Content area
Brucella, the causative agent of brucellosis, is a globally significant zoonotic pathogen with serious public health implications. Understanding the molecular and genetic characteristics of Brucella species is crucial for the precise prevention, control, and epidemiological traceback investigation of brucellosis. In this study, 82 Brucella strains were genotyped via multiple-locus variable-number tandem-repeat analysis (MLVA-11) and multilocus sequence typing (MLST-21). Among these strains, four species and 14 biotypes were identified. MLVA-11 analysis revealed that 82 strains of bacteria contained 25 MLVA-11 genotypes, with genotype 72 (N = 10) and genotype 116 (N = 10) being the dominant genotypes. Hunter & Gaston diversity index (HGDI) analysis was conducted on the repeat results of 11 VNTR loci across all strains. These 11 VNTR loci exhibited varying degrees of polymorphism, with four loci demonstrating high levels of polymorphism. Notably, the 18 loci presented the highest degree of polymorphism, with a polymorphism index reaching 0.712. MLST-21 analysis revealed that 82 strains of Brucella contained 16 genotypes, with ST-8 (N = 33) being the dominant genotype. This study elucidates the phylogenetic relationships among diverse Brucella species. A comparison of the clustering results for 82 Brucella strains obtained via the two methods revealed that the MLVA-11 typing results more reliably encompassed the typing information provided by MLST-21. These findings provide novel insights into the molecular epidemiology of Brucella, which may facilitate the development of more effective strategies for brucellosis prevention and control.
Introduction
Brucellosis is a neglected zoonotic disease of significant economic importance that is endemic in many low- and middle-income countries (Alamian et al 2024; Salmani Seraji et al 2024). The key species affecting livestock include Brucella abortus in cattle, Brucella melitensis in small ruminants, and Brucella suis in pigs (Fang et al 2023). In addition to being an occupational hazard for those in direct contact with animals, such as livestock farmers, veterinarians, abattoir workers, and laboratory staff, the disease can transmit to humans indirectly through the consumption of unpasteurized milk and dairy products (Brangsch et al 2023; Chang et al 2023; Mallappa et al 2025). Brucellosis causes economic losses due to reduced production, including infertility, abortions, decreased milk yield, and the costs associated with prevention, control, and eradication efforts (Glowacka et al 2018). As a globally significant zoonosis, brucellosis has been reported in domestic and wild animal populations spanning more than 50 countries, with a particular prevalence in developing regions (Kurmanov et al 2022; Holloway et al 2025). Human brucellosis remains one of the most common reported zoonoses globally, with an estimated 500,000 cases annually (Dean et al 2012; Awais et al 2024).
In 1970, the FAO/WHO Expert Committee established a standardized classification system for Brucella, categorizing it into six species and 19 biovars on the basis of host specificity and biochemical characteristics (Ali et al 2024; Dadar and Alamian 2025). Notably, different Brucella species exhibit significant variations in pathogenicity and epidemiological traits, making accurate species identification essential for developing targeted prevention strategies and effective source tracing during outbreak investigations. In contemporary molecular epidemiology, two high-resolution genotyping methods have become the most common: multilocus variable-number tandem repeat analysis (MLVA) and multilocus sequence typing (MLST). Compared with conventional methods, MLVA-11 offers superior discriminatory power for strain differentiation, enabling robust phylogenetic analysis and transmission chain reconstruction through the detection of tandem repeat polymorphisms (Özmen et al 2023; Yang et al 2024). MLST-21, on the other hand, provides complementary data by sequencing conserved housekeeping genes, with allele profiles facilitating global strain comparisons through standardized databases.
In this study, both MLVA-11 and MLST-21 genotyping methods were used to analyze 82 Brucella strains. Unlike previous studies that focused on a single genotyping method, the combination of these two powerful approaches can provide a more comprehensive understanding of the genetic diversity and phylogenetic relationships among Brucella species. This dual-marker approach generated comprehensive data for (1) assessing genetic diversity among circulating strains and (2) elucidating potential evolutionary relationships. Through the integrated analysis of 14 biovars across four Brucella species, this study revealed finer-scale evolutionary relationships among Brucella species. Furthermore, we conducted the first systematic comparison of the typing efficiency between MLVA-11 and MLST-21 for Brucella, demonstrating that MLVA-11 captures the typing information of MLST-21 more comprehensively. The results offer new insights into the population genetics of Brucella in the study region and validate the combined use of these methods to increase surveillance efforts (Brangsch et al 2022).
Results
Biological typing of 82 Brucella strains
In this study, the biological species of Brucella were initially identified via MLVA-11, followed by biotype determination by MLST-21. A total of 82 Brucella strains were analyzed, including 11 B. suis strains, 37 B. melitensis strains, 27 B. abortus strains, and seven B. canis strains. Among the B. suis strains, 7 (8.54%) were B. suis bv1, 1 (1.22%) was B. suis bv2, 1 (1.22%) was B. suis bv3, and 2 (2.44%) were B. suis bv4. For B. melitensis, 1 (1.22%) strain was B. melitensis bv1, 3 (3.66%) were B. melitensis bv2, and 33 (40.24%) were B. melitensis bv3. With respect to B. abortus, there were 10 (12.20%) B. abortus bv1, 1 (1.22%) B. abortus bv2, 13 (15.85%) B. abortus bv3, 1 (1.22%) B. abortus bv5, 1 (1.22%) B. abortus bv6, and 1 (1.22%) B. abortus bv9 strain. The seven B. canis strains were all of a single biotype, accounting for 8.54% of the total strains (Fig. 1). Notably, among the 82 Brucella strains, one strain was identified as B. suis bv4, while it was identified as B. canis by MLST-21. The typing results of 18 Brucella isolates revealed that only one strain was B. abortus bv1, while the remaining strains were all B. melitensis bv3.
[See PDF for image]
Fig. 1
Biological typing results of 82 Brucella strains via MLVA-11
MLVA genotyping
MLVA-11 typing classified the 82 Brucella strains into 25 distinct types, specifically types 26, 27, 28, 29, 31, 33, 50, 64, 66, 67, 69, 72, 79, 80, 82, 83, 96, 111, 115, 116, 125, 136, 258, 388, and 406. As shown in Table 1, genotypes 72 and 116 were the most prevalent, each comprising 12.20% of the total strains. Genotypes 82 and 115 followed, each accounting for 8.54% of the total. Furthermore, among the 25 identified genotypes, 10 were unique, whereas 15 were shared. Notably, genotypes 72 and 116 were the most prevalent shared genotypes, each associated with 10 Brucella strains. Hunter & Gaston diversity index (HGDI) analysis was conducted on the repeat results of 11 VNTR loci across all strains. These 11 VNTR loci presented varying degrees of polymorphism. Four of the VNTR loci presented high polymorphism, with the Bruce 18 locus showing the highest level, reaching a polymorphism index of 0.712. The remaining seven VNTR loci presented moderate polymorphism (Table 2).
Table 1. MLVA-11 genotype characteristics of 82 Brucella strains
MLVA-11 | Panel 1 and panel 2A series repetition numbers | Number of strains | Proportion |
|---|---|---|---|
26 | 2–3–9–11–3–1–5–2–5–40–9 | 3 | 3.66% |
27 | 2–3–9–11–3–1–5–2–5–36–9 | 1 | 1.22% |
28 | 2–3–9–11–3–1–5–2–6–40–9 | 1 | 1.22% |
29 | 2–3–9–11–3–1–5–2–4–40–9 | 1 | 1.22% |
31 | 2–3–4–11–3–1–5–2–4–38–9 | 1 | 1.22% |
33 | 2–3–6–10–4–1–5–2–4–38–9 | 5 | 6.10% |
50 | 2–4–8–14–6–1–5–2–6–43–9 | 1 | 1.22% |
64 | 3–5–4–11–2–2–3–3–8–41-–8 | 1 | 1.22% |
66 | 3–5–3–12–2–2–3–3–7–43–8 | 1 | 1.22% |
67 | 3–5–3–12–2–2-2–3–7–43–8 | 2 | 2.44% |
69 | 1–5–3–12–2–2–3–1–6–43–8 | 2 | 2.44% |
72 | 4–5–3–12–2–2–3–1–6–43–8 | 10 | 12.20% |
79 | 4–5–4–12–2–3–3–3–6–43–8 | 1 | 1.22% |
80 | 4–5–4–12–2–1–3–3–6–43-–8 | 1 | 1.22% |
82 | 4–5–4–12–2–2–3–3–6–43-–8 | 7 | 8.54% |
83 | 4–5–4–12–2–2–3–3–5–43–8 | 2 | 2.44% |
96 | 3–5–3–13–1–1–3–3–7–43–8 | 3 | 3.66% |
111 | 1–5–3–13–2–3–3–2–4–41–8 | 6 | 7.32% |
115 | 1–5–3–13–2–2–3–2–3–41–8 | 7 | 8.54% |
116 | 1–5–3–13–2–2–3–2–4–41–8 | 10 | 12.20% |
125 | 1–5–3–13–3–2–3–2–4–41–8 | 6 | 7.32% |
136 | 3–4–2–13–4–2–3–3–5–36–6 | 1 | 1.22% |
258 | 2–3–6–10–4–1–5–2–3–38–9 | 2 | 2.44% |
388 | 1–5–3–13–2–2–3–2–3–41–8 | 4 | 4.88% |
406 | 2–3–8–11–3–1–5–2–5–40–9 | 3 | 3.66% |
Note: The locus sequence of the serial repeats of panel 1 and panel 2 A is as follows: Bruce 06, 08, 11, 12, 42, 43, 45, 55, 18, 19, 21
Table 2. Number of alleles and Hunter & Gaston diversity index (HGDI) values of 82 Brucella strains
Locus | Unit no. of tandem repeat | No. of alleles | HGDI |
|---|---|---|---|
Bruce 06 | 1 (35), 2 (18), 3 (8), 4 (21) | 4 | 0.703 |
Bruce 08 | 3 (17), 4 (2), 5 (63) | 3 | 0.371 |
Bruce 11 | 2 (1), 3 (51), 4 (13), 6 (7), 8 (4), 9 (6) | 6 | 0.580 |
Bruce 12 | 10 (7), 11 (11), 12 (33), 13 (30), 14 (1) | 5 | 0.687 |
Bruce 42 | 1 (3) , 2 (54), 3 (16), 4 (8), 6 (1) | 5 | 0.524 |
Bruce 43 | 1 (22), 2 (53) , 3 (7) | 3 | 0.509 |
Bruce 45 | 2 (2), 3 (62) , 5 (18) | 3 | 0.384 |
Bruce 55 | 1 (12), 2 (51) , 3 (19) | 3 | 0.545 |
Bruce 18 | 3 (6), 4 (36), 5 (10), 6 (23), 7 (6), 8 (1) | 6 | 0.712 |
Bruce 19 | 36 (2) , 38 (8), 40 (8), 41 (34), 43 (30) | 5 | 0.683 |
Bruce 21 | 6 (1), 8 (63), 9 (18) | 3 | 0.366 |
The results of the cluster analysis revealed that the 82 strains of Brucella were primarily grouped into 12 clusters (Clusters A–L). Specifically, Clusters A and C-E correspond to B. abortus and collectively encompass nine genotypes (67, 66, 80, 79, 83, 82, 69, 72, 64); Clusters B and F–H correspond to B. melitensis and collectively encompass seven genotypes (96, 125, 116, 115, 113, 88, 136); Clusters I-L correspond to B. suis and B. canis, collectively encompassing nine genotypes (28, 29, 406, 26, 27, 31, 258, 33, 50) (Fig. 2).
[See PDF for image]
Fig. 2
Cluster analysis diagram of 82 Brucella strains based on MLVA-11 (UPGMA method)
To intuitively analyze the polymorphisms and genetic relationships among 82 Brucella strains, we constructed a minimum spanning tree (MST) on the basis of MLVA-11 data. The MST revealed three primary clustering patterns: Cluster A predominantly comprised 30 B. melitensis bv3 strains and 3 B. melitensis bv2 strains, exhibiting high intragroup genetic similarity. Cluster B included diverse B. abortus biovars (bv1, bv2, bv3, bv5, bv6, and bv9), although notably, one B. melitensis bv1 strain (MLVA-11 genotype 136) was also grouped here. Cluster C consisted of B. canis and B. suis strains, with B. suis bv2 demonstrating marked genetic distinctiveness (Fig. 3).
[See PDF for image]
Fig. 3
Minimum spanning tree for 82 Brucella strains on the basis of the MLVA-11 profile
MLST genotyping
On the basis of MLST-21 analysis, a total of 82 Brucella strains were classified into 16 distinct sequence types (STs), as shown in Fig. 4.
[See PDF for image]
Fig. 4
Cluster analysis diagram of 82 Brucella strains based on MLST-21 (UPGMA method)
Cluster analysis based on MLST-21 revealed that the 82 strains fell into 8 distinct clusters. Clusters A-C included all B. abortus strains, Clusters D and E included all B. melitensis strains, and Clusters F–H included all B. canis and B. suis strains. The detailed findings are illustrated in Fig. 4. Furthermore, MST analysis provided further support for these clustering results. As shown in Fig. 5, 82 strains of Brucella presented distinct clustering patterns corresponding to their respective host species: B. melitensis, B. abortus, B. suis and B. canis.
[See PDF for image]
Fig. 5
Minimum spanning tree for 82 Brucella strains based on the MLST-21 profile
Comparison of MLVA with MLST
The clustering results of 82 Brucella strains obtained via the two methods were systematically compared. As shown in Table 3, the discriminatory power and consistency of these methods were evaluated. The Simpson index for MLVA-11 was 0.823 (95% CI: 0.767–0.879), which was significantly greater than that for MLST-21 (0.742, 95% CI: 0.673–0.811). This finding indicated that MLVA-11 offers superior resolution in distinguishing strain genotypes. Furthermore, the adjusted Wallace coefficient revealed that MLVA-11 fully predicts MLST-21 typing with perfect consistency (1.00), whereas the reverse prediction (MLST-21 to MLVA-11) was only 0.620. These findings demonstrate that MLVA-11 captures the typing information generated by MLST-21 more reliably.
Table 3. The discriminatory power of the MLVA and MLST subtyping methods and the concordance between them
Computing method | MLVA-11 | MLST-21 |
|---|---|---|
Simpson's index of diversity | ||
Number of partitions | 12 | 8 |
Simpson's index (95% CI) | 0.823(0.767–0.879) | 0.742(0.673–0.811) |
Adjust Rand coefficient | ||
MLST-21 | 0.765 | n/a |
Adjusted Wallace cofficient | ||
MLVA-11 | 1.00(1.000–1.000) | |
MLST-21 | 0.620(0.447–0.792) | |
Notes:MLVA multiple-locus variable-number tandem-repeat analysis, MLST multilocus sequence typing
Discussion
MLVA is a molecular typing method that identifies differences in the number of repeat units across various VNTR sites among different strains by detecting variable VNTRs at multiple loci. One of its key advantages is the relatively straightforward operational process, which has been further simplified and enhanced by the advent of capillary electrophoresis technology. This technology allows MLVA to provide digital typing information with high discriminatory power. In Brucella typing, MLVA can reveal subtle genetic variations among strains, which facilitates the tracking of epidemic outbreaks and the determination of host species. In this study, we selected 11 VNTR loci that exhibited relatively stable specificity for MLVA typing. These loci presented high polymorphism rates when 82 Brucella strains were analyzed but low polymorphism rates when 18 isolated strains were analyzed. Among the 82 Brucella strains, there were four species and 14 biotypes. The number of repeat units at the 11 VNTR loci varied significantly across Brucella species, indicating relatively high polymorphism. The high polymorphism index of the Bruce 18 locus (0.712) identified in this study can serve as a molecular marker for tracing transmission chains during outbreak investigations (Pereira et al 2023), and the 25 MLVA-11 genotypes and 16 MLST-21 genotypes obtained in this study should be integrated into the national Brucella molecular surveillance platform. These data can be compared with existing databases to facilitate strain tracing and cross-regional transmission monitoring (Abdel-Glil et al 2022). Conversely, among the 18 isolated strains, only one was identified as B. abortus bv1, while the remaining strains were all B. melitensis bv3. The observed low polymorphism suggests a high degree of genetic relatedness among these isolates. Studies have indicated that low genetic diversity combined with intensive animal farming practices can significantly influence microbial transmission, creating favorable conditions for rapid microbial proliferation and increasing the risk of zoonotic diseases (Hou et al 2013).
The typing results of the 18 Brucella isolates in this study revealed that B. melitensis, specifically the sheep-associated species, constituted the highest proportion (N = 17, 94.4%), with all B. melitensis strains belonging to biovar 3. This finding aligns with reports from various regions worldwide, including Xinjiang and Inner Mongolia in China, Iran, and Turkey, suggesting that B. melitensis bv3 may represent the primary epidemic subtype of Brucella in sheep, potentially indicating stronger adaptability or transmission advantages (Akar and Erganis 2022; Ta et al 2024; Li et al 2025).
MLVA-11 analysis classified the 82 strains into 25 genotypes. Among these, genotypes 72 and 116 (each accounting for 12.20%) were the most prevalent, followed by genotypes 82 and 115 (each accounting for 8.54%). This polymorphic distribution reflects the relatively high genetic heterogeneity of the Brucella strains analyzed in this study. Notably, genotype 111 (7.32%) corresponds to the dominant type reported in Iranian MLVA-11 studies, suggesting potential regional transmission chains. Furthermore, most genotypes corresponded to only one strain (accounting for 1.22%), highlighting the high-resolution characteristic of MLVA-11. This observation corroborates findings from studies conducted in Turkey (Akar and Erganis 2022) and Egypt (Holzer et al 2022), where MLVA outperforms traditional typing methods in distinguishing closely related strains (Akar and Erganis 2022; Wu et al 2022). Cluster analysis further divided the strains into 12 clusters. The distinct separation of Clusters A and C-E and Clusters B and F–H confirmed the genetic independence of Brucella strains originating from sheep and cattle, which is consistent with traditional typing methods (Anbazhagan et al 2024). The clustering of Clusters I–L suggests potential transmission links between swine and dogs or indicates conservation of MLVA loci between these two species (Macías Luaces et al 2023). B. melitensis bv1 formed an independent cluster (Cluster H), indicating significant genotypic differences compared with other B. melitensis bv3 strains, possibly attributable to host specificity or geographical isolation (Ksibi et al 2025).
MLST is a typing method based on sequence polymorphisms within bacterial ribosomal gene spacer regions. It is characterized by high accuracy and stability and can reflect phylogenetic relationships among strains. Currently, it is one of the most widely used bacterial typing methods. In this study, MLST-21 typing was performed on 82 Brucella strains, resulting in the classification of 16 genotypes. Among these strains, ST-8 accounted for the highest proportion (40.24%), suggesting that it may be the predominant epidemic strain in local areas or specific hosts (Cao et al 2025). Previous studies have associated ST-8 with B. melitensis bv3, a finding supported by our results, where all ST-8 types belong to B. melitensis bv3, which is consistent with the MLVA-11 classification results. These findings can inform vaccine strain selection: on the one hand, evaluating the protective efficacy of existing vaccine strains (such as the Rev.1 strain) against epidemic strains is recommended; on the other hand, conserved virulence genes identified through genomic analysis (such as those related to the type IV secretion system) can serve as candidate targets for the development of novel vaccines (Ayoub et al 2025; Ksibi et al 2025). In multiple host transmission regions, such as the northwest area, where B. melitensis bv3 infects at least three animal hosts, the development of multivalent vaccines covering a broader range of genotypes should be considered (Tian et al 2024). The clustering results were highly congruent with the MST analysis, which revealed that B. abortus, B. melitensis, and B. suis/B. can form independent evolutionary branches. These findings support the notion that Brucella genomes are highly conserved across species but clearly feature species-specific single nucleotide polymorphisms (SNPs) (Anbazhagan et al 2024; Yanmaz et al 2024).
This study presents a comparative analysis of two genotyping methods (MLVA-11 and MLST-21) for Brucella strain subtypes. The Simpson index of diversity of MLVA-11 (0.823, 95% CI: 0.767–0.879) was greater than that of MLST-21 (0.742, 95% CI: 0.673–0.811), demonstrating that MLVA-11 has a more robust ability to differentiate Brucella subtypes. This aligns with the literature indicating that MLVA generally offers higher resolution, making it suitable for high-discrimination epidemiological traceback scenarios (Eyüboğlu 2022; Wu et al 2022). When the consistency of the classification results is compared, the adjusted Rand coefficient and Wallace coefficient reveal that MLVA-11 has relatively high predictive consistency for MLST-21, but the reverse is less consistent (Pijnacker et al 2022; Kong et al 2023). This suggests that MLVA-11’s classification results encompass all the clustering information of MLST-21. This might be attributed to the VNTR site mutations detected by MLVA-11, which provide additional resolution that MLST-21 cannot capture (Gana et al 2022; Wu et al 2022). This may explain why there is a strain of Brucella with inconsistent results from two typing methods: cluster analysis via MLVA-11 and MLST-21 revealed that B. suis bv4 and B. suis can share a close phylogenetic relationship, thus requiring higher-resolution methods for their differentiation. However, some studies suggest that differences in certain loci of MLVA-11, such as Bruce 04 and 16, may lead to misjudgments in epidemiological associations (Tan et al 2023). Combining the stable phylogenetic information of MLST-21 can mitigate these issues, underscoring the value of using both methods together (Legouge et al 2023; Tan et al 2023). In summary, MLVA-11 is better for rapid screening and high-resolution typing, whereas MLST-21 is more advantageous for long-term evolutionary analysis and cross-study comparisons. Using both methods can provide more comprehensive typing information. The choice of methods or their combination should be based on specific goals, such as short-term outbreak investigations or long-term strain monitoring (Andrews et al 2023).
This study represents a significant improvement in the molecular characterization of Brucella species by integrating the analysis of four species and fourteen biotypes. While numerous previous studies have employed MLVA or MLST methods to investigate the genotypic features of Brucella, these efforts have focused predominantly on clinical isolates, which typically encompass only one or two biotypes. Our comprehensive approach, encompassing a diverse range of species and biotypes, allows for a more nuanced elucidation of the phylogenetic relationships among Brucella species. This extensive analysis not only provides a detailed genetic landscape but also reveals finer evolutionary connections that were previously obscured by the limited scope of prior research. The integration of MLVA-11 and MLST-21 further enhances the precision and reliability of our findings. By demonstrating that MLVA-11 typing results more reliably encompass the typing information provided by MLST-21, our study offers a more robust framework for understanding Brucella’s genetic diversity. This innovation is crucial for advancing the field of brucellosis epidemiology and has significant implications for the development of targeted prevention and control strategies.
In this study, by integrating two molecular typing techniques, MLVA-11 and MLST-21, the genetic diversity of 82 Brucella strains was systematically analyzed, revealing significant innovations at both the methodological and application levels of molecular epidemiological research. The key innovations include the following: (1) Identification of the Bruce 18 locus as exhibiting the highest polymorphism (HGDI = 0.712), providing crucial guidance for future VNTR locus selection in Brucella genotyping studies (Li et al 2025). This finding contributes to optimizing molecular marker panels for enhanced strain discrimination. (2) MLVA-11 can effectively capture the classification information contained in MLST-21 while establishing robust data correlations between these complementary typing approaches (Tan et al 2023). This validation supports the combined use of these methods for comprehensive strain characterization. (3) Characterization of dominant genotypes, including ST-8 and MLVA-72/116, which serve as valuable molecular markers for tracking Brucella epidemic strains across Asian regions. These findings align with previous reports of the prevalence of ST-8 in Asian Brucella populations (Ali et al 2024; Li et al 2025). The study’s significance is multifaceted: (1) The multilocus joint analysis strategy establishes a methodological framework for investigating cross-border transmission dynamics, which is particularly suitable for monitoring shared genotypes in Asia (for example, the newly reported ST39 in China (Tan et al 2023; Li et al 2025). This approach addresses critical needs in transnational brucellosis surveillance. (2) Epidemiological findings directly inform precision prevention strategies, enabling targeted control measures based on dominant genotype distributions (De Massis et al 2024; Dadar and Alamian 2025). Through its technical innovations and epidemiological insights, this research significantly advances molecular tracing capabilities for zoonotic brucellosis, contributing to the global effort against this important public health threat. Compared with single-method analyses, the integrated genotyping approach demonstrates superior resolution for tracking strain transmission patterns (Tan et al 2023; Dadar and Alamian 2025).
This study has several limitations that should be considered when interpreting the findings. While MLVA and MLST are widely used and provide valuable insights into the genetic diversity of Brucella strains, both methods have inherent limitations. The relatively high mutation rate of MLVA at VNTR sites can lead to unstable typing results, particularly over long periods of epidemiological monitoring, potentially affecting the consistency of strain identification. Additionally, MLST has low resolution, making it challenging to differentiate highly similar strains, and both methods miss certain genetic variations, such as point mutations, insertions, and deletions, which may have significant biological implications. Future research could address these issues by exploring whole-genome sequencing (WGS), which is becoming more cost-effective and accessible. WGS would allow a more comprehensive analysis of genetic diversity, detect a broader range of variations and provide higher resolution for strain differentiation. When MLVA and MLST cannot distinguish highly homologous strains, WGS can provide more refined typing results through SNP analysis. It can also be used to validate the results of MLVA and MLST to ensure the accuracy of typing. In the future, as WGS technology becomes more standardized and automated, it is expected to become more widely used in Brucella typing and may become a route for monitoring and investigating outbreaks. Moreover, WGS data can be integrated into national and international Brucella monitoring platforms to achieve strain tracing and cross-regional transmission monitoring, which will help enhance the global capacity for Brucella control (Daugaliyeva et al 2025; Ksibi et al 2025).
Conclusion
In this study, the molecular epidemiological characteristics of Brucella were elucidated through MLVA-11 and MLST-21 typing analyses of 82 strains. MLVA-11 typing identified 25 genotypes, predominantly type 72 and type 116, with the Bruce 18 locus exhibiting the highest polymorphism (HGDI = 0.712), confirming the significant discriminatory power of the VNTR loci. MLST-21 typing revealed 16 STs, with ST-8 being the predominant type (40.2%). Phylogenetic analysis demonstrated that the MLVA-11 typing results more comprehensively encompassed the genetic information provided by MLST-21, offering a more reliable technical approach for the molecular traceability of Brucella. These findings not only clarify the phylogenetic relationships among Brucella species but also provide critical molecular epidemiological evidence for developing precise prevention and control strategies for brucellosis, thus holding substantial significance for public health practice. Future research could further optimize the surveillance network and traceability system for brucellosis based on the genetic marker system established in this study.
Methods
Bacterial strains
The study utilized a total of 82 Brucella strains selected according to the following criteria: (1) preserved in the National Veterinary Microbiological Culture Collection Center of the China Institute of Veterinary Drug Control (CVCC); (2) clinically isolated by the National Animal Brucellosis Reference Laboratory within the past two years; and (3) nucleic acids meeting the requirements for next-generation sequencing could be extracted. Among these strains, 64 strains were derived from CVCC, whereas 18 were clinical isolates.
Genomic DNA preparation
A total of 82 Brucella strains were resuscitated on Brucella agar plates and incubated at 37°C for 48–72 h. After inactivation, total genomic DNA was extracted via a GeneRotex 96 fully automatic nucleic acid extractor (Tianlong Technology, China) according to the manufacturer’s recommended protocol.
MLVA genotyping
Each VNTR site was amplified via multiplex polymerase chain reaction combined with multicolor capillary electrophoresis. Specifically, the 5 ends of each locus forward promers within each reaction system were synthesized with 6-carboxyfluorescein (FAM), 5-carboxy tetramethylrhodamine (TAMRA), and carboxy-X-rhodamine (ROX) fluorescent labels. The sequence information of the primers and the PCR amplification cycling parameters were as previously described (Le Flèche et al 2006). The products were sent to Sangon Biotech (Shanghai) Co., Ltd., for multicolor capillary electrophoresis, and the loci and values were identified according to the color presented in each graph of each sample. The resulting genotypes were compared via the MLVAbank database (https://microbesgenotyping.i2bc.paris-saclay.fr/databases/view/75).
MLST genotyping
MLST was performed via a previously described method (Whatmore et al 2016). Briefly, 21 independent genetic loci were selected, including gap, aroA, glk, dnaK, gyrB, trpE, omp25, cobQ, int-hyp, prpE, caiA, csdB, soxA, leuA, mviM, fumC, fbaA, ddlA, putA, mutL, and acnA. The primer sequences of the 21 MLST loci and the PCR amplification cycling parameters were shown in the literature (Whatmore et al 2016). Then, the products were sent to Sangon Biotech (Shanghai) Co., Ltd., for sequencing. Each gene sequence was entered into the MLST online database to specify its defined value. The profiles of the 21 genes were subsequently identified as a specific sequence type (ST) on the basis of the MLST online database.
Analysis of genotyping data
To elucidate the molecular characteristics and evolutionary relationships of the measured strains, MLVA data were analyzed via BioNumerics software V. 7.6. Cluster analyses of MLVA-8 and MLVA-11 were conducted on 82 Brucella strains on the basis of the classification coefficient and the unweighted pair‒group method with arithmetic mean (UPGMA). Polymorphisms at each locus were quantified via HGDI. Additionally, a minimum spanning tree (MST) was constructed utilizing MLVA-11 data to investigate the genetic relationships among the strains. The resulting MLST genotypes were compared via the web-based MLST database (https://pubmlst.org/brucella/). The MLST dendrogram was constructed via BioNumerics V. 7.6 software (Liu et al 2019).
Comparison of MLVA and MLST subtyping
The MLVA and MLST typing results were compared by calculating Simpson’s index of diversity and the adjusted Rand and Wallace coefficients of concordance via the online Comparing Partitions tool (http://www.comparingpartitions.info/) (Carriço et al 2006; Andrews et al 2023).
Acknowledgements
We thank the colleagues and collaborators who provided helpful discussions and technical support during the course of this study.
Authors’ contributions
GCY: Data curation, methodology, supervision, writing-review & editing. GKX, PXW, SWF, ZJD, ZXQ and ZYQ: Methodology. LJP and ZXJ: Methology, Writing-review & editing, Funding acquisition. LZF: Methodology, Supervision, Writing-review & editing. All the authors have read and agreed with the final version of the manuscript.
Funding
This work was supported by the National Key Research and Development Program of China (2022YFD1800600, 2022YFD1800601) and the public welfare key projects in the veterinary drug industry of the China Institute of Veterinary Drug Control (QN202403-1).
Data availability
The relevant data and material in this article are available and can be requested from the corresponding authors.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Abbreviations
National Veterinary Microbiological Culture Collection Center of the China Institute of Veterinary Drug Control
Hunter & Gaston diversity index
Multiple-locus variable-number tandem-repeat analysis
Multilocus sequence typing
Minimum spanning tree
Single-nucleotide polymorphism
Sequence type
Unweighted pair‒group method with arithmetic mean
Whole-genome sequencing
Chang Cai
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
Abdel-Glil, MY; Thomas, P; Brandt, C; Melzer, F; Subbaiyan, A; Chaudhuri, P; Harmsen, D; Jolley, KA; Janowicz, A; Garofolo, G; Neubauer, H; Pletz, MW. Core genome multilocus sequence typing scheme for improved characterization and epidemiological surveillance of pathogenic Brucella. J Clin Microbiol; 2022; 60,
Akar, K; Erganis, O. Evaluation of the genetic profiles of Brucella melitensis strain from Turkey using multilocus variable number tandem repeat analysis (MLVA) and multilocus sequence typing (MLST) techniques. Vet Microbiol; 2022; 269, 1:CAS:528:DC%2BB38XhsF2rtb7E [DOI: https://dx.doi.org/10.1016/j.vetmic.2022.109423] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35462118]109423.
Alamian S, Amiry K, Etemadi A, Dadar M., 2024. Characterization of Brucella spp. circulating in industrial dairy cattle farms in Iran: a field study 2016 - 2023. Vet Res Forum, 15 (4): 195–202. https://doi.org/10.30466/vrf.2024.2012972.4028.
Ali, S; Mushtaq, A; Hassan, L; Syed, MA; Foster, JT; Dadar, M. Molecular epidemiology of brucellosis in Asia: Insights from genotyping analyses. Vet Res Commun; 2024; 48,
Anbazhagan, S; Himani, KM; Karthikeyan, R; Prakasan, L; Dinesh, M; Nair, SS; Lalsiamthara, J; Abhishek, Ramachandra S G; Chaturvedi, VK; Chaudhuri, P; Thomas, P. Comparative genomics of Brucella abortus and Brucella melitensis unravels the gene sharing, virulence factors and SNP diversity among the standard, vaccine and field strains. Int Microbiol; 2024; 27,
Andrews, N; McCabe, E; Wall, P; Buckley, JF; Fanning, S. Validating the utility of multilocus variable number tandem-repeat analysis (MLVA) as a subtyping strategy to monitor Listeria monocytogenes In-built food processing environments. J Food Prot; 2023; 86,
Awais, MM; Khadim, G; Akhtar, M; Anwar, MI; Shirwany, A; Raza, A; Razzaq, A; Fatima, Z; Ali, MA; Bhatti, MS. A study on the epidemiology of brucellosis in bovine population of peri-urban and rural areas of district Multan, southern Punjab. Pakistan. BMC Vet Res; 2024; 20,
Ayoub H, Kumar M S, Mehta R, Sethuraj S E, Thomas P, Dhanze H, Dubey M, Salih H M, Chandrashekaraiah G B, Cull C A, Veeranna R P, Amachawadi R G., 2025. Genomic insights into Brucella melitensis in India: stability of ST8 and the role of virulence genes in regional adaptations. Microbiol Spectr, e0264724. https://doi.org/10.1128/spectrum.02647-24.
Brangsch, H; Singha, H; Laroucau, K; Elschner, M. Sequence-based detection and typing procedures for Burkholderia mallei: Assessment and prospects. Front Vet Sci; 2022; 9, 1056996. [DOI: https://dx.doi.org/10.3389/fvets.2022.1056996] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36452150][PubMedCentral: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9703372]
Brangsch, H; Horstkotte, MA; Melzer, F. Genotypic peculiarities of a human brucellosis case caused by Brucella suis biovar 5. Sci Rep; 2023; 13,
Cao, X; Liu, P; Wu, J; Liu, Z; Zhang, Y; Yin, C; Ying, L; Ma, J; He, J; Shang, Y; Du, R; Liu, Z; Li, Z. Genome phylogenetic analysis of Brucella melitensis in Northwest China. BMC Microbiol; 2025; 25,
Carriço, JA; Silva-Costa, C; Melo-Cristino, J; Pinto, FR; de Lencastre, H; Almeida, JS; Ramirez, M. Illustration of a common framework for relating multiple typing methods by application to macrolide-resistant Streptococcus pyogenes. J Clin Microbiol; 2006; 44,
Chang J, Hou X, Yang X, Zhang SJ, Zou DY, Li F, Zhang Y, Li YS, Lu SY, Hu P, Liu ZS, Ren HL., 2023. A rapid and sensitive triplex-recombinase polymerase amplification for simultaneous differentiation of Brucella abortus, Brucella melitensis, and Brucella suis in sera and foods. FEMS Microbiol Lett, 370. https://doi.org/10.1093/femsle/fnad056.
Dadar, M; Alamian, S. In silico MLVA analysis of Brucella melitensis from human and livestock in Iran. Curr Microbiol; 2025; 82,
Daugaliyeva, A; Daugaliyeva, S; Abutalip, A; Adambayeva, A; Kydyr, N; Peletto, S. Study of epidemiological and molecular characteristics of Brucella strains circulating in Kazakhstan. Vet Res Commun; 2025; 49,
De Massis, F; Ali, RM; Serrani, S; Toro, M; Sferrella, A; D'Aurelio, N; Janowicz, A; Zilli, K; Romualdi, T; Felicioni, E; Salman, MH; Fahdel, DH; Rashid, HS; Ameen, BQ; Garofolo, G. Genetic diversity of Brucella melitensis isolated from domestic ruminants in Iraq. Microorganisms; 2024; 12,
Dean, AS; Crump, L; Greter, H; Hattendorf, J; Schelling, E; Zinsstag, J. Clinical manifestations of human brucellosis: A systematic review and meta-analysis. PLoS Negl Trop Dis; 2012; 6,
Eyüboğlu, M. Highlights in the association of fragmented QRS with myocardial fibrosis. Turk J Med Sci; 2022; 52,
Fang, Y.P., Wang, J.J. Zhang, G.Y. Zhu, F.D. Guo, C.Y. Zhang, J.D. Guo, K.X. Deng, Y. Zhang, J.X. Chen, H.C. and Liu, Z.F. 2023. Enzootic epidemiology of Brucella in livestock in central Gansu Province after the National Brucellosis Prevention and Control Plan. Animal Diseases 3: 13. https://doi.org/10.1186/s44149-022-00077-9.
Gana, J; Gcebe, N; Pierneef, R; Moerane, R; Adesiyun, AA. Multiple-locus variable-number tandem repeat analysis genotypes of Listeria monocytogenes isolated from farms, abattoirs, and retail in Gauteng Province. South Africa. J Food Prot; 2022; 85,
Glowacka, P; Zakowska, D; Naylor, K; Niemcewicz, M; Bielawska-Drózd, A. Brucella - virulence factors, pathogenesis and treatment. Pol J Microbiol; 2018; 67,
Holloway, P; Gibson, M; Holloway, T; Pickett, I; Crook, B; Cardwell, JM; Nash, S; Musallam, I; Al-Omari, B; Al-Majali, A; Hayajneh, W; Abu-Basha, E; Mangtani, P; Guitian, J. Camel milk is a neglected source of brucellosis among rural Arab communities. Nat Commun; 2025; 16,
Holzer, K; Wareth, G; El-Diasty, M; Abdel-Hamid, NH; Hamdy, MER; Moustafa, SA; Linde, J; Bartusch, F; Abdel-Glil, MY; Sayour, AE; Elbauomy, EM; Elhadidy, M; Melzer, F; Beyer, W. Tracking the distribution, genetic diversity and lineage of Brucella melitensis recovered from humans and animals in Egypt based on core-genome SNP analysis and in silico MLVA-16. Transbound Emerg Dis; 2022; 69,
Hou, Q; Sun, X; Zhang, J; Liu, Y; Wang, Y; Jin, Z. Modeling the transmission dynamics of sheep brucellosis in Inner Mongolia Autonomous Region. China. Math Biosci; 2013; 242,
Kong, N; Luo, Y; Liu, J; Yao, G; Hu, Y; Shu, S; Li, C; Bi, S. Subtyping of Campylobacter coli isolated from raw poultry meat in retail markets using amplified intergenic locus polymorphism - A novel rapid subtyping method. J Microbiol Meth; 2023; 204, 1:CAS:528:DC%2BB3sXitlSgsQ%3D%3D [DOI: https://dx.doi.org/10.1016/j.mimet.2022.106662] 106662.
Ksibi, B; Smaoui, F; Ben Ayed, N; Guetat, M; Mezghani, S; Ktari, S; Mahjoubi, F; Ben Jemaa, M; Karray, H; Hammami, A. Genomic analysis of Brucella melitensis isolates recovered from humans in south Tunisia over 35 years between 1988 and 2022. BMC Microbiol; 2025; 25,
Kurmanov, B; Zincke, D; Su, W; Hadfield, TL; Aikimbayev, A; Karibayev, T; Berdikulov, M; Orynbayev, M; Nikolich, MP; Blackburn, JK. Assays for identification and differentiation of Brucella species: A review. Microorganisms; 2022; 10,
Le Flèche, P; Jacques, I; Grayon, M; Al Dahouk, S; Bouchon, P; Denoeud, F; Nöckler, K; Neubauer, H; Guilloteau, LA; Vergnaud, G. Evaluation and selection of tandem repeat loci for a Brucella MLVA typing assay. BMC Microbiol; 2006; 6, 9.1:CAS:528:DC%2BD28XksVWjtrw%3D [DOI: https://dx.doi.org/10.1186/1471-2180-6-9] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16469109][PubMedCentral: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1513380]
Legouge, C; Bidet, P; Gits-Muselli, M; Cointe, A; Courroux, C; Birgy, A; Bonacorsi, S. Rapid, simple multi-locus variable number tandem repeat analysis: A reliable tool for Klebsiella pneumoniae outbreak screening. J Hosp Infect; 2023; 141, pp. 41-48.1:CAS:528:DC%2BB3sXhvF2ms7zP [DOI: https://dx.doi.org/10.1016/j.jhin.2023.08.010] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37634603]
Li, W; Zeng, L; Yuan, R; Qi, T; Liao, H; Cao, Y; Huang, S; Liu, Z; Li, Z. Genetic diversity atlas of Brucella melitensis strains from Sichuan Province. China. BMC Microbiol; 2025; 25,
Liu, ZG; Wang, M; Zhao, HY; Piao, DR; Jiang, H; Li, ZJ. Investigation of the molecular characteristics of Brucella isolates from Guangxi Province. China. BMC Microbiol; 2019; 19,
Macías Luaces L, Boll K, Klose C, Domogalla-Urbansky J, Müller M, Eisenberger D, Riehm J M., 2023. Seroprevalence of Brucella infection in Wild Boars (Sus scrofa) of Bavaria, Germany, 2019 to 2021 and associated genome analysis of five B. Suis biovar 2 isolates. Microorganisms, 11 (2): 478. https://doi.org/10.3390/microorganisms11020478.
Mallappa, A; Kuralayanapalya Puttahonnappa, S; Shome, R; Patil, SS; Amachawadi, RG; Mohan, KSK; Venkatesh, SP; Ramesh, V; Sekar, YS; Thippeswamy, H; Patil, AV. Systematic review, meta-analysis, and pan-genome analytics predict the surging of Brucella melitensis by China and India-specific strains, elucidating the demand for enhanced preparedness. J Infect Public Health; 2025; 18,
Özmen, M; Özgen, EK; Sayı, O; Karadeniz Pütür, E; Okumuş, B; İba Yılmaz, S; Aslan, MH; Ulucan, M; Yanmaz, B; Şeri Foğlu Bağatir, P; Turut, N; Karahan, Ş; Eroğlu, B; Gülseren, Y; Küçükayan, U; Nuhay, Ç; Eski, IZRLS; Saka, E; Soysal Sarişahi, NA; Deni, Zİ; Bi Rben, N; Karakuş, K; Şen, E; Sayteki, NA; Akar, K. Genotyping of Brucella isolates from animals and humans by multiple-locus variable-number tandem repeat analysis (MLVA). Comp Immunol Microbiol Infect Dis; 2023; 96, 1:CAS:528:DC%2BB3sXnvVOktrY%3D [DOI: https://dx.doi.org/10.1016/j.cimid.2023.101981] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37043846]101981.
Pereira, CR; Neia, RC; Silva, SB; Williamson, CHD; Gillece, JD; O'Callaghan, D; Foster, JT; Oliveira, IRC; Bueno Filho, JSS; Lage, AP; Azevedo, VAC; Dorneles, EMS. Comparison of Brucella abortus population structure based on genotyping methods with different levels of resolution. J Microbiol Meth; 2023; 211, 1:CAS:528:DC%2BB3sXhsVCjur7P [DOI: https://dx.doi.org/10.1016/j.mimet.2023.106772] 106772.
Pijnacker, R; van den Beld, M; van der Zwaluw, K; Verbruggen, A; Coipan, C; Segura, AH; Mughini-Gras, L; Franz, E; Bosch, T. Comparing multiple locus variable-number tandem repeat analyses with whole-genome sequencing as typing method for salmonella enteritidis surveillance in the Netherlands, January 2019 to March 2020. Microbiol Spectr; 2022; 10,
Salmani Seraji, M; Yazdani Charati, J; Baba Mahmoudi, F; Ali Mohammadpour Tahamtan, R; Vahedi, H; Shojaei, J. Epidemiology of brucellosis in Mazandaran, North of Iran in a nine-year period (2009–2017). Caspian J Intern Med; 2024; 15,
Ta N, Zuo K M, Gao J, Guan N, Song L T, Wen Y J, Yu R P., 2024. Origin tracking of Brucella strain B. melitensics bv.3 ARQ-070 using biochemical and genomic studies. FEMS Microbiol Lett, 371 https://doi.org/10.1093/femsle/fnae085.
Tan, Q; Wang, Y; Liu, Y; Tao, Z; Yu, C; Huang, Y; Yang, X; Ying, X; Hu, Y; Li, S. Molecular epidemiological characteristics of Brucella in Guizhou Province, China, from 2009 to 2021. Front Microbiol; 2023; 14, 1188469. [DOI: https://dx.doi.org/10.3389/fmicb.2023.1188469] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37426016][PubMedCentral: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326899]
Tian, T; Zhu, Y; Shi, J; Shang, K; Yin, Z; Shi, H; He, Y; Ding, J; Zhang, F. The development of a human Brucella mucosal vaccine: What should be considered?. Life Sci; 2024; 355, 1:CAS:528:DC%2BB2cXhvVWhtr%2FI [DOI: https://dx.doi.org/10.1016/j.lfs.2024.122986] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/39151885]122986.
Whatmore, AM; Koylass, MS; Muchowski, J; Edwards-Smallbone, J; Gopaul, KK; Perrett, LL. Extended multilocus sequence analysis to describe the global population structure of the genus Brucella : Phylogeography and relationship to biovars. Front Microbiol; 2016; 7, 2049. [DOI: https://dx.doi.org/10.3389/fmicb.2016.02049] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28066370][PubMedCentral: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5174110]
Wu, Y; Yu, Y; Hua, L; Wei, Y; Gan, Y; Chenia, HY; Wang, Y; Xie, X; Wang, J; Liu, M; Shao, G; Xiong, Q; Feng, Z. Genotyping and biofilm formation of Mycoplasma hyopneumoniae and their association with virulence. Vet Res; 2022; 53,
Yang, X; Liu, Y; Li, N; Peng, X; Zhang, Y; Zhang, X; Liang, L; Bian, Z; Jiang, H; Ding, J. Analysis of the Brucella melitensis epidemic in Xinjiang: Genotyping, polymorphism, antibiotic resistance and tracing. Ann Clin Microbiol Antimicrob; 2024; 23,
Yanmaz, B; Özgen, EK; Sayı, O; Erdoğan, Y; Aslan, MH; İba Yılmaz, S; Karadeniz Pütür, E; Polat, N; Özmen, M; Şerifoğlu Bağatır, P; Ildız, S. Phylogenetic analysis of Brucella melitensis strains isolated from humans using 16S rRNA sequencing and multiple locus variable number of tandem repeats analysis-16. Vector Borne and Zoonotic Dis; 2024; 24,
© The Author(s) 2025. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.