New multilocus sequence typing scheme for 
Vancomycin-resistant Enterococcus faecium (VREfm), now frequently multidrug-resistant, is among the most challenging causes of healthcare-associated infections . Molecular epidemiological tools are important for controlling nosocomial transmissions and must be readily available in clinical laboratories. Pulsed-field gel electrophoresis (PFGE) for E. faecium , introduced in 1991 after the emergence of VREfm , remains in use today despite the increased accessibility of genome analysis. However, PFGE analysis has limitations, including procedural complexity and issues with data incompatibility . Furthermore, as PFGE equipment is no longer commercially available, there is an urgent need for alternative tools that can be implemented in clinical laboratories. In 2002, multilocus sequence typing (MLST) for E. faecium was developed, enabling the classification of evolutionary lineages by comparing the sequences of seven housekeeping genes in the original scheme . However, its discriminatory power is not high, making it unsuitable for epidemiological studies of genetically related isolates, such as those involved in nosocomial outbreaks. However, it is widely used in international comparative studies because of its analytical clarity. In fact, epidemiological studies using the original scheme have helped reveal the global spread of the clonal complex-17 (CC17) strain, which has adapted to the hospital environment . Furthermore, various sequence types (STs) within CC17 lacking the pstS gene, one of the target genes of MLST, have been identified as endemic worldwide . These STs can affect the accuracy of MLST analysis. The original scheme was developed using genomic information of E. faecalis and MLST data of other bacterial species, as the whole genome information of E. faecium was not available at that time. Consequently, phylogenetic evolutionary analysis using the original scheme does not always align with whole-genome analysis . To improve the accuracy of genetic similarity assessment, a new MLST scheme, called the Bezdíček scheme, comprising eight new loci was proposed in 2023 based on genomic analysis of numerous E. faecium isolates . A total of 194 isolates from a Czech hospital were subjected to whole-genome analysis over a prolonged period (June 2017 to July 2022) and were subdivided into 23 STs using the Bezdíček scheme, expanding from the nine STs identified using the original scheme . However, no detailed descriptions of nosocomial transmission between patients or follow-up were provided, leaving the utility of the new scheme during outbreaks unclear. In another report of a VREfm outbreak at a pediatric ward in Brazil, all five analyzed strains were assigned to the same STs using the original and Bezdíček schemes . Therefore, the discriminatory power of the new scheme in outbreak analysis remains uncertain. To address the gap in the literature, this study aimed to validate the clinical utility of the Bezdíček MLST scheme using VREfm isolates from outbreaks at a Japanese tertiary medical center, representing a geographical departure from the previous studies. 

Isolate collection and ethics approval This retrospective study analyzed VREfm isolated from patients at a tertiary medical center in Southern Osaka, Japan, in 2019. An outbreak in early 2019 led to simultaneous VREfm detection in hospitalized patients. During this outbreak, 8,019 VRE screening tests on stools or rectal swabs, as well as follow-up surveys for carriers, were performed. Screening tests and routine culture tests were used to detect vancomycin non-susceptible E. faecium 213 and 11 strains, respectively. The study used 68 strains, the first VREfm isolate from each patient, excluding 154 duplicate cases and two unstored cases. Forty-seven strains were isolated from stools, 19 strains from rectal swabs, one from a wound (R-VRE-029), and one from midstream urine (R-VRE-039), with no infection diagnosed. The carrier of R-VRE-039 was repeatedly identified using stool samples following the isolation of VREfm from urine. However, the stool of carrier of R-VRE-029 was not screened, owing to their poor general condition prior to VRE transmission. Regardless of the number of days between admission and detection, all strains were included in this study to facilitate the analysis of their different epidemiological relationships. This study was approved by the Rinku General Medical Center Ethics Committee (approval number: 2023-011). Informed consent was waived, given the use of anonymized retrospective data. Microbiological tests VREfm was isolated on Trypticase Soy Agar with 5% Sheep Blood (BD, Franklin Lakes, NJ, USA) incubated overnight at 35°C. For VRE screening tests, stool or rectal swab samples were plated on CHROMagar VRE (CHROMagar, Paris, France) and incubated at 35°C for 24 h. The MicroScan WalkAway system (Beckman Coulter, Brea, CA, USA) was used for identification and antimicrobial susceptibility at the time of isolation, following the procedure manual. The stored strains were tested for vancomycin and teicoplanin susceptibility using the E-test (bioMérieux, Marcy l'Etoile, France) and Mueller Hinton II Agar (BD) in accordance with Clinical and Laboratory Standards Institute standard methods ( https://clsi.org/ ). DNA extraction The stored strains were cultured overnight in Brain Heart Infusion Broth (Eiken Chemical, Tokyo, Japan) and then moderately diluted in saline solution. Total DNA was extracted using magLEAD 6gC and MagDEA Dx SV (Precision System Science, Chiba, Japan), following the manufacturer’s instructions. Detection of van and ddl genes The presence of glycopeptide resistance genes ( vanA and vanB ) and the species-specific ddl gene in VREfm isolates was detected using multiplex polymerase chain reaction (PCR), following a modified procedure from a previous study . The primers used are listed in . Briefly, a 20 µL reaction mixture was prepared using the KAPATaq Extra PCR Kit (Kapa Biosystems, Wilmington, MA, USA) according to the manufacturer’s instructions. The PCR conditions were as follows: 94°C for 2 min, followed by 25 cycles at 94°C for 15 s, 54°C for 15 s, 72°C for 45 s, and 72°C for 1 min. Amplified fragments were confirmed using 1.5% agarose gel electrophoresis. PFGE PFGE analysis was also performed as previously described . Briefly, total DNA embedded in agarose plugs was digested with SmaI, and the resulting fragments were separated via PFGE using a CHEF-DRIII apparatus (Bio-Rad Laboratories, Hercules, CA, USA). The band patterns were analyzed using BioNumerics software (Applied Maths, Sint-Martens-Latem, Belgium). Dendrograms for cluster analysis were generated with the following conditions: Dice coefficient, represented by the unweighted pair group method with arithmetic mean (UPGMA), with 1.0% optimization and 1.0% tolerance. Clusters were classified based on 85% similarity. MLST The target genes for MLST were amplified using primer sets from previous studies . The primers used are listed in . A 20 µL reaction mixture was prepared using the KAPATaq Extra PCR Kit. For the original MLST, the PCR conditions were as follows: 94°C for 4 min, followed by 35 cycles of 94°C for 30 s, 52°C for 1 min, 72°C for 1 min, and 72°C for 7 min. For the Bezdíček scheme, the annealing temperature was changed to 60°C, with other conditions remaining the same. After confirmation by agarose gel electrophoresis, the PCR products were purified enzymatically with Exonuclease I (New England Biolab [NEB], Ipswich, MA, USA) and Shrimp Alkaline Phosphatase (NEB) following the manufacturer’s instructions. The purified DNA fragments were sequenced by Fasmac (Kanagawa, Japan) and Eurofins Genomics (Tokyo, Japan). The sequences were checked for allele numbers and STs using pubMLST . A new allelic sequence ( ddl -194) was deposited in the DNA Data Bank of Japan (accession no. LC814434 ), and all MLST data were deposited in the pubMLST database . In this study, to avoid confusion regarding the ST numbering, we used ST O and ST B to distinguish between the original and Bezdíček schemes in E. faecium MLST. Phylogenetic trees were constructed using the UPGMA method in MEGA11  from the concatenated MLST allele sequences of the STs identified in this study. Genetic linkages between the identified MLST allele profiles were analyzed using the goeBURST Full MST algorithm in PHYLOViZ 2.0 . Discriminatory power and clustering concordance Simpson’s index of diversity  and the adjusted Wallace index  were calculated to determine discriminatory power and clustering concordance, respectively, using the online tool for comparing partitions ( http://www. comparingpartitions.info/ ). Investigation of VREfm carriers The ward transfer history of VREfm carriers was investigated, and the number of days spent in each ward before testing positive was tabulated. Data regarding antacid proton pump inhibitors (PPIs), H2 blockers, potassium-competitive acid blockers (P-CABs), and vancomycin administration prior to VREfm isolation were also collected from medical records. 

This retrospective study analyzed VREfm isolated from patients at a tertiary medical center in Southern Osaka, Japan, in 2019. An outbreak in early 2019 led to simultaneous VREfm detection in hospitalized patients. During this outbreak, 8,019 VRE screening tests on stools or rectal swabs, as well as follow-up surveys for carriers, were performed. Screening tests and routine culture tests were used to detect vancomycin non-susceptible E. faecium 213 and 11 strains, respectively. The study used 68 strains, the first VREfm isolate from each patient, excluding 154 duplicate cases and two unstored cases. Forty-seven strains were isolated from stools, 19 strains from rectal swabs, one from a wound (R-VRE-029), and one from midstream urine (R-VRE-039), with no infection diagnosed. The carrier of R-VRE-039 was repeatedly identified using stool samples following the isolation of VREfm from urine. However, the stool of carrier of R-VRE-029 was not screened, owing to their poor general condition prior to VRE transmission. Regardless of the number of days between admission and detection, all strains were included in this study to facilitate the analysis of their different epidemiological relationships. This study was approved by the Rinku General Medical Center Ethics Committee (approval number: 2023-011). Informed consent was waived, given the use of anonymized retrospective data. 

VREfm was isolated on Trypticase Soy Agar with 5% Sheep Blood (BD, Franklin Lakes, NJ, USA) incubated overnight at 35°C. For VRE screening tests, stool or rectal swab samples were plated on CHROMagar VRE (CHROMagar, Paris, France) and incubated at 35°C for 24 h. The MicroScan WalkAway system (Beckman Coulter, Brea, CA, USA) was used for identification and antimicrobial susceptibility at the time of isolation, following the procedure manual. The stored strains were tested for vancomycin and teicoplanin susceptibility using the E-test (bioMérieux, Marcy l'Etoile, France) and Mueller Hinton II Agar (BD) in accordance with Clinical and Laboratory Standards Institute standard methods ( https://clsi.org/ ). 

The stored strains were cultured overnight in Brain Heart Infusion Broth (Eiken Chemical, Tokyo, Japan) and then moderately diluted in saline solution. Total DNA was extracted using magLEAD 6gC and MagDEA Dx SV (Precision System Science, Chiba, Japan), following the manufacturer’s instructions. 

van and ddl genes The presence of glycopeptide resistance genes ( vanA and vanB ) and the species-specific ddl gene in VREfm isolates was detected using multiplex polymerase chain reaction (PCR), following a modified procedure from a previous study . The primers used are listed in . Briefly, a 20 µL reaction mixture was prepared using the KAPATaq Extra PCR Kit (Kapa Biosystems, Wilmington, MA, USA) according to the manufacturer’s instructions. The PCR conditions were as follows: 94°C for 2 min, followed by 25 cycles at 94°C for 15 s, 54°C for 15 s, 72°C for 45 s, and 72°C for 1 min. Amplified fragments were confirmed using 1.5% agarose gel electrophoresis. 

PFGE analysis was also performed as previously described . Briefly, total DNA embedded in agarose plugs was digested with SmaI, and the resulting fragments were separated via PFGE using a CHEF-DRIII apparatus (Bio-Rad Laboratories, Hercules, CA, USA). The band patterns were analyzed using BioNumerics software (Applied Maths, Sint-Martens-Latem, Belgium). Dendrograms for cluster analysis were generated with the following conditions: Dice coefficient, represented by the unweighted pair group method with arithmetic mean (UPGMA), with 1.0% optimization and 1.0% tolerance. Clusters were classified based on 85% similarity. 

The target genes for MLST were amplified using primer sets from previous studies . The primers used are listed in . A 20 µL reaction mixture was prepared using the KAPATaq Extra PCR Kit. For the original MLST, the PCR conditions were as follows: 94°C for 4 min, followed by 35 cycles of 94°C for 30 s, 52°C for 1 min, 72°C for 1 min, and 72°C for 7 min. For the Bezdíček scheme, the annealing temperature was changed to 60°C, with other conditions remaining the same. After confirmation by agarose gel electrophoresis, the PCR products were purified enzymatically with Exonuclease I (New England Biolab [NEB], Ipswich, MA, USA) and Shrimp Alkaline Phosphatase (NEB) following the manufacturer’s instructions. The purified DNA fragments were sequenced by Fasmac (Kanagawa, Japan) and Eurofins Genomics (Tokyo, Japan). The sequences were checked for allele numbers and STs using pubMLST . A new allelic sequence ( ddl -194) was deposited in the DNA Data Bank of Japan (accession no. LC814434 ), and all MLST data were deposited in the pubMLST database . In this study, to avoid confusion regarding the ST numbering, we used ST O and ST B to distinguish between the original and Bezdíček schemes in E. faecium MLST. Phylogenetic trees were constructed using the UPGMA method in MEGA11  from the concatenated MLST allele sequences of the STs identified in this study. Genetic linkages between the identified MLST allele profiles were analyzed using the goeBURST Full MST algorithm in PHYLOViZ 2.0 . 

Simpson’s index of diversity  and the adjusted Wallace index  were calculated to determine discriminatory power and clustering concordance, respectively, using the online tool for comparing partitions ( http://www. comparingpartitions.info/ ). 

The ward transfer history of VREfm carriers was investigated, and the number of days spent in each ward before testing positive was tabulated. Data regarding antacid proton pump inhibitors (PPIs), H2 blockers, potassium-competitive acid blockers (P-CABs), and vancomycin administration prior to VREfm isolation were also collected from medical records. 

Clinical isolate The vanA genes were identified in all 68 VREfm isolates, whereas the vanB gene was not detected. E. faecium -specific ddl genes were also detected in all strains, which is consistent with the MicroScan WalkAway System results. The carriers included 45 male individuals aged 41–90 years and 23 female individuals aged 48–95 years. The mean and median ages were 73.8 and 74.0 years, respectively, for both sexes. Eleven cases were detected within 48 h of admission . Seven individuals (R-VRE-031, -032, -045, -049, -050, -053, and -068) had a history of admission since December 2018, two (R-VRE-061 and -062) were transferred from geriatric facilities, and one (R-VRE-072) was transferred from a neighboring medical institution. The remaining individual (R-VRE-070) had no history of admissions since 2015. Although the minimum inhibitory concentrations (MICs) for vancomycin revealed high resistance in all but one strain, those for teicoplanin exhibited variable results . PFGE analysis Sixty-eight VREfm strains were subjected to PFGE analysis for reference classification and divided into nine clusters . The two main clusters, A and B, contained 85.3% (58/68) of the total strains. The remainder consisted of small clusters or singletons. also shows the detection dates and the number of days from admission to VREfm detection, with concentrated isolation periods observed in clusters A and B. Original MLST analysis The original MLST scheme identified five ST O s: ST O 192 in 56 strains (82.4%), ST O 2669 in two (2.9%), ST O 17 in five (7.4%), ST O 555 in four (5.9%), and ST O 78 in one strain (1.5%) . ST O 2669 closely resembles ST O 192 but is differentiated by a 21-base duplication in a segment of ddl -1, indicating that it is a putative subtype of ST O 192. Phylogenetic tree analysis of the UPGMA showed that the predominant ST O 192 was closely related to ST O 2669 and ST O 78. However, all ST O s were in a single group when classified at an evolutionary distance of 0.001 . The goeBURST Full MST analysis at the single-locus variant (SLV) level grouped the five ST O s into a single group . The group of ST O s shared identical alleles at four of the seven loci . Bezdíček MLST analysis The Bezdíček MLST scheme identified nine ST B s: ST B 1162 in 32 strains (47.1%); ST B 610 in 25 (36.8%); ST B 4 in three (4.4%); ST B 1164 in three (4.4%); and ST B 895, ST B 101, ST B 543, ST B 512, and ST B 1163 in one strain each (1.5% each) . Phylogenetic tree analysis of UPGMA showed that the predominant STs, ST B 1162, and ST B 610, along with ST B 895, were closely related to each other but phylogenetically distinct from the other ST B s . The nine ST B s were divided into two groups and two singletons, based on the goeBURST Full MST analysis at the SLV level . These groups of ST B s shared identical alleles at five or six of the eight loci . Similarly, in the UPGMA tree, classification at an evolutionary distance of 0.001 divided the ST B s into four groups, consistent with the number of groups formed during goeBURST Full MST analysis. Comparison of molecular epidemiological analysis The discriminatory power of each method was evaluated using Simpson’s index of diversity, which was 0.635 (95% CI, 0.560–0.710), 0.317 (95% CI, 0.175–0.458), and 0.648 (95% CI, 0.574–0.722) for PFGE, the original scheme, and the Bezdíček scheme, respectively. The Bezdíček scheme exhibited the same discriminatory power as PFGE, which was higher than that of the original scheme. According to the adjusted Wallace index of clustering concordance between methods, the new Bezdíček scheme and PFGE were highly concordant . A comparison of the distribution of STs in both MLST schemes with the PFGE classification in revealed that the distribution of ST B s in the Bezdíček scheme closely matched the PFGE clustering. This was also confirmed by the results presented in , which depicts the Bezdíček scheme allele profiles overlaid on the PFGE cluster distribution and analyzed using the goeBURST full MST algorithm. These observations suggest that the outbreak was caused by two major ST B s. In contrast, the original scheme failed to distinguish the two major clusters, identifying them as a single large cluster instead . Additionally, ST O 17 and ST O 555 in the original scheme were distantly distributed among multiple PFGE clusters, a discrepancy resolved by the Bezdíček scheme. These results indicate that the Bezdíček scheme shares the same discriminatory powers and a high clustering concordance with PFGE for epidemiologically relevant strains. Visualization of outbreak illustrates the distribution of the date of isolation along with the ST B s identified by the Bezdíček scheme. Different ST B s were detected consecutively, indicating that they had formed distinct clusters. To visualize horizontal transmission within the ward, the number of days patients were hospitalized in the same ward as VREfm pre-carriers was tabulated . The same ST B s were observed in clusters among patients in the same ward to identify horizontal transmission (red box in ). Visual observation confirmed the ward cluster shrinking and the outbreak ending owing to infection control measures. Clear visualization also revealed the dynamics of sequential outbreaks caused by different ST B s. R-VRE-030 was identified on the fourth day of admission; however, VRE with an identical PFGE band pattern was isolated from two patients who stayed in the same ward during that period, leading to the expansion of the ST B 610 cluster ( and red arrow in ). In contrast, transmission could not be tracked in patients who were identified with VREfm on admission using a screening test . Of patients with a history of previous hospital admission, further investigation revealed that three had a history of contact with carriers during the previous admissions . Among them, there was a notable case of suspected transmission from a patient with confirmed negative results on three consecutive VRE culture tests. As shown in , patient B (R-VRE-033 assigned to ST B 1162) is presumed to have transmitted VRE to patient A (R-VRE-053 assigned to ST B 1162) during their initial admission when they shared a room for 5 days. Administration of antacids and vancomycin Approximately 76.5% (52/68) of the patients had used antacids for more than 3 days before VREfm detection . The use of vancomycin was confirmed in 30.9% (21/68) of the patients . 

The vanA genes were identified in all 68 VREfm isolates, whereas the vanB gene was not detected. E. faecium -specific ddl genes were also detected in all strains, which is consistent with the MicroScan WalkAway System results. The carriers included 45 male individuals aged 41–90 years and 23 female individuals aged 48–95 years. The mean and median ages were 73.8 and 74.0 years, respectively, for both sexes. Eleven cases were detected within 48 h of admission . Seven individuals (R-VRE-031, -032, -045, -049, -050, -053, and -068) had a history of admission since December 2018, two (R-VRE-061 and -062) were transferred from geriatric facilities, and one (R-VRE-072) was transferred from a neighboring medical institution. The remaining individual (R-VRE-070) had no history of admissions since 2015. Although the minimum inhibitory concentrations (MICs) for vancomycin revealed high resistance in all but one strain, those for teicoplanin exhibited variable results . 

Sixty-eight VREfm strains were subjected to PFGE analysis for reference classification and divided into nine clusters . The two main clusters, A and B, contained 85.3% (58/68) of the total strains. The remainder consisted of small clusters or singletons. also shows the detection dates and the number of days from admission to VREfm detection, with concentrated isolation periods observed in clusters A and B. 

The original MLST scheme identified five ST O s: ST O 192 in 56 strains (82.4%), ST O 2669 in two (2.9%), ST O 17 in five (7.4%), ST O 555 in four (5.9%), and ST O 78 in one strain (1.5%) . ST O 2669 closely resembles ST O 192 but is differentiated by a 21-base duplication in a segment of ddl -1, indicating that it is a putative subtype of ST O 192. Phylogenetic tree analysis of the UPGMA showed that the predominant ST O 192 was closely related to ST O 2669 and ST O 78. However, all ST O s were in a single group when classified at an evolutionary distance of 0.001 . The goeBURST Full MST analysis at the single-locus variant (SLV) level grouped the five ST O s into a single group . The group of ST O s shared identical alleles at four of the seven loci . 

The Bezdíček MLST scheme identified nine ST B s: ST B 1162 in 32 strains (47.1%); ST B 610 in 25 (36.8%); ST B 4 in three (4.4%); ST B 1164 in three (4.4%); and ST B 895, ST B 101, ST B 543, ST B 512, and ST B 1163 in one strain each (1.5% each) . Phylogenetic tree analysis of UPGMA showed that the predominant STs, ST B 1162, and ST B 610, along with ST B 895, were closely related to each other but phylogenetically distinct from the other ST B s . The nine ST B s were divided into two groups and two singletons, based on the goeBURST Full MST analysis at the SLV level . These groups of ST B s shared identical alleles at five or six of the eight loci . Similarly, in the UPGMA tree, classification at an evolutionary distance of 0.001 divided the ST B s into four groups, consistent with the number of groups formed during goeBURST Full MST analysis. 

The discriminatory power of each method was evaluated using Simpson’s index of diversity, which was 0.635 (95% CI, 0.560–0.710), 0.317 (95% CI, 0.175–0.458), and 0.648 (95% CI, 0.574–0.722) for PFGE, the original scheme, and the Bezdíček scheme, respectively. The Bezdíček scheme exhibited the same discriminatory power as PFGE, which was higher than that of the original scheme. According to the adjusted Wallace index of clustering concordance between methods, the new Bezdíček scheme and PFGE were highly concordant . A comparison of the distribution of STs in both MLST schemes with the PFGE classification in revealed that the distribution of ST B s in the Bezdíček scheme closely matched the PFGE clustering. This was also confirmed by the results presented in , which depicts the Bezdíček scheme allele profiles overlaid on the PFGE cluster distribution and analyzed using the goeBURST full MST algorithm. These observations suggest that the outbreak was caused by two major ST B s. In contrast, the original scheme failed to distinguish the two major clusters, identifying them as a single large cluster instead . Additionally, ST O 17 and ST O 555 in the original scheme were distantly distributed among multiple PFGE clusters, a discrepancy resolved by the Bezdíček scheme. These results indicate that the Bezdíček scheme shares the same discriminatory powers and a high clustering concordance with PFGE for epidemiologically relevant strains. 

illustrates the distribution of the date of isolation along with the ST B s identified by the Bezdíček scheme. Different ST B s were detected consecutively, indicating that they had formed distinct clusters. To visualize horizontal transmission within the ward, the number of days patients were hospitalized in the same ward as VREfm pre-carriers was tabulated . The same ST B s were observed in clusters among patients in the same ward to identify horizontal transmission (red box in ). Visual observation confirmed the ward cluster shrinking and the outbreak ending owing to infection control measures. Clear visualization also revealed the dynamics of sequential outbreaks caused by different ST B s. R-VRE-030 was identified on the fourth day of admission; however, VRE with an identical PFGE band pattern was isolated from two patients who stayed in the same ward during that period, leading to the expansion of the ST B 610 cluster ( and red arrow in ). In contrast, transmission could not be tracked in patients who were identified with VREfm on admission using a screening test . Of patients with a history of previous hospital admission, further investigation revealed that three had a history of contact with carriers during the previous admissions . Among them, there was a notable case of suspected transmission from a patient with confirmed negative results on three consecutive VRE culture tests. As shown in , patient B (R-VRE-033 assigned to ST B 1162) is presumed to have transmitted VRE to patient A (R-VRE-053 assigned to ST B 1162) during their initial admission when they shared a room for 5 days. 

Approximately 76.5% (52/68) of the patients had used antacids for more than 3 days before VREfm detection . The use of vancomycin was confirmed in 30.9% (21/68) of the patients . 

This study validated the clinical utility of the newly proposed Bezdíček MLST scheme for E. faecium during a VREfm outbreak in a medical center. The distribution of ST B s classified by the Bezdíček scheme was sufficiently consistent with the phylogenetic tree analysis by PFGE. Conversely, the original scheme showed limited discriminatory power, as the same ST O s spanned multiple PFGE clusters. Although it suggested a major outbreak caused by ST O 192, the Bezdíček scheme and carrier tracing revealed a series of horizontal transmissions by ST B 1162 and ST B 610. Moreover, although the discriminatory power of the Bezdíček scheme was moderate (0.648) compared with that from a previous study (0.983) , this can be attributed to the analysis of epidemiologically close strain collections. Nonetheless, the results exhibited comparable discriminatory power to PFGE. Generally, MLST is simple, reproducible, and comparable, making it suitable for clinical laboratories. This makes the new Bezdíček scheme a suitable alternative to PFGE as an epidemiological tool for managing nosocomial VREfm infections. In the primary spread, 25 strains (mainly ST B 1162) were detected within 16 days of the start of the epidemic. In the second spread, 13 strains (mainly ST B 610) were detected over a 15-day period starting on day X + 63. Although not evident in the first spread, R-VRE-030 appears to have been the founding strain of the second cluster. It was the ﬁrst ST B 610 strain isolated on day 4 of admission, and its PFGE band pattern was identical to that of VREfm isolated in November 2018 . However, the carriers of the two strains were not hospitalized simultaneously, and no clear contact history could be confirmed. Additionally, Enterococci can survive on dry surfaces for months or even longer , suggesting that these cases might have involved environmental transmission at different times. Research indicates that the use of PPIs is a factor in the increased risk of nosocomial transmission of VRE and drug-resistant bacteria . In this study, 76.5% of patients had a history of taking antacids, such as PPIs, H2 blockers, and P-CABs. As a host-side factor, antacids can increase the pH of the stomach, reducing its barrier function, and allowing bacteria to reach the intestine and persist. Additionally, PPI use can influence the composition of the intestinal microbiota, resulting in a notable increase in the prevalence of Enterococci . This, in turn, may facilitate the establishment of VRE that has passed through the stomach. However, the present study did not assess non-VRE carriers, limiting risk factor evaluation; therefore, further detailed studies are needed. In hospitals where VRE is detected, patient isolation and contact precautions are essential to prevent its spread. However, ongoing carrier management is often discontinued after three consecutive negative cultures . In the investigated hospital, this criterion for confirming negative results led to subsequent VRE carriage . Although VRE can be re-detected after confirmed clearance, especially following antimicrobial therapy , it is crucial to understand that culture-negative clearance does not indicate complete eradication, but rather that detection levels are below sensitivity thresholds . Establishing criteria, such as the addition of a surveillance culture if antimicrobials are administered after a negative confirmation, are recommended. Furthermore, as shown in , patient B (R-VRE-033 carrier) was on continuous PPI therapy at the time of re-detection. This suggests that repeated entry through the gastric barrier might lead to recurrence, warranting future investigations. ST O 192, typed by the original scheme, was the predominant strain and the first isolation reported in Japan according to the pubMLST database ( https://pubmlst.org/ ). Although ST O 192 is an SLV of ST O 78, the Bezdíček scheme results suggest lower genetic relatedness than expected . ST O 192 was often detected in a European VREfm outbreak around 2010, with many strains carrying the vanB gene . In contrast, recent ST O 192 strains in Asia predominantly carry the vanA gene . Notably, an ST O 192 isolate from China in 2019 was re-classified as ST B 895 under the Bezdíček scheme (accession no. JABEXB000000000 ). Although only one ST B 895 strain was detected in the present study, it is an SLV of ST B 1162 and a double-locus variant of ST B 610, suggesting a potential relationship. The origin of this outbreak requires further investigation; however, a Bezdíček scheme with improved discrimination may clarify this issue. Whole-genome sequencing (WGS)-based typing has logically become the new reference standard, and its availability is growing, whereas many clinical laboratories, including ours, still lack the fundamental resources to exploit its full potential. Our study showed that the Bezdíček scheme enables outbreak analysis with accuracy comparable with PFGE, remarkably contributing to nosocomial infection control. Additionally, although isolates from the Czech Republic were used to design the new scheme , high discriminatory power was also confirmed for geographically unrelated Japanese isolates. In these clinical laboratories that are unable to implement WGS, the Bezdíček MLST scheme is an ideal option for monitoring nosocomial VREfm infections. There are two advantages of performing the Bezdíček MLST scheme analysis. First, this scheme has a more precise resolution of genetic similarity and aligns closely with genome-wide data , making it useful for regional and international comparative studies. Second, when implementing WGS in the future, this scheme is compatible with in silico MLST analysis, allowing the use of accumulated data without loss. In contrast, in silico MLST has also been performed to interpret the results, even in studies using WGS . In such cases, it is recommended to use the Bezdíček MLST scheme, which shows more precise classification of genetic similarity than the original scheme. This study had several limitations. First, the discriminatory power of both MLST schemes was evaluated using PFGE cluster analysis, which does not allow whole-genome analysis. Second, the analyzed strains were isolated from a single medical center in 2019 and cannot be determined for more diverse populations or long-term evaluation. In conclusion, the Bezdíček MLST scheme shows great potential as a global epidemiological tool owing to its high discriminatory power and accessibility. Its cost-effectiveness, simplicity, and reproducibility make it suitable for routine clinical use. Additionally, this scheme can effectively visualize VREfm outbreaks and assist in infection control without requiring complicated analyses. Our findings show that the Bezdíček MLST scheme can be a suitable alternative to PFGE for real-time analysis of VREfm nosocomial outbreaks in clinical laboratories. 

