machado J, Novais C, Antunes P, Peixe L. Characterization of the emerging clinically-relevant multidrug-resistant Salmonella enterica serotype 4,[5],12:i:- (monophasic variant of S. Typhimurium) clones. Eur J Clin Microbiol Infect Dis 2014;33:2249-57.
31. de la Torre E, Zapata D, Tello M, Mejía W, Frías N, García Peña FJ, et al. Several Salmonella enterica subsp. enterica serotype 4,5,12:i:- phage types isolated from swine samples originate from serotype Typhimurium DT U302. J Clin Microbiol 2003;41:2395-400.
32. Carattoli A, Tosini F, Visca P. Multidrug-resistant Salmonella enterica serotype Typhimurium infections. N Engl J Med 1998;339:921-2.